diff --git a/.azure-pipelines/compare-refdata.yml b/.azure-pipelines/compare-refdata.yml deleted file mode 100644 index 49d6c77b9ca..00000000000 --- a/.azure-pipelines/compare-refdata.yml +++ /dev/null @@ -1,121 +0,0 @@ -# For more information on how to use this pipeline please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -# IMPORTANT: Only contributors with `Write` permission can trigger the build -# by commenting `/AzurePipelines run ` on the pull -# request. -# -# This feature can be disabled only through the Azure Pipelines -# dashboard. - -trigger: - tags: - include: - - '*' - -pr: - branches: - include: - - '*' - -variables: - system.debug: false - results.url: 'http://opensupernova.org/~azuredevops/files/refdata-results' - pr.number: '$(System.PullRequest.PullRequestNumber)' - commit.sha: '$(Build.SourceVersion)' - #ref1.hash: '' - #ref2.hash: '' - -pool: - vmImage: 'ubuntu-latest' - -jobs: - - job: 'report' - steps: - - template: templates/default.yml - parameters: - fetchRefdata: true - refdataRepo: 'github' - useMamba: true - - - bash: | - source activate tardis - $(package.manager) install bokeh=2.2 --channel conda-forge --no-update-deps --yes - displayName: 'Install Bokeh' - - - bash: | - cd $(refdata.dir) - git remote add upstream $(git remote get-url origin) - git fetch upstream - git fetch upstream "+refs/pull/*/head:refs/remotes/upstream/pr/*" - displayName: 'Set upstream remote' - - - bash: | - cd $(tardis.dir) - source activate tardis - pytest tardis --tardis-refdata=$(refdata.dir) --generate-reference - displayName: 'Generate reference data' - condition: or(eq(variables['ref1.hash'], ''), eq(variables['ref2.hash'], '')) - - - bash: | - cd $(refdata.dir)/notebooks - source activate tardis - jupyter nbconvert ref_data_compare.ipynb --to html --execute --ExecutePreprocessor.timeout=6000 - displayName: 'Render notebook' - - - bash: | - cd $(refdata.dir)/notebooks - source activate tardis - jupyter nbconvert ref_data_compare.ipynb --to html --execute --allow-errors --ExecutePreprocessor.timeout=6000 - displayName: 'Render notebook (allow errors)' - condition: failed() - - - task: PublishPipelineArtifact@1 - inputs: - targetPath: '$(refdata.dir)/notebooks/ref_data_compare.html' - artifactName: 'report' - displayName: 'Upload artifact' - condition: succeededOrFailed() - - - task: InstallSSHKey@0 - inputs: - knownHostsEntry: $(opensupernova_host) - sshPublicKey: $(opensupernova_pubkey) - sshKeySecureFile: openSupernovaKey - - - ${{ if eq(variables['Build.Reason'], 'IndividualCI') }}: - - bash: echo "##vso[task.setvariable variable=subfolder]releases" - displayName: "Set subfolder name" - - - ${{ if eq(variables['Build.Reason'], 'PullRequest') }}: - - bash: echo "##vso[task.setvariable variable=subfolder]$(pr.number)" - displayName: "Set subfolder name" - - - ${{ if eq(variables['Build.Reason'], 'Manual') }}: - - bash: echo "##vso[task.setvariable variable=subfolder]manual" - displayName: "Set subfolder name" - - - bash: | - ssh azuredevops@opensupernova.org "mkdir -p /home/azuredevops/public_html/files/refdata-results/$(subfolder)" - scp $(refdata.dir)/notebooks/ref_data_compare.html azuredevops@opensupernova.org:/home/azuredevops/public_html/files/refdata-results/$(pr.number)/$(commit.sha).html - displayName: 'Copy files to server' - condition: succeededOrFailed() - - # Run if the pipeline is triggered by a pull request. - - ${{ if eq(variables['Build.Reason'], 'PullRequest') }}: - - task: GitHubComment@0 - inputs: - gitHubConnection: 'tardis-sn' - repositoryName: 'tardis-sn/tardis' - id: $(pr.number) - comment: '**Build succeeded** $(commit.sha)

[Click here]($(results.url)/$(pr.number)/$(commit.sha).html) to see results.' - displayName: 'Post results (success)' - - - task: GitHubComment@0 - inputs: - gitHubConnection: 'tardis-sn' - repositoryName: 'tardis-sn/tardis' - id: $(pr.number) - comment: '**Build failed** $(commit.sha)

[Click here]($(results.url)/$(pr.number)/$(commit.sha).html) to see results.' - displayName: 'Post results (failed)' - condition: failed() diff --git a/.azure-pipelines/release-version.yml b/.azure-pipelines/release-version.yml deleted file mode 100644 index 96b088094e4..00000000000 --- a/.azure-pipelines/release-version.yml +++ /dev/null @@ -1,66 +0,0 @@ -# For more information on how to use this pipeline please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -trigger: none -pr: none - -schedules: - - cron: '0 0 * * 0' - displayName: 'Weekly release' - branches: - include: - - master - always: false - -variables: - system.debug: false - -pool: - vmImage: 'ubuntu-latest' - -jobs: - - job: release - displayName: 'TARDIS release' - - steps: - - template: templates/default.yml - parameters: - fetchRefdata: true - refdataRepo: 'azure' - useMamba: true - - # Test before relase, we do not want to release broken software! - - bash: | - cd $(tardis.dir) - source activate tardis - pytest tardis --tardis-refdata=$(refdata.dir) - displayName: 'Run tests' - - - bash: | - cd $(tardis.dir) - source activate tardis - echo $(python .ci-helpers/get_current_version.py) - displayName: 'Check latest tag' - - - bash: | - cd $(tardis.dir) - source activate tardis - echo "##vso[task.setvariable variable=newtag]$(python .ci-helpers/get_next_version.py)" - displayName: 'Get new tag' - - - bash: echo $(newtag) - displayName: 'Check new tag' - - - task: GitHubRelease@1 - inputs: - gitHubConnection: 'tardis-bot' - repositoryName: '$(Build.Repository.Name)' - action: 'create' - target: '$(Build.SourceVersion)' - tagSource: 'userSpecifiedTag' - tag: 'release-$(newtag)' - title: 'TARDIS v$(newtag)' - releaseNotesSource: 'inline' - releaseNotes: 'This release has been made automatically through our continous delivery pipeline. For a complete list of changes see [CHANGELOG.md](https://github.com/tardis-sn/tardis/blob/master/CHANGELOG.md).' - addChangeLog: false - displayName: 'Create GitHub Release' diff --git a/.azure-pipelines/run-unit-tests.yml b/.azure-pipelines/run-unit-tests.yml deleted file mode 100644 index fddb590b6f2..00000000000 --- a/.azure-pipelines/run-unit-tests.yml +++ /dev/null @@ -1,48 +0,0 @@ -# For more information on how to use this pipeline please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -trigger: - branches: - include: - - '*' - -pr: - branches: - include: - - '*' - -variables: - codecov.token: 'a876d307-9ed5-4f5d-a6c4-e58291ac4111' - system.debug: false - -jobs: - - job: - pool: - vmImage: $[variables.vm_Image] - - strategy: - matrix: - Linux: - vm_Image: 'ubuntu-latest' - - macOS: - vm_Image: 'macOS-latest' - - maxParallel: 2 - - steps: - - template: templates/default.yml - parameters: - fetchRefdata: true - refdataRepo: 'azure' - useMamba: true - - - bash: | - cd $(tardis.dir) - source activate tardis - pip install pytest-azurepipelines - pytest tardis --tardis-refdata=$(refdata.dir) --cov=tardis --cov-report=xml --cov-report=html - displayName: 'Run tests' - - - bash: bash <(curl -s https://codecov.io/bash) - displayName: 'Upload to codecov.io' diff --git a/.azure-pipelines/templates/default.yml b/.azure-pipelines/templates/default.yml deleted file mode 100644 index aedecc84cb8..00000000000 --- a/.azure-pipelines/templates/default.yml +++ /dev/null @@ -1,85 +0,0 @@ -# For more information on how to use this template please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -parameters: - - name: useMamba - type: boolean - default: false - - - name: fetchRefdata - type: boolean - default: false - - - name: refdataRepo - type: string - default: azure - values: - - azure - - github - - - name: fetchDepth - type: number - default: 0 - - - name: tardisEnv - type: boolean - default: true - -steps: - - bash: echo "##vso[task.setvariable variable=shellopts]errexit" - displayName: 'Force BASH exit on error' - condition: eq(variables['Agent.OS'], 'Linux') - - - bash: | - echo "##vso[task.setvariable variable=tardis.dir]$(Build.SourcesDirectory)/tardis" - echo "##vso[task.setvariable variable=refdata.dir]$(Build.SourcesDirectory)/tardis-refdata" - displayName: 'Set environment variables' - - - ${{ if eq(parameters.useMamba, false) }}: - - bash: | - echo "##vso[task.setvariable variable=package.manager]conda" - displayName: 'Set environment variables' - - - ${{ if eq(parameters.useMamba, true) }}: - - bash: | - echo "##vso[task.setvariable variable=package.manager]mamba" - displayName: 'Set package manager' - - - checkout: self - path: s/tardis - fetchDepth: ${{ parameters.fetchDepth }} - - - ${{ if and(eq(parameters.fetchRefdata, true), eq(parameters.refdataRepo, 'azure')) }}: - - checkout: git://TARDIS/tardis-refdata - lfs: true - displayName: 'Fetch reference data (Azure)' - - - ${{ if and(eq(parameters.fetchRefdata, true), eq(parameters.refdataRepo, 'github')) }}: - - bash: | - git clone https://github.com/tardis-sn/tardis-refdata.git $(refdata.dir) - cd $(refdata.dir); git lfs fetch - displayName: 'Fetch reference data (GitHub)' - - - bash: echo "##vso[task.prependpath]$CONDA/bin" - displayName: 'Add conda to PATH' - - - bash: sudo chown -R $USER $CONDA - displayName: 'Take ownership of conda installation' - condition: eq(variables['Agent.OS'], 'Darwin') - - - ${{ if eq(parameters.useMamba, true) }}: - - bash: conda install mamba -c conda-forge -y - displayName: 'Install Mamba' - - - ${{ if eq(parameters.tardisEnv, true) }}: - - bash: | - cd $(tardis.dir) - $(package.manager) env create -f tardis_env3.yml - displayName: 'Setup environment' - - - ${{ if eq(parameters.tardisEnv, true) }}: - - bash: | - cd $(tardis.dir) - source activate tardis - python setup.py install - displayName: 'Install package' diff --git a/.azure-pipelines/update-refdata.yml b/.azure-pipelines/update-refdata.yml deleted file mode 100644 index 573cbc2019f..00000000000 --- a/.azure-pipelines/update-refdata.yml +++ /dev/null @@ -1,71 +0,0 @@ -# For more information on how to use this pipeline please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -# IMPORTANT: Only contributors with `Write` permission can trigger the build -# by commenting `/AzurePipelines run ` on the pull -# request. -# -# This feature can be disabled only through the Azure Pipelines -# dashboard. - -trigger: none - -pr: - branches: - include: - - master - -variables: - system.debug: false - commit.sha: '$(Build.SourceVersion)' - pr.number: '$(System.PullRequest.PullRequestNumber)' - build.id: '$(Build.BuildId)' - job.id: '$(System.JobId)' - log.url: 'https://dev.azure.com/tardis-sn/TARDIS/_build/results?buildId=$(build.id)&view=logs&jobId=$(job.id)' - -pool: - vmImage: 'ubuntu-latest' - -jobs: - - job: 'push' - steps: - - template: templates/default.yml - parameters: - fetchRefdata: true - refdataRepo: 'github' - useMamba: true - - - bash: | - cd $(tardis.dir) - source activate tardis - pytest tardis --tardis-refdata=$(refdata.dir) --generate-reference - displayName: 'Generate reference data' - - - bash: | - cd $(refdata.dir) - git add unit_test_data.h5 montecarlo_1e5_compare_data.h5 - git config --local user.email "tardis.sn.bot@gmail.com" - git config --local user.name "tardis-bot" - git commit -m "update reference data (pr $(pr.number))" - git remote set-url origin https://$(bot_token)@github.com/tardis-sn/tardis-refdata - git push origin master - displayName: 'Push new reference data' - - # Run only if the pipeline is triggered by a pull request. - - ${{ if eq(variables['Build.Reason'], 'PullRequest') }}: - - task: GitHubComment@0 - inputs: - gitHubConnection: 'tardis-sn' - repositoryName: 'tardis-sn/tardis' - id: $(pr.number) - comment: '**Update succeeded** $(commit.sha)

Changes pushed to [tardis-sn/tardis-refdata](/tardis-sn/tardis-refdata).' - displayName: 'Post results (success)' - - - task: GitHubComment@0 - inputs: - gitHubConnection: 'tardis-sn' - repositoryName: 'tardis-sn/tardis' - id: $(pr.number) - comment: '**Update failed** $(commit.sha)

For more information, check the [job log]($(log.url)).' - displayName: 'Post results (failed)' - condition: failed() diff --git a/.ci-helpers/download_reference_data.sh b/.ci-helpers/download_reference_data.sh new file mode 100644 index 00000000000..28c37ecb783 --- /dev/null +++ b/.ci-helpers/download_reference_data.sh @@ -0,0 +1,27 @@ +#!/usr/bin/env bash + +set -e + +REF_PATH="$GITHUB_WORKSPACE/tardis-refdata" +REPO_URL="https://dev.azure.com/tardis-sn/TARDIS/_apis/git/repositories/tardis-refdata" + +FILES=('atom_data/kurucz_cd23_chianti_H_He.h5' + 'atom_data/chianti_He.h5' + 'montecarlo_1e5_compare_data.h5' + 'packet_unittest.h5' + 'sdec_ref.h5' + 'unit_test_data.h5' + 'arepo_data/arepo_snapshot.hdf5' + 'arepo_data/arepo_snapshot.json' + 'nlte_atom_data/TestNLTE_He_Ti.h5') + +mkdir -p $REF_PATH/atom_data +mkdir -p $REF_PATH/arepo_data +mkdir -p $REF_PATH/nlte_atom_data + +for FILE in "${FILES[@]}" +do + wget -q "$REPO_URL/items?path=$FILE&resolveLfs=true" -O $REF_PATH/$FILE +done + +exit 0 diff --git a/.ci-helpers/get_current_version.py b/.ci-helpers/get_current_version.py index e1e67ec653f..35aad413593 100644 --- a/.ci-helpers/get_current_version.py +++ b/.ci-helpers/get_current_version.py @@ -2,7 +2,6 @@ import sys from setuptools_scm import version_from_scm -from setuptools_scm.version import guess_next_date_ver version = version_from_scm(".").tag.public diff --git a/.ci-helpers/get_min_docstr_cov.py b/.ci-helpers/get_min_docstr_cov.py new file mode 100644 index 00000000000..bb706250d9c --- /dev/null +++ b/.ci-helpers/get_min_docstr_cov.py @@ -0,0 +1,13 @@ +#!/usr/bin/env python + +import os +import sys +from parse import * + +input = sys.stdin.readline() +result = parse("RESULT: {res} (minimum: {min}%, actual: {act}%)", input.strip()) +minimum = float(result.named["act"]) - float(os.environ["THRESHOLD"]) + +print(round(minimum,2)) + +sys.exit(0) diff --git a/.ci-helpers/get_next_version.py b/.ci-helpers/get_next_version.py index 89bdf3cea35..0be3077414e 100644 --- a/.ci-helpers/get_next_version.py +++ b/.ci-helpers/get_next_version.py @@ -1,12 +1,25 @@ #!/usr/bin/env python import sys +from datetime import date from setuptools_scm import version_from_scm from setuptools_scm.version import guess_next_date_ver -version = version_from_scm(".").tag.public -version = guess_next_date_ver(version) -version = version.rstrip(".0") if version.endswith(".0") else version +scm_version = version_from_scm(".").tag.public +scm_version = guess_next_date_ver(scm_version) +scm_version = [ int(i) for i in scm_version.split(".") ] + +build = scm_version[3] +release = scm_version[0:3] +iso_date = date(*release).isoformat() +iso_date = iso_date.replace("-",".") + +if build > 0: + version = f"{iso_date}.{str(build)}" + +else: + version = iso_date print(version) + sys.exit(0) diff --git a/.ci-helpers/update_credits.py b/.ci-helpers/update_credits.py new file mode 100644 index 00000000000..3a59a7dc640 --- /dev/null +++ b/.ci-helpers/update_credits.py @@ -0,0 +1,84 @@ +"""Script for updating `credits.rst` and `README.rst` between releases, +requires the `rst-include` package""" + +import pathlib +import re +import textwrap +import warnings +from datetime import date + +import requests +from rst_include import rst_include + + +def generate_zenodo(): + """Generates `zenodo.rst` file with BibTeX citation + Adapted from: https://astrodata.nyc/posts/2021-04-23-zenodo-sphinx/""" + + CONCEPT_DOI = "592480" # See: https://help.zenodo.org/#versioning + zenodo_path = pathlib.Path("docs/resources/zenodo.rst") + year = date.today().year + + try: + headers = {"accept": "application/x-bibtex"} + response = requests.get( + f"https://zenodo.org/api/records/{CONCEPT_DOI}", headers=headers + ) + response.encoding = "utf-8" + citation = re.findall("@software{(.*)\,", response.text) + specific_doi = citation[0].lstrip(f"kerzendorf_wolfgang_{year}_") + doi_org_url = f"https://doi.org/10.5281/zenodo.{specific_doi}" + doi_badge = f"https://img.shields.io/badge/DOI-10.5281/zenodo.{specific_doi}-blue" + zenodo_record = ( + f".. |CITATION| replace:: {citation[0]}\n\n" + f".. |DOI_BADGE| image:: {doi_badge}\n" + f" :target: {doi_org_url}\n\n" + ".. code-block:: bibtex\n\n" + + textwrap.indent(response.text, " " * 4) + ) + + except Exception as e: + warnings.warn( + "Failed to retrieve Zenodo record for TARDIS: " f"{str(e)}" + ) + + not_found_msg = """ + Couldn"t retrieve the TARDIS software citation from Zenodo. Get it + directly from `this link `_ . + """ + + zenodo_record = ( + ".. |ZENODO| replace:: \n\n" + ".. warning:: \n\n" + textwrap.indent(not_found_msg, " " * 4) + ) + + with open(zenodo_path, "w") as f: + f.write(zenodo_record) + + print(zenodo_record) + + +def main(): + generate_zenodo() + + rst_include.include( + source="docs/resources/credits_template.rst", + target="docs/resources/credits.rst", + quiet=False, + inplace=False, + source_encoding="utf-8", + target_encoding="utf-8", + ) + + rst_include.include( + source="README_TEMPLATE.rst", + target="README.rst", + quiet=False, + inplace=False, + source_encoding="utf-8", + target_encoding="utf-8", + ) + + +if __name__ == "__main__": + main() diff --git a/.docstr.yaml b/.docstr.yaml deleted file mode 100644 index fff3de64dcd..00000000000 --- a/.docstr.yaml +++ /dev/null @@ -1,27 +0,0 @@ -paths: - - tardis -#badge: docs -#exclude: .*/test # regex -verbose: 2 # int (0-3) -skip_magic: True -skip_file_doc: True -skip_init: True -skip_class_def: False -skip_private: True -follow_links: True -#ignore_names_file: .*/test # regex -#fail_under: 90 -percentage_only: False -#ignore_patterns: # Dict with key/value pairs of file-pattern/node-pattern -# .*: method_to_ignore_in_all_files -# FileWhereWeWantToIgnoreAllSpecialMethods: "__.+__" -# SomeFile: -# - method_to_ignore1 -# - method_to_ignore2 -# - method_to_ignore3 -# a_very_important_view_file: -# - "^get$" -# - "^set$" -# - "^post$" -# detect_.*: -# - "get_val.*" diff --git a/.git-blame-ignore-revs b/.git-blame-ignore-revs index 92264c4aeb8..5f9a4aed526 100644 --- a/.git-blame-ignore-revs +++ b/.git-blame-ignore-revs @@ -1,3 +1,6 @@ # Code Style Black commits 3297d264ba607bc1dc641d130b1764965cf59023 +37875894ccb5f4fd99fcb24b42f0bb16f51c1427 d3f06101703df1e5635fff9a89a736e13d5b68bb +fca2c8c17457347a7b2e58aa3b7390f3fca8bdad +01544d18de7489f05b39ab7749523345236c90f8 diff --git a/.github/FUNDING.yml b/.github/FUNDING.yml deleted file mode 100644 index def7068590d..00000000000 --- a/.github/FUNDING.yml +++ /dev/null @@ -1,15 +0,0 @@ -# These are supported funding model platforms - -# github: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2] -# patreon: # Replace with a single Patreon username -# open_collective: # Replace with a single Open Collective username -# ko_fi: # Replace with a single Ko-fi username -# tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel -# community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry -# liberapay: # Replace with a single Liberapay username -# issuehunt: # Replace with a single IssueHunt username -# otechie: # Replace with a single Otechie username -# custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2'] - -github: numfocus -custom: https://numfocus.org/donate-to-tardis diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md deleted file mode 100644 index 40895f80a59..00000000000 --- a/.github/ISSUE_TEMPLATE.md +++ /dev/null @@ -1,11 +0,0 @@ -#### Code Sample, a copy-pastable example if possible - -```python -# Your code here - -``` -#### Problem description - -[this should explain **why** the current behaviour is a problem and why the expected output is a better solution.] - -#### Expected Output \ No newline at end of file diff --git a/.github/actions/setup_lfs/action.yml b/.github/actions/setup_lfs/action.yml new file mode 100644 index 00000000000..e65045956ca --- /dev/null +++ b/.github/actions/setup_lfs/action.yml @@ -0,0 +1,96 @@ +name: "Setup LFS" +description: "Pull LFS repositories and caches them" + +inputs: + refdata-repo: + description: "tardis refdata repository" + required: false + default: "tardis-sn/tardis-refdata" + regression-data-repo: + description: "tardis regression data repository" + required: false + default: "tardis-sn/tardis-regression-data" + +runs: + using: "composite" + steps: + - name: Clone Refdata Repo + uses: actions/checkout@v4 + with: + repository: ${{ inputs.refdata-repo }} + path: tardis-refdata + lfs: false + + - name: Create LFS file list + run: git lfs ls-files -l | cut -d' ' -f1 | sort > .lfs-assets-id + working-directory: tardis-refdata + shell: bash + + - name: Restore LFS cache + uses: actions/cache/restore@v4 + id: lfs-cache-refdata + with: + path: tardis-refdata/.git/lfs + key: ${{ runner.os }}-lfs-${{ hashFiles('tardis-refdata/.lfs-assets-id') }}-v1 + + - name: Git LFS Pull + run: git lfs pull + working-directory: tardis-refdata + if: steps.lfs-cache-refdata.outputs.cache-hit != 'true' + shell: bash + + - name: Git LFS Checkout + run: git lfs checkout + working-directory: tardis-refdata + if: steps.lfs-cache-refdata.outputs.cache-hit == 'true' + shell: bash + + - name: Save LFS cache if not found + # uses fake ternary + # for reference: https://github.com/orgs/community/discussions/26738#discussioncomment-3253176 + if: ${{ steps.lfs-cache-refdata.outputs.cache-hit != 'true' && always() || false }} + uses: actions/cache/save@v4 + id: lfs-cache-refdata-save + with: + path: tardis-refdata/.git/lfs + key: ${{ runner.os }}-lfs-${{ hashFiles('tardis-refdata/.lfs-assets-id') }}-v1 + + - name: Clone tardis-sn/tardis-regression-data + uses: actions/checkout@v4 + with: + repository: ${{ inputs.regression-data-repo }} + path: tardis-regression-data + + - name: Create LFS file list + run: git lfs ls-files -l | cut -d' ' -f1 | sort > .lfs-assets-id + working-directory: tardis-regression-data + shell: bash + + - name: Restore LFS cache + uses: actions/cache/restore@v4 + id: lfs-cache-regression-data + with: + path: tardis-regression-data/.git/lfs + key: ${{ runner.os }}-lfs-${{ hashFiles('tardis-regression-data/.lfs-assets-id') }}-v1 + + - name: Git LFS Pull + run: git lfs pull + working-directory: tardis-regression-data + if: steps.lfs-cache-regression-data.outputs.cache-hit != 'true' + shell: bash + + - name: Git LFS Checkout + run: git lfs checkout + working-directory: tardis-regression-data + if: steps.lfs-cache-regression-data.outputs.cache-hit == 'true' + shell: bash + + - name: Save LFS cache if not found + # uses fake ternary + # for reference: https://github.com/orgs/community/discussions/26738#discussioncomment-3253176 + if: ${{ steps.lfs-cache-regression-data.outputs.cache-hit != 'true' && always() || false }} + uses: actions/cache/save@v4 + id: lfs-cache-regression-data-save + with: + path: tardis-regression-data/.git/lfs + key: ${{ runner.os }}-lfs-${{ hashFiles('tardis-regression-data/.lfs-assets-id') }}-v1 diff --git a/.github/workflows/benchmarks.yml b/.github/workflows/benchmarks.yml new file mode 100644 index 00000000000..627a144ae84 --- /dev/null +++ b/.github/workflows/benchmarks.yml @@ -0,0 +1,197 @@ +name: benchmarks + +on: + push: + branches: + - master + + pull_request_target: + branches: + - master + + types: + - opened + - reopened + - synchronize + - labeled # benchmarks label required + workflow_dispatch: + +concurrency: + group: ${{ github.workflow }}-${{ github.head_ref || github.ref }} + cancel-in-progress: true + +defaults: + run: + shell: bash -l {0} + +jobs: + build: + if: github.repository_owner == 'tardis-sn' && + (github.event_name == 'push' || + github.event_name == 'workflow_dispatch' || + (github.event_name == 'pull_request_target' && + contains(github.event.pull_request.labels.*.name, 'benchmarks'))) + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + if: github.event_name != 'pull_request_target' + with: + fetch-depth: 0 + + - name: Checkout pull/${{ github.event.number }} + uses: actions/checkout@v4 + with: + ref: ${{ github.sha }} + fetch-depth: 0 + if: github.event_name == 'pull_request_target' + + - name: Restore Atom Data + uses: actions/cache/restore@v4 + id: atom-data-restore + with: + path: benchmarks/data/kurucz_cd23_chianti_H_He.h5 + key: atom-data + + - name: Download Atom Data + if: steps.atom-data-restore.outputs.cache-hit != 'true' + run: | + REPO_URL="https://dev.azure.com/tardis-sn/TARDIS/_apis/git/repositories/tardis-refdata" + wget -q "$REPO_URL/items?path=atom_data/kurucz_cd23_chianti_H_He.h5&versionType=branch&version=master&resolveLfs=true" -O benchmarks/data/kurucz_cd23_chianti_H_He.h5 + + - name: Save Atom Data + uses: actions/cache/save@v4 + if: ${{ steps.atom-data-restore.outputs.cache-hit != 'true' && always() || false }} + id: atom-data-cache-save + with: + path: benchmarks/data/kurucz_cd23_chianti_H_He.h5 + key: atom-data + + - name: Setup Mamba + uses: mamba-org/setup-micromamba@v1 + with: + environment-name: benchmark + init-shell: >- + bash + create-args: >- + python + asv + mamba + + - name: Install asv + run: pip install asv + + - name: Accept all asv questions + run: asv machine --yes + + - name: Run benchmarks for last 5 commits if not PR + if: github.event_name != 'pull_request_target' + run: | + git log -n 5 --pretty=format:"%H" >> tag_commits.txt + asv run HASHFILE:tag_commits.txt | tee asv-output.log + if grep -q failed asv-output.log; then + echo "Some benchmarks have failed!" + exit 1 + fi + + - name: Generate Graphs and HTML + if: github.event_name != 'pull_request_target' + run: asv publish + + - name: Delete env files + if: github.event_name != 'pull_request_target' + run: rm -r .asv/env + + - name: Push results to results repository + if: github.event_name != 'pull_request_target' + continue-on-error: true + uses: cpina/github-action-push-to-another-repository@main + env: + API_TOKEN_GITHUB: ${{ secrets.BOT_TOKEN }} + with: + source-directory: .asv + destination-github-username: tardis-sn + destination-repository-name: tardis-benchmarks + user-email: tardis.sn.bot@gmail.com + target-branch: main + target-directory: .asv + + - name: Compare HEAD with master if PR + if: github.event_name == 'pull_request_target' + continue-on-error: true # TODO: step failed sporadically while testing + run: | + asv continuous ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }} | tee asv-cont-output.log + if grep -q failed asv-cont-output.log; then + echo "Some benchmarks have errors!" + exit 1 + fi + + - name: Compare Master and PR head + run: asv compare ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }} | tee asv-compare-output.log + + - name: Compare Master and PR head but only show changed results + run: asv compare ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }} --only-changed | tee asv-compare-changed-output.log + + - name: Benchmarks compare output + id: asv_pr_vs_master + uses: juliangruber/read-file-action@v1.0.0 + with: + path: asv-compare-output.log + + - name: Benchmarks compare only changed output + id: asv_pr_vs_master_changed + uses: juliangruber/read-file-action@v1.0.0 + with: + path: asv-compare-changed-output.log + + - name: Find Comment + if: always() && github.event_name == 'pull_request_target' + uses: peter-evans/find-comment@v1 + id: fc + with: + issue-number: ${{ github.event.number }} + body-includes: I ran benchmarks as you asked + + - name: Post comment + if: github.event_name == 'pull_request_target' + uses: peter-evans/create-or-update-comment@v2 + with: + token: ${{ secrets.BOT_TOKEN }} + issue-number: ${{ github.event.number }} + comment-id: ${{ steps.fc.outputs.comment-id }} + edit-mode: replace + body: | + *\*beep\* \*bop\** + Hi human, + I ran benchmarks as you asked comparing master (${{ github.event.pull_request.base.sha }}) and the latest commit (${{ github.event.pull_request.head.sha }}). + Here are the logs produced by ASV. + Results can also be downloaded as artifacts [**here**](${{ env.URL }}). + Significantly changed benchmarks: +
+ + ```diff + ${{ steps.asv_pr_vs_master_changed.outputs.content }} + ``` + +
+ + All benchmarks: +
+ + ```diff + ${{ steps.asv_pr_vs_master.outputs.content }} + ``` + +
+ env: + URL: https://github.com/${{ github.repository_owner }}/${{ github.event.repository.name }}/actions/runs/${{ github.run_id }}?check_suite_focus=true + + - name: Save results artifact + uses: actions/upload-artifact@v4 + if: always() + with: + name: asv-benchmark-results-${{ runner.os }} + path: | + .asv/results + asv-cont-output.log + asv-compare-output.log + asv-compare-changed-output.log diff --git a/.github/workflows/black-check.yml b/.github/workflows/black-check.yml deleted file mode 100644 index 2925827b504..00000000000 --- a/.github/workflows/black-check.yml +++ /dev/null @@ -1,26 +0,0 @@ -# For more information on how to use this template please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -name: black - -on: - pull_request: - branches: - - master - -jobs: - check: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v2 - - - name: Setup Python - uses: actions/setup-python@v2 - with: - python-version: 3.x - - - name: Install Black - run: pip install black==21.12b0 - - - name: Run Black - run: black --check tardis diff --git a/.github/workflows/build-docs.yml b/.github/workflows/build-docs.yml new file mode 100644 index 00000000000..7fc44e742e2 --- /dev/null +++ b/.github/workflows/build-docs.yml @@ -0,0 +1,215 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/contributing/development/continuous_integration.html + +name: docs + +on: + push: + branches: + - master + + pull_request_target: + branches: + - master + + types: + - opened + - reopened + - synchronize + - labeled # requires the `build-docs` label + + workflow_dispatch: # manual trigger + +env: + CACHE_NUMBER: 0 # increase to reset cache manually + DEPLOY_BRANCH: gh-pages # deployed docs branch + HDF5_USE_FILE_LOCKING: "FALSE" # disable file locking + +concurrency: + group: ${{ github.workflow }}-${{ github.head_ref || github.ref }} + cancel-in-progress: true + +defaults: + run: + shell: bash -l {0} + +jobs: + check-for-changes: + runs-on: ubuntu-latest + outputs: + trigger-check-outcome: ${{ steps.trigger_check.outcome }} + docs-check-outcome: ${{ steps.docs_check.outcome }} + steps: + - uses: actions/checkout@v4 + if: github.event_name != 'pull_request_target' + + - name: Checkout pull/${{ github.event.number }} + uses: actions/checkout@v4 + with: + fetch-depth: 0 + ref: ${{ github.event.pull_request.head.sha }} + if: github.event_name == 'pull_request_target' + + - name: Check for trigger by push event, manual dispatch, build-docs label on a PR + id: trigger_check + if: github.event_name == 'push' || github.event_name == 'workflow_dispatch' || github.event_name == 'pull_request_target' && contains(github.event.pull_request.labels.*.name, 'build-docs') + run: | + echo "Building docs as a test." + exit 0 + continue-on-error: true + + - name: Check for changes in documentation + run: | + if git diff origin/master..."$(git rev-parse --abbrev-ref HEAD)" --name-only | cat | grep '^docs/' | grep -q .; then + num_files=$(git diff --name-only origin/master...HEAD | grep '^docs/' | wc -l) + echo "Changes found in documentation files: $num_files" + exit 0 + else + echo "No changes found in documentation files - will stop running the pipeline." + exit 1 + fi + id: docs_check + if: steps.trigger_check.outcome != 'success' + continue-on-error: true + + build-docs: + runs-on: ubuntu-latest + needs: check-for-changes + if: needs.check-for-changes.outputs.trigger-check-outcome == 'success' || needs.check-for-changes.outputs.docs-check-outcome == 'success' + steps: + - uses: actions/checkout@v4 + if: github.event_name != 'pull_request_target' + + - name: Checkout pull/${{ github.event.number }} + uses: actions/checkout@v4 + with: + fetch-depth: 0 + ref: ${{ github.event.pull_request.head.sha }} + if: github.event_name == 'pull_request_target' + + - name: Generate Cache Key + run: | + file_hash=$(cat conda-linux-64.lock | shasum -a 256 | cut -d' ' -f1) + echo "file_hash=$file_hash" >> "${GITHUB_OUTPUT}" + id: cache-environment-key + + - name: Setup LFS + uses: ./.github/actions/setup_lfs + + - name: Copy atom_data + run: | + mkdir -p ~/Downloads/tardis-data && cp -a ./tardis-refdata/atom_data/. ~/Downloads/tardis-data + + - uses: mamba-org/setup-micromamba@v1 + with: + environment-file: conda-linux-64.lock + cache-environment-key: ${{ steps.cache-environment-key.outputs.file_hash }} + cache-downloads-key: ${{ steps.cache-environment-key.outputs.file_hash }} + environment-name: tardis + cache-environment: true + cache-downloads: true + + - name: Install package + run: pip install -e . + + - name: Build documentation + run: cd docs/ && make html NCORES=auto + + - name: Set destination directory + run: | + BRANCH=$(echo ${GITHUB_REF#refs/heads/}) + if [[ $EVENT == push ]] || [[ $EVENT == workflow_dispatch ]]; then + + if [[ $BRANCH == $DEFAULT ]]; then + echo "DEST_DIR=" >> $GITHUB_ENV + else + echo "DEST_DIR=branch/$BRANCH" >> $GITHUB_ENV + fi + + elif [[ $EVENT == pull_request_target ]]; then + echo "DEST_DIR=pull/$PR" >> $GITHUB_ENV + + else + echo "Unexpected event trigger $EVENT" + exit 1 + + fi + + cat $GITHUB_ENV + env: + DEFAULT: ${{ github.event.repository.default_branch }} + EVENT: ${{ github.event_name }} + PR: ${{ github.event.number }} + + - name: Set clean branch option + run: | + if [[ $EVENT == workflow_dispatch ]]; then + echo "CLEAN_BRANCH=true" >> $GITHUB_ENV + + else + echo "CLEAN_BRANCH=false" >> $GITHUB_ENV + + fi + + cat $GITHUB_ENV + env: + EVENT: ${{ github.event_name }} + + - name: Deploy ${{ env.DEST_DIR }} + uses: peaceiris/actions-gh-pages@v4 + with: + github_token: ${{ secrets.BOT_TOKEN }} + publish_branch: ${{ env.DEPLOY_BRANCH }} + publish_dir: ./docs/_build/html + destination_dir: ${{ env.DEST_DIR }} + keep_files: true + force_orphan: ${{ env.CLEAN_BRANCH }} + user_name: "TARDIS Bot" + user_email: "tardis.sn.bot@gmail.com" + + - name: Find comment + uses: peter-evans/find-comment@v1 + id: fc + with: + issue-number: ${{ github.event.number }} + body-includes: Hi, human. + if: always() && github.event_name == 'pull_request_target' + + - name: Post comment (success) + uses: peter-evans/create-or-update-comment@v1 + with: + token: ${{ secrets.BOT_TOKEN }} + issue-number: ${{ github.event.number }} + comment-id: ${{ steps.fc.outputs.comment-id }} + edit-mode: replace + body: | + *\*beep\* \*bop\** + + Hi, human. + + The **`${{ github.workflow }}`** workflow has **succeeded** :heavy_check_mark: + + [**Click here**](${{ env.URL }}) to see your results. + env: + URL: https://${{ github.repository_owner }}.github.io/${{ github.event.repository.name }}/pull/${{ github.event.number }}/index.html + if: success() && github.event_name == 'pull_request_target' + + - name: Post comment (failure) + uses: peter-evans/create-or-update-comment@v1 + with: + token: ${{ secrets.BOT_TOKEN }} + issue-number: ${{ github.event.number }} + comment-id: ${{ steps.fc.outputs.comment-id }} + edit-mode: replace + body: | + *\*beep\* \*bop\** + + Hi, human. + + The **`${{ github.workflow }}`** workflow has **failed** :x: + + [**Click here**](${{ env.URL }}) to see the build log. + env: + URL: https://github.com/${{ github.repository_owner }}/${{ github.event.repository.name }}/actions/runs/${{ github.run_id }}?check_suite_focus=true + if: failure() && github.event_name == 'pull_request_target' diff --git a/.github/workflows/clean-docs.yml b/.github/workflows/clean-docs.yml new file mode 100644 index 00000000000..cbbed1b1b53 --- /dev/null +++ b/.github/workflows/clean-docs.yml @@ -0,0 +1,62 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/contributing/development/continuous_integration.html + +name: clean-docs + +on: + delete: + branches: # remove deleted branches + - "*" + + pull_request_target: # remove closed or merged pull requests + branches: + - "*" + types: + - closed + +env: + DEPLOY_BRANCH: gh-pages # deployed docs branch + +jobs: + clean: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set folder to delete + run: | + if [[ $EVENT == delete ]]; then + echo "DEST_DIR=$EVENT_TYPE/$EVENT_REF" >> $GITHUB_ENV + + elif [[ $EVENT == pull_request_target ]]; then + echo "DEST_DIR=pull/$PR" >> $GITHUB_ENV + + else + echo "Unexpected event trigger $EVENT" + exit 1 + + fi + cat $GITHUB_ENV + env: + PR: ${{ github.event.number }} + EVENT: ${{ github.event_name }} + EVENT_REF: ${{ github.event.ref }} + EVENT_TYPE: ${{ github.event.ref_type }} + + - name: Clean ${{ env.DEST_DIR }} + run: | + git fetch origin ${{ env.DEPLOY_BRANCH }} + git checkout ${{ env.DEPLOY_BRANCH }} + git config user.name "TARDIS Bot" + git config user.email tardis.sn.bot@gmail.com + + if [[ -d $DEST_DIR ]]; then + git rm -rf $DEST_DIR + git commit -m "clean $DEST_DIR" + git push + + else + echo "$DEST_DIR does not exist" + + fi diff --git a/.github/workflows/codestyle.yml b/.github/workflows/codestyle.yml new file mode 100644 index 00000000000..82bba3de516 --- /dev/null +++ b/.github/workflows/codestyle.yml @@ -0,0 +1,31 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/contributing/development/continuous_integration.html + +name: codestyle + +on: + push: + branches: + - "*" + + pull_request: + branches: + - "*" + +jobs: + black: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: 3.x + + - name: Install Black + run: pip install black==22.3 + + - name: Run Black + run: black --check tardis diff --git a/.github/workflows/dispatcher.yml b/.github/workflows/dispatcher.yml new file mode 100644 index 00000000000..be007a91270 --- /dev/null +++ b/.github/workflows/dispatcher.yml @@ -0,0 +1,32 @@ +name: slash-command +on: + issue_comment: + types: [created] + +jobs: + dispatch: + runs-on: ubuntu-latest + steps: + - name: Slash Command Dispatcher + uses: peter-evans/slash-command-dispatch@v3 + with: + token: ${{ secrets.BOT_TOKEN }} + commands: | + update-refdata + repository: tardis-sn/tardis + issue-type: pull-request + permission: triage + reaction-token: ${{ secrets.BOT_TOKEN }} + allow-edits: true + + - name: Slash Command Dispatcher + uses: peter-evans/slash-command-dispatch@v3 + with: + token: ${{ secrets.BOT_TOKEN }} + commands: | + compare-refdata + repository: tardis-sn/tardis-refdata + issue-type: pull-request + permission: triage + reaction-token: ${{ secrets.BOT_TOKEN }} + allow-edits: true diff --git a/.github/workflows/docstr-cov.yml b/.github/workflows/docstr-cov.yml new file mode 100644 index 00000000000..6ebe1fd1e24 --- /dev/null +++ b/.github/workflows/docstr-cov.yml @@ -0,0 +1,104 @@ +# Log in to jsonbin.org with tardis-bot GitHub account to get an API key and +# store it as a repository secret. + +# Updated badge will be available at: +# https://img.shields.io/endpoint?url=https://jsonbin.org/tardis-bot/tardis/badges/docstr-cov + +name: docstr-cov + +on: + push: + branches: + - master + + pull_request: + branches: + - master + +env: + THRESHOLD: 0.05 + RANGE: 50..75 + ENDPOINT: https://jsonbin.org/tardis-bot/${{ github.event.repository.name }} + TOKEN: ${{ secrets.JSONBIN_APIKEY }} + +jobs: + check: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + fetch-depth: 0 + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: 3.x + + - name: Install interrogate + run: pip install interrogate==1.5.0 parse==1.19.0 setuptools + + - name: Get SHAs + run: | + if [[ ${{ github.event_name }} == 'push' ]]; then + echo "BASE=$(git rev-parse HEAD^)" >> $GITHUB_ENV + echo "HEAD=$(git rev-parse HEAD)" >> $GITHUB_ENV + + elif [[ ${{ github.event_name }} == 'pull_request' ]]; then + echo "BASE=${{ github.event.pull_request.base.sha }}" >> $GITHUB_ENV + echo "HEAD=${{ github.event.pull_request.head.sha }}" >> $GITHUB_ENV + + else + echo "Unexpected event trigger" + exit 1 + fi + + - name: Get ${{ github.event.pull_request.base.sha }} coverage + run: | + git checkout $BASE + echo "BASE_COV=$(interrogate tardis -c pyproject.toml | python .ci-helpers/get_min_docstr_cov.py)" >> $GITHUB_ENV + + - name: Test ${{ github.event.pull_request.head.sha }} coverage + run: | + echo "$BASE coverage was: $BASE_COV%" + git checkout $HEAD + interrogate tardis -c pyproject.toml --fail-under=$BASE_COV -v + + - name: Blame + run: git diff --name-only $(git merge-base $BASE $HEAD) -- 'tardis/**/*.py' | xargs -i interrogate {} -c pyproject.toml --fail-under=100 -v + if: failure() + + - name: Get new coverage + run: echo "NEW_COV=$(interrogate tardis -c pyproject.toml | python .ci-helpers/get_min_docstr_cov.py)" >> $GITHUB_ENV + if: always() && github.event_name == 'push' + + - name: Set label color + run: | + if [[ $NEW_COV -ge $(echo {${{ env.RANGE }}} | awk '{print $NF;}') ]]; then + echo "COLOR=green" >> $GITHUB_ENV + + elif [[ $NEW_COV -lt $(echo {${{ env.RANGE }}} | awk '{print $1;}') ]]; then + echo "COLOR=red" >> $GITHUB_ENV + + else + echo "COLOR=orange" >> $GITHUB_ENV + + fi + if: always() && github.event_name == 'push' + + - name: Post results + run: | + echo "New coverage is: $NEW_COV%" + curl -X POST $ENDPOINT/badges/docstr-cov \ + -H "authorization: token $TOKEN" \ + -d "{ \"schemaVersion\": 1, \"label\": \"docstr-cov\", \ + \"message\": \"$NEW_COV%\", \"color\": \"$COLOR\" }" + if: always() && github.event_name == 'push' + + - name: Set public endpoint + run: | + curl -X PUT $ENDPOINT/_perms -H "authorization: token $TOKEN" + if: always() && github.event_name == 'push' + + - name: Show badge URL + run: echo "https://img.shields.io/endpoint?url=$ENDPOINT/badges/docstr-cov" + if: always() && github.event_name == 'push' diff --git a/.github/workflows/docstr-coverage.yml b/.github/workflows/docstr-coverage.yml deleted file mode 100644 index 2f25d773db2..00000000000 --- a/.github/workflows/docstr-coverage.yml +++ /dev/null @@ -1,69 +0,0 @@ -name: docstr-coverage - -on: - push: - branches: - - master - - pull_request: - branches: - - master - -jobs: - check: - runs-on: ubuntu-latest - if: ${{ github.event_name == 'pull_request' }} - steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 0 - - - name: Setup Python - uses: actions/setup-python@v2 - with: - python-version: 3.x - - - name: Install docstr-coverage - run: pip install docstr-coverage - - - name: Get base coverage - run: | - git checkout ${{ github.event.pull_request.base.sha }} - echo "BASE_COV=$(docstr-coverage -p)" >> $GITHUB_ENV - - - name: Get head coverage - run: | - git checkout ${{ github.event.pull_request.head.sha }} - docstr-coverage --fail-under=$BASE_COV - - - name: Blame - if: ${{ failure() }} - run: | - git diff --name-only $(git merge-base ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }}) | xargs docstr-coverage --accept-empty - - post: - runs-on: ubuntu-latest - if: github.repository_owner == 'tardis-sn' && github.event_name == 'push' - steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 1 - - - name: Setup Python - uses: actions/setup-python@v2 - with: - python-version: 3.x - - - name: Install docstr-coverage - run: pip install docstr-coverage - - - name: Get coverage (rounded) - run: echo "NEW_COV=$(printf "%.f" $(docstr-coverage -p))" >> $GITHUB_ENV - - # Using jsonbin.org with tardis-bot GitHub account - - name: Post results - run: | - curl -X POST https://jsonbin.org/tardis-bot/badges/tardis/docstr-coverage -H 'authorization: token ${{ secrets.JSONBIN_APIKEY }}' -d "{ \"schemaVersion\": 1, \"label\": \"docstr-coverage\", \"message\": \"$NEW_COV%\", \"color\": \"orange\" }" - - # Updated badge will be available at: https://img.shields.io/endpoint?url=https://jsonbin.org/tardis-bot/badges/tardis/docstr-coverage - # Could take some minutes! diff --git a/.github/workflows/documentation-build.yml b/.github/workflows/documentation-build.yml deleted file mode 100644 index 49481fdb032..00000000000 --- a/.github/workflows/documentation-build.yml +++ /dev/null @@ -1,45 +0,0 @@ -# For more information on how to use this template please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -name: docs - -on: - push: - branches: - - master - - workflow_dispatch: # Manual trigger - -jobs: - build: - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 0 - - - name: Setup environment - uses: conda-incubator/setup-miniconda@v2 - with: - miniforge-variant: Mambaforge - miniforge-version: latest - environment-file: tardis_env3.yml - activate-environment: tardis - use-mamba: true - - - name: Install TARDIS - shell: bash -l {0} - run: python setup.py install - - - name: Build Sphinx Documentation - shell: bash -l {0} - run: cd docs/; make html CORES=auto - - - name: Deploy - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: docs/_build/html/ - publish_branch: gh-pages - force_orphan: true diff --git a/.github/workflows/documentation-preview.yml b/.github/workflows/documentation-preview.yml deleted file mode 100644 index b0d86aa2ef3..00000000000 --- a/.github/workflows/documentation-preview.yml +++ /dev/null @@ -1,60 +0,0 @@ -# For more information on how to use this pipeline please refer to: -# - http://tardis-sn.github.io/tardis/development/continuous_integration.html -# - https://tardis-sn.github.io/tardis/development/documentation_preview.html - -name: docs-preview - -on: - push: - -jobs: - build: - - # This workflow will be triggered: - # - # 1. Only on forks, never on main repository. - # 2. If the branch name contains the word `doc`. - # 3. If the commit message includes the a valid tag. - - if: github.repository_owner != 'tardis-sn' && ( - contains(github.ref, 'doc') || - contains(github.event.head_commit.message, '[build docs]') || - contains(github.event.head_commit.message, '[build_docs]') || - contains(github.event.head_commit.message, '[build doc]') || - contains(github.event.head_commit.message, '[build_doc]')) - - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 0 - - - name: Setup environment - uses: conda-incubator/setup-miniconda@v2 - with: - miniforge-variant: Mambaforge - miniforge-version: latest - environment-file: tardis_env3.yml - activate-environment: tardis - use-mamba: true - - - name: Install package - shell: bash -l {0} - run: python setup.py install - - - name: Build documentation - shell: bash -l {0} - run: cd docs/; make html CORES=auto - - - name: Extract branch name - shell: bash - run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF#refs/heads/})" - id: extract_branch - - - name: Deploy site - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_branch: gh-pages - publish_dir: docs/_build/html/ - destination_dir: branch/${{ steps.extract_branch.outputs.branch }} diff --git a/.github/workflows/mailmap-check.yml b/.github/workflows/mailmap-check.yml deleted file mode 100644 index a22fce5ad42..00000000000 --- a/.github/workflows/mailmap-check.yml +++ /dev/null @@ -1,28 +0,0 @@ -# For more information on how to use this template please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -name: mailmap - -on: - pull_request: - branches: - - master - -jobs: - check: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 0 - - - name: Check PR authors - run: cat .mailmap | grep "$(git log $PR_BASE_SHA..HEAD --pretty='%aN <%aE>')" - env: - PR_BASE_SHA: ${{ github.event.pull_request.base.sha }} - - - name: Error message - run: | - echo "Committer name or email couldn't be found in .mailmap" - echo; git log $PR_BASE_SHA..HEAD --pretty='%aN <%aE>' - if: failure() diff --git a/.github/workflows/mailmap.yml b/.github/workflows/mailmap.yml new file mode 100644 index 00000000000..4ca95d7a198 --- /dev/null +++ b/.github/workflows/mailmap.yml @@ -0,0 +1,46 @@ +# For more information on how to use this template please refer to: +# https://tardis-sn.github.io/tardis/contributing/development/continuous_integration.html + +name: mailmap + +on: + pull_request_target: + branches: + - master + +jobs: + check: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + ref: ${{ github.event.pull_request.head.sha }} + fetch-depth: 0 + + - name: Check PR authors + run: cat .mailmap | grep "$(git log $PR_BASE_SHA..HEAD --pretty='%aN <%aE>')" + env: + PR_BASE_SHA: ${{ github.event.pull_request.base.sha }} + + - name: Error message + run: | + echo "Committer name or email couldn't be found in .mailmap" + echo; git log $PR_BASE_SHA..HEAD --pretty='%aN <%aE>' + if: failure() + + - name: Create comment + uses: peter-evans/create-or-update-comment@v2 + with: + token: ${{ secrets.BOT_TOKEN }} + issue-number: ${{ github.event.pull_request.number }} + body: | + *\*beep\* \*bop\** + + Hi, human. + + I'm the @tardis-bot and couldn't find your records in my database. I think we don't know each other, or you changed your credentials recently. + + Please add your **name** and **email** to `.mailmap` in your current branch and push the changes to this pull request. + + In case you need to map an existing alias, follow [this example](https://docs.enterprise.codescene.io/versions/2.0.0/getting-started/ensure-you-use-a-mailmap.html). + if: failure() diff --git a/.github/workflows/post-release.yml b/.github/workflows/post-release.yml new file mode 100644 index 00000000000..6995d4c6e0b --- /dev/null +++ b/.github/workflows/post-release.yml @@ -0,0 +1,154 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/contributing/development/continuous_integration.html + +name: post-release + +on: + release: + types: [published] + + workflow_dispatch: # manual trigger + +jobs: + changelog: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + repository: tardis-sn/tardis + token: ${{ secrets.BOT_TOKEN }} + fetch-depth: 0 + + - name: Generate a changelog + uses: orhun/git-cliff-action@v3 + with: + config: cliff.toml + args: --verbose + env: + OUTPUT: CHANGELOG.md + + - uses: actions/upload-artifact@v4 + with: + name: changelog + path: CHANGELOG.md + + citation: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Wait for Zenodo webhook + run: sleep 180 + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: "3.x" + + - name: Install doi2cff + run: pip install git+https://github.com/citation-file-format/doi2cff + + - name: Update CITATION.cff + run: | + rm CITATION.cff + doi2cff init 10.5281/zenodo.592480 + + - uses: actions/upload-artifact@v4 + with: + name: citation + path: CITATION.cff + + credits: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Wait for Zenodo webhook + run: sleep 180 + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: "3.x" + + - name: Install rst-include + run: pip install rst-include==2.1.2.2 requests==2.27.1 + + - name: Update README.rst + run: python .ci-helpers/update_credits.py + + - uses: actions/upload-artifact@v4 + with: + name: credits + path: | + README.rst + docs/resources/credits.rst + + pull_request: + needs: [changelog, citation, credits] + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - uses: actions/download-artifact@v4 + with: + path: /tmp + + - name: Copy files to repository + run: | + cp /tmp/changelog/CHANGELOG.md . + cp /tmp/citation/CITATION.cff . + cp -r /tmp/credits/* . + + - name: Get current date + run: echo "DATE=$(date +'%Y.%m.%d')" >> $GITHUB_ENV + + - uses: peter-evans/create-pull-request@v4 + with: + token: ${{ secrets.BOT_TOKEN }} + committer: TARDIS Bot + author: TARDIS Bot + branch: post-release-${{ env.DATE }} + base: master + push-to-fork: tardis-bot/tardis + commit-message: Automated changes for post-release ${{ env.DATE }} + title: Post-release ${{ env.DATE }} + body: | + *\*beep\* \*bop\** + + Hi, human. + + These are the changes required after the latest TARDIS release. + + > :warning: **Warning:** + > + > The `post_release` workflow waits for a webhook and then updates the citation files. If the file is not modified by this pull request, please check the latest release on [Zenodo's website](https://zenodo.org/record/592480), close this pull request, and [manually run the workflow](https://docs.github.com/en/actions/managing-workflow-runs/manually-running-a-workflow). + > + > This pull request should be auto-merged. + labels: automated, build-docs + team-reviewers: tardis-infrastructure + id: create-pr + + - name: Wait for pull request + run: sleep 30 + + - name: Approve pull request (I) + run: gh pr review ${{ steps.create-pr.outputs.pull-request-number }} --approve + env: + GITHUB_TOKEN: ${{ secrets.INFRASTRUCTURE_COORDINATOR_TOKEN }} + if: steps.create-pr.outputs.pull-request-operation == 'created' + + - name: Approve pull request (II) + run: gh pr review ${{ steps.create-pr.outputs.pull-request-number }} --approve + env: + GITHUB_TOKEN: ${{ secrets.CORE_COORDINATOR_TOKEN }} + if: steps.create-pr.outputs.pull-request-operation == 'created' + + - name: Enable automerge + uses: peter-evans/enable-pull-request-automerge@v2 + with: + token: ${{ secrets.INFRASTRUCTURE_COORDINATOR_TOKEN }} + pull-request-number: ${{ steps.create-pr.outputs.pull-request-number }} + merge-method: squash + if: steps.create-pr.outputs.pull-request-operation == 'created' diff --git a/.github/workflows/pr_review_checklist.yml b/.github/workflows/pr_review_checklist.yml deleted file mode 100644 index 5ce96dafc21..00000000000 --- a/.github/workflows/pr_review_checklist.yml +++ /dev/null @@ -1,24 +0,0 @@ -name: pr-review - -on: - pull_request_target: - types: [review_requested] - -jobs: - comment: - runs-on: ubuntu-latest - steps: - - uses: mshick/add-pr-comment@v1 - with: - repo-token: ${{ secrets.BOT_TOKEN }} - repo-token-user-login: 'tardis-bot' - message: "Before a pull request is accepted, it must meet the following criteria: \n - - [ ] Is the necessary information provided? \n - - [ ] Is this a duplicate PR? \n - \t - [ ] If a new PR is clearly a duplicate, ask how this PR is different from the original PR? \n - \t - [ ] If this PR is about to be merged, close the original PR with a link to this new PR that solved the issue. \n - - [ ] Does it pass existing tests and are new tests provided if required? \n - \t - [ ] The test coverage should not decrease, and for new features should be close to 100%. \n - - [ ] Is the code tidy? \n - \t - [ ] No unnecessary print lines or code comments. \n" - allow-repeats: false diff --git a/.github/workflows/pre-release.yml b/.github/workflows/pre-release.yml new file mode 100644 index 00000000000..69268254ed0 --- /dev/null +++ b/.github/workflows/pre-release.yml @@ -0,0 +1,140 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/contributing/development/continuous_integration.html + +name: pre-release + +on: + schedule: + - cron: "0 0 * * 0" + workflow_dispatch: # manual trigger + +defaults: + run: + shell: bash -l {0} + +jobs: + zenodo: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + repository: tardis-sn/tardis_zenodo + token: ${{ secrets.BOT_TOKEN }} + + - name: Dump Secret Key + run: echo "$KEY_SECRET_JSON" > key_secret.json + env: + KEY_SECRET_JSON: ${{ secrets.ZENODO_KEY_SECRET_JSON }} + + - name: Download Lock File + run: wget -q https://raw.githubusercontent.com/tardis-sn/tardis/master/conda-linux-64.lock + + - name: Generate Cache Key + run: | + file_hash=$(cat conda-linux-64.lock | shasum -a 256 | cut -d' ' -f1) + echo "file_hash=$file_hash" >> "${GITHUB_OUTPUT}" + id: cache-environment-key + + - uses: mamba-org/setup-micromamba@v1 + with: + environment-file: conda-linux-64.lock + cache-environment-key: ${{ steps.cache-environment-key.outputs.file_hash }} + cache-downloads-key: ${{ steps.cache-environment-key.outputs.file_hash }} + environment-name: tardis + cache-environment: true + cache-downloads: true + + - name: Run Notebook + run: jupyter nbconvert gather_data.ipynb --to html --execute --ExecutePreprocessor.timeout=6000 + + - name: Run Notebook (allow errors) + run: jupyter nbconvert gather_data.ipynb --to html --execute --ExecutePreprocessor.timeout=6000 --allow-errors + if: failure() + + - uses: actions/upload-artifact@v4 + with: + name: zenodo_json + path: .zenodo.json + + pull_request: + needs: zenodo + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - uses: actions/download-artifact@v4 + with: + path: /tmp + + - name: Copy zenodo.json to repository + run: | + cp /tmp/zenodo_json/.zenodo.json . + + - name: Get current date + run: echo "DATE=$(date +'%Y.%m.%d')" >> $GITHUB_ENV + + - uses: peter-evans/create-pull-request@v4 + with: + token: ${{ secrets.BOT_TOKEN }} + committer: TARDIS Bot + author: TARDIS Bot + branch: pre-release-${{ env.DATE }} + base: master + push-to-fork: tardis-bot/tardis + commit-message: Automated changes for pre-release ${{ env.DATE }} + title: Pre-release ${{ env.DATE }} + body: | + *\*beep\* \*bop\** + + Hi, human. + + I prepared everything for a new TARDIS release. + +
+ + > :warning: **WARNING:** + > + > This pull request should be auto-merged. **Do not merge manually if any check fails**. + > + > Instead, disable auto-merge and push your fixes to the [`pre-release-${{ env.DATE }}`](https://github.com/tardis-bot/tardis/tree/pre-release-${{ env.DATE }}) branch on [**tardis-bot/tardis**](https://github.com/tardis-bot/tardis). + > + > ``` + > $ git remote add tardis-bot git@github.com:tardis-bot/tardis.git + > $ git fetch tardis-bot + > $ git checkout tardis-bot/pre-release-${{ env.DATE }} + > $ git add ... + > $ git commit -m "" + > $ git push tardis-bot HEAD:pre-release-${{ env.DATE }} + > ``` + > + > Once all the checks pass, you can safely merge this pull request manually. + labels: automated, build-docs + team-reviewers: tardis-infrastructure + id: create-pr + + - name: Wait for pull request + run: sleep 30 + + - name: Approve pull request (I) + run: gh pr review ${{ steps.create-pr.outputs.pull-request-number }} --approve + env: + GITHUB_TOKEN: ${{ secrets.INFRASTRUCTURE_COORDINATOR_TOKEN }} + if: steps.create-pr.outputs.pull-request-operation == 'created' + + - name: Approve pull request (II) + run: gh pr review ${{ steps.create-pr.outputs.pull-request-number }} --approve + env: + GITHUB_TOKEN: ${{ secrets.CORE_COORDINATOR_TOKEN }} + if: steps.create-pr.outputs.pull-request-operation == 'created' + + - name: Enable automerge + uses: peter-evans/enable-pull-request-automerge@v2 + with: + token: ${{ secrets.INFRASTRUCTURE_COORDINATOR_TOKEN }} + pull-request-number: ${{ steps.create-pr.outputs.pull-request-number }} + merge-method: squash + if: steps.create-pr.outputs.pull-request-operation == 'created' + + compare_refdata: + uses: tardis-sn/tardis-refdata/.github/workflows/compare-refdata.yml@master diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml new file mode 100644 index 00000000000..be32edfaa4d --- /dev/null +++ b/.github/workflows/release.yml @@ -0,0 +1,56 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/development/continuous_integration.html + +name: release + +on: + pull_request_target: + branches: [master] + types: [closed] + + workflow_dispatch: # manual trigger + +jobs: + create: + if: github.event_name == 'workflow_dispatch' || + (startsWith(github.head_ref, 'pre-release-20') && github.event.pull_request.merged == true) + + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + fetch-depth: 0 + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: "3.x" + + - name: Install setuptools_scm + run: pip install 'setuptools_scm<7' + + - name: Show current version + run: python .ci-helpers/get_current_version.py + + - name: Get next version + run: | + python .ci-helpers/get_next_version.py + echo "NEW_TAG=$(python .ci-helpers/get_next_version.py)" >> $GITHUB_ENV + + - name: Create new release + uses: softprops/action-gh-release@v1 + with: + token: ${{ secrets.BOT_TOKEN }} + name: TARDIS v${{ env.NEW_TAG}} + tag_name: release-${{ env.NEW_TAG }} + prerelease: false + body: | + This release has been created automatically by the TARDIS continuous delivery pipeline. + + A complete list of changes for this release is available at [CHANGELOG.md](https://github.com/tardis-sn/tardis/blob/master/CHANGELOG.md). + files: | + conda-linux-64.lock + conda-osx-64.lock + conda-lock.yml + fail_on_unmatched_files: false diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml new file mode 100644 index 00000000000..515ddc294c7 --- /dev/null +++ b/.github/workflows/tests.yml @@ -0,0 +1,113 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/development/continuous_integration.html + +name: tests + +on: + push: + branches: + - '*' + + pull_request: + branches: + - '*' + + types: + - opened + - reopened + - synchronize + - labeled + +env: + CACHE_NUMBER: 0 # increase to reset cache manually + PYTEST_FLAGS: --tardis-refdata=${{ github.workspace }}/tardis-refdata --tardis-regression-data=${{ github.workspace }}/tardis-regression-data + --cov=tardis --cov-report=xml --cov-report=html + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + +concurrency: + group: ${{ github.workflow }}-${{ github.head_ref || github.ref }} + cancel-in-progress: true + +defaults: + run: + shell: bash -l {0} + +jobs: + build: + if: github.repository_owner == 'tardis-sn' + strategy: + matrix: + pip: [true, false] + label: [osx-64, linux-64] + include: + - label: osx-64 + os: macos-latest + prefix: /Users/runner/miniconda3/envs/tardis + + - label: linux-64 + os: ubuntu-latest + prefix: /usr/share/miniconda3/envs/tardis + + name: ${{ matrix.label }}-pip-${{ matrix.pip }} + runs-on: ${{ matrix.os }} + steps: + - uses: actions/checkout@v4 + + - name: Setup LFS + uses: ./.github/actions/setup_lfs + + - name: Download Lock File + run: wget -q https://raw.githubusercontent.com/tardis-sn/tardis/master/conda-${{ matrix.label }}.lock + if: matrix.pip == true + + - name: Generate Cache Key + run: | + file_hash=$(cat conda-${{ matrix.label }}.lock | shasum -a 256 | cut -d' ' -f1) + echo "file_hash=$file_hash" >> "${GITHUB_OUTPUT}" + id: cache-environment-key + + - uses: mamba-org/setup-micromamba@v1 + with: + environment-file: conda-${{ matrix.label }}.lock + cache-environment-key: ${{ steps.cache-environment-key.outputs.file_hash }} + cache-downloads-key: ${{ steps.cache-environment-key.outputs.file_hash }} + environment-name: tardis + cache-environment: true + cache-downloads: true + + - name: Install package editable + run: | + pip install -e . + echo "TARDIS_PIP_PATH=tardis" >> $GITHUB_ENV + if: matrix.pip == false + + - name: Install package git + run: pip install git+https://github.com/tardis-sn/tardis.git@${{ github.ref }} + if: matrix.pip == true + + - name: Set pip path + if: matrix.pip == true + run: | + location_line=$(pip show tardis | grep -i -x "Location:.*") + directory_path=$(echo $location_line | awk -F " " '{print $2}') + echo "TARDIS_PIP_PATH=$directory_path" >> $GITHUB_ENV + + - name: Set install path + if: matrix.pip == false + run: | + directory_path="." + echo "TARDIS_PIP_PATH=$directory_path" >> $GITHUB_ENV + + - name: Run tests + run: pytest tardis ${{ env.PYTEST_FLAGS }} + working-directory: ${{ env.TARDIS_PIP_PATH }} + if: always() + + - name: Upload to Codecov + run: bash <(curl -s https://codecov.io/bash) + + - name: Refdata Generation tests + run: pytest tardis ${{ env.PYTEST_FLAGS }} --generate-reference + working-directory: ${{ env.TARDIS_PIP_PATH }} + if: contains(github.event.pull_request.labels.*.name, 'run-generation-tests') || github.ref == 'refs/heads/master' diff --git a/.github/workflows/update-changelog.yml b/.github/workflows/update-changelog.yml deleted file mode 100644 index 3cc7ffc1565..00000000000 --- a/.github/workflows/update-changelog.yml +++ /dev/null @@ -1,39 +0,0 @@ -# For more information on how to use this template please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -name: changelog - -on: - push: - tags: - - 'release-*' - - workflow_dispatch: # Manual trigger - -jobs: - push: - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v2 - with: - repository: tardis-sn/tardis - token: ${{ secrets.BOT_TOKEN }} - fetch-depth: 0 - - - name: Install github-changes - run: sudo npm install -g github-changes - - - name: Update changelog - run: github-changes -o tardis-sn -r tardis --only-pulls --use-commit-body -f CHANGELOG.md -k ${{ secrets.GITHUB_TOKEN }} - - - name: Configure bot user - run: | - git config --global user.email "tardis.sn.bot@gmail.com" - git config --global user.name "tardis-bot" - - - name: Push changes - run: | - git add CHANGELOG.md - git commit -m "Post-release updates [auto]" - git push diff --git a/.github/workflows/update-refdata.yml b/.github/workflows/update-refdata.yml new file mode 100644 index 00000000000..467c2c300e6 --- /dev/null +++ b/.github/workflows/update-refdata.yml @@ -0,0 +1,150 @@ +# For more information about TARDIS pipelines, please refer to: +# +# https://tardis-sn.github.io/tardis/development/continuous_integration.html + +name: update-refdata + +on: + repository_dispatch: + types: [update-refdata-command] + +env: + PYTEST_FLAGS: --tardis-refdata=${{ github.workspace }}/tardis-refdata --tardis-regression-data=${{ github.workspace }}/tardis-regression-data --generate-reference + CACHE_NUMBER: 1 # increase to reset cache manually + +concurrency: + group: ${{ github.workflow }}-${{ github.head_ref || github.ref }} + cancel-in-progress: true + +defaults: + run: + shell: bash -l {0} + +jobs: + pr-open: + runs-on: ubuntu-latest + steps: + - name: Checkout pull/${{ github.event.client_payload.pull_request.number }} + uses: actions/checkout@v4 + with: + ref: ${{ github.event.client_payload.pull_request.head.sha }} + + - name: Setup LFS + uses: ./.github/actions/setup_lfs + + - name: Download Lock File + run: wget -q https://raw.githubusercontent.com/tardis-sn/tardis/master/conda-linux-64.lock + + - name: Generate Cache Key + run: | + file_hash=$(cat conda-linux-64.lock | shasum -a 256 | cut -d' ' -f1) + echo "file_hash=$file_hash" >> "${GITHUB_OUTPUT}" + id: cache-environment-key + + - uses: mamba-org/setup-micromamba@v1 + with: + environment-file: conda-linux-64.lock + cache-environment-key: ${{ steps.cache-environment-key.outputs.file_hash }} + cache-downloads-key: ${{ steps.cache-environment-key.outputs.file_hash }} + environment-name: tardis + cache-environment: true + cache-downloads: true + + - name: Install package + run: pip install -e . + + - name: Generate new reference data + run: pytest tardis ${{ env.PYTEST_FLAGS }} + + - name: Remove unwanted files + run: rm .lfs-assets-id + working-directory: tardis-refdata + + - name: Create pull request refdata + uses: peter-evans/create-pull-request@v4 + with: + path: tardis-refdata + token: ${{ secrets.BOT_TOKEN }} + committer: TARDIS Bot + author: TARDIS Bot + branch: pr-${{ github.event.client_payload.pull_request.number }} + base: master + push-to-fork: tardis-bot/tardis-refdata + commit-message: Automated update (tardis pr-${{ github.event.client_payload.pull_request.number }}) + title: Automated update (tardis pr-${{ github.event.client_payload.pull_request.number }}) + body: | + *\*beep\* \*bop\** + + Hi, human. + + These are the changes made by https://github.com/tardis-sn/tardis/pull/${{ github.event.client_payload.pull_request.number }}, please be careful before merging this pull request. + id: create-pr + + - name: Create pull request regression data + uses: peter-evans/create-pull-request@v4 + with: + path: tardis-regression-data + token: ${{ secrets.BOT_TOKEN }} + committer: TARDIS Bot + author: TARDIS Bot + branch: pr-${{ github.event.client_payload.pull_request.number }} + base: master + push-to-fork: tardis-bot/tardis-regression-data + commit-message: Automated update (tardis pr-${{ github.event.client_payload.pull_request.number }}) + title: Automated update (tardis pr-${{ github.event.client_payload.pull_request.number }}) + body: | + *\*beep\* \*bop\** + + Hi, human. + + These are the changes made by https://github.com/tardis-sn/tardis/pull/${{ github.event.client_payload.pull_request.number }}, please be careful before merging this pull request. + id: create-pr-regression + + - name: Find comment + uses: peter-evans/find-comment@v2 + id: fc + with: + issue-number: ${{ github.event.client_payload.pull_request.number }} + body-includes: Hi, human. + if: always() + + - name: Post comment (success) + uses: peter-evans/create-or-update-comment@v2 + with: + token: ${{ secrets.BOT_TOKEN }} + issue-number: ${{ github.event.client_payload.pull_request.number }} + comment-id: ${{ steps.fc.outputs.comment-id }} + edit-mode: replace + body: | + *\*beep\* \*bop\** + + Hi, human. + + The **`${{ github.workflow }}`** workflow has **succeeded** :heavy_check_mark: + + [**Click here**](${{ env.REFDATA_URL }}) to see pull request for refdata update. + [**Click here**](${{ env.REGDATA_URL }}) to see pull request for regression data update. + env: + REFDATA_URL: https://github.com/tardis-sn/tardis-refdata/pulls + REGDATA_URL: https://github.com/tardis-sn/tardis-regression-data/pulls + + if: success() + + - name: Post comment (failure) + uses: peter-evans/create-or-update-comment@v2 + with: + token: ${{ secrets.BOT_TOKEN }} + issue-number: ${{ github.event.client_payload.pull_request.number }} + comment-id: ${{ steps.fc.outputs.comment-id }} + edit-mode: replace + body: | + *\*beep\* \*bop\** + + Hi, human. + + The **`${{ github.workflow }}`** workflow has **failed** :x: + + [**Click here**](${{ env.URL }}) to see the build log. + env: + URL: https://github.com/${{ github.repository_owner }}/${{ github.event.repository.name }}/actions/runs/${{ github.run_id }}?check_suite_focus=true + if: failure() diff --git a/.github/workflows/update-zenodo-json.yml b/.github/workflows/update-zenodo-json.yml deleted file mode 100644 index 8c0cce2d1c1..00000000000 --- a/.github/workflows/update-zenodo-json.yml +++ /dev/null @@ -1,88 +0,0 @@ -# For more information on how to use this template please refer to: -# http://tardis-sn.github.io/tardis/development/continuous_integration.html - -name: zenodo - -on: - schedule: - - cron: '40 23 * * 0' - - workflow_dispatch: # Manual trigger - -jobs: - build: - runs-on: ubuntu-latest - if: ${{ github.repository_owner == 'tardis-sn' }} # Do not run scheduled jobs on forks - - steps: - - uses: actions/checkout@v2 - with: - repository: tardis-sn/tardis_zenodo - token: ${{ secrets.BOT_TOKEN }} - - - name: Dump Secret Key - run: echo "$KEY_SECRET_JSON" > key_secret.json - env: - KEY_SECRET_JSON: ${{ secrets.ZENODO_KEY_SECRET_JSON }} - - - name: Setup Python - uses: actions/setup-python@v2 - with: - python-version: 3.6 - - - name: Install Packages - run: pip install pandas==1.0.5 jupyter==1.0.0 jupyter-client==6.1.2 nbconvert==5.3.1 tornado==4.2 orcid - - - name: Run Notebook - run: jupyter nbconvert gather_data.ipynb --to html --execute --ExecutePreprocessor.timeout=6000 - - - name: Run Notebook (allow errors) - run: jupyter nbconvert gather_data.ipynb --to html --execute --ExecutePreprocessor.timeout=6000 --allow-errors - if: ${{ failure() }} - - - uses: actions/upload-artifact@v2 - with: - name: zenodo_json - path: .zenodo.json - - - uses: actions/upload-artifact@v2 - with: - name: notebook - path: gather_data.html - if: ${{ always() }} - - push: - runs-on: ubuntu-latest - needs: build - steps: - - uses: actions/checkout@v2 - with: - repository: tardis-sn/tardis - token: ${{ secrets.BOT_TOKEN }} - fetch-depth: 0 - - - uses: actions/download-artifact@v2 - with: - name: zenodo_json - - - name: Configure Bot User - run: | - git config --global user.email "tardis.sn.bot@gmail.com" - git config --global user.name "tardis-bot" - - - name: Debug step - run: ls -a - - - name: Push Changes - run: | - git add -f .zenodo.json - - if git diff --staged --quiet; then - echo "No changes made. Exiting." - exit 0 - - else - git commit -m "Update zenodo.json [auto] [skip ci]" - git push - - fi diff --git a/.gitignore b/.gitignore index e06afd9f6e6..4f02f9da6f8 100644 --- a/.gitignore +++ b/.gitignore @@ -5,6 +5,7 @@ *.so __pycache__ + # Ignore .c files by default to avoid including generated code. If you want to # add a non-generated .c extension, use `git add -f filename.c`. *.c @@ -14,16 +15,20 @@ __pycache__ */cython_version.py htmlcov .coverage +coverage.xml MANIFEST .ipynb_checkpoints # Sphinx docs/api docs/_build -docs/resources/ZENODO.rst docs/tutorials.rst docs/io/configuration/components/models/converters/density_parse.csv docs/io/configuration/components/models/converters/abund_parse.csv +docs/io/output/plasma_graph_default.tex +docs/io/output/plasma_graph_scaled.tex +docs/io/output/plasma_graph_no_eq.tex +docs/io/output/plasma_graph_with_args.tex # Eclipse editor project files .project @@ -67,3 +72,17 @@ pip-wheel-metadata/ # Mac OSX .DS_Store + +# Visual Studio Code +*.code-workspace + +# Random files +.hypothesis/unicode_data/11.0.0/charmap.json.gz + +# Data files +benchmarks/data/*.h5 + +# ASV +.asv/ +pkgs/ +release_hashes.txt diff --git a/.mailmap b/.mailmap index ccc114e9b46..3339ecaa8c1 100644 --- a/.mailmap +++ b/.mailmap @@ -1,12 +1,18 @@ +AbhinavOhri +Abhishek Patidar <1e9abhi1e10@gmail.com> Adam Suban-Loewen Alexander Holas +Alexander Holas Alexander Holas AlexHls <70367168+AlexHls@users.noreply.github.com> Alexander Holas AlexHls +Alexander Holas <70367168+AlexHls@users.noreply.github.com> Alice Harpole Alice Harpole Alice Harpole +Aman Kumar + Andreas Flörs Andreas Flörs Andreas Flörs <33418619+afloers@users.noreply.github.com> Andreas Flörs Andreas Flörs @@ -17,14 +23,19 @@ Andrew Fullard Andrew Fullard Aoife Boyle Aoife Boyle aoifeboyle +Aoife Boyle Arib Alam Arib Alam aribalam +Arjun Savel Arjun Savel Arjun Savel Arjun Savel Arjun Savel +Arjun Savel Arjun Savel <35353555+arjunsavel@users.noreply.github.com> Atharva Arya +Atharva Arya Atharva Arya +Atharva Arya atharva-2001 Atharva Arya Atharva Arya <55894364+atharva-2001@users.noreply.github.com> Atharwa Kharkar @@ -32,10 +43,14 @@ Atharwa Kharkar atharwa_24 +Anirban Dutta + Barnabás Barna Caroline Sofiatti +Cecelia Powers + Chaitanya Kolliboyina <61906444+chaitanya-kolliboyina@users.noreply.github.com> Chinmay Talegaonkar @@ -54,6 +69,9 @@ Dhruv Sondhi DhruvSondhi Epson Heringer Epson Heringer Heringer-Epson +Erin Visser +Erin Visser erinvisser + Ezequiel Pássaro Frederik Beaujean @@ -63,7 +81,10 @@ Frederik Beaujean Frederik Beaujean Gaurav Gautam gautam1168 -Isaac Smith +Gerrit Leck +Gerrit Leck Gerrit Leck + +Isaac Smith Isaac Smith Isaac Smith <71480393+smithis7@users.noreply.github.com> Isaac Smith smithis7 <71480393+smithis7@users.noreply.github.com> Isaac Smith smithis7 @@ -76,12 +97,23 @@ James Gillanders James Gillanders jamesgillanders <47385282+jamesgillanders@users.noreply.github.com> James Gillanders James Gillanders James Gillanders James Gillanders +James Gillanders + +Jayant Bhakar + +Jenny Yu +Jenny Yu yuyizh +Jenny Yu Jenny Yu <80535029+yuyizheng1112@users.noreply.github.com> + +Jing Lu John Reichenbach <56849859+jreichenbach-msu@users.noreply.github.com> Jordi Eguren Jordi Eguren jordi5 <45364266+jordi5@users.noreply.github.com> +Josh Shields + Karan Desai Karan Desai karandesai-96 @@ -89,17 +121,22 @@ Kaushik Varanasi Kaushik Varanasi kaushik94 Kevin Cawley -Kevin Cawley KevinCawley <72036796+KevinCawley@users.noreply.github.com> +Kevin Cawley KevinCawley Kevin Cawley KevinCawley +Kevin Cawley KevinCawley <72036796+KevinCawley@users.noreply.github.com> Kevin Yap +Kim Lingemann kimsina +Kim Lingemann kim + Laud Bentil -Laud Bentil Laud Bentil +Laud Bentil Laud Bentil Marc Williamson -Marc Williamson Marc Williamson Marc Williamson Marc Williamson +Marc Williamson Marc Williamson +Marc Williamson Marc Williamson Mark Magee <53613663+MarkMageeAstro@users.noreply.github.com> @@ -111,6 +148,7 @@ Maryam Patel maryam patel Maryam Patel maryampatel Matthew Bartnik +Matthew Bartnik bartnikm <72052791+bartnikm@users.noreply.github.com> Michael Klauser Michael Klauser Michael.Klauser @@ -122,12 +160,19 @@ Mikhail Mishin Morgan Sandler Morgan Sandler Morgan +Musabbiha Zaheer +Musabbiha Zaheer musabbihaz <78879726+musabbihaz@users.noreply.github.com> + Nance Sarafina <31808841+sarafina325@users.noreply.github.com> Nathan Kowalski <56104113+kowal180@users.noreply.github.com> Nilesh Patra <37436956+nileshpatra@users.noreply.github.com> +Nolan Brown + +Nutan Chen + Pratik Patel Pratik Patel Pratik151 @@ -138,9 +183,18 @@ Ran Livneh Ran Livneh Sampark Sharma Shilpi Prasad +Shilpi Prasad Shilpi <72646134+shilpiprd@users.noreply.github.com> + +Shreyas Singh +Shreyas Singh shreyas3156 + +Satwik Kambham +Satwik Kambham code-explorer Sourav Singh +Sona Chitchyan + Srinath Rajagopalan Srinath Rajagopalan Srinath Rajagopalan Srinath R @@ -156,6 +210,12 @@ Stuart Sim ssim Stuart Sim Stuart Sim Stuart Sim Stuart Sim +TARDIS Bot +TARDIS Bot tardis-bot +TARDIS Bot TARDIS Bot +TARDIS Bot TARDIS Bot <60989672+tardis-bot@users.noreply.github.com> +TARDIS Bot Azure Pipelines + Tomas Bylund Tomas Bylund Tobychev @@ -182,3 +242,40 @@ Wolfgang Kerzendorf Wolfgang Kerzendorf Youssef Eweis Youssef Eweis + +Yuki Matsumura + +Rohith Varma Buddaraju +Rohith Varma Buddaraju rohithvarma3000 +Rohith Varma Buddaraju Rohith + +Le Truong + +Ayushi Daksh +Ayushi Daksh AyushiDaksh +Ayushi Daksh AyushiDaksh +Ayushi Daksh AyushiDaksh <37770155+AyushiDaksh@users.noreply.github.com> +Ayushi Daksh Ayushi Daksh +Ayushi Daksh Ayushi Daksh <37770155+AyushiDaksh@users.noreply.github.com> +Ayushi Daksh Ayushi + +Ansh Kumar <1928013@kiit.ac.in> +Ansh Kumar <1928013@kiit.ac.in> xansh <1928013@kiit.ac.in> +Ansh Kumar <1928013@kiit.ac.in> Ansh Kumar <1928013@kiit.ac.in> + +Sarthak Srivastava +Sarthak Srivastava sarthak-dv +Sarthak Srivastava Sarthak Srivastava + +Kim Lingemann kimsina +Kim Lingemann kim + +Sumit Gupta + +Gudur Krishna Chaitanya +Gudur Krishna Chaitanya KC210404 +Gudur Krishna Chaitanya KC210404 + +Israel Roldan Israel Roldan +Israel Roldan AirvZxf +Israel Roldan airv_zxf diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000000..249191508d3 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,15 @@ +repos: + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.5.0 + hooks: + - id: trailing-whitespace + - id: end-of-file-fixer + - id: check-yaml + - repo: https://github.com/astral-sh/ruff-pre-commit + rev: v0.1.14 + hooks: + - id: ruff + - repo: https://github.com/PyCQA/isort + rev: 5.13.2 + hooks: + - id: isort diff --git a/.ruff.toml b/.ruff.toml new file mode 100644 index 00000000000..b599ce8106b --- /dev/null +++ b/.ruff.toml @@ -0,0 +1,219 @@ +# Ruff configuration file adapted from astropy +extend = "pyproject.toml" +lint.ignore = [ + # NOTE: to find a good code to fix, run: + # ruff --select="ALL" --statistics astropy/ + + # flake8-annotations (ANN) : static typing + "ANN001", # Function argument without type annotation + "ANN003", # `**kwargs` without type annotation + "ANN201", # Public function without return type annotation + "ANN202", # Private function without return type annotation + "ANN401", # Use of `Any` type + + # flake8-unused-arguments (ARG) + "ARG001", # unused-function-argument + "ARG002", # unused-method-argument + "ARG003", # unused-class-method-argument + "ARG004", # unused-static-method-argument + "ARG005", # unused-lambda-argument + + # flake8-bugbear (B) + "B006", # MutableArgumentDefault + "B007", # UnusedLoopControlVariable + "B023", # FunctionUsesLoopVariable + "B028", # No-explicit-stacklevel + "B904", # RaiseWithoutFromInsideExcept + "B905", # ZipWithoutExplicitStrict # requires 3.10+ + + # flake8-blind-except (BLE) + "BLE001", # blind-except + + # mccabe (C90) : code complexity + # TODO: configure maximum allowed complexity. + "C901", # McCabeComplexity + + # pydocstyle (D) + # Missing Docstrings + "D100", # undocumented-public-module + "D101", # undocumented-public-class + "D103", # undocumented-public-function + "D104", # undocumented-public-package + "D205", # blank-line-after-summary + # Quotes Issues + "D300", # triple-single-quotes + "D301", # escape-sequence-in-docstring + # Docstring Content Issues + "D403", # first-line-capitalized + "D404", # docstring-starts-with-this + "D401", # non-imperative-mood. + "D414", # empty-docstring-section + "D419", # docstring is empty + + # flake8-datetimez (DTZ) + "DTZ001", # call-datetime-without-tzinfo + "DTZ005", # call-datetime-now-without-tzinfo + + # pycodestyle (E, W) + "E501", # line-too-long + "E721", # type-comparison + "E731", # lambda-assignment + + # flake8-errmsg (EM) : nicer error tracebacks + "EM101", # raw-string-in-exception + "EM102", # f-string-in-exception + "EM103", # dot-format-in-exception + + # eradicate (ERA) + # NOTE: be careful that developer notes are kept. + "ERA001", # commented-out-code + + # flake8-executable (EXE) + "EXE002", # shebang-missing-executable-file + + # Pyflakes (F) + "F841", # unused-variable + + # flake8-boolean-trap (FBT) : boolean flags should be kwargs, not args + # NOTE: a good thing to fix, but changes API. + "FBT001", # boolean-positional-arg-in-function-definition + "FBT002", # boolean-default-value-in-function-definition + "FBT003", # boolean-positional-value-in-function-call + + # flake8-fixme (FIX) + "FIX001", # Line contains FIXME. this should be fixed or at least FIXME replaced with TODO + "FIX004", # Line contains HACK. replace HACK with NOTE. + + # pep8-naming (N) + # NOTE: some of these can/should be fixed, but this changes the API. + "N801", # invalid-class-name + "N802", # invalid-function-name + "N803", # invalid-argument-name + "N804", # invalid-first-argument-name-for-class-method + "N805", # invalid-first-argument-name-for-method + "N807", # dunder-function-name + "N813", # camelcase-imported-as-lowercase + "N815", # mixed-case-variable-in-class-scope + "N816", # mixed-case-variable-in-global-scope + "N818", # error-suffix-on-exception-name + + # NumPy-specific rules (NPY) + "NPY002", # Replace legacy `np.random.rand` call with `np.random.Generator` (2023-05-03) + + # Perflint (PERF) + "PERF203", # `try`-`except` within a loop incurs performance overhead + "PERF401", # Use a list comprehension to create a transformed list + + # Pylint (PLC, PLE, PLR, PLW) + "PLE0101", # return-in-init + "PLR0124", # Name compared with itself + "PLR0402", # ConsiderUsingFromImport + "PLR0912", # too-many-branches + "PLR0913", # too-many-args + "PLR0915", # too-many-statements + "PLR1714", # Consider merging multiple comparisons + "PLR2004", # MagicValueComparison + "PLR5501", # collapsible-else-if + "PLW0603", # global-statement + "PLW2901", # redefined-loop-name + + # flake8-pytest-style (PT) + "PT001", # pytest-fixture-incorrect-parentheses-style + "PT003", # pytest-extraneous-scope-function + "PT004", # pytest-missing-fixture-name-underscore + "PT006", # pytest-parametrize-names-wrong-type + "PT007", # pytest-parametrize-values-wrong-type + "PT011", # pytest-raises-too-broad + "PT012", # pytest-raises-with-multiple-statements + "PT017", # pytest-assert-in-exceptinstead + "PT018", # pytest-composite-assertion + "PT022", # pytest-useless-yield-fixture + "PT023", # pytest-incorrect-mark-parentheses-style + + # flake8-use-pathlib (PTH) + "PTH100", # os-path-abspath + "PTH101", # os-chmod + "PTH102", # os-mkdir + "PTH103", # os-makedirs + "PTH104", # os-rename + "PTH107", # os-remove + "PTH108", # os-unlink + "PTH109", # os-getcwd + "PTH110", # os-path-exists + "PTH111", # os-path-expanduser + "PTH112", # os-path-isdir + "PTH113", # os-path-isfile + "PTH118", # os-path-join + "PTH119", # os-path-basename + "PTH120", # os-path-dirname + "PTH122", # os-path-splitext + "PTH123", # builtin-open + "PTH202", # `os.path.getsize` should be replaced by `Path.stat().st_size` + "PTH207", # Replace `glob` with `Path.glob` or `Path.rglob` + + # flake8-return (RET) + "RET501", # unnecessary-return-none + "RET502", # implicit-return-value + "RET503", # implicit-return + "RET504", # unnecessary-assign + "RET507", # superfluous-else-continue + + # flake8-raise (RSE) + "RSE102", # unnecessary-paren-on-raise-exception + + # Ruff-specific rules (RUF) + "RUF001", # ambiguous-unicode-character-string + "RUF002", # ambiguous-unicode-character-docstring + "RUF010", # use conversion in f-string + "RUF012", # Mutable class attributes should be annotated with `typing.ClassVar` + + # flake8-bandit (S) + "S101", # Use of `assert` detected + "S105", # hardcoded-password-string + "S110", # try-except-pass + "S112", # try-except-continue + "S301", # suspicious-pickle-usage + "S307", # Use of possibly insecure function; consider using `ast.literal_eval` + "S311", # suspicious-non-cryptographic-randomness + "S324", # hashlib-insecure-hash-function + "S506", # UnsafeYAMLLoad + "S310", # Suspicious-url-open-usage + "S603", # `subprocess` call: check for execution of untrusted input + "S607", # Starting a process with a partial executable path + + # flake8-simplify (SIM) + "SIM102", # NestedIfStatements + "SIM105", # UseContextlibSuppress + "SIM108", # UseTernaryOperator + "SIM114", # if-with-same-arms + "SIM115", # OpenFileWithContextHandler + "SIM117", # MultipleWithStatements + "SIM118", # KeyInDict + "SIM201", # NegateEqualOp + "SIM300", # yoda condition + + # flake8-print (T20) + "T201", # PrintUsed + + # flake8-todos (TD) + "TD001", # Invalid TODO tag + "TD003", # Missing issue link on the line following this TODO + "TD004", # Missing colon in TODO + "TD007", # Missing space after colon in TODO + + # tryceratops (TRY) + "TRY002", # raise-vanilla-class + "TRY003", # raise-vanilla-args + "TRY004", # prefer-type-error + "TRY201", # verbose-raise + "TRY301", # raise-within-try + + # flake8-quotes (Q) + "Q000", # use double quotes +] +lint.unfixable = [ + "E711" # NoneComparison. Hard to fix b/c numpy has it's own None. +] + +[lint.extend-per-file-ignores] +"docs/*" = [] diff --git a/.zenodo.json b/.zenodo.json index 044367da45a..c809d7ce3fb 100644 --- a/.zenodo.json +++ b/.zenodo.json @@ -27,11 +27,12 @@ { "name": "Fl\u00f6rs, Andreas", "orcid": "0000-0003-2024-2819", - "affiliation": "Max-Planck-Institut f\u00fcr Astrophysik" + "affiliation": "GSI Helmholtz Centre for Heavy Ion Research" }, { "name": "Camacho, Yssa", - "orcid": "0000-0002-9830-3880" + "orcid": "0000-0002-9830-3880", + "affiliation": "Rutgers The State University of New Jersey" }, { "name": "Jan\u010dauskas, Vytautas", @@ -98,56 +99,77 @@ "orcid": "0000-0001-7343-1678", "affiliation": "Michigan State University" }, + { + "name": "Arya, Atharva" + }, + { + "name": "Smith, Isaac" + }, { "name": "Cawley, Kevin" }, { "name": "Singhal, Jaladh", - "orcid": "0000-0002-8310-0829", - "affiliation": "Python Software Foundation (StarKit)" + "orcid": "0000-0002-8310-0829" }, { - "name": "Smith, Isaac" + "name": "Shields, Joshua" }, { - "name": "Barbosa, Talytha" + "name": "O'Brien, Jack" }, { "name": "Sondhi, Dhruv" }, + { + "name": "Barbosa, Talytha" + }, + { + "name": "Yu, Jenny" + }, { "name": "Patel, Maryam" }, + { + "name": "Rathi, Shikha" + }, { "name": "Varanasi, Kaushik" }, { - "name": "Gillanders, James", - "orcid": "0000-0002-8094-6108" + "name": "Chitchyan, Sona" }, { - "name": "Arya, Atharva" + "name": "Gillanders, James", + "orcid": "0000-0002-8094-6108", + "affiliation": "University of Oxford" }, { - "name": "O'Brien, Jack" + "name": "Singh, Shreyas" }, { - "name": "Eweis, Youssef" + "name": "Savel, Arjun" }, { "name": "Reinecke, Martin" }, + { + "name": "Holas, Alexander" + }, + { + "name": "Eweis, Youssef" + }, { "name": "Bylund, Tomas" }, { - "name": "Bentil, Laud" + "name": "Black, William" }, { - "name": "Savel, Arjun" + "name": "Bentil, Laud" }, { - "name": "Yu, Jenny" + "name": "Kumar, Ansh" }, { "name": "Eguren, Jordi", @@ -156,48 +178,114 @@ { "name": "Alam, Arib" }, + { + "name": "Bartnik, Matthew" + }, + { + "name": "Varma Buddaraju, Rohith" + }, + { + "name": "Gupta, Sumit" + }, { "name": "Magee, Mark" }, { "name": "Livneh, Ran" }, + { + "name": "Daksh, Ayushi" + }, + { + "name": "Kambham, Satwik" + }, + { + "name": "Dutta, Anirban" + }, + { + "name": "Visser, Erin" + }, { "name": "Rajagopalan, Srinath" }, + { + "name": "Lu, Jing" + }, { "name": "Mishra, Sashank", "orcid": "0000-0001-8302-1584" }, { - "name": "Reichenbach, John" + "name": "Roldan, Israel" }, { "name": "Jain, Rinkle" }, + { + "name": "Reichenbach, John" + }, + { + "name": "Bhakar, Jayant" + }, + { + "name": "Actions, GitHub" + }, { "name": "Floers, Andreas" }, + { + "name": "Singh, Sourav" + }, + { + "name": "Chaumal, Aarya" + }, { "name": "Brar, Antreev" }, { - "name": "Singh, Sourav" + "name": "Srivastava, Sarthak" }, { - "name": "Talegaonkar, Chinmay" + "name": "Gupta, Harshul" + }, + { + "name": "Patidar, Abhishek" + }, + { + "name": "Matsumura, Yuki" }, { "name": "Kowalski, Nathan" }, + { + "name": "Kumar, Aman" + }, { "name": "Selsing, Jonatan" }, + { + "name": "Talegaonkar, Chinmay" + }, { "name": "Sofiatti, Caroline" }, { - "name": "Aggarwal, Yash" + "name": "Venkat, Shashank" + }, + { + "name": "Buchner, Johannes" + }, + { + "name": "Yap, Kevin" + }, + { + "name": "Truong, Le" + }, + { + "name": "Sandler, Morgan" + }, + { + "name": "Zaheer, Musabbiha" }, { "name": "Sarafina, Nance" @@ -206,7 +294,10 @@ "name": "Patra, Nilesh" }, { - "name": "Singh Rathore, Parikshit" + "name": "Dasgupta, Debajyoti" + }, + { + "name": "Chen, Nutan" }, { "name": "Patel, Pratik" @@ -214,32 +305,41 @@ { "name": "Sharma, Sampark" }, + { + "name": "Volodin, Dmitry" + }, + { + "name": "Prasad, Shilpi" + }, { "name": "Gupta, Suyash" }, + { + "name": "Lemoine, Thom" + }, { "name": "Wahi, Ujjwal" }, { - "name": "Sandler, Morgan" + "name": "Aggarwal, Yash" }, { - "name": "Volodin, Dmitry" + "name": "Singh Rathore, Parikshit" }, { - "name": "Dasgupta, Debajyoti" + "name": "Kolliboyina, Chaitanya" }, { - "name": "Yap, Kevin" + "name": "PATIDAR, ABHISHEK" }, { - "name": "Kharkar, Atharwa" + "name": "Martinez, Laureano" }, { "name": "Nayak U, Ashwin" }, { - "name": "Kolliboyina, Chaitanya" + "name": "Kharkar, Atharwa" }, { "name": "Kumar, Atul" diff --git a/CHANGELOG.md b/CHANGELOG.md index b089142901b..adfbf0fa264 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,35 +1,394 @@ ## Change Log -### release-2021.10.31 (2021/10/27 19:00 +00:00) +### release-2023.08.13 (2023/08/13 21:04 +00:00) +- [#2391](https://github.com/tardis-sn/tardis/pull/2391) Pre-release 2023.08.13 (#2391) (@tardis-bot) +- [#2379](https://github.com/tardis-sn/tardis/pull/2379) Tests for doppler factor functions (#2379) (@sonachitchyan) +- [#2348](https://github.com/tardis-sn/tardis/pull/2348) Fixes gamma-ray notebook to run more easily (#2348) (@andrewfullard) +- [#2381](https://github.com/tardis-sn/tardis/pull/2381) Removed hardcoding of RPacket radius (#2381) (@xansh) +- [#2384](https://github.com/tardis-sn/tardis/pull/2384) Post-release 2023.08.06 (#2384) (@tardis-bot) + +### release-2023.08.06 (2023/08/06 00:43 +00:00) +- [#2383](https://github.com/tardis-sn/tardis/pull/2383) Pre-release 2023.08.06 (#2383) (@tardis-bot) +- [#2382](https://github.com/tardis-sn/tardis/pull/2382) Remove outdated docstring from test_montecarlo.py (#2382) (@chvogl) +- [#2376](https://github.com/tardis-sn/tardis/pull/2376) Add init.py to energy input module (#2376) (@andrewfullard) +- [#2373](https://github.com/tardis-sn/tardis/pull/2373) Post-release 2023.07.30 (#2373) (@tardis-bot) + +### release-2023.07.30 (2023/07/30 00:47 +00:00) +- [#2372](https://github.com/tardis-sn/tardis/pull/2372) Pre-release 2023.07.30 (#2372) (@tardis-bot) +- [#2365](https://github.com/tardis-sn/tardis/pull/2365) integrate radiation field (#2365) (@wkerzendorf) +- [#2371](https://github.com/tardis-sn/tardis/pull/2371) Prevent empty convergence plot Error when n_iteration=1 (#2371) (@DeerWhale) +- [#2369](https://github.com/tardis-sn/tardis/pull/2369) Post-release 2023.07.23 (#2369) (@tardis-bot) + +### release-2023.07.23 (2023/07/23 14:47 +00:00) +- [#2368](https://github.com/tardis-sn/tardis/pull/2368) Pre-release 2023.07.23 (#2368) (@tardis-bot) +- [#2367](https://github.com/tardis-sn/tardis/pull/2367) integrate new packetsource (#2367) (@wkerzendorf) +- [#2366](https://github.com/tardis-sn/tardis/pull/2366) New packet source (extending 2352) (#2366) (@wkerzendorf) +- [#2354](https://github.com/tardis-sn/tardis/pull/2354) removed duplicate entry of afloers (#2354) (@afloers) +- [#2360](https://github.com/tardis-sn/tardis/pull/2360) restructure configuration object (#2360) (@wkerzendorf) +- [#2361](https://github.com/tardis-sn/tardis/pull/2361) add deprecated decorator (#2361) (@wkerzendorf) +- [#2359](https://github.com/tardis-sn/tardis/pull/2359) Rename NumbaPlasma to OpacityState (#2359) (@andrewfullard) +- [#2313](https://github.com/tardis-sn/tardis/pull/2313) Grotrian Diagram Plot Appearance (#2313) (@AyushiDaksh) +- [#2357](https://github.com/tardis-sn/tardis/pull/2357) Post-release 2023.07.16 (#2357) (@tardis-bot) + +### release-2023.07.16 (2023/07/16 19:15 +00:00) +- [#2356](https://github.com/tardis-sn/tardis/pull/2356) Pre-release 2023.07.16 (#2356) (@tardis-bot) +- [#2355](https://github.com/tardis-sn/tardis/pull/2355) Fixed spelling mistake in Wien's displacement law (#2355) (@afloers) +- [#2351](https://github.com/tardis-sn/tardis/pull/2351) Post-release 2023.07.09 (#2351) (@tardis-bot) + +### release-2023.07.09 (2023/07/09 16:30 +00:00) +- [#2350](https://github.com/tardis-sn/tardis/pull/2350) Pre-release 2023.07.09 (#2350) (@tardis-bot) +- [#2347](https://github.com/tardis-sn/tardis/pull/2347) Fix frame transformations of continuum opacity (#2347) (@chvogl) +- [#2139](https://github.com/tardis-sn/tardis/pull/2139) Gamma ray refactor (#2139) (@andrewfullard) +- [#2327](https://github.com/tardis-sn/tardis/pull/2327) Refactor Model Reader on the Stella example (#2327) (@wkerzendorf) +- [#2346](https://github.com/tardis-sn/tardis/pull/2346) Post-release 2023.07.02 (#2346) (@tardis-bot) + +### release-2023.07.02 (2023/07/02 00:49 +00:00) +- [#2345](https://github.com/tardis-sn/tardis/pull/2345) Pre-release 2023.07.02 (#2345) (@tardis-bot) +- [#2344](https://github.com/tardis-sn/tardis/pull/2344) Make MontecarloTransport and montecarlo_numba track the last line interaction shell ids for real and virtual packets (#2344) (@AyushiDaksh) +- [#2343](https://github.com/tardis-sn/tardis/pull/2343) Rename RPacketTracker.interact_id to RPacketTracker.num_interactions (#2343) (@AyushiDaksh) +- [#2221](https://github.com/tardis-sn/tardis/pull/2221) Fix typos in repository (#2221) (@AyushiDaksh) +- [#2330](https://github.com/tardis-sn/tardis/pull/2330) Benchmarks Push To Repo Bug Fix (#2330) (@atharva-2001) +- [#2335](https://github.com/tardis-sn/tardis/pull/2335) Dispatch Compare Refdata Event to Refdata Repo (#2335) (@atharva-2001) +- [#2305](https://github.com/tardis-sn/tardis/pull/2305) Fix to helium indexing in NLTE (#2305) (@aoifeboyle) +- [#2341](https://github.com/tardis-sn/tardis/pull/2341) Remove duplicated continuum interaction code (#2341) (@chvogl) +- [#2340](https://github.com/tardis-sn/tardis/pull/2340) Post-release 2023.06.25 (#2340) (@tardis-bot) + +### release-2023.06.25 (2023/06/25 16:43 +00:00) +- [#2339](https://github.com/tardis-sn/tardis/pull/2339) Pre-release 2023.06.25 (#2339) (@tardis-bot) +- [#2337](https://github.com/tardis-sn/tardis/pull/2337) Seperate the last iteration from Simulation.run() (#2337) (@xansh) +- [#2219](https://github.com/tardis-sn/tardis/pull/2219) Remove dead (unused) fixtures (#2219) (@xansh) +- [#2336](https://github.com/tardis-sn/tardis/pull/2336) Fix doc failure after restructuring packet source seed (#2336) (@xansh) +- [#2329](https://github.com/tardis-sn/tardis/pull/2329) Move packet seeds logic into PacketSource instead of MontecarloTransport (#2329) (@xansh) +- [#2326](https://github.com/tardis-sn/tardis/pull/2326) Track bf and ff opacities with vpackets (#2326) (@ymatsumu) +- [#2334](https://github.com/tardis-sn/tardis/pull/2334) Post-release 2023.06.18 (#2334) (@tardis-bot) + +### release-2023.06.18 (2023/06/18 00:48 +00:00) +- [#2333](https://github.com/tardis-sn/tardis/pull/2333) Pre-release 2023.06.18 (#2333) (@tardis-bot) +- [#2311](https://github.com/tardis-sn/tardis/pull/2311) Make nthreads a property of MontecarloRunner instead of Simulation class (#2311) (@xansh) +- [#2260](https://github.com/tardis-sn/tardis/pull/2260) [WIP] Basic Benchmarks Using ASV (#2260) (@atharva-2001) +- [#2317](https://github.com/tardis-sn/tardis/pull/2317) Rename MontecarloRunner to MontecarloTransport (#2317) (@xansh) +- [#2307](https://github.com/tardis-sn/tardis/pull/2307) Post-release 2023.06.04 (#2307) (@tardis-bot) + +### release-2023.06.04 (2023/06/04 00:53 +00:00) +- [#2306](https://github.com/tardis-sn/tardis/pull/2306) Pre-release 2023.06.04 (#2306) (@tardis-bot) +- [#2302](https://github.com/tardis-sn/tardis/pull/2302) Disable HDF5 file locking on documentation workflow (#2302) (@epassaro) +- [#2300](https://github.com/tardis-sn/tardis/pull/2300) Post-release 2023.05.28 (#2300) (@tardis-bot) + +### release-2023.05.28 (2023/05/28 00:51 +00:00) +- [#2299](https://github.com/tardis-sn/tardis/pull/2299) Pre-release 2023.05.28 (#2299) (@tardis-bot) +- [#2298](https://github.com/tardis-sn/tardis/pull/2298) Bump hdf5 to v1.12 (#2298) (@epassaro) +- [#2297](https://github.com/tardis-sn/tardis/pull/2297) Post-release 2023.05.21 (#2297) (@tardis-bot) + +### release-2023.05.21 (2023/05/21 00:53 +00:00) +- [#2296](https://github.com/tardis-sn/tardis/pull/2296) Pre-release 2023.05.21 (#2296) (@tardis-bot) +- [#2295](https://github.com/tardis-sn/tardis/pull/2295) Post-release 2023.05.15 (#2295) (@tardis-bot) + +### release-2023.05.15 (2023/05/15 14:10 +00:00) +- [#2294](https://github.com/tardis-sn/tardis/pull/2294) Pre-release 2023.05.14 (#2294) (@tardis-bot) +- [#2290](https://github.com/tardis-sn/tardis/pull/2290) Post-release 2023.05.07 (#2290) (@tardis-bot) + +### release-2023.05.07 (2023/05/07 17:47 +00:00) +- [#2289](https://github.com/tardis-sn/tardis/pull/2289) Pre-release 2023.05.07 (#2289) (@tardis-bot) +- [#2201](https://github.com/tardis-sn/tardis/pull/2201) Changing construction of the first guess and coefficient matrices in NLTE solver (#2201) (@sonachitchyan) +- [#2287](https://github.com/tardis-sn/tardis/pull/2287) Post-release 2023.04.30 (#2287) (@tardis-bot) + +### release-2023.04.30 (2023/04/30 17:26 +00:00) +- [#2286](https://github.com/tardis-sn/tardis/pull/2286) Pre-release 2023.04.30 (#2286) (@tardis-bot) +- [#2284](https://github.com/tardis-sn/tardis/pull/2284) Save LFS Objects `always()` (#2284) (@atharva-2001) +- [#2280](https://github.com/tardis-sn/tardis/pull/2280) Prevent tests from running on forks (#2280) (@atharva-2001) +- [#2283](https://github.com/tardis-sn/tardis/pull/2283) Post-release 2023.04.23 (#2283) (@tardis-bot) + +### release-2023.04.23 (2023/04/23 00:49 +00:00) +- [#2282](https://github.com/tardis-sn/tardis/pull/2282) Pre-release 2023.04.23 (#2282) (@tardis-bot) +- [#2121](https://github.com/tardis-sn/tardis/pull/2121) adding nonhomologous_grid.py (#2121) (@sonachitchyan) +- [#2278](https://github.com/tardis-sn/tardis/pull/2278) Post-release 2023.04.16 (#2278) (@tardis-bot) + +### release-2023.04.16 (2023/04/16 00:47 +00:00) +- [#2277](https://github.com/tardis-sn/tardis/pull/2277) Pre-release 2023.04.16 (#2277) (@tardis-bot) +- [#2267](https://github.com/tardis-sn/tardis/pull/2267) Check MD5 sums of downloaded atom data (#2267) (@epassaro) +- [#2273](https://github.com/tardis-sn/tardis/pull/2273) Fixes for update reference data workflow (#2273) (@epassaro) +- [#2275](https://github.com/tardis-sn/tardis/pull/2275) Post-release 2023.04.09 (#2275) (@tardis-bot) + +### release-2023.04.09 (2023/04/09 00:44 +00:00) +- [#2274](https://github.com/tardis-sn/tardis/pull/2274) Pre-release 2023.04.09 (#2274) (@tardis-bot) +- [#2249](https://github.com/tardis-sn/tardis/pull/2249) Port update reference data pipeline to GitHub Actions (#2249) (@epassaro) +- [#2233](https://github.com/tardis-sn/tardis/pull/2233) Added documentation for parallel fixes for estimators (#2233) (@1e9abhi1e10) +- [#2250](https://github.com/tardis-sn/tardis/pull/2250) Arepo mass average fix (#2250) (@AlexHls) +- [#2257](https://github.com/tardis-sn/tardis/pull/2257) Post-release 2023.03.26 (#2257) (@tardis-bot) + +### release-2023.03.26 (2023/03/26 05:55 +00:00) +- [#2256](https://github.com/tardis-sn/tardis/pull/2256) Pre-release 2023.03.26 (#2256) (@tardis-bot) +- [#2248](https://github.com/tardis-sn/tardis/pull/2248) Post-release 2023.03.20 (#2248) (@tardis-bot) + +### release-2023.03.20 (2023/03/20 16:39 +00:00) +- [#2247](https://github.com/tardis-sn/tardis/pull/2247) Pre-release 2023.03.20 (#2247) (@tardis-bot) +- [#2246](https://github.com/tardis-sn/tardis/pull/2246) Fix team reviewers on workflows (#2246) (@epassaro) +- [#2237](https://github.com/tardis-sn/tardis/pull/2237) MonteCarlo packet progress bar completes to 100% (#2237) (@shreyas3156) +- [#2243](https://github.com/tardis-sn/tardis/pull/2243) Fix for release dates (#2243) (@epassaro) +- [#2242](https://github.com/tardis-sn/tardis/pull/2242) Fix for automerge (#2242) (@epassaro) +- [#2236](https://github.com/tardis-sn/tardis/pull/2236) Docs Fix: Download Atom Data in rpacket_tracking.ipynb (#2236) (@atharva-2001) +- [#2204](https://github.com/tardis-sn/tardis/pull/2204) Add docstrings to subpackages (#2204) (@PommesFrittes) +- [#2223](https://github.com/tardis-sn/tardis/pull/2223) Post-release 2023.02.27 (#2223) (@tardis-bot) + +### release-2023.02.27 (2023/02/27 13:53 +00:00) +- [#2222](https://github.com/tardis-sn/tardis/pull/2222) Pre-release 2023.02.26 (#2222) (@tardis-bot) +- [#2214](https://github.com/tardis-sn/tardis/pull/2214) Correct the description of 'no_of_packets' in Monte Carlo Configuration (#2214) (@1e9abhi1e10) +- [#2213](https://github.com/tardis-sn/tardis/pull/2213) Post-release 2023.02.20 (#2213) (@tardis-bot) +- [#2194](https://github.com/tardis-sn/tardis/pull/2194) Cache LFS objects in the tests workflow (#2194) (@atharva-2001) + +### release-2023.02.2 (2023/02/20 15:04 +00:00) +- [#2211](https://github.com/tardis-sn/tardis/pull/2211) Pre-release 2023.02.19 (#2211) (@tardis-bot) +- [#2210](https://github.com/tardis-sn/tardis/pull/2210) Post-release 2023.02.16 (#2210) (@tardis-bot) + +### release-2023.02.16 (2023/02/16 14:18 +00:00) +- [#2208](https://github.com/tardis-sn/tardis/pull/2208) Pre-release 2023.02.12 (#2208) (@tardis-bot) +- [#2190](https://github.com/tardis-sn/tardis/pull/2190) Add version tag to simulation objects (#2190) (@kimsina) +- [#2206](https://github.com/tardis-sn/tardis/pull/2206) Post-release 2023.02.06 (#2206) (@tardis-bot) + +### release-2023.02.06 (2023/02/06 15:00 +00:00) +- [#2205](https://github.com/tardis-sn/tardis/pull/2205) Pre-release 2023.02.05 (#2205) (@tardis-bot) +- [#2200](https://github.com/tardis-sn/tardis/pull/2200) Fix config reader tests (#2200) (@chvogl) +- [#2195](https://github.com/tardis-sn/tardis/pull/2195) Reading nlte_excitation_species from config (#2195) (@sonachitchyan) +- [#2198](https://github.com/tardis-sn/tardis/pull/2198) Fixing test_store_runner_to_hdf (#2198) (@sonachitchyan) +- [#2185](https://github.com/tardis-sn/tardis/pull/2185) Rename T variables to temperature (#2185) (@1e9abhi1e10) +- [#2171](https://github.com/tardis-sn/tardis/pull/2171) Adding nlte solver (#2171) (@sonachitchyan) +- [#2187](https://github.com/tardis-sn/tardis/pull/2187) Downloading nlte_atom_data in ref data (#2187) (@sonachitchyan) +- [#2188](https://github.com/tardis-sn/tardis/pull/2188) Post-release 2023.01.11 (#2188) (@tardis-bot) + +### release-2023.01.11 (2023/01/11 16:25 +00:00) +- [#2186](https://github.com/tardis-sn/tardis/pull/2186) Pre-release 2023.01.08 (#2186) (@tardis-bot) +- [#2182](https://github.com/tardis-sn/tardis/pull/2182) Post-release 2022.12.26 (#2182) (@tardis-bot) + +### release-2022.12.26 (2022/12/26 14:51 +00:00) +- [#2180](https://github.com/tardis-sn/tardis/pull/2180) Pre-release 2022.12.25 (#2180) (@tardis-bot) +- [#2170](https://github.com/tardis-sn/tardis/pull/2170) Add missing __init__.py files to transport and geometry subpackages (#2170) (@epassaro) +- [#2173](https://github.com/tardis-sn/tardis/pull/2173) Post-release 2022.12.12 (#2173) (@tardis-bot) + +### release-2022.12.12 (2022/12/12 15:02 +00:00) +- [#2172](https://github.com/tardis-sn/tardis/pull/2172) Pre-release 2022.12.11 (#2172) (@tardis-bot) +- [#2150](https://github.com/tardis-sn/tardis/pull/2150) Kilonova missing zeta (#2150) (@gleck97) +- [#2158](https://github.com/tardis-sn/tardis/pull/2158) NLTE jacobian matrix (#2158) (@sonachitchyan) +- [#2154](https://github.com/tardis-sn/tardis/pull/2154) Fixing typos for nlte ion (#2154) (@sonachitchyan) +- [#2159](https://github.com/tardis-sn/tardis/pull/2159) Fix relativistic packet initialization (#2159) (@chvogl) + +### release-2022.11.21 (2022/11/21 15:15 +00:00) +- [#2160](https://github.com/tardis-sn/tardis/pull/2160) Pre-release 2022.11.20 (#2160) (@tardis-bot) +- [#2156](https://github.com/tardis-sn/tardis/pull/2156) Post-release 2022.11.17 (#2156) (@tardis-bot) + +### release-2022.11.17 (2022/11/17 18:45 +00:00) +- [#2155](https://github.com/tardis-sn/tardis/pull/2155) Pre-release 2022.11.17 (#2155) (@tardis-bot) +- [#2152](https://github.com/tardis-sn/tardis/pull/2152) Set specific qgrid feedstock version (#2152) (@andrewfullard) +- [#2140](https://github.com/tardis-sn/tardis/pull/2140) Adding nlte_rate_equation_solver.py (#2140) (@sonachitchyan) +- [#2147](https://github.com/tardis-sn/tardis/pull/2147) Pin setuptools_scm to v6 (#2147) (@epassaro) +- [#2127](https://github.com/tardis-sn/tardis/pull/2127) Possible fix for prerelease workflow (#2127) (@andrewfullard) +- [#2146](https://github.com/tardis-sn/tardis/pull/2146) Add missing cell to download atom data (#2146) (@epassaro) +- [#2136](https://github.com/tardis-sn/tardis/pull/2136) Restructuring NumbaModel (#2136) (@satwik-kambham) +- [#2132](https://github.com/tardis-sn/tardis/pull/2132) Adding rate matrix index (#2132) (@sonachitchyan) +- [#2130](https://github.com/tardis-sn/tardis/pull/2130) moved helium nlte to a seperate file `helium_nlte.py` (#2130) (@sonachitchyan) +- [#2124](https://github.com/tardis-sn/tardis/pull/2124) Cleaning model state (#2124) (@satwik-kambham) +- [#2096](https://github.com/tardis-sn/tardis/pull/2096) Small bug fix for He NLTE. (#2096) (aoife-boyle) +- [#1923](https://github.com/tardis-sn/tardis/pull/1923) Fixing latex_label Parameter within write_to_tex function (#1923) (@bartnikm) +- [#2095](https://github.com/tardis-sn/tardis/pull/2095) Removing outdated documentation and creating developer tools section (#2095) (@smithis7) +- [#2099](https://github.com/tardis-sn/tardis/pull/2099) Arbitrary isotope decay handling and positronium (#2099) (@andrewfullard) +- [#2118](https://github.com/tardis-sn/tardis/pull/2118) Integrating experimental model state (#2118) (@satwik-kambham) +- [#2120](https://github.com/tardis-sn/tardis/pull/2120) Update arepo docs notebook to be pre-run (#2120) (@AlexHls) +- [#2115](https://github.com/tardis-sn/tardis/pull/2115) added docs for montecarlo packet visualization (#2115) (@jayantbhakar) +- [#2117](https://github.com/tardis-sn/tardis/pull/2117) Runs cells in arepo notebook to avoid downloading files (#2117) (@andrewfullard) +- [#2103](https://github.com/tardis-sn/tardis/pull/2103) New geometry class (#2103) (@satwik-kambham) +- [#2111](https://github.com/tardis-sn/tardis/pull/2111) New TARDIS flowchart and cleaning up physics walkthrough (#2111) (@smithis7) +- [#2098](https://github.com/tardis-sn/tardis/pull/2098) New Composition Class (#2098) (@satwik-kambham) +- [#2108](https://github.com/tardis-sn/tardis/pull/2108) Rework Estimators and Convergence Docs (#2108) (@smithis7) +- [#2105](https://github.com/tardis-sn/tardis/pull/2105) Documentation for Features In-Progress (#2105) (@smithis7) +- [#2107](https://github.com/tardis-sn/tardis/pull/2107) Added positronium notes (#2107) (@andrewfullard) +- [#2091](https://github.com/tardis-sn/tardis/pull/2091) Added interaction type in rpacket_tracker (#2091) (@jayantbhakar) +- [#2110](https://github.com/tardis-sn/tardis/pull/2110) removed scatter function from interaction.py (#2110) (@sonachitchyan) +- [#2106](https://github.com/tardis-sn/tardis/pull/2106) Resturcture ABCs import from collections module (#2106) (@rohithvarma3000) +- [#2093](https://github.com/tardis-sn/tardis/pull/2093) Fixing Docs Warnings (#2093) (@smithis7) +- [#2073](https://github.com/tardis-sn/tardis/pull/2073) rpacket_tracker returns dataframe (#2073) (@jayantbhakar) +- [#2104](https://github.com/tardis-sn/tardis/pull/2104) Re-produced PR 1826 (#2104) (@andrewfullard) +- [#2097](https://github.com/tardis-sn/tardis/pull/2097) Creating new docs building instructions (#2097) (@smithis7) +- [#2088](https://github.com/tardis-sn/tardis/pull/2088) Arepo docs fix (#2088) (@AlexHls) +- [#1941](https://github.com/tardis-sn/tardis/pull/1941) Improved arepo parser (#1941) (@AlexHls) +- [#2026](https://github.com/tardis-sn/tardis/pull/2026) Adding physics introduction to documentation (#2026) (@smithis7) +- [#2084](https://github.com/tardis-sn/tardis/pull/2084) Fix broken links in workflow files and goverance md (#2084) (@rohithvarma3000) +- [#2083](https://github.com/tardis-sn/tardis/pull/2083) Moved `trace_packet` to tardis tansport (#2083) (@Rodot-) +- [#2082](https://github.com/tardis-sn/tardis/pull/2082) Added documetation on how to compare environment before update (#2082) (@jaladh-singhal) +- [#2076](https://github.com/tardis-sn/tardis/pull/2076) Modified Function Name in Config validator according to PEP8 (#2076) (@rohithvarma3000) +- [#2062](https://github.com/tardis-sn/tardis/pull/2062) Remove yaml_load_config_file (#2062) (@aman1971) +- [#2052](https://github.com/tardis-sn/tardis/pull/2052) Created a smart HDF Reader which can re-produce simulation object (#2052) (@satwik-kambham) +- [#2070](https://github.com/tardis-sn/tardis/pull/2070) Pre-release 2022.06.26 (#2070) (@tardis-bot) +- [#2069](https://github.com/tardis-sn/tardis/pull/2069) Wait for pull request creation (#2069) (@epassaro) +- [#2067](https://github.com/tardis-sn/tardis/pull/2067) Begin geometry subfolder (#2067) (@nolanbrown01) +- [#2050](https://github.com/tardis-sn/tardis/pull/2050) Update Jsonschema package to V4 (#2050) (@rohithvarma3000) +- [#2065](https://github.com/tardis-sn/tardis/pull/2065) Continuing geometry restructure (#2065) (@nolanbrown01) +- [#2063](https://github.com/tardis-sn/tardis/pull/2063) Initial geometry restructure (#2063) (@nolanbrown01) +- [#2061](https://github.com/tardis-sn/tardis/pull/2061) Post-release 2022.06.19 (#2061) (@tardis-bot) + +### release-2022.06.19 (2022/06/19 02:25 +00:00) +- [#2060](https://github.com/tardis-sn/tardis/pull/2060) Pre-release 2022.06.19 (#2060) (@tardis-bot) +- [#2036](https://github.com/tardis-sn/tardis/pull/2036) Restructure code to remove the single_packet_seed field (#2036) (@rohithvarma3000) +- [#2054](https://github.com/tardis-sn/tardis/pull/2054) Auto-merge fixes (#2054) (@epassaro) +- [#2053](https://github.com/tardis-sn/tardis/pull/2053) Change developer installation command (#2053) (@epassaro) +- [#2048](https://github.com/tardis-sn/tardis/pull/2048) Disable profiling page build on pull requests (#2048) (@epassaro) +- [#2042](https://github.com/tardis-sn/tardis/pull/2042) Polish up Quickstart guide (#2042) (@epassaro) +- [#2010](https://github.com/tardis-sn/tardis/pull/2010) Enable automerge on pre and post-release workflows (#2010) (@epassaro) +- [#2046](https://github.com/tardis-sn/tardis/pull/2046) Stop redirecting docs page (#2046) (@epassaro) +- [#2045](https://github.com/tardis-sn/tardis/pull/2045) Add DOI badge to credits section (#2045) (@epassaro) +- [#2047](https://github.com/tardis-sn/tardis/pull/2047) Ignore gamma-ray deposition notebook for now (#2047) (@andrewfullard) +- [#1698](https://github.com/tardis-sn/tardis/pull/1698) Gamma ray propagation (#1698) (@andrewfullard) +- [#2044](https://github.com/tardis-sn/tardis/pull/2044) Post-release 2022.06.05 (#2044) (@tardis-bot) + +### release-2022.06.05 (2022/06/05 01:07 +00:00) +- [#2043](https://github.com/tardis-sn/tardis/pull/2043) Pre-release 2022.06.05 (#2043) (@tardis-bot) +- [#2039](https://github.com/tardis-sn/tardis/pull/2039) Check PEP8 on CI (#2039) (@epassaro) +- [#2037](https://github.com/tardis-sn/tardis/pull/2037) Update README.rst in post-release (#2037) (@epassaro) +- [#2024](https://github.com/tardis-sn/tardis/pull/2024) Added v_inner and v_outer, enable_nonhomologous_expansion for future use in nonhomologous expansion (#2024) (@sonachitchyan) +- [#2038](https://github.com/tardis-sn/tardis/pull/2038) Fix bot aliases in .mailmap (#2038) (@epassaro) +- [#2027](https://github.com/tardis-sn/tardis/pull/2027) Replace docstr-coverage with interrogate (#2027) (@epassaro) +- [#2020](https://github.com/tardis-sn/tardis/pull/2020) Fixes for CITATION.cff (#2020) (@epassaro) +- [#2033](https://github.com/tardis-sn/tardis/pull/2033) Merge all CI users on mailmap (#2033) (@epassaro) +- [#2028](https://github.com/tardis-sn/tardis/pull/2028) Rebuild installation page (#2028) (@epassaro) +- [#1921](https://github.com/tardis-sn/tardis/pull/1921) Formal integral documentation (#1921) (@smithis7) +- [#2030](https://github.com/tardis-sn/tardis/pull/2030) Fix estimators parallel (#2030) (@Rodot-) +- [#2019](https://github.com/tardis-sn/tardis/pull/2019) Added compatability to current version of carsus atomic data (#2019) (@Rodot-) +- [#2011](https://github.com/tardis-sn/tardis/pull/2011) Build and cache conda environments with lockfiles (#2011) (@epassaro) +- [#1991](https://github.com/tardis-sn/tardis/pull/1991) Re-write `download_from_url` using Astropy's `download_file` (#1991) (@epassaro) +- [#1992](https://github.com/tardis-sn/tardis/pull/1992) Fix low temperature problem of Van Regemorter approximation (#1992) (@chvogl) +- [#2018](https://github.com/tardis-sn/tardis/pull/2018) Automated changes for post-release 2022.05.08 (#2018) (@tardis-bot) + +### release-2022.05.08 (2022/05/08 00:27 +00:00) +- [#2016](https://github.com/tardis-sn/tardis/pull/2016) Automated changes for pre-release 2022.05.08 (#2016) (@tardis-bot) +- [#1996](https://github.com/tardis-sn/tardis/pull/1996) Fixes for compare-refdata pipeline (#1996) (@epassaro) +- [#2012](https://github.com/tardis-sn/tardis/pull/2012) Supply `base` input to the create pull request action (#2012) (@epassaro) +- [#2007](https://github.com/tardis-sn/tardis/pull/2007) [fix] Use `pull_request_target` trigger in release workflow (#2007) (@epassaro) +- [#2008](https://github.com/tardis-sn/tardis/pull/2008) Move link_t_rad_t_electron to config file (@sonachitchyan) +- [#1957](https://github.com/tardis-sn/tardis/pull/1957) Revert "Removing Levels Index Variable Within Atomic Data Preperation (#1957)" (#2009) (@Rodot-) +- [#2006](https://github.com/tardis-sn/tardis/pull/2006) Automated changes for post-release 2022.05.04 (#2006) (@tardis-bot) + +### release-2022.05.04 (2022/05/04 16:35 +00:00) +- [#2005](https://github.com/tardis-sn/tardis/pull/2005) Automated changes for pre-release 2022.05.04 (#2005) (@tardis-bot) +- [#2003](https://github.com/tardis-sn/tardis/pull/2003) Fix for isotope abundance parsing (#2003) (@Rodot-) +- [#1995](https://github.com/tardis-sn/tardis/pull/1995) Force constant version date length (#1995) (@epassaro) +- [#1999](https://github.com/tardis-sn/tardis/pull/1999) Create TARDIS release workflow (#1999) (@epassaro) +- [#2001](https://github.com/tardis-sn/tardis/pull/2001) Post-release workflow (#2001) (@epassaro) +- [#2000](https://github.com/tardis-sn/tardis/pull/2000) Update build-docs.yml (#2000) (@smithis7) +- [#1998](https://github.com/tardis-sn/tardis/pull/1998) Fix concurrency groups in workflows (#1998) (@epassaro) +- [#1987](https://github.com/tardis-sn/tardis/pull/1987) Better documentation build workflow from 2021 GA Hackathon (#1987) (@epassaro) +- [#1989](https://github.com/tardis-sn/tardis/pull/1989) Pre-release workflow (#1989) (@epassaro) +- [#1988](https://github.com/tardis-sn/tardis/pull/1988) Use Azure mirror for reference data in testing pipeline (#1988) (@epassaro) +- [#1978](https://github.com/tardis-sn/tardis/pull/1978) Plasma number densities using isotopes (#1978) (@andrewfullard) +- [#1985](https://github.com/tardis-sn/tardis/pull/1985) Migrate testing pipeline to GitHub Actions (#1985) (@epassaro) +- [#1981](https://github.com/tardis-sn/tardis/pull/1981) Better docstring coverage workflow from 2021 GA Hackathon (#1981) (@epassaro) +- [#1980](https://github.com/tardis-sn/tardis/pull/1980) Check Black format on `master` branch (#1980) (@epassaro) +- [#1982](https://github.com/tardis-sn/tardis/pull/1982) Add bot comment with directions to update .mailmap (#1982) (@epassaro) +- [#1973](https://github.com/tardis-sn/tardis/pull/1973) deploy environment with spec file; add aliases to mailmap (#1973) (@epassaro) +- [#1983](https://github.com/tardis-sn/tardis/pull/1983) Remove files already superseded by templates (#1983) (@epassaro) +- [#1977](https://github.com/tardis-sn/tardis/pull/1977) Ignore more Black commits (#1977) (@epassaro) +- [#1971](https://github.com/tardis-sn/tardis/pull/1971) Blackify TARDIS again (#1971) (@epassaro) +- [#1974](https://github.com/tardis-sn/tardis/pull/1974) Add disclaimer to environment file regarding conda-forge recipe (#1974) (@epassaro) +- [#1970](https://github.com/tardis-sn/tardis/pull/1970) Remove pull request bot comment workflow (#1970) (@epassaro) +- [#1969](https://github.com/tardis-sn/tardis/pull/1969) Fix docs build after upgrading conda environment (#1969) (@wkerzendorf) + +### release-2022.4.24 (2022/04/22 00:19 +00:00) +- [#1933](https://github.com/tardis-sn/tardis/pull/1933) Intensity p rays (#1933) (@Rodot-) +- [#1948](https://github.com/tardis-sn/tardis/pull/1948) Update TARDIS environment after replacing PyNE (#1948) (@epassaro) +- [#1957](https://github.com/tardis-sn/tardis/pull/1957) Removing Levels Index Variable Within Atomic Data Preperation (#1957) (@bartnikm) +- [#1968](https://github.com/tardis-sn/tardis/pull/1968) fixed index type in Saha solver documentation (#1968) (@afloers) +- [#1959](https://github.com/tardis-sn/tardis/pull/1959) disable mamba on azure pipelines (#1959) (@epassaro) +- [#1967](https://github.com/tardis-sn/tardis/pull/1967) Logging/csvy parsers errors (#1967) (@wkerzendorf) +- [#1813](https://github.com/tardis-sn/tardis/pull/1813) Replacing PyNE with radioactivedecay for radionuclide decay calculations (#1813) (@lemointm) + +### release-2022.4.1 (2022/04/07 14:38 +00:00) +- [#1925](https://github.com/tardis-sn/tardis/pull/1925) Plasma Graph Tutorial (#1925) (@bartnikm) + +### release-2022.4.3 (2022/03/28 14:30 +00:00) +- [#1899](https://github.com/tardis-sn/tardis/pull/1899) Filtering Levels Parameter within Plasma Calculations (#1899) (@bartnikm) +- [#1920](https://github.com/tardis-sn/tardis/pull/1920) Estimators and Convergence Documentation (#1920) (@smithis7) +- [#1938](https://github.com/tardis-sn/tardis/pull/1938) Pin Jinja version (#1938) (@smithis7) + +### release-2022.3.27 (2022/03/23 15:51 +00:00) +- [#1928](https://github.com/tardis-sn/tardis/pull/1928) Fixing various physics documentation issues (#1928) (@smithis7) + +### release-2022.3.2 (2022/03/14 15:16 +00:00) +- [#1898](https://github.com/tardis-sn/tardis/pull/1898) making changes to estimators (#1898) (@smithis7) + +### release-2022.3.13 (2022/03/10 15:35 +00:00) +- [#1922](https://github.com/tardis-sn/tardis/pull/1922) Fixing documentation links and misc. API documentation fixes (#1922) (@smithis7) + +### release-2022.3.6 (2022/03/03 19:21 +00:00) +- [#1919](https://github.com/tardis-sn/tardis/pull/1919) GPU Options (#1919) (@KevinCawley) +- [#1918](https://github.com/tardis-sn/tardis/pull/1918) Fix documentation build failure due to PR #1823 (#1918) (@atharva-2001) +- [#1917](https://github.com/tardis-sn/tardis/pull/1917) Continuum Opacities (#1917) (@Rodot-) +- [#1823](https://github.com/tardis-sn/tardis/pull/1823) Disable Convergence Plots by default (#1823) (@atharva-2001) +- [#1914](https://github.com/tardis-sn/tardis/pull/1914) add continuum tracer (#1914) (@wkerzendorf) + +### release-2022.2.27 (2022/02/24 21:00 +00:00) +- [#1886](https://github.com/tardis-sn/tardis/pull/1886) Continuum branch [attempted merge with master] (#1886) (@wkerzendorf) +- [#1907](https://github.com/tardis-sn/tardis/pull/1907) Add note on GPU selection to formal integral (#1907) (@KevinCawley) +- [#1710](https://github.com/tardis-sn/tardis/pull/1710) Changed Formatting for the logger based on Log Level (#1710) (@DhruvSondhi) +- [#1901](https://github.com/tardis-sn/tardis/pull/1901) Fix PyTest fixtures and updated mainloop to properly compile (#1901) (@Rodot-) +- [#1900](https://github.com/tardis-sn/tardis/pull/1900) Make update-refdata pipeline open a PR instead of merging changes (#1900) (@epassaro) + +### release-2022.2.2 (2022/02/17 20:14 +00:00) +- [#1837](https://github.com/tardis-sn/tardis/pull/1837) CUDA Version of the Formal Integral (#1837) (@KevinCawley) +- [#1891](https://github.com/tardis-sn/tardis/pull/1891) Fixing Broken Latex Code (#1891) (@bartnikm) +- [#1868](https://github.com/tardis-sn/tardis/pull/1868) Fixing Plasma Graph to Allow .dot and .tex file Generation (#1868) (@bartnikm) +- [#1893](https://github.com/tardis-sn/tardis/pull/1893) Fixing small docs issues (#1893) (@smithis7) + +### release-2022.2.6 (2022/02/02 17:16 +00:00) +- [#1888](https://github.com/tardis-sn/tardis/pull/1888) Pin Black (#1888) (@atharva-2001) +- [#1881](https://github.com/tardis-sn/tardis/pull/1881) Changed to append `seed` & `index` values only once for a particular `RPacketTracker` instance (#1881) (@DhruvSondhi) +- [#1877](https://github.com/tardis-sn/tardis/pull/1877) printing packet information (#1877) (@wkerzendorf) +- [#1867](https://github.com/tardis-sn/tardis/pull/1867) Arepo parser (#1867) (@AlexHls) +- [#1843](https://github.com/tardis-sn/tardis/pull/1843) Changed default Log level to INFO (#1843) (@DhruvSondhi) +- [#1849](https://github.com/tardis-sn/tardis/pull/1849) Interactive docs for models (#1849) (@smithis7) +- [#1876](https://github.com/tardis-sn/tardis/pull/1876) fixed pytest tardis command in documentation (#1876) (@afloers) +- [#1874](https://github.com/tardis-sn/tardis/pull/1874) move transport related parts to r_packet_transport (#1874) (@wkerzendorf) +- [#1872](https://github.com/tardis-sn/tardis/pull/1872) Fix links in the code of conduct (#1872) (@smithis7) +- [#1847](https://github.com/tardis-sn/tardis/pull/1847) Add a ModelState class (#1847) (@atharva-2001) + +### release-2022.1.23 (2022/01/21 16:50 +00:00) +- [#1865](https://github.com/tardis-sn/tardis/pull/1865) fixing links (#1865) (@smithis7) +- [#1866](https://github.com/tardis-sn/tardis/pull/1866) Refactor `test_configuration_namespace.py` (#1866) (@atharva-2001) +- [#1861](https://github.com/tardis-sn/tardis/pull/1861) Renamed `RPacketCollection` Class to `RPacketTracker` (#1861) (@DhruvSondhi) + +### release-2022.1.16 (2022/01/12 15:11 +00:00) +- [#1827](https://github.com/tardis-sn/tardis/pull/1827) Adding Explanations to Spectrum Configuration (#1827) (@bartnikm) +- [#1752](https://github.com/tardis-sn/tardis/pull/1752) Add tests to SDEC plotter module (#1752) (@jaladh-singhal) +- [#1848](https://github.com/tardis-sn/tardis/pull/1848) Switching progress bars page to rst (#1848) (@smithis7) + +### release-2022.1.9 (2022/01/06 15:59 +00:00) +- [#1846](https://github.com/tardis-sn/tardis/pull/1846) Fix Virtual Packet Logging Bug (#1846) (@atharva-2001) +- [#1834](https://github.com/tardis-sn/tardis/pull/1834) Adding Luminosity Integral Explanation to Supernova Configuration (#1834) (@bartnikm) +- [#1842](https://github.com/tardis-sn/tardis/pull/1842) Fixed fstring issue from mixing quotes and reformatted files from fstring PR with black (#1842) (@Rodot-) +- [#1841](https://github.com/tardis-sn/tardis/pull/1841) Fixed the Failing Documentation for Tracking `RPacket` Feature (#1841) (@DhruvSondhi) +- [#1835](https://github.com/tardis-sn/tardis/pull/1835) Reorganizing docs for website release (#1835) (@smithis7) +- [#1748](https://github.com/tardis-sn/tardis/pull/1748) Tracking RPacket Properties in Montecarlo Single Packet Loop Function (#1748) (@DhruvSondhi) +- [#1706](https://github.com/tardis-sn/tardis/pull/1706) Changed to fstring (#1706) (@svenkat19) +- [#1833](https://github.com/tardis-sn/tardis/pull/1833) Editing instructions for contributing to the documentation (#1833) (@smithis7) +- [#1832](https://github.com/tardis-sn/tardis/pull/1832) Convert quantities to arrays when plotting in SDEC plot (#1832) (@atharva-2001) +- [#1830](https://github.com/tardis-sn/tardis/pull/1830) Name plotly traces in SDEC plot (#1830) (@atharva-2001) +- [#1825](https://github.com/tardis-sn/tardis/pull/1825) changed all files to import constants from only tardis (#1825) (@shilpiprd) +- [#1799](https://github.com/tardis-sn/tardis/pull/1799) Bug fixes and Improvements in Custom Abundance Widget (#1799) (@yuyizheng1112) +- [#1803](https://github.com/tardis-sn/tardis/pull/1803) Option to make docs build in parallel (#1803) (@smithis7) +- [#1817](https://github.com/tardis-sn/tardis/pull/1817) Fixing SDEC docs page (#1817) (@smithis7) - [#1821](https://github.com/tardis-sn/tardis/pull/1821) remove numexpr (#1821) (@wkerzendorf) - [#1788](https://github.com/tardis-sn/tardis/pull/1788) Add cmap option to specify the colormap of abundance plot (#1788) (@yuyizheng1112) - [#1801](https://github.com/tardis-sn/tardis/pull/1801) Cleaning up docs build (#1801) (@smithis7) - [#1808](https://github.com/tardis-sn/tardis/pull/1808) Fix importing scipy.sparse.linalg for binder (#1808) (@smithis7) - [#1816](https://github.com/tardis-sn/tardis/pull/1816) fix push job on update changelog workflow (#1816) (@epassaro) - -### release-2021.10.17 (2021/10/14 15:37 +00:00) - [#1811](https://github.com/tardis-sn/tardis/pull/1811) Fixing broken documentation build (#1811) (@smithis7) - [#1744](https://github.com/tardis-sn/tardis/pull/1744) Basic Spectrum Generation Interactive Documentation (#1744) (@smithis7) - [#1810](https://github.com/tardis-sn/tardis/pull/1810) Add option to add Observed Spectrum (2) (#1810) (@atharva-2001) - -### release-2021.10.1 (2021/10/06 13:38 +00:00) - [#1806](https://github.com/tardis-sn/tardis/pull/1806) Pin `jsonschema` to v3 (#1806) (@atharva-2001) - [#1761](https://github.com/tardis-sn/tardis/pull/1761) Revert "Add option to add Observed Spectrum (#1761)" (#1805) (@jamesgillanders) - [#1761](https://github.com/tardis-sn/tardis/pull/1761) Add option to add Observed Spectrum (#1761) (@atharva-2001) - [#1794](https://github.com/tardis-sn/tardis/pull/1794) Change virtual spectrum spawn range start value to 1 (#1794) (@atharva-2001) - -### release-2021.9.26 (2021/09/24 21:20 +00:00) - [#1757](https://github.com/tardis-sn/tardis/pull/1757) Auto-Generating Tutorials Page (#1757) (@smithis7) - -### release-2021.9.19 (2021/09/17 14:41 +00:00) - [#1784](https://github.com/tardis-sn/tardis/pull/1784) Restructure Custom Abundance Widget code (#1784) (@yuyizheng1112) - [#1763](https://github.com/tardis-sn/tardis/pull/1763) Making Changes to Several Tutorials (#1763) (@smithis7) - -### release-2021.9.12 (2021/09/09 11:18 +00:00) - [#1790](https://github.com/tardis-sn/tardis/pull/1790) disable changelog in release pipeline (#1790) (@epassaro) - [#1769](https://github.com/tardis-sn/tardis/pull/1769) Changed the way `specific_log_level` flag works in the Logging Configuration (#1769) (@DhruvSondhi) - -### release-2021.8.26 (2021/08/26 16:40 +00:00) - [#1789](https://github.com/tardis-sn/tardis/pull/1789) add explicit jupyter dependency (#1789) (@epassaro) - [#1787](https://github.com/tardis-sn/tardis/pull/1787) fix zenodo pipeline env (#1787) (@epassaro) - [#1786](https://github.com/tardis-sn/tardis/pull/1786) fix for release task (#1786) (@epassaro) @@ -37,22 +396,14 @@ - [#1775](https://github.com/tardis-sn/tardis/pull/1775) orchestrating continuous delivery pipeline (#1775) (@epassaro) - [#1778](https://github.com/tardis-sn/tardis/pull/1778) Fix hoverdata in plasma plots (#1778) (@atharva-2001) - [#1693](https://github.com/tardis-sn/tardis/pull/1693) Enabling virtual_packet_logging by default in the visualization folder (#1693) (@atharva-2001) - -### release-2021.8.15.0 (2021/08/12 14:24 +00:00) - [#1770](https://github.com/tardis-sn/tardis/pull/1770) Rename cplots to convergence_plots (#1770) (@atharva-2001) - [#1772](https://github.com/tardis-sn/tardis/pull/1772) Reverse legend in Plasma Convergence Plots (#1772) (@atharva-2001) - -### release-2021.8.8.0 (2021/08/05 18:49 +00:00) - [#1768](https://github.com/tardis-sn/tardis/pull/1768) Renamed `specific` log flag to `specific_log_level` (#1768) (@DhruvSondhi) - [#1721](https://github.com/tardis-sn/tardis/pull/1721) Restructure Model Configuration Documentation (#1721) (@smithis7) - -### release-2021.8.1.0 (2021/07/29 18:57 +00:00) - [#1753](https://github.com/tardis-sn/tardis/pull/1753) Adding Convergence Plots to the Documentation (#1753) (@atharva-2001) - [#1738](https://github.com/tardis-sn/tardis/pull/1738) TARDIS Grid (#1738) (@marxwillia) - [#1755](https://github.com/tardis-sn/tardis/pull/1755) changing note format (#1755) (@smithis7) - [#1740](https://github.com/tardis-sn/tardis/pull/1740) Renamed `montecarlo_logger.py` to `montecarlo_tracking.py` (#1740) (@DhruvSondhi) - -### release-2021.7.25.0 (2021/07/23 16:16 +00:00) - [#1697](https://github.com/tardis-sn/tardis/pull/1697) Interact Button in Documentation (#1697) (@smithis7) - [#1636](https://github.com/tardis-sn/tardis/pull/1636) Adding Convergence Plots (#1636) (@atharva-2001) - [#1723](https://github.com/tardis-sn/tardis/pull/1723) Edit docstring in `run_tardis` (#1723) (@atharva-2001) @@ -63,38 +414,24 @@ - [#1737](https://github.com/tardis-sn/tardis/pull/1737) Add Jaladh to mailmap (#1737) (@jaladh-singhal) - [#1739](https://github.com/tardis-sn/tardis/pull/1739) Fixed IPython Displaying the Plasma Stratification (Table) even when the Logger is turned Off (#1739) (@DhruvSondhi) - [#1742](https://github.com/tardis-sn/tardis/pull/1742) Reduce damping_constant under t_inner for tardis_example.yml (#1742) (@atharva-2001) - -### release-2021.7.18.0 (2021/07/16 14:41 +00:00) - [#1665](https://github.com/tardis-sn/tardis/pull/1665) Demonstrating the `nelements` and the `species_list` functionality in the SDEC plot notebook (@atharva-2001) - [#1727](https://github.com/tardis-sn/tardis/pull/1727) Fixing Quickstart Metadata (#1727) (@smithis7) - [#1726](https://github.com/tardis-sn/tardis/pull/1726) display "latest" in doc version (#1726) (@epassaro) - [#1716](https://github.com/tardis-sn/tardis/pull/1716) Small fixes to docs (#1716) (@smithis7) - [#1722](https://github.com/tardis-sn/tardis/pull/1722) Added missing import for IonNumberDensityHeNLTE (#1722) (@DhruvSondhi) - [#1714](https://github.com/tardis-sn/tardis/pull/1714) Removed Formatting from exisiting log messages (#1714) (@DhruvSondhi) - -### release-2021.7.14.0 (2021/07/14 15:39 +00:00) - [#1707](https://github.com/tardis-sn/tardis/pull/1707) Open in VSCode badge (#1707) (@wkerzendorf) - [#1713](https://github.com/tardis-sn/tardis/pull/1713) fix package data for conda-forge package (#1713) (@epassaro) - [#1711](https://github.com/tardis-sn/tardis/pull/1711) Changed the xlim and the ylabel in the quickstart notebook plot (#1711) (@Rodot-) - -### release-2021.7.12.0 (2021/07/12 20:05 +00:00) - [#1686](https://github.com/tardis-sn/tardis/pull/1686) fix pip install (#1686) (@epassaro) - [#1701](https://github.com/tardis-sn/tardis/pull/1701) Adding Logging Support for Caught Exceptions (#1701) (@DhruvSondhi) - [#1684](https://github.com/tardis-sn/tardis/pull/1684) Moved Simulation & Montecarlo Logging Frameworks to `tardis/io/logger` folder (#1684) (@DhruvSondhi) - [#1691](https://github.com/tardis-sn/tardis/pull/1691) Create profiling documentation directory (#1691) (@KevinCawley) - -### release-2021.7.11.0 (2021/07/09 17:07 +00:00) - [#1680](https://github.com/tardis-sn/tardis/pull/1680) Added docstring-coverage badge (#1680) (@epassaro) - [#1696](https://github.com/tardis-sn/tardis/pull/1696) Adding mu and r to virtual packet logging (#1696) (@smithis7) - [#1695](https://github.com/tardis-sn/tardis/pull/1695) Enabling spectrum plotting in the frequency domain (#1695) (@smithis7) - -### release-2021.7.5 (2021/07/05 14:32 +00:00) - [#1688](https://github.com/tardis-sn/tardis/pull/1688) final changes for release pipeline (#1688) (@epassaro) - -### release-2021.7.2.dev1+g58e4e79d (2021/07/02 15:44 +00:00) - [#1683](https://github.com/tardis-sn/tardis/pull/1683) prepare release pipeline for CalVer (#1683) (@epassaro) - -### release-2021.07.01 (2021/07/01 23:05 +00:00) - [#1674](https://github.com/tardis-sn/tardis/pull/1674) APE 17 migration (#1674) (@epassaro) - [#1658](https://github.com/tardis-sn/tardis/pull/1658) add refdata repo selection in template (#1658) (@epassaro) - [#1682](https://github.com/tardis-sn/tardis/pull/1682) Opacities script with proper credit (#1682) (@andrewfullard) @@ -426,23 +763,15 @@ - [#1032](https://github.com/tardis-sn/tardis/pull/1032) Add Mark Magee to .mailmap (#1032) (@epassaro) - [#1025](https://github.com/tardis-sn/tardis/pull/1025) Add `compilers` to environment YAML file (#1025) (@epassaro) - [#1026](https://github.com/tardis-sn/tardis/pull/1026) Minor changes (#1026) (@epassaro) - -### 3.0.dev3396 (2020/02/07 15:00 +00:00) - [#1027](https://github.com/tardis-sn/tardis/pull/1027) Added Mark Magee (#1027) (@MarkMageeAstro) - [#1024](https://github.com/tardis-sn/tardis/pull/1024) Add epassaro orcid (#1024) (@epassaro) - [#1022](https://github.com/tardis-sn/tardis/pull/1022) added Alice's orcid (#1022) (@harpolea) - -### 3.0.dev3384 (2020/02/02 21:56 +00:00) - [#1021](https://github.com/tardis-sn/tardis/pull/1021) Set cron job, disable CI and PR (#1021) (@epassaro) - -### 3.0.dev3383 (2020/02/02 19:01 +00:00) - [#1015](https://github.com/tardis-sn/tardis/pull/1015) Set up release TARDIS version with Azure Pipelines (#1015) (@epassaro) - [#1020](https://github.com/tardis-sn/tardis/pull/1020) Update .mailmap (#1020) (@livnehra) - [#1018](https://github.com/tardis-sn/tardis/pull/1018) Updated .mailmap (#1018) (@epassaro) - [#1010](https://github.com/tardis-sn/tardis/pull/1010) Pipeline for comparing reference data (#1010) (@epassaro) - [#1016](https://github.com/tardis-sn/tardis/pull/1016) Removed GH Action for release versions (#1016) (@epassaro) - -### 3.0.dev3388 (2020/01/25 22:36 +00:00) - [#1013](https://github.com/tardis-sn/tardis/pull/1013) Fixed typo (#1013) (@epassaro) - [#1006](https://github.com/tardis-sn/tardis/pull/1006) Trying to get the right version number for automatic release (#1006) (@epassaro) - [#1008](https://github.com/tardis-sn/tardis/pull/1008) Improvements for the update_reference section [docs] (#1008) (@epassaro) @@ -806,10 +1135,10 @@ - [#225](https://github.com/tardis-sn/tardis/pull/225) Test added in test_atomic.py (@vaibhav4595) - [#223](https://github.com/tardis-sn/tardis/pull/223) Update git_workflow.rst (@ujjwalwahi) -### 1.0rc3 (2015/03/03 12:54 +00:00) +### v1.0 (2015/03/03 12:58 +00:00) - [#219](https://github.com/tardis-sn/tardis/pull/219) fixing run_tardis (@wkerzendorf) -### 1.0.dev1419 (2015/02/19 13:58 +00:00) +### v1.0rc3 (2015/02/19 14:40 +00:00) - [#218](https://github.com/tardis-sn/tardis/pull/218) Docs/anaconda install (@wkerzendorf) - [#217](https://github.com/tardis-sn/tardis/pull/217) Docs/fixing pip requirements (@wkerzendorf) - [#216](https://github.com/tardis-sn/tardis/pull/216) some fixes to the gui so it works with pyside (@wkerzendorf) @@ -840,8 +1169,6 @@ - [#164](https://github.com/tardis-sn/tardis/pull/164) Config/toggle validation (@wkerzendorf) - [#151](https://github.com/tardis-sn/tardis/pull/151) WIP Montecarlo C Rewrite (@orbitfold) - [#160](https://github.com/tardis-sn/tardis/pull/160) how to get constant density? broken? (@wkerzendorf) - -### 0.9.2 (2014/06/12 23:37 +00:00) - [#158](https://github.com/tardis-sn/tardis/pull/158) updated astropy_helpers version (@wkerzendorf) - [#157](https://github.com/tardis-sn/tardis/pull/157) added yaml to pip-requirements and linked the doc pip-requirements to this (@wkerzendorf) - [#154](https://github.com/tardis-sn/tardis/pull/154) renamed Config to ConfigurationValidator (@wkerzendorf) @@ -886,8 +1213,6 @@ - [#101](https://github.com/tardis-sn/tardis/pull/101) Fix for Issue #88: Moved test functions for tardis.util from test_config_reader (@thegyro) - [#94](https://github.com/tardis-sn/tardis/pull/94) Fix coveralls (@wkerzendorf) - [#87](https://github.com/tardis-sn/tardis/pull/87) Added --profile and --profiler_log_file command line arguments to enable... (@orbitfold) - -### 0.9.1 (2014/02/04 01:51 +00:00) - [#74](https://github.com/tardis-sn/tardis/pull/74) fixed manifest to incluse ez_setup.py and setuptools_bootstrap.py. fixes... (@wkerzendorf) - [#78](https://github.com/tardis-sn/tardis/pull/78) cosmetic fixes (@ssim) - [#77](https://github.com/tardis-sn/tardis/pull/77) Docs edit (@ssim, @wkerzendorf) diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 00000000000..777b70c46c0 --- /dev/null +++ b/CITATION.cff @@ -0,0 +1,240 @@ +# YAML 1.2 +# Metadata for citation of this software according to the CFF format (https://citation-file-format.github.io/) +cff-version: 1.0.3 +message: If you use this software, please cite it using these metadata. +# FIXME title as repository name might not be the best name, please make human readable +title: 'tardis-sn/tardis: TARDIS v2023.08.13' +doi: 10.5281/zenodo.8244935 +# FIXME splitting of full names is error prone, please check if given/family name are correct +authors: +- given-names: Wolfgang + family-names: Kerzendorf + affiliation: Michigan State University + orcid: https://orcid.org/0000-0002-0479-7235 +- given-names: Stuart + family-names: Sim + affiliation: Queen's University Belfast + orcid: https://orcid.org/0000-0002-9774-1192 +- given-names: Christian + family-names: Vogl + affiliation: Max-Planck-Institut für Astrophysik + orcid: https://orcid.org/0000-0002-7941-5692 +- given-names: Marc + family-names: Williamson + affiliation: New York University + orcid: https://orcid.org/0000-0003-2544-4516 +- given-names: Ezequiel + family-names: Pássaro + orcid: https://orcid.org/0000-0002-3707-1975 +- given-names: Andreas + family-names: Flörs + affiliation: GSI Helmholtz Centre for Heavy Ion Research + orcid: https://orcid.org/0000-0003-2024-2819 +- given-names: Yssa + family-names: Camacho + affiliation: Rutgers The State University of New Jersey + orcid: https://orcid.org/0000-0002-9830-3880 +- given-names: Vytautas + family-names: Jančauskas + orcid: https://orcid.org/0000-0002-6051-210X +- given-names: Alice + family-names: Harpole + affiliation: Stony Brook University + orcid: https://orcid.org/0000-0002-1530-781X +- given-names: Ulrich + family-names: Nöbauer + affiliation: Max-Planck-Institut für Astrophysik + orcid: https://orcid.org/0000-0002-2453-853X +- given-names: Stefan + family-names: Lietzau + orcid: https://orcid.org/0000-0002-7131-3341 +- given-names: Mikhail + family-names: Mishin +- given-names: Fotis + family-names: Tsamis + affiliation: National Observatory of Athens + orcid: https://orcid.org/0000-0003-4875-1623 +- given-names: Aoife + family-names: Boyle +- given-names: Luke + family-names: Shingles +- given-names: Vaibhav + family-names: Gupta +- given-names: Karan + family-names: Desai +- given-names: Michael + family-names: Klauser +- given-names: Frederik + family-names: Beaujean + affiliation: Ludwig-Maximilians-Universität München Fakultät für Physik + orcid: https://orcid.org/0000-0001-9901-8785 +- given-names: Adam + family-names: Suban-Loewen +- given-names: Epson + family-names: Heringer + affiliation: University of Toronto + orcid: https://orcid.org/0000-0002-1502-9127 +- given-names: Barnabás + family-names: Barna +- given-names: Gaurav + family-names: Gautam +- given-names: Andrew + family-names: Fullard + affiliation: Michigan State University + orcid: https://orcid.org/0000-0001-7343-1678 +- given-names: Isaac + family-names: Smith +- given-names: Kevin + family-names: Cawley +- given-names: Jaladh + family-names: Singhal + orcid: https://orcid.org/0000-0002-8310-0829 +- given-names: Atharva + family-names: Arya +- given-names: Jack + family-names: O'Brien +- given-names: Talytha + family-names: Barbosa +- given-names: Dhruv + family-names: Sondhi +- given-names: Jenny + family-names: Yu +- given-names: Maryam + family-names: Patel +- given-names: Kaushik + family-names: Varanasi +- given-names: James + family-names: Gillanders + orcid: https://orcid.org/0000-0002-8094-6108 +- given-names: Shikha + family-names: Rathi +- given-names: Sona + family-names: Chitchyan +- given-names: Arjun + family-names: Savel +- given-names: Martin + family-names: Reinecke +- given-names: Youssef + family-names: Eweis +- given-names: Tomas + family-names: Bylund +- given-names: Laud + family-names: Bentil +- given-names: William + family-names: Black +- given-names: Joshua + family-names: Shields +- given-names: Jordi + family-names: Eguren + orcid: https://orcid.org/0000-0002-2328-8030 +- given-names: Arib + family-names: Alam +- given-names: Ansh + family-names: Kumar +- given-names: Matthew + family-names: Bartnik +- given-names: Mark + family-names: Magee +- given-names: Shreyas + family-names: Singh +- given-names: Rohith + family-names: Varma Buddaraju +- given-names: Ran + family-names: Livneh +- given-names: Satwik + family-names: Kambham +- given-names: Srinath + family-names: Rajagopalan +- given-names: Ayushi + family-names: Daksh +- given-names: Sashank + family-names: Mishra + orcid: https://orcid.org/0000-0001-8302-1584 +- given-names: Rinkle + family-names: Jain +- given-names: John + family-names: Reichenbach +- given-names: Andreas + family-names: Floers +- given-names: GitHub + family-names: Actions +- given-names: Alexander + family-names: Holas +- given-names: Sourav + family-names: Singh +- given-names: Antreev + family-names: Brar +- given-names: Aarya + family-names: Chaumal +- given-names: Jayant + family-names: Bhakar +- given-names: Jonatan + family-names: Selsing +- given-names: Nathan + family-names: Kowalski +- given-names: Aman + family-names: Kumar +- given-names: Abhishek + family-names: Patidar +- given-names: Chinmay + family-names: Talegaonkar +- given-names: Caroline + family-names: Sofiatti +- given-names: Shashank + family-names: Venkat +- given-names: Sampark + family-names: Sharma +- given-names: Nance + family-names: Sarafina +- given-names: Pratik + family-names: Patel +- given-names: Parikshit + family-names: Singh Rathore +- given-names: Nilesh + family-names: Patra +- given-names: Jing + family-names: Lu +- given-names: Musabbiha + family-names: Zaheer +- given-names: Morgan + family-names: Sandler +- given-names: Le + family-names: Truong +- given-names: Kevin + family-names: Yap +- given-names: Johannes + family-names: Buchner +- given-names: Suyash + family-names: Gupta +- given-names: Shilpi + family-names: Prasad +- given-names: Chaitanya + family-names: Kolliboyina +- given-names: Thom + family-names: Lemoine +- given-names: Ujjwal + family-names: Wahi +- given-names: Yash + family-names: Aggarwal +- given-names: Yuki + family-names: Matsumura +- given-names: Harshul + family-names: Gupta +- given-names: Dmitry + family-names: Volodin +- given-names: ABHISHEK + family-names: PATIDAR +- given-names: Laureano + family-names: Martinez +- given-names: Atharwa + family-names: Kharkar +- given-names: Ashwin + family-names: Nayak U +- given-names: Debajyoti + family-names: Dasgupta +- given-names: Atul + family-names: Kumar +version: release-2023.08.13 +date-released: 2023-08-13 +repository-code: https://github.com/tardis-sn/tardis +license: other-open diff --git a/GOVERNANCE.md b/GOVERNANCE.md index 119b2ece98a..d0563d3d05e 100644 --- a/GOVERNANCE.md +++ b/GOVERNANCE.md @@ -1,3 +1,3 @@ # TARDIS Collaboration Governance -Please visit our website to learn more about the [TARDIS Governance](https://tardis-sn.github.io/tardis/governance.html). +Please visit our website to learn more about the [TARDIS Governance](https://tardis-sn.github.io/team/governance/). diff --git a/README.rst b/README.rst index 9c9c87a847f..03dd1718465 100644 --- a/README.rst +++ b/README.rst @@ -2,105 +2,98 @@ TARDIS ====== -TARDIS is a tool that creates synthetic observations (*spectra*) for exploding -stars (*supernovae*). - .. image:: https://img.shields.io/badge/Donate-to%20TARDIS-brightgreen.svg :target: https://numfocus.salsalabs.org/donate-to-tardis/index.html -.. image:: https://open.vscode.dev/badges/open-in-vscode.svg +.. image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A + :target: http://numfocus.org + +.. image:: https://badges.gitter.im/Join%20Chat.svg + :target: https://gitter.im/tardis-sn/tardis + +.. image:: https://img.shields.io/static/v1?logo=visualstudiocode&label=&message=Open%20in%20Visual%20Studio%20Code&labelColor=2c2c32&color=007acc&logoColor=007acc :target: https://open.vscode.dev/tardis-sn/tardis +| + +TARDIS is a tool that creates synthetic observations (*spectra*) for exploding +stars (*supernovae*). .. image:: https://codecov.io/gh/tardis-sn/tardis/branch/master/graph/badge.svg :target: https://codecov.io/gh/tardis-sn/tardis -.. image:: https://img.shields.io/endpoint?url=https://jsonbin.org/tardis-bot/badges/tardis/docstr-coverage - :target: https://github.com/tardis-sn/tardis/actions/workflows/docstr-coverage.yml?query=branch%3Amaster - -.. image:: https://img.shields.io/badge/DOI-10.5281%2Fzenodo.592480-blue - :target: https://doi.org/10.5281/zenodo.592480 - -.. image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A - :target: http://numfocus.org - :alt: Powered by NumFOCUS +.. image:: https://img.shields.io/endpoint?url=https://jsonbin.org/tardis-bot/tardis/badges/docstr-cov + :target: https://github.com/tardis-sn/tardis/actions/workflows/docstr-cov.yml?query=branch%3Amaster -.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat - :target: http://www.astropy.org +.. image:: https://github.com/tardis-sn/tardis/actions/workflows/tests.yml/badge.svg + :target: https://github.com/tardis-sn/tardis/actions/workflows/tests.yml -.. image:: https://badges.gitter.im/Join%20Chat.svg - :target: https://gitter.im/tardis-sn/tardis +.. image:: https://github.com/tardis-sn/tardis/actions/workflows/build-docs.yml/badge.svg + :target: https://tardis-sn.github.io/tardis/index.html .. image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black +| -.. image:: https://github.com/tardis-sn/tardis/actions/workflows/documentation-build.yml/badge.svg - :target: https://tardis-sn.github.io/tardis/index.html - -.. image:: https://dev.azure.com/tardis-sn/TARDIS/_apis/build/status/TARDIS%20tests?branchName=master - :target: https://dev.azure.com/tardis-sn/TARDIS/_build/latest?definitionId=6&branchName=master - +.. _tardiscredits: ****************************** Credits & Publication Policies ****************************** +|DOI_BADGE| + We provide TARDIS as a free, open-source tool. If you are using it, please adhere to a few policies and acknowledge the TARDIS Team. - Publication Policies ==================== If you use this code for any publications or presentations please acknowledge it. Please cite `Kerzendorf & Sim 2014 -`_ in the text. - -Please add this paragraph to the Acknowledgement: +`_ in the text and add the +following paragraph to the Acknowledgement section: -.. code-block:: none +.. parsed-literal:: - This research made use of \textsc{Tardis}, a community-developed software - package for spectral synthesis in supernovae - \citep{2014MNRAS.440..387K, kerzendorf_wolfgang_2019_2590539}. - The development of \textsc{Tardis} received support from the - Google Summer of Code initiative - and from ESA's Summer of Code in Space program. \textsc{Tardis} makes - extensive use of Astropy and PyNE. + This research made use of \\textsc{tardis}, a community-developed software package for spectral + synthesis in supernovae \\citep{2014MNRAS.440..387K, |CITATION|}. The + development of \\textsc{tardis} received support from GitHub, the Google Summer of Code + initiative, and from ESA's Summer of Code in Space program. \\textsc{tardis} is a fiscally + sponsored project of NumFOCUS. \\textsc{tardis} makes extensive use of Astropy and Pyne. +If you use any of the full relativity treatments or use TARDIS for modelling +Type II supernovae, also add `Spectral modeling of type II supernovae. I. Dilution factors `_ +to the Acknowledgement. -If you use any of the full relativity treatments or use TARDIS for -modelling Type II supernovae you also add this citation to acknowledgement -`Spectral modeling of type II supernovae. I. Dilution factors -`_: - -.. code-block:: none +.. parsed-literal:: \citep{2019A&A...621A..29V} The following BibTeX entries are needed for the references: -.. code-block:: none +.. code-block:: bibtex @ARTICLE{2014MNRAS.440..387K, - author = {{Kerzendorf}, W.~E. and {Sim}, S.~A.}, - title = "{A spectral synthesis code for rapid modelling of supernovae}", - journal = {\mnras}, + author = {{Kerzendorf}, W.~E. and {Sim}, S.~A.}, + title = "{A spectral synthesis code for rapid modelling of supernovae}", + journal = {\mnras}, archivePrefix = "arXiv", - eprint = {1401.5469}, - primaryClass = "astro-ph.SR", - keywords = {radiative transfer, methods: numerical, supernovae: general}, - year = 2014, - month = may, - volume = 440, - pages = {387-404}, - doi = {10.1093/mnras/stu055}, - adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.440..387K}, - adsnote = {Provided by the SAO/NASA Astrophysics Data System} + eprint = {1401.5469}, + primaryClass = "astro-ph.SR", + keywords = {radiative transfer, methods: numerical, supernovae: general}, + year = 2014, + month = may, + volume = 440, + pages = {387-404}, + doi = {10.1093/mnras/stu055}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.440..387K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +.. code-block:: bibtex + @ARTICLE{2019A&A...621A..29V, - author = {{Vogl}, C. and {Sim}, S.~A. and {Noebauer}, U.~M. and - {Kerzendorf}, W.~E. and {Hillebrandt}, W.}, + author = {{Vogl}, C. and {Sim}, S.~A. and {Noebauer}, U.~M. and {Kerzendorf}, W.~E. and {Hillebrandt}, W.}, title = "{Spectral modeling of type II supernovae. I. Dilution factors}", journal = {\aap}, keywords = {radiative transfer, methods: numerical, stars: distances, supernovae: general, supernovae: individual: SN1999em, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics}, @@ -117,8 +110,14 @@ The following BibTeX entries are needed for the references: adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +.. |CITATION| replace:: kerzendorf_wolfgang_2023_8244935 - @software{kerzendorf_wolfgang_2020_3893940, +.. |DOI_BADGE| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.8244935-blue + :target: https://doi.org/10.5281/zenodo.8244935 + +.. code-block:: bibtex + + @software{kerzendorf_wolfgang_2023_8244935, author = {Kerzendorf, Wolfgang and Sim, Stuart and Vogl, Christian and @@ -142,55 +141,104 @@ The following BibTeX entries are needed for the references: Heringer, Epson and Barna, Barnabás and Gautam, Gaurav and + Fullard, Andrew and + Smith, Isaac and + Cawley, Kevin and + Singhal, Jaladh and + Arya, Atharva and + O'Brien, Jack and Barbosa, Talytha and + Sondhi, Dhruv and + Yu, Jenny and Patel, Maryam and Varanasi, Kaushik and - Eweis, Youssef and + Gillanders, James and + Rathi, Shikha and + Chitchyan, Sona and + Savel, Arjun and Reinecke, Martin and + Eweis, Youssef and Bylund, Tomas and Bentil, Laud and + Black, William and + Shields, Joshua and Eguren, Jordi and + Alam, Arib and + Kumar, Ansh and + Bartnik, Matthew and + Magee, Mark and + Singh, Shreyas and + Varma Buddaraju, Rohith and Livneh, Ran and - Singhal, Jaladh and - O'Brien, Jack and + Kambham, Satwik and Rajagopalan, Srinath and + Daksh, Ayushi and + Mishra, Sashank and Jain, Rinkle and Reichenbach, John and - Mishra, Sashank and + Floers, Andreas and + Actions, GitHub and + Holas, Alexander and Singh, Sourav and - Sofiatti, Caroline and + Brar, Antreev and + Chaumal, Aarya and + Bhakar, Jayant and Selsing, Jonatan and Kowalski, Nathan and - Savel, Arjun and + Kumar, Aman and + Patidar, Abhishek and Talegaonkar, Chinmay and + Sofiatti, Caroline and + Venkat, Shashank and + Sharma, Sampark and + Sarafina, Nance and Patel, Pratik and + Singh Rathore, Parikshit and Patra, Nilesh and - Nayak, Ashwin and - Kumar, Atul and - Sarafina, Nance and - Gillanders, James and - Sharma, Sampark and + Lu, Jing and + Zaheer, Musabbiha and + Sandler, Morgan and + Truong, Le and + Yap, Kevin and + Buchner, Johannes and + Gupta, Suyash and + Prasad, Shilpi and + Kolliboyina, Chaitanya and + Lemoine, Thom and Wahi, Ujjwal and + Aggarwal, Yash and + Matsumura, Yuki and + Gupta, Harshul and + Volodin, Dmitry and + PATIDAR, ABHISHEK and + Martinez, Laureano and + Kharkar, Atharwa and + Nayak U, Ashwin and Dasgupta, Debajyoti and - Magee, Mark and - Yap, Kevin and - Gupta, Suyash}, - title = {tardis-sn/tardis: TARDIS v3.0.dev3459}, - month = jun, - year = 2020, + Kumar, Atul}, + title = {tardis-sn/tardis: TARDIS v2023.08.13}, + month = aug, + year = 2023, publisher = {Zenodo}, - version = {v3.0.dev3459}, - doi = {10.5281/zenodo.3893940}, - url = {https://doi.org/10.5281/zenodo.3893940} + version = {release-2023.08.13}, + doi = {10.5281/zenodo.8244935}, + url = {https://doi.org/10.5281/zenodo.8244935} } - ******* License ******* +.. image:: https://img.shields.io/conda/l/conda-forge/tardis-sn + :target: https://github.com/tardis-sn/tardis/blob/master/licenses/LICENSE.rst + +.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat + :target: http://www.astropy.org +| + This project is Copyright (c) TARDIS Collaboration and licensed under the terms of the BSD 3-Clause license. This package is based upon the `Astropy package template `_ which is licensed under the BSD 3-clause license. See the licenses folder for more information. + diff --git a/README_TEMPLATE.rst b/README_TEMPLATE.rst new file mode 100644 index 00000000000..2310b633728 --- /dev/null +++ b/README_TEMPLATE.rst @@ -0,0 +1,56 @@ +====== +TARDIS +====== + +.. image:: https://img.shields.io/badge/Donate-to%20TARDIS-brightgreen.svg + :target: https://numfocus.salsalabs.org/donate-to-tardis/index.html + +.. image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A + :target: http://numfocus.org + +.. image:: https://badges.gitter.im/Join%20Chat.svg + :target: https://gitter.im/tardis-sn/tardis + +.. image:: https://img.shields.io/static/v1?logo=visualstudiocode&label=&message=Open%20in%20Visual%20Studio%20Code&labelColor=2c2c32&color=007acc&logoColor=007acc + :target: https://open.vscode.dev/tardis-sn/tardis +| + +TARDIS is a tool that creates synthetic observations (*spectra*) for exploding +stars (*supernovae*). + +.. image:: https://codecov.io/gh/tardis-sn/tardis/branch/master/graph/badge.svg + :target: https://codecov.io/gh/tardis-sn/tardis + +.. image:: https://img.shields.io/endpoint?url=https://jsonbin.org/tardis-bot/tardis/badges/docstr-cov + :target: https://github.com/tardis-sn/tardis/actions/workflows/docstr-cov.yml?query=branch%3Amaster + +.. image:: https://github.com/tardis-sn/tardis/actions/workflows/tests.yml/badge.svg + :target: https://github.com/tardis-sn/tardis/actions/workflows/tests.yml + +.. image:: https://github.com/tardis-sn/tardis/actions/workflows/build-docs.yml/badge.svg + :target: https://tardis-sn.github.io/tardis/index.html + +.. image:: https://img.shields.io/badge/code%20style-black-000000.svg + :target: https://github.com/psf/black +| + + +.. include:: docs/resources/credits.rst + + +******* +License +******* + +.. image:: https://img.shields.io/conda/l/conda-forge/tardis-sn + :target: https://github.com/tardis-sn/tardis/blob/master/licenses/LICENSE.rst + +.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat + :target: http://www.astropy.org +| + +This project is Copyright (c) TARDIS Collaboration and licensed under +the terms of the BSD 3-Clause license. This package is based upon +the `Astropy package template `_ +which is licensed under the BSD 3-clause license. See the licenses folder for +more information. diff --git a/asv.conf.json b/asv.conf.json new file mode 100644 index 00000000000..351c2a78502 --- /dev/null +++ b/asv.conf.json @@ -0,0 +1,20 @@ +{ + "version": 1, + "project": "tardis", + "project_url": "https://tardis-sn.github.io/tardis", + "repo": ".", + "install_command": ["in-dir={env_dir} python -mpip install {wheel_file}"], + "uninstall_command": ["return-code=any python -mpip uninstall -y {project}"], + "build_command": [ + "python setup.py build", + "PIP_NO_BUILD_ISOLATION=false python -mpip wheel --no-deps --no-index -w {build_cache_dir} {build_dir}" + ], + "branches": ["master"], + "environment_type": "mamba", + "show_commit_url": "https://github.com/tardis-sn/tardis/commit/", + "conda_environment_file": "tardis_env3.yml", + "benchmark_dir": "benchmarks", + "env_dir": ".asv/env", + "results_dir": ".asv/results", + "html_dir": ".asv/html" +} diff --git a/asv/asv.conf.json b/asv/asv.conf.json deleted file mode 100644 index 82b305d0773..00000000000 --- a/asv/asv.conf.json +++ /dev/null @@ -1,11 +0,0 @@ -{ - "version": 1, - "project": "tardis", - "project_url": "https://github.com/tardis-sn/tardis", - "repo": "https://github.com/tardis-sn/tardis.git", - "matrix": { - "numpy": [], - "astropy": [], - "Cython": [] - } -} diff --git a/asv/benchmarks/benchmarks.py b/asv/benchmarks/benchmarks.py deleted file mode 100644 index 1e828a7cd27..00000000000 --- a/asv/benchmarks/benchmarks.py +++ /dev/null @@ -1,66 +0,0 @@ -# Write the benchmarking functions here. -# See "Writing benchmarks" in the asv docs for more information. - -import numpy as np -from tardis.tests import montecarlo_test_wrappers as montecarlo - -LINE_SIZE = 10000000 - - -class TimeSuite: - """ - An example benchmark that times the performance of various kinds - of iterating over dictionaries in Python. - """ - - def setup(self): - self.line = np.arange(LINE_SIZE, 1, -1).astype(np.float64) - - def time_binarysearch(self): - for _ in range(LINE_SIZE): - montecarlo.binary_search_wrapper( - self.line, np.random.random() * LINE_SIZE, 0, LINE_SIZE - 1 - ) - - def time_compute_distance2outer(self): - for _ in range(1000000): - montecarlo.compute_distance2outer_wrapper(0.0, 0.5, 1.0) - montecarlo.compute_distance2outer_wrapper(1.0, 0.5, 1.0) - montecarlo.compute_distance2outer_wrapper(0.3, 1.0, 1.0) - montecarlo.compute_distance2outer_wrapper(0.3, -1.0, 1.0) - montecarlo.compute_distance2outer_wrapper(0.5, 0.0, 1.0) - - def time_compute_distance2inner(self): - for _ in range(1000000): - montecarlo.compute_distance2inner_wrapper(1.5, -1.0, 1.0) - montecarlo.compute_distance2inner_wrapper(0.0, 0.0, 0.0) - montecarlo.compute_distance2inner_wrapper(1.2, -0.7, 1.0) - - def time_compute_distance2line(self): - for _ in range(1000000): - montecarlo.compute_distance2line_wrapper( - 2.20866912e15, - -0.251699059004, - 1.05581082105e15, - 1.06020910733e15, - 1693440.0, - 5.90513983371e-07, - 1.0602263591e15, - 1.06011723237e15, - 2, - ) - montecarlo.compute_distance2line_wrapper( - 2.23434667994e15, - -0.291130548401, - 1.05581082105e15, - 1.06733618121e15, - 1693440.0, - 5.90513983371e-07, - 1.06738407486e15, - 1.06732933961e15, - 3, - ) - - def time_compute_distance2electron(self): - for _ in range(1000000): - montecarlo.compute_distance2electron_wrapper(0.0, 0.0, 2.0, 2.0) diff --git a/tardis/gui/__init.py__ b/benchmarks/__init__.py similarity index 100% rename from tardis/gui/__init.py__ rename to benchmarks/__init__.py diff --git a/benchmarks/asv_by_release.bash b/benchmarks/asv_by_release.bash new file mode 100755 index 00000000000..815f1ebb636 --- /dev/null +++ b/benchmarks/asv_by_release.bash @@ -0,0 +1,99 @@ +#!/usr/bin/env bash + +RELEASE_LIST=$(git tag -l "release-202[34]*" | sort -r) + +readarray -t RELEASE_TAGS <<<"${RELEASE_LIST[@]}" +RELEASE_HASHES=() +for release_tag in "${RELEASE_TAGS[@]}"; do + echo "Tag: ${release_tag}" + HASH_COMMIT=$(git show-ref -s "${release_tag}") + RELEASE_HASHES+=("${HASH_COMMIT}") +done +echo "RELEASE_HASHES: ${#RELEASE_HASHES[*]}" + +ASV_CONFIG_PATH="/app/asv" +cd "${ASV_CONFIG_PATH}" || exit + +rm -f release_hashes.txt +touch release_hashes.txt +for release_hash in "${RELEASE_HASHES[@]}"; do + echo "${release_hash}" >>release_hashes.txt +done + +function show_timed_time { + local time=${1} + local milliseconds="${time: -3}" + local seconds=$((time / 1000)) + local minutes=0 + local minutes_display="" + local hours=0 + local hours_display="" + local days=0 + local days_display="" + + if [[ "${seconds}" -gt 59 ]]; then + minutes=$((seconds / 60)) + seconds=$((seconds % 60)) + minutes_display="${minutes}m " + fi + + if [[ "${minutes}" -gt 59 ]]; then + hours=$((minutes / 60)) + minutes=$((minutes % 60)) + minutes_display="${minutes}m " + hours_display="${hours}h " + fi + + if [[ "${hours}" -gt 23 ]]; then + days=$((hours / 24)) + hours=$((hours % 24)) + hours_display="${hours}h " + days_display="${days}d " + fi + + echo "${days_display}${hours_display}${minutes_display}${seconds}.${milliseconds}s" +} + +start=$(date +%s%N | cut -b1-13) + +# ASV has an argument called “bench”, which filters the benchmarks. +# I had two problems with ASV regarding benchmark filtering. +# 1. If we want to run only the `time_read_stella_model` benchmark. +# ASV will run 3 benchmarks using this argument +# `--bench time_read_stella_model`: +# - `time_read_stella_model`. +# - `time_read_stella_model_meta`. +# - `time_read_stella_model_data`. +# It is because the ASV uses regular expressions to match the name. +# To run only the benchmark `time_read_stella_model` we need to run: +# - `--bench "time_read_stella_model$"` +# - The `$` means that it matches the end of a string without +# consuming any characters. +# Note: +# - If the benchmark doesn't have parameters (`@parameterize`), +# then the name in ASV is the benchmark name without parameters. +# 2. The second problem is when I want to search for some benchmark that +# has parameters (`@parameterize`) because the name of the benchmark +# includes parenthesis and the parameters and their values. +# One example is `time_get_inverse_doppler_factor` which has 3 benchmarks +# with this prefix, and has parameters. +# To prevent it, we need to add the argument with this syntax: +# `--bench time_benchmark_name([^_A-Za-z]|$)` +# The regular expression match with all the parameters generated by ASV. +#time asv run \ +# --bench "time_read_stella_model$" +# --bench "time_get_inverse_doppler_factor([^_A-Za-z]|$)" \ +# --bench "time_get_inverse_doppler_factor_full_relativity([^_A-Za-z]|$)" \ +# release-2023.01.11..master + +# This command runs all benchmarks for all commits that have not been run. +time asv run \ + --skip-existing-commits \ + ALL + +end=$(date +%s%N | cut -b1-13) +runtime=$((end - start)) +display_time="$(show_timed_time ${runtime})" +echo "" +echo "Time: ${display_time}" +echo "" diff --git a/benchmarks/benchmark_base.py b/benchmarks/benchmark_base.py new file mode 100644 index 00000000000..3069ce6a1b3 --- /dev/null +++ b/benchmarks/benchmark_base.py @@ -0,0 +1,362 @@ +from copy import deepcopy +from os.path import dirname, join, realpath +from pathlib import Path +from tempfile import mkstemp + +import astropy.units as u +import numpy as np +import pandas as pd +from numba import njit + +from benchmarks.util.nlte import NLTE +from tardis.io.atom_data import AtomData +from tardis.io.configuration import config_reader +from tardis.io.configuration.config_reader import Configuration +from tardis.io.util import YAMLLoader, yaml_load_file +from tardis.model import SimulationState +from tardis.simulation import Simulation +from tardis.tests.fixtures.atom_data import DEFAULT_ATOM_DATA_UUID +from tardis.tests.fixtures.regression_data import RegressionData +from tardis.transport.montecarlo import RPacket +from tardis.transport.montecarlo.numba_interface import ( + opacity_state_initialize, +) +from tardis.transport.montecarlo.packet_collections import ( + VPacketCollection, +) + + +class BenchmarkBase: + # It allows 10 minutes of runtime for each benchmark and includes + # the total time for all the repetitions for each benchmark. + timeout = 600 + + def __init__(self): + self.nlte = NLTE() + + @staticmethod + def get_relative_path(partial_path: str): + path = dirname(realpath(__file__)) + targets = Path(partial_path).parts + + for target in targets: + path = join(path, target) + + return path + + def get_absolute_path(self, partial_path): + partial_path = "../" + partial_path + + return self.get_relative_path(partial_path) + + @property + def tardis_config_verysimple(self): + filename = self.get_absolute_path( + "tardis/io/configuration/tests/data/tardis_configv1_verysimple.yml" + ) + return yaml_load_file( + filename, + YAMLLoader, + ) + + @property + def tardis_ref_path(self): + # TODO: This route is fixed but needs to get from the arguments given in the command line. + # /app/tardis-refdata + ref_data_path = Path( + Path(__file__).parent.parent, + "tardis-refdata", + ).resolve() + return ref_data_path + + @property + def atomic_dataset(self) -> AtomData: + atomic_data = AtomData.from_hdf(self.atomic_data_fname) + + if atomic_data.md5 != DEFAULT_ATOM_DATA_UUID: + message = f'Need default Kurucz atomic dataset (md5="{DEFAULT_ATOM_DATA_UUID}")' + raise Exception(message) + else: + return atomic_data + + @property + def atomic_data_fname(self): + atomic_data_fname = ( + f"{self.tardis_ref_path}/atom_data/kurucz_cd23_chianti_H_He.h5" + ) + + if not Path(atomic_data_fname).exists(): + atom_data_missing_str = ( + f"{atomic_data_fname} atomic datafiles " + f"does not seem to exist" + ) + raise Exception(atom_data_missing_str) + + return atomic_data_fname + + @property + def example_configuration_dir(self): + return self.get_absolute_path("tardis/io/configuration/tests/data") + + @property + def hdf_file_path(self): + # TODO: Delete this files after ASV runs the benchmarks. + # ASV create a temporal directory in runtime per test: `tmpiuxngvlv`. + # The ASV and ASV_Runner, not has some way to get this temporal directory. + # The idea is use this temporal folders to storage this created temporal file. + _, path = mkstemp("-tardis-benchmark-hdf_buffer-test.hdf") + return path + + def create_temporal_file(self, suffix=None): + # TODO: Delete this files after ASV runs the benchmarks. + # ASV create a temporal directory in runtime per test: `tmpiuxngvlv`. + # The ASV and ASV_Runner, not has some way to get this temporal directory. + # The idea is use this temporal folders to storage this created temporal file. + suffix_str = "" if suffix is None else f"-{suffix}" + _, path = mkstemp(suffix_str) + return path + + @property + def gamma_ray_simulation_state(self): + self.gamma_ray_config.model.structure.velocity.start = 1.0 * u.km / u.s + self.gamma_ray_config.model.structure.density.rho_0 = ( + 5.0e2 * u.g / u.cm**3 + ) + self.gamma_ray_config.supernova.time_explosion = 150 * u.d + + return SimulationState.from_config( + self.gamma_ray_config, atom_data=self.atomic_dataset + ) + + @property + def gamma_ray_config(self): + yml_path = f"{self.example_configuration_dir}/tardis_configv1_density_exponential_nebular_multi_isotope.yml" + + return config_reader.Configuration.from_yaml(yml_path) + + @property + def example_model_file_dir(self): + return self.get_absolute_path("tardis/io/model/readers/tests/data") + + @property + def kurucz_atomic_data(self) -> AtomData: + return deepcopy(self.atomic_dataset) + + @property + def example_csvy_file_dir(self): + return self.get_absolute_path("tardis/model/tests/data/") + + @property + def simulation_verysimple(self): + atomic_data = deepcopy(self.atomic_dataset) + sim = Simulation.from_config( + self.config_verysimple, atom_data=atomic_data + ) + sim.iterate(4000) + return sim + + @property + def config_verysimple(self): + return Configuration.from_yaml( + f"{self.example_configuration_dir}/tardis_configv1_verysimple.yml" + ) + + class CustomPyTestRequest: + def __init__( + self, + tardis_regression_data_path: str, + node_name: str, + node_module_name: str, + regression_data_dir: str, + ): + self.tardis_regression_data_path = tardis_regression_data_path + self.node_name = node_name + self.node_module_name = node_module_name + self.regression_data_dir = regression_data_dir + + @property + def config(self): + class SubClass: + @staticmethod + def getoption(option): + if option == "--tardis-regression-data": + return self.tardis_regression_data_path + return None + + return SubClass() + + @property + def node(self): + class SubClass: + def __init__(self, parent): + self.parent = parent + + @property + def name(self): + return self.parent.node_name + + @property + def module(self): + class SubSubClass: + def __init__(self, parent): + self.parent = parent + + @property + def __name__(self): + return self.parent.node_module_name + + return SubSubClass(self.parent) + + return SubClass(self) + + @property + def cls(self): + return None + + @property + def relative_regression_data_dir(self): + return self.regression_data_dir + + @staticmethod + def regression_data(request: CustomPyTestRequest): + return RegressionData(request) + + @property + def packet(self): + return RPacket( + r=7.5e14, + nu=self.verysimple_packet_collection.initial_nus[0], + mu=self.verysimple_packet_collection.initial_mus[0], + energy=self.verysimple_packet_collection.initial_energies[0], + seed=1963, + index=0, + ) + + @property + def verysimple_packet_collection(self): + return ( + self.nb_simulation_verysimple.transport.transport_state.packet_collection + ) + + @property + def nb_simulation_verysimple(self): + atomic_data = deepcopy(self.atomic_dataset) + sim = Simulation.from_config( + self.config_verysimple, atom_data=atomic_data + ) + sim.iterate(10) + return sim + + @property + def verysimple_time_explosion(self): + model = self.nb_simulation_verysimple.simulation_state + return model.time_explosion.cgs.value + + @property + def verysimple_opacity_state(self): + return opacity_state_initialize( + self.nb_simulation_verysimple.plasma, + line_interaction_type="macroatom", + disable_line_scattering=self.nb_simulation_verysimple.transport.montecarlo_configuration.DISABLE_LINE_SCATTERING, + continuum_processes_enabled=self.nb_simulation_verysimple.transport.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + ) + + @property + def verysimple_enable_full_relativity(self): + return self.nb_simulation_verysimple.transport.enable_full_relativity + + @property + def verysimple_disable_line_scattering(self): + return ( + self.nb_simulation_verysimple.transport.montecarlo_configuration.DISABLE_LINE_SCATTERING + ) + + @property + def verysimple_continuum_processes_enabled(self): + return ( + self.nb_simulation_verysimple.transport.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED + ) + + @property + def verysimple_tau_russian(self): + return ( + self.nb_simulation_verysimple.transport.montecarlo_configuration.VPACKET_TAU_RUSSIAN + ) + + @property + def verysimple_survival_probability(self): + return ( + self.nb_simulation_verysimple.transport.montecarlo_configuration.SURVIVAL_PROBABILITY + ) + + @property + def static_packet(self): + return RPacket( + r=7.5e14, + nu=0.4, + mu=0.3, + energy=0.9, + seed=1963, + index=0, + ) + + @property + def set_seed_fixture(self): + def set_seed(value): + np.random.seed(value) + + return njit(set_seed) + + @property + def verysimple_3vpacket_collection(self): + spectrum_frequency = ( + self.nb_simulation_verysimple.transport.spectrum_frequency.value + ) + return VPacketCollection( + source_rpacket_index=0, + spectrum_frequency=spectrum_frequency, + number_of_vpackets=3, + v_packet_spawn_start_frequency=0, + v_packet_spawn_end_frequency=np.inf, + temporary_v_packet_bins=0, + ) + + @property + def verysimple_numba_radial_1d_geometry(self): + return ( + self.nb_simulation_verysimple.simulation_state.geometry.to_numba() + ) + + @property + def simulation_verysimple_vpacket_tracking(self): + atomic_data = deepcopy(self.atomic_dataset) + sim = Simulation.from_config( + self.config_verysimple, + atom_data=atomic_data, + virtual_packet_logging=True, + ) + sim.last_no_of_packets = 4000 + sim.run_final() + return sim + + @property + def generate_reference(self): + # TODO: Investigate how to get the `--generate-reference` parameter passed in the command line. + # `request.config.getoption("--generate-reference")` + option = None + if option is None: + return False + else: + return option + + @property + def tardis_ref_data(self): + # TODO: This function is not working in the benchmarks. + if self.generate_reference: + mode = "w" + else: + mode = "r" + with pd.HDFStore( + f"{self.tardis_ref_path}/unit_test_data.h5", mode=mode + ) as store: + yield store diff --git a/benchmarks/data/tardis_configv1_benchmark.yml b/benchmarks/data/tardis_configv1_benchmark.yml new file mode 100644 index 00000000000..578cd76b1f7 --- /dev/null +++ b/benchmarks/data/tardis_configv1_benchmark.yml @@ -0,0 +1,49 @@ +tardis_config_version: v1.0 + +supernova: + luminosity_requested: 2.8e9 solLum + time_explosion: 13 day + +atom_data: kurucz_cd23_chianti_H_He.h5 + +model: + structure: + type: specific + velocity: + start: 1.1e4 km/s + stop: 2.0e4 km/s + num: 20 + density: + type: branch85_w7 + abundances: + type: uniform + O: 0.19 + Mg: 0.03 + Si: 0.52 + S: 0.19 + Ar: 0.04 + Ca: 0.03 + +plasma: + ionization: lte + excitation: lte + radiative_rates_type: dilute-blackbody + line_interaction_type: macroatom + +montecarlo: + seed: 23111963 + no_of_packets : 400 + iterations: 2 + last_no_of_packets: -1 + no_of_virtual_packets: 1 + convergence_strategy: + type: damped + damping_constant: 0.5 + threshold: 0.05 + lock_t_inner_cycles: 1 + t_inner_update_exponent: -0.5 + +spectrum: + start: 500 angstrom + stop: 20000 angstrom + num: 200 diff --git a/benchmarks/run_tardis.py b/benchmarks/run_tardis.py new file mode 100644 index 00000000000..8fca11f6030 --- /dev/null +++ b/benchmarks/run_tardis.py @@ -0,0 +1,25 @@ +""" +Basic TARDIS Benchmark. +""" + +from benchmarks.benchmark_base import BenchmarkBase +from tardis import run_tardis +from tardis.io.configuration.config_reader import Configuration + + +class BenchmarkRunTardis(BenchmarkBase): + """ + Class to benchmark the `run tardis` function. + """ + + def __init__(self): + super().__init__() + self.config = None + + def setup(self): + filename = "data/tardis_configv1_benchmark.yml" + path = self.get_relative_path(filename) + self.config = Configuration.from_yaml(path) + + def time_run_tardis(self): + run_tardis(self.config, log_level="ERROR", show_progress_bars=False) diff --git a/benchmarks/transport_montecarlo_interaction.py b/benchmarks/transport_montecarlo_interaction.py new file mode 100644 index 00000000000..b27d3ac9396 --- /dev/null +++ b/benchmarks/transport_montecarlo_interaction.py @@ -0,0 +1,113 @@ +""" +Basic TARDIS Benchmark. +""" + +import numpy as np +from asv_runner.benchmarks.mark import parameterize, skip_benchmark + +import tardis.transport.montecarlo.interaction as interaction +from benchmarks.benchmark_base import BenchmarkBase +from tardis.transport.montecarlo.numba_interface import ( + LineInteractionType, +) + + +@skip_benchmark +class BenchmarkMontecarloMontecarloNumbaInteraction(BenchmarkBase): + """ + Class to benchmark the numba interaction function. + """ + + def time_thomson_scatter(self): + packet = self.packet + init_mu = packet.mu + init_nu = packet.nu + init_energy = packet.energy + time_explosion = self.verysimple_time_explosion + enable_full_relativity = self.verysimple_enable_full_relativity + + interaction.thomson_scatter( + packet, time_explosion, enable_full_relativity + ) + + assert np.abs(packet.mu - init_mu) > 1e-7 + assert np.abs(packet.nu - init_nu) > 1e-7 + assert np.abs(packet.energy - init_energy) > 1e-7 + + @parameterize( + { + "Line interaction type": [ + LineInteractionType.SCATTER, + LineInteractionType.DOWNBRANCH, + LineInteractionType.MACROATOM, + ], + } + ) + def time_line_scatter(self, line_interaction_type): + packet = self.packet + init_mu = packet.mu + init_nu = packet.nu + init_energy = packet.energy + packet.initialize_line_id( + self.verysimple_opacity_state, + self.verysimple_time_explosion, + self.verysimple_enable_full_relativity, + ) + time_explosion = self.verysimple_time_explosion + + interaction.line_scatter( + packet, + time_explosion, + line_interaction_type, + self.verysimple_opacity_state, + self.verysimple_enable_full_relativity, + self.verysimple_continuum_processes_enabled, + ) + + assert np.abs(packet.mu - init_mu) > 1e-7 + assert np.abs(packet.nu - init_nu) > 1e-7 + assert np.abs(packet.energy - init_energy) > 1e-7 + + @parameterize( + { + "Test packet": [ + { + "mu": 0.8599443103322428, + "emission_line_id": 1000, + "energy": 0.9114437898710559, + }, + { + "mu": -0.6975116557422458, + "emission_line_id": 2000, + "energy": 0.8803098648913266, + }, + { + "mu": -0.7115661419975774, + "emission_line_id": 0, + "energy": 0.8800385929341252, + }, + ] + } + ) + def time_line_emission(self, test_packet): + emission_line_id = test_packet["emission_line_id"] + packet = self.packet + packet.mu = test_packet["mu"] + packet.energy = test_packet["energy"] + packet.initialize_line_id( + self.verysimple_opacity_state, + self.verysimple_time_explosion, + self.verysimple_enable_full_relativity, + ) + + time_explosion = self.verysimple_time_explosion + + interaction.line_emission( + packet, + emission_line_id, + time_explosion, + self.verysimple_opacity_state, + self.verysimple_enable_full_relativity, + ) + + assert packet.next_line_id == emission_line_id + 1 diff --git a/benchmarks/transport_montecarlo_numba_formal_integral_p.py b/benchmarks/transport_montecarlo_numba_formal_integral_p.py new file mode 100644 index 00000000000..0e084505404 --- /dev/null +++ b/benchmarks/transport_montecarlo_numba_formal_integral_p.py @@ -0,0 +1,176 @@ +""" +Basic TARDIS Benchmark. +""" + +import numpy as np +from asv_runner.benchmarks.mark import parameterize, skip_benchmark + +import tardis.transport.montecarlo.formal_integral as formal_integral +from benchmarks.benchmark_base import BenchmarkBase +from tardis import constants as c +from tardis.model.geometry.radial1d import NumbaRadial1DGeometry +from tardis.util.base import intensity_black_body + + +class BenchmarkMontecarloMontecarloNumbaNumbaFormalIntegral(BenchmarkBase): + """ + Class to benchmark the numba formal integral function. + """ + + @parameterize( + { + "nu": [1e14, 0, 1], + "temperature": [1e4, 1, 1], + } + ) + def time_intensity_black_body(self, nu, temperature): + func = formal_integral.intensity_black_body + actual = func(nu, temperature) + print(actual, type(actual)) + intensity_black_body(nu, temperature) + + @parameterize({"N": (1e2, 1e3, 1e4, 1e5)}) + def time_trapezoid_integration(self, n): + func = formal_integral.trapezoid_integration + h = 1.0 + n = int(n) + data = np.random.random(n) + + func(data, h) + np.trapz(data) + + @staticmethod + def calculate_z(r, p): + return np.sqrt(r * r - p * p) + + TESTDATA = [ + np.linspace(1, 2, 3, dtype=np.float64), + np.linspace(0, 1, 3), + # np.linspace(1, 2, 10, dtype=np.float64), + ] + + def formal_integral_geometry(self, r): + # NOTE: PyTest is generating a full matrix with all the permutations. + # For the `time_calculate_z` function with values: [0.0, 0.5, 1.0] + # - p=0.0, formal_integral_geometry0-0.0, param["r"]: [1. 1.5 2. ] + # - p=0.5, formal_integral_geometry0-0.5, param["r"]: [1. 1.5 2. ] + # - p=1.0, formal_integral_geometry0-1.0, param["r"]: [1. 1.5 2. ] + # - p=0.0, formal_integral_geometry1-0.0, param["r"]: [0. 0.5 1. ] + # - p=1.0, formal_integral_geometry1-1.0, param["r"]: [0. 0.5 1. ] + # Same for `test_populate_z_photosphere` function + # And for `test_populate_z_shells` function + # - p=1e-05, formal_integral_geometry0-1e-05, param["r"]: [1. 1.5 2. ] + # - p=0.5, formal_integral_geometry0-0.5, param["r"]: [1. 1.5 2. ] + # - p=0.99, formal_integral_geometry0-0.99, param["r"]: [1. 1.5 2. ] + # - p=1, formal_integral_geometry0-1, param["r"]: [1. 1.5 2. ] + # - p=1e-05, formal_integral_geometry1-1e-05, param["r"]: [0. 0.5 1. ] + # - p=0.5, formal_integral_geometry1-0.5, param["r"]: [0. 0.5 1. ] + # - p=0.99, formal_integral_geometry1-0.99, param["r"]: [0. 0.5 1. ] + # - p=1, formal_integral_geometry1-1, param["r"]: [0. 0.5 1. ] + geometry = NumbaRadial1DGeometry( + r[:-1], + r[1:], + r[:-1] * c.c.cgs.value, + r[1:] * c.c.cgs.value, + ) + return geometry + + @property + def time_explosion(self): + # previously used model value that passes tests + # time taken for a photon to move 1 cm + return 1 / c.c.cgs.value + + @parameterize({"p": [0.0, 0.5, 1.0], "Test data": TESTDATA}) + def time_calculate_z(self, p, test_data): + func = formal_integral.calculate_z + inv_t = 1.0 / self.time_explosion + len(self.formal_integral_geometry(test_data).r_outer) + r_outer = self.formal_integral_geometry(test_data).r_outer + + for r in r_outer: + actual = func(r, p, inv_t) + if p >= r: + assert actual == 0 + else: + np.sqrt(r * r - p * p) * formal_integral.C_INV * inv_t + + @skip_benchmark + @parameterize({"p": [0, 0.5, 1], "Test data": TESTDATA}) + def time_populate_z_photosphere(self, p, test_data): + formal_integral.FormalIntegrator( + self.formal_integral_geometry(test_data), None, None + ) + func = formal_integral.populate_z + size = len(self.formal_integral_geometry(test_data).r_outer) + r_inner = self.formal_integral_geometry(test_data).r_inner + self.formal_integral_geometry(test_data).r_outer + + p = r_inner[0] * p + oz = np.zeros_like(r_inner) + oshell_id = np.zeros_like(oz, dtype=np.int64) + + n = func( + self.formal_integral_geometry(test_data), + self.formal_integral_geometry(test_data), + p, + oz, + oshell_id, + ) + assert n == size + + @skip_benchmark + @parameterize({"p": [1e-5, 0.5, 0.99, 1], "Test data": TESTDATA}) + def time_populate_z_shells(self, p, test_data): + formal_integral.FormalIntegrator( + self.formal_integral_geometry(test_data), None, None + ) + func = formal_integral.populate_z + + size = len(self.formal_integral_geometry(test_data).r_inner) + r_inner = self.formal_integral_geometry(test_data).r_inner + r_outer = self.formal_integral_geometry(test_data).r_outer + + p = r_inner[0] + (r_outer[-1] - r_inner[0]) * p + idx = np.searchsorted(r_outer, p, side="right") + + oz = np.zeros(size * 2) + oshell_id = np.zeros_like(oz, dtype=np.int64) + + offset = size - idx + + expected_n = (offset) * 2 + expected_oz = np.zeros_like(oz) + expected_oshell_id = np.zeros_like(oshell_id) + + # Calculated way to determine which shells get hit + expected_oshell_id[:expected_n] = ( + np.abs(np.arange(0.5, expected_n, 1) - offset) - 0.5 + idx + ) + + expected_oz[0:offset] = 1 + self.calculate_z( + r_outer[np.arange(size, idx, -1) - 1], p + ) + expected_oz[offset:expected_n] = 1 - self.calculate_z( + r_outer[np.arange(idx, size, 1)], p + ) + + n = func( + self.formal_integral_geometry(test_data), + self.formal_integral_geometry(test_data), + p, + oz, + oshell_id, + ) + + assert n == expected_n + + @parameterize({"N": [100, 1000, 10000]}) + def time_calculate_p_values(self, n): + r = 1.0 + func = formal_integral.calculate_p_values + + expected = r / (n - 1) * np.arange(0, n, dtype=np.float64) + np.zeros_like(expected, dtype=np.float64) + + func(r, n) diff --git a/benchmarks/transport_montecarlo_numba_interface.py b/benchmarks/transport_montecarlo_numba_interface.py new file mode 100644 index 00000000000..bb9ac4e5b8d --- /dev/null +++ b/benchmarks/transport_montecarlo_numba_interface.py @@ -0,0 +1,82 @@ +""" +Basic TARDIS Benchmark. +""" + +import numpy as np +from asv_runner.benchmarks.mark import parameterize + +import tardis.opacities.opacity_state as numba_interface +from benchmarks.benchmark_base import BenchmarkBase + + +class BenchmarkMontecarloMontecarloNumbaNumbaInterface(BenchmarkBase): + """ + Class to benchmark the numba interface function. + """ + + @parameterize({"Input params": ["scatter", "macroatom", "downbranch"]}) + def time_opacity_state_initialize(self, input_params): + line_interaction_type = input_params + plasma = self.nb_simulation_verysimple.plasma + numba_interface.opacity_state_initialize( + plasma, + line_interaction_type, + self.verysimple_disable_line_scattering, + self.verysimple_continuum_processes_enabled, + ) + + if line_interaction_type == "scatter": + np.zeros(1, dtype=np.int64) + + def time_VPacketCollection_add_packet(self): + verysimple_3vpacket_collection = self.verysimple_3vpacket_collection + assert verysimple_3vpacket_collection.length == 0 + + nus = [3.0e15, 0.0, 1e15, 1e5] + energies = [0.4, 0.1, 0.6, 1e10] + initial_mus = [0.1, 0, 1, 0.9] + initial_rs = [3e42, 4.5e45, 0, 9.0e40] + last_interaction_in_nus = np.array( + [3.0e15, 0.0, 1e15, 1e5], dtype=np.float64 + ) + last_interaction_types = np.array([1, 1, 3, 2], dtype=np.int64) + last_interaction_in_ids = np.array([100, 0, 1, 1000], dtype=np.int64) + last_interaction_out_ids = np.array( + [1201, 123, 545, 1232], dtype=np.int64 + ) + last_interaction_shell_ids = np.array([2, -1, 6, 0], dtype=np.int64) + + for ( + nu, + energy, + initial_mu, + initial_r, + last_interaction_in_nu, + last_interaction_type, + last_interaction_in_id, + last_interaction_out_id, + last_interaction_shell_id, + ) in zip( + nus, + energies, + initial_mus, + initial_rs, + last_interaction_in_nus, + last_interaction_types, + last_interaction_in_ids, + last_interaction_out_ids, + last_interaction_shell_ids, + ): + verysimple_3vpacket_collection.add_packet( + nu, + energy, + initial_mu, + initial_r, + last_interaction_in_nu, + last_interaction_type, + last_interaction_in_id, + last_interaction_out_id, + last_interaction_shell_id, + ) + + assert verysimple_3vpacket_collection.length == 9 diff --git a/benchmarks/transport_montecarlo_opacities.py b/benchmarks/transport_montecarlo_opacities.py new file mode 100644 index 00000000000..c5fe0196f47 --- /dev/null +++ b/benchmarks/transport_montecarlo_opacities.py @@ -0,0 +1,91 @@ +""" +Basic TARDIS Benchmark. +""" + +from asv_runner.benchmarks.mark import parameterize + +import tardis.opacities.opacities as calculate_opacity +from benchmarks.benchmark_base import BenchmarkBase + + +class BenchmarkMontecarloMontecarloNumbaOpacities(BenchmarkBase): + """ + Class to benchmark the numba opacities function. + """ + + @parameterize( + { + "Electron number density": [ + 1.0e11, + 1e15, + 1e5, + ], + "Energy": [ + 511.0, + 255.5, + 511.0e7, + ], + } + ) + def time_compton_opacity_calculation(self, electron_number_density, energy): + calculate_opacity.compton_opacity_calculation( + energy, electron_number_density + ) + + @parameterize( + { + "Ejecta density": [ + 1.0, + 1e-2, + 1e-2, + 1e5, + ], + "Energy": [ + 511.0, + 255.5, + 255.5, + 511.0e7, + ], + "Iron group fraction": [ + 0.0, + 0.5, + 0.25, + 1.0, + ], + } + ) + def time_photoabsorption_opacity_calculation( + self, ejecta_density, energy, iron_group_fraction + ): + calculate_opacity.photoabsorption_opacity_calculation( + energy, ejecta_density, iron_group_fraction + ) + + @parameterize( + { + "Ejecta density": [ + 1.0, + 1e-2, + 1e-2, + 1e5, + ], + "Energy": [ + 511.0, + 1500, + 1200, + 511.0e7, + ], + "Iron group fraction": [ + 0.0, + 0.5, + 0.25, + 1.0, + ], + } + ) + def time_pair_creation_opacity_calculation( + self, ejecta_density, energy, iron_group_fraction + ): + calculate_opacity.pair_creation_opacity_calculation( + energy, ejecta_density, iron_group_fraction + ) diff --git a/benchmarks/transport_montecarlo_packet.py b/benchmarks/transport_montecarlo_packet.py new file mode 100644 index 00000000000..088cda90d7f --- /dev/null +++ b/benchmarks/transport_montecarlo_packet.py @@ -0,0 +1,316 @@ +""" +Basic TARDIS Benchmark. +""" + +import numpy as np +from asv_runner.benchmarks.mark import parameterize, skip_benchmark + +import tardis.transport.frame_transformations as frame_transformations +import tardis.transport.geometry.calculate_distances as calculate_distances +import tardis.transport.montecarlo.estimators.radfield_mc_estimators +import tardis.transport.montecarlo.opacities as opacities +import tardis.transport.montecarlo.r_packet as r_packet +import tardis.transport.montecarlo.r_packet_transport as r_packet_transport +import tardis.transport.montecarlo.utils as utils +from benchmarks.benchmark_base import BenchmarkBase +from tardis.model.geometry.radial1d import NumbaRadial1DGeometry +from tardis.transport.montecarlo.estimators.radfield_estimator_calcs import ( + update_line_estimators, +) + + +class BenchmarkMontecarloMontecarloNumbaPacket(BenchmarkBase): + """ + Class to benchmark the numba packet function. + """ + + @property + def geometry(self): + return NumbaRadial1DGeometry( + r_inner=np.array([6.912e14, 8.64e14], dtype=np.float64), + r_outer=np.array([8.64e14, 1.0368e15], dtype=np.float64), + v_inner=np.array([-1, -1], dtype=np.float64), + v_outer=np.array([-1, -1], dtype=np.float64), + ) + + @property + def model(self): + return 5.2e7 + + @property + def estimators(self): + return tardis.transport.montecarlo.estimators.radfield_mc_estimators.RadiationFieldMCEstimators( + j_estimator=np.array([0.0, 0.0], dtype=np.float64), + nu_bar_estimator=np.array([0.0, 0.0], dtype=np.float64), + j_blue_estimator=np.array( + [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], dtype=np.float64 + ), + Edotlu_estimator=np.array( + [[0.0, 0.0, 1.0], [0.0, 0.0, 1.0]], dtype=np.float64 + ), + photo_ion_estimator=np.empty((0, 0), dtype=np.float64), + stim_recomb_estimator=np.empty((0, 0), dtype=np.float64), + bf_heating_estimator=np.empty((0, 0), dtype=np.float64), + stim_recomb_cooling_estimator=np.empty((0, 0), dtype=np.float64), + photo_ion_estimator_statistics=np.empty((0, 0), dtype=np.int64), + ) + + @parameterize( + { + "Packet params": [ + {"mu": 0.3, "r": 7.5e14}, + {"mu": -0.3, "r": 7.5e13}, + {"mu": -0.3, "r": 7.5e14}, + ] + } + ) + def time_calculate_distance_boundary(self, packet_params): + mu = packet_params["mu"] + r = packet_params["r"] + + calculate_distances.calculate_distance_boundary( + r, mu, self.geometry.r_inner[0], self.geometry.r_outer[0] + ) + + @parameterize( + { + "Parameters": [ + { + "packet": {"nu_line": 0.1, "is_last_line": True}, + "expected": None, + "enable_full_relativity": True, + }, + { + "packet": {"nu_line": 0.2, "is_last_line": False}, + "expected": None, + "enable_full_relativity": True, + }, + { + "packet": {"nu_line": 0.5, "is_last_line": False}, + "expected": utils.MonteCarloException, + "enable_full_relativity": False, + }, + { + "packet": {"nu_line": 0.6, "is_last_line": False}, + "expected": utils.MonteCarloException, + "enable_full_relativity": False, + }, + ] + } + ) + def time_calculate_distance_line(self, parameters): + packet_params = parameters["packet"] + expected_params = parameters["expected"] + nu_line = packet_params["nu_line"] + is_last_line = packet_params["is_last_line"] + enable_full_relativity = parameters["enable_full_relativity"] + + time_explosion = self.model + doppler_factor = frame_transformations.get_doppler_factor( + self.static_packet.r, + self.static_packet.mu, + time_explosion, + enable_full_relativity, + ) + comov_nu = self.static_packet.nu * doppler_factor + + obtained_tardis_error = None + try: + calculate_distances.calculate_distance_line( + self.static_packet, + comov_nu, + is_last_line, + nu_line, + time_explosion, + enable_full_relativity, + ) + except utils.MonteCarloException: + obtained_tardis_error = utils.MonteCarloException + + assert obtained_tardis_error == expected_params + + @parameterize( + { + "Parameters": [ + { + "electron_density": 1e-5, + "tua_event": 1e10, + }, + {"electron_density": 1.0, "tua_event": 1e10}, + ] + } + ) + def time_calculate_distance_electron(self, parameters): + electron_density = parameters["electron_density"] + tau_event = parameters["tua_event"] + calculate_distances.calculate_distance_electron( + electron_density, tau_event + ) + + @parameterize( + { + "Parameters": [ + { + "electron_density": 1e-5, + "distance": 1.0, + }, + { + "electron_density": 1e10, + "distance": 1e10, + }, + { + "electron_density": -1, + "distance": 0, + }, + { + "electron_density": -1e10, + "distance": -1e10, + }, + ] + } + ) + def time_calculate_tau_electron(self, parameters): + electron_density = parameters["electron_density"] + distance = parameters["distance"] + opacities.calculate_tau_electron(electron_density, distance) + + def time_get_random_mu(self): + self.set_seed_fixture(1963) + + output1 = utils.get_random_mu() + assert output1 == 0.9136407866175174 + + @parameterize( + { + "Parameters": [ + { + "cur_line_id": 0, + "distance_trace": 1e12, + "time_explosion": 5.2e7, + "enable_full_relativity": True, + }, + { + "cur_line_id": 0, + "distance_trace": 0, + "time_explosion": 5.2e7, + "enable_full_relativity": True, + }, + { + "cur_line_id": 1, + "distance_trace": 1e5, + "time_explosion": 1e10, + "enable_full_relativity": False, + }, + ] + } + ) + def time_update_line_estimators(self, parameters): + cur_line_id = parameters["cur_line_id"] + distance_trace = parameters["distance_trace"] + time_explosion = parameters["time_explosion"] + enable_full_relativity = parameters["enable_full_relativity"] + update_line_estimators( + self.estimators, + self.static_packet, + cur_line_id, + distance_trace, + time_explosion, + enable_full_relativity, + ) + + @parameterize( + { + "Parameters": [ + { + "current_shell_id": 132, + "delta_shell": 11, + "no_of_shells": 132, + }, + { + "current_shell_id": 132, + "delta_shell": 1, + "no_of_shells": 133, + }, + { + "current_shell_id": 132, + "delta_shell": 2, + "no_of_shells": 133, + }, + ] + } + ) + def time_move_packet_across_shell_boundary_emitted(self, parameters): + current_shell_id = parameters["current_shell_id"] + delta_shell = parameters["delta_shell"] + no_of_shells = parameters["no_of_shells"] + packet = self.packet + packet.current_shell_id = current_shell_id + r_packet_transport.move_packet_across_shell_boundary( + packet, delta_shell, no_of_shells + ) + assert packet.status == r_packet.PacketStatus.EMITTED + + @skip_benchmark + @parameterize( + { + "Parameters": [ + { + "current_shell_id": 132, + "delta_shell": 132, + "no_of_shells": 132, + }, + { + "current_shell_id": -133, + "delta_shell": -133, + "no_of_shells": -1e9, + }, + { + "current_shell_id": 132, + "delta_shell": 133, + "no_of_shells": 133, + }, + ] + } + ) + def time_move_packet_across_shell_boundary_reabsorbed(self, parameters): + current_shell_id = parameters["current_shell_id"] + delta_shell = parameters["delta_shell"] + no_of_shells = parameters["no_of_shells"] + packet = self.packet + packet.current_shell_id = current_shell_id + r_packet_transport.move_packet_across_shell_boundary( + packet, delta_shell, no_of_shells + ) + assert packet.status == r_packet.PacketStatus.REABSORBED + + @parameterize( + { + "Parameters": [ + { + "current_shell_id": 132, + "delta_shell": -1, + "no_of_shells": 199, + }, + { + "current_shell_id": 132, + "delta_shell": 0, + "no_of_shells": 132, + }, + { + "current_shell_id": 132, + "delta_shell": 20, + "no_of_shells": 154, + }, + ] + } + ) + def time_move_packet_across_shell_boundary_increment(self, parameters): + current_shell_id = parameters["current_shell_id"] + delta_shell = parameters["delta_shell"] + no_of_shells = parameters["no_of_shells"] + packet = self.packet + packet.current_shell_id = current_shell_id + r_packet_transport.move_packet_across_shell_boundary( + packet, delta_shell, no_of_shells + ) + assert packet.current_shell_id == current_shell_id + delta_shell diff --git a/benchmarks/transport_montecarlo_r_packet.py b/benchmarks/transport_montecarlo_r_packet.py new file mode 100644 index 00000000000..3ee85eef518 --- /dev/null +++ b/benchmarks/transport_montecarlo_r_packet.py @@ -0,0 +1,67 @@ +""" +Basic TARDIS Benchmark. +""" + +from copy import deepcopy + +from benchmarks.benchmark_base import BenchmarkBase +from tardis.base import run_tardis +from tardis.transport.montecarlo.packet_trackers import ( + rpacket_trackers_to_dataframe, +) + + +class BenchmarkMontecarloMontecarloNumbaRPacket(BenchmarkBase): + """ + Class to benchmark the numba R packet function. + """ + + @property + def simulation_rpacket_tracking_enabled(self): + config_verysimple = self.config_verysimple + config_verysimple.montecarlo.iterations = 3 + config_verysimple.montecarlo.no_of_packets = 4000 + config_verysimple.montecarlo.last_no_of_packets = -1 + config_verysimple.spectrum.virtual.virtual_packet_logging = True + config_verysimple.montecarlo.no_of_virtual_packets = 1 + config_verysimple.montecarlo.tracking.track_rpacket = True + config_verysimple.spectrum.num = 2000 + atomic_data = deepcopy(self.atomic_dataset) + sim = run_tardis( + config_verysimple, + atom_data=atomic_data, + show_convergence_plots=False, + ) + return sim + + def time_rpacket_trackers_to_dataframe(self): + sim = self.simulation_rpacket_tracking_enabled + transport_state = sim.transport.transport_state + rtracker_df = rpacket_trackers_to_dataframe( + transport_state.rpacket_tracker + ) + + # check df shape and column names + assert rtracker_df.shape == ( + sum( + [len(tracker.r) for tracker in transport_state.rpacket_tracker] + ), + 8, + ) + + # check all data with rpacket_tracker + expected_rtrackers = [] + for rpacket in transport_state.rpacket_tracker: + for rpacket_step_no in range(len(rpacket.r)): + expected_rtrackers.append( + [ + rpacket.status[rpacket_step_no], + rpacket.seed, + rpacket.r[rpacket_step_no], + rpacket.nu[rpacket_step_no], + rpacket.mu[rpacket_step_no], + rpacket.energy[rpacket_step_no], + rpacket.shell_id[rpacket_step_no], + rpacket.interaction_type[rpacket_step_no], + ] + ) diff --git a/benchmarks/transport_montecarlo_vpacket.py b/benchmarks/transport_montecarlo_vpacket.py new file mode 100644 index 00000000000..a1141a89c65 --- /dev/null +++ b/benchmarks/transport_montecarlo_vpacket.py @@ -0,0 +1,153 @@ +""" +Basic TARDIS Benchmark. +""" + +import numpy as np + +import tardis.transport.montecarlo.vpacket as vpacket +from benchmarks.benchmark_base import BenchmarkBase +from tardis.transport.frame_transformations import ( + get_doppler_factor, +) + + +class BenchmarkMontecarloMontecarloNumbaVpacket(BenchmarkBase): + """ + Class to benchmark the single packet loop function. + """ + + @property + def v_packet(self): + return vpacket.VPacket( + r=7.5e14, + nu=4e15, + mu=0.3, + energy=0.9, + current_shell_id=0, + next_line_id=0, + index=0, + ) + + def v_packet_initialize_line_id( + self, v_packet, opacity_state, time_explosion, enable_full_relativity + ): + inverse_line_list_nu = opacity_state.line_list_nu[::-1] + doppler_factor = get_doppler_factor( + v_packet.r, v_packet.mu, time_explosion, enable_full_relativity + ) + comov_nu = v_packet.nu * doppler_factor + next_line_id = len(opacity_state.line_list_nu) - np.searchsorted( + inverse_line_list_nu, comov_nu + ) + v_packet.next_line_id = next_line_id + + def time_trace_vpacket_within_shell(self): + v_packet = self.v_packet + verysimple_numba_radial_1d_geometry = ( + self.verysimple_numba_radial_1d_geometry + ) + verysimple_time_explosion = self.verysimple_time_explosion + verysimple_opacity_state = self.verysimple_opacity_state + enable_full_relativity = self.verysimple_enable_full_relativity + continuum_processes_enabled = ( + self.verysimple_continuum_processes_enabled + ) + + # Give the vpacket a reasonable line ID + self.v_packet_initialize_line_id( + v_packet, + verysimple_opacity_state, + verysimple_time_explosion, + enable_full_relativity, + ) + + ( + tau_trace_combined, + distance_boundary, + delta_shell, + ) = vpacket.trace_vpacket_within_shell( + v_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + enable_full_relativity, + continuum_processes_enabled, + ) + + assert delta_shell == 1 + + def time_trace_vpacket(self): + v_packet = self.v_packet + verysimple_numba_radial_1d_geometry = ( + self.verysimple_numba_radial_1d_geometry + ) + verysimple_time_explosion = self.verysimple_time_explosion + verysimple_opacity_state = self.verysimple_opacity_state + enable_full_relativity = self.verysimple_enable_full_relativity + continuum_processes_enabled = ( + self.verysimple_continuum_processes_enabled + ) + tau_russian = self.verysimple_tau_russian + survival_probability = self.verysimple_survival_probability + + # Set seed because of RNG in trace_vpacket + np.random.seed(1) + + # Give the vpacket a reasonable line ID + self.v_packet_initialize_line_id( + v_packet, + verysimple_opacity_state, + verysimple_time_explosion, + enable_full_relativity, + ) + + tau_trace_combined = vpacket.trace_vpacket( + v_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + tau_russian, + survival_probability, + enable_full_relativity, + continuum_processes_enabled, + ) + + assert v_packet.next_line_id == 2773 + assert v_packet.current_shell_id == 1 + + @property + def broken_packet(self): + return vpacket.VPacket( + r=1286064000000000.0, + nu=1660428912896553.2, + mu=0.4916053094346575, + energy=2.474533071386993e-07, + index=3, + current_shell_id=0, + next_line_id=5495, + ) + + def time_trace_bad_vpacket(self): + broken_packet = self.broken_packet + verysimple_numba_radial_1d_geometry = ( + self.verysimple_numba_radial_1d_geometry + ) + enable_full_relativity = self.verysimple_enable_full_relativity + verysimple_time_explosion = self.verysimple_time_explosion + verysimple_opacity_state = self.verysimple_opacity_state + continuum_processes_enabled = ( + self.verysimple_continuum_processes_enabled + ) + tau_russian = self.verysimple_tau_russian + survival_probability = self.verysimple_survival_probability + + vpacket.trace_vpacket( + broken_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + tau_russian, + survival_probability, + enable_full_relativity, + continuum_processes_enabled, + ) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_montecarlo_logger.py b/benchmarks/util/__init__.py similarity index 100% rename from tardis/montecarlo/montecarlo_numba/tests/test_montecarlo_logger.py rename to benchmarks/util/__init__.py diff --git a/benchmarks/util/base.py b/benchmarks/util/base.py new file mode 100644 index 00000000000..7dd61629e3e --- /dev/null +++ b/benchmarks/util/base.py @@ -0,0 +1,20 @@ +from os.path import dirname, realpath, join +from pathlib import Path, PosixPath + + +class Base: + @staticmethod + def get_path(partial_path: str) -> Path: + base_path = dirname(realpath(__file__)) + path = Path(base_path) / Path(partial_path) + return path + + @property + def tardis_ref_path(self) -> Path: + # TODO: This route is fixed but needs to get from the arguments given in the command line. + # /app/tardis-refdata + return Path("/app/tardis-refdata") + + @property + def example_configuration_dir(self) -> Path: + return self.get_path("../../tardis/io/configuration/tests/data") diff --git a/benchmarks/util/nlte.py b/benchmarks/util/nlte.py new file mode 100644 index 00000000000..7cfed4ef4dd --- /dev/null +++ b/benchmarks/util/nlte.py @@ -0,0 +1,78 @@ +from collections import OrderedDict +from copy import deepcopy +from pathlib import Path + +from benchmarks.util.base import Base +from tardis.io.atom_data import AtomData +from tardis.io.configuration.config_reader import Configuration +from tardis.io.util import yaml_load_file, YAMLLoader +from tardis.model import SimulationState + + +class NLTE: + def __init__(self): + self.__base = Base() + + @property + def tardis_config_verysimple_nlte(self) -> OrderedDict: + path: str = ( + "../../tardis/io/configuration/tests/data/tardis_configv1_nlte.yml" + ) + filename: Path = self.__base.get_path(path) + + return yaml_load_file( + filename, + YAMLLoader, + ) + + @property + def nlte_raw_model_root(self) -> SimulationState: + return SimulationState.from_config( + self.tardis_model_config_nlte_root, self.nlte_atom_data + ) + + @property + def nlte_raw_model_lu(self) -> SimulationState: + return SimulationState.from_config( + self.tardis_model_config_nlte_lu, self.nlte_atom_data + ) + + @property + def nlte_atom_data(self) -> AtomData: + atomic_data = deepcopy(self.nlte_atomic_dataset) + return atomic_data + + @property + def nlte_atomic_dataset(self) -> AtomData: + nlte_atomic_data = AtomData.from_hdf(self.nlte_atomic_data_fname) + return nlte_atomic_data + + @property + def nlte_atomic_data_fname(self) -> str: + atomic_data_fname = ( + f"{self.__base.tardis_ref_path}/nlte_atom_data/TestNLTE_He_Ti.h5" + ) + + if not Path(atomic_data_fname).exists(): + atom_data_missing_str = ( + f"Atomic datafiles {atomic_data_fname} does not seem to exist" + ) + raise Exception(atom_data_missing_str) + + return atomic_data_fname + + @property + def tardis_model_config_nlte_root(self) -> Configuration: + config = Configuration.from_yaml( + f"{self.__base.example_configuration_dir}/tardis_configv1_nlte.yml" + ) + config.plasma.nlte_solver = "root" + return config + + @property + def tardis_model_config_nlte_lu(self) -> Configuration: + config = Configuration.from_yaml( + f"{self.__base.example_configuration_dir}/tardis_configv1_nlte.yml" + ) + config.plasma.nlte_solver = "lu" + return config diff --git a/cliff.toml b/cliff.toml new file mode 100644 index 00000000000..42fd21ddd6b --- /dev/null +++ b/cliff.toml @@ -0,0 +1,23 @@ +[changelog] +header = "## Changelog\n\n" +body = """ +### {{version}} ({{ timestamp | date(format="%Y/%m/%d %H:%M", timezone="America/New_York") }}) +{% for commit in commits %} + {%- if commit.github.pr_number -%} + - [{{commit.github.pr_number}}](https://github.com/tardis-sn/tardis/pull/{{commit.github.pr_number}}) {{ commit.github.pr_title | split(pat="\n") | first | trim }} ({{commit.github.pr_number}}) (@{{ commit.github.username }}) + {% endif -%} +{%- endfor -%} +""" + +trim = true +footer = "" +postprocessors = [{ pattern = "foo", replace = "bar"}] + +[git] +conventional_commits = false +filter_unconventional = false +sort_commits = "newest" + +[remote.github] +owner = "tardis-sn" +repo = "tardis" diff --git a/conda-linux-64.lock b/conda-linux-64.lock new file mode 100644 index 00000000000..d7f25021a46 --- /dev/null +++ b/conda-linux-64.lock @@ -0,0 +1,321 @@ +# Generated by conda-lock. +# platform: linux-64 +# input_hash: 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+https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.8-pyhd8ed1ab_0.conda#611a35a27914fac3aa37611a6fe40bb5 +https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-bibtex-2.6.2-pyhd8ed1ab_0.conda#ac0947374ec8b703181808828bf5dfec +https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-devhelp-1.0.6-pyhd8ed1ab_0.conda#d7e4954df0d3aea2eacc7835ad12671d +https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.5-pyhd8ed1ab_0.conda#7e1e7437273682ada2ed5e9e9714b140 +https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-jquery-4.1-pyhd8ed1ab_0.conda#914897066d5873acfb13e75705276ad1 +https://conda.anaconda.org/conda-forge/noarch/sphinx-astropy-1.9.1-pyhd8ed1ab_0.conda#b6a0939e7b6b3a854b8c8f04606da1a7 +https://conda.anaconda.org/conda-forge/noarch/sphinx_rtd_theme-2.0.0-pyha770c72_0.conda#baf6d9a33df1a789ca55e3b404c7ea28 +https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-qthelp-1.0.7-pyhd8ed1ab_0.conda#26acae54b06f178681bfb551760f5dd1 +https://conda.anaconda.org/conda-forge/noarch/sphinx-7.3.7-pyhd8ed1ab_0.conda#7b1465205e28d75d2c0e1a868ee00a67 +https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-serializinghtml-1.1.10-pyhd8ed1ab_0.conda#e507335cb4ca9cff4c3d0fa9cdab255e diff --git a/docs/Makefile b/docs/Makefile index 04627e5229e..c32622e3bb4 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -6,7 +6,7 @@ SPHINXOPTS = SPHINXBUILD = sphinx-build PAPER = BUILDDIR = _build -CORES = 1 +NCORES = 1 # Internal variables. PAPEROPT_a4 = -D latex_paper_size=a4 @@ -42,7 +42,7 @@ clean: -rm -rf generated html: - $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html -j $(CORES) + $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html -j $(NCORES) @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/html." diff --git a/docs/_templates/layout.html b/docs/_templates/layout.html index 9bc5acc27d2..c861ae40191 100644 --- a/docs/_templates/layout.html +++ b/docs/_templates/layout.html @@ -5,6 +5,15 @@ {# Add github banner (from: https://github.com/blog/273-github-ribbons). #} {% block header %} {{ super() }} + + + Fork me on GitHub {% endblock %} {% block extrahead %} diff --git a/docs/conf.py b/docs/conf.py index 3e0a96be777..a1f2640a849 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -28,6 +28,7 @@ import os import sys import datetime +import tardis # FIXME: this import is required by astropy.constants from importlib import import_module try: @@ -62,6 +63,7 @@ # directories to ignore when looking for source files. exclude_patterns.append("_templates") exclude_patterns.append("_build") +exclude_patterns.append("**_template.rst") exclude_patterns.append("**.ipynb_checkpoints") exclude_patterns.append("resources/research_done_using_TARDIS/ads.ipynb") @@ -124,7 +126,7 @@ nbsphinx_execute_arguments = [ "--InlineBackend.figure_formats={'svg', 'pdf'}", - "--InlineBackend.rc={'figure.dpi': 96}", + "--rc figure.dpi=96", ] nbsphinx_prolog = r""" @@ -132,6 +134,12 @@ .. raw:: html
-

You can interact with this notebook online: Launch interactive version

+

You can interact with this notebook online: Launch notebook

""" @@ -333,61 +341,16 @@ # -- Sphinx hook-ins --------------------------------------------------------- -import re -import pathlib -import requests -import textwrap -import warnings from shutil import copyfile -def generate_ZENODO(app): - """Creating ZENODO.rst - Adapted from: https://astrodata.nyc/posts/2021-04-23-zenodo-sphinx/""" - CONCEPT_DOI = "592480" # See: https://help.zenodo.org/#versioning - zenodo_path = pathlib.Path("resources/ZENODO.rst") - - try: - headers = {"accept": "application/x-bibtex"} - response = requests.get( - f"https://zenodo.org/api/records/{CONCEPT_DOI}", headers=headers - ) - response.encoding = "utf-8" - citation = re.findall("@software{(.*)\,", response.text) - zenodo_record = ( - f".. |ZENODO| replace:: {citation[0]}\n\n" - ".. code-block:: bibtex\n\n" - + textwrap.indent(response.text, " " * 4) - ) - - except Exception as e: - warnings.warn( - "Failed to retrieve Zenodo record for TARDIS: " f"{str(e)}" - ) - - not_found_msg = """ - Couldn"t retrieve the TARDIS software citation from Zenodo. Get it - directly from `this link `_ . - """ - - zenodo_record = ( - ".. |ZENODO| replace:: \n\n" - ".. warning:: \n\n" + textwrap.indent(not_found_msg, " " * 4) - ) - - with open(zenodo_path, "w") as f: - f.write(zenodo_record) - - print(zenodo_record) - - def generate_tutorials_page(app): """Create tutorials.rst""" notebooks = "" for root, dirs, fnames in os.walk("io/"): for fname in fnames: - if fname.endswith(".ipynb") and "checkpoint" not in fname: + if fname.startswith("tutorial_") and fname.endswith(".ipynb") and "checkpoint" not in fname: notebooks += f"\n* :doc:`{root}/{fname[:-6]}`" title = "Tutorials\n*********\n" @@ -396,6 +359,21 @@ def generate_tutorials_page(app): with open("tutorials.rst", mode="wt", encoding="utf-8") as f: f.write(f"{title}\n{description}\n{notebooks}") +def generate_how_to_guides_page(app): + """Create how_to_guides.rst""" + notebooks = "" + + for root, dirs, fnames in os.walk("io/"): + for fname in fnames: + if fname.startswith("how_to_") and fname.endswith(".ipynb") and "checkpoint" not in fname: + notebooks += f"\n* :doc:`{root}/{fname[:-6]}`" + + title = "How-To Guides\n*********\n" + description = "The following pages contain the TARDIS how-to guides:" + + with open("how_to_guides.rst", mode="wt", encoding="utf-8") as f: + f.write(f"{title}\n{description}\n{notebooks}") + def autodoc_skip_member(app, what, name, obj, skip, options): """Exclude specific functions/methods from the documentation""" @@ -433,7 +411,7 @@ def create_redirect_files(app, docname): def setup(app): - app.connect("builder-inited", generate_ZENODO) app.connect("builder-inited", generate_tutorials_page) + app.connect("builder-inited", generate_how_to_guides_page) app.connect("autodoc-skip-member", autodoc_skip_member) app.connect("build-finished", create_redirect_files) diff --git a/docs/contributing/development/benchmarks.rst b/docs/contributing/development/benchmarks.rst new file mode 100644 index 00000000000..f94d85301f3 --- /dev/null +++ b/docs/contributing/development/benchmarks.rst @@ -0,0 +1,89 @@ +.. _benchmarks: + +********** +Benchmarks +********** + +The objective of the benchmarking system is to detect regressions +that affect the performance of the TARDIS. This means we can visually +check whether there is a positive or negative spike in the TARDIS' performance. + + +AirSpeed Velocity (``ASV``) +=========================== + +TARDIS bases its benchmarking system on +`AirSpeed Velocity `_ (``ASV``). +Since it has a great advantage, which is that it is designed to run benchmarks on +`random servers `_ +such as those provided by +`GitHub Actions `_. +ASV eliminates the noise due to the technical differences between the servers +and produces graphs that indicate whether there is a regression or not. +It indicates the commit for the changes added or removed that affected performance +in some functions. + + +Installation +============ + +The complete guide is on the +`official ASV site `_, +however, here is detailed and summarized information to configure TARDIS with ASV. + +ASV needs `Conda `_ +(or `Miniconda `_) +and `Mamba `_. +To make configuration easier, you can use +`Mini-forge `_, +which includes the installers mentioned above. +In this step, Mamba installs Python, ASV, and Mamba; +however, this step does not configure Mamba with the TARDIS. + +.. code-block:: shell + + > export MAMBA_ENV_NAME="benchmark" + > mamba create --yes --name "${MAMBA_ENV_NAME}" python asv mamba + > mamba init + + +Set up +====== + +In this step, ASV configures TARDIS through Mamba. +Packages that use TARIDS are downloaded here. +These packages are mainly found in this ``tardis_env3.yml`` file. +The environment is also configured for ASV to execute benchmarks +and store the results through the ``asv.conf.json`` file. + +.. code-block:: shell + + > cd tardis + > export MAMBA_ENV_NAME="benchmark" + > mamba activate "${MAMBA_ENV_NAME}" + > asv setup + > asv machine --yes + + +Execution +========= + +ASV commands are used for execution. The first ``run`` command execute +the benchmarks found in the Python files that are in the ``benchmarks/`` +folder. Subsequently, the data and information are stored in the ``.asv/`` folder. + +.. code-block:: shell + + > cd tardis + > export MAMBA_ENV_NAME="benchmark" + > mamba activate "${MAMBA_ENV_NAME}" + > asv run + > asv publish + + +Visualization +============= + +There are two ways to view the data. The simplest thing is +to execute the ``asv preview`` command, creating a local web server. +The second is to run a local web server of your choice. diff --git a/docs/contributing/development/code_quality.rst b/docs/contributing/development/code_quality.rst index cd5ae10bc6d..acd65445ca6 100644 --- a/docs/contributing/development/code_quality.rst +++ b/docs/contributing/development/code_quality.rst @@ -19,13 +19,44 @@ TARDIS follows the `PEP 8 `_ style gu Black ----- `Black `_ is a PEP 8 compliant opinionated code formatter. At TARDIS. we use Black to automatically conform to PEP 8. It is already installed in the TARDIS conda environment, so all you have to do is to run Black before commiting your changes: :: - + black {source_file_or_directory} A better method is to run Black automatically - first `integrate it within the code editor `_ you use and then enable the "format on save" or "format on type" option in your editor settings. .. warning :: If your code doesn't follow the Black code style, then the Black-check action on your PR will fail. +Ruff +---- +`Ruff `_ is a code linter and formatter that checks for common mistakes and automatically fixes them. It is currently not installed in the TARDIS conda environment, so you will have to install it manually: :: + + conda install -c conda-forge ruff + +To run Ruff, use the following command: :: + + ruff check # Lints the code + ruff check --fix # Lints and fixes any fixable errors + +Currently, Ruff is not integrated with the TARDIS CI and is not a requirement for merging a PR. However, it is recommended to run Ruff on your code before commiting it to ensure that new code already follows these rules. + +.. note :: We adopt the linting rules utilized by astropy. Permanent rules are defined in the ``pyproject.toml``, non-permanent rules are defined in the ``.ruff.toml`` file. If you want to add a new rule, please add it to the ``.ruff.toml`` file. If you want to add a permanent rule, please open a PR to the ``pyproject.toml``. + +.. note :: Ruff can also be used for formatting code, but for now we recommend using Black for this purpose as the CI is configured to run Black on all PRs. + +Pre-commit (Optional) +---- +`Pre-commit `_ hooks are tools that help enforce quality standards by running checks on your code before you commit. If you choose to use pre-commit on your local machine, please follow these steps: + +Install pre-commit by running: :: + + pip install pre-commit + +Set up the pre-commit hooks with: :: + + pre-commit install + +This needs to be done only once per repository. The pre-commit hooks will now automatically run on each commit to ensure your changes meet our code quality standards. + Naming Conventions ------------------ @@ -33,7 +64,7 @@ While Black automatically conforms your code to a majority of the PEP 8 style gu - Function names should be lowercase, with words separated by underscores as necessary to improve readability (i.e. snake_case). -- Variable names follow the same convention as function names. +- Variable names follow the same convention as function names. - Class names should use the CapWords convention. @@ -74,7 +105,7 @@ At TARDIS, we follow the `Numpy docstring format /`` folder structure. If the pipeline fails, also a report is generated, but not necessarily gives useful debug information (depends on which step the pipeline has failed). + + +TARDIS Carsus Compatibility Check +================================= +The TARDIS Carsus Compatibility Check or the "Bridge" compares reference data +generated with different versions of Carsus. It consists of two jobs- a "carsus-build" job to +generate an atomic file with the latest version of Carsus and a "tardis-build" job +to generate a new reference data with it. These two reference data files are compared using the +`this notebook `_. +The workflow has a ``workflow_dispatch`` event so that it can be triggered manually, but is also +triggered every week due to the "save-atomic-files" workflow. + + +The Save Atomic Files Workflow +============================== +The Save Atomic Files workflow runs every week but can also be triggered manually. +It runs the "Bridge" and sends an artifact containing the generated atomic data file +and the comparison notebook to Moria. This workflow has a separate job to indicate if the +bridge has failed. diff --git a/docs/contributing/development/debug_numba.rst b/docs/contributing/development/debug_numba.rst index 2f5e1c210ef..4ac9ab7fcc4 100644 --- a/docs/contributing/development/debug_numba.rst +++ b/docs/contributing/development/debug_numba.rst @@ -5,8 +5,8 @@ To facilitate more in-depth debugging when interfacing with the `montecarlo_numb module, we provide a set of debugging configurations. PyCharm debugging configurations, in addition to related scripts and .yml files, are contained in `tardis.scripts.debug`. Currently, these include the ability to run TARDIS -in asingle-packet mode, with the packet seed identified at debug time. -`tardis_example_single.yml` is the configuration filethat is used to set up the +in a single-packet mode. +`tardis_example_single.yml` is the configuration file that is used to set up the single-packet TARDIS run; `run_numba_single.py` is thePython script that runs this .yml file; `run_numba_single.xml` is the PyCharmdebug configuration file that can be used in conjunction with the above files. diff --git a/docs/contributing/development/documentation_guidelines.rst b/docs/contributing/development/documentation_guidelines.rst index 75019b91245..49e40822edd 100644 --- a/docs/contributing/development/documentation_guidelines.rst +++ b/docs/contributing/development/documentation_guidelines.rst @@ -18,7 +18,7 @@ When making or adding changes to the functionality of an aspect of TARDIS, an `` RST Documentation ----------------- -Documentation not featuring interactive code examples is written in Sphinx's reStructuredText (see `here `_). Files written in reStructuredText have a ``.rst`` file extension, and are then built as HTML filed by Sphinx during the documentation build. Only the RST file, not the built HTML file, are committed to the repository. Documentation should be clear and concise. See :doc:`../../io/visualization/using_widgets` as a good example of an RST-generated page. +Documentation not featuring interactive code examples is written in Sphinx's reStructuredText (see the `sphinx documentation `_). Files written in reStructuredText have a ``.rst`` file extension, and are then built as HTML filed by Sphinx during the documentation build. Only the RST file, not the built HTML file, are committed to the repository. Documentation should be clear and concise. See :doc:`../../io/visualization/using_widgets` as a good example of an RST-generated page. IPYNB Documentation @@ -59,36 +59,34 @@ To build TARDIS documentation locally, use the following commands: - If you're working on a fresh local copy of the TARDIS repository, you might need to do ``python setup.py develop`` before executing these commands. - Use ``DISABLE_NBSPHINX=1 make html`` to disable notebook rendering (fast mode). - - Use ``make html CORES=`` to have the documentation build in parallel. Using ``make html CORES=auto`` instructs Sphinx to use all of your device's cores. + - Use ``make html NCORES=`` to have the documentation build in parallel. Using ``make html NCORES=auto`` instructs Sphinx to use all of your device's cores. + - Use ``make html SPHINXOPTS=""`` to include additional sphinx options, which can be found `here `_. After running this command, you can find the built docs (i.e. HTML webpages) in ``docs/_build/html``. Open the ``index.html`` in your browser to see how the documentation looks like with your edits. Navigate to page where you made changes or file that you added to check whether it looks as intended or not. -Additionally, check your terminal for warning messages during the documentation build (often caused by faulty hyperlinks or failing to include the page in the documentation). These should be repaired prior to merging your changes into the documentation. +Additionally, check your terminal for warning messages during the documentation build (often caused by faulty hyperlinks or failing to include the page in the documentation). These should be repaired prior to merging your changes into the documentation. See below for troubleshooting tips. .. _doc-preview: -Sharing the built documentation in your PR (Documentation Preview) -================================================================== +Sharing the built documentation in your pull request +==================================================== -When you make edits in TARDIS documentation and submit a PR, we can only see the changes in source files in GitHub files diff, but not the built documentation (webpages). This is usually fine unless you have made changes in the documentation itself or changes that could break the Jupyter notebooks used in the documentation. In such cases, you should share the preview of documentation with your changes by building it online via GitHub. This will help us (the reviewers of your PR) to check how the documentation will look once your PR is merged. +When proposing changes to the documentation, or the code in general, it is useful to reviewers to see how the documentation will look once your pull request is merged. This is done by adding the ``build-docs`` label to your pull request on GitHub. If you do not have permission to add the label, leave a comment in your pull request or contact a senior member of the collaboration and it will be added. -To preview your changes to the documentation on GitHub, please: +The documentation will be built as soon as the label is added, and any subsequent commits while the label is present will trigger a documentation build. Your built documentation will be available at ``https://tardis-sn.github.io/tardis/pull//index.html``. It will also be automatically linked to in the comments of the pull request. -#. Enable GitHub Actions in the *Actions* tab of your fork. -#. Under *Settings -> Pages* in your fork, make sure GitHub Pages is being built from the ``gh-pages`` branch and the ``/ (root)`` folder. +Finally, to view the build logs (which will contain warning and error messages), go to the ``Actions`` tab in the TARDIS repository, and click on ``docs`` in the list of workflows. You can search documentation builds by branch to find your build log. -Then, there are two ways to trigger the build: -#. If the branch you are working on contains the word ``doc`` in it, then every commit pushed to that branch will trigger the build. -#. If your commit message contains the ``[build docs]`` tag, then that commit will trigger the build. +Troubleshooting Your Documentation +================================== -You can check for warning messages via the *Actions* tab of your fork. Your preview will be available at ``.github.io/tardis/branch//index.html``. +It is important to keep your documentation free of warnings and errors, which can be found in the build logs (locally these will appear in your terminal, and for builds on GitHub see the last paragraph in the above section). On GitHub, these will give you a notification that your documentation build failed. Below are some pointers for resolving these issues: -.. note:: - - You always can trigger a new build by pushing an empty commit: ``git commit --allow-empty -m "[build docs]"`` +* Errors often are a result of notebooks being incompatible with your new code. Make sure notebooks are always updated to reflect your additions. +* Warnings are often due to incorrect syntax in RST documentation regarding links, section headers, tables of contents, etc. The `Sublime and Sphinx Guide `_ is a good resource for learning proper syntax. +* Warnings can also be because docstrings are not consistent with the `numpy docstring format `_. +* On GitHub, built documentation files (including ``.ipynb`` files built by Sphinx) can be a maximum of 100 MB. You can check the file sizes after a local documentation build in ``docs/_build/html``. Note that image output in notebooks built by Sphinx is by default in SVG format. For detailed images, these images can be very large. If file size becomes a problem, you will need to change the image format for that notebook by placing ``%config InlineBackend.figure_formats='png2x'`` in a `hidden cell `_ at the beginning of the notebook. -.. warning:: - - On GitHub, built documentation files (including ``.ipynb`` files built by Sphinx) can be a maximum of 100 MB. You can check the file sizes after a local documentation build in ``docs/_build/html``, or after a documentation preview on GitHub in the ``gh-pages`` branch. Note that image output in notebooks built by Sphinx are by default in SVG format. For detailed images, these images can be very large. If file size becomes a problem, you will need to change the image format for that notebook by placing ``%config InlineBackend.figure_formats='png2x'`` in a `hidden cell `_ at the beginning of the notebook. \ No newline at end of file +Please reach out for help if you have difficulties resolving issues in your documentation. diff --git a/docs/contributing/development/git_workflow.rst b/docs/contributing/development/git_workflow.rst index f49414f8faf..47dbc1408e7 100644 --- a/docs/contributing/development/git_workflow.rst +++ b/docs/contributing/development/git_workflow.rst @@ -276,7 +276,7 @@ In more detail #. Once you are a bit further along, test your changes do not lead to regressions, and add new tests (see the Astropy :ref:`testing-guidelines` we follow):: - python setup.py test + pytest tardis If you have `Sphinx `_ installed, you can also check that the documentation builds and looks correct:: @@ -352,6 +352,8 @@ When you are ready to ask for someone to review your code and consider a merge: pull request message. This is still a good way to start a preliminary code review. +The TARDIS documentation features interactive notebooks that run varius aspects of the code, as well as API documentation. To make sure that these notebooks remain up-to-date with the code, and that your docstrings are correctly incorporated into the API documentation, we ask that you build the documentation for your pull request following the instructions :ref:`here `. + .. _using-virtualenv: Making sure your Pull Request stays up-to-date @@ -364,6 +366,8 @@ To make sure that your changes are still working on the new master, you want to *rebase* your branch on top of the evolved master. +.. _rebase-on-trunk: + Rebasing on trunk ^^^^^^^^^^^^^^^^^ diff --git a/docs/contributing/development/index.rst b/docs/contributing/development/index.rst index 3ad0131b325..53fde2cc824 100644 --- a/docs/contributing/development/index.rst +++ b/docs/contributing/development/index.rst @@ -1,3 +1,5 @@ +.. _developer_guidelines: + ****************** Developer Workflow ****************** @@ -15,6 +17,7 @@ to the Astropy team for designing it. git_workflow documentation_guidelines running_tests + benchmarks code_quality developer_faq @@ -30,4 +33,3 @@ the core team (active maintainers) of TARDIS. update_refdata matterbridge debug_numba - profiling/index diff --git a/docs/contributing/development/integration.yml b/docs/contributing/development/integration.yml index 3d3ab2cef9b..e638fa3d9dd 100644 --- a/docs/contributing/development/integration.yml +++ b/docs/contributing/development/integration.yml @@ -1,24 +1,5 @@ atom_data_path: "~/projects/tardis/integration/" -# This section holds information about mechanism of saving the HTML -# report of the tests. -# "save_mode" is mandatory: It can be either "local" or "remote". -report: - save_mode: "local" - - # This section contains credentials for dokuwiki instance. - # It is mandatory if "save_mode" is "remote", else can be removed. - dokuwiki: - url: "http://opensupernova.org/~karandesai96/integration/" - username: "private" - password: "private" - - # If "save_mode" is "local", a sub directory will be made in this - # directory according to commit hash (shortened), and it will contain - # the complete report content. - reportpath: "~/projects/tardis/integration" - - # Path to directory where reference HDF files will be generated and # saved during the test run. Use "--generate-reference" flag in command # line args for the purpose, for other cases this will denote path diff --git a/docs/contributing/development/profiling/tardis_profiling_threads.ipynb b/docs/contributing/development/profiling/tardis_profiling_threads.ipynb deleted file mode 100644 index b0dd15af057..00000000000 --- a/docs/contributing/development/profiling/tardis_profiling_threads.ipynb +++ /dev/null @@ -1,368 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "61f49e0f", - "metadata": {}, - "source": [ - "# Profiling the effect of input parameters on TARDIS runtime #" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2c26cee6", - "metadata": {}, - "outputs": [], - "source": [ - "import tardis\n", - "from tardis import run_tardis\n", - "\n", - "from tardis.io.config_reader import Configuration\n", - "from tardis.io.atom_data.base import AtomData\n", - "from tardis.simulation import Simulation\n", - "from tardis import run_tardis\n", - "from tardis.io.atom_data.util import download_atom_data\n", - "download_atom_data('kurucz_cd23_chianti_H_He')\n", - "\n", - "import time\n", - "import numpy as np\n", - "from astropy import units as u\n", - "import csv\n", - "import statistics\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "markdown", - "id": "dac6305a", - "metadata": {}, - "source": [ - "### Functions for building the dictionaries and interacting with files ###" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a806b64e", - "metadata": {}, - "outputs": [], - "source": [ - "def build_dictionary(fp):\n", - " \"\"\"\n", - " Uses the fp generated from open_file to return a dictionary. Then closes\n", - " the file at the end of execution.\n", - "\n", - " 'testing_param' : dict\n", - " 'iteration' : time\n", - " \n", - " Parameters\n", - " ----------\n", - " fp : file\n", - " \n", - " Returns\n", - " -------\n", - " data_dict : dictionary\n", - " \"\"\"\n", - " \n", - " data_dict = {}\n", - " reader = csv.reader(fp)\n", - " for line in reader:\n", - " testing_param = int(line[0])\n", - " \n", - " iteration = int(line[1])\n", - " \n", - " time_of_run = float(line[2])\n", - " \n", - " if testing_param not in data_dict:\n", - " data_dict[testing_param] = {}\n", - " if iteration not in data_dict[testing_param]:\n", - " data_dict[testing_param][iteration] = time_of_run\n", - " fp.close()\n", - " return data_dict \n", - "\n", - "def add_to_dictionary(data_dict, info):\n", - " \"\"\"\n", - " Adds the data to the dictionary\n", - " \n", - " Parameters\n", - " ----------\n", - " data_dict : dictionary\n", - " info : list\n", - " It is set up as [testing_param, iteration, run_time]\n", - " \"\"\"\n", - " \n", - " testing_param = info[0]\n", - " iteration = info[1]\n", - " time_of_run = info[2]\n", - " if testing_param not in data_dict:\n", - " data_dict[testing_param] = {}\n", - " data_dict[testing_param][iteration] = time_of_run\n", - "\n", - "\n", - "def check_existance(data_dict, info):\n", - " \"\"\"\n", - " Checks to see if a data poitn already exists in data_dict.\n", - " Returns true if it exists, false if it does not.\n", - " \n", - " Parameters\n", - " ----------\n", - " data_dict : dictionary\n", - " info : list\n", - " [testing_param, iteration]\n", - " \n", - " Returns\n", - " -------\n", - " Boolean\n", - " \"\"\"\n", - " \n", - " testing_param = info[0]\n", - " iteration = info[1]\n", - " #Checks if it thread already exists\n", - " if testing_param not in data_dict:\n", - " return False\n", - " #If it does\n", - " elif (testing_param in data_dict):\n", - " #Does the iteration exist yet\n", - " if iteration not in data_dict[testing_param]:\n", - " return False\n", - " return True" - ] - }, - { - "cell_type": "markdown", - "id": "92662ad4", - "metadata": {}, - "source": [ - "## Timing of a specific parameter in TARDIS ##" - ] - }, - { - "cell_type": "markdown", - "id": "a55336ba", - "metadata": {}, - "source": [ - "### Number of Threads ###" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "411e12a2", - "metadata": {}, - "outputs": [], - "source": [ - "def generate_data(thread_count, \n", - " iteration_count, \n", - " thread_dictionary, \n", - " cpu_timing_dictionary, \n", - " tardis_file, \n", - " thread_file, \n", - " cpu_file,):\n", - " \"\"\"\n", - " This function generates data for running a tardis file on different numbers of threads different times.\n", - " It writes the data to two dictionaries and their respecitve files.\n", - " \n", - " This function can be modified to write to as many or as few dictionaries and files as necessary.\n", - " In order to test different parameters, the index into the tardis_config must be adjusted. This must be done \n", - " manually in order to select the correct testing parameter.\n", - " \n", - " Parameters\n", - " ----------\n", - " thread_count : int\n", - " Max number of threads to be tested\n", - " iteration_count : int\n", - " Amount of testing on each thread\n", - " thread_dictionary : dict\n", - " cpu_timing_dictionary : dict\n", - " tardis_file : str\n", - " TARDIS config file\n", - " thread_file : str\n", - " .csv file name\n", - " cpu_file : str\n", - " .csv file name\n", - " \"\"\"\n", - "\n", - " tardis_config = Configuration.from_yaml(tardis_file)\n", - "\n", - " for threads in range(1, thread_count+1):\n", - " for i in range(1, iteration_count+1):\n", - " #Continue if this data point already exists. If it exists in one it exists in both\n", - " if check_existance(thread_dictionary, [threads, i]):\n", - " continue\n", - "\n", - " print(threads, \" : \", i)\n", - " tardis_config[\"montecarlo\"][\"nthreads\"] = threads\n", - "\n", - " sim = Simulation.from_config(tardis_config)\n", - " start = time.monotonic()\n", - " sim.run()\n", - " end = time.monotonic()\n", - " run_time = end-start\n", - " \n", - " add_to_dictionary(thread_dictionary, [threads, i, run_time])\n", - " add_to_dictionary(cpu_timing_dictionary, [threads, i, (run_time * threads)])\n", - "\n", - " with open(thread_file, \"a\") as data_file:\n", - " data_file.write(\"{}, {}, {}\\n\".format(threads, i, run_time))\n", - " with open(cpu_file, \"a\") as data_file:\n", - " data_file.write(\"{}, {}, {}\\n\".format(threads, i, run_time * threads))\n", - " \n", - " print(\"Completed\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d6966653", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "TARDIS_FILE = 'tardis_example.yml'\n", - "STORAGE_FILE = 'threads_dict_128_threads_1_node.csv'\n", - "CPU_STORAGE_FILE = 'cpu_threads_dict_128_threads_1_node.csv'\n", - "\n", - "#Compile the numba functions\n", - "run_tardis(TARDIS_FILE)\n", - "\n", - "#Opens file and builds the dictionary\n", - "with open(STORAGE_FILE, \"r\") as threads_fp:\n", - " threads_dict = build_dictionary(threads_fp)\n", - "\n", - "with open(CPU_STORAGE_FILE, \"r\") as cpu_fp:\n", - " cpu_threads_dict = build_dictionary(cpu_fp)\n", - "\n", - "#Creates list of main data\n", - "threads_numbers = [i for i in range(1, 129, 1)]\n", - "cpu_threads_numbers = [i for i in range(1, 129, 1)]\n", - "\n", - "generate_data(128, 30, threads_dict, cpu_threads_dict, TARDIS_FILE, STORAGE_FILE, CPU_STORAGE_FILE)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7056ee6e", - "metadata": {}, - "outputs": [], - "source": [ - "def create_stat_dictionaries(main_dict):\n", - " \"\"\"\n", - " This builds two dictionaries, one that holds the mean of the data and the other that holds the stdev\n", - " \n", - " Parameters\n", - " ----------\n", - " main_dict : dict\n", - " Data dictionary, format of\n", - " testing_param : dictionary\n", - " iteration : time\n", - " \n", - " Returns\n", - " -------\n", - " main_dict_mean : dict\n", - " main_dict_stdev : dict\n", - " \"\"\"\n", - "\n", - " main_dict_list = {}\n", - " for thread, iteration_dict in main_dict.items():\n", - " main_dict_list[thread] = [v for (k, v) in iteration_dict.items()]\n", - "\n", - " main_dict_mean = {}\n", - " main_dict_stdev = {}\n", - " for thread, timing_list in main_dict_list.items():\n", - " main_dict_mean[thread] = statistics.mean(timing_list)\n", - " main_dict_stdev[thread] = statistics.stdev(timing_list)\n", - "\n", - " return main_dict_mean, main_dict_stdev\n", - "\n", - "threads_dict_mean, threads_dict_stdev = create_stat_dictionaries(threads_dict)\n", - "cpu_threads_dict_mean, cpu_threads_dict_stdev = create_stat_dictionaries(cpu_threads_dict)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ae1e8624", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "def graph_data(testing_params, mean_dict, stdev_dict, x_axis_title, y_axis_title, graph_title, text_labels=False):\n", - " \"\"\"\n", - " Uses pyplot to graph the data given the mean and standard deviation of data.\n", - " \n", - " Parameters\n", - " ----------\n", - " testing_params : list\n", - " This is a list of the testing parameters, which is used for the axis construction.\n", - " mean_dict : dict\n", - " stdev_dict : dict\n", - " x_axis_title : str\n", - " y_axis_title : str\n", - " graph_title : str\n", - " text_labels : bool\n", - " This is a boolean parameter for if the testing parameters are text. If they are text, then\n", - " it will set each tick mark on the x-axis to be a label in testing_params.\n", - " \"\"\"\n", - " \n", - " lists = sorted(mean_dict.items())\n", - " lists_stdev = sorted(stdev_dict.items())\n", - " x, y = zip(*lists)\n", - " x_stdev, y_stdev = zip(*lists_stdev)\n", - "\n", - " fig = plt.figure(figsize=(20,10))\n", - " ax = fig.add_subplot(1,1,1)\n", - " ax.set_xlabel(x_axis_title)\n", - " ax.set_ylabel(y_axis_title)\n", - " ax.set_title(graph_title)\n", - " ax.grid(True)\n", - " \n", - " if text_labels:\n", - " xtick_spacer = np.arange(0, len(testing_params), 1)\n", - " xticks = testing_params\n", - " ax.set_xticks(xtick_spacer)\n", - " ax.set_xticklabels(xticks, rotation='horizontal', fontsize=18)\n", - " elif not text_labels:\n", - " #If there are a lot of ticks, it will reduce for visibility.\n", - " interval = testing_params[1] - testing_params[0]\n", - " if len(testing_params) > 80:\n", - " xticks = np.arange(testing_params[0], testing_params[-1]+interval, interval*2)\n", - " else:\n", - " xticks = np.arange(testing_params[0], testing_params[-1]+interval, interval)\n", - " ax.set_xticks(xticks)\n", - " \n", - " ax.plot(x, y, color='tab:blue', label=\"{} vs {}\".format(x_axis_title, y_axis_title))\n", - " plt.errorbar(x, y, yerr=y_stdev, label='stdev')\n", - " leg = plt.legend(loc='best', ncol=1, mode='expanded', fancybox=False)\n", - " leg.get_frame().set_alpha(0.5)\n", - "\n", - "graph_data(threads_numbers, threads_dict_mean, threads_dict_stdev, \"threads\", \"time (sec)\", \"threads vs time\")\n", - "graph_data(cpu_threads_numbers, cpu_threads_dict_mean, cpu_threads_dict_stdev, \"threads\", \"time (sec)\", \"threads vs cpu time\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/contributing/development/running_tests.rst b/docs/contributing/development/running_tests.rst index 702ee0b088d..5ae85734861 100644 --- a/docs/contributing/development/running_tests.rst +++ b/docs/contributing/development/running_tests.rst @@ -28,12 +28,60 @@ tests, you can run this with: Running the more advanced unit tests requires TARDIS Reference data that can be downloaded -(`tardis_refdata `_). +(`tardis-refdata `_). +`Git LFS `_ is used +to download the large refdata files in the tardis-refdata repository. + +However, it is not required to download the entire repository. Firstly it is +important to identify the refdata files that are needed. Sometimes, it is possible +that a preused fixture that is also being used in the current tests is using some +refdata. So, it is advised to check for such cases beforehand. + +After identifying the refdata files to be used in the unit tests, those particular +files can be downloaded using ``git lfs`` + +.. code-block:: shell + + > git lfs pull --include=filename + +It is important to maintain the same directory structure as the tardis-refdata repo +i.e. the lfs files should be in the same directory tree exactly as in tardis-refdata +repository. + +Finally, the tests can be run using the following command .. code-block:: shell > pytest tardis --tardis-refdata=/path/to/tardis-refdata/ +Or, to run tests for a particular file or directory + +.. code-block:: shell + + > pytest tardis/path/to/test_file_or_directory --tardis-refdata=/path/to/tardis-refdata/ + +.. warning:: + The `tests workflow `_ runs on + `pull requests `_ and on + `push `_ events. + To prevent leaking LFS quota, tests have been disabled on forks. + If, by any chance, you need to run tests on your fork, make sure to run the tests workflow on master branch first. + The LFS cache generated in the master branch should be available in all child branches. + You can check if cache was generated by looking in the ``Restore LFS Cache`` step of the workflow run. + Cache can also be found under the "Management" Section under "Actions" tab. + + +Running Syrupy Tests +====================== +The tests module is currently being restructured to use `Syrupy `_. +These tests generate individual HDF(for Pandas) and ``.npy`` or ``.npz`` (for NumPy) files(or snapshots) for each test case. +For other objects, the plugin serialises them and saves them as ``.ambr`` files. There is a custom extension in the +main local `conftest `_ file to get this to work. +The plugin currently only supports ``assert_allclose`` for NumPy and ``assert_series_equal`` and ``assert_frame_equal`` for +Pandas. Snapshots can be generated by using the same ``--generate-reference`` flag and are compared automatically. +You however need to provide the location to your snapshot directory using the ``--tardis-snapshot-data`` flag. +The snapshots are also saved in `tardis-sn/tardis-regressions `_. + Generating Plasma Reference =========================== @@ -77,24 +125,3 @@ needed is: > python setup.py test --args="--integration=integration.yml -m integration --less-packets" --remote-data - - -Setting up the DokuWiki report -============================== - -A normal `DokuWiki `_ installation is performed on the required server. Before the -connection works one is requires to set the option remote access in the -settings. If this is not done the ``dokuwiki`` python plugin will not connect -with the warning ``DokuWikiError: syntax error: line 1, column 0``. One also -has to enable this for users (``remoteuser`` option) otherwise the error: -``ProtocolError for xmlrpc.php?p=xxxxxx&u=tardistester: 403 Forbidden`` -will appear. - -Another important configuration option is to enable embedded html ``htmlok``; -otherwise, it won't show nice html page reports. - -Finally, one has to call the `python setup.py test` with the ``--remote-data`` -option to allow posting to an external DokuWiki server. - - - diff --git a/docs/contributing/in_progress/index.rst b/docs/contributing/in_progress/index.rst new file mode 100644 index 00000000000..a2cabd59cc3 --- /dev/null +++ b/docs/contributing/in_progress/index.rst @@ -0,0 +1,80 @@ +.. _in-progress: + +******************** +Features In-Progress +******************** + +This is a current status summary of ongoing development projects in the TARDIS collaboration. Brief summaries of the projects are listed below. Other projects and their descriptions can be found in the `GitHub Projects `_ or the `TARDIS Enhancement Proposals (TEPS) repository `_. + +Additionally, documentation for features that are not yet implemented can be found here. + + +Google Summer of Code (GSOC) +============================ + +Many new TARDIS developments are made through GSOC students. To learn more about potential GSOC projects, see the `GSOC ideas page `_. + + + +Restructure +=========== + +Restructuring TARDIS to be more modularized in order to facilitate the addition of new physics modules and improve maintainability. + + +New Physics +=========== + +TARDIS is currently capable of simulating spherically symmetric type Ia and stripped envelope supernovae at a single point in time in the earlier stages of the explosion. To expand to more types of supernovae, such as type Ib, Ic, and IIP, and to model a larger variety of times after the explosion, new physics capabilities are necessary. + + +Simulate Supernovae in the Nebular Phase +---------------------------------------- + +* Currently, TARDIS assumes an inner boundary approximation to the photosphere. New physics is required to handle the breakdown of the photosphere at late times. This involves a detailed treatment of the decay products of the radioactive isotopes in SN ejecta, as well as their deposition in various processes such as Compton scattering, photoabsorption and pair production. +* Deposited energy needs to be thermalized by solving the Spencer-Fano equations, resulting in fractions of the energy going into heating, non-thermal excitation and non-thermal ionization. +* At late times when the densities are low collisions become too infrequent to quickly de-excite metastable energy levels. Forbidden lines arising from these levels need to be included. Transitions between levels have to include ion-electron collisions. + +.. toctree:: + nebular_phase/gammaray_deposition + nebular_phase/positronium + + +Implement More Continuum Interactions +------------------------------------- + +* Currently, TARDIS considers Thomson electron scattering and line interactions when performing radiative transfer. In many cases, other continuum interactions have nontrivial effects of the propagation of light. +* Treatment of bound-free and free-free processes have been developed and are being integrated into TARDIS. + + +Simulate Non-Homologous Expansion +--------------------------------- + +* Currently, TARDIS models supernovae as expanding homologously. This is not always the case in many types of supernovae, and much of the simulation needs to be modified in order to drop this assumption. + + +Simulate Asymmetric Supernovae +------------------------------ + +* Currently, TARDIS assumes spherical symmetry in its calculations. A framework is being developed to allow for dropping this assumption and modeling 2D and 3D radiative transfer for spherically asymmetric supernovae. + + +Adding Time Dependence +---------------------- + +* Currently, TARDIS performs time-independent radiative transfer. Groundwork is being laid for the eventual goal of having TARDIS perform *time-dependent* radiative transfer. + + +Interoperability +================ + +Read Different Model Data +------------------------- + +Adding parsers to generate TARDIS models produced by other codes. + + +STARDIS +======= + +Developing a radiative transfer code using the TARDIS infrastructure that produces synthetic stellar spectra. See https://github.com/tardis-sn/stardis. diff --git a/docs/contributing/in_progress/nebular_phase/gammaray_deposition.ipynb b/docs/contributing/in_progress/nebular_phase/gammaray_deposition.ipynb new file mode 100644 index 00000000000..8c36359faea --- /dev/null +++ b/docs/contributing/in_progress/nebular_phase/gammaray_deposition.ipynb @@ -0,0 +1,1154 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Gamma-ray energy deposition\n", + "\n", + "This notebook provides the initial implementation of Gamma-ray energy deposition into an arbitrary ejecta.\n", + "It is a WORK IN PROGRESS and should NOT be used for any science work until further notice." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Main loop\n", + "\n", + "Generates a simple 1D ejecta and a list of gamma-ray objects.\n", + "\n", + "Runs packets of gamma-rays through the ejecta. Handles interactions by calling the appropriate function. \n", + "\n", + "Adds deposited energy and output energy to 2 different dataframes." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model setup" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "import matplotlib.pyplot as plt\n", + "from tardis.model import SimulationState\n", + "from tardis.io.config_reader import Configuration\n", + "\n", + "from tardis.plasma.properties import Density, Abundance, IsotopeAbundance, IsotopeNumberDensity, AtomicData, AtomicMass, IsotopeMass, NumberDensity, SelectedAtoms\n", + "from tardis.plasma.base import BasePlasma\n", + "from tardis.io.atom_data import AtomData\n", + "\n", + "import astropy.units as u\n", + "from tardis.energy_input.gamma_ray_transport import main_gamma_ray_loop\n", + "\n", + "# Adjust model \n", + "config = Configuration.from_yaml(\"../../../../tardis/io/tests/data/tardis_configv1_density_exponential_nebular.yml\")\n", + "config.model.structure.velocity.start = 1 * u.km / u.s\n", + "config.model.structure.density.rho_0 = 5e2 * u.g / (u.cm ** 3)\n", + "config.supernova.time_explosion = 2.0 * u.d\n", + "\n", + "config.atom_data = \"kurucz_cd23_chianti_H_He.h5\"\n", + "\n", + "model = SimulationState.from_config(config)\n", + "\n", + "# Construct plasma\n", + "input = [Density, Abundance, IsotopeAbundance, AtomicData, AtomicMass, IsotopeNumberDensity, NumberDensity, SelectedAtoms, IsotopeMass]\n", + "\n", + "plasma = BasePlasma(\n", + " plasma_properties=input,\n", + " density = model.density,\n", + " abundance = model.abundance,\n", + " isotope_abundance = model.raw_isotope_abundance,\n", + " atomic_data = AtomData.from_hdf(config.atom_data)\n", + " )\n", + "\n", + "# Set up packet count\n", + "num_packets = 500000\n", + "\n", + "# Lock seed\n", + "np.random.seed(1)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generate plasma" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "from tardis.plasma.properties import Density, Abundance, IsotopeAbundance, IsotopeNumberDensity, AtomicData, AtomicMass, IsotopeMass, NumberDensity, SelectedAtoms\n", + "from tardis.plasma.base import BasePlasma\n", + "from tardis.io.atom_data import AtomData\n", + "\n", + "input = [Density, Abundance, IsotopeAbundance, AtomicData, AtomicMass, IsotopeNumberDensity, NumberDensity, SelectedAtoms, IsotopeMass]\n", + "\n", + "plasma = BasePlasma(\n", + " plasma_properties=input,\n", + " density = model.density,\n", + " abundance = model.abundance,\n", + " isotope_abundance = model.raw_isotope_abundance,\n", + " atomic_data = AtomData.from_hdf(config.atom_data)\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total gamma-ray energy\n", + "6.389259861704378e+49\n", + "Total positron energy\n", + "8.454621397870039e+47\n", + "Total packets: 500000\n", + "Energy per packet 7.975724746893494e+52\n", + "Initializing packets\n", + "Total positron energy from packets\n", + "8.417997803471385e+47\n", + "Total CMF energy\n", + "3.7264874091697995e+58\n", + "Total RF energy\n", + "3.7279788130927574e+58\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/afullard/tardis/tardis/energy_input/gamma_packet_loop.py:129: NumbaPerformanceWarning: \u001b[1m\u001b[1m\u001b[1mnp.dot() is faster on contiguous arrays, called on (array(float64, 1d, A), array(float64, 1d, C))\u001b[0m\u001b[0m\u001b[0m\n", + " doppler_factor = doppler_factor_3d(\n", + "/home/afullard/tardis/tardis/energy_input/gamma_packet_loop.py:197: NumbaPerformanceWarning: \u001b[1m\u001b[1m\u001b[1m\u001b[1mnp.dot() is faster on contiguous arrays, called on (array(float64, 1d, C), array(float64, 1d, A))\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n", + " ) = distance_trace(\n", + "/home/afullard/tardis/tardis/energy_input/gamma_packet_loop.py:245: NumbaPerformanceWarning: \u001b[1m\u001b[1m\u001b[1m\u001b[1m\u001b[1mnp.dot() is faster on contiguous arrays, called on (array(float64, 1d, A), array(float64, 1d, C))\u001b[0m\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n", + " packet, ejecta_energy_gained = process_packet_path(packet)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Entering gamma ray loop for 500000 packets\n", + "Escaped packets: 81593\n", + "Scattered packets: 23333\n", + "Final energy to test for conservation\n", + "3.720648730441454e+58\n" + ] + } + ], + "source": [ + "\n", + "# Compute energy deposition rate\n", + "# ejecta_energy_df is the deposited energy\n", + "# ejecta_plot_energy_df is information for plotting\n", + "# escape_energy is the escaping energy\n", + "# decayed_packet_count is the number of packets created per shell\n", + "# energy_plot_positrons is the deposited energy from positrons\n", + "# estimated_deposition is the deposited energy from the Kasen (2006) estimator (currently not functional)\n", + "(\n", + " energy_df,\n", + " energy_plot_df,\n", + " escape_energy,\n", + " decayed_packet_count,\n", + " energy_plot_positrons,\n", + " estimated_deposition\n", + ") = main_gamma_ray_loop(\n", + " num_packets,\n", + " model,\n", + " plasma,\n", + " time_steps=50,\n", + " time_end=50.0,\n", + " path_to_decay_data=\"~/compiled_ensdf.hdf\"\n", + ")\n", + "\n", + "ejecta_energy = energy_plot_df[\"energy_input\"]\n", + "ejecta_energy_r = energy_plot_df[\"energy_input_r\"]\n", + "energy_input_time = energy_plot_df[\"energy_input_time\"]\n", + "energy_input_type = energy_plot_df[\"energy_input_type\"]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting results\n", + "\n", + "Energy deposited at a given radius" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(dpi=150, facecolor='w')\n", + "ax = fig.add_subplot(111)\n", + "\n", + "scatter = ax.scatter(np.array(ejecta_energy_r)/np.max(model.v_outer.value), np.array(ejecta_energy), s=1, alpha=0.1)\n", + "ax.set_xlabel(\"r/R\")\n", + "ax.set_ylabel(\"E (keV)\")\n", + "ax.semilogy();" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Interactions binned by radius" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(dpi=150, facecolor='w')\n", + "ax = fig.add_subplot(111)\n", + "ax.hist(np.array(ejecta_energy_r), bins=200)\n", + "#ax.set_xlim(0, 1)\n", + "ax.set_xlabel(\"r (cm)\")\n", + "ax.set_ylabel(\"Interaction count\");" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Density Profile" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(dpi=150, facecolor='w')\n", + "plt.semilogy(model.r_middle/np.max(model.r_outer), model.density)\n", + "plt.plot(0,0)\n", + "plt.ylabel(\"Density g cm$^{-3}$\")\n", + "plt.xlabel(\"r/R\");" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Fraction of energy escaping from the ejecta" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.844372140556195e-53" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(np.sum(escape_energy) / (np.sum(escape_energy) + np.sum(energy_df)))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Spectrum of escape energy at the final time step" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/afullard/tardis/tardis/energy_input/energy_source.py:170: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n", + " return pd.read_csv(\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from tardis.energy_input.energy_source import read_artis_lines\n", + "\n", + "ni56_lines = read_artis_lines(\"ni56\", \"~/Downloads/tardisnuclear/\")\n", + "co56_lines = read_artis_lines(\"co56\", \"~/Downloads/tardisnuclear/\")\n", + "\n", + "plt.figure(figsize=(12, 6), dpi=150)\n", + "plt.step(escape_energy.index, escape_energy.iloc[:,49], label=\"$\\gamma$-spectrum\", where=\"post\")\n", + "plt.xlabel(\"Energy (keV)\")\n", + "plt.ylabel(\"keV/keV/s\");\n", + "plt.loglog()\n", + "plt.xlim(100, 4000)\n", + "#plt.ylim(0.01, 100)\n", + "plt.vlines(ni56_lines.energy*1000, 0.1, 0.2, color=\"k\", label=\"Ni56\")\n", + "plt.vlines(co56_lines.energy*1000, 0.1, 0.2, color=\"r\", label=\"Co56\")\n", + "plt.legend()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Energy deposition rate\n", + "\n", + "Dataframe index is the radial grid location. Columns are time steps in seconds" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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4.808035e+53 3.888501e+53 5.008029e+53 4.654530e+53 ... \n", + "17 4.121339e+53 4.278267e+53 4.491534e+53 2.649101e+53 3.225867e+53 ... \n", + "18 3.660111e+53 3.573277e+53 4.006494e+53 2.275214e+53 2.788264e+53 ... \n", + "19 2.653951e+53 2.443372e+53 2.982978e+53 2.598039e+53 2.129802e+53 ... \n", + "\n", + " 2.269320e+06 2.420218e+06 2.581151e+06 2.752784e+06 2.935830e+06 \\\n", + "0 2.413105e+52 1.946078e+52 1.601020e+52 1.681973e+52 1.532812e+52 \n", + "1 1.326250e+53 1.128764e+53 9.533177e+52 9.066819e+52 8.349490e+52 \n", + "2 2.548472e+53 2.394402e+53 2.271846e+53 1.892756e+53 1.689675e+53 \n", + "3 3.721530e+53 3.252044e+53 2.997976e+53 2.889827e+53 2.407073e+53 \n", + "4 4.067807e+53 3.866050e+53 3.417029e+53 3.527510e+53 2.975597e+53 \n", + "5 4.533677e+53 4.126323e+53 3.522390e+53 3.371528e+53 3.012767e+53 \n", + "6 4.401336e+53 3.829897e+53 3.344355e+53 3.361478e+53 2.807300e+53 \n", + "7 4.041338e+53 3.574777e+53 3.243658e+53 2.860518e+53 2.836507e+53 \n", + "8 3.376278e+53 3.379366e+53 2.893652e+53 2.460482e+53 2.349191e+53 \n", + "9 2.819492e+53 2.637785e+53 2.536277e+53 2.043085e+53 1.644105e+53 \n", + "10 2.130141e+53 2.118125e+53 1.711647e+53 1.648757e+53 1.546999e+53 \n", + "11 1.757030e+53 1.548390e+53 1.376493e+53 1.125006e+53 1.040292e+53 \n", + "12 1.138373e+53 9.911889e+52 8.863272e+52 9.083607e+52 7.878527e+52 \n", + "13 9.137514e+52 8.480772e+52 7.327633e+52 5.763397e+52 5.614848e+52 \n", + "14 5.413666e+52 4.705275e+52 4.130852e+52 3.872048e+52 4.527747e+52 \n", + "15 3.969469e+52 4.340826e+52 3.682750e+52 3.111694e+52 2.165591e+52 \n", + "16 2.642693e+52 2.896227e+52 2.212667e+52 2.213041e+52 1.790653e+52 \n", + "17 2.639209e+52 1.600225e+52 1.834074e+52 1.458769e+52 1.407996e+52 \n", + "18 1.712318e+52 7.255677e+51 1.114020e+52 1.186242e+52 1.025083e+52 \n", + "19 9.081512e+51 5.451095e+51 9.925498e+51 8.614093e+51 9.119476e+51 \n", + "\n", + " 3.131048e+06 3.339247e+06 3.561290e+06 3.798098e+06 4.050652e+06 \n", + "0 1.746724e+52 1.142765e+52 1.155513e+52 1.013063e+52 6.851335e+51 \n", + "1 6.819232e+52 7.361927e+52 6.937388e+52 5.521254e+52 4.563154e+52 \n", + "2 1.628341e+53 1.372483e+53 1.343997e+53 1.264984e+53 1.023617e+53 \n", + "3 2.254808e+53 2.174352e+53 1.838789e+53 1.819876e+53 1.590544e+53 \n", + "4 2.717593e+53 2.501916e+53 2.181535e+53 1.990705e+53 1.963625e+53 \n", + "5 2.863011e+53 2.678039e+53 2.315553e+53 1.989705e+53 1.950900e+53 \n", + "6 2.594261e+53 2.613329e+53 2.173414e+53 2.075456e+53 1.861470e+53 \n", + "7 2.387642e+53 2.345213e+53 2.193704e+53 1.705966e+53 1.731529e+53 \n", + "8 2.123134e+53 1.840041e+53 1.691727e+53 1.431448e+53 1.261554e+53 \n", + "9 1.596846e+53 1.468581e+53 1.328962e+53 1.123189e+53 9.315640e+52 \n", + "10 1.292042e+53 1.012572e+53 1.090591e+53 8.554179e+52 7.878659e+52 \n", + "11 9.341924e+52 8.638519e+52 7.397325e+52 6.592805e+52 5.976537e+52 \n", + "12 6.366229e+52 6.144144e+52 4.775543e+52 4.849689e+52 4.762654e+52 \n", + "13 4.220384e+52 4.918503e+52 3.944850e+52 3.457032e+52 2.885190e+52 \n", + "14 3.207596e+52 2.490193e+52 2.495629e+52 2.457263e+52 1.981165e+52 \n", + "15 2.104476e+52 2.120679e+52 2.012698e+52 1.412540e+52 1.609626e+52 \n", + "16 1.690462e+52 1.916662e+52 1.402938e+52 8.857395e+51 1.167084e+52 \n", + "17 1.274043e+52 9.493741e+51 8.616331e+51 8.732235e+51 8.816470e+51 \n", + "18 9.771694e+51 6.949339e+51 7.629940e+51 6.335910e+51 4.726639e+51 \n", + "19 5.419938e+51 4.528037e+51 3.783831e+51 4.377392e+51 3.675127e+51 \n", + "\n", + "[20 rows x 50 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "energy_df" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Energy deposition rate versus radius at time_explosion" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(dpi=150, facecolor='w')\n", + "plt.semilogy(model.v_middle/np.max(model.v_outer), energy_df.iloc[:, 0])\n", + "plt.xlabel(\"r/R\")\n", + "plt.ylabel(\"Energy deposition rate [eV/s$]\");" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Energy Deposition rate versus time compared to the analytic estimate" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "data": { + "text/plain": [ + "(0.7, 1.1)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "energy = energy_df.T.sum(axis=1) * u.eV.to('erg')\n", + "\n", + "def analytic_estimate(t):\n", + " return 0.6 * (0.97 * (1 - np.exp(-(40 / t)**2)) + 0.03) * (6.45 * np.exp(-t/8.8) + 1.45 * np.exp(-t/111.3)) * 1e43\n", + "\n", + "t_tardis = energy.index * u.s.to('d')\n", + "\n", + "plt.figure(dpi=150)\n", + "plt.plot(t_tardis, energy / analytic_estimate(t_tardis), \"-\")\n", + "plt.xlabel(\"t_exp (d)\")\n", + "plt.ylabel(\"Energy deposition / analytic\")\n", + "plt.legend()\n", + "plt.xlim(0, 50)\n", + "plt.ylim(0.7, 1.1)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.8.13 ('tardis')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" + }, + "vscode": { + "interpreter": { + "hash": "ab6b335b7cc719c38d57322c8d43d734486986c3f7383dc4955a9aacbba5e549" + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/contributing/in_progress/nebular_phase/positronium.rst b/docs/contributing/in_progress/nebular_phase/positronium.rst new file mode 100644 index 00000000000..443d317d3da --- /dev/null +++ b/docs/contributing/in_progress/nebular_phase/positronium.rst @@ -0,0 +1,23 @@ +*********** +Positronium +*********** + +Positronium (Ps) is the pairing of an electron and positron into a bound state analogous to a hydrogen atom (see `Wikipedia `_). This occurs when the relative motion between the positron and electron is small :cite:`Jauch1976` (:math:`\beta \rightarrow 0`, :math:`\beta=v/c`). + +The mean lifetime of Ps is very short, on the order of nanoseconds. It is most likely to produce 2 or 3 gamma-ray photons depending on if it is para-Ps (2 photons of 511 keV each) or ortho-Ps (3 photons). The Ps types are dependent on the spin state of the electron and so occur in a 1/4 (para-Ps, S = 0, Ms = 0) to 3/4 (ortho-Ps, S = 1, Ms = −1, 0, 1) ratio. The triplet emission produces a continuum of photon energies described in :cite:`Ore1949`. + +In supernovae, Ps can form when :math:`\beta`-decay occurs in the radioactive material produced as part of the explosion. The amount of Ps formed compared to immediate 2 photon annihilation in supernovae is unknown. In the galaxy, the value is determined to be :math:`0.94\pm0.04` :cite:`Milne2004`. Gamma-ray transport codes typically assume either no Ps formation (and thus all :math:`\beta`-decay releases 2 511 keV photons) or 100% Ps formation (and thus photons are released in pairs or triplets in a 1/4 to 3/4 ratio). + +According to :cite:`Jauch1976` the density-dependent reciprocal lifetime :math:`\frac{1}{\tau_2}` (called a "cross-section") of para-Ps is + +.. math:: + P \equiv \frac{1}{\tau_2} = r_0^2 \pi \rho + +where :math:`r_0` is the classical electron radius and :math:`\rho` is the electron number density. Note that the units here appear to be inverse length rather than the expected inverse time. + +For ortho-Ps, the cross-section is + +.. math:: + P \equiv \frac{1}{\tau_3} = \frac{4}{3} (\pi^2-9) \alpha r_0^2 \rho + +where :math:`\alpha` is the fine structure constant. This makes the ortho-Ps cross-section (and associated lifetime) roughly 300 times smaller than that of para-Ps. \ No newline at end of file diff --git a/docs/contributing/roadmap.rst b/docs/contributing/roadmap.rst deleted file mode 100644 index 6c8c924d81a..00000000000 --- a/docs/contributing/roadmap.rst +++ /dev/null @@ -1,124 +0,0 @@ -.. _roadmap: - -******************* -Development Roadmap -******************* - -This is a current status summary of ongoing development projects -in the TARDIS collaboration. Brief summaries of the projects as -well as timelines are listed below. More detailed descriptions -of the projects can be found in the Github Projects or the TARDIS -Enhancement Proposals (TEPS) repository under the TARDIS-SN -collaboration github page. - -Physics -####### - -* Simulate Type IIP Supernovae (Fall 2020) - - - TARDIS is currently capable of simulating type Ia and stripped - envelope supernovae, but Type IIP require new physics. - - NLTE ionization and excitation treatment of Hydrogen, relativistic - effects, free-free and bound-free processes have all been implemented - and are being integrated into the main TARDIS branch. - -* Simulate Supernovae in the Nebular Phase (Summer 2021) - - - Currently TARDIS assumes an inner boundary approximation to the - photosphere. New physics is required to handle the breakdown of the - photosphere at late times. This involves a detailed treatment of the - decay products of the radioactive isotopes in SN ejecta, as well as - their deposition in various processes such as Compton scattering, - photoabsorption and pair production. - - Deposited energy needs to be thermalized by solving the Spencer-Fano - equations, resulting in fractions of the energy going into heating, - non-thermal excitation and non-thermal ionization. - - At late times when the densities are low collisions become too - infrequent to quickly de-excite metastable energy levels. Forbidden - lines arising from these levels need to be included. Transitions between - levels have to include ion-electron collisions. - -Website and Documentation -######################### - -* Notebookify (Fall 2021) - - - TARDIS currently has detailed code and physics documentation - (https://tardis-sn.github.io/tardis/) - - In order to help new members join the TARDIS development team, we want - to create interactive jupyter notebooks that are incorporated into the - documentation to better illustrate how the code is used and show how - the physics of TARDIS works. - - Apply to Google Summer of Docs to get a dedicated, professional - documentation writer. - -Analysis -######## - -* Visualization (Fall 2020) - - - TARDIS is used to explore potential models for observed supernovae, - and it is often difficult to find optimal parameter values. - - We are working on an interactive Graphical User Interface for - TARDIS that will allow users to visually inspect their models and - obtain physical information from the TARDIS simulation easily. - - Most of the analysis will be used via Jupyter Notebooks. - - This is a Google Summer of Code project - (see https://github.com/tardis-sn/tardis/projects/5 ) with time to - completion aimed Fall 2020. - -Maintenance -########### - -* TARDIS Code Restructure (Fall 2020) - - - TARDIS needs to be more modularized to facilitate the addition of - new physics modules (see https://github.com/tardis-sn/tardis/projects/11 ) - and improve maintainability. - - Google Summer of Code project is currently underway to restructure the - model classes that TARDIS uses. - - Cython and C code for monte carlo simulation is currently being replaced - with Numba to facilitate modularity and debugging. - -Performance -########### - -* Numba (Spring 2021) - - - In the past, TARDIS has used Cython and C for performance-critical parts - of the code. However, this requires significant code overhead and is difficult - to maintain given that many of our developers are junior researchers who may - be less familiar with C code. - - As one of TARDIS’ key focuses is its use as an educational tool, we would like - to minimize the complexity of the code so that it can be understood by a wider - audience. - - We are currently in the process of converting this Cython and C code to Numba, - which we hope will allow us to maintain the performance of Cython but with code - that is now exclusively written in (numba-fied) Python. - -* GPU (Spring 20201) - - - As part of our work to optimize TARDIS’ performance, we would like to explore - GPUs and see if there are parts of the code which would benefit from GPU - acceleration. - - We are looking into using CUDA-accelerated Numba for this (does TARDIS use - matrices a lot? CuPy might also be useful here). - -Interoperability -################ - -* Carsus (Fall 2020) - - - There is evidence that the choice of atomic data has a significant impact on - model results. As part of Google Summer of Code a version control system for - atomic data is being implemented, so that previously published results become - reproducible. - - Carsus will include readers for the biggest atomic data compilations such as - CMFGEN, Chianti and Kurucz, and output the data in the Tardis format. - - Updated properties of the atomic data will be automatically collected and - ingested by Carsus. In addition, a comparison spectrum will be computed, - highlighting the effects of the new atomic data. - -* Read different model data (Fall 2020) - - - Add readers for more types of initial model data. \ No newline at end of file diff --git a/docs/outdated/hdf_writer.ipynb b/docs/contributing/tools/hdf_writer.ipynb similarity index 96% rename from docs/outdated/hdf_writer.ipynb rename to docs/contributing/tools/hdf_writer.ipynb index eba1e42912a..543d222a2af 100644 --- a/docs/outdated/hdf_writer.ipynb +++ b/docs/contributing/tools/hdf_writer.ipynb @@ -1,16 +1,10 @@ { "cells": [ { - "cell_type": "raw", - "metadata": { - "raw_mimetype": "text/restructuredtext" - }, + "cell_type": "markdown", + "metadata": {}, "source": [ - ".. _hdf_writer:\n", - "\n", - "**************************\n", - "Example Usage of HDFWriter\n", - "**************************" + "# Example Usage of HDFWriter" ] }, { @@ -255,7 +249,7 @@ "metadata": { "celltoolbar": "Raw Cell Format", "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.8.13 ('tardis')", "language": "python", "name": "python3" }, @@ -269,7 +263,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.8.13" + }, + "vscode": { + "interpreter": { + "hash": "c20eb03b6e6c860a5223c79131a5cfd0b7e61a9aa5d08c2b1400663bc6cc4e6d" + } } }, "nbformat": 4, diff --git a/docs/contributing/tools/index.rst b/docs/contributing/tools/index.rst new file mode 100644 index 00000000000..09859323645 --- /dev/null +++ b/docs/contributing/tools/index.rst @@ -0,0 +1,11 @@ +*************** +Developer Tools +*************** + +The following pages contain information about coding concepts used in the development of TARDIS: + +.. toctree:: + + hdf_writer + isotope_pd_subclass + profiling/index diff --git a/docs/outdated/isotope_pd_subclass.ipynb b/docs/contributing/tools/isotope_pd_subclass.ipynb similarity index 100% rename from docs/outdated/isotope_pd_subclass.ipynb rename to docs/contributing/tools/isotope_pd_subclass.ipynb diff --git a/docs/contributing/development/profiling/cpu_threads_dict_128_threads_1_node.csv b/docs/contributing/tools/profiling/cpu_threads_dict_128_threads_1_node.csv similarity index 100% rename from docs/contributing/development/profiling/cpu_threads_dict_128_threads_1_node.csv rename to docs/contributing/tools/profiling/cpu_threads_dict_128_threads_1_node.csv diff --git a/docs/contributing/development/profiling/index.rst b/docs/contributing/tools/profiling/index.rst similarity index 100% rename from docs/contributing/development/profiling/index.rst rename to docs/contributing/tools/profiling/index.rst diff --git a/docs/contributing/development/profiling/profiling_example.ipynb b/docs/contributing/tools/profiling/profiling_example.ipynb similarity index 80% rename from docs/contributing/development/profiling/profiling_example.ipynb rename to docs/contributing/tools/profiling/profiling_example.ipynb index 3398c10269a..d89f522e450 100644 --- a/docs/contributing/development/profiling/profiling_example.ipynb +++ b/docs/contributing/tools/profiling/profiling_example.ipynb @@ -20,10 +20,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "88cdeafd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c685f4df288947f7bc11b26978c355bb", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? [00:00" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def graph_data(testing_params, mean_dict, stdev_dict, x_axis_title, y_axis_title, graph_title, text_labels=False):\n", + " \"\"\"\n", + " Uses pyplot to graph the data given the mean and standard deviation of data.\n", + " \n", + " Parameters\n", + " ----------\n", + " testing_params : list\n", + " This is a list of the testing parameters, which is used for the axis construction.\n", + " mean_dict : dict\n", + " stdev_dict : dict\n", + " x_axis_title : str\n", + " y_axis_title : str\n", + " graph_title : str\n", + " text_labels : bool\n", + " This is a boolean parameter for if the testing parameters are text. If they are text, then\n", + " it will set each tick mark on the x-axis to be a label in testing_params.\n", + " \"\"\"\n", + " \n", + " lists = sorted(mean_dict.items())\n", + " lists_stdev = sorted(stdev_dict.items())\n", + " x, y = zip(*lists)\n", + " x_stdev, y_stdev = zip(*lists_stdev)\n", + "\n", + " fig = plt.figure(figsize=(20,10))\n", + " ax = fig.add_subplot(1,1,1)\n", + " ax.set_xlabel(x_axis_title)\n", + " ax.set_ylabel(y_axis_title)\n", + " ax.set_title(graph_title)\n", + " ax.grid(True)\n", + " \n", + " if text_labels:\n", + " xtick_spacer = np.arange(0, len(testing_params), 1)\n", + " xticks = testing_params\n", + " ax.set_xticks(xtick_spacer)\n", + " ax.set_xticklabels(xticks, rotation='horizontal', fontsize=18)\n", + " elif not text_labels:\n", + " #If there are a lot of ticks, it will reduce for visibility.\n", + " interval = testing_params[1] - testing_params[0]\n", + " if len(testing_params) > 80:\n", + " xticks = np.arange(testing_params[0], testing_params[-1]+interval, interval*2)\n", + " else:\n", + " xticks = np.arange(testing_params[0], testing_params[-1]+interval, interval)\n", + " ax.set_xticks(xticks)\n", + " \n", + " ax.plot(x, y, color='tab:blue', label=\"{} vs {}\".format(x_axis_title, y_axis_title))\n", + " plt.errorbar(x, y, yerr=y_stdev, label='stdev')\n", + " leg = plt.legend(loc='best', ncol=1, mode='expanded', fancybox=False)\n", + " leg.get_frame().set_alpha(0.5)\n", + "\n", + "graph_data(threads_numbers, threads_dict_mean, threads_dict_stdev, \"threads\", \"time (sec)\", \"threads vs time\")\n", + "graph_data(cpu_threads_numbers, cpu_threads_dict_mean, cpu_threads_dict_stdev, \"threads\", \"time (sec)\", \"threads vs cpu time\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" + }, + "vscode": { + "interpreter": { + "hash": "c20eb03b6e6c860a5223c79131a5cfd0b7e61a9aa5d08c2b1400663bc6cc4e6d" + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/contributing/development/profiling/threads_dict_128_threads_1_node.csv b/docs/contributing/tools/profiling/threads_dict_128_threads_1_node.csv similarity index 100% rename from docs/contributing/development/profiling/threads_dict_128_threads_1_node.csv rename to docs/contributing/tools/profiling/threads_dict_128_threads_1_node.csv diff --git a/docs/faq.rst b/docs/faq.rst new file mode 100644 index 00000000000..de5f9e737cc --- /dev/null +++ b/docs/faq.rst @@ -0,0 +1,39 @@ +.. _installation: + +************************** +Frequently Asked Questions +************************** + +Overview +-------- + +Welcome to the FAQ section! Here, you'll find answers to common questions about TARDIS. + +- :ref:`faq-usage` + + - :ref:`faq-usage-memory` + + +.. _faq-usage: + +Usage +----- + +.. _faq-usage-memory: + +My simulation seems to consume excessive amounts of memory +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + + +High memory usage can have many reasons. Both your model +and certain simulation settings can increase the memory +usage significantly + +1. Enabling ``track_rpacket: true`` will take up substantial + amounts of memory, in particular for higher packet counts. + Consider turning this feature off or only use it with a + small amount of packets. +2. Both the number of shells and the number of packets + increase the memory requirements. Consider using only + as many shells/ packets as are required to converge + on a result. diff --git a/docs/index.rst b/docs/index.rst index e22c73e86ca..ce71ae3b974 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -47,7 +47,6 @@ Mission Statement using an open-community model that emphasizes interdisciplinary research and science reproducibility.* - .. toctree:: :maxdepth: 2 :hidden: @@ -55,6 +54,8 @@ Mission Statement installation quickstart tutorials + how_to_guides + faq API @@ -63,7 +64,9 @@ Mission Statement :caption: Input/Output :hidden: + io/hdf/index io/configuration/index + io/model/index io/optional/index io/visualization/index io/output/index @@ -74,9 +77,10 @@ Mission Statement :caption: Physics Walkthrough :hidden: + physics/intro/index physics/setup/index physics/montecarlo/index - physics/est_and_conv/index + physics/update_and_conv/update_and_conv physics/spectrum/index @@ -87,8 +91,9 @@ Mission Statement contributing/CONTRIBUTING.md contributing/development/index + contributing/tools/index contributing/CHANGELOG.md - contributing/roadmap + contributing/in_progress/index .. toctree:: @@ -99,11 +104,3 @@ Mission Statement resources/research_done_using_TARDIS/research_papers resources/code_comparison/index resources/zreferences - - -.. toctree:: - :maxdepth: 2 - :caption: Outdated - :hidden: - - outdated/index diff --git a/docs/installation.rst b/docs/installation.rst index cc3fd79ecd6..b3fc1a886dc 100644 --- a/docs/installation.rst +++ b/docs/installation.rst @@ -4,84 +4,127 @@ Installation ************ -Before installing TARDIS, please check its :ref:`requirements -`. We provide :ref:`instructions ` for installing TARDIS using -Anaconda. Once you have installed TARDIS, check out the "Input/Output" section (in sidebar) for instructions -regarding how to perform simple TARDIS calculations. -.. _requirements_label: +.. warning:: + + - TARDIS is only supported on macOS and GNU/Linux. Windows users can run TARDIS + from our official Docker image (*coming soon*), `WSL `_ + or a Virtual Machine. + - TARDIS packages and dependencies are distributed only through the `conda `_ + package management system, therefore installation requires `Anaconda `_ + or `Miniconda `_ + to be installed on your system. -.. note:: - - TARDIS is only compatible with Python >=3.6 - - TARDIS only supports MacOS and Linux. - - We strongly recommend installing TARDIS within an Anaconda environment and to always use the latest GitHub development version. +Install with lockfiles +====================== +Conda lockfiles are platform-specific dependency files that produce repeatable environments. +These files are generated on every new release. We strongly recommend installing TARDIS using +this method by following the steps described below. -Requirements -============ +1. Download the latest lockfile for your operating system from our + `releases section `_, or run + the following command while replacing ``{platform}`` with ``linux`` or ``osx`` as appropriate. -You can see a list of all the requirements of TARDIS in the `environment definition file `_. + :: -TARDIS is using Astropy's excellent installation helpers and thus uses similar -instructions to Astropy. + $ wget -q https://raw.githubusercontent.com/tardis-sn/tardis/master/conda-{platform}-64.lock -.. _anaconda_inst_label: +2. Create and activate the ``tardis`` environment. -Installing TARDIS with Anaconda -=============================== + :: -We highly recommend using the `Anaconda `_ Python environment to install TARDIS (or -any other scientific packages for that matter). Anaconda has the advantage of -being an isolated environment that can be set to be the default one, but by no -means will mess with your other environments. It will also work on computers -where ``root``-rights are not available. Use these `instructions -`_ to install Anaconda on your -machine. The next step is to create an environment for TARDIS that contains all -of the necessary packages (this ensures that TARDIS requirements won't clash -with any other Python installs on disc): + $ conda create --name tardis --file conda-{platform}-64.lock + $ conda activate tardis -First, download the `environment definition file `_ from: -:: +3. a. Developers should `fork the repository `_, configure + GitHub to `work with SSH keys `_, + set up the `upstream remote `_, + and install the package in development mode. - https://raw.githubusercontent.com/tardis-sn/tardis/master/tardis_env3.yml + :: -To create the environment, change to the directory that you downloaded the environment definition file and run: -:: + $ git clone git@github.com:/tardis.git + $ cd tardis + $ git remote add upstream git@github.com:tardis-sn/tardis.git + $ git fetch upstream + $ git checkout upstream/master + $ python setup.py develop - conda env create -f tardis_env3.yml + .. note:: -Then to activate this environment simply do: -:: + The complete developer guidelines can be found :ref:`here `. + + b. Non-developers can install from specific releases using pip- - source activate tardis + :: -or the new method: -:: + $ pip install git+https://github.com/tardis-sn/tardis.git@{tag} - conda activate tardis + For example- -and after you are done with TARDIS you can deactivate: -:: + :: + + $ pip install git+https://github.com/tardis-sn/tardis.git@release-latest + + or trying the most recent, unreleased changes from upstream. + + :: + + $ pip install git+https://github.com/tardis-sn/tardis.git@master + +4. Once finished working, you can deactivate your environment. + + :: + + $ conda deactivate + +From now on, just activate the ``tardis`` environment before working with the TARDIS package. + +You have successfully installed TARDIS! 🎉 Please refer to `Quickstart for TARDIS `_ +to start running simulations. - conda deactivate -One does not need to recreate the environment, but simply activate it every time -TARDIS is used. +.. Install from package +.. ==================== -For TARDIS development purposes please follow the steps :ref:`here ` -until the step to install TARDIS in the development mode -``python setup.py develop``. Development guidelines for -TARDIS can be found `here `_. +.. It's also possible to install TARDIS by pulling the `conda-forge package `_ +.. into a clean environment. However, we still encourage using lockfiles to ensure +.. reproducibility of scientific results. + +.. :: + +.. $ conda create --name tardis-forge tardis-sn --channel conda-forge + + +Environment update +================== + +To update the environment after a new release, download the latest lockfile and run ``conda update``. -To install TARDIS, it is recommended to first clone our repository and -then install TARDIS, as follows: :: - git clone https://github.com/tardis-sn/tardis.git - cd tardis - python setup.py install + $ wget -q https://github.com/tardis-sn/tardis/releases/latest/download/conda-{platform}-64.lock + $ conda update --name tardis --file conda-{platform}-64.lock + +.. note:: + + If you have installed the tardis package in development mode, you should *ideally* update your environment whenever you pull latest tardis code because the new code added might be using updated (or new) dependencies. If you don't do that and your tardis installation seems broken, you can check if your environment requires update by comparing it against the latest environment file: + + :: + + $ conda compare --name tardis tardis_env3.yml + +**Recommended approach:** +We highly recommend deleting your existing environment and creating a new one using the latest lockfile whenever you need to update your environment after a new release. + +Use the following ``conda`` command to remove your current ``tardis`` environment: + +:: + $ conda remove --name tardis --all +Now, you can create a new environment by following the steps given `here `_. diff --git a/docs/io/configuration/components/index.rst b/docs/io/configuration/components/index.rst index f71282f61c4..2757b50646c 100644 --- a/docs/io/configuration/components/index.rst +++ b/docs/io/configuration/components/index.rst @@ -10,6 +10,7 @@ settings for the different aspects of the TARDIS calculation. An example configuration file (with a small subset of the options that can be specified) can be downloaded `here `_. + .. warning:: One should note that currently floats in YAML that are expressed in scientific notation need to be specified in a special format: diff --git a/docs/io/configuration/components/models/converters/arepo_snapshot.hdf5 b/docs/io/configuration/components/models/converters/arepo_snapshot.hdf5 deleted file mode 100644 index e7af8adbdaa..00000000000 Binary files a/docs/io/configuration/components/models/converters/arepo_snapshot.hdf5 and /dev/null differ diff --git a/docs/io/configuration/components/models/converters/arepo_snapshot.json b/docs/io/configuration/components/models/converters/arepo_snapshot.json deleted file mode 120000 index 36e77dc1478..00000000000 --- a/docs/io/configuration/components/models/converters/arepo_snapshot.json +++ /dev/null @@ -1 +0,0 @@ -../../../../../../tardis/io/tests/data/arepo_snapshot.json \ No newline at end of file diff --git a/docs/io/configuration/components/models/converters/arepo_to_tardis.ipynb b/docs/io/configuration/components/models/converters/arepo_to_tardis.ipynb index f386cf5e998..0dc8b3f6734 100644 --- a/docs/io/configuration/components/models/converters/arepo_to_tardis.ipynb +++ b/docs/io/configuration/components/models/converters/arepo_to_tardis.ipynb @@ -8,6 +8,24 @@ "# Converting Arepo snapshots to be usable by TARDIS" ] }, + { + "cell_type": "markdown", + "id": "2676a559", + "metadata": {}, + "source": [ + "
\n", + "\n", + "\n", + "\n", + "Note\n", + "\n", + "\n", + "This notebook cannot be run interactively!\n", + "\n", + "\n", + "
" + ] + }, { "cell_type": "markdown", "id": "b4ffa8ca", @@ -24,7 +42,7 @@ "id": "e3b3a256", "metadata": {}, "source": [ - "This parser is intended for loading Arepo output files ('snapshots'), extracting the relevant (line-of-sight dependent) data and exporting it to `csvy` files, which can in turn be used in TARDIS models ([see CSVY model](../index.html#csvy-model))." + "This parser is intended for loading Arepo output files ('snapshots'), extracting the relevant (line-of-sight dependent) data and exporting it to `csvy` files, which can in turn be used in TARDIS models ([see CSVY model](../index.rst#csvy-model))." ] }, { @@ -47,10 +65,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "998d5c4d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? [00:00\n", + "\n", + "\n", + "\n", + "Note\n", + "\n", + "\n", + "The built in functionality only loads Arepo particle species `0`, i.e. gas particles. For most (if not all) purposes connected to TARDIS, gas particles should be the only species of interest. In case you need to load a different particle species, please manually load the data.\n", + "\n", + "" ] }, { @@ -97,53 +175,71 @@ "id": "49203e1f", "metadata": {}, "source": [ - "This will fail with an error if you do not have the arepo-snap-util package installed. Since this is not a default dependency of TARDIS, lets manually load the data. *(This manual load can effectively be used to load all kinds of models unrelated to Arepo, as long as the data comes in the correct format.)*\n", + "This will fail with an error if you do not have the arepo-snap-util package installed. Since this is not a default dependency of TARDIS, the data can also be loaded manually. *(This manual load can effectively be used to load all kinds of models unrelated to Arepo, as long as the data comes in the correct format.)*\n", "\n", - "In this case the data is loaded from a `json` file. This file has been created manually by dumping the data which would have been loaded from the snapshot to a `json` file. *(The `json` file is only an example and more for illustrative purposes. As long as the data is provided in the correct format (see below) it is up to the user how it is saved/loaded.)*\n", + "The data could be loaded from a previously generated `json` file, where all necessary input from the snapshot has been dumped in. *(The `json` file is only an example and more for illustrative purposes. As long as the data is provided in the correct format (see below) it is up to the user how it is saved/loaded.)*\n", "
\n", "Code: (click to expand) \n", " \n", "```python\n", + " \n", + "### Dumping the data:\n", "data = {\n", " \"pos\" : pos.tolist(),\n", " \"vel\" : vel.tolist(),\n", " \"rho\" : rho.tolist(),\n", + " \"mass\" : mass.tolist(),\n", " \"xnuc\": [xnuc[x].tolist() for x in list(xnuc.keys())],\n", " \"time\": time,\n", "}\n", "json_string = json.dumps(data)\n", "with open('arepo_snapshot.json', 'w') as outfile:\n", " json.dump(json_string, outfile)\n", - "```\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6da0f3b9", - "metadata": {}, - "outputs": [], - "source": [ + " \n", + "### Loading the data:\n", "with open('arepo_snapshot.json') as json_file:\n", " data = json.loads(json.load(json_file))\n", "\n", "# The following lines only parse the .json file. You might not need this depending on how you saved \n", "# the snapshot data \n", - "pos, vel, rho, nucs, time = data[\"pos\"], data[\"vel\"], data[\"rho\"], data[\"xnuc\"], data[\"time\"]\n", + "pos, vel, rho, mass, nucs, time = data[\"pos\"], data[\"vel\"], data[\"rho\"], data[\"mass\"], data[\"xnuc\"], data[\"time\"]\n", "pos = np.array(pos)\n", "vel = np.array(vel)\n", "rho = np.array(rho)\n", + "mass = np.array(mass)\n", "\n", "# The nuclear data should be in a dict where each element has its own entry (with the key being the element name)\n", "xnuc = {\n", " \"ni56\" : np.array(nucs[0]),\n", " \"si28\" : np.array(nucs[1]),\n", "}\n", - "\n", + "```\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "6da0f3b9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Position data shape: (3, 1218054)\n", + "Velocity data shape: (3, 1218054)\n", + "Density data shape: (1218054,)\n", + "Mass data shape: (1218054,)\n", + "Nuclear data shape (per element): (1218054,)\n" + ] + } + ], + "source": [ "print(\"Position data shape: \", pos.shape)\n", "print(\"Velocity data shape: \", vel.shape)\n", "print(\"Density data shape: \", rho.shape)\n", + "print(\"Mass data shape: \", mass.shape)\n", "print(\"Nuclear data shape (per element): \", xnuc[\"ni56\"].shape)" ] }, @@ -156,10 +252,11 @@ "- Position in the center of mass frame (\"pos\") -> `np.array`\n", "- Velocity (\"vel\") -> `np.array`\n", "- Density (\"rho\") -> `np.array`\n", + "- Mass (\"mass\") -> `np.array`\n", "- Nuclear fraction (\"xnuc\") of each element you want to include -> `dict` containing `np.array` \n", "- Time of the snapshot (\"time\") -> `float`\n", "\n", - "The data is expected to be mapped to a Carthesian grid and should have the same shape as the one provided by the built-in tool." + "The data should have the same shape as the one provided by the built-in tool (see the given shapes above for an example)." ] }, { @@ -168,21 +265,20 @@ "metadata": {}, "source": [ "### Extracting a profile and converting it to a csvy file\n", - "Now You can create a TARDIS model. There are three possibilities on how to extract the profiles from the snapshot: \n", + "Now You can create a TARDIS model. There are two possibilities on how to extract the profiles from the snapshot: \n", " \n", - "- **Line profile**: This extracts the data along a straight line (the x-axis) \n", "- **Cone profile**: This extracts the data within a specified cone \n", "- **Full profile**: This averages over the whole simulation " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "cf051ded", "metadata": {}, "outputs": [], "source": [ - "profile = arepo.ConeProfile(pos, vel, rho, xnuc, time)" + "profile = arepo.ConeProfile(pos, vel, rho, mass, xnuc, time)" ] }, { @@ -192,7 +288,6 @@ "source": [ "This loads the data (in this example for a cone profile), which can then be cut to the ranges which you want to include in your TARDIS model. The syntax for the other profiles is similar: \n", " \n", - "- `arepo.LineProfile()` \n", "- `arepo.FullProfile()` " ] }, @@ -226,12 +321,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "0aa59e7e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "profile.create_profile(opening_angle=40)\n", + "profile.rebin(100)\n", + "profile.plot_profile()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "bfd37bad", + "metadata": {}, "source": [ - "profile.create_profile(opening_angle=40)" + "### Plotting the data\n", + "\n", + "Using `profile.plot_profile(save=, dpi=)` you can create a plot of the exported profile. Due to the large number of cells usually used in Arepo simulations, it is recommended to plot the data only **after** rebinning the profiles or exporting them to a `csvy` file (which automatically rebins the data).\n", + "\n", + "### Manually rebinning the data\n", + "Using `profile.rebin()`, you can manually rebin the data , using the mean value of the data in each bin. Rebinning only works when decreasing the number of bins. In case you need to increase resolution, you will need to create a new profile." ] }, { @@ -239,17 +363,34 @@ "id": "d619b5d0", "metadata": {}, "source": [ + "### Selecting a specific region\n", "In many cases you only want a very specific region from the snapshot, e.g. cutting out the dense, optically thick regions. This can be acchieved using the keywords `inner_radius` and `outer_radius`." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "bd934289", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "profile.create_profile(opening_angle=40, inner_radius=1e11, outer_radius=2e11)" + "profile.create_profile(opening_angle=40, inner_radius=1e11, outer_radius=2e11)\n", + "profile.rebin(100)\n", + "profile.plot_profile()\n", + "plt.show()" ] }, { @@ -257,17 +398,28 @@ "id": "dd6310ec", "metadata": {}, "source": [ - "Once you have created a profile of the desired region, you can export the profile to a `csvy` file, which in turn can be used in a TARDIS model. Here you have to specify how many shells you want to export. The profiles are rebinned using [Scipys binned_statistic function](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.binned_statistic.html), using the mean value of the data in each bin." + "Once you have created a profile of the desired region, you can export the profile to a `csvy` file, which in turn can be used in a TARDIS model. Here you have to specify how many shells you want to export. The profiles are rebinned automatically using [Scipys binned_statistic function](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.binned_statistic.html), using the mean value of the data in each bin." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "e918835b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'snapshot_converted_to_tardis.csvy'" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "profile.export(20, \"snapshot_converted_to_tardis.csvy\")" + "profile.export(20, \"snapshot_converted_to_tardis.csvy\", overwrite=True)" ] }, { @@ -300,29 +452,6 @@ "" ] }, - { - "cell_type": "markdown", - "id": "5a5ec37b", - "metadata": {}, - "source": [ - "### Manually rebinning the data\n", - "Using `profile.rebin(, statistic=)`, you can manually rebin the data and use all `` keywords accepted by the `scipy.stats.binned_statistic` function. In this case you should pass the `statistic=None` keyword to the `export` function, so the data does not get rebinned twice." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "15fd5925", - "metadata": {}, - "outputs": [], - "source": [ - "profile.create_profile(opening_angle=40, inner_radius=1e11, outer_radius=2e11, show_plot=False)\n", - "profile.rebin(20)\n", - "profile.plot_profile()\n", - "plt.show()\n", - "profile.export(20, \"snapshot_converted_to_tardis.csvy\", statistic=None)" - ] - }, { "cell_type": "markdown", "id": "da49c11a", @@ -340,7 +469,7 @@ "\n", "To export the same profile as in the example above you can run:\n", "```bash\n", - "python .//arepo.py snapshot.hdf5 snapshot_converted.csvy -o 40 -n 20 --inner_radius 1e11 --outer_radius 2e11 -e ni56 si28 --save_plot plot.png --resolution 32 --plot_rebinned plot_binned.png\n", + "python .//arepo.py snapshot.hdf5 snapshot_converted.csvy -o 40 -n 20 --inner_radius 1e11 --outer_radius 2e11 -e ni56 si28 --plot plot.png\n", "```\n", "\n", "This will also save diagnostic plots of both the raw and rebinned profiles. For more information on how to use the command line tool run:\n", @@ -387,7 +516,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.12" + "version": "3.8.13" + }, + "vscode": { + "interpreter": { + "hash": "c20eb03b6e6c860a5223c79131a5cfd0b7e61a9aa5d08c2b1400663bc6cc4e6d" + } } }, "nbformat": 4, diff --git a/docs/io/configuration/components/models/converters/stella_to_tardis.ipynb b/docs/io/configuration/components/models/converters/stella_to_tardis.ipynb deleted file mode 100644 index e00103152f0..00000000000 --- a/docs/io/configuration/components/models/converters/stella_to_tardis.ipynb +++ /dev/null @@ -1,118 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# Converting STELLA Files to be usable by TARDIS" - ], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "from tardis.io.parsers import stella\n", - "from astropy import units as u" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "data = stella.read_stella_data('mesa.stella.dat')" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "data" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "# extract outer radius boundaries \n", - "radii = data.loc[:,'outer_edge_r'].values * u.cm\n", - "\n", - "# calculate t_explosion\n", - "t_explosion = 50 * u.day #days\n", - "\n", - "# calculate outer velocities of each zone assuming homologous expansion (v=r/t) \n", - "velocities = (radii/t_explosion).to(u.km/u.s) \n", - "\n", - "# create a new column of our velocities (OPTIONAL)\n", - "data['velocity'] = velocities" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "density_dat = data[['velocity', 'avg_density']].reset_index(drop=True)\n", - "density_dat.to_csv('density_parse.csv', sep = ' ')" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "# import all elements and isotopes and export to TARDIS\n", - "data_elements = data.iloc[:,12:33].reset_index(drop=True)\n", - "data_elements.to_csv('abund_parse.csv', sep = ' ')" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "density_dat" - ], - "outputs": [], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": null, - "source": [ - "data_elements" - ], - "outputs": [], - "metadata": {} - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.10" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file diff --git a/docs/io/configuration/components/models/index.rst b/docs/io/configuration/components/models/index.rst index 7fb87af0e18..ff7bc621f35 100644 --- a/docs/io/configuration/components/models/index.rst +++ b/docs/io/configuration/components/models/index.rst @@ -96,7 +96,6 @@ Here we aim to provide converters for the most commonly used file formats. .. toctree:: :maxdepth: 2 - converters/stella_to_tardis converters/cmfgen converters/arepo_to_tardis @@ -279,8 +278,8 @@ factor of .8, etc. .. note:: ``t_rad`` and ``dilution_factor`` are the values of the temperature and dilution factor for the first - iteration, and will be updated in subsequent iterations (see :ref:`est_and_conv`). To prevent these - quantities from being changed, you must set the damping constant to zero in the :ref:`Damped Convergence + iteration, and will be updated in subsequent iterations (see :doc:`../../../../physics/update_and_conv/update_and_conv`). + To prevent these quantities from being changed, you must set the damping constant to zero in the :ref:`Damped Convergence Configuration ` in the Monte Carlo section of the configuration file. CSVY Model Tutorial diff --git a/docs/io/configuration/components/montecarlo.rst b/docs/io/configuration/components/montecarlo.rst index d8c8d548744..0f57b2a50ed 100644 --- a/docs/io/configuration/components/montecarlo.rst +++ b/docs/io/configuration/components/montecarlo.rst @@ -16,7 +16,7 @@ of the Monte Carlo loop (which calculates the final spectrum!) when the radiatio ``no_of_packets`` to create a less noisy output spectrum. ``no_of_virtual_packets`` can also be set to greater than 0 (a useful number is 3) to use the Virtual Packet formalism. Increasing this number drastically increases computational costs (and memory requirements if they are logged). The ``iterations`` parameter describes the maximum number of Monte Carlo loops executed in a simulation before it ends. Convergence criteria can be used to make the simulation stop -sooner when the convergence threshold has been reached (see :ref:`convergence`). +sooner when the convergence threshold has been reached (see :doc:`../../../physics/update_and_conv/update_and_conv`). .. _conv-config: diff --git a/docs/io/configuration/components/plasma.rst b/docs/io/configuration/components/plasma.rst index cb9ab851e92..7ff017c9776 100644 --- a/docs/io/configuration/components/plasma.rst +++ b/docs/io/configuration/components/plasma.rst @@ -16,14 +16,14 @@ ionization equilibrium and level population calculations (see :ref:`plasma` for The radiative rates describe how to calculate the :math:`J_\textrm{blue}` needed for the :ref:`nlte` calculations and :ref:`macroatom` calculations. There are three options for ``radiative_rates_type``: -1) ``lte``, in which +1) ``blackbody``, in which :math:`J_\textrm{blue} = \textrm{Blackbody}(T_\textrm{rad})` -2) ``nebular`` in which +2) ``dilute-blackbody`` in which :math:`J_\textrm{blue} = W \times \textrm{Blackbody}(T_\textrm{rad})` 3) ``detailed`` in which the :math:`J_\textrm{blue}` -are calculated using an estimator (this is described in :ref:`estimators`). +are calculated using an estimator (this is described in :doc:`../../../physics/montecarlo/estimators`). TARDIS currently supports three different kinds of line interaction: ``scatter`` --- a resonance scattering implementation, ``macroatom`` --- the most complex form of line interaction described in :ref:`macroatom` and ``downbranch`` a simplified @@ -32,6 +32,25 @@ version of ``macroatom`` in which only downward transitions are allowed (see :re Finally, ``w_epsilon`` describes the dilution factor to use to calculate :math:`J_\textrm{blue}` that are 0, which causes problems with the code (so :math:`J_\textrm{blue}` are set to a very small number). +Continuum Interaction +^^^^^^^^^^^^^^^^^^^^^ + +.. code-block:: yaml + + plasma: + link_t_rad_t_electron: 1.0 + continuum_interaction: + species: + - H I + - H II + - He I + - He II + enable_adiabatic_cooling: True + +This will add continuum interactions for all specified species. Setting :math:`T_\textrm{rad} = T_\textrm{electron}` through +``link_t_rad_t_electron: 1.0`` is recommended to enforce LTE (unless the simulation uses NLTE treatment). +``enable_adiabatic_cooling`` enables adiabatic cooling. + NLTE ^^^^ @@ -44,4 +63,31 @@ NLTE The NLTE configuration currently allows setting ``coronal_approximation``, which sets all :math:`J_\textrm{blue}` to 0. This is useful for debugging with :term:`chianti` for example. Furthermore, one can enable 'classical_nebular' to set all :math:`\beta_\textrm{Sobolev}` to 1. Both options are used for checking with other codes and should not be enabled in -normal operations. \ No newline at end of file +normal operations. + +NLTE Ionization +^^^^^^^^^^^^^^^ + +.. code-block:: yaml + + plasma: + nlte_ionization_species: [H I, H II, He I, He II] + nlte_solver: root + +This option allows the user to specify which species should be included in the NLTE ionization treatment. Note that the +species must be present in the continuum interaction species as well. +Here, ``nlte_solver`` can be set to ``root`` or ``lu``. ``root`` is the default and uses a root solver to calculate the +NLTE populations. ``lu`` uses an iterative LU decomposition scheme to calculate the NLTE populations. + +.. note :: + + ``lu`` iterates over the solutions up to a set tolerance. This tolerance is currently hard-coded to 1e-3. This + can be changed in the code by changing the ``NLTE_POPULATION_SOLVER_TOLERANCE`` constant in ``tardis/plasma/properties/nlte_rate_equation_solver.py``. + Furthermore, the maximum number of iterations is set to 1000. This can be changed in the code by changing the ``NLTE_POPULATION_SOLVER_MAX_ITERATIONS`` + constant in ``tardis/plasma/properties/nlte_rate_equation_solver.py``. + +.. warning :: + + ``lu`` is generally faster than ``root`` but does not solve explicitly for the electron density. Therefore, it is + not recommended to use ``lu`` for simulations where the electron density is important (e.g. for simulations where + NLTE excitation is important). diff --git a/docs/io/configuration/components/spectrum.rst b/docs/io/configuration/components/spectrum.rst index b93776caa0c..6f20b3b8519 100644 --- a/docs/io/configuration/components/spectrum.rst +++ b/docs/io/configuration/components/spectrum.rst @@ -17,7 +17,7 @@ pages below: * virtual: :ref:`Virtual Packet Scheme ` * integrated: :ref:`Formal Integral Method ` -The three methods can be specified when plotting the spectrum (see the :doc:`quickstart guide <../../../quickstart/quickstart>` for an example of this). +The three methods can be specified when plotting the spectrum (see the :doc:`quickstart guide <../../../quickstart>` for an example of this). The following example shows how to edit variables for the different methods. @@ -38,12 +38,12 @@ The following example shows how to edit variables for the different methods. virtual_packet_logging: True -One can also change these parameters as they wish by reading in the configuration file and editing them before running the simulation (see :doc:`Reading a Configuration <../read_configuration>`). +One can also change these parameters as they wish by reading in the configuration file and editing them before running the simulation (see :doc:`Reading a Configuration <../tutorial_read_configuration>`). .. warning:: As of now, the `method` argument serves no purpose other than adding the integrated spectrum to the HDF output when "integrated" is used as the method - (see :doc:`Storing Simulations to HDF <../../output/to_hdf>`). + (see :doc:`How to Store Simulations to HDF <../../output/how_to_to_hdf>`). diff --git a/docs/io/configuration/components/supernova.rst b/docs/io/configuration/components/supernova.rst index 02cb62b864d..f01583c5c92 100644 --- a/docs/io/configuration/components/supernova.rst +++ b/docs/io/configuration/components/supernova.rst @@ -8,7 +8,7 @@ The supernova component of the configuration file contains some key information .. jsonschema:: schemas/supernova.yml -As luminosity (in units of energy/s) is computed by integrating over the spectral luminosity (in units of energy/s/wavelength), TARDIS sums over all discrete energy packets to compute luminosity when ran, attempting to converge the output spectrum to match `luminosity_requested` (see :ref:`est_and_conv`). `luminosity_requested` can be given in standard units, such as erg/s or J/s, or in logarithmic units such as log_lsun. The range over which TARDIS sums these energy packets is set by default from 0 to infinity via `luminosity_wavelength_start` and `luminosity_wavelength_end`, respectively, so as to generate a spectrum whose total luminosity across the entire spectrum is `luminosity_requested`. However, if in the event only the luminosity within a certain range of wavelengths is known, then `luminosity_wavelength_start` and `luminosity_wavelength_end` can be changed as necessary to reflect this, allowing TARDIS to attempt to create a spectrum whose luminosity within the set range will converge to the value defined in `luminosity_requested`. +As luminosity (in units of energy/s) is computed by integrating over the spectral luminosity (in units of energy/s/wavelength), TARDIS sums over all discrete energy packets to compute luminosity when ran, attempting to converge the output spectrum to match `luminosity_requested` (see :doc:`../../../physics/update_and_conv/update_and_conv`). `luminosity_requested` can be given in standard units, such as erg/s or J/s, or in logarithmic units such as log_lsun. The range over which TARDIS sums these energy packets is set by default from 0 to infinity via `luminosity_wavelength_start` and `luminosity_wavelength_end`, respectively, so as to generate a spectrum whose total luminosity across the entire spectrum is `luminosity_requested`. However, if in the event only the luminosity within a certain range of wavelengths is known, then `luminosity_wavelength_start` and `luminosity_wavelength_end` can be changed as necessary to reflect this, allowing TARDIS to attempt to create a spectrum whose luminosity within the set range will converge to the value defined in `luminosity_requested`. As an example, here is a sample code which will generate a specturm where only the luminosity of the visible light portion of the spectrum is given. Here, the output spectrum will have a luminosity of approximately :math:`10^{9.44}L_{sun}` within the visible range. diff --git a/docs/io/configuration/index.rst b/docs/io/configuration/index.rst index b7293213f39..b2330f44ebd 100644 --- a/docs/io/configuration/index.rst +++ b/docs/io/configuration/index.rst @@ -9,12 +9,11 @@ The necessary parameters for a TARDIS simulation are provided via a `YAML `_ is a high-performance data software library and file format to manage, process, and store your heterogeneous data. HDF5 is built for fast I/O processing and storage. + +In TARDIS, it is used to store the data from simulations and other actions. + + +HDF5 structure +-------------- + +All this data is stored in the following structure: + +- **File:** a contiguous string of bytes in a computer store (memory, disk, etc.), and the bytes represent zero or more objects of the model. +- **Group:** a collection of objects (including groups). +- **Dataset:** a multidimensional array of data elements with attributes and other metadata. +- **Dataspace:** a description of the dimensions of a multidimensional array. +- **Datatype:** a description of a specific class of data element, including its storage layout as a pattern of bits. +- **Attribute:** a named data value associated with a group, dataset, or named datatype. +- **Property List:** a collection of parameters (some permanent and some transient) controlling options in the library. +- **Link:** the way objects are connected + +This structure is stored in a file with the extension “.h5”. + + +Libraries +--------- + +TARDIS uses `these libraries `_ in Python, but they could be installed on the computer to work with the H5 files. The advantage of installing the libraries on the computer is that it allows you to handle the HDF5 with command-line instructions quickly and powerfully. + + +HDFView +------- + +`HDFView is a visual tool `_ written in Java for browsing and editing HDF (HDF5 and HDF4) files. Using HDFView, you can: + +- View a file hierarchy in a tree structure. +- Create new files; add or delete groups and datasets. +- View and modify the content of a dataset. +- Add, delete, and modify attributes. + + +Extract data +============ + + +Extract data using the HDF5 libraries +------------------------------------- + +In TARDIS the generated data is valuable because it has been reviewed and validated. For this reason, TARDIS tests against the generated data. + +Then the question is how to extract data from the actual “.h5” files. It could be easily pulled and followed by the next commands: + +Copy the specific group of data in a new “.h5” file. + +.. code-block:: shell + + h5copy \ + --input unit_test_data.h5 \ + --source "/test_transport_simple/transport_state" \ + --output TestTransportSimple.h5\ + --destination "/transport_state" + +Compare and validate that the original and copy data are the same. + +.. code-block:: shell + + h5diff \ + -r \ + unit_test_data.h5 \ + TestTransportSimple.h5 \ + /test_transport_simple/transport_state/j_blue_estimator \ + /transport_state/j_blue_estimator + +It produces the following output, which confirms that the data is the same: + +.. code-block:: text + + attribute: > and > + 0 differences found + attribute: > and <TITLE of </transport_state/j_blue_estimator>> + 0 differences found + … + attribute: <VERSION of </test_transport_simple/transport_state/j_blue_estimator/block0_values>> and <VERSION of </transport_state/j_blue_estimator/block0_values>> + 0 differences found + attribute: <transposed of </test_transport_simple/transport_state/j_blue_estimator/block0_values>> and <transposed of </transport_state/j_blue_estimator/block0_values>> + 0 differences found diff --git a/docs/io/images/energy_level_widget_demo.gif b/docs/io/images/energy_level_widget_demo.gif new file mode 100644 index 00000000000..a9242e39b00 Binary files /dev/null and b/docs/io/images/energy_level_widget_demo.gif differ diff --git a/docs/io/images/energy_level_widget_options.gif b/docs/io/images/energy_level_widget_options.gif new file mode 100644 index 00000000000..d3c7361b057 Binary files /dev/null and b/docs/io/images/energy_level_widget_options.gif differ diff --git a/docs/io/images/packet_diagram.jpg b/docs/io/images/packet_diagram.jpg new file mode 100644 index 00000000000..409af1b39b8 Binary files /dev/null and b/docs/io/images/packet_diagram.jpg differ diff --git a/docs/io/model/cmfgen_model.csv b/docs/io/model/cmfgen_model.csv new file mode 120000 index 00000000000..8f4a56d0de5 --- /dev/null +++ b/docs/io/model/cmfgen_model.csv @@ -0,0 +1 @@ +../../../tardis/io/tests/data/cmfgen_model.csv \ No newline at end of file diff --git a/docs/io/model/how_to_read_cmfgen_model.ipynb b/docs/io/model/how_to_read_cmfgen_model.ipynb new file mode 100644 index 00000000000..756f0a7a106 --- /dev/null +++ b/docs/io/model/how_to_read_cmfgen_model.ipynb @@ -0,0 +1,335 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# How to Read CMFGEN models with TARDIS" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Packets: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from tardis.io.model import read_cmfgen_model" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "cmfgen_model = read_cmfgen_model('cmfgen_model.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>velocity</th>\n", + " <th>temperature</th>\n", + " <th>densities</th>\n", + " <th>electron_densities</th>\n", 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<td>0.2</td>\n", + " <td>0.8</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>6</th>\n", + " <td>1115.15450</td>\n", + " <td>76459.592</td>\n", + " <td>4.256360e-09</td>\n", + " <td>2.600000e+14</td>\n", + " <td>0.0</td>\n", + " <td>0.2</td>\n", + " <td>0.8</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>7</th>\n", + " <td>1183.37410</td>\n", + " <td>76633.367</td>\n", + " <td>4.268308e-09</td>\n", + " <td>2.610000e+14</td>\n", + " <td>0.0</td>\n", + " <td>0.2</td>\n", + " <td>0.8</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>8</th>\n", + " <td>1255.76700</td>\n", + " <td>77312.120</td>\n", + " <td>4.290997e-09</td>\n", + " <td>2.640000e+14</td>\n", + " <td>0.5</td>\n", + " <td>0.5</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>9</th>\n", + " <td>1332.58860</td>\n", + " <td>79602.375</td>\n", + " <td>4.339684e-09</td>\n", + " <td>2.720000e+14</td>\n", + " <td>0.5</td>\n", + " <td>0.5</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " velocity temperature densities electron_densities c o mg \\\n", + "0 \n", + "0 871.66905 76395.577 4.253719e-09 2.600000e+14 0.0 0.0 0.0 \n", + "1 877.44269 76395.577 4.253719e-09 2.600000e+14 0.0 0.0 0.0 \n", + "2 894.99407 76395.631 4.253719e-09 2.600000e+14 0.0 0.0 0.0 \n", + "3 931.15710 76396.057 4.253719e-09 2.600000e+14 0.0 0.2 0.8 \n", + "4 990.30752 76399.042 4.253727e-09 2.600000e+14 0.0 0.3 0.7 \n", + "5 1050.86760 76411.983 4.253954e-09 2.600000e+14 0.0 0.2 0.8 \n", + "6 1115.15450 76459.592 4.256360e-09 2.600000e+14 0.0 0.2 0.8 \n", + "7 1183.37410 76633.367 4.268308e-09 2.610000e+14 0.0 0.2 0.8 \n", + "8 1255.76700 77312.120 4.290997e-09 2.640000e+14 0.5 0.5 0.0 \n", + "9 1332.58860 79602.375 4.339684e-09 2.720000e+14 0.5 0.5 0.0 \n", + "\n", + " si ni56 ni58 \n", + "0 \n", + "0 0.6 0.4 0.0 \n", + "1 0.1 0.5 0.4 \n", + "2 0.3 0.0 0.7 \n", + "3 0.0 0.0 0.0 \n", + "4 0.0 0.0 0.0 \n", + "5 0.0 0.0 0.0 \n", + "6 0.0 0.0 0.0 \n", + "7 0.0 0.0 0.0 \n", + "8 0.0 0.0 0.0 \n", + "9 0.0 0.0 0.0 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cmfgen_model.data" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'t0': <Quantity 0.976 d>,\n", + " 'velocity_unit': Unit(\"km / s\"),\n", + " 'temperature_unit': Unit(\"K\"),\n", + " 'densities_unit': Unit(\"g / cm3\"),\n", + " 'electron_densities_unit': Unit(\"1 / cm3\")}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cmfgen_model.metadata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/io/model/how_to_read_stella_model.ipynb b/docs/io/model/how_to_read_stella_model.ipynb new file mode 100644 index 00000000000..82427924175 --- /dev/null +++ b/docs/io/model/how_to_read_stella_model.ipynb @@ -0,0 +1,535 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# How to Read STELLA models with TARDIS" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Packets: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from tardis.io.model import read_stella_model" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "stella_model = read_stella_model('mesa.stella.dat')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>mass_of_cell</th>\n", + " <th>cell_center_m</th>\n", + " <th>cell_center_r</th>\n", + " <th>cell_center_v</th>\n", + " <th>avg_density</th>\n", + " <th>radiation_pressure</th>\n", + " <th>avg_temperature</th>\n", + " <th>radiation_temperature</th>\n", + " <th>avg_opacity</th>\n", + " <th>tau</th>\n", + " <th>...</th>\n", + " <th>cr48</th>\n", + " <th>cr60</th>\n", + " <th>fe52</th>\n", + " <th>fe54</th>\n", + " <th>fe56</th>\n", + " <th>co56</th>\n", + " <th>ni56</th>\n", + " <th>luminosity</th>\n", + " <th>n_bar</th>\n", + " <th>n_e</th>\n", + " </tr>\n", + " <tr>\n", + " <th>0</th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>6.006769e+29</td>\n", + " <td>5.190243e+33</td>\n", + " 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<td>3.729654e+41</td>\n", + " <td>9.283015e+09</td>\n", + " <td>4.408753e+05</td>\n", + " </tr>\n", + " <tr>\n", + " <th>397</th>\n", + " <td>1.511951e+31</td>\n", + " <td>2.614332e+34</td>\n", + " <td>1.576303e+15</td>\n", + " <td>3.545750e+08</td>\n", + " <td>1.168519e-14</td>\n", + " <td>0.128874</td>\n", + " <td>3192.480784</td>\n", + " <td>2673.651060</td>\n", + " <td>0.000467</td>\n", + " <td>0.000941</td>\n", + " <td>...</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.000017</td>\n", + " <td>0.0</td>\n", + " <td>1.108306e-14</td>\n", + " <td>3.719770e+41</td>\n", + " <td>7.040251e+09</td>\n", + " <td>3.305759e+05</td>\n", + " </tr>\n", + " <tr>\n", + " <th>398</th>\n", + " <td>1.512167e+31</td>\n", + " <td>2.615844e+34</td>\n", + " <td>1.632356e+15</td>\n", + " <td>3.682800e+08</td>\n", + " <td>8.348776e-15</td>\n", + " <td>0.119719</td>\n", + " <td>3126.918024</td>\n", + " <td>2624.851429</td>\n", + " <td>0.000525</td>\n", + " <td>0.000695</td>\n", + " <td>...</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.000017</td>\n", + " <td>0.0</td>\n", + " <td>1.108306e-14</td>\n", + " <td>3.719654e+41</td>\n", + " <td>5.027256e+09</td>\n", + " <td>2.333801e+05</td>\n", + " </tr>\n", + " <tr>\n", + " <th>399</th>\n", + " <td>1.512377e+31</td>\n", + " <td>2.617356e+34</td>\n", + " <td>1.698066e+15</td>\n", + " <td>4.244850e+08</td>\n", + " <td>6.601396e-15</td>\n", + " <td>0.110183</td>\n", + " <td>3055.657872</td>\n", + " <td>2570.946173</td>\n", + " <td>0.000569</td>\n", + " <td>0.000448</td>\n", + " <td>...</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.000017</td>\n", + " <td>0.0</td>\n", + " <td>1.108306e-14</td>\n", + " <td>3.709770e+41</td>\n", + " <td>3.975759e+09</td>\n", + " <td>1.842764e+05</td>\n", + " </tr>\n", + " <tr>\n", + " <th>400</th>\n", + " <td>1.512582e+31</td>\n", + " <td>2.618867e+34</td>\n", + " <td>2.126273e+15</td>\n", + " <td>4.732800e+08</td>\n", + " <td>7.649548e-16</td>\n", + " <td>0.076237</td>\n", + " <td>2780.233476</td>\n", + " <td>2344.794175</td>\n", + " <td>0.001368</td>\n", + " <td>0.000000</td>\n", + " <td>...</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.000017</td>\n", + " <td>0.0</td>\n", + " <td>1.108306e-14</td>\n", + " <td>3.679885e+41</td>\n", + " <td>4.606795e+08</td>\n", + " <td>2.123225e+04</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>400 rows × 36 columns</p>\n", + "</div>" + ], + "text/plain": [ + " mass_of_cell cell_center_m cell_center_r cell_center_v avg_density \\\n", + "0 \n", + "1 6.006769e+29 5.190243e+33 2.517209e+13 3.930633e+06 1.005529e-11 \n", + "2 1.262406e+30 5.191506e+33 2.970626e+13 5.050403e+06 2.928088e-11 \n", + "3 1.264624e+30 5.192771e+33 3.198879e+13 5.680288e+06 4.619659e-11 \n", + "4 1.263067e+30 5.194034e+33 3.357130e+13 6.135230e+06 5.896887e-11 \n", + "5 1.259387e+30 5.195293e+33 3.480638e+13 6.495173e+06 6.912717e-11 \n", + ".. ... ... ... ... ... \n", + "396 1.511731e+31 2.612818e+34 1.533756e+15 3.435050e+08 1.540408e-14 \n", + "397 1.511951e+31 2.614332e+34 1.576303e+15 3.545750e+08 1.168519e-14 \n", + "398 1.512167e+31 2.615844e+34 1.632356e+15 3.682800e+08 8.348776e-15 \n", + "399 1.512377e+31 2.617356e+34 1.698066e+15 4.244850e+08 6.601396e-15 \n", + "400 1.512582e+31 2.618867e+34 2.126273e+15 4.732800e+08 7.649548e-16 \n", + "\n", + " radiation_pressure avg_temperature radiation_temperature avg_opacity \\\n", + "0 \n", + "1 11237.954506 45943.453023 45943.453023 0.162712 \n", + "2 11236.544022 45942.182229 45942.182229 0.164412 \n", + "3 11133.526767 45836.518142 45836.518142 0.165012 \n", + "4 11133.526767 45836.518142 45836.518142 0.165310 \n", + "5 11032.838720 45732.362031 45732.362031 0.165510 \n", + ".. ... ... ... ... \n", + "396 0.136196 3259.329684 2710.845252 0.000430 \n", + "397 0.128874 3192.480784 2673.651060 0.000467 \n", + "398 0.119719 3126.918024 2624.851429 0.000525 \n", + "399 0.110183 3055.657872 2570.946173 0.000569 \n", + "400 0.076237 2780.233476 2344.794175 0.001368 \n", + "\n", + " tau ... cr48 cr60 fe52 fe54 fe56 co56 ni56 \\\n", + "0 ... \n", + "1 5403.504881 ... 0.0 0.0 0.0 0.0 0.000021 0.0 4.079500e-03 \n", + "2 5381.678444 ... 0.0 0.0 0.0 0.0 0.000021 0.0 4.079500e-03 \n", + "3 5364.280084 ... 0.0 0.0 0.0 0.0 0.000021 0.0 4.079500e-03 \n", + "4 5348.854704 ... 0.0 0.0 0.0 0.0 0.000021 0.0 4.079500e-03 \n", + "5 5334.724893 ... 0.0 0.0 0.0 0.0 0.000021 0.0 4.079500e-03 \n", + ".. ... ... ... ... ... ... ... ... ... \n", + "396 0.001173 ... 0.0 0.0 0.0 0.0 0.000017 0.0 1.108306e-14 \n", + "397 0.000941 ... 0.0 0.0 0.0 0.0 0.000017 0.0 1.108306e-14 \n", + "398 0.000695 ... 0.0 0.0 0.0 0.0 0.000017 0.0 1.108306e-14 \n", + "399 0.000448 ... 0.0 0.0 0.0 0.0 0.000017 0.0 1.108306e-14 \n", + "400 0.000000 ... 0.0 0.0 0.0 0.0 0.000017 0.0 1.108306e-14 \n", + "\n", + " luminosity n_bar n_e \n", + "0 \n", + "1 7.648868e+38 6.055413e+12 2.412188e+12 \n", + "2 9.609214e+38 1.762304e+13 6.969790e+12 \n", + "3 1.050921e+39 2.783916e+13 1.091728e+13 \n", + "4 1.100921e+39 3.545183e+13 1.392188e+13 \n", + "5 1.140921e+39 4.166219e+13 1.632649e+13 \n", + ".. ... ... ... \n", + "396 3.729654e+41 9.283015e+09 4.408753e+05 \n", + "397 3.719770e+41 7.040251e+09 3.305759e+05 \n", + "398 3.719654e+41 5.027256e+09 2.333801e+05 \n", + "399 3.709770e+41 3.975759e+09 1.842764e+05 \n", + "400 3.679885e+41 4.606795e+08 2.123225e+04 \n", + "\n", + "[400 rows x 36 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stella_model.data" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'t_max': <Quantity 50. d>,\n", + " 'zones': 400,\n", + " 'inner_boundary_mass': <Quantity 5.19024252e+33 g>,\n", + " 'total_mass': <Quantity 2.61886734e+34 g>,\n", + " 'mass_of_cell_unit': Unit(\"g\"),\n", + " 'cell_center_m_unit': Unit(\"g\"),\n", + " 'cell_center_r_unit': Unit(\"cm\"),\n", + " 'cell_center_v_unit': Unit(\"cm / s\"),\n", + " 'outer_edge_m_unit': Unit(\"g\"),\n", + " 'outer_edge_r_unit': Unit(\"cm\")}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stella_model.metadata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/io/model/index.rst b/docs/io/model/index.rst new file mode 100644 index 00000000000..c43d7a5a7a6 --- /dev/null +++ b/docs/io/model/index.rst @@ -0,0 +1,11 @@ +************** +Reading Models +************** + +TARDIS can read a variety of models. The following models are currently supported: + +.. toctree:: + :maxdepth: 1 + + how_to_read_stella_model.ipynb + how_to_read_cmfgen_model.ipynb diff --git a/docs/io/model/mesa.stella.dat b/docs/io/model/mesa.stella.dat new file mode 120000 index 00000000000..560c3f5be56 --- /dev/null +++ b/docs/io/model/mesa.stella.dat @@ -0,0 +1 @@ +../../../tardis/io/model/tests/data/mesa.stella.dat \ No newline at end of file diff --git a/docs/io/optional/custom_source.ipynb b/docs/io/optional/custom_source.ipynb deleted file mode 100644 index d1f4b988116..00000000000 --- a/docs/io/optional/custom_source.ipynb +++ /dev/null @@ -1,193 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Running TARDIS with a Custom Packet Source" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "By default, TARDIS generates energy packets using its `BasePacketSource` class, which models the photosphere of the supernova as a perfect blackbody (see [Energy Packet Initialization](../../physics/montecarlo/initialization.ipynb)). However, users may create their own packet source, as will be shown in this notebook. In order to do this, a user must create a class (that can but does not have to inherit from `BasePacketSource`) which contains a method `create_packets` that takes in (in this order):\n", - "- the photospheric temperature\n", - "- the number of packets\n", - "- a random number generator\n", - "- the photospheric radius\n", - "\n", - "and returns arrays of the radii, frequencies, propogation directions, and energies of the ensemble of packets (once again see [Energy Packet Initialization](../../physics/montecarlo/initialization.ipynb) for more information). To use your packet source in a run of TARDIS, you must pass an instance of your class into the `run_tardis` function under the `packet_source` keyword argument.\n", - "\n", - ".. note:: In both the `BasePacketSource` class and in the example here, all packets are generated at the same radius. This need not be true in general (although the `create_packets` method should only take in a single radius as its argument).\n", - "\n", - "We show an example of how a custom packet source is used:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Import necessary packages\n", - "import numpy as np\n", - "from tardis import constants as const\n", - "from astropy import units as u\n", - "from tardis.montecarlo.packet_source import BasePacketSource\n", - "from tardis import run_tardis\n", - "import matplotlib.pyplot as plt\n", - "from tardis.io.atom_data import download_atom_data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Download the atomic data used for a run of TARDIS\n", - "download_atom_data('kurucz_cd23_chianti_H_He')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Create a packet source class that contains a create_packets method\n", - "class TruncBlackbodySource(BasePacketSource):\n", - " \"\"\"\n", - " Custom inner boundary source class to replace the Blackbody source\n", - " with a truncated Blackbody source.\n", - " \"\"\"\n", - " \n", - " def __init__(self, seed, truncation_wavelength):\n", - " super().__init__(seed)\n", - " self.rng = np.random.default_rng(seed=seed)\n", - " self.truncation_wavelength = truncation_wavelength\n", - " \n", - " def create_packets(self, T, no_of_packets, rng, radius,\n", - " drawing_sample_size=None):\n", - " \"\"\"\n", - " Packet source that generates a truncated Blackbody source.\n", - " \n", - " Parameters\n", - " ----------\n", - " T : float\n", - " Blackbody temperature\n", - " no_of_packets : int\n", - " number of packets to be created\n", - " truncation_wavelength : float\n", - " truncation wavelength in Angstrom. \n", - " Only wavelengths higher than the truncation wavelength\n", - " will be sampled.\n", - " \"\"\"\n", - " \n", - " # Makes uniform array of packet radii\n", - " radii = np.ones(no_of_packets) * radius\n", - "\n", - " # Use mus and energies from normal blackbody source.\n", - " mus = self.create_zero_limb_darkening_packet_mus(no_of_packets, self.rng)\n", - " energies = self.create_uniform_packet_energies(no_of_packets, self.rng)\n", - "\n", - " # If not specified, draw 2 times as many packets and reject any beyond no_of_packets.\n", - " if drawing_sample_size is None:\n", - " drawing_sample_size = 2 * no_of_packets\n", - "\n", - " # Blackbody will be truncated below truncation_wavelength / above truncation_frequency.\n", - " truncation_frequency = u.Quantity(self.truncation_wavelength, u.Angstrom).to(\n", - " u.Hz, equivalencies=u.spectral()).value\n", - " \n", - " # Draw nus from blackbody distribution and reject based on truncation_frequency.\n", - " # If more nus.shape[0] > no_of_packets use only the first no_of_packets.\n", - " nus = self.create_blackbody_packet_nus(T, drawing_sample_size, self.rng)\n", - " nus = nus[nus<truncation_frequency][:no_of_packets]\n", - " \n", - " \n", - " # Only required if the truncation wavelength is too big compared to the maximum \n", - " # of the blackbody distribution. Keep sampling until nus.shape[0] > no_of_packets.\n", - " while nus.shape[0] < no_of_packets:\n", - " additional_nus = self.create_blackbody_packet_nus(\n", - " T, drawing_sample_size, self.rng\n", - " )\n", - " mask = additional_nus < truncation_frequency\n", - " additional_nus = additional_nus[mask][:no_of_packets]\n", - " nus = np.hstack([nus, additional_nus])[:no_of_packets]\n", - " \n", - " return radii, nus, mus, energies" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Call an instance of the packet source class\n", - "packet_source = TruncBlackbodySource(\n", - " 53253, truncation_wavelength=2000\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We now run TARDIS both with and without our custom packet source, and we compare the results:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "mdl = run_tardis('tardis_example.yml',\n", - " packet_source=packet_source)\n", - "mdl_norm = run_tardis('tardis_example.yml')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "plt.plot(mdl.runner.spectrum_virtual.wavelength,\n", - " mdl.runner.spectrum_virtual.luminosity_density_lambda,\n", - " color='red', label='truncated blackbody (custom packet source)')\n", - "plt.plot(mdl_norm.runner.spectrum_virtual.wavelength,\n", - " mdl_norm.runner.spectrum_virtual.luminosity_density_lambda,\n", - " color='blue', label='normal blackbody (default packet source)')\n", - "plt.xlabel('$\\lambda [\\AA]$')\n", - "plt.ylabel('$L_\\lambda$ [erg/s/$\\AA$]')\n", - "plt.xlim(500, 10000)\n", - "plt.legend()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.10" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file diff --git a/docs/io/optional/how_to_custom_source.ipynb b/docs/io/optional/how_to_custom_source.ipynb new file mode 100644 index 00000000000..99bd5da7915 --- /dev/null +++ b/docs/io/optional/how_to_custom_source.ipynb @@ -0,0 +1,228 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# How to Run TARDIS with a Custom Packet Source\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By default, TARDIS generates energy packets using its interface `BasePacketSource` class, which has a derived class `BlackBodySimpleSource`, which models the photosphere of the supernova as a perfect blackbody (see [Energy Packet Initialization](../../physics/montecarlo/initialization.ipynb)). However, users may create their own packet source, as will be shown in this notebook. In order to do this, a user must create a class (that inherits from `BasePacketSource`) and implement the following abstract functions:\n", + "\n", + "- create_packet_radii (returns array of packet radii)\n", + "- create_packet_nus (returns array of packet frequencies)\n", + "- create_packet_mus (returns array of packet directions)\n", + "- create_packet_energies (returns array of packet energies. See [Energy Packet Initialization](../../physics/montecarlo/initialization.ipynb) for more information)\n", + "- create_packets (wrapper which calls the above 4 functions, and is the function used by external code)\n", + "- set_state_from_model (set the state of the source from a model object)\n", + "\n", + "[Note: In this notebook, we have extended the `BlackBodySimpleSource` class because it already implements some of the above functions]\n", + "\n", + "To use your packet source in a run of TARDIS, you must pass an instance of your class into the `run_tardis` function under the `packet_source` keyword argument.\n", + "\n", + ".. note:: In both the `BlackBodySimpleSource` class and in the example here, all packets are generated at the same radius. This need not be true in general (though one call of the `create_packets` method will pick the same radius from the packet source state).\n", + "\n", + "We show an example of how a custom packet source is used:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Import necessary packages\n", + "import numpy as np\n", + "from tardis import constants as const\n", + "from astropy import units as u\n", + "from tardis.transport.montecarlo.packet_source import BlackBodySimpleSource\n", + "from tardis.transport.montecarlo.packet_collections import (\n", + " PacketCollection,\n", + ")\n", + "from tardis import run_tardis\n", + "import matplotlib.pyplot as plt\n", + "from tardis.io.atom_data import download_atom_data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Download the atomic data used for a run of TARDIS\n", + "download_atom_data(\"kurucz_cd23_chianti_H_He\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a packet source class that contains a create_packets method\n", + "class TruncBlackbodySource(BlackBodySimpleSource):\n", + " \"\"\"\n", + " Custom inner boundary source class to replace the Blackbody source\n", + " with a truncated Blackbody source.\n", + "\n", + " Parameters\n", + " ----------\n", + " truncation_wavelength : float\n", + " truncation wavelength in Angstrom.\n", + " Only wavelengths higher than the truncation wavelength\n", + " will be sampled.\n", + " radius : float64\n", + " Initial packet radius\n", + " temperature : float\n", + " Absolute Temperature.\n", + " base_seed : int\n", + " Base Seed for random number generator\n", + " \"\"\"\n", + "\n", + " def __init__(self, truncation_wavelength=None, **kwargs):\n", + " self.truncation_wavelength = truncation_wavelength\n", + " super().__init__(**kwargs)\n", + "\n", + " def create_packets(self, no_of_packets, drawing_sample_size=None, seed_offset=0, *args, **kwargs):\n", + " \"\"\"\n", + " Packet source that generates a truncated Blackbody source.\n", + "\n", + " Parameters\n", + " ----------\n", + " no_of_packets : int\n", + " number of packets to be created\n", + "\n", + " Returns\n", + " -------\n", + " array\n", + " Packet radii\n", + " array\n", + " Packet frequencies\n", + " array\n", + " Packet directions\n", + " array\n", + " Packet energies\n", + " \"\"\"\n", + "\n", + " self._reseed(self.base_seed + seed_offset)\n", + " packet_seeds = self.rng.choice(\n", + " self.MAX_SEED_VAL, no_of_packets, replace=True\n", + " )\n", + "\n", + " # Makes uniform array of packet radii from blackbody source\n", + " radii = self.create_packet_radii(no_of_packets, *args, **kwargs)\n", + "\n", + " # Use mus and energies from normal blackbody source.\n", + " mus = self.create_packet_mus(no_of_packets, *args, **kwargs)\n", + " energies = self.create_packet_energies(no_of_packets, *args, **kwargs)\n", + "\n", + " # If not specified, draw 2 times as many packets and reject any beyond no_of_packets.\n", + " if drawing_sample_size is None:\n", + " drawing_sample_size = 2 * no_of_packets\n", + "\n", + " # Blackbody will be truncated below truncation_wavelength / above truncation_frequency.\n", + " truncation_frequency = (\n", + " u.Quantity(self.truncation_wavelength, u.Angstrom)\n", + " .to(u.Hz, equivalencies=u.spectral())\n", + " .value\n", + " )\n", + "\n", + " # Draw nus from blackbody distribution and reject based on truncation_frequency.\n", + " # If more nus.shape[0] > no_of_packets use only the first no_of_packets.\n", + " nus = self.create_packet_nus(drawing_sample_size, *args, **kwargs)\n", + " nus = nus[nus < truncation_frequency][:no_of_packets]\n", + "\n", + " # Only required if the truncation wavelength is too big compared to the maximum\n", + " # of the blackbody distribution. Keep sampling until nus.shape[0] > no_of_packets.\n", + " while nus.shape[0] < no_of_packets:\n", + " additional_nus = self.create_packet_nus(drawing_sample_size, *args, **kwargs)\n", + " mask = additional_nus < truncation_frequency\n", + " additional_nus = additional_nus[mask][:no_of_packets]\n", + " nus = np.hstack([nus, additional_nus])[:no_of_packets]\n", + "\n", + " radiation_field_luminosity = (\n", + " self.calculate_radfield_luminosity().to(u.erg / u.s).value\n", + " )\n", + "\n", + " return PacketCollection(radii, nus, mus, energies, packet_seeds, radiation_field_luminosity)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Call an instance of the packet source class\n", + "packet_source = TruncBlackbodySource(\n", + " truncation_wavelength=2000, base_seed=53253\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now run TARDIS both with and without our custom packet source, and we compare the results:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mdl = run_tardis(\"tardis_example.yml\", packet_source=packet_source)\n", + "mdl_norm = run_tardis(\"tardis_example.yml\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "plt.plot(mdl.transport.transport_state.spectrum_virtual.wavelength,\n", + " mdl.transport.transport_state.spectrum_virtual.luminosity_density_lambda,\n", + " color='red', label='truncated blackbody (custom packet source)')\n", + "plt.plot(mdl_norm.transport.transport_state.spectrum_virtual.wavelength,\n", + " mdl_norm.transport.transport_state.spectrum_virtual.luminosity_density_lambda,\n", + " color='blue', label='normal blackbody (default packet source)')\n", + "plt.xlabel('$\\lambda [\\AA]$')\n", + "plt.ylabel('$L_\\lambda$ [erg/s/$\\AA$]')\n", + "plt.xlim(500, 10000)\n", + "plt.legend()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/io/optional/index.rst b/docs/io/optional/index.rst index 92fb7fb60f7..79123dc01db 100644 --- a/docs/io/optional/index.rst +++ b/docs/io/optional/index.rst @@ -9,9 +9,9 @@ TARDIS also allows other inputs that are passed as keyword arguments into the `` .. toctree:: :maxdepth: 1 - custom_source - callback_example - logging_configuration + how_to_custom_source + tutorial_callback_example + tutorial_logging_configuration Additionally, ``run_tardis`` can take in a filepath for the atomic data and a boolean for virtual packet logging. For example: diff --git a/docs/io/optional/callback_example.ipynb b/docs/io/optional/tutorial_callback_example.ipynb similarity index 94% rename from docs/io/optional/callback_example.ipynb rename to docs/io/optional/tutorial_callback_example.ipynb index e5c4b6c462b..04fa294f37e 100644 --- a/docs/io/optional/callback_example.ipynb +++ b/docs/io/optional/tutorial_callback_example.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8,6 +9,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -23,13 +25,14 @@ "outputs": [], "source": [ "def average_temp(sim):\n", - " t_rads = sim.model.t_rad\n", - " volumes = sim.model.volume\n", + " t_rads = sim.simulation_state.t_radiative\n", + " volumes = sim.simulation_state.volume\n", " avg = sum(t_rads*volumes) / sum(volumes)\n", " print(f\"Average temperature for iteration {sim.iterations_executed}: {avg}\")" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -58,6 +61,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -74,11 +78,12 @@ "source": [ "def append_num_emitted_to_list(sim, lst):\n", " if sim.iterations_executed < sim.iterations:\n", - " num_emitted_packets = len(sim.runner.emitted_packet_nu)\n", + " num_emitted_packets = len(sim.transport.transport_state.emitted_packet_nu)\n", " lst.append(num_emitted_packets)" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -104,6 +109,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -128,6 +134,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -166,6 +173,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -184,6 +192,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ diff --git a/docs/io/optional/logging_configuration.ipynb b/docs/io/optional/tutorial_logging_configuration.ipynb similarity index 99% rename from docs/io/optional/logging_configuration.ipynb rename to docs/io/optional/tutorial_logging_configuration.ipynb index 278ada1b04a..759f334dd06 100644 --- a/docs/io/optional/logging_configuration.ipynb +++ b/docs/io/optional/tutorial_logging_configuration.ipynb @@ -278,7 +278,7 @@ "metadata": {}, "outputs": [], "source": [ - "from tardis.io.config_reader import Configuration" + "from tardis.io.configuration.config_reader import Configuration" ] }, { diff --git a/docs/io/output/callback.rst b/docs/io/output/callback.rst index 3f42e7ff04d..809ebda9492 100644 --- a/docs/io/output/callback.rst +++ b/docs/io/output/callback.rst @@ -3,4 +3,4 @@ Callbacks ********* Outputs can be customized using callbacks that are executed at the end of each Monte Carlo iteration. For more -information, see :doc:`../optional/callback_example`. \ No newline at end of file +information, see :doc:`../optional/tutorial_callback_example`. \ No newline at end of file diff --git a/docs/io/output/default_plasma_graph.png b/docs/io/output/default_plasma_graph.png new file mode 100644 index 00000000000..4e3d9fca5b2 Binary files /dev/null and b/docs/io/output/default_plasma_graph.png differ diff --git a/docs/io/output/physical_quantities.ipynb b/docs/io/output/how_to_physical_quantities.ipynb similarity index 91% rename from docs/io/output/physical_quantities.ipynb rename to docs/io/output/how_to_physical_quantities.ipynb index 0eb2aee8e83..ba5076dcf3e 100644 --- a/docs/io/output/physical_quantities.ipynb +++ b/docs/io/output/how_to_physical_quantities.ipynb @@ -6,7 +6,7 @@ "raw_mimetype": "text/restructuredtext" }, "source": [ - "# Accessing Physical Quantities" + "# How to Access Physical Quantities" ] }, { @@ -24,7 +24,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Runing in interactive Python session" + "### Running an interactive Python session" ] }, { @@ -111,7 +111,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Several important quantities that were setup when the model was defined by the configuration file are located in the `model` section of the simulation. For example, the inner and outer velocity boundaries of the zones in the model is given by `simulation.model.v_inner.cgs` and `simulation.model.v_outer.cgs` respectively. These exist as Astropy [Quantities](http://astropy.readthedocs.org/en/v0.2.1/_generated/astropy.units.quantity.Quantity.html)." + "Several important quantities that were setup when the model was defined by the configuration file are located in the `model` section of the simulation. For example, the inner and outer velocity boundaries of the zones in the model is given by `simulation.simulation_state.v_inner.cgs` and `simulation.simulation_state.v_outer.cgs` respectively. These exist as Astropy [Quantities](http://astropy.readthedocs.org/en/v0.2.1/_generated/astropy.units.quantity.Quantity.html)." ] }, { @@ -120,7 +120,7 @@ "metadata": {}, "outputs": [], "source": [ - "simulation.model.v_inner.cgs" + "simulation.simulation_state.v_inner.cgs" ] }, { @@ -129,14 +129,14 @@ "metadata": {}, "outputs": [], "source": [ - "simulation.model.v_outer.cgs" + "simulation.simulation_state.v_outer.cgs" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The average density in the zones is given by `simulation.model.density.cgs`. These also exist as Astropy [Quantities](http://astropy.readthedocs.org/en/v0.2.1/_generated/astropy.units.quantity.Quantity.html)." + "The average density in the zones is given by `simulation.simulation_state.density.cgs`. These also exist as Astropy [Quantities](http://astropy.readthedocs.org/en/v0.2.1/_generated/astropy.units.quantity.Quantity.html)." ] }, { @@ -145,7 +145,7 @@ "metadata": {}, "outputs": [], "source": [ - "simulation.model.density.cgs" + "simulation.simulation_state.density.cgs" ] }, { diff --git a/docs/io/output/how_to_plasma_graph.ipynb b/docs/io/output/how_to_plasma_graph.ipynb new file mode 100644 index 00000000000..68dd0e5a571 --- /dev/null +++ b/docs/io/output/how_to_plasma_graph.ipynb @@ -0,0 +1,390 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c7835cf9", + "metadata": {}, + "source": [ + "# How to Generate the Plasma Graph" + ] + }, + { + "cell_type": "markdown", + "id": "0329e9f4", + "metadata": {}, + "source": [ + "After running a simulation, TARDIS has the ability to create a [graph](https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)) showcasing how each variable used to compute the plasma state is connected and calculated (see the [Plasma Documentation](../../physics/setup/plasma/index.rst) for more information). To do so, one needs to utilize the `write_to_tex` command to generate a .tex file that displays the graph. This tutorial aims to showcase how the .tex file can be generated and what options can be inputted to display the graph in a preferred method. To start, TARDIS needs to perform a simulation. Here the `tardis_example.yml` configuration file is used as in the [quickstart guide](../../quickstart.ipynb)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9fbaaa9", + "metadata": {}, + "outputs": [], + "source": [ + "#downloading necessary modules\n", + "from tardis import run_tardis\n", + "from tardis.io.atom_data.util import download_atom_data\n", + "\n", + "import networkx as nx\n", + "\n", + "from IPython.core.display import Image, display" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "631f5cd2", + "metadata": {}, + "outputs": [], + "source": [ + "#downloading atom data\n", + "download_atom_data('kurucz_cd23_chianti_H_He')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2212037a", + "metadata": {}, + "outputs": [], + "source": [ + "#running simulation\n", + "sim = run_tardis('tardis_example.yml')" + ] + }, + { + "cell_type": "markdown", + "id": "2eff6574", + "metadata": {}, + "source": [ + "## Displaying the Graph Within A Jupyter Notebook" + ] + }, + { + "cell_type": "markdown", + "id": "12802d67", + "metadata": {}, + "source": [ + "Now that TARDIS has finished a simulation run, the plasma graph can now be generated. To display the basic graph within a Jupyter Notebook, one can simply use the `nx.draw` as follows: " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ca47e24a", + "metadata": {}, + "outputs": [], + "source": [ + "%pylab inline\n", + "\n", + "nx.draw(sim.plasma.graph)" + ] + }, + { + "cell_type": "markdown", + "id": "54a7c171", + "metadata": {}, + "source": [ + "There are many different ways of displaying the graph in a more readable format. One such example is shown below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6cf742ed", + "metadata": {}, + "outputs": [], + "source": [ + "position = nx.spring_layout(sim.plasma.graph, k=0.75, iterations=15)\n", + "\n", + "nx.draw(sim.plasma.graph, position, with_labels=True)" + ] + }, + { + "cell_type": "markdown", + "id": "671db7f1", + "metadata": {}, + "source": [ + "<div class=\"alert alert-info\">\n", + " \n", + "Note\n", + "\n", + "For the purposes of this tutorial, pylab inline has been used to display the graph within the tutorial page. It is recommended to use pylab notebook when displaying the graph on a local Jupyter Notebook to explore the nodes in depth.\n", + "\n", + "</div>" + ] + }, + { + "cell_type": "markdown", + "id": "31f0fc69", + "metadata": {}, + "source": [ + "## Saving the Graph Onto a .tex File" + ] + }, + { + "cell_type": "markdown", + "id": "c4bbc23e", + "metadata": {}, + "source": [ + "With the `write_to_tex` command, a copy of the graph can be saved within a .tex file. Currently, there are four parameters TARDIS uses to write the graph in [LaTeX](https://en.wikipedia.org/wiki/LaTeX) and save it to a .tex file:\n", + "\n", + " <ul>\n", + " <li> fname_graph: The name of the file TARDIS will save the graph onto (<b>required</b>)</li>\n", + " <li> scale: a scaling factor to expand/contract the generated graph</li>\n", + " <li> args: a list of optional settings for displaying the graph</li>\n", + " <li> latex_label: a parameter that enables or disables writing LaTeX equations and edge labels onto the file (default set to <code>True</code> to enable writing)</li>\n", + "</ul> \n", + "\n", + "With these parameters, TARDIS can write the graph in many different ways. For this tutorial, only a few examples will be shown to display what each parameter exactly does and what the resulting graph will look like when generated in a LaTeX environment. " + ] + }, + { + "cell_type": "markdown", + "id": "2347c37b", + "metadata": {}, + "source": [ + "<div class=\"alert alert-warning\">\n", + " \n", + "Warning\n", + "\n", + "As of now, TARDIS has an issue of not spacing edges correctly, causing the default output to look very condensed and unreadable in certain areas. It is recommended, therefore, to use the given parameters to generate a graph that displays everything in as readable a format as possible. \n", + "\n", + "</div>" + ] + }, + { + "cell_type": "markdown", + "id": "8bbac606", + "metadata": {}, + "source": [ + "### Default Plasma Graph" + ] + }, + { + "cell_type": "markdown", + "id": "bb12a9e1", + "metadata": {}, + "source": [ + "From above, TARDIS only needs the name of the file it should save the graph to as default." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b3bd85b7", + "metadata": {}, + "outputs": [], + "source": [ + "sim.plasma.write_to_tex(\"plasma_graph_default.tex\")" + ] + }, + { + "cell_type": "markdown", + "id": "d0ab8466", + "metadata": {}, + "source": [ + "With the default settings, the contents of the file will simply be the graph written in LaTeX.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "45288d3b", + "metadata": {}, + "outputs": [], + "source": [ + "with open(\"plasma_graph_default.tex\", \"r\") as file:\n", + " print(file.read())\n", + " file.close()" + ] + }, + { + "cell_type": "markdown", + "id": "33c2a897", + "metadata": {}, + "source": [ + "If one was to build the .tex file, the following graph will be generated:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2ad68ca3", + "metadata": {}, + "outputs": [], + "source": [ + "display(Image('default_plasma_graph.png', unconfined=True))" + ] + }, + { + "cell_type": "markdown", + "id": "e89230d5", + "metadata": {}, + "source": [ + "<div class=\"alert alert-info\">\n", + " \n", + "Note\n", + "\n", + "For the remainder of this tutorial, the contents of the .tex file will be omitted and only the generated graph will be shown.\n", + "\n", + "</div>" + ] + }, + { + "cell_type": "markdown", + "id": "815dd554", + "metadata": {}, + "source": [ + "### Plasma Graph with Different Scale" + ] + }, + { + "cell_type": "markdown", + "id": "00ad603d", + "metadata": {}, + "source": [ + "One can change the scaling of the graph by passing in a positive, non-zero float into the `scale` parameter to either make the resulting graph larger (scale > 0.5) or smaller (scale < 0.5)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f4dab02", + "metadata": {}, + "outputs": [], + "source": [ + "sim.plasma.write_to_tex(\"plasma_graph_scaled.tex\", scale = 1.25)" + ] + }, + { + "cell_type": "markdown", + "id": "73c2a8af", + "metadata": {}, + "source": [ + "With a scale of 1.25, the graph TARDIS will output will look as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9b85ef0a", + "metadata": {}, + "outputs": [], + "source": [ + "display(Image('plasma_graph_scaled.png', unconfined=True))" + ] + }, + { + "cell_type": "markdown", + "id": "6661eeae", + "metadata": {}, + "source": [ + "### Plasma Graph with No Equations\n", + "\n", + "TARDIS has the option to generate a graph without any equations or edge labels via the `latex_label` command. The graph in this case will only consist of nodes containing the names of variables used to calculate the plasma state connected with edges." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "764aa91a", + "metadata": {}, + "outputs": [], + "source": [ + "sim.plasma.write_to_tex(\"plasma_graph_no_eq.tex\", latex_label=False)" + ] + }, + { + "cell_type": "markdown", + "id": "3335a526", + "metadata": {}, + "source": [ + "With these inputs, the graph will look like this:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e97c276", + "metadata": {}, + "outputs": [], + "source": [ + "display(Image('plasma_graph_no_eq.png', unconfined=True))" + ] + }, + { + "cell_type": "markdown", + "id": "43196f07", + "metadata": {}, + "source": [ + "### Plasma Graph with Inputted Arguments\n", + "\n", + "In order to create the .tex file, TARDIS will first convert the graph into a readable [DOT](https://graphviz.org/doc/info/lang.html) format via the `write_to_dot` function. As such, using the `args` parameter within the `write_to_tex` function, one can pass in any Graphviz attribute for TARDIS to implement as a list. In this example, the following attributes are used:\n", + "\n", + " <ul>\n", + " <li> <code>nodesep</code>: changes spacing of nodes</li>\n", + " <li><code>edge[lblstyle]</code>: edits the edge labels</li>\n", + " <li><code>margin</code>: sets the margins of the outputted graph</li>\n", + " <li><code>ratio</code>: sets the drawing height and width</li>\n", + " <li><code>size</code>: sets the maximum height and width of the graph</li>\n", + "</ul> \n", + "\n", + "For more information on these attributes, visit the [Graphviz attributes documentation](https://graphviz.org/doc/info/attrs.html)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0bd9b8dd", + "metadata": {}, + "outputs": [], + "source": [ + "attributes_list = [r\"nodesep=1.0\", r'edge[lblstyle=\"fill=white\"]', r'margin=0', r'ratio=\"fill\"', r'size=\"8.3,11.7!\"']\n", + "\n", + "sim.plasma.write_to_tex(\"plasma_graph_with_args.tex\", args=attributes_list)" + ] + }, + { + "cell_type": "markdown", + "id": "858b7509", + "metadata": {}, + "source": [ + "With these attributes, the following graph can be generated:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8018b7f", + "metadata": {}, + "outputs": [], + "source": [ + "display(Image('plasma_graph_args.png', unconfined=True))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/io/output/rpacket_tracking.ipynb b/docs/io/output/how_to_rpacket_tracking.ipynb similarity index 52% rename from docs/io/output/rpacket_tracking.ipynb rename to docs/io/output/how_to_rpacket_tracking.ipynb index a93959e67ba..c088a7e53a4 100644 --- a/docs/io/output/rpacket_tracking.ipynb +++ b/docs/io/output/how_to_rpacket_tracking.ipynb @@ -1,14 +1,16 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "f57cd4fe", "metadata": {}, "source": [ - "# Tracking the Properties of Real Packets" + "# How to Track the Properties of Real Packets" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c103617c", "metadata": {}, @@ -17,6 +19,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ce6214b9", "metadata": {}, @@ -33,25 +36,23 @@ " <li><b>mu</b> - Propagation Direction of the Packet (cosine of the angle the packet’s path makes with the radial direction)</li>\n", " <li><b>energy</b> - Energy of the Packet</li>\n", " <li><b>shell_id</b> - Current Shell Id where the Packet is present</li>\n", + " <li><b>interaction_type</b> - Last Interaction type of the packet</li>\n", " </ol>\n", " </body>\n", "</html>" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "4b0de6ca", "metadata": {}, "source": [ - "<div class=\"alert alert-warning\">\n", - "\n", - "Warning\n", - "\n", - "Current implementation stores all the data for the interaction of the packets in a `list`, so it needs to accessed with a `list index` for each property for a particular `rpacket`. Examples for the same are shown as follows. \n", - "</div>" + "The data can be obtained in two ways i.e. `rpacket_tracker` and `rpacket_tracker_df`. The `rpacket_tracker` stores all the data for the interaction of the packets in a `list`, so it needs to accessed with a `list index` for each property for a particular `rpacket`. `rpacket_tracker_df` stores the data in a dataframe. Examples for the same are shown as follows. " ] }, { + "attachments": {}, "cell_type": "markdown", "id": "1686d9f1", "metadata": {}, @@ -60,6 +61,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "29e14475", "metadata": {}, @@ -76,6 +78,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "13b6420b", "metadata": {}, @@ -84,6 +87,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2634c571", "metadata": {}, @@ -98,7 +102,7 @@ "metadata": {}, "outputs": [], "source": [ - "from tardis.io.config_reader import Configuration" + "from tardis.io.configuration.config_reader import Configuration" ] }, { @@ -154,7 +158,18 @@ "metadata": {}, "outputs": [], "source": [ - "from tardis import run_tardis" + "from tardis import run_tardis\n", + "from tardis.io.atom_data.util import download_atom_data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7d8471c3", + "metadata": {}, + "outputs": [], + "source": [ + "download_atom_data('kurucz_cd23_chianti_H_He')" ] }, { @@ -172,11 +187,12 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "532bfafc", "metadata": {}, "source": [ - "Now, the `tracked` properties can be accessed via the `rpacket_tracker` attribute of the `sim.runner` object. " + "Now, the `tracked` properties can be accessed via the `rpacket_tracker` attribute of the `sim.transport` object. " ] }, { @@ -186,18 +202,20 @@ "metadata": {}, "outputs": [], "source": [ - "type(sim.runner.rpacket_tracker)" + "type(sim.transport.transport_state.rpacket_tracker)" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "4771d92a", "metadata": {}, "source": [ - "It can be seen from the above code, that the `sim.runner.rpacket_tracker` is an instance of the `List` specifically *Numba Typed List*. The `RPacketCollection` class has the following structure for the properties : {More information in the **TARDIS API** for `RPacketCollection` class}" + "It can be seen from the above code, that the `sim.transport.rpacket_tracker` is an instance of the `List` specifically *Numba Typed List*. The `RPacketCollection` class has the following structure for the properties : {More information in the **TARDIS API** for `RPacketCollection` class}" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ce587807", "metadata": {}, @@ -214,6 +232,7 @@ " mu\n", " energy\n", " shell_id\n", + " interaction_type\n", "```" ] }, @@ -224,10 +243,20 @@ "metadata": {}, "outputs": [], "source": [ - "len(sim.runner.rpacket_tracker)" + "len(sim.transport.transport_state.rpacket_tracker)" ] }, { + "attachments": {}, + "cell_type": "markdown", + "id": "0f8566f4", + "metadata": {}, + "source": [ + "### Accessing properties through `rpacket_tracker`" + ] + }, + { + "attachments": {}, "cell_type": "markdown", "id": "411f2ef9", "metadata": {}, @@ -237,11 +266,12 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "a4772b00", "metadata": {}, "source": [ - "- Accessing the `index` property for the packet {`10`}:" + "#### Accessing the `index` property for the packet with index = 10 :" ] }, { @@ -251,15 +281,16 @@ "metadata": {}, "outputs": [], "source": [ - "sim.runner.rpacket_tracker[10].index" + "sim.transport.transport_state.rpacket_tracker[10].index" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "d81fbbf7", "metadata": {}, "source": [ - "- Accessing the `seed` property for the packet {`10`}:" + "#### Accessing the `seed` property for the packet with index = 10 :" ] }, { @@ -269,15 +300,16 @@ "metadata": {}, "outputs": [], "source": [ - "sim.runner.rpacket_tracker[10].seed" + "sim.transport.transport_state.rpacket_tracker[10].seed" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "7afe2110", "metadata": {}, "source": [ - "- Accessing the `status` property for the packet {`10`}:" + "#### Accessing the `status` property for the packet with index = 10 :" ] }, { @@ -287,18 +319,20 @@ "metadata": {}, "outputs": [], "source": [ - "sim.runner.rpacket_tracker[10].status" + "sim.transport.transport_state.rpacket_tracker[10].status" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ea308a55", "metadata": {}, "source": [ - "Thus, all other properties {`r`, `nu`, `mu`, `energy`, `shell_id`} can be accessed accordingly." + "Thus, all other properties (`r`, `nu`, `mu`, `energy`, `shell_id`,`interaction_type`) can be accessed accordingly." ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c83dd906", "metadata": {}, @@ -313,10 +347,11 @@ "metadata": {}, "outputs": [], "source": [ - "len(sim.runner.rpacket_tracker[10].shell_id)" + "len(sim.transport.transport_state.rpacket_tracker[10].shell_id)" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "9136fba1", "metadata": {}, @@ -325,11 +360,12 @@ "\n", "Warning\n", "\n", - "If we try to access `sim.runner.rpacket_tracker` property when we have the `track_rpacket` property in the `tracking` subsection of `montecarlo` config, turned off as follows `config[\"montecarlo\"][\"tracking\"][\"track_rpacket\"] = False`, it will return `None`. Error will be raised if we try to access the properties i.e. `seed`, `index`, etc.\n", + "If we try to access `sim.transport.rpacket_tracker` property when we have the `track_rpacket` property in the `tracking` subsection of `montecarlo` config, turned off as follows `config[\"montecarlo\"][\"tracking\"][\"track_rpacket\"] = False`, it will return `None`. Error will be raised if we try to access the properties i.e. `seed`, `index`, etc.\n", "</div>" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "afa3c7f4", "metadata": {}, @@ -341,6 +377,178 @@ "When we initialise the `RPacketCollection()` class, the properties arrays {`index`, `seed`, `status`, etc} are allocated certain length based on the `initial_array_length` parameter that can be set via the `initial_array_length` property under `montecarlo -> tracking` section of the configuration. The default size of the array is `10`. This variable is important as the number of interactions a packet may have is variable, thus we need to allocate space dynamically. This variable is used to compute the size and expand the array such that the properties are able to hold these values for the packet interaction. Higher number, allocates more space initially leading to lesser times the arrays expands and vice versa. It can be set in the following manner `config[\"montecarlo\"][\"tracking\"][\"initial_array_length\"] = {value}`.\n", "</div>" ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "2da1215e", + "metadata": {}, + "source": [ + "### Accessing properties with `rpacket_tracker_df`" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "6eaee13d", + "metadata": {}, + "source": [ + "Also, the `tracked` properties can be accessed via the `rpacket_tracker_df` attribute of the `sim.transport` object. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5fa074c2", + "metadata": {}, + "outputs": [], + "source": [ + "type(sim.transport.transport_state.rpacket_tracker_df)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "9a39309b", + "metadata": {}, + "source": [ + "Here, all the properties of the rpackets discussed above are stored as a `Pandas.Dataframe` object. This makes accessing the properties of any rpacket more convenient and in a more organized way." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "93e78750", + "metadata": {}, + "source": [ + "<html>\n", + " <body>\n", + " The Basic structure of the Dataframe is as follows:<br><br>\n", + " Index Columns:\n", + " <ol>\n", + " <li><b>index</b> - Indicates the index number of the packet.</li>\n", + " <li><b>step</b> - It is the step number that any particular packet is on, as it moves through the ejecta.</li>\n", + " </ol>\n", + " Properties:<br><br>\n", + " These following properties are present as columns in the Dataframe. These are the same properties that were present in the <b>rpacket_tracker</b>\n", + " <ol>\n", + " <li><b>status</b></li>\n", + " <li><b>seed</b></li>\n", + " <li><b>r</b></li>\n", + " <li><b>nu</b></li>\n", + " <li><b>mu</b></li>\n", + " <li><b>energy</b></li>\n", + " <li><b>shell_id</b></li>\n", + " <li><b>interaction_type</b></li>\n", + " </ol>\n", + " </body>\n", + "</html>" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "54dce761", + "metadata": {}, + "source": [ + "The entire dataframe, containing all the properties mentioned above, can be fetched as:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ec47b2f", + "metadata": {}, + "outputs": [], + "source": [ + "sim.transport.transport_state.rpacket_tracker_df" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "81f1d718", + "metadata": {}, + "source": [ + "To access these different properties in the dataframe, we may consider the following examples for the `rpacket_tracker_df`:\n", + "<br>In this Example, we are trying to access the properties of the packet at index `10`.<br>In a similar way, we can check for any property for any packet in the range of packets for the last iteration." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "eb8df3d9", + "metadata": {}, + "source": [ + "#### Accessing all the properties for the packet with index = 10:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "612c8234", + "metadata": {}, + "outputs": [], + "source": [ + "sim.transport.transport_state.rpacket_tracker_df.loc[10]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "75d86f95", + "metadata": {}, + "source": [ + "#### Accessing the `energy` property for the packet with index = 10:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2c84adb1", + "metadata": {}, + "outputs": [], + "source": [ + "sim.transport.transport_state.rpacket_tracker_df.loc[10][\"energy\"]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "1beffb1f", + "metadata": {}, + "source": [ + "The above command returns a Pandas Series for the packet `#10` across different steps. To access any property at a particular step (for example at step `5`), the following commands can be used." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1d7f0bb4", + "metadata": {}, + "outputs": [], + "source": [ + "sim.transport.transport_state.rpacket_tracker_df.loc[10,5][\"energy\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1cf17109", + "metadata": {}, + "outputs": [], + "source": [ + "sim.transport.transport_state.rpacket_tracker_df.loc[10][\"energy\"][5]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "6921f480", + "metadata": {}, + "source": [ + "Thus, all other properties (`status`, `seed`, `r`, `nu`, `mu`, `shell_id`,`interaction_type`) can be accessed accordingly." + ] } ], "metadata": { @@ -359,7 +567,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.11.5" + }, + "vscode": { + "interpreter": { + "hash": "6890d83cfa6c65bebc4bd449872c06a268510d8b8ae8c923ce6786e6c4796836" + } } }, "nbformat": 4, diff --git a/docs/io/output/to_hdf.ipynb b/docs/io/output/how_to_to_hdf.ipynb similarity index 86% rename from docs/io/output/to_hdf.ipynb rename to docs/io/output/how_to_to_hdf.ipynb index 8ee546920a9..81998c3e9c2 100644 --- a/docs/io/output/to_hdf.ipynb +++ b/docs/io/output/how_to_to_hdf.ipynb @@ -1,17 +1,19 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ - "# Storing Simulations to HDF\n", + "# How to Store Simulations to HDF\n", "\n", "You can ask TARDIS to store the state of each iteration of the simulation you are running. We show examples of how this is done:" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -35,6 +37,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -69,6 +72,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -91,10 +95,11 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "Access `model.homologous_density.density_0` under simulation, which is a one-dimensional array" + "Access `model.density` under simulation, which is a one-dimensional array" ] }, { @@ -103,10 +108,11 @@ "metadata": {}, "outputs": [], "source": [ - "print(data['/simulation/model/homologous_density/density_0'])" + "print(data['/simulation/simulation_state/density'])" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { "collapsed": true @@ -121,10 +127,11 @@ "metadata": {}, "outputs": [], "source": [ - "print(data['/simulation/model/scalars']['t_inner'])" + "print(data['/simulation/simulation_state/scalars']['t_inner'])" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -133,6 +140,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -165,6 +173,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -195,11 +204,12 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### Model\n", - "The following call will store properties of the `Radial1DModel` to `/tmp/model_output.hdf` under `/model`." + "The following call will store properties of the `SimulationState` to `/tmp/model_output.hdf` under `/simulation_state`." ] }, { @@ -208,7 +218,7 @@ "metadata": {}, "outputs": [], "source": [ - "simulation.model.to_hdf('/tmp/model_output.hdf', overwrite=True)" + "simulation.simulation_state.to_hdf('/tmp/model_output.hdf', overwrite=True)" ] }, { @@ -225,11 +235,12 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "### MontecarloRunner\n", - "The following call will store properties of the `MontecarloRunner` to `/tmp/runner_output.hdf` under `/runner`." + "### MontecarloTransport\n", + "The following call will store properties of the `MontecarloTransport` to `/tmp/transport_output.hdf` under `/transport`." ] }, { @@ -238,7 +249,7 @@ "metadata": {}, "outputs": [], "source": [ - "simulation.runner.to_hdf('/tmp/runner_output.hdf', overwrite=True)" + "simulation.transport.to_hdf('/tmp/transport_output.hdf', overwrite=True)" ] }, { @@ -249,9 +260,9 @@ "source": [ "import pandas\n", "\n", - "runner_data = pandas.HDFStore('/tmp/runner_output.hdf')\n", + "transport_data = pandas.HDFStore('/tmp/transport_output.hdf')\n", "\n", - "runner_data.keys()" + "transport_data.keys()" ] } ], diff --git a/docs/io/output/index.rst b/docs/io/output/index.rst index bb9f5650bc0..11f3eefccb9 100644 --- a/docs/io/output/index.rst +++ b/docs/io/output/index.rst @@ -7,10 +7,11 @@ In addition to the widgets, TARDIS can output information in several other forms .. toctree:: :maxdepth: 1 - physical_quantities + how_to_physical_quantities access_iterations - to_hdf + how_to_to_hdf callback vpacket_logging progress_bars - rpacket_tracking + how_to_rpacket_tracking + how_to_plasma_graph diff --git a/docs/io/output/plasma_graph_args.png b/docs/io/output/plasma_graph_args.png new file mode 100644 index 00000000000..1526f5807ab Binary files /dev/null and b/docs/io/output/plasma_graph_args.png differ diff --git a/docs/io/output/plasma_graph_no_eq.png b/docs/io/output/plasma_graph_no_eq.png new file mode 100644 index 00000000000..938498baba2 Binary files /dev/null and b/docs/io/output/plasma_graph_no_eq.png differ diff --git a/docs/io/output/plasma_graph_scaled.png b/docs/io/output/plasma_graph_scaled.png new file mode 100644 index 00000000000..ec7a5e41fdc Binary files /dev/null and b/docs/io/output/plasma_graph_scaled.png differ diff --git a/docs/io/output/vpacket_logging.rst b/docs/io/output/vpacket_logging.rst index 18fd7350c7e..308ce6af409 100644 --- a/docs/io/output/vpacket_logging.rst +++ b/docs/io/output/vpacket_logging.rst @@ -11,7 +11,7 @@ After running the simulation, the following information can be retrieved: .. note:: The following tables list the attributes of the simulation in which the information would be stored. For example, if you call your TARDIS simulation ``sim``, you would access the virtual packet frequencies by running - ``sim.runner.virt_packet_nus``. + ``sim.transport.virt_packet_nus``. .. list-table:: @@ -23,32 +23,37 @@ After running the simulation, the following information can be retrieved: * - ``virt_packet_logging`` - Boolean - Shows if virtual packet logging is turned on - * - ``runner.virt_packet_nus`` + * - ``transport.virt_packet_nus`` - Numpy array - Virtual packet frequencies - * - ``runner.virt_packet_energies`` + * - ``transport.virt_packet_energies`` - Numpy array - Virtual packet energies - * - ``runner.virt_packet_initial_mus`` + * - ``transport.virt_packet_initial_mus`` - Numpy array - Propagation directions that virtual packets are launched at - * - ``runner.virt_packet_initial_rs`` + * - ``transport.virt_packet_initial_rs`` - Numpy array - Radii that virtual packets are launched at - * - ``runner.virt_packet_last_interaction_type`` + * - ``transport.virt_packet_last_interaction_type`` - Numpy array - | Type of interaction that caused the virtual packets to be spawned - | (enum, see :doc:`physical_quantities`) - * - ``runner.virt_packet_last_interaction_in_nu`` + | (enum, see :doc:`how_to_physical_quantities`) + * - ``transport.virt_packet_last_interaction_in_nu`` - Numpy array - Frequencies of the r-packets which spawned the virtual packet - * - ``runner.virt_packet_last_line_interaction_in_id`` + * - ``transport.virt_packet_last_line_interaction_in_id`` - Numpy array - | If the last interaction was a line interaction, the | line_interaction_in_id for that interaction - | (see :doc:`physical_quantities`) - * - ``runner.virt_packet_last_line_interaction_out_id`` + | (see :doc:`how_to_physical_quantities`) + * - ``transport.virt_packet_last_line_interaction_out_id`` - Numpy array - | If the last interaction was a line interaction, the | line_interaction_out_id for that interaction - | (see :doc:`physical_quantities`) \ No newline at end of file + | (see :doc:`how_to_physical_quantities`) + * - ``transport.virt_packet_last_line_interaction_shell_id`` + - Numpy array + - | If the last interaction was a line interaction, the + | line_interaction_shell_id for that interaction + | (see :doc:`how_to_physical_quantities`) \ No newline at end of file diff --git a/docs/io/visualization/demo.hdf b/docs/io/visualization/demo.hdf deleted file mode 100644 index 8513ceb6e4f..00000000000 Binary files a/docs/io/visualization/demo.hdf and /dev/null differ diff --git a/docs/io/visualization/abundance_widget.ipynb b/docs/io/visualization/how_to_abundance_widget.ipynb similarity index 95% rename from docs/io/visualization/abundance_widget.ipynb rename to docs/io/visualization/how_to_abundance_widget.ipynb index 0fd25710f40..ec906eb34ad 100644 --- a/docs/io/visualization/abundance_widget.ipynb +++ b/docs/io/visualization/how_to_abundance_widget.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Generating Custom Abundance Widget" + "# How to Generate Custom Abundance Widget" ] }, { @@ -97,7 +97,7 @@ "outputs": [], "source": [ "# sim = run_tardis(\"tardis_example.yml\")\n", - "# widget = CustomAbundanceWidget.from_sim(sim)" + "# widget = CustomAbundanceWidget.from_simulation(sim)" ] }, { @@ -113,7 +113,7 @@ "metadata": {}, "outputs": [], "source": [ - "# widget = CustomAbundanceWidget.from_hdf(\"demo.hdf\")" + "# widget = CustomAbundanceWidget.from_hdf(\"demo.h5\")" ] }, { diff --git a/docs/io/visualization/generating_widgets.ipynb b/docs/io/visualization/how_to_generating_widgets.ipynb similarity index 71% rename from docs/io/visualization/generating_widgets.ipynb rename to docs/io/visualization/how_to_generating_widgets.ipynb index 333e9020697..7e7b2a9e499 100644 --- a/docs/io/visualization/generating_widgets.ipynb +++ b/docs/io/visualization/how_to_generating_widgets.ipynb @@ -4,17 +4,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Generating Data Exploration Widgets\n", + "# How to Generate Data Exploration Widgets\n", "A demonstration of how to generate TARDIS widgets that allows you to **explore simulation data within Jupyter Notebook with ease**!\n", "\n", - "This notebook is a quickstart tutorial, but more details on each widget (and its features) is given in the [Using TARDIS Widgets](https://tardis-sn.github.io/tardis/using/visualization/using_widgets.html) section of the documentation." + "This notebook is a quickstart how-to guide, but more details on each widget (and its features) is given in the [Using TARDIS Widgets](https://tardis-sn.github.io/tardis/io/visualization/using_widgets.html) section of the documentation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First create and run a simulation that we can use to generate widgets (more details about running simulation in [Quickstart](https://tardis-sn.github.io/tardis/quickstart/quickstart.html) section):" + "First create and run a simulation that we can use to generate widgets (more details about running simulation in [Quickstart](https://tardis-sn.github.io/tardis/quickstart/quickstart.html) section):\n" ] }, { @@ -33,16 +33,16 @@ "from tardis.io.atom_data.util import download_atom_data\n", "\n", "# We download the atomic data needed to run the simulation\n", - "download_atom_data('kurucz_cd23_chianti_H_He')\n", + "download_atom_data(\"kurucz_cd23_chianti_H_He\")\n", "\n", - "sim = run_tardis('tardis_example.yml', virtual_packet_logging=True)" + "sim = run_tardis(\"tardis_example.yml\", virtual_packet_logging=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Now, import functions & class to create widgets from `visualization` subpackage:" + "Now, import functions & class to create widgets from `visualization` subpackage:\n" ] }, { @@ -60,6 +60,7 @@ " shell_info_from_simulation,\n", " shell_info_from_hdf,\n", " LineInfoWidget,\n", + " GrotrianWidget,\n", ")" ] }, @@ -68,9 +69,10 @@ "metadata": {}, "source": [ "## Shell Info Widget\n", + "\n", "This widget allows you to explore chemical abundances of each shell - all the way from elements to ions to levels - by just clicking on the rows you want to explore!\n", "\n", - "There are two ways in which you can generate the widget:" + "There are two ways in which you can generate the widget:\n" ] }, { @@ -78,7 +80,8 @@ "metadata": {}, "source": [ "### Using a Simulation object\n", - "We will use the simulation object we created in the beginning, `sim` to generate shell info widget. Then simply display it to start using." + "\n", + "We will use the simulation object we created in the beginning, `sim` to generate shell info widget. Then simply display it to start using.\n" ] }, { @@ -104,7 +107,7 @@ "\n", "![Shell Info Widget Demo](../images/shell_info_widget_demo.gif)\n", "\n", - "Use the button at the top of this page to run the notebook in interactively to use the widgets!" + "Use the button at the top of this page to run the notebook in interactively to use the widgets!\n" ] }, { @@ -112,7 +115,8 @@ "metadata": {}, "source": [ "### Using a saved simulation (HDF file)\n", - "Alternatively, if you have a TARDIS simulation model saved on your disk as an HDF file, you can also use it to generate the shell info widget." + "\n", + "Alternatively, if you have a TARDIS simulation model saved on your disk as an HDF file, you can also use it to generate the shell info widget.\n" ] }, { @@ -127,7 +131,7 @@ }, "outputs": [], "source": [ - "# shell_info_widget = shell_info_from_hdf('demo.hdf')\n", + "# shell_info_widget = shell_info_from_hdf('demo.h5')\n", "# shell_info_widget.display()" ] }, @@ -136,16 +140,17 @@ "metadata": {}, "source": [ "## Line Info Widget\n", + "\n", "This widget lets you explore the atomic lines responsible for producing features in the simulated spectrum.\n", "\n", - "You can select any wavelength range in the spectrum interactively to display a table giving the fraction of packets that experienced their last interaction with each species. Using toggle buttons, you can specify whether to filter the selected range by the emitted or absorbed wavelengths of packets. Clicking on a row in the species table, shows packet counts for each last line interaction of the selected species, which can be grouped in several ways." + "You can select any wavelength range in the spectrum interactively to display a table giving the fraction of packets that experienced their last interaction with each species. Using toggle buttons, you can specify whether to filter the selected range by the emitted or absorbed wavelengths of packets. Clicking on a row in the species table, shows packet counts for each last line interaction of the selected species, which can be grouped in several ways.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "To generate line info widget, we will again use the simulation object `sim` and then display the widget:" + "To generate line info widget, we will again use the simulation object `sim` and then display the widget:\n" ] }, { @@ -169,7 +174,7 @@ "source": [ "You can interact with this widget (which again won't be visible if you're viewing this notebook in our docs as an html page) like this:\n", "\n", - "![Line Info Widget Demo](../images/line_info_widget_demo.gif)" + "![Line Info Widget Demo](../images/line_info_widget_demo.gif)\n" ] }, { @@ -179,11 +184,58 @@ "<div class=\"alert alert-info\">\n", "\n", "Note\n", - " \n", + "\n", "The virtual packet logging capability must be active in order to produce virtual packets' spectrum in `Line Info Widget`. Thus, make sure to set `virtual_packet_logging: True` in your configuration file. It should be added under `virtual` property of `spectrum` property, as described in [configuration schema](https://tardis-sn.github.io/tardis/using/components/configuration/configuration.html#spectrum).\n", "\n", - "</div>" + "</div>\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Energy Level Diagram\n", + "\n", + "This widget lets you explore and visualize the various level populations and line interactions in a simulation in the form of an Energy Level Diagram.\n", + "\n", + "You can select any ion present in the simulation and filter the transitions by wavelength or model shell to display an energy level diagram, where:\n", + "\n", + "- The horizontal lines represent the energy levels. The thickness of each line shows the relative population of that energy level, with thicker lines being more populated.\n", + "- The arrows represent the line interactions between levels, with the arrow direction giving the direction of the transition. The thickness of each arrow also shows the number of packets that underwent the transition while the wavelength is given by the color.\n", + "\n", + "In addition, you can also select between linear- and log-scaling for the y-axis (which represents the energy of each level) and the maximum number of levels to display, beginning from the lowest energy levels.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To generate the energy level diagram, we will again use the simulation object `sim` and then display the widget:\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "energy_level_widget = GrotrianWidget.from_simulation(sim)\n", + "energy_level_widget.display()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can interact with this widget (which again won't be visible if you're viewing this notebook in our docs as an html page) like this:\n", + "\n", + "![Energy Level Diagram Demo](../images/energy_level_widget_options.gif)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] } ], "metadata": { diff --git a/docs/io/visualization/sdec_plot.ipynb b/docs/io/visualization/how_to_sdec_plot.ipynb similarity index 95% rename from docs/io/visualization/sdec_plot.ipynb rename to docs/io/visualization/how_to_sdec_plot.ipynb index 9f52dbdb6aa..671c1a11686 100644 --- a/docs/io/visualization/sdec_plot.ipynb +++ b/docs/io/visualization/how_to_sdec_plot.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Spectral element DEComposition (SDEC) Plot\n", + "# How to Generate a Spectral element DEComposition (SDEC) Plot\n", "The SDEC Plot illustrates the contributions of different chemical elements in the formation of a simulation model's spectrum. It is a spectral diagnostic plot similar to those originally proposed by M. Kromer (see, for example, [Kromer et al. 2013](https://arxiv.org/abs/1311.0310), figure 4)." ] }, @@ -22,7 +22,7 @@ "source": [ "# We filter out warnings throughout this notebook\n", "import warnings\n", - "warnings.filterwarnings('ignore');\n", + "warnings.filterwarnings('ignore')\n", "\n", "# Due to the large size of the SDEC plots in SVG format, we request output as a\n", "# high-resolution PNG\n", @@ -54,7 +54,7 @@ "# We download the atomic data needed to run the simulation\n", "download_atom_data('kurucz_cd23_chianti_H_He')\n", "\n", - "sim = run_tardis(\"tardis_example.yml\", virtual_packet_logging=True)" + "sim = run_tardis(\"tardis_example.yml\", virtual_packet_logging=True)\n" ] }, { @@ -139,7 +139,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl();" + "plotter.generate_plot_mpl()" ] }, { @@ -162,7 +162,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(\"real\");" + "plotter.generate_plot_mpl(\"real\")" ] }, { @@ -198,7 +198,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(packet_wvl_range=[3000, 9000] * u.AA);" + "plotter.generate_plot_mpl(packet_wvl_range=[3000, 9000] * u.AA)" ] }, { @@ -226,7 +226,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(packet_wvl_range=[2000, 8000] * u.AA, nelements = 3);" + "plotter.generate_plot_mpl(packet_wvl_range=[2000, 8000] * u.AA, nelements = 3)" ] }, { @@ -254,7 +254,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(packet_wvl_range=[2000, 8000] * u.AA, species_list = ['Si II', 'S I-V', 'Ca']);" + "plotter.generate_plot_mpl(packet_wvl_range=[2000, 8000] * u.AA, species_list = ['Si II', 'S I-V', 'Ca'])" ] }, { @@ -275,7 +275,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(nelements = 3, species_list = ['Si II', 'S I-V', 'Ca']);" + "plotter.generate_plot_mpl(nelements = 3, species_list = ['Si II', 'S I-V', 'Ca'])" ] }, { @@ -297,7 +297,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(distance=100 * u.Mpc);" + "plotter.generate_plot_mpl(distance=100 * u.Mpc)" ] }, { @@ -338,7 +338,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(observed_spectrum = (observed_spectrum_wavelength, observed_spectrum_flux), distance = 6 * u.Mpc);" + "plotter.generate_plot_mpl(observed_spectrum = (observed_spectrum_wavelength, observed_spectrum_flux), distance = 6 * u.Mpc)" ] }, { @@ -360,7 +360,7 @@ }, "outputs": [], "source": [ - "plotter.generate_plot_mpl(show_modeled_spectrum=False);" + "plotter.generate_plot_mpl(show_modeled_spectrum=False)" ] }, { @@ -382,7 +382,7 @@ }, "outputs": [], "source": [ - "# To list all avaialble options (or parameters) with their description\n", + "# To list all available options (or parameters) with their description\n", "help(plotter.generate_plot_mpl)" ] }, @@ -490,7 +490,7 @@ }, "outputs": [], "source": [ - "# To list all avaialble options (or parameters) with their description\n", + "# To list all available options (or parameters) with their description\n", "help(plotter.generate_plot_ply)" ] }, @@ -513,7 +513,7 @@ }, "outputs": [], "source": [ - "hdf_plotter = SDECPlotter.from_hdf(\"demo.hdf\")" + "# hdf_plotter = SDECPlotter.from_hdf(\"demo.h5\") ## Files is too large - just as an example" ] }, { @@ -535,7 +535,7 @@ "outputs": [], "source": [ "# Static plot with virtual packets mode\n", - "hdf_plotter.generate_plot_mpl();" + "# hdf_plotter.generate_plot_mpl()" ] }, { @@ -550,7 +550,7 @@ "outputs": [], "source": [ "# Static plot with real packets mode\n", - "hdf_plotter.generate_plot_mpl(\"real\");" + "# hdf_plotter.generate_plot_mpl(\"real\")" ] }, { @@ -565,7 +565,7 @@ "outputs": [], "source": [ "# Interactive plot with virtual packets mode\n", - "hdf_plotter.generate_plot_ply()" + "# hdf_plotter.generate_plot_ply()" ] } ], diff --git a/docs/io/visualization/index.rst b/docs/io/visualization/index.rst index bb16a845310..b0ff58a6f3b 100644 --- a/docs/io/visualization/index.rst +++ b/docs/io/visualization/index.rst @@ -12,8 +12,9 @@ diagnostic visualizations. .. toctree:: :maxdepth: 2 - sdec_plot - convergence_plot + how_to_sdec_plot + tutorial_convergence_plot + tutorial_montecarlo_packet_visualization TARDIS Widgets (Graphical User Interfaces) @@ -27,5 +28,5 @@ Jupyter Notebooks, making data exploration much easier. :maxdepth: 2 using_widgets - Generating Custom Abundance Widget <abundance_widget> - Generating Data Exploration Widgets <generating_widgets> \ No newline at end of file + Generating Custom Abundance Widget <how_to_abundance_widget> + Generating Data Exploration Widgets <how_to_generating_widgets> \ No newline at end of file diff --git a/docs/io/visualization/convergence_plot.ipynb b/docs/io/visualization/tutorial_convergence_plot.ipynb similarity index 92% rename from docs/io/visualization/convergence_plot.ipynb rename to docs/io/visualization/tutorial_convergence_plot.ipynb index ed5075c9958..819ad47b236 100644 --- a/docs/io/visualization/convergence_plot.ipynb +++ b/docs/io/visualization/tutorial_convergence_plot.ipynb @@ -13,9 +13,7 @@ "id": "dc1a0c1f", "metadata": {}, "source": [ - "The Convergence Plots consist of two Plotly FigureWidget Subplots, the `plasma_plot` and the `t_inner_luminosities_plot`. The plots are stored in the `convergence_plots` attribute of the simulation object `sim` and can be accessed using `sim.convergence_plots.plasma_plot` and `sim.convergence_plots.t_inner_luminosities_plot`.\n", - "\n", - "The Convergence Plots are shown by default when you running TARDIS because `show_convergence_plots` parameter of the `run_tardis()` function is set to `True`. If you don't want to do this, set it to `False`. " + "The Convergence Plots consist of two Plotly FigureWidget Subplots, the `plasma_plot` and the `t_inner_luminosities_plot`. The plots can be displayed by setting the `show_convergence_plots` option in the `run_tardis` function to `True`. The plots are stored in the `convergence_plots` attribute of the simulation object `sim` and can be accessed using `sim.convergence_plots.plasma_plot` and `sim.convergence_plots.t_inner_luminosities_plot`." ] }, { @@ -48,7 +46,7 @@ "download_atom_data('kurucz_cd23_chianti_H_He')\n", "\n", "# We run a simulation\n", - "sim = run_tardis('tardis_example.yml', export_convergence_plots=True)" + "sim = run_tardis('tardis_example.yml', show_convergence_plots=True, export_convergence_plots=True)" ] }, { @@ -89,7 +87,7 @@ "The default line-colors of the plasma plots can be changed by passing the name of the cmap in the `plasma_cmap` option. \n", "\n", "```py\n", - "sim = run_tardis(\"tardis_example.yml\",plasma_cmap= \"viridis\")\n", + "sim = run_tardis(\"tardis_example.yml\", show_convergence_plots=True, plasma_cmap=\"viridis\")\n", "```\n", "\n", "Alongwith the cmap name, one can also provide a list of colors in rgb, hex or css-names format in the `t_inner_luminosities_colors` option to change the default colors of the luminosity and inner boundary temperature plots. \n", @@ -127,6 +125,7 @@ "source": [ "sim = run_tardis(\n", " \"tardis_example.yml\",\n", + " show_convergence_plots=True,\n", " plasma_cmap= \"viridis\", \n", " t_inner_luminosities_colors = ['rgb(102, 197, 204)',\n", " 'rgb(246, 207, 113)',\n", @@ -173,6 +172,7 @@ "source": [ "sim = run_tardis(\n", " \"tardis_example.yml\",\n", + " show_convergence_plots=True,\n", " plasma_plot_config={\n", " \"layout\": {\n", " \"template\": \"ggplot2\",\n", diff --git a/docs/io/visualization/tutorial_montecarlo_packet_visualization.ipynb b/docs/io/visualization/tutorial_montecarlo_packet_visualization.ipynb new file mode 100644 index 00000000000..c92c3e1122b --- /dev/null +++ b/docs/io/visualization/tutorial_montecarlo_packet_visualization.ipynb @@ -0,0 +1,385 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Montecarlo Packet Visualization" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This visualization tool plots the `RPackets` that are generated by the [Montecarlo](https://tardis-sn.github.io/tardis/physics/montecarlo/index.html) method and creates an animated plot that contains the packet trajectories as they move away from the photosphere.\n", + "The properties of individual RPackets are taken from the [rpacket_tracker](https://tardis-sn.github.io/tardis/io/output/how_to_rpacket_tracking.html). " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from tardis import run_tardis\n", + "from tardis.io.configuration.config_reader import Configuration\n", + "from tardis.io.atom_data.util import download_atom_data\n", + "import plotly.express as px\n", + "import plotly.graph_objects as go\n", + "import math\n", + "import pandas as pd\n", + "import numpy as np\n", + "import random" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Download atom data\n", + "download_atom_data('kurucz_cd23_chianti_H_He')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Reading the Configuration stored in `tardis_example.yml` into config\n", + "\n", + "config = Configuration.from_yaml(\"tardis_example.yml\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# changing config file for plotting 15 packets\n", + "\n", + "config[\"montecarlo\"][\"tracking\"][\"track_rpacket\"]=True\n", + "config[\"montecarlo\"][\"seed\"]= 457\n", + "config[\"montecarlo\"][\"no_of_packets\"]=10\n", + "config[\"montecarlo\"][\"iterations\"]=1\n", + "config[\"montecarlo\"][\"last_no_of_packets\"]=15\n", + "config[\"montecarlo\"][\"no_of_virtual_packets\"]=3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "sim = run_tardis(config, show_progress_bars=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# accessing the rpacket_tracker dataframe\n", + "sim.transport.transport_state.rpacket_tracker_df" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Finding packet coordinates\n", + "\n", + "\\\n", + "<img src=\"../images/packet_diagram.jpg\" style=\"width:400px\">\n", + "\n", + "<br><br>The diagram above shows the packet trajectory as it starts from photosphere `P0` and continues to move along the subsequent points `P1`, `P2`, and so on.\n", + "\n", + "<div class=\"alert alert-info\">\n", + "\n", + "Note\n", + " \n", + "Here `μ` represents the direction of packet propagation with respect to the radial line.\n", + " \n", + "</div>\n", + "\n", + "To determine the polar coordinates of any arbitrary point, say `P2`, we need `r2` and `θ2`. `r2` is already present in the array obtained from the simulation. To determine `θ2`, we use sine rule and apply it to the triangle `OP1P2`, where `O` is the center.\n", + "\n", + "$$\n", + "\\frac{r_{2}}{\\sin(\\pi - \\mu_{1})} = \\frac{r_{1}}{\\sin(\\alpha)}\n", + "$$\n", + "\n", + "Now, writing `α` in terms of `μ1` and `θ2`\n", + "\n", + "$$ \n", + "α = μ_{1} - θ_{2}\n", + "$$\n", + "$$\n", + "\\frac{r_{2}}{\\sin(\\pi - \\mu_{1})} = \\frac{r_{1}}{\\sin(μ_{1} - θ_{2})}\n", + "$$\n", + "\n", + "Thus,\n", + "\n", + "$$ \n", + "θ_{2} = -\\sin^{-1}(\\frac{r1}{r2}\\sin(\\mu_{1})) + \\mu_{1}\n", + "$$\n", + "\n", + "Hence, for `ith` point, `θ` will be:\n", + "\n", + "$$ \n", + "θ_{i} = -\\sin^{-1}(\\frac{r_{i-1}}{r_{i}}\\sin(\\mu_{i-1})) + \\mu_{i-1}\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# function for getting x y coordinates and interactions for a packet\n", + "def get_x_y_ints_with_theta_init(r_track,mu_track,time,last_interaction_type,direction=\"normal\",theta_initial=0):\n", + " xs,ys,theta,ints = [],[],[],[]\n", + " \n", + " for i in range(len(r_track)):\n", + " if(i==0):\n", + " theta.append(theta_initial)\n", + " else:\n", + " if(direction == 'random' or direction == 'r'):\n", + " multiplier = random.choice([-1,1])\n", + " elif(direction == 'opposite' or direction == 'o'):\n", + " multiplier = -1\n", + " else:\n", + " multiplier = 1\n", + " if (r_track[i]<r_track[i-1]):\n", + " theta.append(theta[-1] - math.pi + math.asin(r_track[i-1]*math.sin(multiplier * math.acos(mu_track[i-1]))/r_track[i]) + multiplier * math.acos(mu_track[i-1]))\n", + " else:\n", + " theta.append(theta[-1]+math.asin(-1*r_track[i-1]*math.sin(multiplier * math.acos(mu_track[i-1]))/r_track[i]) + multiplier * math.acos(mu_track[i-1]))\n", + " \n", + " \n", + " xs = (np.array(r_track))*np.cos(np.array(theta))*1e-5/time\n", + " ys = (np.array(r_track))*np.sin(np.array(theta))*1e-5/time\n", + " \n", + " for i in range(len(r_track)):\n", + " if(i==0 or i == len(r_track)-1):\n", + " ints.append(0)\n", + " else:\n", + " s0 = (ys[i]-ys[i-1])/(xs[i]-xs[i-1])\n", + " s1 = (ys[i+1]-ys[i])/(xs[i+1]-xs[i])\n", + " if(math.isclose(s0,s1,rel_tol=1e-11)):\n", + " ints.append(0)\n", + " else:\n", + " ints.append(last_interaction_type[i])\n", + "\n", + " return xs,ys,ints" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# function for getting coordinates of all packets\n", + "def get_coordinates_multiple_packets_ints(r_packet_tracker,time):\n", + " thetas = np.linspace(0, 2*math.pi,sim.transport.transport_state.rpacket_tracker_df.index[-1][0]+2)\n", + " x = []\n", + " y = []\n", + " inters = []\n", + " for i in range(sim.transport.transport_state.rpacket_tracker_df.index[-1][0]+1):\n", + " xs,ys,ints = get_x_y_ints_with_theta_init(r_packet_tracker.loc[i][\"r\"],r_packet_tracker.loc[i][\"mu\"],time,r_packet_tracker.loc[i][\"interaction_type\"],'n',thetas[i])\n", + " x.append(xs)\n", + " y.append(ys)\n", + " inters.append(ints)\n", + " return np.array(x,dtype=\"object\"),np.array(y,dtype=\"object\"),np.array(inters,dtype=\"object\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# function for normalizing array size for animation\n", + "def get_equal_array_size(xs,ys,ints):\n", + " max_size = max(list(map(len,xs)))\n", + " for i in range(len(xs)):\n", + " xs[i] = np.append(xs[i],xs[i][-1]*np.ones([max_size-len(xs[i])]))\n", + " ys[i] = np.append(ys[i],ys[i][-1]*np.ones([max_size-len(ys[i])]))\n", + " ints[i] = np.append(ints[i],ints[i][-1]*np.ones([max_size-len(ints[i])]))\n", + " return xs,ys,ints,max_size" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting Packet Trajectories" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# animated plot\n", + "\n", + "v_shells = sim.simulation_state.radius.value * 1e-5 / sim.simulation_state.time_explosion.value\n", + "xs,ys,ints = get_coordinates_multiple_packets_ints(sim.transport.transport_state.rpacket_tracker_df,sim.simulation_state.time_explosion.value)\n", + "xs,ys,ints,max_size = get_equal_array_size(xs,ys,ints)\n", + "\n", + "fig = go.Figure()\n", + "\n", + "# Set axes properties\n", + "fig.update_xaxes(range=[-1.1*v_shells[-1],1.1*v_shells[-1]],title=\"VELOCITY (KM/S)\",exponentformat=\"none\",linecolor=\"#555\",gridcolor=\"#fafafa\",zerolinecolor=\"#fafafa\")\n", + "fig.update_yaxes(range=[-1.1*v_shells[-1],1.1*v_shells[-1]],title=\"VELOCITY (KM/S)\",exponentformat=\"none\",linecolor=\"#555\",gridcolor=\"#fafafa\",zerolinecolor=\"#fafafa\")\n", + "\n", + "# adding the shells\n", + "shell_shapes={}\n", + "for i in range(len(sim.simulation_state.radius.value)-2,-2,-1):\n", + " if i==0:\n", + " fig.add_shape(type=\"circle\",\n", + " xref=\"x\", yref=\"y\",\n", + " x0=-1*v_shells[i], y0=-1*v_shells[i], x1=v_shells[i], y1=v_shells[i],\n", + " line_color=\"black\",\n", + " fillcolor=\"darkgrey\",\n", + " opacity=1\n", + " )\n", + " elif i==(len(sim.simulation_state.radius.value)-1):\n", + " fig.add_shape(type=\"circle\",\n", + " xref=\"x\", yref=\"y\",\n", + " x0=-1*v_shells[i], y0=-1*v_shells[i], x1=v_shells[i], y1=v_shells[i],\n", + " line_color=\"black\",\n", + " opacity=1\n", + " )\n", + " else:\n", + " fig.add_shape(type=\"circle\",\n", + " xref=\"x\", yref=\"y\",\n", + " x0=-1*v_shells[i], y0=-1*v_shells[i], x1=v_shells[i], y1=v_shells[i],\n", + " line_color=\"black\",\n", + " opacity=0.1\n", + " )\n", + "\n", + "#Add the packet trajectory\n", + "\n", + "df = sim.transport.transport_state.rpacket_tracker_df\n", + "interaction_from_num = {0: \"No Interaction\", 1: \"EScattering\", 2: \"Line\"}\n", + "interaction_color_from_num = {0: \"darkslategrey\", 1: \"#3366FF\", 2: \"#FF3300\"}\n", + "interaction_opacity_from_num = {0: 0, 1: 1, 2: 1}\n", + "\n", + "for i in range(len(xs)):\n", + " fig.add_trace(go.Scatter(\n", + " x=xs[i],\n", + " y=ys[i],\n", + " mode=\"markers+lines\",\n", + " name=\"Packet \"+str(i+1),\n", + " showlegend=False,\n", + " hovertemplate =\n", + " '<b>X</b>: %{x}'+\n", + " '<br><b>Y</b>: %{y}<br>'+\n", + " '<b>Last Interaction: %{text}</b>',\n", + " text = [interaction_from_num.get(ints[i][j]) for j in range(len(xs[i]))],\n", + " line = dict(color=\"darkslategrey\"),\n", + "# line_shape = \"spline\",\n", + " marker = dict(opacity = [interaction_opacity_from_num.get(ints[i][j]) for j in range(len(xs[i]))],color=[interaction_color_from_num.get(ints[i][j]) for j in range(len(xs[i]))])\n", + " ))\n", + "\n", + "#adding legends\n", + "fig.add_trace(go.Scatter(\n", + " x=[9999999],\n", + " y=[0],\n", + " legendgroup=\"a\",\n", + " opacity=1,\n", + " legendgrouptitle=dict(font=dict(color=\"#444\"),text=\"Interaction Type:\"),\n", + " mode=\"lines+markers\",\n", + " name=\"Escattering\",\n", + " hoverlabel=dict(font=dict(color=\"#222\")),\n", + " marker = dict(color=\"#3366FF\"),\n", + "))\n", + "fig.add_trace(go.Scatter(\n", + " x=[9999999],\n", + " y=[0],\n", + " legendgroup=\"a\",\n", + " opacity=1,\n", + " mode=\"lines+markers\",\n", + " name=\"Line\",\n", + " marker = dict(color=\"#FF3300\"),\n", + "))\n", + "\n", + "\n", + "# Set figure size\n", + "fig.layout.plot_bgcolor = '#fafafa'\n", + "fig.layout.paper_bgcolor = '#fafafa'\n", + "\n", + "fig.update_layout(width=900, height=900,\n", + " title=\"Packet Trajectories\",\n", + " title_font_color=\"#444\",\n", + " updatemenus=[dict(type=\"buttons\",\n", + " pad=dict(t=750),\n", + " buttons=[dict(label=\"Play\",\n", + " method=\"animate\",\n", + " args=[None])])])\n", + "\n", + "# creating frames for animation\n", + "def get_frames(l):\n", + " frames=[]\n", + " for i in range(len(xs)):\n", + " frames.append(go.Scatter(\n", + " x=xs[i].tolist()[0:l],\n", + " y=ys[i].tolist()[0:l],\n", + " mode=\"markers+lines\",\n", + " name=\"Packet \"+str(i+1),\n", + " showlegend=False,\n", + " hovertemplate =\n", + " '<b>X</b>: %{x}'+\n", + " '<br><b>Y</b>: %{y}<br>'+\n", + " '<b>Last Interaction: %{text}</b>',\n", + " text = [interaction_from_num.get(ints[i][j]) for j in range(len(xs[i]))],\n", + " line = dict(color=\"darkslategrey\"),\n", + " # line_shape = \"spline\",\n", + " marker = dict(opacity = [interaction_opacity_from_num.get(ints[i][j]) for j in range(len(xs[i]))],color=[interaction_color_from_num.get(ints[i][j]) for j in range(len(xs[i]))])\n", + " ))\n", + " return frames\n", + " \n", + "fig.frames=[go.Frame(data=get_frames(i)) for i in range(max_size+1)]\n", + "\n", + "fig.show(renderer=\"notebook_connected\")" + ] + } + ], + "metadata": { + "interpreter": { + "hash": "6890d83cfa6c65bebc4bd449872c06a268510d8b8ae8c923ce6786e6c4796836" + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/io/visualization/using_widgets.rst b/docs/io/visualization/using_widgets.rst index bd6fa8ef442..c8e03016fcd 100644 --- a/docs/io/visualization/using_widgets.rst +++ b/docs/io/visualization/using_widgets.rst @@ -4,8 +4,8 @@ Using TARDIS Widgets This page describes what each TARDIS Widget has to offer and how you can make the best use of it. If you're looking for the code to generate widgets, head -over to `Generating Custom Abundance Widget <abundance_widget>`_ section or -`Generating Data Exploration Widgets <generating_widgets>`_ section to see the +over to `Generating Custom Abundance Widget <how_to_abundance_widget>`_ section or +`Generating Data Exploration Widgets <how_to_generating_widgets>`_ section to see the notebook in action. Currently, TARDIS supports the following widgets: @@ -178,4 +178,40 @@ There are also several other options in the modebar which we have not explained you remember to click back on the **Box Select** option for making selections on spectrum. +Energy Level Diagram +################ + +This widget lets you visualize the last line interactions + +.. image:: ../images/energy_level_widget_demo.gif + :alt: Demo of Energy Level Diagram + +By selecting an ion on the widget, you can see its energy level diagram, which +also shows information about the last line interactions experienced by packets +in the simulation. + +The y-axis of the plot represents energy while the horizontal lines show +discrete energy levels. The thickness of each line represents the level +population, with thicker lines representing a greater population than the thin lines. + +Arrows represent the line interactions experienced by packets. Upwards arrows +show excitation from lower energy levels to higher levels and downward arrows +show de-excitation from higher energy levels to lower levels. The thickness of +each arrow represents the number of packets that underwent that interaction, +with thicker lines representing more packets than the thin lines. +The wavelength of the transition is given by the color. + +Setting Other Options +----------------- +You can select the range on which to filter the wavelength using the slider. +You can also select the model shell by which to filter the last line interactions +and the level populations. If no shell is selected, then all the last line +interactions are plotted and the level populations are averaged across all shells +in the simulation. You can also set the maximum number of levels to show on the plot. + +Lastly, you can also set the scale of the y-axis: Linear or Log. + +.. image:: ../images/energy_level_widget_options.gif + :alt: Demo of using options + .. Toggle legend diff --git a/docs/multiindex_isotope_decay_data.ipynb b/docs/multiindex_isotope_decay_data.ipynb new file mode 100644 index 00000000000..af07d7b8be3 --- /dev/null +++ b/docs/multiindex_isotope_decay_data.ipynb @@ -0,0 +1,426 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c2a689492f444a09a1641707600dbbae", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c485612f1f674a699550f3ec2237cc86", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Packets: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# general imports\n", + "from pathlib import Path\n", + "\n", + "# TARDIS imports for the gamma-ray code\n", + "from tardis.io.atom_data import AtomData\n", + "from tardis.model import SimulationState\n", + "from tardis.plasma.base import BasePlasma\n", + "from tardis.io.configuration import config_reader\n", + "from tardis.io.atom_data.util import download_atom_data\n", + "from tardis.energy_input.energy_source import get_nuclear_lines_database\n", + "from tardis.energy_input.gamma_ray_channel import create_isotope_dicts, create_inventories_dict, calculate_total_decays, create_isotope_decay_df\n", + "from tardis.plasma.properties import Density, Abundance, IsotopeAbundance, \\\n", + " IsotopeNumberDensity, AtomicData, AtomicMass, IsotopeMass, NumberDensity, \\\n", + " SelectedAtoms" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tardis.io.atom_data.atom_web_download:Atomic Data kurucz_cd23_chianti_H_He already exists in /Users/anirbandutta/Downloads/tardis-data/kurucz_cd23_chianti_H_He.h5. Will not download - override with force_download=True.\n", + "INFO:tardis.io.atom_data.base:Reading Atom Data with: UUID = 6f7b09e887a311e7a06b246e96350010 MD5 = 864f1753714343c41f99cb065710cace \n", + "INFO:tardis.io.atom_data.base:Non provided Atomic Data: synpp_refs, photoionization_data, yg_data, two_photon_data, linelist\n" + ] + } + ], + "source": [ + "# Download the atom data file from tardis-refdata repo to run this cell.\n", + "download_atom_data('kurucz_cd23_chianti_H_He')\n", + "atom_data_file = 'kurucz_cd23_chianti_H_He.h5'\n", + "atom_data = AtomData.from_hdf(atom_data_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the config file and create a configuration object\n", + "config = config_reader.Configuration.from_yaml(\"tardis_configv1_density_exponential_nebular.yml\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tardis.model.parse_input:Abundances have not been normalized to 1. - normalizing\n", + "INFO:tardis.model.matter.decay:Decaying abundances for 2600540.0352 seconds\n", + "/Users/anirbandutta/Software/tardis/tardis/model/matter/composition.py:101: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '7.961942738176252e-23' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n", + " isotope_mass_df[isotope_tuple] = isotope_mass\n" + ] + } + ], + "source": [ + "# Create the model\n", + "model = SimulationState.from_csvy(config, atom_data)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "gamma_ray_lines = get_nuclear_lines_database(atom_data_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "raw_isotope_abundance = model.composition.raw_isotope_abundance" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Construct the Plasma\n", + "\n", + "input = [Density, Abundance, IsotopeAbundance, AtomicData, AtomicMass, IsotopeNumberDensity, NumberDensity, SelectedAtoms, IsotopeMass]\n", + "\n", + "plasma = BasePlasma(plasma_properties=input, density = model.density, \n", + " abundance=model.abundance, isotope_abundance=model.composition.raw_isotope_abundance,\n", + " atomic_data = atom_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "shell_masses = model.volume * model.density" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "isotope_dict = create_isotope_dicts(raw_isotope_abundance, shell_masses)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "inventories_dict = create_inventories_dict(isotope_dict)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "total_decays = calculate_total_decays(inventories_dict, 80)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " 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<td>52.268439</td>\n", + " <td>0.000000e+00</td>\n", + " </tr>\n", + " <tr>\n", + " <th>V48</th>\n", + " <td>0.000000e+00</td>\n", + " <td>EC</td>\n", + " <td>g</td>\n", + " <td>2375.200000</td>\n", + " <td>0.0087</td>\n", + " <td>0.206642</td>\n", + " <td>0.000000e+00</td>\n", + " </tr>\n", + " <tr>\n", + " <th>V48</th>\n", + " <td>0.000000e+00</td>\n", + " <td>EC</td>\n", + " <td>g</td>\n", + " <td>2420.940000</td>\n", + " <td>0.0067</td>\n", + " <td>0.162203</td>\n", + " <td>0.000000e+00</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>18744 rows × 7 columns</p>\n", + "</div>" + ], + "text/plain": [ + " number_of_decays decay_mode radiation \\\n", + "shell_number isotope \n", + "0 Fe52 4.075312e+34 EC bp \n", + " Fe52 4.075312e+34 EC bp av \n", + " Fe52 4.075312e+34 EC e \n", + " Fe52 4.075312e+34 EC e \n", + " Fe52 4.075312e+34 EC e \n", + "... ... ... ... \n", + "65 V48 0.000000e+00 EC g \n", + " V48 0.000000e+00 EC g \n", + " V48 0.000000e+00 EC g \n", + " V48 0.000000e+00 EC g \n", + " V48 0.000000e+00 EC g \n", + "\n", + " radiation_energy_keV radiation_intensity \\\n", + "shell_number isotope \n", + "0 Fe52 340.000000 55.4900 \n", + " Fe52 340.000001 55.4900 \n", + " Fe52 5.190000 26.9000 \n", + " Fe52 0.610000 62.5000 \n", + " Fe52 162.149000 0.6990 \n", + "... ... ... \n", + "65 V48 1312.105000 98.2000 \n", + " V48 1437.521000 0.1200 \n", + " V48 2240.396000 2.3330 \n", + " V48 2375.200000 0.0087 \n", + " V48 2420.940000 0.0067 \n", + "\n", + " energy_per_channel_keV decay_energy_keV \n", + "shell_number isotope \n", + "0 Fe52 188.666000 7.688728e+36 \n", + " Fe52 188.666000 7.688728e+36 \n", + " Fe52 1.396110 5.689584e+34 \n", + " Fe52 0.381250 1.553713e+34 \n", + " Fe52 1.133422 4.619046e+34 \n", + "... ... ... \n", + "65 V48 1288.487110 0.000000e+00 \n", + " V48 1.725025 0.000000e+00 \n", + " V48 52.268439 0.000000e+00 \n", + " V48 0.206642 0.000000e+00 \n", + " V48 0.162203 0.000000e+00 \n", + "\n", + "[18744 rows x 7 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "create_isotope_decay_df(total_decays, gamma_ray_lines)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "tardis", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/outdated/commandline.rst b/docs/outdated/commandline.rst deleted file mode 100644 index e7f8625a7a8..00000000000 --- a/docs/outdated/commandline.rst +++ /dev/null @@ -1,34 +0,0 @@ -Running TARDIS in the commandline -================================= - -.. warning:: - - This option will be removed in the next versions of TARDIS - - -After installing TARDIS, just download the configuration file from the -`tardis-setups <https://github.com/tardis-sn/tardis-setups>`_ and the standard -atomic data set from the `tardis-refdata -<https://github.com/tardis-sn/tardis-refdata>`_ repository and run TARDIS. -Assuming you have ``wget``, you could follow the procedure: - - -.. code-block:: none - - mkdir tardis_example - cd tardis_example - wget https://raw.githubusercontent.com/tardis-sn/tardis-setups/master/2014/2014_kerzendorf_sim/appendix_A1/tardis_example.yml - wget https://github.com/tardis-sn/tardis-refdata/raw/master/atom_data/kurucz_cd23_chianti_H_He.h5 - tardis tardis_example.yml output_spectrum.dat - - -Then plot the output_spectrum.dat with your favourite plotting program. Here's an example of how to do this with python -(the only thing you need to install is ipython and matplotlib --- in addition to TARDIS's requirements). - -.. code-block:: python - - ipython --pylab - >>> tardis_spec = loadtxt('output_spectrum.dat') - >>> plot(tardis_spec[:,0], tardis_spec[:,1]) - -More atomic datasets can be downloaded from :ref:`atomic-data-download`. \ No newline at end of file diff --git a/docs/outdated/index.rst b/docs/outdated/index.rst deleted file mode 100644 index a34afb56642..00000000000 --- a/docs/outdated/index.rst +++ /dev/null @@ -1,26 +0,0 @@ -********************** -Outdated Documentation -********************** - -The following pages are no longer relevant to the most recent release of TARDIS: - -.. warning:: Please update to a newer version of TARDIS. The most recent version number can be found near the top of the documentation sidebar. - -.. toctree:: - - commandline - old_gui - openmp - old_install - - -The following pages are no longer applicable to the TARDIS documentation in its current form, but will be edited -and incorporated back into the documentation in the future: - -.. toctree:: - - init_trad_bug - isotope_pd_subclass - hdf_writer - integrator - using_formal_integral \ No newline at end of file diff --git a/docs/outdated/init_trad_bug.ipynb b/docs/outdated/init_trad_bug.ipynb deleted file mode 100644 index 4a756cabc46..00000000000 --- a/docs/outdated/init_trad_bug.ipynb +++ /dev/null @@ -1,1710 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Initial_t_rad Bug\n", - "\n", - "The purpose of this notebook is to demonstrate the bug associated with setting the initial_t_rad tardis.plasma property." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/Users/marcwilliamson/src/dev/tardis/docs/notebooks'" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pwd" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/anaconda2/envs/tardis/lib/python3.6/site-packages/tqdm/autonotebook/__init__.py:14: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n", - " \" (e.g. in jupyter console)\", TqdmExperimentalWarning)\n" - ] - } - ], - "source": [ - "import tardis\n", - "import numpy as np" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Density and Abundance test files\n", - "\n", - "Below are the density and abundance data from the test files used for demonstrating this bug." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.00000000e+00 2.90000000e+03 4.28253781e-16]\n", - " [1.00000000e+00 3.00000000e+03 4.12668886e-16]\n", - " [2.00000000e+00 3.10000000e+03 3.94940562e-16]\n", - " [3.00000000e+00 3.20000000e+03 3.80047743e-16]\n", - " [4.00000000e+00 3.30000000e+03 3.63720829e-16]\n", - " [5.00000000e+00 3.40000000e+03 3.53372945e-16]\n", - " [6.00000000e+00 3.50000000e+03 3.46148955e-16]\n", - " [7.00000000e+00 3.60000000e+03 3.37683976e-16]\n", - " [8.00000000e+00 3.70000000e+03 3.30780715e-16]\n", - " [9.00000000e+00 3.80000000e+03 3.26689004e-16]\n", - " [1.00000000e+01 3.90000000e+03 3.23089580e-16]]\n", - "[[0. 1. ]\n", - " [0.1 0.9]\n", - " [0.2 0.8]\n", - " [0.3 0.7]\n", - " [0.4 0.6]\n", - " [0.5 0.5]\n", - " [0.6 0.4]\n", - " [0.7 0.3]\n", - " [0.8 0.2]\n", - " [0.9 0.1]]\n" - ] - } - ], - "source": [ - "density_dat = np.loadtxt('data/density.txt',skiprows=1)\n", - "abund_dat = np.loadtxt('data/abund.dat', skiprows=1)\n", - "\n", - "print(density_dat)\n", - "print(abund_dat)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## No initial_t_rad\n", - "\n", - "Below we run a simple tardis simulation where `initial_t_rad` is not set. The simulation has v_inner_boundary = 3350 km/s and v_outer_boundary = 3750 km/s, both within the velocity range in the density file. The simulation runs fine." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/importlib/_bootstrap.py:219: QAWarning: pyne.data is not yet QA compliant.\n", - " return f(*args, **kwds)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/importlib/_bootstrap.py:219: QAWarning: pyne.material is not yet QA compliant.\n", - " return f(*args, **kwds)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:394)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /Users/marcwilliamson/Research/TARDIS/tardis-refdata/atom_data/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:74)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/IPython/core/interactiveshell.py:3296: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Read Atom Data with UUID=6f7b09e887a311e7a06b246e96350010 and MD5=864f1753714343c41f99cb065710cace. (\u001b[1mbase.py\u001b[0m:184)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Non provided atomic data: synpp_refs, photoionization_data (\u001b[1mbase.py\u001b[0m:187)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/ion_population.py:63: FutureWarning: \n", - "Passing list-likes to .loc or [] with any missing label will raise\n", - "KeyError in the future, you can use .reindex() as an alternative.\n", - "\n", - "See the documentation here:\n", - "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", - " partition_function.index].dropna())\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 1/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 7.60257e+41 erg / s Luminosity absorbed = 2.81189e+40 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 9464.058312 9484.781155 0.439255 0.464482\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 9464.848 K -- next t_inner 12021.255 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/ion_population.py:63: FutureWarning: \n", - "Passing list-likes to .loc or [] with any missing label will raise\n", - "KeyError in the future, you can use .reindex() as an alternative.\n", - "\n", - "See the documentation here:\n", - "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", - " partition_function.index].dropna())\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 2/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.60837e+42 erg / s Luminosity absorbed = 5.98006e+40 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 9484.781155 12054.327238 0.464482 0.464327\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12021.255 K -- next t_inner 10497.194 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 3/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 9.75339e+41 erg / s Luminosity absorbed = 1.31663e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12054.327238 10542.291939 0.464327 0.509656\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 10497.194 K -- next t_inner 11770.965 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 4/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.41912e+42 erg / s Luminosity absorbed = 1.52432e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 10542.291939 11750.092484 0.509656 0.512801\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11770.965 K -- next t_inner 10942.574 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 5/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.11236e+42 erg / s Luminosity absorbed = 1.52914e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11750.092484 10938.987367 0.512801 0.525724\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 10942.574 K -- next t_inner 11489.809 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 6/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.29924e+42 erg / s Luminosity absorbed = 1.66012e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 1/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 10938.987367 11456.397166 0.525724 0.521184\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11489.809 K -- next t_inner 11163.104 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 7/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.16874e+42 erg / s Luminosity absorbed = 1.57467e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 2/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11456.397166 11225.829447 0.521184 0.516013\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11163.104 K -- next t_inner 11435.147 K (\u001b[1mbase.py\u001b[0m:350)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 8/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.27029e+42 erg / s Luminosity absorbed = 1.71822e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 3/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11225.829447 11346.454712 0.516013 0.53765\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11435.147 K -- next t_inner 11235.867 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 9/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.20003e+42 erg / s Luminosity absorbed = 1.63905e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 4/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11346.454712 11219.677659 0.53765 0.529105\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11235.867 K -- next t_inner 11358.682 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 10/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.24727e+42 erg / s Luminosity absorbed = 1.71495e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 5/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11219.677659 11296.3854 0.529105 0.53421\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11358.682 K -- next t_inner 11263.268 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 11/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.20567e+42 erg / s Luminosity absorbed = 1.59529e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 6/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11296.3854 11282.219084 0.53421 0.519595\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11263.268 K -- next t_inner 11359.683 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 12/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23796e+42 erg / s Luminosity absorbed = 1.69674e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 7/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11282.219084 11392.613803 0.519595 0.515397\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11359.683 K -- next t_inner 11306.524 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 13/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22796e+42 erg / s Luminosity absorbed = 1.72554e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11392.613803 11274.095909 0.515397 0.534286\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11306.524 K -- next t_inner 11299.342 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 14/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22087e+42 erg / s Luminosity absorbed = 1.68061e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 1/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11274.095909 11272.622074 0.534286 0.523052\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11299.342 K -- next t_inner 11324.894 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 15/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23507e+42 erg / s Luminosity absorbed = 1.67026e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 2/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11272.622074 11242.582689 0.523052 0.53977\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11324.894 K -- next t_inner 11285.077 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 16/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.21940e+42 erg / s Luminosity absorbed = 1.66346e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 3/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11242.582689 11290.452474 0.53977 0.522924\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11285.077 K -- next t_inner 11317.456 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 17/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22578e+42 erg / s Luminosity absorbed = 1.67022e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 4/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11290.452474 11301.322725 0.522924 0.528649\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11317.456 K -- next t_inner 11320.345 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 18/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22546e+42 erg / s Luminosity absorbed = 1.63272e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 5/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11301.322725 11321.012024 0.528649 0.522716\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11320.345 K -- next t_inner 11324.684 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 19/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22575e+42 erg / s Luminosity absorbed = 1.70322e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 6/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11321.012024 11372.823716 0.522716 0.516131\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11324.684 K -- next t_inner 11327.703 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 20/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23543e+42 erg / s Luminosity absorbed = 1.67596e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Simulation finished in 20 iterations and took 1.61 s (\u001b[1mbase.py\u001b[0m:306)\n" - ] - } - ], - "source": [ - "no_init_trad = tardis.run_tardis('data/config_no_init_trad.yml')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$[3.35 \\times 10^{8},~3.4 \\times 10^{8},~3.5 \\times 10^{8},~3.6 \\times 10^{8},~3.7 \\times 10^{8},~3.75 \\times 10^{8}] \\; \\mathrm{\\frac{cm}{s}}$" - ], - "text/plain": [ - "<Quantity [3.35e+08, 3.40e+08, 3.50e+08, 3.60e+08, 3.70e+08, 3.75e+08] cm / s>" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "no_init_trad.model.velocity" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(5, 10)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "no_init_trad.model.no_of_shells, no_init_trad.model.no_of_raw_shells" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "raw velocity: \n", - " [2.9e+08 3.0e+08 3.1e+08 3.2e+08 3.3e+08 3.4e+08 3.5e+08 3.6e+08 3.7e+08\n", - " 3.8e+08 3.9e+08] cm / s\n", - "raw velocity shape: (11,)\n", - "(v_boundary_inner, v_boundary_outer) = (3350, 3750)\n", - "v_boundary_inner_index: 4\n", - "v_boundary_outer_index: 10\n", - "t_rad [11372.82371614 11426.15383155 11420.35713928 11382.47864204\n", - " 11375.63115928] K\n" - ] - } - ], - "source": [ - "print('raw velocity: \\n',no_init_trad.model.raw_velocity)\n", - "print('raw velocity shape: ',no_init_trad.model.raw_velocity.shape)\n", - "print('(v_boundary_inner, v_boundary_outer) = (%i, %i)'%\n", - " (no_init_trad.model.v_boundary_inner.to('km/s').value, no_init_trad.model.v_boundary_outer.to('km/s').value))\n", - "print('v_boundary_inner_index: ', no_init_trad.model.v_boundary_inner_index)\n", - "print('v_boundary_outer_index: ', no_init_trad.model.v_boundary_outer_index)\n", - "print('t_rad', no_init_trad.model.t_rad)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Debugging" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOTE: Enter 'c' at the ipdb> prompt to continue execution.\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> b tardis/plasma/properties/j_blues:34\n", - "Breakpoint 1 at /Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/j_blues.py:34\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:368)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /Users/marcwilliamson/Research/TARDIS/tardis-refdata/atom_data/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:74)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/bdb.py:434: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " exec(cmd, globals, locals)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Read Atom Data with UUID=6f7b09e887a311e7a06b246e96350010 and MD5=864f1753714343c41f99cb065710cace. (\u001b[1mbase.py\u001b[0m:184)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Non provided atomic data: synpp_refs, photoionization_data (\u001b[1mbase.py\u001b[0m:187)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/j_blues.py\u001b[0m(34)\u001b[0;36mcalculate\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 32 \u001b[0;31m \u001b[0;34m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 33 \u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0mcalculate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlines\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_rad\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m--> 34 \u001b[0;31m \u001b[0mj_blues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mw\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mintensity_black_body\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnewaxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_rad\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 35 \u001b[0;31m j_blues = pd.DataFrame(j_blues, index=lines.index,\n", - "\u001b[0m\u001b[0;32m 36 \u001b[0;31m columns=np.arange(len(t_rad)))\n", - "\u001b[0m\n", - "ipdb> n\n", - "ValueError: operands could not be broadcast together with shapes (5,) (247,6)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/j_blues.py\u001b[0m(34)\u001b[0;36mcalculate\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 32 \u001b[0;31m \u001b[0;34m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 33 \u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0mcalculate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlines\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_rad\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m--> 34 \u001b[0;31m \u001b[0mj_blues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mw\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mintensity_black_body\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnewaxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_rad\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 35 \u001b[0;31m j_blues = pd.DataFrame(j_blues, index=lines.index,\n", - "\u001b[0m\u001b[0;32m 36 \u001b[0;31m columns=np.arange(len(t_rad)))\n", - "\u001b[0m\n", - "ipdb> restart\n", - "Restarting\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:368)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /Users/marcwilliamson/Research/TARDIS/tardis-refdata/atom_data/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:74)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/bdb.py:434: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " exec(cmd, globals, locals)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Read Atom Data with UUID=6f7b09e887a311e7a06b246e96350010 and MD5=864f1753714343c41f99cb065710cace. (\u001b[1mbase.py\u001b[0m:184)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Non provided atomic data: synpp_refs, photoionization_data (\u001b[1mbase.py\u001b[0m:187)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/j_blues.py\u001b[0m(34)\u001b[0;36mcalculate\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 32 \u001b[0;31m \u001b[0;34m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 33 \u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0mcalculate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlines\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_rad\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m--> 34 \u001b[0;31m \u001b[0mj_blues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mw\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mintensity_black_body\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnewaxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_rad\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 35 \u001b[0;31m j_blues = pd.DataFrame(j_blues, index=lines.index,\n", - "\u001b[0m\u001b[0;32m 36 \u001b[0;31m columns=np.arange(len(t_rad)))\n", - "\u001b[0m\n", - "ipdb> t_rad\n", - "array([11000., 11000., 11000., 11000., 11000., 11000.])\n", - "ipdb> lines.shape\n", - "(247, 9)\n", - "ipdb> intensity_black_body(nu.values[np.newaxis].T, t_rad)\n", - "array([[3.45300820e-23, 3.45300820e-23, 3.45300820e-23, 3.45300820e-23,\n", - " 3.45300820e-23, 3.45300820e-23],\n", - " [3.45300820e-23, 3.45300820e-23, 3.45300820e-23, 3.45300820e-23,\n", - " 3.45300820e-23, 3.45300820e-23],\n", - " [1.17024224e-22, 1.17024224e-22, 1.17024224e-22, 1.17024224e-22,\n", - " 1.17024224e-22, 1.17024224e-22],\n", - " ...,\n", - " [1.65889253e-10, 1.65889253e-10, 1.65889253e-10, 1.65889253e-10,\n", - " 1.65889253e-10, 1.65889253e-10],\n", - " [1.65754663e-10, 1.65754663e-10, 1.65754663e-10, 1.65754663e-10,\n", - " 1.65754663e-10, 1.65754663e-10],\n", - " [8.99221749e-11, 8.99221749e-11, 8.99221749e-11, 8.99221749e-11,\n", - " 8.99221749e-11, 8.99221749e-11]])\n", - "ipdb> intensity_black_body(nu.values[np.newaxis].T, t_rad).shape\n", - "(247, 6)\n", - "ipdb> lines.shape\n", - "(247, 9)\n", - "ipdb> nu.shape\n", - "(247,)\n", - "ipdb> restart\n", - "Restarting\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> b tardis/simulation/base:436\n", - "Breakpoint 2 at /Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py:436\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:368)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py\u001b[0m(436)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 434 \u001b[0;31m \u001b[0mplasma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'plasma'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 435 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m-> 436 \u001b[0;31m plasma = assemble_plasma(config, model,\n", - "\u001b[0m\u001b[0;32m 437 \u001b[0;31m atom_data=kwargs.get('atom_data', None))\n", - "\u001b[0m\u001b[0;32m 438 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;34m'runner'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ipdb> model\n", - "<tardis.model.base.Radial1DModel object at 0x12e05a940>\n", - "ipdb> model.trad\n", - "*** AttributeError: 'Radial1DModel' object has no attribute 'trad'\n", - "ipdb> model.t_rad\n", - "<Quantity [11000., 11000., 11000., 11000., 11000., 11000.] K>\n", - "ipdb> model.velocity\n", - "<Quantity [3.35e+08, 3.40e+08, 3.50e+08, 3.60e+08, 3.70e+08, 3.75e+08] cm / s>\n", - "ipdb> b tardis/model/base:334\n", - "Breakpoint 3 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:334\n", - "ipdb> restart\n", - "Restarting\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> c\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(334)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 332 \u001b[0;31m \u001b[0mt_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtemperature\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 333 \u001b[0;31m \u001b[0;32melif\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplasma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minitial_t_rad\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m3\u001b[0;32m-> 334 \u001b[0;31m \u001b[0mt_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mones\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mno_of_shells\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplasma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minitial_t_rad\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 335 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 336 \u001b[0;31m \u001b[0mt_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> n\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(338)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 336 \u001b[0;31m \u001b[0mt_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 337 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m--> 338 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplasma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minitial_t_inner\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0.0\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 339 \u001b[0;31m \u001b[0mluminosity_requested\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupernova\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mluminosity_requested\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 340 \u001b[0;31m \u001b[0mt_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> t_radiative\n", - "<Quantity [11000., 11000., 11000., 11000., 11000., 11000., 11000., 11000.,\n", - " 11000., 11000.] K>\n", - "ipdb> b tardis/model/base:107\n", - "Breakpoint 4 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:107\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:368)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(107)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 105 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 106 \u001b[0;31m \u001b[0;31m#self._t_radiative = t_radiative[self.v_boundary_inner_index + 0:self.v_boundary_outer_index-1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m4\u001b[0;32m-> 107 \u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_t_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_radiative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 108 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 109 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mdilution_factor\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> t_radiative\n", - "<Quantity [11000., 11000., 11000., 11000., 11000., 11000., 11000., 11000.,\n", - " 11000., 11000.] K>\n" - ] - } - ], - "source": [ - "%%debug\n", - "init_trad = tardis.run_tardis('data/config_init_trad.yml')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:394)\n", - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /Users/marcwilliamson/Research/TARDIS/tardis-refdata/atom_data/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:74)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/IPython/core/interactiveshell.py:3296: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Read Atom Data with UUID=6f7b09e887a311e7a06b246e96350010 and MD5=864f1753714343c41f99cb065710cace. (\u001b[1mbase.py\u001b[0m:184)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Non provided atomic data: synpp_refs, photoionization_data (\u001b[1mbase.py\u001b[0m:187)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/ion_population.py:63: FutureWarning: \n", - "Passing list-likes to .loc or [] with any missing label will raise\n", - "KeyError in the future, you can use .reindex() as an alternative.\n", - "\n", - "See the documentation here:\n", - "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", - " partition_function.index].dropna())\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 1/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 5.98252e+41 erg / s Luminosity absorbed = 1.50141e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11000.0 10177.195287 0.408333 0.538077\n", - "\t5 11000.0 10160.603522 0.229156 0.282716\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 10172.718 K -- next t_inner 14565.035 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 2/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.82691e+42 erg / s Luminosity absorbed = 2.82152e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 10177.195287 14593.630626 0.538077 0.496563\n", - "\t5 10160.603522 14511.556871 0.282716 0.275395\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 14565.035 K -- next t_inner 11933.532 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 3/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 9.71423e+41 erg / s Luminosity absorbed = 2.55207e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 14593.630626 11959.523175 0.496563 0.536576\n", - "\t5 14511.556871 11863.444513 0.275395 0.288444\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11933.532 K -- next t_inner 13408.534 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 4/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.34841e+42 erg / s Luminosity absorbed = 3.56350e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11959.523175 13397.442807 0.536576 0.545853\n", - "\t5 11863.444513 13434.561796 0.288444 0.279834\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 13408.534 K -- next t_inner 12787.534 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 5/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.18228e+42 erg / s Luminosity absorbed = 3.17468e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 13397.442807 12761.259654 0.545853 0.549926\n", - "\t5 13434.561796 12694.451547 0.279834 0.291458\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12787.534 K -- next t_inner 13023.975 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 6/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.24451e+42 erg / s Luminosity absorbed = 3.27235e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 1/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12761.259654 12957.006442 0.549926 0.556939\n", - "\t5 12694.451547 12962.669431 0.291458 0.289348\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 13023.975 K -- next t_inner 12928.870 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 7/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.20889e+42 erg / s Luminosity absorbed = 3.17537e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 2/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12957.006442 13011.562529 0.556939 0.528909\n", - "\t5 12962.669431 12911.385086 0.289348 0.287062\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12928.870 K -- next t_inner 13022.158 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 8/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23931e+42 erg / s Luminosity absorbed = 3.40055e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 3/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 13011.562529 12935.144806 0.528909 0.559823\n", - "\t5 12911.385086 12870.837942 0.287062 0.295395\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 13022.158 K -- next t_inner 12954.144 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 9/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22083e+42 erg / s Luminosity absorbed = 3.29617e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 4/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12935.144806 12952.771269 0.559823 0.547270\n", - "\t5 12870.837942 12869.711846 0.295395 0.288923\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12954.144 K -- next t_inner 12983.662 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 10/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23857e+42 erg / s Luminosity absorbed = 3.31449e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 5/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12952.771269 12942.126028 0.547270 0.550270\n", - "\t5 12869.711846 12884.875415 0.288923 0.292539\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12983.662 K -- next t_inner 12919.755 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 11/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.21056e+42 erg / s Luminosity absorbed = 3.23893e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 6/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12942.126028 12918.966676 0.550270 0.544292\n", - "\t5 12884.875415 12886.798065 0.292539 0.286558\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12919.755 K -- next t_inner 13004.019 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 12/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22616e+42 erg / s Luminosity absorbed = 3.33203e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 7/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12918.966676 13031.662542 0.544292 0.538490\n", - "\t5 12886.798065 13010.109337 0.286558 0.282402\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 13004.019 K -- next t_inner 13005.291 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 13/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.24894e+42 erg / s Luminosity absorbed = 3.24574e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 8/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 13031.662542 12990.586647 0.538490 0.548625\n", - "\t5 13010.109337 13019.214949 0.282402 0.283709\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 13005.291 K -- next t_inner 12887.418 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 14/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.21057e+42 erg / s Luminosity absorbed = 3.20036e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 9/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12990.586647 12897.972400 0.548625 0.540328\n", - "\t5 13019.214949 12826.318536 0.283709 0.288119\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12887.418 K -- next t_inner 12971.403 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 15/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23054e+42 erg / s Luminosity absorbed = 3.31427e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12897.972400 12860.146712 0.540328 0.564957\n", - "\t5 12826.318536 12875.961642 0.288119 0.291152\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12971.403 K -- next t_inner 12949.598 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 16/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22535e+42 erg / s Luminosity absorbed = 3.21967e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 1/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12860.146712 12941.966455 0.564957 0.546565\n", - "\t5 12875.961642 12851.925013 0.291152 0.290785\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12949.598 K -- next t_inner 12955.177 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 17/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.21929e+42 erg / s Luminosity absorbed = 3.29847e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 2/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12941.966455 12925.141575 0.546565 0.554237\n", - "\t5 12851.925013 12885.285408 0.290785 0.289662\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12955.177 K -- next t_inner 12992.898 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 18/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22332e+42 erg / s Luminosity absorbed = 3.27060e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 3/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12925.141575 13004.854945 0.554237 0.543770\n", - "\t5 12885.285408 13027.690260 0.289662 0.281762\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12992.898 K -- next t_inner 13009.263 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 19/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22932e+42 erg / s Luminosity absorbed = 3.29206e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 4/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 13004.854945 13056.576129 0.543770 0.537160\n", - "\t5 13027.690260 13038.177112 0.281762 0.277439\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 13009.263 K -- next t_inner 12993.824 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 20/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23821e+42 erg / s Luminosity absorbed = 3.24957e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Simulation finished in 20 iterations and took 2.23 s (\u001b[1mbase.py\u001b[0m:306)\n" - ] - } - ], - "source": [ - "init_trad = tardis.run_tardis('data/config_init_trad.yml')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Debugging" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Debugging No initial_t_radiative run to compare with Yes initial_t_radiative run\n", - "\n", - "\n", - "We place two breakpoints:\n", - "\n", - "break 1. tardis/base:37 --> Stops in the run_tardis() function when the simulation is initialized.\n", - "\n", - "break 2. tardis/simulation/base:436 --> Stops after the Radial1DModel has been built from the config file, but before the plasma has been initialized.\n", - "\n", - "## IMPORTANT:\n", - "\n", - "We check the model.t_radiative property INSIDE the assemble_plasma function. Notice that it has len(model.t_radiative) = model.no_of_shells = 5" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOTE: Enter 'c' at the ipdb> prompt to continue execution.\n", - "None\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> b tardis/base:37\n", - "Breakpoint 1 at /Users/marcwilliamson/src/dev/tardis/tardis/base.py:37\n", - "ipdb> b tardis/simulation/base:436\n", - "Breakpoint 2 at /Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py:436\n", - "ipdb> c\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/base.py\u001b[0m(37)\u001b[0;36mrun_tardis\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 35 \u001b[0;31m \u001b[0mtardis_config\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mConfiguration\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_config_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 36 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m--> 37 \u001b[0;31m \u001b[0msimulation\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSimulation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_config\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtardis_config\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0matom_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0matom_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 38 \u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mcb\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msimulation_callbacks\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 39 \u001b[0;31m \u001b[0msimulation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_callback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:367)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py\u001b[0m(436)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 434 \u001b[0;31m \u001b[0mplasma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'plasma'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 435 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m-> 436 \u001b[0;31m plasma = assemble_plasma(config, model,\n", - "\u001b[0m\u001b[0;32m 437 \u001b[0;31m atom_data=kwargs.get('atom_data', None))\n", - "\u001b[0m\u001b[0;32m 438 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;34m'runner'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> s\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py\u001b[0m(437)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 435 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m 436 \u001b[0;31m plasma = assemble_plasma(config, model,\n", - "\u001b[0m\u001b[0;32m--> 437 \u001b[0;31m atom_data=kwargs.get('atom_data', None))\n", - "\u001b[0m\u001b[0;32m 438 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;34m'runner'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 439 \u001b[0;31m \u001b[0mrunner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'runner'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> s\n", - "--Call--\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/standard_plasmas.py\u001b[0m(33)\u001b[0;36massemble_plasma\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 31 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 32 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m---> 33 \u001b[0;31m\u001b[0;32mdef\u001b[0m \u001b[0massemble_plasma\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0matom_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 34 \u001b[0;31m \"\"\"\n", - "\u001b[0m\u001b[0;32m 35 \u001b[0;31m \u001b[0mCreate\u001b[0m \u001b[0ma\u001b[0m \u001b[0mBasePlasma\u001b[0m \u001b[0minstance\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0ma\u001b[0m \u001b[0mConfiguration\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> n\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/standard_plasmas.py\u001b[0m(52)\u001b[0;36massemble_plasma\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 50 \u001b[0;31m \"\"\"\n", - "\u001b[0m\u001b[0;32m 51 \u001b[0;31m \u001b[0;31m# Convert the nlte species list to a proper format.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m---> 52 \u001b[0;31m nlte_species = [species_string_to_tuple(s) for s in\n", - "\u001b[0m\u001b[0;32m 53 \u001b[0;31m config.plasma.nlte.species]\n", - "\u001b[0m\u001b[0;32m 54 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> model.t_radiative\n", - "<Quantity [9464.0583115 , 9461.69144847, 9458.53747203, 9455.38559759,\n", - " 9453.02306994] K>\n", - "ipdb> model.no_of_shells\n", - "5\n", - "ipdb> len(model.t_radiative)==model.no_of_shells\n", - "True\n", - "ipdb> exit\n" - ] - } - ], - "source": [ - "%%debug\n", - "no_init_trad = tardis.run_tardis('config_no_init_trad.yml')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Debugging Yes initial_t_radiative run\n", - "\n", - "\n", - "\n", - "We place the same two breakpoints as above:\n", - "\n", - "break 1. tardis/base:37 --> Stops in the run_tardis() function when the simulation is initialized.\n", - "\n", - "break 2. tardis/simulation/base:436 --> Stops after the Radial1DModel has been built from the config file, but before the plasma has been initialized.\n", - "\n", - "## IMPORTANT:\n", - "\n", - "We check the model.t_radiative property INSIDE the assemble_plasma function. Notice that it has len(model.t_radiative) = 6 which is NOT EQUAL to model.no_of_shells = 5" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOTE: Enter 'c' at the ipdb> prompt to continue execution.\n", - "None\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> b tardis/base:37\n", - "Breakpoint 1 at /Users/marcwilliamson/src/dev/tardis/tardis/base.py:37\n", - "ipdb> b tardis/simulation/base:436\n", - "Breakpoint 2 at /Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py:436\n", - "ipdb> c\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/base.py\u001b[0m(37)\u001b[0;36mrun_tardis\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 35 \u001b[0;31m \u001b[0mtardis_config\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mConfiguration\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_config_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 36 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m--> 37 \u001b[0;31m \u001b[0msimulation\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSimulation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_config\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtardis_config\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0matom_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0matom_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 38 \u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mcb\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msimulation_callbacks\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 39 \u001b[0;31m \u001b[0msimulation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_callback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:367)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py\u001b[0m(436)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 434 \u001b[0;31m \u001b[0mplasma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'plasma'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 435 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m-> 436 \u001b[0;31m plasma = assemble_plasma(config, model,\n", - "\u001b[0m\u001b[0;32m 437 \u001b[0;31m atom_data=kwargs.get('atom_data', None))\n", - "\u001b[0m\u001b[0;32m 438 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;34m'runner'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> s\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/simulation/base.py\u001b[0m(437)\u001b[0;36mfrom_config\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 435 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m 436 \u001b[0;31m plasma = assemble_plasma(config, model,\n", - "\u001b[0m\u001b[0;32m--> 437 \u001b[0;31m atom_data=kwargs.get('atom_data', None))\n", - "\u001b[0m\u001b[0;32m 438 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;34m'runner'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 439 \u001b[0;31m \u001b[0mrunner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'runner'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> s\n", - "--Call--\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/standard_plasmas.py\u001b[0m(33)\u001b[0;36massemble_plasma\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 31 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 32 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m---> 33 \u001b[0;31m\u001b[0;32mdef\u001b[0m \u001b[0massemble_plasma\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0matom_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 34 \u001b[0;31m \"\"\"\n", - "\u001b[0m\u001b[0;32m 35 \u001b[0;31m \u001b[0mCreate\u001b[0m \u001b[0ma\u001b[0m \u001b[0mBasePlasma\u001b[0m \u001b[0minstance\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0ma\u001b[0m \u001b[0mConfiguration\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> n\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/plasma/standard_plasmas.py\u001b[0m(52)\u001b[0;36massemble_plasma\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 50 \u001b[0;31m \"\"\"\n", - "\u001b[0m\u001b[0;32m 51 \u001b[0;31m \u001b[0;31m# Convert the nlte species list to a proper format.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m---> 52 \u001b[0;31m nlte_species = [species_string_to_tuple(s) for s in\n", - "\u001b[0m\u001b[0;32m 53 \u001b[0;31m config.plasma.nlte.species]\n", - "\u001b[0m\u001b[0;32m 54 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> model.t_radiative\n", - "<Quantity [11000., 11000., 11000., 11000., 11000., 11000.] K>\n", - "ipdb> len(model.t_radiative) == model.no_of_shells\n", - "False\n", - "ipdb> exit\n" - ] - } - ], - "source": [ - "%%debug\n", - "init_trad = tardis.run_tardis('config_init_trad.yml')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Checking model.t_radiative initialization when YES initial_t_rad\n", - "\n", - "In the above debugging blocks, we have identified the following discrepancy INSIDE assemble_plasma(): \n", - "\n", - "### len(model.t_radiative) = 6 when YES initial_t_rad\n", - "### len(model.t_radiative) = 5 when NO initial_t_rad\n", - "\n", - "Therefore, we investigate in the following debugging block how model.t_radiative is initialized. We place a breakpoint at tardis/simulation/base:432 and step INSIDE the Radial1DModel initialization.\n", - "\n", - "Breakpoints:\n", - "\n", - "break 1. tardis/simulation/base:432 --> Stops so that we can step INSIDE Radial1DModel initialization from_config().\n", - "\n", - "break 2. tardis/model/base:330 --> Where temperature is handled INSIDE Radial1DModel initialization from_config().\n", - "\n", - "break 3. tardis/model/base:337 --> `t_radiative` is initialized. It has the same length as `velocity` which is the raw velocities from the density file.\n", - "\n", - "break 4. tardis/model/base:374 --> init() for Radial1DModel is called. We check values of relevant variables.\n", - "\n", - "break 5. tardis/model/base:76 --> Stops at first line of Radial1DModel init() function.\n", - "\n", - "break 6. tardis/model/base:101 --> self.\\_t\\_radiative is set.\n", - "\n", - "break 7. tardis/model/base:140 --> Stops at first line of self.t_radiative setter.\n", - "\n", - "break 8. tardis/model/base:132 --> Stops at first line of self.t_radiative getter.\n", - "\n", - "break 9. tardis/model/base:108 --> Stop right after self.\\_t\\_radiative is set. NOTICE that neither the setter nor the getter was called. __IMPORTANT:__ at line 108, we have len(self.\\_t\\_radiative) = 10. __TO DO:__ Check len(self.\\_t\\_radiative) at line 108 in the NO initial\\_t\\_rad case." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOTE: Enter 'c' at the ipdb> prompt to continue execution.\n", - "None\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> b tardis/model/base:101\n", - "Breakpoint 1 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:101\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:367)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(101)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 99 \u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 100 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m-> 101 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mt_radiative\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 102 \u001b[0;31m \u001b[0mlambda_wien_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstants\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb_wien\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 103 \u001b[0;31m self._t_radiative = constants.b_wien / (lambda_wien_inner * (\n", - "\u001b[0m\n", - "ipdb> n\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(106)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 104 \u001b[0;31m 1 + (self.v_middle - self.v_boundary_inner) / constants.c))\n", - "\u001b[0m\u001b[0;32m 105 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m--> 106 \u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_t_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_radiative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 107 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 108 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mdilution_factor\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> b tardis/model/base:108\n", - "Breakpoint 2 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:108\n", - "ipdb> b tardis/model/base:140\n", - "Breakpoint 3 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:140\n", - "ipdb> b tardis/model/base:132\n", - "Breakpoint 4 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:132\n", - "ipdb> c\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(108)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 106 \u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_t_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_radiative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 107 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m-> 108 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mdilution_factor\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 109 \u001b[0;31m self.dilution_factor = 0.5 * (1 - np.sqrt(\n", - "\u001b[0m\u001b[0;32m 110 \u001b[0;31m 1 - (self.r_inner[0] ** 2 / self.r_middle ** 2).to(1).value))\n", - "\u001b[0m\n", - "ipdb> self._t_radiative\n", - "<Quantity [11000., 11000., 11000., 11000., 11000., 11000., 11000., 11000.,\n", - " 11000., 11000.] K>\n", - "ipdb> exit\n" - ] - } - ], - "source": [ - "%%debug\n", - "init_trad = tardis.run_tardis('config_init_trad.yml')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Checking self.\\_t\\_radiative initialization when NO initial_t_rad at line 108\n", - "\n", - "__IMPORTANT:__ We find that len(self.\\_t\\_radiative) = 5. This is a DISCREPANCY with the YES initial_t_rad case." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NOTE: Enter 'c' at the ipdb> prompt to continue execution.\n", - "None\n", - "> \u001b[0;32m<string>\u001b[0m(2)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n", - "\n", - "ipdb> b tardis/model/base:101\n", - "Breakpoint 1 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:101\n", - "ipdb> c\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:367)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(101)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 99 \u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 100 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m-> 101 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mt_radiative\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 102 \u001b[0;31m \u001b[0mlambda_wien_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstants\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb_wien\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 103 \u001b[0;31m self._t_radiative = constants.b_wien / (lambda_wien_inner * (\n", - "\u001b[0m\n", - "ipdb> n\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(102)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 100 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m1\u001b[0;32m 101 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mt_radiative\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m--> 102 \u001b[0;31m \u001b[0mlambda_wien_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstants\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb_wien\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 103 \u001b[0;31m self._t_radiative = constants.b_wien / (lambda_wien_inner * (\n", - "\u001b[0m\u001b[0;32m 104 \u001b[0;31m 1 + (self.v_middle - self.v_boundary_inner) / constants.c))\n", - "\u001b[0m\n", - "ipdb> n\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(103)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[1;31m1\u001b[0;32m 101 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mt_radiative\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 102 \u001b[0;31m \u001b[0mlambda_wien_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstants\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb_wien\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m--> 103 \u001b[0;31m self._t_radiative = constants.b_wien / (lambda_wien_inner * (\n", - "\u001b[0m\u001b[0;32m 104 \u001b[0;31m 1 + (self.v_middle - self.v_boundary_inner) / constants.c))\n", - "\u001b[0m\u001b[0;32m 105 \u001b[0;31m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\n", - "ipdb> l\n", - "\u001b[1;32m 98 \u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;32m 99 \u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;32m 100 \u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;31m1\u001b[1;32m 101 \u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mt_radiative\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;32m 102 \u001b[0m \u001b[0mlambda_wien_inner\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstants\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb_wien\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m--> 103 \u001b[0;31m self._t_radiative = constants.b_wien / (lambda_wien_inner * (\n", - "\u001b[0m\u001b[1;32m 104 \u001b[0m 1 + (self.v_middle - self.v_boundary_inner) / constants.c))\n", - "\u001b[1;32m 105 \u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;32m 106 \u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_t_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_radiative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;32m 107 \u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[1;32m 108 \u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mdilution_factor\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\n", - "ipdb> b tardis/model/base:108\n", - "Breakpoint 2 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:108\n", - "ipdb> b tardis/model/base:140\n", - "Breakpoint 3 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:140\n", - "ipdb> b tardis/model/base:132\n", - "Breakpoint 4 at /Users/marcwilliamson/src/dev/tardis/tardis/model/base.py:132\n", - "ipdb> c\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "> \u001b[0;32m/Users/marcwilliamson/src/dev/tardis/tardis/model/base.py\u001b[0m(108)\u001b[0;36m__init__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32m 106 \u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_t_radiative\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt_radiative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 107 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[1;31m2\u001b[0;32m-> 108 \u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mdilution_factor\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0m\u001b[0;32m 109 \u001b[0;31m self.dilution_factor = 0.5 * (1 - np.sqrt(\n", - "\u001b[0m\u001b[0;32m 110 \u001b[0;31m 1 - (self.r_inner[0] ** 2 / self.r_middle ** 2).to(1).value))\n", - "\u001b[0m\n", - "ipdb> self._t_radiative\n", - "<Quantity [9464.0583115 , 9461.69144847, 9458.53747203, 9455.38559759,\n", - " 9453.02306994] K>\n", - "ipdb> exit\n" - ] - } - ], - "source": [ - "%%debug\n", - "no_init_trad = tardis.run_tardis('config_no_init_trad.yml')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## CODE CHANGE:\n", - "\n", - "We propose the following change to tardis/model/base:106\n", - "\n", - "__Line 106 Before Change:__ `self._t_radiative = t_radiative`\n", - "\n", - "__Line 106 After Change:__ `self._t_radiative = t_radiative[1:1 + self.no_of_shells]`\n", - "\n", - "t_radiative\\[0\\] corresponds to the temperature within the inner boundary, and so should be ignored. " - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/importlib/_bootstrap.py:219: QAWarning: pyne.data is not yet QA compliant.\n", - " return f(*args, **kwds)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/importlib/_bootstrap.py:219: QAWarning: pyne.material is not yet QA compliant.\n", - " return f(*args, **kwds)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.model.base \u001b[0m][\u001b[1;33mWARNING\u001b[0m] Abundances have not been normalized to 1. - normalizing (\u001b[1mbase.py\u001b[0m:367)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /Users/marcwilliamson/Research/TARDIS/tardis-refdata/atom_data/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:74)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/IPython/core/interactiveshell.py:3296: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Read Atom Data with UUID=6f7b09e887a311e7a06b246e96350010 and MD5=864f1753714343c41f99cb065710cace. (\u001b[1mbase.py\u001b[0m:184)\n", - "[\u001b[1mtardis.io.atom_data.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Non provided atomic data: synpp_refs, photoionization_data (\u001b[1mbase.py\u001b[0m:187)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/ion_population.py:63: FutureWarning: \n", - "Passing list-likes to .loc or [] with any missing label will raise\n", - "KeyError in the future, you can use .reindex() as an alternative.\n", - "\n", - "See the documentation here:\n", - "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", - " partition_function.index].dropna())\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /anaconda2/envs/tardis/lib/python3.6/site-packages/astropy/units/quantity.py:1067: AstropyDeprecationWarning: The truth value of a Quantity is ambiguous. In the future this will raise a ValueError.\n", - " AstropyDeprecationWarning)\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 1/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 6.99873e+41 erg / s Luminosity absorbed = 8.78774e+40 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11000.0 9480.001506 0.439255 0.516372\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 9464.848 K -- next t_inner 12529.122 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mpy.warnings \u001b[0m][\u001b[1;33mWARNING\u001b[0m] /Users/marcwilliamson/src/dev/tardis/tardis/plasma/properties/ion_population.py:63: FutureWarning: \n", - "Passing list-likes to .loc or [] with any missing label will raise\n", - "KeyError in the future, you can use .reindex() as an alternative.\n", - "\n", - "See the documentation here:\n", - "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", - " partition_function.index].dropna())\n", - " (\u001b[1mwarnings.py\u001b[0m:99)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 2/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.81607e+42 erg / s Luminosity absorbed = 6.48628e+40 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 9480.001506 12575.745392 0.516372 0.460796\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 12529.122 K -- next t_inner 10296.058 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 3/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 9.13387e+41 erg / s Luminosity absorbed = 1.26685e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 12575.745392 10311.711267 0.460796 0.518384\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 10296.058 K -- next t_inner 11930.539 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 4/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.49508e+42 erg / s Luminosity absorbed = 1.38767e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 10311.711267 11931.816104 0.518384 0.501568\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11930.539 K -- next t_inner 10805.487 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 5/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.06943e+42 erg / s Luminosity absorbed = 1.45352e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11931.816104 10806.647371 0.501568 0.521923\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 10805.487 K -- next t_inner 11571.347 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 6/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.33219e+42 erg / s Luminosity absorbed = 1.63948e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 10806.647371 11489.044309 0.521923 0.530125\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11571.347 K -- next t_inner 11102.402 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 7/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.14086e+42 erg / s Luminosity absorbed = 1.63206e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 1/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11489.044309 11163.609414 0.530125 0.515142\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11102.402 K -- next t_inner 11511.109 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 8/20 (\u001b[1mbase.py\u001b[0m:266)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.29957e+42 erg / s Luminosity absorbed = 1.72175e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 2/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11163.609414 11445.235326 0.515142 0.532271\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11511.109 K -- next t_inner 11182.357 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 9/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.18350e+42 erg / s Luminosity absorbed = 1.62089e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 3/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11445.235326 11107.763629 0.532271 0.539148\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11182.357 K -- next t_inner 11383.212 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 10/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.25575e+42 erg / s Luminosity absorbed = 1.74191e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 4/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11107.763629 11352.769902 0.539148 0.529162\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11383.212 K -- next t_inner 11249.393 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 11/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.20017e+42 erg / s Luminosity absorbed = 1.59589e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 5/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11352.769902 11267.543143 0.529162 0.52175\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11249.393 K -- next t_inner 11371.684 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 12/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.24238e+42 erg / s Luminosity absorbed = 1.69634e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 6/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11267.543143 11429.077116 0.52175 0.509304\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11371.684 K -- next t_inner 11298.313 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 13/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22572e+42 erg / s Luminosity absorbed = 1.70964e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 7/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11429.077116 11267.038005 0.509304 0.531961\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11298.313 K -- next t_inner 11301.467 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 14/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22675e+42 erg / s Luminosity absorbed = 1.64233e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 8/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11267.038005 11304.057113 0.531961 0.517281\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11301.467 K -- next t_inner 11299.844 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 15/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22841e+42 erg / s Luminosity absorbed = 1.63765e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 9/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11304.057113 11214.865131 0.517281 0.539284\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11299.844 K -- next t_inner 11290.591 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 16/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.21989e+42 erg / s Luminosity absorbed = 1.68821e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 10/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11214.865131 11251.931472 0.539284 0.531043\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11290.591 K -- next t_inner 11320.702 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 17/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22643e+42 erg / s Luminosity absorbed = 1.68202e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 11/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11251.931472 11227.712604 0.531043 0.545636\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11320.702 K -- next t_inner 11320.578 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 18/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22398e+42 erg / s Luminosity absorbed = 1.65226e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 12/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11227.712604 11322.952999 0.545636 0.520921\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11320.578 K -- next t_inner 11331.772 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 19/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.22450e+42 erg / s Luminosity absorbed = 1.74119e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Iteration converged 13/4 consecutive times. (\u001b[1mbase.py\u001b[0m:194)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Plasma stratification:\n", - "\t t_rad next_t_rad w next_w\n", - "\tShell \n", - "\t0 11322.952999 11343.010318 0.520921 0.523692\n", - "\n", - " (\u001b[1mbase.py\u001b[0m:348)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] t_inner 11331.772 K -- next t_inner 11340.566 K (\u001b[1mbase.py\u001b[0m:350)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 20/20 (\u001b[1mbase.py\u001b[0m:266)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 1.23739e+42 erg / s Luminosity absorbed = 1.70270e+41 erg / s Luminosity requested = 1.22640e+42 erg / s (\u001b[1mbase.py\u001b[0m:357)\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Simulation finished in 20 iterations and took 1.57 s (\u001b[1mbase.py\u001b[0m:306)\n" - ] - } - ], - "source": [ - "init_trad = tardis.run_tardis('config_init_trad.yml')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "a = np.array([1,2,3,4,5,6,7,8])" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([4, 5, 6, 7, 8])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a[3:8]" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([1, 2, 3, 4, 5, 6, 7, 8])" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "2 in a" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.argwhere(a==6)[0][0]" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "6" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.searchsorted(a, 6.5)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "if (2 in a) and (3.5 in a):\n", - " print('hi')" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "ename": "AssertionError", - "evalue": "test", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m<ipython-input-15-43ea828a8ceb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m1.2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"test\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;31mAssertionError\u001b[0m: test" - ] - } - ], - "source": [ - "assert 1==1.2, \"test\"" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([4, 5, 6])" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a[3:6]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/outdated/integrator.ipynb b/docs/outdated/integrator.ipynb deleted file mode 100644 index 6708397c631..00000000000 --- a/docs/outdated/integrator.ipynb +++ /dev/null @@ -1,1754 +0,0 @@ -{ - "cells": [ - { - "cell_type": "raw", - "metadata": { - "raw_mimetype": "text/restructuredtext" - }, - "source": [ - ".. _integrator:\n", - "\n", - "***********************************\n", - "API example for the formal integral\n", - "***********************************" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "There are currently two ways to invoke the calculation of the formal integral with tardis. The first is for the use in interactive shells and scripts and the second one for running tardis with the command line script `tardis`.\n", - "\n", - "Let's start with some common imports:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/stefan/anaconda2/envs/tardis/lib/python2.7/site-packages/IPython/kernel/__init__.py:13: ShimWarning: The `IPython.kernel` package has been deprecated since IPython 4.0.You should import from ipykernel or jupyter_client instead.\n", - " \"You should import from ipykernel or jupyter_client instead.\", ShimWarning)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Populating the interactive namespace from numpy and matplotlib\n" - ] - } - ], - "source": [ - "%pylab notebook\n", - "import tardis\n", - "from tardis.io.config_reader import Configuration\n", - "from tardis.simulation import Simulation\n", - "config_fname = tardis.__path__[0] + '/../../data/tardis_example/tardis_example_integral.yml'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We run tardis in an interactive shell the usual way. Afterwards, we can call `simulation.runner.integrator.calculate_spectrum(frequency)` to create an integrated spectrum for any list of frequencies." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /media/data/projects/tardis/tardis-code/tardis/../../data/tardis_example/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:72)\n", - "tardis.plasma.standard_plasmas - \u001b[1;37mINFO\u001b[0m - Reading Atomic Data from /media/data/projects/tardis/tardis-code/tardis/../../data/tardis_example/kurucz_cd23_chianti_H_He.h5\n", - "tardis.atomic - INFO - Read Atom Data with UUID=5ca3035ca8b311e3bb684437e69d75d7 and MD5=21095dd25faa1683f4c90c911a00c3f8\n", - "[\u001b[1mtardis.plasma.base \u001b[0m][\u001b[1;34mDEBUG\u001b[0m ] Updating modules in the following order: (\u001b[1mbase.py\u001b[0m:195)\n", - "tardis.plasma.base - \u001b[1;34mDEBUG\u001b[0m - Updating modules in the following order:\n", - "[\u001b[1mtardis.montecarlo.base\u001b[0m][\u001b[1;34mDEBUG\u001b[0m ] Electron scattering switched on (\u001b[1mbase.py\u001b[0m:411)\n", - "tardis.montecarlo.base - \u001b[1;34mDEBUG\u001b[0m - Electron scattering switched on\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 1/1 (\u001b[1mbase.py\u001b[0m:194)\n", - "tardis.simulation.base - \u001b[1;37mINFO\u001b[0m - Starting iteration 1/1\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 8.03041e+42 erg / s Luminosity absorbed = 2.57695e+42 erg / s Luminosity requested = 1.05928e+43 erg / s (\u001b[1mbase.py\u001b[0m:271)\n", - "tardis.simulation.base - \u001b[1;37mINFO\u001b[0m - Luminosity emitted = 8.03041e+42 erg / s Luminosity absorbed = 2.57695e+42 erg / s Luminosity requested = 1.05928e+43 erg / s\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Simulation finished in 1 iterations and took 0.90 s (\u001b[1mbase.py\u001b[0m:221)\n", - "tardis.simulation.base - \u001b[1;37mINFO\u001b[0m - Simulation finished in 1 iterations and took 0.90 s\n" - ] - } - ], - "source": [ - "simulation = tardis.run_tardis(config_fname);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For simplicity we use the list of frequencies defined by the configuration. We could use any other list that is a astropy Quantity which can be transformed into a frequency (e.g. a list of wavelengths in angstrom works, too).\n", - "\n", - "The integration returns a `TARDISSpectrum` instance holding variables like the luminosity_density in nu and lambda." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "wl = simulation.runner.spectrum.frequency\n", - "spectrum = simulation.runner.integrator.calculate_spectrum(wl)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here is a simple plot of the integrated spectrum (blue) in comparison with the virtual spectrum (green)." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function() {\n", - " if (typeof(WebSocket) !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof(MozWebSocket) !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert('Your browser does not have WebSocket support.' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. 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" this.image_mode = 'full';\n", - "\n", - " this.root = $('<div/>');\n", - " this._root_extra_style(this.root)\n", - " this.root.attr('style', 'display: inline-block');\n", - "\n", - " $(parent_element).append(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", - " fig.send_message(\"send_image_mode\", {});\n", - " fig.send_message(\"refresh\", {});\n", - " }\n", - "\n", - " this.imageObj.onload = function() {\n", - " if (fig.image_mode == 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " fig.waiting = false;\n", - " };\n", - "\n", - " this.imageObj.onunload = function() {\n", - " this.ws.close();\n", - " }\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "}\n", - "\n", - "mpl.figure.prototype._init_header = function() {\n", - " var titlebar = $(\n", - " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n", - " 'ui-helper-clearfix\"/>');\n", - " var titletext = $(\n", - " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n", - " 'text-align: center; padding: 3px;\"/>');\n", - " titlebar.append(titletext)\n", - " this.root.append(titlebar);\n", - " this.header = titletext[0];\n", - "}\n", - "\n", - "\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", - "\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._init_canvas = function() {\n", - " var fig = this;\n", - "\n", - " var canvas_div = $('<div/>');\n", - "\n", - " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", - "\n", - " function canvas_keyboard_event(event) {\n", - " return fig.key_event(event, event['data']);\n", - " }\n", - "\n", - " canvas_div.keydown('key_press', canvas_keyboard_event);\n", - " canvas_div.keyup('key_release', canvas_keyboard_event);\n", - " this.canvas_div = canvas_div\n", - " this._canvas_extra_style(canvas_div)\n", - " this.root.append(canvas_div);\n", - "\n", - " var canvas = $('<canvas/>');\n", - " canvas.addClass('mpl-canvas');\n", - " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", - "\n", - " this.canvas = canvas[0];\n", - " this.context = canvas[0].getContext(\"2d\");\n", - "\n", - " var rubberband = $('<canvas/>');\n", - " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", - "\n", - " var pass_mouse_events = true;\n", - "\n", - " canvas_div.resizable({\n", - " start: function(event, ui) {\n", - " pass_mouse_events = false;\n", - " },\n", - " resize: function(event, ui) {\n", - " fig.request_resize(ui.size.width, ui.size.height);\n", - " },\n", - " stop: function(event, ui) {\n", - " pass_mouse_events = true;\n", - " fig.request_resize(ui.size.width, ui.size.height);\n", - " },\n", - " });\n", - "\n", - " function mouse_event_fn(event) {\n", - " if (pass_mouse_events)\n", - " return fig.mouse_event(event, event['data']);\n", - " }\n", - "\n", - " rubberband.mousedown('button_press', mouse_event_fn);\n", - " rubberband.mouseup('button_release', mouse_event_fn);\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband.mousemove('motion_notify', mouse_event_fn);\n", - "\n", - " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", - " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", - "\n", - " canvas_div.on(\"wheel\", function (event) {\n", - " event = event.originalEvent;\n", - " event['data'] = 'scroll'\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " mouse_event_fn(event);\n", - " });\n", - "\n", - " canvas_div.append(canvas);\n", - " canvas_div.append(rubberband);\n", - "\n", - " this.rubberband = rubberband;\n", - " this.rubberband_canvas = rubberband[0];\n", - " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", - " this.rubberband_context.strokeStyle = \"#000000\";\n", - "\n", - " this._resize_canvas = function(width, height) {\n", - " // Keep the size of the canvas, canvas container, and rubber band\n", - " // canvas in synch.\n", - " canvas_div.css('width', width)\n", - " canvas_div.css('height', height)\n", - "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", - "\n", - " rubberband.attr('width', width);\n", - " rubberband.attr('height', height);\n", - " }\n", - "\n", - " // Set the figure to an initial 600x600px, this will subsequently be updated\n", - " // upon first draw.\n", - " this._resize_canvas(600, 600);\n", - "\n", - " // Disable right mouse context menu.\n", - " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", - " return false;\n", - " });\n", - "\n", - " function set_focus () {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "}\n", - "\n", - "mpl.figure.prototype._init_toolbar = function() {\n", - " var fig = this;\n", - "\n", - " var nav_element = $('<div/>')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " // put a spacer in here.\n", - " continue;\n", - " }\n", - " var button = $('<button/>');\n", - " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n", - " 'ui-button-icon-only');\n", - " button.attr('role', 'button');\n", - " button.attr('aria-disabled', 'false');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - "\n", - " var icon_img = $('<span/>');\n", - " icon_img.addClass('ui-button-icon-primary ui-icon');\n", - " icon_img.addClass(image);\n", - " icon_img.addClass('ui-corner-all');\n", - "\n", - " var tooltip_span = $('<span/>');\n", - " tooltip_span.addClass('ui-button-text');\n", - " tooltip_span.html(tooltip);\n", - "\n", - " button.append(icon_img);\n", - " button.append(tooltip_span);\n", - "\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " var fmt_picker_span = $('<span/>');\n", - "\n", - " var fmt_picker = $('<select/>');\n", - " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n", - " fmt_picker_span.append(fmt_picker);\n", - " nav_element.append(fmt_picker_span);\n", - " this.format_dropdown = fmt_picker[0];\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = $(\n", - " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n", - " fmt_picker.append(option)\n", - " }\n", - "\n", - " // Add hover states to the ui-buttons\n", - " $( \".ui-button\" ).hover(\n", - " function() { $(this).addClass(\"ui-state-hover\");},\n", - " function() { $(this).removeClass(\"ui-state-hover\");}\n", - " );\n", - "\n", - " var status_bar = $('<span class=\"mpl-message\"/>');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "}\n", - "\n", - "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n", - "}\n", - "\n", - "mpl.figure.prototype.send_message = function(type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "}\n", - "\n", - "mpl.figure.prototype.send_draw_message = function() {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n", - " }\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype.handle_resize = function(fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1]);\n", - " fig.send_message(\"refresh\", {});\n", - " };\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0, 0, fig.canvas.width, fig.canvas.height);\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch(cursor)\n", - " {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_message = function(fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_draw = function(fig, msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "}\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function() {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message(\"ack\", {});\n", - "}\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function(fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = \"image/png\";\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src);\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data);\n", - " fig.updated_canvas_event();\n", - " return;\n", - " }\n", - " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig[\"handle_\" + msg_type];\n", - " } catch (e) {\n", - " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n", - " }\n", - " }\n", - " };\n", - "}\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function(e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e)\n", - " e = window.event;\n", - " if (e.target)\n", - " targ = e.target;\n", - " else if (e.srcElement)\n", - " targ = e.srcElement;\n", - " if (targ.nodeType == 3) // defeat Safari bug\n", - " targ = targ.parentNode;\n", - "\n", - " // jQuery normalizes the pageX and pageY\n", - " // pageX,Y are the mouse positions relative to the document\n", - " // offset() returns the position of the element relative to the document\n", - " var x = e.pageX - $(targ).offset().left;\n", - " var y = e.pageY - $(targ).offset().top;\n", - "\n", - " return {\"x\": x, \"y\": y};\n", - "};\n", - "\n", - "mpl.figure.prototype.mouse_event = function(event, name) {\n", - " var canvas_pos = mpl.findpos(event)\n", - "\n", - " if (name === 'button_press')\n", - " {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", - "\n", - " this.send_message(name, {x: x, y: y, button: event.button,\n", - " step: event.step});\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "}\n", - "\n", - "mpl.figure.prototype.key_event = function(event, name) {\n", - "\n", - " // Prevent repeat events\n", - " if (name == 'key_press')\n", - " {\n", - " if (event.which === this._key)\n", - " return;\n", - " else\n", - " this._key = event.which;\n", - " }\n", - " if (name == 'key_release')\n", - " this._key = null;\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which != 17)\n", - " value += \"ctrl+\";\n", - " if (event.altKey && event.which != 18)\n", - " value += \"alt+\";\n", - " if (event.shiftKey && event.which != 16)\n", - " value += \"shift+\";\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, {key: value});\n", - " return false;\n", - "}\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n", - " if (name == 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message(\"toolbar_button\", {name: name});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n", - "\n", - "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function() {\n", - " comm.close()\n", - " };\n", - " ws.send = function(m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function(msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overriden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data'])\n", - " });\n", - " return ws;\n", - "}\n", - "\n", - "mpl.mpl_figure_comm = function(comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = $(\"#\" + id);\n", - " var ws_proxy = comm_websocket_adapter(comm)\n", - "\n", - " function ondownload(figure, format) {\n", - " window.open(figure.imageObj.src);\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy,\n", - " ondownload,\n", - " element.get(0));\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element.get(0);\n", - " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n", - " if (!fig.cell_info) {\n", - " console.error(\"Failed to find cell for figure\", id, fig);\n", - " return;\n", - " }\n", - "\n", - " var output_index = fig.cell_info[2]\n", - " var cell = fig.cell_info[0];\n", - "\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function(fig, msg) {\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n", - " fig.send_message('closing', {});\n", - " fig.ws.close()\n", - "}\n", - "\n", - "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n", - "}\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function() {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message(\"ack\", {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () { fig.push_to_output() }, 1000);\n", - "}\n", - "\n", - "mpl.figure.prototype._init_toolbar = function() {\n", - " var fig = this;\n", - "\n", - " var nav_element = $('<div/>')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items){\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) { continue; };\n", - "\n", - " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n", - " var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n", - " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", - " button.mouseover('Close figure', toolbar_mouse_event);\n", - " buttongrp.append(button);\n", - " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", - " titlebar.prepend(buttongrp);\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(el){\n", - " // this is important to make the div 'focusable\n", - " el.attr('tabindex', 0)\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " }\n", - " else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager)\n", - " manager = IPython.keyboard_manager;\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which == 13) {\n", - " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", - " }\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " fig.ondownload(fig, null);\n", - "}\n", - "\n", - "\n", - "mpl.find_output_cell = function(html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i=0; i<ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code'){\n", - " for (var j=0; j<cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] == html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "}\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel != null) {\n", - " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", - "}\n" - ], - "text/plain": [ - "<IPython.core.display.Javascript object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "<img 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\">" - ], - "text/plain": [ - "<IPython.core.display.HTML object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = figure()\n", - "ax = plt.gca()\n", - "spectrum.plot(ax)\n", - "simulation.runner.spectrum_virtual.plot(ax)\n", - "fig.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "When running the command line script, we can control the type of spectrum that is written to txt with the `method` option of the `spectrum` setting in the YAML. If omitted, the default value is 'virtual', however it can be set to 'real' for the spectrum of the real packets, or to 'integrated' for a spectrum from the formal integral approach.\n", - "\n", - "Here we verify our method for the spectral generation is 'integrated'." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'method': 'integrated',\n", - " 'num': 10000,\n", - " 'start': <Quantity 500.0 Angstrom>,\n", - " 'stop': <Quantity 20000.0 Angstrom>}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "config = Configuration.from_yaml(config_fname)\n", - "config['spectrum']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Afterwards we run the tardis script in the shell and save the spectrum to /tmp/tardis_spec.txt" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\u001b[1mtardis.plasma.standard_plasmas\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Reading Atomic Data from /media/data/projects/tardis/tardis-code/tardis/../../data/tardis_example/kurucz_cd23_chianti_H_He.h5 (\u001b[1mstandard_plasmas.py\u001b[0m:72)\n", - "tardis.plasma.standard_plasmas - \u001b[1;37mINFO\u001b[0m - Reading Atomic Data from /media/data/projects/tardis/tardis-code/tardis/../../data/tardis_example/kurucz_cd23_chianti_H_He.h5\n", - "tardis.atomic - INFO - Read Atom Data with UUID=5ca3035ca8b311e3bb684437e69d75d7 and MD5=21095dd25faa1683f4c90c911a00c3f8\n", - "[\u001b[1mtardis.plasma.base \u001b[0m][\u001b[1;34mDEBUG\u001b[0m ] Updating modules in the following order: (\u001b[1mbase.py\u001b[0m:195)\n", - "tardis.plasma.base - \u001b[1;34mDEBUG\u001b[0m - Updating modules in the following order:\n", - "[\u001b[1mtardis.montecarlo.base\u001b[0m][\u001b[1;34mDEBUG\u001b[0m ] Electron scattering switched on (\u001b[1mbase.py\u001b[0m:411)\n", - "tardis.montecarlo.base - \u001b[1;34mDEBUG\u001b[0m - Electron scattering switched on\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Starting iteration 1/1 (\u001b[1mbase.py\u001b[0m:194)\n", - "tardis.simulation.base - \u001b[1;37mINFO\u001b[0m - Starting iteration 1/1\n", - "Running with OpenMP - 4 threads\n", - "\u001b[2K\t[100%] Packets(finished/total): 10000/10000\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Luminosity emitted = 8.03041e+42 erg / s Luminosity absorbed = 2.57695e+42 erg / s Luminosity requested = 1.05928e+43 erg / s (\u001b[1mbase.py\u001b[0m:271)\n", - "tardis.simulation.base - \u001b[1;37mINFO\u001b[0m - Luminosity emitted = 8.03041e+42 erg / s Luminosity absorbed = 2.57695e+42 erg / s Luminosity requested = 1.05928e+43 erg / s\n", - "[\u001b[1mtardis.simulation.base\u001b[0m][\u001b[1;37mINFO\u001b[0m ] Simulation finished in 1 iterations and took 1.05 s (\u001b[1mbase.py\u001b[0m:221)\n", - "tardis.simulation.base - \u001b[1;37mINFO\u001b[0m - Simulation finished in 1 iterations and took 1.05 s\n", - "Saving the integrated spectrum.\n", - "Doing the formal integral with 4 threads\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n" - ] - } - ], - "source": [ - "!tardis $config_fname /tmp/tardis_spec.txt" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally we plot the result and verify, that this looks indeed how a integrated spectrum should look like (no spread due to noise). As the run was done with only 10 000 packets, one would expect significant visible noise." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function() {\n", - " if (typeof(WebSocket) !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof(MozWebSocket) !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert('Your browser does not have WebSocket support.' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.');\n", - " };\n", - "}\n", - "\n", - "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = (this.ws.binaryType != undefined);\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById(\"mpl-warnings\");\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent = (\n", - " \"This browser does not support binary websocket messages. \" +\n", - " \"Performance may be slow.\");\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = $('<div/>');\n", - " this._root_extra_style(this.root)\n", - " this.root.attr('style', 'display: inline-block');\n", - "\n", - " $(parent_element).append(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", - " fig.send_message(\"send_image_mode\", {});\n", - " fig.send_message(\"refresh\", {});\n", - " }\n", - "\n", - " this.imageObj.onload = function() {\n", - " if (fig.image_mode == 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " fig.waiting = false;\n", - " };\n", - "\n", - " this.imageObj.onunload = function() {\n", - " this.ws.close();\n", - " }\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "}\n", - "\n", - "mpl.figure.prototype._init_header = function() {\n", - " var titlebar = $(\n", - " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n", - " 'ui-helper-clearfix\"/>');\n", - " var titletext = $(\n", - " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n", - " 'text-align: center; padding: 3px;\"/>');\n", - " titlebar.append(titletext)\n", - " this.root.append(titlebar);\n", - " this.header = titletext[0];\n", - "}\n", - "\n", - "\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", - "\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._init_canvas = function() {\n", - " var fig = this;\n", - "\n", - " var canvas_div = $('<div/>');\n", - "\n", - " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", - "\n", - " function canvas_keyboard_event(event) {\n", - " return fig.key_event(event, event['data']);\n", - " }\n", - "\n", - " canvas_div.keydown('key_press', canvas_keyboard_event);\n", - " canvas_div.keyup('key_release', canvas_keyboard_event);\n", - " this.canvas_div = canvas_div\n", - " this._canvas_extra_style(canvas_div)\n", - " this.root.append(canvas_div);\n", - "\n", - " var canvas = $('<canvas/>');\n", - " canvas.addClass('mpl-canvas');\n", - " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", - "\n", - " this.canvas = canvas[0];\n", - " this.context = canvas[0].getContext(\"2d\");\n", - "\n", - " var rubberband = $('<canvas/>');\n", - " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", - "\n", - " var pass_mouse_events = true;\n", - "\n", - " canvas_div.resizable({\n", - " start: function(event, ui) {\n", - " pass_mouse_events = false;\n", - " },\n", - " resize: function(event, ui) {\n", - " fig.request_resize(ui.size.width, ui.size.height);\n", - " },\n", - " stop: function(event, ui) {\n", - " pass_mouse_events = true;\n", - " fig.request_resize(ui.size.width, ui.size.height);\n", - " },\n", - " });\n", - "\n", - " function mouse_event_fn(event) {\n", - " if (pass_mouse_events)\n", - " return fig.mouse_event(event, event['data']);\n", - " }\n", - "\n", - " rubberband.mousedown('button_press', mouse_event_fn);\n", - " rubberband.mouseup('button_release', mouse_event_fn);\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband.mousemove('motion_notify', mouse_event_fn);\n", - "\n", - " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", - " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", - "\n", - " canvas_div.on(\"wheel\", function (event) {\n", - " event = event.originalEvent;\n", - " event['data'] = 'scroll'\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " mouse_event_fn(event);\n", - " });\n", - "\n", - " canvas_div.append(canvas);\n", - " canvas_div.append(rubberband);\n", - "\n", - " this.rubberband = rubberband;\n", - " this.rubberband_canvas = rubberband[0];\n", - " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", - " this.rubberband_context.strokeStyle = \"#000000\";\n", - "\n", - " this._resize_canvas = function(width, height) {\n", - " // Keep the size of the canvas, canvas container, and rubber band\n", - " // canvas in synch.\n", - " canvas_div.css('width', width)\n", - " canvas_div.css('height', height)\n", - "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", - "\n", - " rubberband.attr('width', width);\n", - " rubberband.attr('height', height);\n", - " }\n", - "\n", - " // Set the figure to an initial 600x600px, this will subsequently be updated\n", - " // upon first draw.\n", - " this._resize_canvas(600, 600);\n", - "\n", - " // Disable right mouse context menu.\n", - " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", - " return false;\n", - " });\n", - "\n", - " function set_focus () {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "}\n", - "\n", - "mpl.figure.prototype._init_toolbar = function() {\n", - " var fig = this;\n", - "\n", - " var nav_element = $('<div/>')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " // put a spacer in here.\n", - " continue;\n", - " }\n", - " var button = $('<button/>');\n", - " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n", - " 'ui-button-icon-only');\n", - " button.attr('role', 'button');\n", - " button.attr('aria-disabled', 'false');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - "\n", - " var icon_img = $('<span/>');\n", - " icon_img.addClass('ui-button-icon-primary ui-icon');\n", - " icon_img.addClass(image);\n", - " icon_img.addClass('ui-corner-all');\n", - "\n", - " var tooltip_span = $('<span/>');\n", - " tooltip_span.addClass('ui-button-text');\n", - " tooltip_span.html(tooltip);\n", - "\n", - " button.append(icon_img);\n", - " button.append(tooltip_span);\n", - "\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " var fmt_picker_span = $('<span/>');\n", - "\n", - " var fmt_picker = $('<select/>');\n", - " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n", - " fmt_picker_span.append(fmt_picker);\n", - " nav_element.append(fmt_picker_span);\n", - " this.format_dropdown = fmt_picker[0];\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = $(\n", - " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n", - " fmt_picker.append(option)\n", - " }\n", - "\n", - " // Add hover states to the ui-buttons\n", - " $( \".ui-button\" ).hover(\n", - " function() { $(this).addClass(\"ui-state-hover\");},\n", - " function() { $(this).removeClass(\"ui-state-hover\");}\n", - " );\n", - "\n", - " var status_bar = $('<span class=\"mpl-message\"/>');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "}\n", - "\n", - "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n", - "}\n", - "\n", - "mpl.figure.prototype.send_message = function(type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "}\n", - "\n", - "mpl.figure.prototype.send_draw_message = function() {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n", - " }\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype.handle_resize = function(fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1]);\n", - " fig.send_message(\"refresh\", {});\n", - " };\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0, 0, fig.canvas.width, fig.canvas.height);\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch(cursor)\n", - " {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_message = function(fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_draw = function(fig, msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "}\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function() {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message(\"ack\", {});\n", - "}\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function(fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = \"image/png\";\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src);\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data);\n", - " fig.updated_canvas_event();\n", - " return;\n", - " }\n", - " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig[\"handle_\" + msg_type];\n", - " } catch (e) {\n", - " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n", - " }\n", - " }\n", - " };\n", - "}\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function(e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e)\n", - " e = window.event;\n", - " if (e.target)\n", - " targ = e.target;\n", - " else if (e.srcElement)\n", - " targ = e.srcElement;\n", - " if (targ.nodeType == 3) // defeat Safari bug\n", - " targ = targ.parentNode;\n", - "\n", - " // jQuery normalizes the pageX and pageY\n", - " // pageX,Y are the mouse positions relative to the document\n", - " // offset() returns the position of the element relative to the document\n", - " var x = e.pageX - $(targ).offset().left;\n", - " var y = e.pageY - $(targ).offset().top;\n", - "\n", - " return {\"x\": x, \"y\": y};\n", - "};\n", - "\n", - "mpl.figure.prototype.mouse_event = function(event, name) {\n", - " var canvas_pos = mpl.findpos(event)\n", - "\n", - " if (name === 'button_press')\n", - " {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", - "\n", - " this.send_message(name, {x: x, y: y, button: event.button,\n", - " step: event.step});\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "}\n", - "\n", - "mpl.figure.prototype.key_event = function(event, name) {\n", - "\n", - " // Prevent repeat events\n", - " if (name == 'key_press')\n", - " {\n", - " if (event.which === this._key)\n", - " return;\n", - " else\n", - " this._key = event.which;\n", - " }\n", - " if (name == 'key_release')\n", - " this._key = null;\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which != 17)\n", - " value += \"ctrl+\";\n", - " if (event.altKey && event.which != 18)\n", - " value += \"alt+\";\n", - " if (event.shiftKey && event.which != 16)\n", - " value += \"shift+\";\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, {key: value});\n", - " return false;\n", - "}\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n", - " if (name == 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message(\"toolbar_button\", {name: name});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n", - "\n", - "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function() {\n", - " comm.close()\n", - " };\n", - " ws.send = function(m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function(msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overriden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data'])\n", - " });\n", - " return ws;\n", - "}\n", - "\n", - "mpl.mpl_figure_comm = function(comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = $(\"#\" + id);\n", - " var ws_proxy = comm_websocket_adapter(comm)\n", - "\n", - " function ondownload(figure, format) {\n", - " window.open(figure.imageObj.src);\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy,\n", - " ondownload,\n", - " element.get(0));\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element.get(0);\n", - " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n", - " if (!fig.cell_info) {\n", - " console.error(\"Failed to find cell for figure\", id, fig);\n", - " return;\n", - " }\n", - "\n", - " var output_index = fig.cell_info[2]\n", - " var cell = fig.cell_info[0];\n", - "\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function(fig, msg) {\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n", - " fig.send_message('closing', {});\n", - " fig.ws.close()\n", - "}\n", - "\n", - "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n", - "}\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function() {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message(\"ack\", {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () { fig.push_to_output() }, 1000);\n", - "}\n", - "\n", - "mpl.figure.prototype._init_toolbar = function() {\n", - " var fig = this;\n", - "\n", - " var nav_element = $('<div/>')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items){\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) { continue; };\n", - "\n", - " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n", - " var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n", - " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", - " button.mouseover('Close figure', toolbar_mouse_event);\n", - " buttongrp.append(button);\n", - " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", - " titlebar.prepend(buttongrp);\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(el){\n", - " // this is important to make the div 'focusable\n", - " el.attr('tabindex', 0)\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " }\n", - " else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager)\n", - " manager = IPython.keyboard_manager;\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which == 13) {\n", - " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", - " }\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " fig.ondownload(fig, null);\n", - "}\n", - "\n", - "\n", - "mpl.find_output_cell = function(html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i=0; i<ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code'){\n", - " for (var j=0; j<cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] == html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "}\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel != null) {\n", - " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", - "}\n" - ], - "text/plain": [ - "<IPython.core.display.Javascript object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "<img 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\">" - ], - "text/plain": [ - "<IPython.core.display.HTML object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "wl, lum = np.loadtxt('/tmp/tardis_spec.txt', unpack=True);\n", - "figure()\n", - "plot(wl, lum);" - ] - } - ], - "metadata": { - "celltoolbar": "Raw Cell Format", - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.8" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/docs/outdated/old_gui.rst b/docs/outdated/old_gui.rst deleted file mode 100644 index 322c203bd9f..00000000000 --- a/docs/outdated/old_gui.rst +++ /dev/null @@ -1,125 +0,0 @@ -*************************************** -Old Graphical User Interface (Outdated) -*************************************** - -TARDIS uses the `PyQt5 framework <http://www.riverbankcomputing.com/software/pyqt/download5>`_ for its cross-platform -interface. - - - -This module can be imported inside IPython console or Jupyter Notebook. The console provides the event loop and the place -to create/calculate the tardis model. So the module is basically a tool to visualize results. - -**To setup and run the GUI (under development) follow these steps:** - -The GUI can use one of two python bindings for qt, namely PyQt5 -and PySide2. You can choose which binding is used by setting the -environment variable QT_API in your bash. Currently, the TARDIS team uses PyQT5. - -**1**. Installing required packages - -PyQt is installed by default in the tardis enviroment (see installation). -To use PySide2: - -.. code-block:: shell - - conda activate tardis - conda install pyside2 -c conda-forge --no-update-deps - - -**2**. Choosing between PySide2 and PyQt5 - -.. code-block:: shell - - #To choose PySide - export QT_API=pyside - - #To choose PyQt - this is what the TARDIS team does - export QT_API=pyqt - -**3**. An example of creating a model and GUI - -First, get the example file `tardis_example.yml <https://raw.githubusercontent.com/tardis-sn/tardis/master/docs/using/components/models/examples/tardis_example.yml>`_. - -To download a copy of the atomic database (if you haven't already), add: - - -.. code-block:: python - - from tardis.io.atom_data.util import download_atom_data - download_atom_data('kurucz_cd23_chianti_H_He') - -To show the GUI from a Jupyter Notebook, use the following commands: - - -.. code-block:: python - - from tardis import run_tardis - from tardis.gui import interface - sim = run_tardis('tardis_example.yml', 'kurucz_cd23_chianti_H_He.h5') - - interface.show(sim) - -If you just want to run from a configuration file and show the results, you can -do that outside the Jupyter notebook. Navigate to the folder where you -installed TARDIS, go to tardis/tardis/gui, and use the following command. - -.. code-block:: none - - python interface.py path-to-yaml-configuration-file path-to-atomic-data-file - - - -Running Instructions --------------------- -Decide which Qt binding you want to use (PySide or PyQt) and -accordingly set QT_API in shell:: - - export QT_API=pyside - or: - export QT_API=pyqt - -Start the IPython console with eventloop integration:: - - ipython - -Display your model:: - - from tardis import run_tardis - mdl = run_tardis('tardis_example.yml','kurucz_cd23_chianti_H_He.h5') - from tardis.gui import interface - interface.show(mdl) - -(WIP) You can also run a configuration from the shell. To do this, first set -QT_API in the shell. Next, navigate to the TARDIS installation folder and go to -tardis/tardis/gui. Then use the command:: - - python interface.py path-to-configuration-file path-to-atomic-data-file - -GUI Layout and Features ------------------------ -When you launch the GUI, the first screen that you see will be something like the snapshot below. -You can inspect the plot of shells on this window and use the toggle button to change between the -plot of dilution factor and the radiation temperature in shells. - -.. image:: ../io/images/OpeningScreen.png - :width: 900 - -Shell Info -~~~~~~~~~~ -To see the abundances in a shell, double-click on the shell number in the table. You can follow a -similar strategy in the tables that appear to bring up the ion and level populations for each shell. -The snapshot below shows all the tables that you can bring up by successively clicking the horizontal -table headers. This feature is not supported at the moment. - -.. image:: ../io/images/ShellInfo.png - :width: 900 - -Line Info -~~~~~~~~~ -If you switch to the spectrum tab, you can see the spectrum plot and a button to show line info. -Once again, you can double-click the table headers to get further information. The snapshot below -shows all the tables that you can bring up in this window. This feature is not supported at the moment. - -.. image:: ../io/images/LineInfo.png - :width: 900 diff --git a/docs/outdated/old_install.rst b/docs/outdated/old_install.rst deleted file mode 100644 index 26bbea58ef5..00000000000 --- a/docs/outdated/old_install.rst +++ /dev/null @@ -1,56 +0,0 @@ -************************** -Outdated Installation FAQs -************************** - -We highly encourage with any installation problems to try the recommended install -method because this often fixes problems. Here are some common problems when -installing and their fixes: - -**Problem:** While building TARDIS via ``python setup.py`` build you -may encounter the following error:: - - error: tardis/montecarlo/montecarlo.c: Could not find C file tardis/montecarlo/montecarlo.c for Cython file tardis/montecarlo/montecarlo.pyx when building extension tardis.montecarlo.montecarlo. Cython must be installed to build from a git checkout. - - -**Solution:** There are several solutions to this problem. A clean checkout will -help. To clean up your repository please try ``python setup.py clean`` and -then ``git clean -dfx`` (**WARNING** will delete any non-TARDIS file in that directory) -This will often clean this problem. If it still persists: - -Go into the tardis/montecarlo directory and build montecarlo.c by hand:: - - cython montecarlo.pyx - -Then, ``python setup.py build`` should run without problems. - - -**Problem:** when trying to set up CC=gcc python setup.py develop --with-openmp the following error popped up: -from tardis/_compiler.c:1: /Users/yssavo/miniconda2/envs/tardis-show2/lib/gcc/x86_64-apple-darwin13.4.0/5.2.0/include-fixed/limits.h:168:61: fatal error: limits.h: No such file or directory - -**Solution:** Run on terminal: - - open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10.14.pkg - -**Problem:** Symbol not found: _GOMP_parallel when compiling with `--with-openmp` - -**Solution:** Install gcc8 from macports and then install with these flags: `link_args = ['-fopenmp','-Wl,-rpath,/opt/local/lib/gcc8/']` - -**Problem:** While building TARDIS (via python 2.7) via ``python setup.py`` build you -may encounter the following error:: - - TypeError: super() argument 1 must be type, not None - - ---------------------------------------- - Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-req-build-wPB39p/ - - -**Solution:** The cause for this problem is Sphinx or Sphinx version. It can be easily solved by installing Sphinx 1.5.6. - The command for the same is : - - pip install sphinx==1.5.6 - - or - - conda install sphinx==1.5.6 - -Then, ``python setup.py build install`` should run without problems. diff --git a/docs/outdated/openmp.rst b/docs/outdated/openmp.rst deleted file mode 100644 index 97f191712ff..00000000000 --- a/docs/outdated/openmp.rst +++ /dev/null @@ -1,26 +0,0 @@ -****************************** -Parallel execution with OpenMP -****************************** - -.. note:: TARDIS no longer uses C, and thus OpenMP is not relevant to TARDIS. - -Enabling parallel execution with OpenMP -======================================== - -Manually, cloning the repository enables other options such as running the code in parallel (enabling OpenMP). -In general, we encourage downloading the compilers from `conda` as we then can ensure that they work with TARDIS. -Within the TARDIS conda environment do:: - - conda install -c conda-forge compilers - -For macOS:: - - conda install -c conda-forge llvm-openmp - -For Linux:: - - conda install -c conda-forge openmp - -To compile TARDIS for parallel execution:: - - python setup.py install --with-openmp \ No newline at end of file diff --git a/docs/outdated/using_formal_integral.rst b/docs/outdated/using_formal_integral.rst deleted file mode 100644 index 7c03d44ded7..00000000000 --- a/docs/outdated/using_formal_integral.rst +++ /dev/null @@ -1,28 +0,0 @@ -************************************************** -Spectral Synthesis with the Formal Integral Method -************************************************** - -In addition to generating the final Monte Carlo spectrum from the population of -Monte Carlo packets and the implemented variant of the "peeling-off" technique -(see :ref:`virtual_packets`), TARDIS supports spectral synthesis with -so-called formal integral method by :cite:`Lucy1999a` (see a detailed -description of the method at :ref:`formal_integral`) - -Using the Formal Integral Method -================================ - -The formal integral spectral synthesis mode is activated by setting the - -.. code-block:: none - - method: integrated - -configuration option in the ``spectrum`` block of the yml file. - -Note that the integrated spectrum (``simulation.runner.spectrum_integrated``) -is a lazy property so it will be only generated (and then cached) once it is -accessed. The spectrum integration routine is Open-MP parallelized, so this -process may be significantly sped-up if TARDIS is built with the -``--with-openmp`` option and more then one thread is used. More instructions on -how to enable parallelisation of the code is given in the :ref:`parallelization` -section. diff --git a/docs/physics/est_and_conv/convergence.rst b/docs/physics/est_and_conv/convergence.rst deleted file mode 100644 index b11a98dfb85..00000000000 --- a/docs/physics/est_and_conv/convergence.rst +++ /dev/null @@ -1,7 +0,0 @@ -.. _convergence: - -*********** -Convergence -*********** - -Coming soon. \ No newline at end of file diff --git a/docs/physics/est_and_conv/estimators.rst b/docs/physics/est_and_conv/estimators.rst deleted file mode 100644 index 7a44735ce40..00000000000 --- a/docs/physics/est_and_conv/estimators.rst +++ /dev/null @@ -1,113 +0,0 @@ -.. _estimators: - -*********************************** -Volume-based Monte Carlo Estimators -*********************************** - -An integral part of Monte Carlo radiative transfer calculations consists of -reconstructing macroscopic radiation field properties from the ensemble of -packet interaction histories. TARDIS uses volume-based Monte Carlo estimators -for this purpose. This concept was originally developed by :cite:`Lucy1999` and -successively refined, for example, by :cite:`Lucy1999a`, :cite:`Lucy2002` and -:cite:`Lucy2003`. - -Basic Principle -=============== - -The basic principle underlying volume-based estimators is best illustrated -by the example of reconstructing the mean radiation field energy density within -a certain control volume (in most cases, this will be a grid cell). A simple -approach would involve explicitly counting the number of Monte Carlo packets -which reside in the control volume at a certain time. Although being intuitive, -this approach suffers heavily from Monte Carlo shot noise, in particular in -situations in which only few (or even zero) packets reside in the control -volume when performing the counting. - -The volume-based estimator approach addresses this weakness. It considers a -certain time interval :math:`\Delta t` and accounts for all packets which at -any point during the control interval resided in the control volume. Each -packet then contributes to the total time and volume-averaged radiation field -energy density according to its energy weighted by the time it spent in the -control volume :math:`\delta t` relative to the control interval :math:`\Delta -t`: - -.. math:: - - E = \frac{1}{\Delta V} \sum_i \varepsilon_i \frac{\delta t_i}{\Delta t} - -This may be turned into the following estimator involving the trajectory -segment lengths :math:`l_i` - -.. math:: - - E = \frac{1}{c \Delta V \Delta t} \sum_i \varepsilon_i l_i - -by exploiting :math:`l_i = \delta t_i c`. Compared to the simple counting -approach, the volume-based estimator will yield non-zero results as long as at -least one packet passed through the control volume. Additionally, as one packet -may generally contribute multiple times to the estimator (e.g. if it is -deflected by a scattering), these estimators typically suffer from less Monte -Carlo noise than simple counting reconstruction schemes. - -Volume-based Estimators in TARDIS -================================= - -Within TARDIS, volume-based estimators are used to reconstruct the mean -intensity and the mean frequency of the radiation field (see also -:cite:`Kerzendorf2014`). An estimator for the former is easily formulated by -using the fundamental relation :math:`J = \frac{c}{4\pi} E` and the energy density -estimator derived above: - -.. math:: - - J = \frac{1}{4\pi \Delta V \Delta t}\sum_i \varepsilon_i l_i D_{\mu} - -An intensity-weighted estimate for the mean frequency is obtained from - -.. math:: - - \bar \nu = \frac{1}{4\pi \Delta V \Delta t}\sum_i \varepsilon_i \nu_i l_i D_{\mu}. - -.. note:: - - Compared to the estimators derived in the previous section, the ones - presented here involve a relativistic factor, :math:`D_{\mu} = (1 - \beta - \mu)`, which ensures the correct frame transformation behaviour of the - estimators (to first order in :math:`v/c`). - - -Using the estimators just derived the radiation temperature (which should be -interpreted as a colour temperature) of the radiation field, - -.. math:: - - T_{\mathrm{R}} = \frac{h}{k_{\mathrm{B}}} \frac{\pi^4}{360 \zeta(5)} \frac{\bar \nu}{J} - -may be derived. The normalization constants, involving Riemann's zeta function, -are a consequence from the definition of this colour temperature: This should -be the temperature of a black-body radiation field whose mean frequency is -equal to the one reconstructed from the Monte Carlo simulation. With the -temperature determined, the dilution factor, describing the deviation of the -radiation field from a thermal field with the same colour temperature may be calculated - -.. math:: - - W = \frac{\pi J}{\sigma_{\mathrm{R}} T_{\mathrm{R}}^4} - - -These two quantities, :math:`T_{\mathrm{R}}` and :math:`W` are vital for the -calculation of the plasma state of the ejecta (see :ref:`plasma_calculations`). - -Finally, TARDIS also reconstructs the mean intensity of the radiation field in -the blue wing of each line transition :math:`l \rightarrow u`, which is used in -the Macro Atom treatment and in the ionisation calculation. - -.. math:: - - J_{lu}^b = \frac{1}{4\pi \Delta V \Delta t} \frac{t_{\mathrm{exp}}}{c} \sum_i \frac{\varepsilon_i}{\nu_{lu}} D_{\mu}. - -The summation here only involves packets which passed through the Sobolev point -(see :ref:`Propagation <propagation>`) of the transition. For a derivation of this -estimator, in particular, for a motivation of the expansion factor involving -the time since explosion :math:`t_{\mathrm{exp}}`, we refer to -:cite:`Lucy2003`, section 6.2. diff --git a/docs/physics/est_and_conv/index.rst b/docs/physics/est_and_conv/index.rst deleted file mode 100644 index 12efba92450..00000000000 --- a/docs/physics/est_and_conv/index.rst +++ /dev/null @@ -1,32 +0,0 @@ -.. _est_and_conv: - -************************** -Estimators and Convergence -************************** - -As light travels through a real plasma, it has effects on the properties of the plasma due to light-matter -interactions as well as the presence of extra energy from the light. Additionally, as :ref:`previously discussed -<propagation>`, properties of the plasma affect how light travels through it. Things like this (where two things -both affect each other on different ways) frequently occur in physics. The solution is finding a steady-state for -the plasma properties; that is, the actual plasma will be in a state such that the plasma state will not change as -light propagates through it, because the effects of the light on the plasma and the effects of the plasma on the -light have been "balanced out." - -One of TARDIS's main goals is to determine this plasma state (as we need the actual plasma properties in order to -get an accurate spectrum). This is done in an iterative process. After each :ref:`Monte Carlo iteration -<montecarlo>` (which sends light through the supernova ejecta), TARDIS uses objects called estimators to determine -how the propagating light affects the plasma state, after which the plasma state is updated (as will be demonstrated -in the estimators page linked below). We do this many times, and attempt to have the plasma state converge -to the steady-state we are looking for. In fact, all but the last Monte Carlo iteration is used for this purpose -(after which TARDIS will have the needed plasma state for its last iteration which calculates the spectrum). - -.. note:: - For all but the last iteration, TARDIS uses the number of Monte Carlo packets specified in the - :ref:`configuration file <montecarlo-config>` under the ``no_of_packets`` argument. 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First, the TARDIS simulation is set up (:doc:`../setup/index`) from a TARDIS configuration (see :doc:`here <../../io/configuration/tutorial_read_configuration>` for how the configuration is created). This involves the creation of the supernova model and the initial conditions of the supernova's plasma, as well as initializing the Monte Carlo transport. Next is the Monte Carlo Iteration (:doc:`../montecarlo/index`) where the heart of TARDIS takes place; packets of light are sent through the supernova and tracked as they interact with matter. Next, TARDIS uses information from the Monte Carlo iteration to update properties of the plasma to eventually find the correct plasma state (:doc:`../update_and_conv/update_and_conv`). This process of doing a Monte Carlo iteration and then updating the plasma is repeated for a specified number of times or until certain aspects of the plasma state converge (as is also discussed in :doc:`../update_and_conv/update_and_conv`). After that, data generated in the Monte Carlo simulation is used to synthesize the output spectrum of the supernova (:doc:`../spectrum/index`). + +In the diagram, each physics step is shown in a box with the name of the step (bolded and underlined) along with the method that triggers the step (italicized) and the major components of the step. The reading of the configuration and the overall iterative process (comprising the Monte Carlo Iteration step and Updating Plasma and Convergence step) are also shown, again with the methods triggering these processes in italics. + +.. graphviz:: tardis_flowchart.dot + + +Background Material +=================== + +TARDIS is home to an incredibly diverse, multidisciplinary team. As such, we believe that it is important to make an understanding of the physics of TARDIS accessible to all, from students just getting started with physics and astronomy to expert researchers. The following pages are designed to give an overview of the basic physics that TARDIS relies upon to new students or anyone else in need of a refresher! + +.. toctree:: + light_and_matter diff --git a/docs/physics/intro/light_and_matter.rst b/docs/physics/intro/light_and_matter.rst new file mode 100644 index 00000000000..2163dacb978 --- /dev/null +++ b/docs/physics/intro/light_and_matter.rst @@ -0,0 +1,125 @@ +.. _light_and_matter: + +************************************ +Light, Matter, and How They Interact +************************************ + +Given that TARDIS tracks light as it travels through the ejecta of a supernova, one of the most fundamental pieces of physics used in TARDIS is what light and matter are, and how they interact. + + +Light +===== + +In the early 1900s, it was `shown <https://webs.morningside.edu/slaven/Physics/uncertainty/uncertainty2.html>`_ that light exhibits properties of both particles and waves. Like a particle, light comes in discrete units called photons, which could be understood as the "particle of light." Light is then just a collection of photons traveling through space. These photons each have an energy and momentum like any other particle. However, like a wave, light (and thus photons) has a frequency and a wavelength. Photons can thus be thought of as discrete units of a light wave with a certain wavelength and frequency. + +The energy :math:`E` of a photon is related to its frequency :math:`\nu` by the relation + +.. math:: E = h\nu + +where :math:`h` is Planck's constant. Thus a light made up of :math:`N` photons of frequency :math:`\nu` will have a total energy of :math:`Nh\nu`. Additionally, since light travels at the "speed of light" :math:`c`, approximately 300,000,000 meters per second, basic wave mechanics tells us that the wavelength :math:`\lambda` and frequency :math:`\nu` of light/photons are related by + +.. math:: \lambda\nu=c + +and thus :math:`\nu=c/\lambda` and :math:`\lambda=c/\nu`. These relations tell us that light with a lower frequency will have a lower amount of energy per photon and a longer wavelength, and light with a higher frequency will have a higher amount of energy per photon and a shorter wavelength. + +Light can then be classified by its frequency/wavelength on the electromagnetic spectrum, shown below. To the left is light with higher energy/higher frequency/shorter wavelength, and to the right is light with lower energy/lower frequency/longer wavelength. Notice visible light as a small branch of the spectrum, which ranges from a wavelength of about 400 nm (violet) to 700 nm (red). Because red is on the lower frequency/longer wavelength side of the visible light spectrum, we say if some light has a lower frequency/longer wavelength compared to other light, it is called "redder." Conversely, because blue is on the higher frequency/shorter wavelength side of the visible light spectrum, we say if some light has a higher frequency/shorter wavelength compared to other light, it is called "bluer." + +.. figure:: images/emspectrum.jpg + + Image from https://imagine.gsfc.nasa.gov/science/toolbox/emspectrum1.html. + +.. note:: + A common unit of wavelength used in astronomy is the Angstrom (:math:`\r{A}`), which is equal to :math:`10^{-10}` meters. Visible light consists of wavelengths between 4000 and 7000 Angstroms. + + +Matter +====== + +The other main ingredient of the physics of TARDIS is matter. Strictly speaking, matter is anything that has mass and takes up space. However, in supernovae as well as in every-day life (this is no coincidence -- everything on Earth came from the remnants of supernovae), matter refers to atoms and the particles that make them up. Atoms are, in that sense, the basic building block of matter. They are composed of three particles: protons, neutrons, and electrons. The protons and neutrons are found in the center of the atom, called the nucleus, and the electrons surround the nucleus, as shown in the figure below. Note that while electrons are often shown as orbiting the nucleus, this is not strictly true (see `atomic orbitals <https://en.wikipedia.org/wiki/Atomic_orbital>`_). However, it is still a useful way to think of atoms for our purposes. + +.. figure:: images/atom.jpg + + Image from https://alevelchemistry.co.uk/notes/atomic-structure-and-periodic-table/. + +Protons are positively charged particles with a charge of one elementary charge unit (e, about :math:`1.6\times 10^{-19}` Coulombs) and a mass of one atomic mass unit (amu, about :math:`1.66\times 10^{-24}` grams). Atoms are classified into elements on the `periodic table <https://en.wikipedia.org/wiki/Periodic_table>`_, based on the number of protons. For example, an atom with one proton is Hydrogen, an atom with two protons is Helium, and so on. In this way, the number of protons determines the identity of the atom. + +Neutrons are electrically neutral particles with roughly the same mass as a proton (1 amu). Protons and neutrons are far heavier than electrons, so the total mass of an atom in atomic mass units is roughly the number of protons plus the number of neutrons. Neutrons control the stability of atoms -- for example, Helium with 2 protons and 2 neutrons, called Helium-4, is stable; while Helium with 2 protons and 3 neutrons, called Helium-5, is highly unstable. Atoms of the same type (number of protons) but different numbers of neutrons (different masses) are called **isotopes**. Unstable isotopes will decay into more stable isotopes either of the same type of atom or a different type of atom (see `radioactive decay <https://en.wikipedia.org/wiki/Radioactive_decay>`_). This decay process helps power supernovae. + +The final part of atoms, electrons, are negatively charged with a charge of -1 e, the opposite of a proton. Their mass, as previously mentioned, is very small in comparison to protons and neutrons, less than 1/1800 of an amu. The number of electrons determines the overall electrical charge of the atom. For example, helium with 2 protons and 2 electrons will have a net neutral charge, but helium with 2 protons and 3 electrons will have a net charge of -1e. Atoms with unequal numbers of protons and electrons, and thus a non-neutral electrical charge, are called **ions**. In TARDIS, we generally deal with ions with more protons than electrons, called cations, which will have an overall positive charge. The "ion number" refers to how many more protons there are than electrons -- i.e. neutral Helium with 2 protons and 2 electrons would have an ion number of 0, and Helium with 2 protons and 0 electrons, which would have a charge of +2e, has an ion number of 2. + +.. note:: + + Often in astronomy, Roman numerals are used to denote ion number. Confusingly, an ion number of 0 is denoted by ``I``, an ion number of 1 is denoted by ``II``, and so on. + +Now, the electrons that are *bound to atoms* have very particular energies that they are allowed to have -- no other energies are allowed. These are called energy levels, or simply **levels**. An energy level diagram for lithium with a single electron (lithium III, with ion number 2) is shown below. Roughly, these energy levels have to do with how far away the electron is from the nucleus; a higher energy means farther away, a lower energy means closer together. By convention, an electron infinitely far away from the nucleus has zero energy, and all others have a negative energy. + +.. figure:: images/levels.png + + Image from http://dev.physicslab.org/Document.aspx?doctype=3&filename=AtomicNuclear_EnergyLevelDiagrams.xml. + +As we will see in the following section, electrons are the main part of an atom responsible for light-matter interactions. + + +Light-Matter Interactions +========================= + +Now that we have discussed light and matter, we can focus on how the two interact. For our purposes, this occurs in three main ways: line interactions, ionization, and electron scattering. + +Excitation (bound-bound interactions) +------------------------------------- + +The first type of light-matter interaction occurs when a photon carrying some energy :math:`E` is absorbed by an electron bound to an atom at an energy level :math:`l` with energy :math:`E_l`, and the electron "jumps" to a higher energy level :math:`u` with energy :math:`E_u` (:math:`l` meaning "lower" and :math:`u` meaning "upper"), as in the diagram below. We say that the electron is **excited** from the lower to higher energy level, and that it goes through a **transition** :math:`l\rightarrow u`. For this to happen, the photon has to have an energy equal to the difference between the two energy levels involved. That is, for an electron to be excited from :math:`l` to :math:`u`, it will gain an energy :math:`E_u-E_l` and thus the photon exciting the electron must have an energy :math:`E_u-E_l` and therefore a frequency :math:`\frac{E_u-E_l}{h}`. + +An electron in a higher energy level :math:`u` can also de-excite to a lower energy level :math:`l`, *releasing* a photon of energy :math:`E_u-E_l` and frequency :math:`\frac{E_u-E_l}{h}` (this would be notated as :math:`u\rightarrow l`). Note that if an electron is excited :math:`l\rightarrow u`, it need not de-excite back to the energy level :math:`l` where it began. It could de-excite to any level with a lower energy than :math:`E_u`. + +.. figure:: images/excitation.png + + Image from http://www.pas.rochester.edu/~blackman/ast104/bohr.html. + +Since energy levels are discrete, excitation can only be caused by certain frequencies of light. Specifically, it is caused by photons with an energy that equals the difference between two electron energy levels. The various energies/frequencies allowed to cause an excitation are called atomic **lines**, and thus excitation is frequently referred to as a **line interaction**. A photon with the right frequency to induce a line interaction (i.e. for the transition :math:`l\rightarrow u` this frequency would be :math:`\frac{E_u-E_l}{h}` as before), we say that the photon **resonates** with the line. Three atomic lines are shown below, again for Lithium with a single electron, represented by arrows connecting the energy levels (specifically, these arrows show a few possible transitions :math:`u\rightarrow l`). Note that transitions between any other pair of levels are also allowed atomic lines, though they are not explicitly shown on the diagram. + +.. figure:: images/lines.png + + Image from http://dev.physicslab.org/Document.aspx?doctype=3&filename=AtomicNuclear_EnergyLevelDiagrams.xml. + +Note that these are sometimes called bound-bound interactions, since the electron starts bound to an atom and ends bound to the same atom. + +Ionization (bound-free interactions) +------------------------------------ + +The next type of interaction is called ionization. This is when a photon interacts with an electron and gives the electron enough energy to escape from the atom, as shown in the diagram below. Unlike line interactions, the final energy of the electron is not restricted to discrete energy levels since the electron is not bound to an atom. The difference in energy :math:`E_f-E_i` of the electron can be anything above the ionization energy :math:`E_\mathrm{ion}`, or the minimum energy it takes to ionize the atom. This energy can be seen as the difference between the initial energy level and the dotted line labeled "ionization" on the energy level diagrams above. So, an ionizing photon can have any frequency greater than or equal to :math:`\frac{E_\mathrm{ion}}{h}`. Note that this is called ionization because the final atom is missing an electron and is thus an ion. + +.. figure:: images/ionization.png + + Image from https://idahoaskascientist.com/2016/01/08/why-are-gamma-rays-more-harmful-than-radio-waves/. + +Ionization is also called a bound-free interaction, since the electron starts bound to an atom and ends up not bound to an atom (i.e. free). + +Note that just like with de-excitation, ionization can be "reversed" through **recombination**. This is where any free electron (not necessarily one that was ionized off the particular atom) becomes bound to an atom (recombines with the atom). The electron's energy is lowered to one of the energy levels of the atom, and a photon is released with an energy equal to the amount of energy the electron loses in the recombination process. + +Electron Scattering +------------------- + +The final type of interaction is electron scattering. This is when a photon collides with a free electron, which then, like any two particles colliding, sends the electron and the light off in different directions in accordance with the `conservation of momentum <https://www.physicsclassroom.com/class/momentum/Lesson-2/Momentum-Conservation-Principle>`_. This is shown in the diagram below. If the electron is moving far slower than the speed of light, this is called `Thomson scattering <https://en.wikipedia.org/wiki/Thomson_scattering>`_, and the wavelength, frequency, and energy of the photon remains the same before and after the collision. If the electron is moving close to the speed of light, `relativity <https://en.wikipedia.org/wiki/Special_relativity>`_ kicks in, and we have `Compton scattering <https://en.wikipedia.org/wiki/Compton_scattering>`_ in which the wavelength, frequency, and energy of the photon will change after the collision. In Thomson scattering, photons of any frequency have the same likelihood of scattering with an electron. In Compton scattering, while any photon of any frequency can scatter, the likelihood of scattering depends on the frequency of the photon. + +.. figure:: images/escat.png + + Image from https://en.wikipedia.org/w/index.php?title=File%3ACompton-scattering.svg. + + +.. _opacity: + +Opacity and Optical Depth +========================= + +Consider the following experiment -- you fill a clear glass of water completely, shine a light down on it, and look through the bottom of the glass. Then, you drink half of the cup, and repeat. The light coming out from the bottom will be brighter. This is because as light travels through the water, it has a probability of interacting with the matter that makes up the water, and the longer it travels in the water, the more likely it is for the light to interact and thus not come out the other side. + +This is described by the Beer-Lambert law, which says that the intensity :math:`I` of light (related to how bright the light is -- more on this soon) after traveling a distance :math:`d` through some material is related to the initial intensity :math:`I_0` of the light before traveling through the material by + +.. math:: \frac{I}{I_0} = e^{-\alpha d} + +where :math:`\alpha` is called the **opacity**. Note that for our purposes, the intensity at some frequency is proportional to the number of photons at that frequency, so :math:`\frac{I}{I_0}` is the fraction of photons who enter the material who do not interact and thus make it out the other side. Note that the opacity can and typically does depend on the frequency of light, which is why we frequently interpret Beer-Lambert's law as applying to a specific frequency. + +We can interpret this in the following way: prior to traveling a distance :math:`d`, a photon will have had a :math:`e^{-\alpha d}` probability of *not* interacting with matter (and thus a :math:`1-e^{-\alpha d}` probability of having gone through an interaction). As you would expect, the larger the distance, the more likely it is that a photon interacts prior to traveling that distance, since it would have "more opportunities" to interact. Additionally, a higher :math:`\alpha` means a photon has a higher likelihood of interacting. So, more dense materials, for example, have a higher :math:`\alpha` since there is more matter for the light to interact with. Because :math:`\alpha` must take into account all three types of light-matter interactions, many of which depend on the frequency of light, it can be very difficult to calculate -- this is one of TARDIS's main tasks. + +Finally, the term :math:`\alpha d` has a special name: the **optical depth** :math:`\tau`. It is a dimensionless quantity that gives information about how likely it is for a photon to have gone through an interaction. Specifically, there is a :math:`1-e^{-1}\approx 63.2\%` of a photon interacting prior to traveling an optical depth of 1. The actual distance required to travel an optical depth of 1 depends on :math:`\alpha` and thus the material and the frequency of the light. diff --git a/docs/physics/intro/tardis_flowchart.dot b/docs/physics/intro/tardis_flowchart.dot new file mode 100644 index 00000000000..1f62e996e1d --- /dev/null +++ b/docs/physics/intro/tardis_flowchart.dot @@ -0,0 +1,19 @@ +digraph { + compound = true + graph [nodesep=4, ranksep=1] + config [label=<<B>Configuration</B><br/><br/> <i><Configuration object>=Configuration.from_yaml(...)</i><br/> <i><Configuration object>=Configuration.from_config_dict(...)</i>>, shape=oval] + setup_sim [label=<<B><u>Setting up the Simulation</u></B> <br/><br/> <i><Simulation object>=Simulation.from_config(...)</i> <br/><br/> - Creates and calculates model <br/> - Creates and calculates plasma <br/> - Initializes Monte Carlo transport>, shape=rectangle] + mc_iteration [label=<<B><u>Monte Carlo Iteration</u></B> <br/><br/> <i><Simulation object>.iterate(...)</i><br/> <br/> - Initializes packets <br/> - Propagates packets <br/> - Calculates estimators>, shape=rectangle] + adv_state [label=<<B><u>Updating Plasma and Convergence</u></B> <br/><br/> <i><Simulation object>.advance_state()</i> <br/><br/> - Estimates and updates t_rad, w, and t_inner in model <br/> - Updates plasma <br/> - Checks for convergence>, shape=rectangle] + spec_gen [label=<<B><u>Spectrum Generation</u></B> <br/><br/> <i>From final Monte Carlo iteration</i> <br/><br/> - Basic spectrum generation <br/> - Virtual packets <br/> - Formal integral>, shape=rectangle] + subgraph cluster1 { + style = rounded + margin = .25 + label=<<br/><br/><i><Simulation object>.run_convergence()</i><br/> >; + mc_iteration -> adv_state + adv_state -> mc_iteration + } + config -> setup_sim + setup_sim -> mc_iteration [lhead=cluster1, minlen=2] + adv_state -> spec_gen [ltail=cluster1] +} diff --git a/docs/physics/montecarlo/basicprinciples.rst b/docs/physics/montecarlo/basicprinciples.rst index adee47f05bd..1b24408e1e0 100644 --- a/docs/physics/montecarlo/basicprinciples.rst +++ b/docs/physics/montecarlo/basicprinciples.rst @@ -12,12 +12,13 @@ successful and elegant tool particularly for radiative transfer problems in supe Monte Carlo Radiative Transfer methods track a sufficiently large number of photons (light particles) as they propagate through the supernova ejecta. The initial properties of these photons are randomly (in a probabilistic -sense) assigned in accordance with the macroscopic properties of the radiation field (see :ref:`initialization`) +sense) assigned in accordance with the macroscopic properties of the radiation field (see :doc:`initialization`) and in a similar manner the decisions about when, where and how the photons interact with the surrounding material -are made (see :ref:`Propagation <propagation>`). Given a large enough sample, these photons behave as a microcosom +are made (see :ref:`Propagation <propagation>`). Given a large enough sample, these photons behave as a microcosm of all of the light traveling through the ejecta -- that is, based on the behavior of these photons, we can draw -conclusions about the propagation of light through the ejecta as a whole. This is eventually used to determine the -actual steady-state plasma properties (see :ref:`est_and_conv`) and the emitted spectrum (see :ref:`spectrum`). +conclusions about the propagation of light through the ejecta as a whole (see :ref:`estimators`). This is eventually +used to determine the actual steady-state plasma properties (see :doc:`../update_and_conv/update_and_conv`) and the +emitted spectrum (see :ref:`spectrum`). .. _randomsampling: @@ -25,7 +26,7 @@ actual steady-state plasma properties (see :ref:`est_and_conv`) and the emitted Random Sampling Basics ====================== -During both the initialization of these photons and their propagation through the ejecta are modeled through +Both the initialization of these photons and their propagation through the ejecta are modeled through probabilistic processes. This involves assigning probabilities to the occurrence of certain events or properties. For example, during isotropic scattering, finding a photon scattering into any given direction is equally likely. During the Monte Carlo simulation, assignments @@ -94,8 +95,8 @@ Here, all scattering angles are equally likely. Thus, the corresponding .. math:: - \rho_{\mu}(\mu) &= \frac{1}{2}\\ - f_{\mu}(\mu) &= \frac{1}{2} (\mu - 1). + \rho(\mu) &= \frac{1}{2}\\ + f(\mu) &= \frac{1}{2} (\mu + 1). This leads to the sampling rule @@ -111,8 +112,8 @@ The probability of a photon interacting after covering an optical depth .. math:: - \rho_{\tau}(\tau) &= \exp(-\tau)\\ - f_{\tau}(\tau) &= 1 - \exp(-\tau). + \rho(\tau) &= \exp(-\tau)\\ + f(\tau) &= 1 - \exp(-\tau). With the inverse transformation method, the optical depth to the next interaction location may then be sampled by @@ -126,4 +127,4 @@ which is equivalent to .. math:: - \tau = - \mathrm{ln}z. \ No newline at end of file + \tau = - \mathrm{ln}z. diff --git a/docs/physics/montecarlo/estimators.rst b/docs/physics/montecarlo/estimators.rst new file mode 100644 index 00000000000..1163580d8bc --- /dev/null +++ b/docs/physics/montecarlo/estimators.rst @@ -0,0 +1,94 @@ +.. _estimators: + +*********************** +Volume-Based Estimators +*********************** + +Besides from just tracking the propagation of our packets, TARDIS also uses the Monte Carlo iteration is to determine useful information about the light traveling through the supernova (also called the radiation field). This information will eventually be used to help :doc:`update the plasma state <../update_and_conv/update_and_conv>` as well as :doc:`generate different types of spectra <../spectrum/index>`. We determine this information through volume-based estimators. The concept was originally developed by :cite:`Lucy1999` and successively refined by :cite:`Lucy1999a`, :cite:`Lucy2002` and :cite:`Lucy2003`. + + +Theory +====== + +:math:`J` and :math:`\bar \nu` Estimators +----------------------------------------- + +Ordinarily, TARDIS is not concerned about the physical amount of time a packet spends traveling through the ejecta. Instead, we consider the "time of simulation" :math:`\Delta t` which is chosen to be the amount of time in which the photosphere emits the ensemble of packets (see :doc:`Energy Packet Initialization <initialization>`). When looking at the estimators, a slightly different interpretation of the packets is necessary. Here, we view the packets as not carrying a discrete amount of energy :math:`\varepsilon` that is emitted in a time interval :math:`\Delta t`, but as being a flow of energy that carries an energy :math:`\varepsilon` over a time :math:`\Delta t` -- that is, each packet is carrying a luminosity (energy per unit time) of :math:`L = \frac{\varepsilon}{\Delta t}`. Now, we can say that if a packet spends a time :math:`\delta t` in the supernova's ejecta, it contributes an energy of :math:`L\delta t= \frac{\varepsilon}{\Delta t}\delta t` into the radiation energy of the ejecta. + +To account for the effects of the Monte Carlo packets on the ejecta, TARDIS uses the packets to first determine the average radiation energy density :math:`E` throughout each shell, where the energy density is the total radiation energy in the shell divided by the volume of the shell :math:`V=\frac{4}{3}\pi (r_\mathrm{outer}^3-r_\mathrm{inner}^3)`. Therefore, we add up the amount of energy each packet contributes to the radiation energy in that shell, and divide by the total volume of the shell: + +.. math:: E=\frac{1}{V}\sum_i L_i\delta t_i=\frac{1}{V}\sum_i \frac{\varepsilon_i}{\Delta t}\delta t_i = \frac{1}{V\Delta t}\sum_i \varepsilon_i\delta t_i + +where we sum over every Monte Carlo packet in the shell. Note that we are interested in the energy density in the co-moving frame (i.e. the energy density "according to the plasma," see :ref:`referenceframes`). Now, we note that the amount of time the Monte Carlo packet spends in a shell is :math:`\delta t = \frac{l_i}{c}` where :math:`l` is the distance that the packet travels through the shell. Thus, our estimator is + +.. math:: E=\frac{1}{V\Delta t}\sum_i \varepsilon_i\frac{l_i}{c} = \frac{1}{cV\Delta t}\sum_i \varepsilon_i l_i. + +Using this energy density, we can then calculate the mean radiation intensity :math:`J` in that shell using the relation :math:`J=\frac{c}{4\pi} E`, which gives us + +.. math:: J=\frac{1}{4\pi V\Delta t}\sum_i \varepsilon_i l_i. + +Since along any path the co-moving energy of the packet is continuously doppler shifted, we approximate this estimator using the co-moving energy at the beginning of the packet's path (theoretically, the midpoint of the path would be a better option. However, we use the beginning of the path for computational ease at a very small cost to the estimator's accuracy). + +Next, we calculate the mean radiation frequency in each shell. For this, in each shell we add up the frequency of each packet weighted by the intensity they contribute to the shell (and then divide by the total intensity, as will be discussed below). Remembering that intensity is :math:`\frac{c}{4\pi}` times the energy density, and as before each packet contributes an energy of :math:`\frac{\varepsilon_i l_i}{c\Delta t}` and thus energy density of :math:`\frac{\varepsilon_i l_i}{cV\Delta t}` to its shell, we have that each packet contributes an intensity of :math:`\frac{\varepsilon_i l_i}{4\pi V\Delta t}` to its shell. So, + +.. math:: \bar \nu = \sum_i \frac{\varepsilon_i l_i}{4\pi V \Delta t} \nu_i = \frac{1}{4\pi V \Delta t}\sum_i \varepsilon_i \nu_i l_i + +where once again the co-moving energy and frequency of each packet are taken at the beginning of the packet's path. + +It is important to note that, confusingly, :math:`\bar \nu` is not truly the mean frequency (as can be seen by its units -- it has dimensions of intensity times frequency). Indeed, the true mean frequency is actually :math:`\frac{\bar \nu}{J}`. + +.. note:: Both estimators take on a different value in each shell. + +These estimators will be used in the :doc:`../update_and_conv/update_and_conv` step to help update the plasma state between iterations. + + +.. _j-blue-estimator: + +:math:`J^b_{lu}` Estimator +-------------------------- + +Another estimator, called the ``j_blue`` or :math:`J^b_{lu}` estimator, is unlike the two previous estimators discussed. Instead of storing the mean intensity over the entire spectrum, it stores the intensity at a specific frequency. More precisely, since frequency is a continuum, it stores the intensity per unit frequency. In each shell, we record the intensity per unit frequency at the blue end (higher frequency end; this is where the ":math:`b`" superscript in :math:`J^b_{lu}` comes from) of each line transition -- that is, if a line transition :math:`l\rightarrow u` (from the lower energy level :math:`l` to the upper energy level :math:`u`, hence the :math:`lu` in :math:`J^b_{lu}`) has a frequency :math:`\nu_{lu}`, the mean intensity between :math:`\nu_{lu}` and :math:`\nu_{lu}+d\nu` is :math:`J^b_{lu}d\nu`. **This means that the** :math:`J^b_{lu}` **estimator contains values for each atomic line in each shell**, and is hence called a *line estimator*. Now, using our previous :math:`J` estimator, we have + +.. math:: J^b_{lu}d\nu = \frac{1}{4\pi V\Delta t}\sum_i \varepsilon_i dl_i + +where :math:`dl_i` is the infinitesimal distance that the packet travels while it has a co-moving frequency between :math:`\nu_{lu}` and :math:`\nu_{lu}+d\nu` (here, therefore, we are summing over all packets in a shell that achieve a co-moving frequency of :math:`\nu_{lu}` and thus come into resonance with the line transition :math:`l\rightarrow u` within that shell). + +Now, say the packet with lab frequency :math:`\nu_\mathrm{lab}` has a co-moving frequency of :math:`\nu_{lu}` at a radius :math:`r_1` and propagation direction :math:`\mu_1`, and it has a co-moving frequency of :math:`\nu_{lu}+d\nu` at a radius :math:`r_2` and propagation direction :math:`\mu_2`. Then (see :ref:`referenceframes`): + +.. math:: \nu_{lu}=\left(1-\frac{r_1\mu_1}{ct_\mathrm{explosion}}\right)\nu_\mathrm{lab} + +and + +.. math:: \nu_{lu}+d\nu=\left(1-\frac{r_2\mu_2}{ct_\mathrm{explosion}}\right)\nu_\mathrm{lab}. + +But then subtracting, we get + +.. math:: d\nu = (r_2\mu_2-r_1\mu_1)\frac{\nu_\mathrm{lab}}{ct_\mathrm{explosion}}=dl*\frac{\nu_\mathrm{lab}}{ct_\mathrm{explosion}} + +(for the last equality, see :ref:`spherical-domain`). + +But now inputting this into the equation for :math:`J^b_{lu}` (using :math:`\frac{dl_i}{d\nu}=\frac{ct_\mathrm{explosion}}{\nu_\mathrm{lab,i}}`), we get + +.. math:: J^b_{lu} = \frac{ct_\mathrm{explosion}}{4\pi V\Delta t}\sum_i \frac{\varepsilon_i}{\nu_\mathrm{lab,i}}. + + +.. _edotlu: + +:math:`\dot{E}_{lu}` Estimator +------------------------------ + +The final estimator we consider, like the ``j_blue`` estimator, is a line estimator, meaning it has contains values for each atomic line in each shell. It calculates the rate at which energy density interacts with a line transition :math:`l\rightarrow u`. The first step is to calculate the rate at which energy density resonates with some line in some shell. Each packet that comes into resonance with the transition :math:`l\rightarrow u` in a shell of volume :math:`V` contributes an energy density to that shell of :math:`\frac{\varepsilon}{V}` over a time :math:`\Delta t`, meaning the rate at which energy density resonates with the line is :math:`\sum_i \frac{\varepsilon_i}{\Delta t V} = \frac{1}{\Delta t V} \sum \varepsilon` where we are summing over all packets which come into resonance with the atomic line in some shell (as usual, this sum is done using the energies in the co-moving frame). Finally, this light then has a :math:`\left( 1- e^{-\tau_{lu}}\right)` probability of interacting with the line (where :math:`\tau_{lu}` is the Sobolev optical depth for the transition :math:`l\rightarrow u`, see :ref:`physical-interactions`), so the rate at which energy density is absorbed into the transition :math:`l\rightarrow u`, called the ``Edotlu`` estimator, is + +.. math:: \dot{E}_{lu} = \frac{1}{\Delta t V} \left( 1- e^{-\tau_{lu}}\right) \sum_i \varepsilon_i. + +Note that while one may expect us to merely add up the contributions of each packet that *interacts* with the line, eliminating the need for the :math:`\left( 1- e^{-\tau_{lu}}\right)` term, the former determines the desired quantity with more accuracy and less noise than the latter, (this is because it does not depend on the limited number of packets TARDIS uses, rather a theoretical equation, to determine how much of the light that comes into resonance with a line actually interacts with that line). + + +Implementation +============== + +As previously discussed, a major component of each Monte Carlo iteration is the packet propagation process. During the packet propagation process this step, the :math:`J` and :math:`\bar \nu` estimators are updates every time a packet is moved to the next event location. Specifically, every time a packet is moved, :math:`\varepsilon l` is added to the "running total" :math:`J` estimator in the shell where the packet is, and :math:`\varepsilon \nu l` is added to the "running total" :math:`\bar\nu` estimator in the shell where the packet is (where :math:`l` is the distance the packet is moved, and :math:`\varepsilon` and :math:`\nu` are respectively the packet's co-moving energy and frequency at the beginning of the packet's path). The factor of :math:`\frac{1}{4\pi V\Delta t}`, for computational ease, is not attached to the estimators but is included during any calculations using these estimators, see :doc:`../update_and_conv/update_and_conv`. + +Additionally, during the propagation process, every time a packet passes through a Sobolev point, meaning it reaches a co-moving frequency of :math:`\nu_{lu}` for some transition :math:`l\rightarrow u` and thus comes in resonance with an atomic line, the :math:`J^b_{lu}` for that atomic transition in the shell it is in is incremented by :math:`\frac{\varepsilon}{\nu_\mathrm{lab}}`, where :math:`\varepsilon` is the packet's energy and :math:`\nu_\mathrm{lab}` is the packet's lab-frame frequency. As before, for computational ease, the factor :math:`\frac{ct_\mathrm{explosion}}{4\pi V \Delta t}` is included in calculations involving the estimator (such as when `updating <../update_and_conv/update_and_conv.ipynb#updating-other-quantities>`_ :math:`J^b_{lu}` in the plasma or in the :ref:`formal integral <formal_integral>`). Similarly, when a packet passes through a Sobolev point, the :math:`\dot{E}_{lu}` for that atomic transition in the shell it is in is incremented by :math:`\varepsilon`, and once again, for computational ease, the term :math:`\frac{1}{\Delta t V} \left( 1- e^{-\tau_{lu}}\right)` is not included until calculations involving the estimator are performed (specifically in the :ref:`formal integral <formal_integral>`). + +.. note:: Since the ``j_blue`` and ``Edotlu`` estimators are updated every time a packet comes into resonance with an atomic line (not necessarily going through a line interaction), these estimators are equal to zero in some shell for a specific line if (and only if) no packet comes into resonance with that line within the shell. diff --git a/docs/physics/montecarlo/index.rst b/docs/physics/montecarlo/index.rst index d4c69971330..f23def90068 100644 --- a/docs/physics/montecarlo/index.rst +++ b/docs/physics/montecarlo/index.rst @@ -4,16 +4,16 @@ Monte Carlo Iteration ********************* -After setting up the simulation, TARDIS runs the simulation using the ``.run()`` method. This runs several Monte -Carlo iterations (which will be described in the links below), corresponding to the number of iterations specified -in the :ref:`Monte Carlo Configuration <montecarlo-config>`. As will be decribed in :ref:`est_and_conv` and -:ref:`spectrum`, most of these iterations will eventually be used to calculate the steady-state plasma properties, -with the last iteration being used to determine the spectrum. +After setting up the simulation, TARDIS runs the simulation using the ``.run_convergence()`` method. This runs several Monte +Carlo iterations (which will be described in the links below), corresponding to one less than the number of iterations specified +in the :ref:`Monte Carlo Configuration <montecarlo-config>`. As will be described in :doc:`../update_and_conv/update_and_conv` and +:ref:`spectrum`, these iterations will eventually be used to calculate the steady-state plasma properties. +TARDIS runs the last iteration of the simulation using the ``.run_final()`` method to determine the spectrum. The following pages provide a very basic introduction to Monte Carlo radiative transfer techniques as they are used in TARDIS. All the information listed here can also be found in various papers by L. Lucy and in the main TARDIS publication -(c.f. :cite:`Abbott1985`, :cite:`Mazzali1993`, :cite:`Lucy1999`, +(cf. :cite:`Abbott1985`, :cite:`Mazzali1993`, :cite:`Lucy1999`, :cite:`Long2002`, :cite:`Lucy2002`, :cite:`Lucy2003`, :cite:`Lucy2005`, :cite:`Kerzendorf2014`). @@ -23,4 +23,5 @@ can also be found in various papers by L. Lucy and in the main TARDIS publicatio basicprinciples initialization propagation - lineinteraction \ No newline at end of file + lineinteraction + estimators \ No newline at end of file diff --git a/docs/physics/montecarlo/initialization.ipynb b/docs/physics/montecarlo/initialization.ipynb index a180e93ede0..63ebff07f84 100644 --- a/docs/physics/montecarlo/initialization.ipynb +++ b/docs/physics/montecarlo/initialization.ipynb @@ -1,12 +1,15 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "6c0dbe0a", "metadata": {}, "source": [ "# Energy Packet Initialization\n", "\n", + "## Theory\n", + "\n", "While it is instructive to think about tracking the propagation history of\n", "individual photons when illustrating the basic idea behind Monte Carlo radiative transfer\n", "techniques, there are important numerical reasons for using a different\n", @@ -17,7 +20,9 @@ "are commonly referred to as \"energy packets\" or simply \"packets\", and are composed of many photons with the same frequency.\n", "\n", "During a Monte Carlo calculation, $N$ (a large number) packets, all with a certain\n", - "energy $\\varepsilon$, are created at the inner boundary of the computational domain (which is discussed in [Model of Supernova Domain](../setup/model.rst)) known as the photosphere. Currently, the photosphere is modeled as a spherical blackbody with a radius $R_\\mathrm{phot}$ and temperature $T_\\mathrm{phot}$. In TARDIS, all packets are assigned identical energies, and the total energy of the packets is 1 erg (and thus each packet has an energy of $\\frac{1}{N}$ ergs).\n", + "energy $\\varepsilon$, are created at the inner boundary of the computational domain (which is discussed in the [model section](../setup/model.rst)) known as the photosphere. Currently, the photosphere is modeled as a spherical [blackbody](https://en.wikipedia.org/wiki/Black-body_radiation) with a radius $r_\\mathrm{boundary\\_inner}$ and temperature $T_\\mathrm{inner}$. Both of these quantities are calculated as a part of the [model](../setup/model.ipynb), and $T_\\mathrm{inner}$ is additionally updated throughout the simulation as a part of the [Updating Plasma and Convergence](../update_and_conv/update_and_conv.ipynb) process.\n", + "\n", + "In TARDIS, all packets are assigned identical energies **in the lab frame** (see [Reference Frames](propagation.rst#reference-frames)), and the total (lab-frame) energy of the packets is 1 erg (and thus each packet has an energy of $\\frac{1}{N}$ ergs).\n", "\n", "<div class=\"alert alert-info\">\n", " \n", @@ -27,22 +32,42 @@ "\n", "</div>\n", "\n", - "Since the photosphere is modeled as a blackbody, its total luminosity $L$ (recall that luminosity is energy emitted divided by the time in which it is emitted) is\n", - "$$L=\\frac{N\\varepsilon}{\\Delta t}=4 \\pi R_{\\mathrm{phot}}^2 \\sigma_{\\mathrm{R}} T_{\\mathrm{phot}}^4$$\n", + "<div class=\"alert alert-info\">\n", + " \n", + "Note\n", + "\n", + "Since all packets have the same total, and photon energy is proportional to frequency, higher-frequency packets will represent less real photons than lower-frequency packets.\n", + "\n", + "</div>\n", + "\n", + "Since the photosphere is modeled as a blackbody, its total luminosity $L_\\mathrm{inner}$ (recall that luminosity is energy emitted divided by the time in which it is emitted) is\n", + "$$L_\\mathrm{inner}=\\frac{N\\varepsilon}{\\Delta t}=4 \\pi r_\\mathrm{boundary\\_inner}^2 \\sigma_{\\mathrm{R}} T_{\\mathrm{inner}}^4$$\n", "where $\\sigma_\\mathrm{R}$ is the Stefan-Boltzmann constant and $\\Delta t$ is the physical duration of the simulation. In order to make this relationship hold (remembering that $N\\varepsilon = 1$ erg), we use\n", - "$$\\Delta t = \\frac{1}{L}=\\frac{1}{4 \\pi R_{\\mathrm{phot}}^2 \\sigma_{\\mathrm{R}} T_{\\mathrm{phot}}^4}.$$\n", + "$$\\Delta t = \\frac{1}{L_\\mathrm{inner}}=\\frac{1}{4 \\pi r_\\mathrm{boundary\\_inner}^2 \\sigma_{\\mathrm{R}} T_{\\mathrm{inner}}^4}.$$\n", "\n", - "During packet initialization, each packet is assigned an initial propagation direction $\\mu$ which is the cosine of the angle $\\theta$ which the packet's path makes with the radial direction. Using a pseudo-random number generator which generates numbers $z$ uniformly distributed on the interval $[0,1]$, the propagation direction is determined according to\n", + "<div class=\"alert alert-info\">\n", + " \n", + "Note\n", + "\n", + "As will be shown in the code example, this will lead to unphysically small values for $\\Delta t$. It may be easier to think of the Monte Carlo packets not as packets of energy $\\epsilon$ going through a simulation of duration $\\Delta t$, but as packets of luminosity that carry an energy $\\epsilon$ over a time $\\Delta t$ (and thus truly being luminosity packets of luminosity $\\frac{\\epsilon}{\\Delta t}$). Indeed, this view of the packets will be useful when deriving the [Monte Carlo Estimators](estimators.rst).\n", + "\n", + "</div>\n", + "\n", + "During packet initialization, each packet is assigned an initial propagation direction $\\mu$ which is the cosine of the angle $\\theta$ which the packet's path makes with the radial direction (see the image below). Using a pseudo-random number generator which generates numbers $z$ uniformly distributed on the interval $[0,1]$, the propagation direction is determined (due to physical considerations beyond the scope of this documentation) according to\n", "$$\\mu = \\sqrt{z}.$$\n", - "This sampling is demonstrated in the code below.\n", + "This sampling is shown in the \"Code Example\" section.\n", + "\n", + "<img src=\"../images/propagation_direction.png\" width=500>\n", "\n", "Finally, each packet is assigned an initial frequency (or more precisely, the initial frequency of its constituent photons). Note that since each packet has the same energy, each packet will represent a different number of real photons. The sampling on packet frequencies is more involved than that of the propagation direction, as it involves sampling the Planck distribution (see below). TARDIS uses the technique described in <strong data-cite=\"Carter1975\">[]</strong> and summarized in <strong data-cite=\"Bjorkman2001\">[]</strong> for this purpose.\n", "\n", "During the simulation, the energy of the packet remains constant in the local\n", "co-moving frame (see [Reference Frames](propagation.rst#reference-frames)). This naturally ensures energy\n", - "conservation and constitutes the main advantage of this discretization scheme. **However, while the energy of the packets is conserved in the co-moving frame, the frequency of the constituent photons (in the local co-moving frame) may vary over the course of the simulation. Thus, a packet may represent several different numbers of real photons throughout their lifetimes.**\n", + "conservation and constitutes the main advantage of this discretization scheme. **However, while the energy of the packets is conserved in the co-moving frame, the co-moving frequency of the packet (and thus the photons represented by the packet) may vary over the course of the simulation. Thus, a packet may represent several different numbers of real photons throughout their lifetimes.**\n", "\n", - "We now demonstrate the TARDIS packet initialization framework:" + "## Code Example\n", + "\n", + "We now demonstrate the TARDIS packet initialization framework:\n" ] }, { @@ -53,21 +78,22 @@ "outputs": [], "source": [ "import numpy as np\n", - "from tardis.montecarlo.packet_source import BlackBodySimpleSource\n", + "from tardis.transport.montecarlo.packet_source import BlackBodySimpleSource\n", + "from tardis.transport.montecarlo.packet_collections import (\n", + " PacketCollection,\n", + ")\n", "from astropy import units as u\n", "from tardis import constants as const\n", - "import matplotlib.pyplot as plt\n", - "\n", - "#The random number generator that will be used\n", - "rng = np.random.default_rng()" + "import matplotlib.pyplot as plt" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "4ae02998", "metadata": {}, "source": [ - "The following cell contains values that you can change to see how it affects the spectrum:" + "The following cell contains values that you can change to see how it affects the spectrum (in an actual simulation, the seed and number of packets are set in the [Monte Carlo configuration](../../io/configuration/components/montecarlo.rst), and the photospheric radius is calculated as a part of the [model](../setup/model.ipynb)):\n" ] }, { @@ -77,66 +103,58 @@ "metadata": {}, "outputs": [], "source": [ - "# Seed for the pseudo-random number generator\n", - "seed = 1\n", - "\n", - "# Radius of the supernova's photosphere in cm\n", - "r_phot = 1e15 * u.cm\n", + "# Base seed for the packet source\n", + "base_seed = 1\n", + "# Seed offset resets the Pseudo Random Number Generator with a new seed at each iteration\n", + "seed_offset = 0\n", "\n", "# Number of packets generated\n", - "n_packets = 40000" + "n_packets = 40000\n", + "\n", + "# Radius of the supernova's photosphere in cm\n", + "r_boundary_inner = 1e15 * u.cm" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "450faf76", "metadata": {}, "source": [ - "You can either set a temperatature of the photosphere, which will determine its luminosity; or you can set the luminosity of the photosphere, which will determine its temperature." + "We set the temperature of the photosphere $T_\\mathrm{inner}$, which will determine the photospheric luminosity (in an actual simulation, $T_\\mathrm{inner}$ is initially calculated as a part of the [model](../setup/model.ipynb) and updated as a part of the [Updating Plasma and Convergence](../update_and_conv/update_and_conv.ipynb) process):\n" ] }, { "cell_type": "code", "execution_count": null, - "id": "8f2c15a9", + "id": "3fb3ca8c", "metadata": {}, "outputs": [], "source": [ "# Temperature in K\n", - "temperature = 10000 * u.K\n", + "temperature_inner = 10000 * u.K\n", "\n", - "luminosity = 4 * np.pi * (r_phot**2) * const.sigma_sb * (temperature**4)\n", + "luminosity_inner = (\n", + " 4\n", + " * np.pi\n", + " * (r_boundary_inner**2)\n", + " * const.sigma_sb\n", + " * (temperature_inner**4)\n", + ")\n", "\n", "# Makes sure the luminosity is given in erg/s\n", - "luminosity = luminosity.to('erg/s')\n", + "luminosity_inner = luminosity_inner.to(\"erg/s\")\n", "\n", - "print('Luminosity:', luminosity)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3fb3ca8c", - "metadata": {}, - "outputs": [], - "source": [ - "# Luminosity in erg/s\n", - "luminosity = 7e42 * u.erg / u.s\n", - "\n", - "temperature = (luminosity / (4 * np.pi * const.sigma_sb))**0.25 / np.sqrt(r_phot)\n", - "\n", - "# Makes sure the termperature is given in K\n", - "temperature = temperature.to('K')\n", - "\n", - "print('Temperature:', temperature)" + "print(\"Luminosity of photosphere:\", luminosity_inner)" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "516633c5", "metadata": {}, "source": [ - "We now generate the ensemble of packets. The array of packet energies and radii are also shown." + "We now generate the ensemble of packets. The array of packet energies and radii are also shown.\n" ] }, { @@ -147,30 +165,32 @@ "outputs": [], "source": [ "# We define our packet source\n", - "packet_source = BlackBodySimpleSource(seed)\n", + "packet_source = BlackBodySimpleSource(base_seed=base_seed)\n", "\n", - "radii, nus, mus, energies = packet_source.create_packets(\n", - " temperature.value, \n", - " n_packets, \n", - " rng, \n", - " r_phot)\n", + "# Set radii and temperature from model\n", + "packet_source.radius = r_boundary_inner\n", + "packet_source.temperature = temperature_inner\n", + "\n", + "# Create packets\n", + "packet_collection = packet_source.create_packets(n_packets)\n", "\n", "# Sets the energies in units of ergs\n", - "energies *= u.erg\n", + "packet_collection.initial_energies *= u.erg\n", "\n", "# Sets the frequencies in units of Hz\n", - "nus *= u.Hz\n", + "packet_collection.initial_nus *= u.Hz\n", "\n", - "print('Energies:', energies)\n", - "print('Radii:', radii)" + "print(\"Energies:\", packet_collection.initial_energies)\n", + "print(\"Radii:\", packet_collection.initial_radii)" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "16936bce", "metadata": {}, "source": [ - "We set the timespan of the simulation so that each packet contributes the appropriate luminosity to the spectrum." + "We set the timespan of the simulation so that each packet contributes the appropriate luminosity to the spectrum.\n" ] }, { @@ -181,22 +201,23 @@ "outputs": [], "source": [ "# Time of simulation\n", - "t_simulation = 1 * u.erg / luminosity\n", - "print('Time of simulation:', t_simulation)\n", + "t_simulation = 1 * u.erg / luminosity_inner\n", + "print(\"Time of simulation:\", t_simulation)\n", "\n", "# Array of luminosity contribution by each packet\n", - "lumin_per_packet = energies / t_simulation\n", - "print('Luminosity per packet:', lumin_per_packet)" + "lumin_per_packet = packet_collection.initial_energies / t_simulation\n", + "print(\"Luminosity per packet:\", lumin_per_packet)" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "0d839222", "metadata": {}, "source": [ "We define important constants, and for comparison's sake, we code the Planck distribution function\n", - "$$L_\\nu (\\nu)=\\frac{8\\pi R_\\mathrm{phot}^2 h\\nu^3}{c^2}\\frac{1}{\\exp\\left(\\frac{h\\nu}{k_BT_\\mathrm{phot}}\\right)-1}$$\n", - "where $L_\\nu$ is the luminosity density (see [Basic Spectrum Generation](../spectrum/basic.ipynb)) with respect to frequency, $\\nu$ is frequency, $h$ is Planck's constant, $c$ is the speed of light, and $k_B$ is Boltzmann's constant:" + "$$L_\\nu (\\nu)=\\frac{8\\pi^2 r_\\mathrm{boundary\\_inner}^2 h\\nu^3}{c^2}\\frac{1}{\\exp\\left(\\frac{h\\nu}{k_BT_\\mathrm{inner}}\\right)-1}$$\n", + "where $L_\\nu$ is the luminosity density (see [Basic Spectrum Generation](../spectrum/basic.ipynb)) with respect to frequency, $\\nu$ is frequency, $h$ is Planck's constant, $c$ is the speed of light, and $k_B$ is Boltzmann's constant:\n" ] }, { @@ -212,16 +233,25 @@ "c2 = const.c.cgs**2\n", "kB = const.k_B.cgs\n", "\n", + "\n", "def planck_function(nu):\n", - " return 8 * np.pi**2 * r_phot**2 * h * nu**3 / (c2 * (np.exp(h * nu / (kB * temperature)) - 1))" + " return (\n", + " 8\n", + " * np.pi**2\n", + " * r_boundary_inner**2\n", + " * h\n", + " * nu**3\n", + " / (c2 * (np.exp(h * nu / (kB * temperature_inner)) - 1))\n", + " )" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "78230177", "metadata": {}, "source": [ - "We plot the Planck distribution and a histogram of the generated packet distribution:" + "We plot the Planck distribution and a histogram of the generated packet distribution:\n" ] }, { @@ -233,29 +263,28 @@ "source": [ "# We set important quantites for making our histogram\n", "bins = 200\n", - "nus_planck = np.linspace(min(nus), max(nus), bins)\n", + "nus_planck = np.linspace(min(packet_collection.initial_nus), max(packet_collection.initial_nus), bins).value\n", "bin_width = nus_planck[1] - nus_planck[0]\n", "\n", - "# In the histogram plot below, the weights argument is used \n", + "# In the histogram plot below, the weights argument is used\n", "# to make sure our plotted spectrum has the correct y-axis scale\n", - "plt.hist(nus.value,\n", - " bins=bins,\n", - " weights=lumin_per_packet/bin_width)\n", + "plt.hist(packet_collection.initial_nus.value, bins=bins, weights=lumin_per_packet / bin_width)\n", "\n", "# We plot the planck function for comparison\n", - "plt.plot(nus_planck, planck_function(nus_planck))\n", + "plt.plot(nus_planck * u.Hz, planck_function(nus_planck * u.Hz))\n", "\n", - "plt.xlabel('Frequency (Hz)')\n", - "plt.ylabel('Luminosity density w.r.t. frequency (erg/s/Hz)')\n", + "plt.xlabel(\"Frequency (Hz)\")\n", + "plt.ylabel(\"Luminosity density w.r.t. frequency (erg/s/Hz)\")\n", "plt.show()" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ad4f0f0e", "metadata": {}, "source": [ - "We finally plot the generated $\\mu$ density distribution, followed by the generated $\\theta=\\arccos (\\mu)$ density distribution, compared with the respective curves $\\rho = 2\\mu$ and $\\rho = \\sin(2\\theta)$:" + "We finally plot the generated $\\mu$ density distribution, followed by the generated $\\theta=\\arccos (\\mu)$ density distribution, compared with the respective curves $\\rho = 2\\mu$ and $\\rho = \\sin(2\\theta)$:\n" ] }, { @@ -267,10 +296,10 @@ "source": [ "x = np.linspace(0, 1, 1000)\n", "\n", - "plt.hist(mus, bins=bins, density=True)\n", - "plt.plot(x, 2*x)\n", - "plt.xlabel('Propagation direction')\n", - "plt.ylabel('Probability density')\n", + "plt.hist(packet_collection.initial_mus, bins=bins, density=True)\n", + "plt.plot(x, 2 * x)\n", + "plt.xlabel(\"Propagation direction\")\n", + "plt.ylabel(\"Probability density\")\n", "plt.show()" ] }, @@ -281,30 +310,31 @@ "metadata": {}, "outputs": [], "source": [ - "thetas = np.linspace(0, np.pi/2, 1000)\n", + "thetas = np.linspace(0, np.pi / 2, 1000)\n", "\n", - "plt.hist(np.arccos(mus), bins=bins, density=True)\n", - "plt.plot(thetas, np.sin(2*thetas))\n", - "plt.xlabel('Angle with normal (rad)')\n", - "plt.ylabel('Probability density')\n", + "plt.hist(np.arccos(packet_collection.initial_mus), bins=bins, density=True)\n", + "plt.plot(thetas, np.sin(2 * thetas))\n", + "plt.xlabel(\"Angle with normal (rad)\")\n", + "plt.ylabel(\"Probability density\")\n", "plt.show()" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2f661592", "metadata": {}, "source": [ "## Custom Packet Source\n", "\n", - "TARDIS allows for the user to input a custom function that generates energy packets instead of the basic blackbody source described here. See [Running TARDIS with a Custom Packet Source](../../io/optional/custom_source.ipynb) for more information." + "TARDIS allows for the user to input a custom function that generates energy packets instead of the basic blackbody source described here. See [How to Run TARDIS with a Custom Packet Source](../../io/optional/how_to_custom_source.ipynb) for more information." ] } ], "metadata": { "celltoolbar": "Raw Cell Format", "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -318,7 +348,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/docs/physics/montecarlo/lineinteraction.rst b/docs/physics/montecarlo/lineinteraction.rst index 43f65553aaa..6e1c23ba725 100644 --- a/docs/physics/montecarlo/lineinteraction.rst +++ b/docs/physics/montecarlo/lineinteraction.rst @@ -8,7 +8,7 @@ TARDIS currently offers different ways to handle line interactions, which may be activated via the :term:`YAML` configuration file. Independently of the chosen treatment, a number of steps are always carried out when a Monte Carlo packet performs a line interaction. Since TARDIS adopts the indivisible energy packet -formalism (see :ref:`Energy Packets <initialization>`), the packet will have the +formalism (see :doc:`Energy Packets <initialization>`), the packet will have the same energy in the co-moving frame after (f for final) the line interaction as before (i for initial). Thus, after accounting for the frame transformations, diff --git a/docs/physics/montecarlo/propagation.rst b/docs/physics/montecarlo/propagation.rst index c7ccd293fb9..15050b1c6d6 100644 --- a/docs/physics/montecarlo/propagation.rst +++ b/docs/physics/montecarlo/propagation.rst @@ -6,7 +6,7 @@ Packet Propagation The bulk of a Monte Carlo Radiative Transfer calculation is spent on determining the propagation history of the different packets. After a packet is -initialized (see :ref:`initialization`), it is launched and may then perform interactions with the +initialized (see :doc:`initialization`), it is launched and may then perform interactions with the surrounding material. This occurs again in a probabilistic manner. The packet propagation is followed until it escapes through the outer boundary of the computational domain, at which point the packet contributes to the synthetic @@ -14,6 +14,8 @@ spectrum, the main product of a TARDIS calculation. The different spectral features are simply a combined product of the changes in the packet properties induced in the radiation-matter interactions. +.. _spherical-domain: + Propagation in a Spherical Domain ================================= @@ -155,6 +157,7 @@ When a packet is moved into a new cell, as mentioned before, it is moved to the boundary, the plasma properties are recalculated, and the propagation direction of the packet is updated (using :math:`\mu_f = \frac{l + r_i \mu_i}{r_f}`). +.. _physical-interactions: Physical Interactions --------------------- @@ -162,12 +165,14 @@ Physical Interactions As a packet propagates through the computational domain, physical radiation-matter interactions can trigger changes in the packet properties. The probability that a photon/packet will interact with matter is characterized by its optical depth :math:`\tau`; the probability that a packet will have interacted after going through an optical depth -:math:`\Delta \tau` is :math:`1-e^{-\Delta \tau}`. To model this (see :ref:`Random Sampling <randomsampling>`), the +:math:`\Delta \tau` is :math:`1-e^{-\Delta \tau}` (see :ref:`opacity` for more). To model this +(see :ref:`Random Sampling <randomsampling>`), the packet is assigned a random value of optical depth :math:`\tau_\mathrm{interaction} = -\log z` (for another random :math:`z` between 0 and 1), and upon reaching that optical depth, the packet will interact. TARDIS considers two different radiation-matter interactions within the simulation: electron scattering and atomic -line interactions. As packets propagate, they accumulate optical depth due to the possibility of going through either +line interactions (see :ref:`light_and_matter` for a basic introduction to these interactions). As packets propagate, +they accumulate optical depth due to the possibility of going through either of these interactions. Since the main focus of TARDIS is to calculate optical spectra, electron-scatterings are treated in the elastic low-energy limit as classical Thomson scatterings. In this case, the electron scattering process is frequency-independent. As a consequence to the @@ -181,9 +186,9 @@ Thomson scattering is calculated by the formula \Delta \tau = \sigma_{\mathrm{T}} n_e l. The Thomson cross section :math:`\sigma_{\mathrm{T}}`, which is a constant, -appears here. This corresponds to the fact that a packet has a probability of :math:`1-e^{\sigma_{\mathrm{T}} n_e l}` +appears here. This corresponds to the fact that a packet has a probability of :math:`1-e^{-\sigma_{\mathrm{T}} n_e l}` of going through a Thomson scattering prior to traveling a distance :math:`l` (in other words, the probability of the -packet making it across a distance :math:`l` without scattering is :math:`e^{\sigma_{\mathrm{T}} n_e l}`). +packet making it across a distance :math:`l` without scattering is :math:`e^{-\sigma_{\mathrm{T}} n_e l}`). The situation is complicated by the inclusion of frequency-dependent bound-bound interactions, i.e. interactions with atomic line transitions. @@ -260,7 +265,9 @@ interaction with the corresponding atomic line transition. In both of these case interaction location, the interaction will be performed (as will be described in the next section), and the process of accumulating optical depth starts over. Finally, if the packet reaches the shell boundary before the optical depth value necessary for a physical interaction is achieved (as in case III), the packet will be moved to the next cell, -the plasma properties will be updated, and the accumulation of optical depth will continue in the next cell. +the plasma properties will be updated, and the accumulation of optical depth will **restart** in the next cell. + +.. note:: While it would make physical sense for the accumulation of optical depth to continue between cells until the packet eventually interacts, due to the exponential nature of optical depth and interaction probabilities, both continuing and restarting the accumulation of optical depth between cells can be mathematically shown to yield the same overall statistical results. Restarting the optical depth accumulation is computationally easier, and hence it is the method employed by TARDIS. Performing an Interaction ------------------------- diff --git a/docs/physics/setup/index.rst b/docs/physics/setup/index.rst index 20ced5b27c4..38e716717a6 100644 --- a/docs/physics/setup/index.rst +++ b/docs/physics/setup/index.rst @@ -5,9 +5,9 @@ Setting Up the Simulation ************************* The first step executed when TARDIS runs is to call an instance of the ``Simulation`` class. This sets up a lot of -things that TARDIS will need during its run. The main things that are set up are the supernova model (a ``Radial1DModel`` object), the -initial plasma state (a ``BasePlasma`` object, which may be updated throughout the simulation, see :ref:`est_and_conv`), -and a ``MonteCarloRunner`` object. The pages linked below explain how the former two are calculated (the latter is used mainly in the +things that TARDIS will need during its run. The main things that are set up are the supernova model (a ``SimulationState`` object), the +initial plasma state (a ``BasePlasma`` object, which may be updated throughout the simulation, see :doc:`../update_and_conv/update_and_conv`), +and a ``MonteCarloTransport`` object. The pages linked below explain how the former two are calculated (the latter is used mainly in the :doc:`next step of the calculation <../montecarlo/index>`), as well as showing this in action by calling an instance of the ``Simulation`` class. diff --git a/docs/physics/setup/model.ipynb b/docs/physics/setup/model.ipynb index 11fbb287f80..a74cf57b31c 100644 --- a/docs/physics/setup/model.ipynb +++ b/docs/physics/setup/model.ipynb @@ -7,11 +7,11 @@ "source": [ "# Model\n", "\n", - "As shown previously, when `Simulation.from_config()` is called, a `Radial1DModel` object is created. This is done via the class method `Radial1DModel.from_config()`. This model object contains important information about the shell structure, density, abundance, radiative temperature, and dilution factor throughout the supernova.\n", + "As shown previously, when `Simulation.from_config()` is called, a `SimulationState` object is created. This is done via the class method `SimulationState.from_config()`. This model object contains important information about the shell structure, density, abundance, radiative temperature, and dilution factor throughout the supernova.\n", "\n", - "Throughout this notebook, we show various configuration inputs into the TARDIS model and the resulting model. In interactive mode, these parameters can be varied to explore how the model changes. Editing configuration parameters in the notebook is explained [here](../../io/configuration/read_configuration.ipynb).\n", + "Throughout this notebook, we show various configuration inputs into the TARDIS model and the resulting model. In interactive mode, these parameters can be varied to explore how the model changes. Editing configuration parameters in the notebook is explained [here](../../io/configuration/tutorial_read_configuration.ipynb).\n", "\n", - "This notebook is based on the [built-in TARDIS models](../../io/configuration/components/models/index.rst#built-in-structure-density-and-abundance), but these parameters can also be input via [custom model configurations](../../io/configuration/components/models/index.rst#custom-model-configurations), the [CSVY model](../../io/configuration/components/models/index.rst#csvy-model) or the [custom abundance widget](../../io/visualization/abundance_widget.ipynb).\n", + "This notebook is based on the [built-in TARDIS models](../../io/configuration/components/models/index.rst#built-in-structure-density-and-abundance), but these parameters can also be input via [custom model configurations](../../io/configuration/components/models/index.rst#custom-model-configurations), the [CSVY model](../../io/configuration/components/models/index.rst#csvy-model) or the [custom abundance widget](../../io/visualization/how_to_abundance_widget.ipynb).\n", "\n", "## Shell Structure\n", "\n", @@ -52,15 +52,17 @@ "outputs": [], "source": [ "# We import the necessary packages\n", - "from tardis.io.config_reader import Configuration\n", - "from tardis.model import Radial1DModel\n", + "from tardis.io.configuration.config_reader import Configuration\n", + "from tardis.model import SimulationState\n", "from tardis.io.atom_data.util import download_atom_data\n", + "from tardis.io.atom_data.base import AtomData\n", "from astropy import units as u\n", "import matplotlib.pyplot as plt\n", "import copy\n", "\n", "# We download the atomic data needed to run the simulation\n", - "download_atom_data('kurucz_cd23_chianti_H_He')" + "download_atom_data('kurucz_cd23_chianti_H_He')\n", + "atom_data = AtomData.from_hdf('kurucz_cd23_chianti_H_He.h5')" ] }, { @@ -79,7 +81,7 @@ "id": "cee054e9", "metadata": {}, "source": [ - "In the cell below, we set up a model. We use the [specific structure](../../io/configuration/components/models/index.rst#specific-structure) where we supply $t_\\mathrm{explosion}$, the velocity of the inner and outer boundaries of the supernova (labeled `start` and `stop`), and the number of shells (labeled `num`). The shells are then evenly spaced between the inner and outer boundaries of the supernova. The time after the explosion, the inner and outer velocities, and the number of shells can be varied to get different shell structures. The `Radial1DModel` object stores information about the model in the following attributes: `velocity` shows the velocity of the shell boundaries, `v_inner` shows the velocities of the inner boundaries of each shell, `v_outer` shows the velocity of the outer boundaries of each shell, and `v_middle` shows the velocity of the middle of each shell. Similarly, `radius`, `r_inner`, `r_outer`, and `r_middle` show the radii of each shell boundary, the inner boundaries, the outer boundaries, and the middles of each shell, respectively. `v_boundary_inner` shows the velocity of the inner boundary of the computational domain, and `v_boundary_outer` shows the velocity of the outer boundary of the computational domain. Finally, `volume` shows the volume of each shell, calculated via the formula of the volume of a spherical shell: $V=\\frac{4}{3}\\pi (r_\\mathrm{outer}^3-r_\\mathrm{inner}^3)$." + "In the cell below, we set up a model. We use the [specific structure](../../io/configuration/components/models/index.rst#specific-structure) where we supply $t_\\mathrm{explosion}$, the velocity of the inner and outer boundaries of the supernova (labeled `start` and `stop`), and the number of shells (labeled `num`). The shells are then evenly spaced between the inner and outer boundaries of the supernova. The time after the explosion, the inner and outer velocities, and the number of shells can be varied to get different shell structures. The `SimulationState` object stores information about the model in the following attributes: `velocity` shows the velocity of the shell boundaries, `v_inner` shows the velocities of the inner boundaries of each shell, `v_outer` shows the velocity of the outer boundaries of each shell, and `v_middle` shows the velocity of the middle of each shell. Similarly, `radius`, `r_inner`, `r_outer`, and `r_middle` show the radii of each shell boundary, the inner boundaries, the outer boundaries, and the middles of each shell, respectively. `v_boundary_inner` shows the velocity of the inner boundary of the computational domain, and `v_boundary_outer` shows the velocity of the outer boundary of the computational domain. Finally, `volume` shows the volume of each shell, calculated via the formula of the volume of a spherical shell: $V=\\frac{4}{3}\\pi (r_\\mathrm{outer}^3-r_\\mathrm{inner}^3)$." ] }, { @@ -103,19 +105,19 @@ "shell_config.model.structure.velocity.stop = 2000 * u.km/u.s\n", "shell_config.model.structure.velocity.num = 20\n", "\n", - "shell_model = Radial1DModel.from_config(shell_config)\n", - "\n", - "print('velocity:\\n', shell_model.velocity)\n", - "print('v_inner:\\n', shell_model.v_inner)\n", - "print('v_outer:\\n', shell_model.v_outer)\n", - "print('v_middle:\\n', shell_model.v_middle)\n", - "print('v_boundary_inner:\\n', shell_model.v_boundary_inner)\n", - "print('v_boundary_outer:\\n', shell_model.v_boundary_outer)\n", - "print('radius:\\n', shell_model.radius)\n", - "print('r_inner:\\n', shell_model.r_inner)\n", - "print('r_outer:\\n', shell_model.r_outer)\n", - "print('r_middle:\\n', shell_model.r_middle)\n", - "print('volume:\\n', shell_model.volume)" + "shell_simulation_state = SimulationState.from_config(shell_config, atom_data=atom_data)\n", + "\n", + "print('velocity:\\n', shell_simulation_state.velocity)\n", + "print('v_inner:\\n', shell_simulation_state.v_inner)\n", + "print('v_outer:\\n', shell_simulation_state.v_outer)\n", + "print('v_middle:\\n', shell_simulation_state.v_middle)\n", + "print('v_boundary_inner:\\n', shell_simulation_state.v_boundary_inner)\n", + "print('v_boundary_outer:\\n', shell_simulation_state.v_boundary_outer)\n", + "print('radius:\\n', shell_simulation_state.radius)\n", + "print('r_inner:\\n', shell_simulation_state.r_inner)\n", + "print('r_outer:\\n', shell_simulation_state.r_outer)\n", + "print('r_middle:\\n', shell_simulation_state.r_middle)\n", + "print('volume:\\n', shell_simulation_state.volume)" ] }, { @@ -123,13 +125,13 @@ "id": "1ee56110", "metadata": {}, "source": [ - "Notice that `radius = velocity*time_explosion`, and similarly for `r_inner`, `r_outer`, and `r_middle`. You can get the radius of the photosphere via `v_inner_boundary*time_explosion` and outer edge of the supernova via `v_outer_boundary*time_explosion`.\n", + "Notice that `radius = velocity*time_explosion`, and similarly for `r_inner`, `r_outer`, and `r_middle`. You can get the radius of the photosphere via `v_boundary_inner*time_explosion` and outer edge of the supernova via `v_boundary_outer*time_explosion`.\n", "\n", "<div class=\"alert alert-info\">\n", " \n", "Note\n", "\n", - "Using the built-in shell structure, as shown here, the shells are all equally spaced. This is not necessarily the case if one uses the [file structure](../../io/configuration/components/models/index.rst#file-structure), [CSVY model](../../io/configuration/components/models/index.rst#csvy-model), or [custom abundance widget](../../io/visualization/abundance_widget.ipynb).\n", + "Using the built-in shell structure, as shown here, the shells are all equally spaced. This is not necessarily the case if one uses the [file structure](../../io/configuration/components/models/index.rst#file-structure), [CSVY model](../../io/configuration/components/models/index.rst#csvy-model), or [custom abundance widget](../../io/visualization/how_to_abundance_widget.ipynb).\n", "\n", "</div>" ] @@ -141,9 +143,9 @@ "source": [ "## Density\n", "\n", - "We now look at how TARDIS models the density inside each shell. If you use the [built-in densities](../../io/configuration/components/models/index.rst#density), TARDIS allows you to choose between the four models discussed below. The [file structure](../../io/configuration/components/models/index.rst#file-structure), [CSVY model](../../io/configuration/components/models/index.rst#csvy-model), and [custom abundance widget](../../io/visualization/abundance_widget.ipynb) options allow more freedom in assigning densities to each shell.\n", + "We now look at how TARDIS models the density inside each shell. If you use the [built-in densities](../../io/configuration/components/models/index.rst#density), TARDIS allows you to choose between the four models discussed below. The [file structure](../../io/configuration/components/models/index.rst#file-structure), [CSVY model](../../io/configuration/components/models/index.rst#csvy-model), and [custom abundance widget](../../io/visualization/how_to_abundance_widget.ipynb) options allow more freedom in assigning densities to each shell.\n", "\n", - "In general, the density in the supernova at a specific moment in time is a function of the radius or velocity of the ejecta (either canbe used, since the radius and velocity are linearly related at any moment of time). Since the shell velocities do not change over time, it is more simple to write the densities as a function of ejecta velocity. If we do this, the time-dependence of the density is simple. We know the total mass of the ejecta is constant in each shell due to the nature of homologous expansion. The inner and outer radii of each shell increases linearly over time, meaning the volume increases as time cubed. Since density is mass divided by volume, the density is inverse-cubic in time. Mathematically, if $\\rho(v,t_\\mathrm{explosion})$ is the density at a velocity $v$ after a time $t_\\mathrm{explosion}$, given some characteristic time $t_0$, we have\n", + "In general, the density in the supernova at a specific moment in time is a function of the radius or velocity of the ejecta (either can be used, since the radius and velocity are linearly related at any moment of time). Since the shell velocities do not change over time, it is more simple to write the densities as a function of ejecta velocity. If we do this, the time-dependence of the density is simple. We know the total mass of the ejecta is constant in each shell due to the nature of homologous expansion. The inner and outer radii of each shell increase linearly over time, meaning the volume increases as time cubed. Since density is mass divided by volume, the density is inverse-cubic in time. Mathematically, if $\\rho(v,t_\\mathrm{explosion})$ is the density at a velocity $v$ after a time $t_\\mathrm{explosion}$, given some characteristic time $t_0$, we have\n", "\n", "$$\\rho(v,t_\\mathrm{explosion})=\\rho(v,t_0)*\\left(\\frac{t_0}{t_\\mathrm{explosion}}\\right)^3$$\n", "\n", @@ -151,7 +153,7 @@ "\n", "Since the state of the ejecta, including the density, is the same throughout the shell, we determine the shell's density by plugging the velocity/radius at the center of the shell into the density function. We now explore the various built-in density profiles. For each profile, we build an example model using the density profile and example parameters (which can be varied in interactive mode), print the densities in each shell, and show a graph of density versus radius (specifically the radius at the center of each shell).\n", "\n", - "Note that the density in each shell is stored in the `density` attribute of the `Radial1DModel` object.\n", + "Note that the density in each shell is stored in the `density` attribute of the `SimulationState` object.\n", "\n", "### Branch85 W7 Density\n", "\n", @@ -181,7 +183,7 @@ "\n", "w7_density_config.model.structure.density.type = 'branch85_w7'\n", "\n", - "w7_density_model = Radial1DModel.from_config(w7_density_config)\n", + "w7_density_model = SimulationState.from_config(w7_density_config, atom_data=atom_data)\n", "\n", "print('density:\\n', w7_density_model.density)\n", "\n", @@ -209,7 +211,7 @@ "\n", "w7_modified_config.supernova.time_explosion = 12 * u.day\n", "\n", - "w7_modified_model = Radial1DModel.from_config(w7_modified_config)\n", + "w7_modified_model = SimulationState.from_config(w7_modified_config, atom_data=atom_data)\n", "\n", "print('density:\\n', w7_modified_model.density)\n", "\n", @@ -273,7 +275,7 @@ "uni_density_config.model.structure.density.time_0 = 1 * u.day\n", "uni_density_config.model.structure.density.value = 5e-10 * u.kg/u.cm**3\n", "\n", - "uni_density_model = Radial1DModel.from_config(uni_density_config)\n", + "uni_density_model = SimulationState.from_config(uni_density_config, atom_data=atom_data)\n", "\n", "print('density:\\n', uni_density_model.density)\n", "\n", @@ -327,7 +329,7 @@ "pow_density_config.model.structure.density.v_0 = 500 * u.km/u.s\n", "pow_density_config.model.structure.density.exponent = -2\n", "\n", - "pow_density_model = Radial1DModel.from_config(pow_density_config)\n", + "pow_density_model = SimulationState.from_config(pow_density_config, atom_data=atom_data)\n", "\n", "print('density:\\n', pow_density_model.density)\n", "\n", @@ -378,7 +380,7 @@ "exp_density_config.model.structure.density.rho_0 = 5e-10 * u.kg/u.cm**3\n", "exp_density_config.model.structure.density.v_0 = 500 * u.km/u.s\n", "\n", - "exp_density_model = Radial1DModel.from_config(exp_density_config)\n", + "exp_density_model = SimulationState.from_config(exp_density_config, atom_data=atom_data)\n", "\n", "print('density:\\n', exp_density_model.density)\n", "\n", @@ -394,11 +396,11 @@ "source": [ "## Abundance\n", "\n", - "The `Radial1DModel` also carries important information about elemental abundances in each shell. These are mass abundances -- that is, the abundance of oxygen is the fraction of the shell's mass that is made up of oxygen.\n", + "The `SimulationState` also carries important information about elemental abundances in each shell. These are mass abundances -- that is, the abundance of oxygen is the fraction of the shell's mass that is made up of oxygen.\n", "\n", - "The only built-in abundance model that TARDIS offers is a uniform abundance, meaning each shell has identical abundances. Like density, however, the [file abundance](../../io/configuration/components/models/index.rst#file-abundance), [CSVY model](../../io/configuration/components/models/index.rst#csvy-model), and [custom abundance widget](../../io/visualization/abundance_widget.ipynb) methods allow users more freedom with assigning different abundances in each shell.\n", + "The only built-in abundance model that TARDIS offers is a uniform abundance, meaning each shell has identical abundances. Like density, however, the [file abundance](../../io/configuration/components/models/index.rst#file-abundance), [CSVY model](../../io/configuration/components/models/index.rst#csvy-model), and [custom abundance widget](../../io/visualization/how_to_abundance_widget.ipynb) methods allow users more freedom with assigning different abundances in each shell.\n", "\n", - "A table of abundances in each shell is stored in the `abundance` attribute of the `Radial1DModel` object.\n", + "A table of abundances in each shell is stored in the `abundance` attribute of the `SimulationState` object.\n", "\n", "In this first example, the abundances in each shell do not depend on the time after the explosion and are identical to those provided in the configuration." ] @@ -423,7 +425,7 @@ " 'Si':.3,\n", " 'He': .1}\n", "\n", - "abund_model = Radial1DModel.from_config(abund_config)\n", + "abund_model = SimulationState.from_config(abund_config, atom_data=atom_data)\n", "\n", "abund_model.abundance" ] @@ -459,9 +461,9 @@ " 'Ni57':.1,\n", " 'Cr51':.4}\n", "\n", - "abund_isotopes_model = Radial1DModel.from_config(abund_isotopes_config)\n", + "abund_isotopes_simulation_state = SimulationState.from_config(abund_isotopes_config, atom_data=atom_data)\n", "\n", - "abund_isotopes_model.abundance" + "abund_isotopes_simulation_state.abundance" ] }, { @@ -469,27 +471,27 @@ "id": "9fded236", "metadata": {}, "source": [ - "## Radiative Temperature\n", + "## Temperatures\n", "\n", - "Next, TARDIS finds the temperature of the plasma in each cell, called the radiative temperature. In fact, this temperature changes throughout the simulation based on light-matter interations (see [Estimators and Convergence](../est_and_conv/index.ipynb)). When the model is initiated, TARDIS must calculate an initial guess for the radiative temperature in each shell.\n", + "The model also includes information about the temperature of the photosphere/inner boundary, labeled as $T_\\mathrm{inner}$, and the temperature of the plasma in each cell, called the radiative temperature and labeled as $T_\\mathrm{rad}$. As will be explained, both of these quantities are be updated throughout the simulation, so the calculations in this section are the initial guesses.\n", "\n", - "To do this, TARDIS also calculates the temperature at the surface of the photosphere $T_\\mathrm{inner}$. This is calculated as the temperature of a blackbody:\n", + "TARDIS initially calculates $T_\\mathrm{inner}$ as the temperature of a [blackbody](https://en.wikipedia.org/wiki/Black-body_radiation) such that the luminosity of the photosphere (see [initialization](../montecarlo/initialization.ipynb)) matches the requested output luminosity of the entire supernova $L_\\mathrm{requested}$, which is specified in the [spectrum configuration](../../io/configuration/components/spectrum.rst):\n", "\n", - "$$T_{\\mathrm{inner}}=\\left(\\frac{L}{4 \\pi r_{\\mathrm{boundary\\_inner}}^2 \\sigma_{\\mathrm{R}}}\\right)^{1/4}$$\n", + "$$T_{\\mathrm{inner}}=\\left(\\frac{L_\\mathrm{requested}}{4 \\pi r_{\\mathrm{boundary\\_inner}}^2 \\sigma_{\\mathrm{R}}}\\right)^{1/4}$$\n", "\n", - "where $\\sigma_{\\mathrm{R}}$ is the Stefan-Boltzmann constant, $r_{\\mathrm{boundary\\_inner}}$ is the radius of the photosphere, and $L$ is the luminosity of the photosphere (this is initially taken as the requested luminosity of the supernova, though it is changed throughout the simulation as part of the [convergence](../est_and_conv/convergence.rst)). This calculation is also described in [Energy Packet Initialization](../montecarlo/initialization.ipynb).\n", + "where $\\sigma_{\\mathrm{R}}$ is the Stefan-Boltzmann constant and $r_{\\mathrm{boundary\\_inner}}$ is once again the radius of the photosphere, calculated as part of the shell structure. Because of light-matter interactions, the output luminosity of the supernova will not be the same as the luminosity of the photosphere, so the photospheric temperature is updated throughout the simulation as part of the convergence process in order to match the output luminosity to the requested luminosity (see [Updating Plasma and Convergence](../update_and_conv/update_and_conv.ipynb)).\n", "\n", - "TARDIS calculates the initial guess for the radiative temperature using Wein's Law. Wein's Law states that the temperature of a blackbody is inversely proportional to the blackbody's peak wavelength. The proportionality constant, labeled $b$, is approximately $2.898*10^{-3} m*K$. In equation form,\n", + "Next, TARDIS calculates the initial guess for the radiative temperature in each shell. This temperature is also updated throughout the simulation based on light-matter interactions (see once again [Updating Plasma and Convergence](../update_and_conv/update_and_conv.ipynb)). The initial guess for $T_\\mathrm{rad}$ is calculated using [Wien's Law](https://en.wikipedia.org/wiki/Wien%27s_displacement_law). Wien's Law states that the temperature of a blackbody is inversely proportional to the blackbody's peak wavelength. The proportionality constant, labeled $b$, is approximately $2.898*10^{-3} m*K$. In equation form,\n", "\n", "$$T=\\frac{b}{\\lambda_\\mathrm{peak}}.$$\n", "\n", - "Since we know $T_\\mathrm{inner}$ (from the previous calculation), at the photosphere, we have $\\lambda_\\mathrm{peak,inner}=\\frac{b}{T_\\mathrm{inner}}$. Now, when the ejecta is moving at a velocity $v$, $\\lambda_\\mathrm{peak}$ is doppler shifted (in more technical language, we find the peak wavelength in the co-moving frame, see [reference frames](../montecarlo/propagation.rst#reference-frames)). The doppler factor is (approximately) $1-\\frac{\\Delta v}{c}$ where $\\Delta v$ is the difference between $v$ and the velocity at the photosphere (i.e. $\\Delta v = v-v_\\mathrm{boundary\\_inner}$). So,\n", + "Since we know $T_\\mathrm{inner}$ (from the previous calculation), at the photosphere, we have $\\lambda_\\mathrm{peak,inner}=\\frac{b}{T_\\mathrm{inner}}$. Now, when the ejecta is moving at a velocity $v$, $\\lambda_\\mathrm{peak}$ is doppler shifted (in more technical language, we find the peak wavelength in the co-moving frame, see [reference frames](../montecarlo/propagation.rst#reference-frames)). The doppler factor is (approximately) $1+\\frac{\\Delta v}{c}$ where $\\Delta v$ is the difference between $v$ and the velocity at the photosphere (i.e. $\\Delta v = v-v_\\mathrm{boundary\\_inner}$). So,\n", "\n", - "$$\\lambda_\\mathrm{peak}(v)=\\left(1-\\frac{v-v_\\mathrm{boundary\\_inner}}{c}\\right)\\lambda_\\mathrm{peak,inner}=\\left(1-\\frac{v-v_\\mathrm{boundary\\_inner}}{c}\\right)\\frac{b}{T_\\mathrm{inner}}.$$\n", + "$$\\lambda_\\mathrm{peak}(v)=\\left(1+\\frac{v-v_\\mathrm{boundary\\_inner}}{c}\\right)\\lambda_\\mathrm{peak,inner}=\\left(1+\\frac{v-v_\\mathrm{boundary\\_inner}}{c}\\right)\\frac{b}{T_\\mathrm{inner}}.$$\n", "\n", "Thus, the temperature at a velocity $v$ is\n", "\n", - "$$T(v)=\\frac{b}{\\lambda_\\mathrm{peak}(v)}=\\frac{T_\\mathrm{inner}}{1-\\frac{v-v_\\mathrm{boundary\\_inner}}{c}}.$$\n", + "$$T_\\mathrm{rad}(v)=\\frac{b}{\\lambda_\\mathrm{peak}(v)}=\\frac{T_\\mathrm{inner}}{1+\\frac{v-v_\\mathrm{boundary\\_inner}}{c}}.$$\n", "\n", "As with density, the radiative temperature is modeled as constant throughout the shell, so we determine the temperature of the shell based on the ejecta's velocity at the center of the shell.\n", "\n", @@ -527,15 +529,15 @@ "t_rad_config.model.structure.velocity.stop = 2000 * u.km/u.s\n", "t_rad_config.model.structure.velocity.num = 20\n", "\n", - "t_rad_model = Radial1DModel.from_config(t_rad_config)\n", + "t_radiative_simulation_state = SimulationState.from_config(t_rad_config, atom_data=atom_data)\n", "\n", - "print('t_inner:\\n', t_rad_model.t_inner)\n", - "print('t_rad:\\n', t_rad_model.t_rad)\n", + "print('t_inner:\\n', t_radiative_simulation_state.t_inner)\n", + "print('t_rad:\\n', t_radiative_simulation_state.t_radiative)\n", "\n", - "plt.plot(t_rad_model.r_middle, t_rad_model.t_rad)\n", - "plt.scatter(t_rad_model.radius[0], t_rad_model.t_inner)\n", - "plt.xlabel(f'Radius ({t_rad_model.r_middle.unit})')\n", - "plt.ylabel(f'Radiative Temperature ({t_rad_model.t_rad.unit})');" + "plt.plot(t_radiative_simulation_state.r_middle, t_radiative_simulation_state.t_radiative)\n", + "plt.scatter(t_radiative_simulation_state.radius[0], t_radiative_simulation_state.t_inner)\n", + "plt.xlabel(f'Radius ({t_radiative_simulation_state.r_middle.unit})')\n", + "plt.ylabel(f'Radiative Temperature ({t_radiative_simulation_state.t_radiative.unit})');" ] }, { @@ -551,12 +553,12 @@ "\n", "Using geometry (in 3D, where the photosphere in the figure is a sphere, not a circle), the fraction of the point's \"field of view\" taken up by the sphere is\n", "\n", - "$$\\frac{1}{2}\\sqrt{1-\\frac{r_\\mathrm{boundary\\_inner}^2}{r^2}}$$\n", + "$$\\frac{1}{2}\\left(1-\\sqrt{1-\\frac{r_\\mathrm{boundary\\_inner}^2}{r^2}}\\right)$$\n", "\n", "where $r_\\mathrm{boundary\\_inner}$ is the radius of the circle in the picture (the photosphere in terms of TARDIS). This is the geometric dilution factor.\n", "\n", "\n", - "Like the radiative temperature, the dilution factor in each cell changes throughout the simulation based on the light-matter interactions (see [Estimators and Convergence](../est_and_conv/index.ipynb)). TARDIS uses the geometric dilution factor as the initial guess for the dilution factor in each cell, plugging in the radius at the center of the cell to determine the initial dilution factor in the cell. \n", + "Like the radiative temperature, the dilution factor in each cell changes throughout the simulation based on the light-matter interactions (see [Updating Plasma and Convergence](../update_and_conv/update_and_conv.ipynb)). TARDIS uses the geometric dilution factor as the initial guess for the dilution factor in each cell, plugging in the radius at the center of the cell to determine the initial dilution factor in the cell. \n", "\n", "<div class=\"alert alert-info\">\n", " \n", @@ -578,24 +580,24 @@ }, "outputs": [], "source": [ - "w_config = copy.deepcopy(base_config)\n", + "dilution_factor_config = copy.deepcopy(base_config)\n", "\n", - "w_config.supernova.time_explosion = 10 * u.day\n", + "dilution_factor_config.supernova.time_explosion = 10 * u.day\n", "\n", "# This line is necessary to indicate we are using a built-in shell structure\n", "# and density. Do not change it.\n", - "w_config.model.structure.type = 'specific'\n", + "dilution_factor_config.model.structure.type = 'specific'\n", "\n", - "w_config.model.structure.velocity.start = 1000 * u.km/u.s\n", - "w_config.model.structure.velocity.stop = 2000 * u.km/u.s\n", - "w_config.model.structure.velocity.num = 20\n", + "dilution_factor_config.model.structure.velocity.start = 1000 * u.km/u.s\n", + "dilution_factor_config.model.structure.velocity.stop = 2000 * u.km/u.s\n", + "dilution_factor_config.model.structure.velocity.num = 20\n", "\n", - "w_model = Radial1DModel.from_config(w_config)\n", + "dilution_factor_simulation_state = SimulationState.from_config(dilution_factor_config, atom_data=atom_data)\n", "\n", - "print('w:\\n', w_model.w)\n", + "print(f'dilution_factor: {dilution_factor_simulation_state.dilution_factor}')\n", "\n", - "plt.plot(w_model.r_middle, w_model.w)\n", - "plt.xlabel(f'Radius ({w_model.r_middle.unit})')\n", + "plt.plot(dilution_factor_simulation_state.r_middle, dilution_factor_simulation_state.dilution_factor)\n", + "plt.xlabel(f'Radius ({dilution_factor_simulation_state.r_middle.unit})')\n", "plt.ylabel(f'Dilution Factor');" ] } @@ -616,7 +618,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.12" + "version": "3.8.16" } }, "nbformat": 4, diff --git a/docs/physics/setup/plasma/helium_nlte.rst b/docs/physics/setup/plasma/helium_nlte.rst index 99267d6de20..b328c4b9b4a 100644 --- a/docs/physics/setup/plasma/helium_nlte.rst +++ b/docs/physics/setup/plasma/helium_nlte.rst @@ -3,7 +3,7 @@ Helium NLTE The `helium_treatment` setting in the TARDIS config. file will accept one of three options: * `none`: The default setting. Populate helium in the same way as the other elements. - * `recomb-nlte`: Treats helium in NLTE using the analytical approximation outlined in an upcoming paper. + * `recomb-nlte`: Treats helium in NLTE using the analytical approximation outlined in :cite:`Boyle2017`. * `numerical-nlte`: To be implemented. Will allow the use of a separate module (not distributed with TARDIS) to perform helium NLTE calculations numerically. Recombination He NLTE @@ -25,7 +25,7 @@ Symbols/Indexing: n_{2,0,0} = 0 .. math:: - n_{2,0,k}~(k\geq1) = n_{2,1,0}\times n_{e}\times\frac{1}{W}\times\frac{g_{2,0,k}}{2g_{2,1,0}}\times\left(\frac{h^{2}}{2\pi m_{e}kT_{r}}\right)^{3/2}\times\exp{\left(\frac{\chi_{2,1}-\epsilon_{2,0,k}}{kT_{r}}}\right)\times\left(\frac{T_{r}}{T_{e}}\right)^{1/2} + n_{2,0,k}~(k\geq1) = n_{2,1,0}\times n_{e}\times\frac{1}{W}\times\frac{g_{2,0,k}}{2g_{2,1,0}}\times\left(\frac{h^{2}}{2\pi m_{e}kT_{r}}\right)^{3/2}\times\exp{\left(\frac{\chi_{2,1}-\epsilon_{2,0,k}}{kT_{r}}\right)}\times\left(\frac{T_{r}}{T_{e}}\right)^{1/2} (Note: An extra factor of :math:`\frac{1}{W}` is included for the metastable states of He I.) @@ -48,4 +48,4 @@ In the TARDIS plasma, some of these equations are re-written slightly to make us Numerical He NLTE ------------------ -Another `helium_treatment` option offered by TARDIS is `numerical-nlte`. The use of this plasma property requires an additional code that is the property of Stephan Hachinger (see arXiv:1201.1506) and is not distributed with TARDIS. TARDIS also requires a specific atomic datafile to use this module. This plasma option is included so that people who have access to and permission to use the necessary module may use it. Otherwise, the `recomb-NLTE` option provides a very accurate alternative approximation. \ No newline at end of file +Another `helium_treatment` option offered by TARDIS is `numerical-nlte`. The use of this plasma property requires an additional code that is the property of Stephan Hachinger (see arXiv:1201.1506) and is not distributed with TARDIS. TARDIS also requires a specific atomic datafile to use this module. This plasma option is included so that people who have access to and permission to use the necessary module may use it. Otherwise, the `recomb-NLTE` option provides a very accurate alternative approximation. diff --git a/docs/physics/setup/plasma/index.rst b/docs/physics/setup/plasma/index.rst index e54e1e0dccc..359c7585a98 100644 --- a/docs/physics/setup/plasma/index.rst +++ b/docs/physics/setup/plasma/index.rst @@ -37,7 +37,12 @@ Every property has a `calculate` function that returns the values of its outputs The Plasma Graph ---------------- -If the necessary Python modules (`PyGraphviz <https://pygraphviz.github.io/>`_ and `dot2tex <https://dot2tex.readthedocs.io/en/latest/>`_) are available, TARDIS will automatically output a .tex file at the beginning of each run that can be compiled to produce a PDF image of the plasma module graph. The nodes on this graph are the names of plasma properties, e.g. `Levels`, `TauSobolev`, `IonNumberDensity`, along with a list of outputs from those properties and equations showing how they are calculated. These nodes are connected by arrows linking nodes with the sources of their inputs, and labelled with the name of the input/output linking the two properties, e.g. `levels`, :math:`\tau_{\textrm{sobolev}}`, :math:`n_{e}`. +If the necessary Python modules (`PyGraphviz <https://pygraphviz.github.io/>`_ and `dot2tex <https://dot2tex.readthedocs.io/en/latest/>`_) are available, TARDIS can output a .dot and a .tex file at the beginning of each run that can be compiled to produce a PDF image of the plasma module graph via the :code:`write_to_dot()` and :code:`write_to_tex()` functions, respectively. The nodes on this graph are the names of plasma properties, e.g. `Levels`, `TauSobolev`, `IonNumberDensity`, along with a list of outputs from those properties. These nodes are connected by edges linking them with the sources of their inputs. The .tex file contains the name of the input/output linking the properties (e.g. `levels`, :math:`\tau_{\textrm{sobolev}}`, :math:`n_{e}`), as well as the equations used to calculate them, written in LaTeX. See the tutorial below! + +.. toctree:: + :maxdepth: 2 + + ../../../io/output/plasma_graph Updating the Plasma ------------------- @@ -68,6 +73,9 @@ The next more complex class is `LTEPlasma` which will calculate the ionization b TARDIS also allows for NLTE treatments of specified species, as well as special NLTE treatments for Helium. +.. note:: + The NLTE treatment of specified species is currently incompatible with the NLTE treatment for helium and cannot be used simultaneously. + .. toctree:: :maxdepth: 2 @@ -100,4 +108,4 @@ The following page describes the macro atom treatment of line interactions: .. toctree:: :maxdepth: 2 - macroatom \ No newline at end of file + macroatom diff --git a/docs/physics/setup/plasma/lte_plasma.rst b/docs/physics/setup/plasma/lte_plasma.rst index c7c831cdcbe..ce06d924651 100644 --- a/docs/physics/setup/plasma/lte_plasma.rst +++ b/docs/physics/setup/plasma/lte_plasma.rst @@ -25,7 +25,7 @@ In the second step (`LTEPlasma.calculate_ionization_balance`), we calculate in a N(X) &= N_1 + N_2 + N_3 + \dots\\ N(X) &= N_1 + \frac{N_2}{N_1} N_1 + \frac{N_3}{N_2}\frac{N_2}{N_1} N_1 + \frac{N_4}{N_3}\frac{N_3}{N_2}\frac{N_2}{N_1} N_1 + \dots\\ N(X) &= N_1 (1 + \frac{N_2}{N_1} + \frac{N_3}{N_2}\frac{N_2}{N_1} + \frac{N_4}{N_3}\frac{N_3}{N_2}\frac{N_2}{N_1} + \dots)\\ - N(X) &= N_1 \underbrace{(1 + \frac{\Phi_{i, 2/1}}{N_e} + \frac{\Phi_{i, 2/2}}{N_e}\frac{\Phi_{i, 2/1}}{N_e} + + N(X) &= N_1 \underbrace{(1 + \frac{\Phi_{i, 2/1}}{N_e} + \frac{\Phi_{i, 3/2}}{N_e}\frac{\Phi_{i, 2/1}}{N_e} + \frac{\Phi_{i, 4/3}}{N_e}\frac{\Phi_{i, 3/2}}{N_e}\frac{\Phi_{i, 2/1}}{N_e} + \dots)}_{\alpha}\\ N_1 &= \frac{N(X)}{\alpha} diff --git a/docs/physics/setup/plasma/macroatom.rst b/docs/physics/setup/plasma/macroatom.rst index 523a0baecc6..da0dd590686 100644 --- a/docs/physics/setup/plasma/macroatom.rst +++ b/docs/physics/setup/plasma/macroatom.rst @@ -3,7 +3,7 @@ Macro Atom ---------- -The macro atom is described in detail in :cite:`Lucy2002`. The basic principal is that when an energy packet +The macro atom is described in detail in :cite:`Lucy2002`. The basic principle is that when an energy packet is absorbed that the macro atom is on a certain level. Three probabilities govern the next step the P\ :sub:`up`, P\ :sub:`down` and P\ :sub:`down emission` being the probability for going to a higher level, a lower level and a lower level and emitting a photon while doing this respectively (see Figure 1 in :cite:`Lucy2002` ). @@ -11,7 +11,7 @@ level and emitting a photon while doing this respectively (see Figure 1 in :cite The macro atom is the most complex idea to implement as a data structure. The setup is done in `~tardisatomic`, but we will nonetheless discuss it here (as `~tardisatomic` is even less documented than this one). -For each level, we look at the line list to see what transitions (upwards or downwards are possible). We create a two arrays, +For each level, we look at the line list to see what transitions (upwards or downwards is possible). We create two arrays, the first is a long one-dimensional array containing the probabilities. Each level contains a set of probabilities. The first part of each set contains the upwards probabilities (internal upward), the second part the downwards probabilities (internal downward), and the last part is the downward and emission probability. @@ -28,7 +28,7 @@ The second array is for book-keeping; it has exactly the length as levels (with +--------+------------------+------------+----------------+-----------------+ -We now will calculate the transition probabilites, using the radiative rates in Equation 20, 21, and 22 +We now will calculate the transition probabilities, using the radiative rates in Equation 20, 21, and 22 in :cite:`Lucy2002`. Then we calculate the downward emission probability from Equation 5, the downward and upward internal transition probabilities in :cite:`Lucy2003`. diff --git a/docs/physics/setup/setup_example.ipynb b/docs/physics/setup/setup_example.ipynb index c588a8e3271..04f54704cbf 100644 --- a/docs/physics/setup/setup_example.ipynb +++ b/docs/physics/setup/setup_example.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "77634745", "metadata": {}, @@ -18,7 +19,7 @@ "outputs": [], "source": [ "# We import the necessary packages\n", - "from tardis.io.config_reader import Configuration\n", + "from tardis.io.configuration.config_reader import Configuration\n", "from tardis.simulation import Simulation\n", "from tardis.io.atom_data.util import download_atom_data\n", "\n", @@ -27,11 +28,12 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "97737e54", "metadata": {}, "source": [ - "We read a configuration as shown [here](../../io/configuration/read_configuration.ipynb):" + "We read a configuration as shown [here](../../io/configuration/tutorial_read_configuration.ipynb):" ] }, { @@ -45,6 +47,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "168f583c", "metadata": {}, @@ -64,11 +67,12 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "e3f86364", "metadata": {}, "source": [ - "When the `Simulation` object is created, a `Radial1DModel`, `BasePlasma`, and `MonteCarloRunner` object are created and stored as attributes of the `Simulation` object." + "When the `Simulation` object is created, a `SimulationState`, `BasePlasma`, and `MontecarloTransport` object are created and stored as attributes of the `Simulation` object." ] }, { @@ -78,7 +82,7 @@ "metadata": {}, "outputs": [], "source": [ - "sim.model" + "sim.simulation_state" ] }, { @@ -98,7 +102,7 @@ "metadata": {}, "outputs": [], "source": [ - "sim.runner" + "sim.transport" ] } ], diff --git a/docs/physics/spectrum/basic.ipynb b/docs/physics/spectrum/basic.ipynb index fb8b59df817..8a1ba43bd93 100644 --- a/docs/physics/spectrum/basic.ipynb +++ b/docs/physics/spectrum/basic.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "1a955596", "metadata": {}, @@ -29,6 +30,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f5196349", "metadata": {}, @@ -43,9 +45,9 @@ "metadata": {}, "outputs": [], "source": [ - "from tardis.io.config_reader import Configuration\n", + "from tardis.io.configuration.config_reader import Configuration\n", "from tardis.simulation import Simulation\n", - "from tardis.montecarlo import TARDISSpectrum\n", + "from tardis.spectrum import TARDISSpectrum\n", "from tardis.io.atom_data.util import download_atom_data\n", "from astropy import units as u\n", "import numpy as np\n", @@ -76,6 +78,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f169c41b", "metadata": {}, @@ -100,6 +103,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "de4cd415", "metadata": {}, @@ -114,7 +118,7 @@ "metadata": {}, "outputs": [], "source": [ - "nus = sim.runner.output_nu\n", + "nus = sim.transport.transport_state.output_nu\n", "nus" ] }, @@ -125,11 +129,12 @@ "metadata": {}, "outputs": [], "source": [ - "energies = sim.runner.output_energy\n", + "energies = sim.transport.transport_state.output_energy\n", "energies" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "6fc8a089", "metadata": {}, @@ -148,6 +153,22 @@ ] }, { + "attachments": {}, + "cell_type": "markdown", + "id": "70c979d2", + "metadata": {}, + "source": [ + "<div class=\"alert alert-info\">\n", + "\n", + "Note\n", + "\n", + "The energies used for the spectrum are in the lab frame (see [Reference Frames](../montecarlo/propagation.rst#reference-frames)). Recall that while packets are all initialized with the same energy in the lab frame, throughout the simulation energy is conserved in the co-moving frame, allowing the lab frame energies of the packets to change though interactions (see [Performing an Interaction](../montecarlo/propagation.rst#performing-an-interaction)), creating the varied lab-frame energies that we see at the end of the simulation.\n", + " \n", + "</div>" + ] + }, + { + "attachments": {}, "cell_type": "markdown", "id": "54466d70", "metadata": {}, @@ -162,11 +183,12 @@ "metadata": {}, "outputs": [], "source": [ - "luminosities = energies / sim.runner.time_of_simulation\n", + "luminosities = energies / sim.transport.transport_state.time_of_simulation\n", "luminosities" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "e10d9567", "metadata": {}, @@ -181,7 +203,7 @@ "metadata": {}, "outputs": [], "source": [ - "emitted_mask = sim.runner.emitted_packet_mask\n", + "emitted_mask = sim.transport.transport_state.emitted_packet_mask\n", "emitted_mask" ] }, @@ -208,6 +230,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f7cc4807", "metadata": {}, @@ -226,6 +249,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2a29c4c9", "metadata": {}, @@ -246,6 +270,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ee595852", "metadata": {}, @@ -262,6 +287,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "dbc69e96", "metadata": {}, @@ -287,6 +313,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2e375d04", "metadata": {}, @@ -309,6 +336,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "30e8090a", "metadata": {}, @@ -328,6 +356,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "12663ddd", "metadata": {}, @@ -344,12 +373,13 @@ "source": [ "emitted_luminosity_hist = u.Quantity(np.histogram(emitted_nus,\n", " weights=emitted_luminosities,\n", - " bins=spectrum_frequency.value,\n", + " bins=spectrum_frequency,\n", " )[0], \"erg / s\",)\n", "emitted_luminosity_hist" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "59c0fbfd", "metadata": {}, @@ -388,6 +418,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "a53e2b79", "metadata": {}, @@ -396,25 +427,26 @@ "\n", "Note\n", "\n", - "Most of this process is done internally by TARDIS. Given a simulation object `sim` that has been run, calling `sim.runner.spectrum` will give you a `TARDISSpectrum` object that can then be plotted using the `.plot()` method. See, for example, our [Quickstart Guide](../../quickstart.ipynb). This notebook just demonstrates how TARDIS generates this spectrum when `sim.runner.spectrum` is called.\n", + "Most of this process is done internally by TARDIS. Given a simulation object `sim` that has been run, calling `sim.transport.spectrum` will give you a `TARDISSpectrum` object that can then be plotted using the `.plot()` method. See, for example, our [Quickstart Guide](../../quickstart.ipynb). This notebook just demonstrates how TARDIS generates this spectrum when `sim.transport.spectrum` is called.\n", "\n", "</div>" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "49b60fed", "metadata": {}, "source": [ "You may notice that the bins are not uniformly spaced with respect to wavelength. This is because we use the same bins for both wavelength and frequency, and thus the bins which are uniformly spaced with respect to frequency are not uniformly spaced with respect to wavelength. This is okay though, since luminosity density allows us to alter the bins without significantly altering the graph!\n", "\n", - "Another thing you may notice in these graphs is the lack of a smooth curve. This is due to **noise**: the effects of the random nature of Monte Carlo simulations. This makes it very difficult to get a precise spectrum without drastically increasing the number of Monte Carlo packets. To solve this problem, TARDIS uses [virtual packets](virtualpackets.rst) and [the formal integral method](sourceintegration.rst) to generate a spectrum with less noise." + "Another thing you may notice in these graphs is the lack of a smooth curve. This is due to **noise**: the effects of the random nature of Monte Carlo simulations. This makes it very difficult to get a precise spectrum without drastically increasing the number of Monte Carlo packets. To solve this problem, TARDIS uses [virtual packets](virtualpackets.rst) and [the formal integral method](formal_integral.rst) to generate a spectrum with less noise." ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -428,7 +460,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/docs/physics/spectrum/formal_integral.rst b/docs/physics/spectrum/formal_integral.rst new file mode 100644 index 00000000000..0d58b9c44eb --- /dev/null +++ b/docs/physics/spectrum/formal_integral.rst @@ -0,0 +1,144 @@ +.. _formal_integral: + +******************************************** +Spectrum Generation with the Formal Integral +******************************************** + +:cite:`Lucy1999a` describes an alternative method for calculating the TARDIS spectrum while eliminating nearly all Monte Carlo noise. Instead of calculating the spectrum directly from the Monte Carlo (or virtual) packets, we use information from the Monte Carlo simulation to build an analytical solution for the supernova spectrum. + +.. warning:: + + The current implementation of the formal integral has several limitations. + Please consult the corresponding section below to ensure that these + limitations do not apply to your TARDIS. + + +Deriving the Integral +===================== + +The spectrum generated by TARDIS includes light that is released in all directions. However, we approximate the supernova as spherically symmetric, meaning the light is released isotropically (equally in all directions). Thus, it will suffice to calculate the spectrum of light propagating in a single direction, call it the positive z-direction, and then sum over every direction. Specifically, we have + +.. math:: L_\nu = \int L_{\nu z} d\Omega = L_{\nu z} \int d\Omega = 4\pi L_{\nu z} + +where :math:`L_\nu` is the luminosity density at a frequency :math:`\nu`, :math:`L_{\nu z}` is the luminosity density at a frequency :math:`\nu` for light propagating in the positive z-direction, and :math:`\Omega` is the solid angle. + +We now must calculate :math:`L_{\nu z}`, starting with more symmetry considerations. The figures below show various rays of light (in black) coming out of the supernova at various values of :math:`p`, the impact parameter (defined as the distance from the x-axis, and can be seen as the value along the blue :math:`p`-axis). By symmetry, the intensity :math:`I_\nu` (luminosity density per unit area) along the ray will be identical anywhere on the blue circles shown (each of which has a constant impact parameter). Each circle has a circumference of :math:`2\pi p`. The luminosity density per unit distance on any given circle would then be :math:`I_\nu(p)\times 2\pi p` (specifically, we are integrating the constant intensity around the circumference of the circle). Finally, to get :math:`L_{\nu z}`, we must integrate :math:`I_\nu(p)\times 2\pi p` over every possible impact parameter, whose values range from zero to the outer radius of the supernova, :math:`r_\mathrm{boundary\_outer}`. So, + +.. math:: L_{\nu z} = \int_0^{r_\mathrm{boundary\_outer}} I_\nu(p)\times 2\pi p dp = 2\pi \int_0^{r_\mathrm{boundary\_outer}} I_\nu(p) p dp. + +Putting this all together, we get + +.. math:: L_\nu = 8\pi^2 \int_0^{r_\mathrm{boundary\_outer}} I_\nu(p) p dp. + +.. note:: + + A separate integral must be done for each frequency. + +.. image:: ../images/formal_integral_sphere.jpg + :width: 1000 + + +Summary of Implementation +========================= + +Since there is a continuum of frequencies represented in a spectrum, the formal integral cannot calculate the luminosity density at *every* frequency. Instead, we calculate :math:`L_\nu` at a finite number of frequencies between the ``start`` and ``stop`` wavelengths provided in the :ref:`spectrum-config` (converting between frequency and wavelength using :math:`\nu=\frac{c}{\lambda}` where :math:`\lambda` is wavelength and :math:`c` is the speed of light) to give us an approximate spectrum. The number of frequencies we use is the ``num`` argument in the configuration. The frequencies are evenly spaced **in wavelength space** (exactly like histogram bins in :doc:`basic` -- see near the bottom of that page for more information). + +Similarly, when doing the integral for a particular frequency, there is a continuum of impact parameters, so we cannot calculate :math:`I_\nu(p)` for every single one. We instead use a finite list of impact parameters between 0 and the supernova's outer boundary. The number of impact parameters we use is the value of ``points`` provided in the ``integrated`` section of the spectrum configuration. + +For each frequency in our list of frequencies, TARDIS calculates :math:`I_\nu(p)` for each :math:`p` in the list of impact parameters, and then performs the integral :math:`\int_0^{r_\mathrm{boundary\_outer}} I_\nu(p) p dp` using `trapezoid integration <https://en.wikipedia.org/wiki/Trapezoidal_rule>`_. Our result is then multiplied by :math:`8\pi^2` to get the correct luminosity density. The most involved part of the calculation is calculating :math:`I_\nu(p)` for every combination of :math:`\nu` in the list of frequencies and :math:`p` in the list of impact parameters. This step is described in detail in the following section: + + +Calculating :math:`I_\nu(p)` +============================ + +Setting Up +---------- + +We now calculate :math:`I_\nu(p)`, which is the intensity of the light with a **lab frame** (see :ref:`referenceframes`) frequency :math:`\nu` exiting a the supernova along a ray with impact parameter :math:`p`, as shown in the diagram below (we use the lab frame frequency as that is the frame in which the spectrum is observed). Specifically, we are looking for the intensity of light with a frequency :math:`\nu` traveling to the right on the right side of the ray. We start by discussing the case where :math:`p>r_\mathrm{boundary\_inner}` (where the ray does not intersect the photosphere). After, we will comment on what occurs when :math:`p<r_\mathrm{boundary\_inner}`. + +.. image:: ../images/formal_integral_2d_above.png + +Since every point on the ray has the same lab frame frequency, the co-moving frequency will vary along the ray. Specifically, at the point :math:`z_k`, we have + +.. math:: \nu_{\mathrm{co-moving},k}=(1-\beta_k \mu_k)\nu = \left( 1-\frac{r_k \cos(\theta)}{ct_\mathrm{explosion}}\right) \nu. + +But, :math:`\cos(\theta)=\frac{z_k}{r_k}`, so + +.. math:: \nu_{\mathrm{co-moving},k}= \left( 1-\frac{z_k}{ct_\mathrm{explosion}}\right) \nu. + +Notice that the co-moving frequency decreases as you move farther to the right, i.e. as the z-coordinate increases. With this, we can see where along the ray each line resonance occurs -- a line with a frequency :math:`\nu_\mathrm{line}` (which comes into resonance in the co-moving frame) will come into resonance at :math:`z=ct_\mathrm{explosion}\left(1-\frac{\nu_\mathrm{line}}{\nu}\right)`. The highest line frequency that can resonate on our ray is :math:`\nu_\mathrm{max}=\left(1-\frac{z_\mathrm{min}}{ct_\mathrm{explosion}}\right)\nu`, and the lowest line frequency that can resonate on our ray is :math:`\nu_\mathrm{min}=\left(1-\frac{z_\mathrm{max}}{ct_\mathrm{explosion}}\right)\nu`, where :math:`z_\mathrm{max}=\sqrt{r_\mathrm{boundary\_outer}^2-p^2}` and by symmetry :math:`z_\mathrm{min}=-z_\mathrm{max}`. Every line between those frequencies will resonate on our ray -- the points at which each line resonates is shown on the diagram (though in reality there are far more resonances than in this shown in this example diagram). The line resonating at the point :math:`z_0` has the highest frequency of any line with a frequency below :math:`\nu_\mathrm{max}`, and the line resonating at the point :math:`z_{N-1}` (the Nth line) has the highest frequency of any line with a frequency above :math:`\nu_\mathrm{min}`. Finally, we denote the intensity along the ray directly to the left of a point :math:`z_k` as :math:`I_k^b` with "b" for blue, as it has a slightly higher ("bluer") frequency than the line resonating at :math:`z_k`. Similarly, we denote the intensity along the ray directly to the right of a point :math:`z_k` as :math:`I_k^r` with "r" for red, as it has a slightly lower ("redder") frequency than the line resonating at :math:`z_k`. + +Our goal is to find :math:`I_{N-1}^r`, as this is the light that will exit the supernova. We start with :math:`I_0^b=0` (as we assume no light is entering the supernova externally). We then increment the intensity along the ray. To do this, we will need the line source function. + + +Constructing the Source Function +-------------------------------- + +Our problem is to determine the intensity that is added to the ray at a line resonance :math:`l\rightarrow u` based on the Monte Carlo packets. + +Consider another transition :math:`i\rightarrow u`. We know (see :ref:`edotlu`) that the rate at which energy density interacts with the transition is :math:`\dot{E}_{iu}`, i.e. the ``Edotlu`` estimator for the transition :math:`i\rightarrow u`. Now, sum up these estimators for every level :math:`i` that can be excited to the level :math:`u` -- this will give us the rate at which energy density is added to the level :math:`u` from all line transitions that can be excited to :math:`u`: + +.. math:: \dot{E}_u = \sum_{i < u} \dot E_{iu}. + +The rate at which energy density is then de-excited from :math:`u\rightarrow l` (and thus be deposited into the ray's intensity at the resonance point of :math:`l\rightarrow u`) is :math:`q_{ul}\dot{E}_u`, where :math:`q_{ul}` is the fraction of energy at the level :math:`u` which de-excites in the transition :math:`u\rightarrow l`. To turn this into the intensity added to the ray at a resonance point, for reasons presented in :cite:`Lucy1999a`, we include a factor of :math:`\frac{\lambda_{ul} t_\mathrm{explosion}}{4 \pi}` where :math:`\lambda_{ul}` is the wavelength of the light released in the transition :math:`u\rightarrow l`. So, the intensity that is added to our ray at the resonance point of :math:`l\rightarrow u`, which we will label as :math:`\left( 1- e^{-\tau_{lu}}\right) S_{ul}`, is + +.. math:: \left( 1- e^{-\tau_{lu}}\right) S_{ul} = \frac{\lambda_{ul} t}{4 \pi} q_{ul}\dot E_u. + +Here, :math:`S_{ul}` is the source function -- interpret it as the intensity that is eligible to interact and end up on our ray (i.e. the source of the intensity that ends up on our ray). The actual intensity that ends up being added to the ray is the source function times the probability of the transition :math:`l\rightarrow u`, which is :math:`\left( 1- e^{-\tau_{lu}}\right)`. + + +Incrementing the Intensity +-------------------------- + +With this, we can now show how the intensity along our ray is incremented. First, at the kth line resonance there is an :math:`e^{-\tau_{k}}` probability that light does not interact with the line. So, on the red side of the line we only have :math:`e^{-\tau_k}` times the intensity on the blue side. But, we also have an intensity :math:`\left(1- e^{-\tau_k}\right) S_k` that is added to the ray at the line resonance, so in total we have + +.. math:: I_k^r = I_k^b e^{-\tau_k} + \left( 1- e^{-\tau_k}\right) S_{k}. + +If there is no electron scattering, this would be it; we would have :math:`I^b_{k+1}=I^r_k` (the intensity on the left of a line would be the intensity on the right of the next line, since no interactions would take place between the locations of line resonances). However, with electron scattering, this is not the case. In between line resonances, light has a probability of :math:`e^{-\Delta \tau_e}` of not scattering, where :math:`\Delta \tau_e=\sigma_{\mathrm{T}} n_e \Delta z` is the electron scattering optical depth (see :ref:`physical-interactions`). So, we would have :math:`I^b_{k+1}=I^r_ke^{-\Delta \tau_e}`. But, light can also scatter onto the ray. The intensity is increased by the mean intensity between the two resonance points times the probability of light scattering (and thus ending up on the ray), this probability being :math:`1-e^{-\Delta \tau_e}`. For the intensity between :math:`z_k` and :math:`z_{k+1}` we use the average of the mean intensity to the right of :math:`z_k` and the mean intensity to the left of :math:`z_{k+1}`, which is :math:`\frac{1}{2}\left(J_k^r+J_{k+1}^b\right)`. Here, :math:`J^b_{k}` is calculated from the ``j_blue`` estimator for the kth line transition (see :ref:`j-blue-estimator`), and then + +.. math:: J_k^r = J_k^b e^{-\tau_k} + \left( 1- e^{-\tau_k}\right) S_{k} + +for the same reasoning as before (since :math:`J`, like :math:`I`, is an intensity and thus by identical logic is increased by :math:`\left( 1- e^{-\tau_k}\right) S_{k}` at line resonances). + +This gives us + +.. math:: I_{k+1}^b = I_k^r e^{-\Delta \tau_e} + (1-e^{-\Delta \tau_e})*\frac{1}{2}\left(J_k^r+J_{k+1}^b\right). + +Note that here the mean intensity is acting as the source function. The final step, for computational ease, approximates :math:`e^{-\Delta \tau_e}\approx 1-\Delta \tau_e` since the resonance points will be so close together that :math:`\Delta \tau_e << 1`. Our final result is then + +.. math:: I_{k+1}^b = I_k^r + \Delta \tau_e \left[ \frac{1}{2}\left(J_k^r + J_{k+1}^b\right) - I_k^r \right]. + + +**In summary**, when calculating :math:`I_\nu(p)` for some ray, we start with :math:`I_0^b=0` and then calculate :math:`I_0^r`, then :math:`I_1^b`, then :math:`I_1^r`, etc. via the relations + +.. math:: I_k^r = I_k^b e^{-\tau_k} + \left( 1- e^{-\tau_k}\right) S_{k} + +.. math:: I_{k+1}^b = I_k^r + \Delta \tau_e \left[ \frac{1}{2}\left(J_k^r + J_{k+1}^b\right) - I_k^r \right] + +until we get to :math:`I_{N-1}^r`, which is then used as the value of :math:`I_\nu(p)` that goes into the integral :math:`L_\nu = 8\pi^2 \int_0^{r_\mathrm{boundary\_outer}} I_\nu(p) p dp`. + +.. note:: The values for the source function (and the quantities and estimators used to calculate it), Sobolev optical depths, electron densities, the mean intensity, and all other non-constant quantities are taken in the cell in which the line resonance takes place. However, to improve results, TARDIS breaks down the model into more cells than used in the rest of the simulation and interpolates the values of these quantities. The number of shells TARDIS uses for this interpolation process is specified in the :doc:`spectrum configuration <../../io/configuration/components/spectrum>`. + + +Rays Intersecting the Photosphere +--------------------------------- + +Since the photosphere is modeled as being optically thick, if a ray intersects the photosphere, anything that happens prior to the photosphere does not matter -- the photosphere absorbs all light that hits it. Because of this, to calculate :math:`I_\nu(p)` over a ray that starts by exiting the photosphere, we must slightly adjust our approach, as shown in the diagram below. In this case, we now have that the minimum z-coordinate is :math:`z_\mathrm{min}=\sqrt{r_\mathrm{boundary\_inner}^2-p^2}`, and we use this to determine the lowest possible resonant frequency on the ray as before, which will then give us :math:`z_0`, as it did before. Finally, since light along this ray is released from the photosphere, we have + +.. math:: I_0^b = B_\nu(T_\mathrm{inner})= \frac{2h}{c^2}\frac{\nu^3}{e^{h\nu/k_BT}-1}. + +which is the Planck function (see :doc:`../montecarlo/initialization`). After making those small adjustments, we increment the intensity exactly as in the other case. + +.. image:: ../images/formal_integral_2d_below.png + :width: 700 + + +Current Limitations +=================== + +The current implementation of the formal integral has some limitations: + +* Once electron scattering is included, the scheme only produces accurate results when many resonances occur on the rays. This is simply because otherwise the average of :math:`J^b` and :math:`J^r` does not provide an accurate representation of the mean intensity between successive resonance points. Also, :math:`d\tau` can become large which can create unphysical, negative intensities. + +It is always advised to check the results of the formal integration against the +spectrum constructed from the emerging Monte Carlo packets. diff --git a/docs/physics/spectrum/index.rst b/docs/physics/spectrum/index.rst index aaa7a9b242d..3de45aaa376 100644 --- a/docs/physics/spectrum/index.rst +++ b/docs/physics/spectrum/index.rst @@ -17,4 +17,4 @@ below. .. toctree:: basic virtualpackets - sourceintegration \ No newline at end of file + formal_integral \ No newline at end of file diff --git a/docs/physics/spectrum/sourceintegration.rst b/docs/physics/spectrum/sourceintegration.rst deleted file mode 100644 index c06a621feae..00000000000 --- a/docs/physics/spectrum/sourceintegration.rst +++ /dev/null @@ -1,191 +0,0 @@ -.. _formal_integral: - -***************************************** -Direct integration of the radiation field -***************************************** - -:cite:`Lucy1999a` describes an alternative method for the generation of -synthetic supernova spectra. Instead of using the frequency and energy of -virtual Monte Carlo (MC) packets to create a spectrum through binning, one can -formally integrate the line source functions which can be calculated from -volume-based estimators collected during the MC simulation. Spectra generated -using this method are virtually noise-free. However, statistical fluctuations -inherent to Monte Carlo calculations still affect the determination of the -source functions and thus indirectly introduce an uncertainty in the spectral -synthesis process. - -.. warning:: - - The current implementation of the formal integral has several limitations. - Please consult the corresponding section below to ensure that these - limitations do not apply to your application. - - -Estimators -========== - -The procedure relies on determining line absorption rates, which are calculated -during the Monte Carlo simulation by incrementing the volume-based estimator - -.. math:: - - \dot E_{lu} = \frac{1}{\Delta t V} \left( 1- e^{-\tau_{lu}}\right) \sum - \epsilon - -Here, the sum involves all packages in a given shell that come into resonance -with the transition :math:`u \rightarrow l`, :math:`\epsilon` denotes the -energy of one such packet, and :math:`\tau_{lu}` the Sobolev optical depth of -the line transition. - -After the Monte Carlo radiative transfer step, a level absorption estimator is -calculated by summing up all absorption rates for transitions which lead to the -target level - -.. math:: - - \dot E_u = \sum_{i < u} \dot E_{iu} - -Finally, the line source function for each transition can be derived with - -.. math:: - - \left( 1- e^{-\tau_{lu}}\right) S_{ul} = \frac{\lambda_{ul} t}{4 \pi} q_{ul} - \dot E_u - -Here, :math:`\lambda_{ul}` is the wavelength of the line :math:`u \rightarrow -l`, and :math:`q_{ul}` is the corresponding branching ratio, i.e. the fraction -of de-excitations of level :math:`u` proceeding via the transition -:math:`u\rightarrow l`. For convenience, the attenuating factor is kept on the -left-hand side because it is the product of the two that will appear in later -formulae. - -Finally, if the contribution by electron-scattering has to be taken into -account, estimators for the diffuse radiation field in the blue and red wings -of the different transitions are needed. These can again be determined with -volume-based estimators according to - -.. math:: - - J_{lu}^b = \frac{\lambda_{lu}}{4 \pi \Delta t V} \sum \varepsilon - - -and - -.. math:: - - J_{lu}^r = J_{lu}^b e^{-\tau_{lu}} + S_{ul} (1 + e^{-\tau_{lu}}) - - -Integration -=========== - -Calculating the emergent spectrum proceeds by casting rays parallel to the line -of sight to the observer through the ejecta. The distance along these rays will -be measured by :math:`z` and the offset to ejecta centre by the impact -parameter :math:`p`. The following figure illustrates this "impact geometry": - -.. image:: https://i.imgur.com/WwVHp5c.png - -The emergent monochromatic luminosity can then be obtained by integrating over -the limiting specific intensities of these rays - -.. math:: - - L_\nu = 8 \pi^2 \int_0^\infty I_\nu (p) p dp - -To obtain the limiting intensity, we have to consider the different line -resonances along the ray and calculate how much radiation is added and removed. -At the resonance point with the :math:`k`-th line transition, the intensity -increment is - -.. math:: - - I_k^r = I_k^b e^{-\tau_k} + \left( 1- e^{-\tau_k}\right) S_{k} - -In the absence of continuum interactions, the relation - -.. math:: - - I_{k+1}^b = I_k^r - -establishes the connection to the next resonance point. If electron-scattering -is taken into account its contribution between successive resonances has to be -considered - -.. math:: - - I_{k+1}^b = I_k^r + \Delta \tau_k \left[ \frac 1 2(J_k^r + J_{k+1}^b) - - I_k^r \right] - - -Thus, by recursively applying the above relations for all resonances occurring -on the ray, the limiting specific intensity for the final integration can be -calculated. The boundary conditions for this process are either :math:`I_0^r = -B_\nu(T)` if the ray intersects the photosphere or :math:`I_0^r = 0` otherwise. - -Implementation Details -====================== - -We seek to integrate all emissions at a certain wavelength :math:`\nu` along a -ray with impact parameter :math:`p`. Because the supernova ejecta is expanding -homologously, the co-moving frame frequency is continuously shifted to longer -wavelengths due to the relativistic Doppler effect as the packet/photon -propagates. - -To find out which lines can shift into the target frequency, we need to -calculate the maximum Doppler shift along a given ray. At any point, the -Doppler effect in our coordinates is - -.. math:: - - \nu = \nu_0 \left( 1 + \beta \mu \right) - -where :math:`\beta = \frac v c`, and :math:`\mu = \cos \theta`. Here -:math:`\theta` is the angle between the radial direction and the ray to the -observer, as shown in the figure below. Because we are in the homologous -expansion regime :math:`v = \frac r t`. Solving for :math:`\nu_0` in the above -gives the relation we seek, but we require an expression for :math:`\mu`. -Examining the figure, we see that for positive :math:`z` the angle -:math:`\theta_2` can be related to the :math:`z` coordinate of the point C by - -.. math:: - - \cos \theta_2 = \frac{z_c}{r} = \mu - - -and in turn :math:`z_c` can be given as - -.. math:: - - z_c = \sqrt{r_c^2 + p_c^2} - -where the subscripts indicate the value at point C. By symmetry, the -intersection point for negative :math:`z` is simply :math:`-z_c`. - -Using the expression for :math:`\mu`, :math:`\beta` above leads to the -dependence on :math:`r` cancelling, and solving for :math:`\nu_0` gives - -.. math:: - - \nu_0 = \frac{\nu}{1 + \frac{z}{ct}} - -For any given shell and impact parameter, we can thus find the maximum and -minimum co-moving frequency that will give the specified lab frame frequency. -This allows us to find the section of the line list with the transitions whose -resonances have to be considered in the calculation of the limiting specific -intensity. - -Current Limitations -=================== - -The current implementation of the formal integral has some limitations: - -* once electron scattering is included, the scheme only produces accurate - results when multiple resonances occur on the rays. This is simply because - otherwise the :math:`J^b` and :math:`J^r` do not provide an accurate - representation of the diffuse radiation field at the current location on the - ray. Also, :math:`d\tau` can become large which can create unphysical, - negative intensities. - -It is always advised to check the results of the formal integration against the -spectrum constructed from the emerging Monte Carlo packets. diff --git a/docs/physics/update_and_conv/tardis_example.yml b/docs/physics/update_and_conv/tardis_example.yml new file mode 120000 index 00000000000..665fe53411f --- /dev/null +++ b/docs/physics/update_and_conv/tardis_example.yml @@ -0,0 +1 @@ +../../tardis_example.yml \ No newline at end of file diff --git a/docs/physics/update_and_conv/update_and_conv.ipynb b/docs/physics/update_and_conv/update_and_conv.ipynb new file mode 100644 index 00000000000..2735da970fc --- /dev/null +++ b/docs/physics/update_and_conv/update_and_conv.ipynb @@ -0,0 +1,609 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "4d53d061", + "metadata": {}, + "source": [ + "# Updating Plasma and Convergence\n", + "\n", + "As light travels through a real plasma, it has effects on the properties of the plasma due to light-matter\n", + "interactions as well as the presence of extra energy from the light. Additionally, as [previously discussed](../montecarlo/propagation.rst), properties of the plasma affect how light travels through it. This is a typical equilibrium problem. We solve for the plasma properties by finding a steady-state solution; that is, the actual plasma will be in a state such that the plasma state will not change as\n", + "light propagates through it, because the effects of the light on the plasma and the effects of the plasma on the\n", + "light are in equilibrium.\n", + "\n", + "One of TARDIS's main goals is to determine this plasma state (as we need the actual plasma properties in order to\n", + "get an accurate spectrum). This is done in an iterative process. After each [Monte Carlo iteration](../montecarlo/index.rst) (which sends light through the supernova ejecta), TARDIS uses the [Monte Carlo estimators](../montecarlo/estimators.rst)\n", + "how the propagating light affects the plasma state, after which the plasma state is updated (as will be explained below and demonstrated in the code example). We do this many times, and attempt to have the plasma state converge\n", + "to the steady-state we are looking for. In fact, all but the last Monte Carlo iteration is used for this purpose\n", + "(after which TARDIS will have the necessary plasma state for its last iteration which calculates the spectrum).\n", + "\n", + "<div class=\"alert alert-info\">\n", + "\n", + "Note\n", + "\n", + "For all but the last iteration, TARDIS uses the number of Monte Carlo packets specified in the\n", + "[Monte Carlo configuration](../../io/configuration/components/montecarlo.rst) under the ``no_of_packets`` argument. This is because\n", + "a different number of packets may be necessary to calculate the spectrum as opposed to calculate the\n", + "plasma state.\n", + "\n", + "</div>\n", + "\n", + "After each iteration the values for radiative temperature and dilution factor are updated by calling the ``advance_state`` method on a ``Simulation`` object as will be shown below in the code example. The goal of this is to eventually have the radiative temperature and dilution factor converge to a single value so that the steady-state plasma state can be determined. To ensure that the simulation converges, TARDIS employs a convergence strategy. Currently, only one convergence strategy is available: damped convergence. This will be described in the following sections.\n", + "\n", + "<div class=\"alert alert-info\">\n", + "\n", + "Note\n", + " \n", + "Unless otherwise noted, all user-supplied quantities mentioned on this page are supplied in the [convergence section of the Monte Carlo configuration](../../io/configuration/components/montecarlo.rst#damped-convergence-strategy), which will be referenced as the convergence configuration.\n", + "\n", + "</div>" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "8ffc4479", + "metadata": {}, + "source": [ + "## $T_\\mathrm{rad}$ and $W$\n", + "\n", + "The main way in which the plasma state is updated is by using the ``j`` and ``nu_bar`` estimators (see [here](../montecarlo/estimators.rst#j-and-bar-nu-estimators)) to update two of the key plasma inputs (see [Plasma](../setup/plasma/index.rst)): the radiative temperature $T_\\mathrm{rad}$ and dilution factor $W$. Recall that each of these quantities takes on a different value in each shell.\n", + "\n", + "Using the estimators $J$ and $\\bar \\nu$, we estimate these quantities using\n", + "\n", + "$$T_{\\mathrm{rad\\ estimated}} = \\frac{h}{k_{\\mathrm{B}}} \\frac{\\pi^4}{360 \\zeta(5)} \\frac{\\bar \\nu}{J}$$\n", + "\n", + "and\n", + "\n", + "$$W_\\mathrm{estimated} = \\frac{\\pi J}{\\sigma_{\\mathrm{R}} T_{\\mathrm{rad\\ estimated}}^4}$$\n", + "\n", + "where $h$ is Planck's constant, $k_{\\mathrm{B}}$ is Boltzmann's constant, $\\sigma_{\\mathrm{R}}$ is the Stefan–Boltzmann constant, and $\\zeta$ is the Riemann zeta function. The equation for $W$ comes from the fact that the dilution factor is the ratio of the actual mean intensity to that of a blackbody, which is $J_{\\mathrm{blackbody}}=\\frac{\\sigma_{\\mathrm{R}} T^4}{\\pi}$.\n", + "\n", + "Recall (see [Implementation](../montecarlo/estimators.rst#implementation)), however, that when TARDIS stores these estimators, it leaves out the prefactor of $\\frac{1}{4\\pi V\\Delta t}$ for computational ease. That is, $J=\\frac{1}{4\\pi V\\Delta t}\\sum_i \\varepsilon_i l_i=\\frac{1}{4\\pi V\\Delta t}*\\mathrm{real\\ j\\ estimator}$, and $\\bar \\nu=\\frac{1}{4\\pi V\\Delta t}\\sum_i \\varepsilon_i \\nu_i l_i=\\frac{1}{4\\pi V\\Delta t}*\\mathrm{real\\ nu\\_ bar\\ estimator}$. These factors are then included in our calculations; specifically, using the previous relations we have\n", + "\n", + "$$T_\\mathrm{rad\\ estimated}= \\frac{h}{k_{\\mathrm{B}}} \\frac{\\pi^4}{360 \\zeta(5)} \\frac{\\sum_i \\varepsilon_i \\nu_i l_i}{\\sum_i \\varepsilon_i l_i} = \\frac{h}{k_{\\mathrm{B}}} \\frac{\\pi^4}{360 \\zeta(5)} \\frac{\\mathrm{real\\ nu\\_ bar\\ estimator}}{\\mathrm{real\\ j\\ estimator}}$$\n", + "and\n", + "$$W_\\mathrm{estimated} = \\frac{\\sum_i \\varepsilon_i l_i}{4\\sigma_{\\mathrm{R}} T_{\\mathrm{rad\\ estimated}}^4V\\Delta t} = \\frac{\\mathrm{real\\ j\\ estimator}}{4\\sigma_{\\mathrm{R}} T_{\\mathrm{rad\\ estimated}}^4V\\Delta t}.$$\n", + "\n", + "While TARDIS can then update the plasma state using the estimated values, there is a good chance that these estimated values would “overshoot” the true value we want to converge to (for example, if the current value of the dilution factor in some cell the dilution factor is 0.4, and the true steady-state value TARDIS wants to find is 0.45, there is a good chance that the estimated value will be greater than 0.45). This could make the simulation take longer to converge or, at worst, make it so the simulation does not converge at all. To account for this, users can set (in the convergence configuration) a \"damping constant\" for both the radiative temperature ($d_{T_\\mathrm{rad}}$) and the dilution factor ($d_W$). When ``advance_state`` is called, these quantities update as follows:\n", + "\n", + "$$T_\\mathrm{rad\\ updated} = T_\\mathrm{rad\\ current} + d_{T_\\mathrm{rad}}(T_\\mathrm{rad\\ estimated}-T_\\mathrm{rad\\ current})$$\n", + " \n", + "and\n", + " \n", + "$$ W_\\mathrm{updated} = W_\\mathrm{current} + d_W(W_\\mathrm{estimated}-W_\\mathrm{current}).$$\n", + "\n", + "This means, for example, if the damping constant is 0.5, the updated value is halfway between the current value and the estimated value. If the damping constant is 0.7, the updated value is 70% of the way between the current value and the estimated value, and so on. **If the damping constant is 1, then the updated value is exactly the estimated value, and if the damping constant is zero, the value stays the same throughout the simulation and is not updated.**\n", + "\n", + "The updated $T_\\mathrm{rad}$ and $W$ are then used as inputs to the updated [plasma calculations](../setup/plasma/index.rst) which account for the effect of the Monte Carlo packets on the plasma state." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "f346fb77", + "metadata": {}, + "source": [ + "## $T_\\mathrm{inner}$\n", + "\n", + "The temperature of the inner boundary, $T_\\mathrm{inner}$, plays a unique role in the simulation, as it is the primary determiner of the output luminosity. This is because the the luminosity of the inner boundary is proportional to $T_\\mathrm{inner}^4$ (see [Energy Packet Initialization](../montecarlo/initialization.ipynb)). Thus, $T_\\mathrm{inner}$ is updated throughout the simulation in order to match the output luminosity to the requested luminosity specified in the [supernova configuration](../../io/configuration/components/supernova.rst) between the bounds specified in the supernova configuration. However, there is not necessarily a quartic relationship between $T_\\mathrm{inner}$ and the output luminosity, as changing $T_\\mathrm{inner}$ also changes the frequency distribution of the initialized packets (once again see [Energy Packet Initialization](../montecarlo/initialization.ipynb)). This then affects the light-matter interactions, affecting which packets make it to the outer boundary, which also affects the output luminosity. Because of this, there is not an exact way to estimate $T_\\mathrm{inner}$. To do this estimation, we use\n", + "\n", + "$$T_\\mathrm{inner\\ estimated} = T_\\mathrm{inner\\ current} * \\left(\\frac{L_\\mathrm{output}}{L_\\mathrm{requested}}\\right)^{\\mathrm{t\\_inner\\_update\\_exponent}}$$\n", + " \n", + "where $L_\\mathrm{output}$ is the output luminosity calculated by adding up the luminosity of each packet (see [Basic Spectrum Generation](../spectrum/basic.ipynb)) between the bounds specified in the [supernova configuration](../../io/configuration/components/supernova.rst), $L_\\mathrm{requested}$ is the luminosity requested also in the supernova configuration (requested between those bounds previously mentioned), and ``t_inner_update_exponent`` is provided by the user in the convergence configuration. Note that what we are doing is \"correcting\" the previous value of the inner temperature by a factor of $\\left(\\frac{L_\\mathrm{output}}{L_\\mathrm{requested}}\\right)^{\\mathrm{t\\_inner\\_update\\_exponent}}$. Note that if $\\frac{L_\\mathrm{output}}{L_\\mathrm{requested}}$ is greater than 1, we want to lower $T_\\mathrm{inner}$ as the output luminosity is too high, and vice versa if the ratio is less than 1. Thus ``t_inner_update_exponent`` should be negative. Naively one might set ``t_inner_update_exponent=-0.25``, however as a default TARDIS uses ``t_inner_update_exponent=-0.5`` as -0.25 may undershoot the correct $T_\\mathrm{inner}$ because of its previously mentioned effects on the initial frequency distribution.\n", + "\n", + "After calculating the estimated $T_\\mathrm{inner}$, the quantity is updated using damped convergence with its own damping constant (once again set in the convergence configuration):\n", + "\n", + "$$T_\\mathrm{inner\\ updated} = T_\\mathrm{inner\\ current} + d_{T_\\mathrm{inner}}(T_\\mathrm{inner\\ estimated}-T_\\mathrm{inner\\ current}).$$\n", + "\n", + "Once again, If the damping constant is 1, then the updated value is exactly the estimated value, and if the damping constant is zero, the value stays the same throughout the simulation and is not updated.\n", + "\n", + "Additionally, because of the vast impact of $T_\\mathrm{inner}$ on the simulation, one may want to update it less frequently -- i.e. allow $W$ and $T_\\mathrm{rad}$ to reach a steady-state value for a particular $T_\\mathrm{inner}$ before updating $T_\\mathrm{inner}$. To do this, in the convergence configuration we set ``lock_t_inner_cycles``, which is the number of iterations to wait before updating $T_\\mathrm{inner}$. It is set to 1 by default, meaning $T_\\mathrm{inner}$ would be updated every iteration." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "9a3bee0e", + "metadata": {}, + "source": [ + "## Convergence Information\n", + "\n", + "During the simulation, information about the how $T_\\mathrm{rad}$, $W$, and $T_\\mathrm{inner}$ are updated as well as a comparison of the total output luminosity and the requested luminosity are logged at the INFO level (see [Configuring the Logging Output for TARDIS](../../io/optional/tutorial_logging_configuration.ipynb)) as shown in the code below, to give users a better idea of how the convergence process is working.\n", + "\n", + "In addition, TARDIS allows for the displaying of convergence plots, which allows users to visualize the convergence process for $T_\\mathrm{rad}$, $W$, $T_\\mathrm{inner}$, and the total luminosity of the supernova being modeled. For more information, see [Convergence Plots](../../io/visualization/tutorial_convergence_plot.ipynb)." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "3bc752ec", + "metadata": {}, + "source": [ + "## Convergence Criteria\n", + "\n", + "TARDIS also allows users to stop the simulation if the simulation reaches a certain level of convergence, which is checked upon the call of the ``advance_state`` method. To enable this, users must set ``stop_if_converged=True`` in the convergence configuration. Also in the configuration, the quantities ``hold_iterations``, ``threshold``, and ``fraction`` are be specified to determine convergence as follows:\n", + "\n", + "For the simulation to be considered to have converged, for ``hold_iterations`` successive iterations, the estimated values of $T_\\mathrm{rad}$, $W$, and $T_\\mathrm{inner}$ may differ from the previous value by a fraction of at most ``threshold`` in at least ``fraction`` fraction of the shells (for $T_\\mathrm{inner}$, since there is only one value, the ``fraction`` part does not apply). For example, if ``hold_iterations=3``, ``threshold=0.05`` for all three quantities, and ``fraction=0.8``, the simulation will be considered to have converged if for 3 successive iterations the estimated values of $T_\\mathrm{rad}$ and $W$ differ from the current respective values by at most 5% in at least 80% of the shells, *and* the estimated $T_\\mathrm{inner}$ differs by at most 5%. See the [convergence configuration schema](../../io/configuration/components/montecarlo.rst#damped-convergence-strategy) for default values of these quantities.\n", + "\n", + "<div class=\"alert alert-info\">\n", + "\n", + "Note\n", + " \n", + "To determine convergence, we compare the estimated value, **not** the updated value (which is related to the estimated value via the damping constant), with the previous value. If $T_\\mathrm{inner}$ is locked (see the previous section), the estimated value will still be calculated so convergence can be checked as usual.\n", + "\n", + "</div>\n", + "\n", + "<div class=\"alert alert-info\">\n", + "\n", + "Note\n", + " \n", + "``hold_iterations`` and ``fraction`` are universal quantities, i.e. they are each a single value that applies to $T_\\mathrm{rad}$ and $W$, and for ``hold_iterations`` also $T_\\mathrm{inner}$. ``threshold``, on the other hand, is supplied for each quantity separately, so for instance you could require $T_\\mathrm{rad}$ to differ by less than 1%, $W$ to differ by less than 3%, and $T_\\mathrm{inner}$ to differ by less than 5% for convergence to be reached.\n", + "\n", + "</div>\n", + "\n", + "\n", + "## Updating Other Quantities\n", + "\n", + "Other quantities in the plasma state can depend on other estimators. Currently, this is only implemented for the ``j_blue`` estimator: If ``radiative_rates_type`` in the [plasma configuration](../../io/configuration/components/plasma.rst) is set to ``detailed``, the `j_blues` plasma property will will be replaced with the value of the $J^b_{lu}$ [estimator](../montecarlo/estimators.rst#j-b-lu-estimator) (the raw estimator times the factor of $\\frac{ct_\\mathrm{explosion}}{4\\pi V \\Delta t}$, once again see [Implementation](../montecarlo/estimators.rst#implementation)), which would then affect other plasma properties that depend on the `j_blues` values (see [Plasma](../setup/plasma/index.rst)). Otherwise, the `j_blues` values in the plasma are calculated as they typically are in the plasma calculations, and the $J^b_{lu}$ estimator is only used for the [formal integral](../spectrum/formal_integral.rst). Even in the former case, while the estimator does contribute to the updating of the plasma when the ``advance_state`` method is called, it does **not** contribute to the determination of if the simulation has converged, and it does **not** show up in the convergence logging or convergence plots." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "127746c2", + "metadata": {}, + "source": [ + "## Code Example\n", + "\n", + "We now show a detailed example of how the plasma is updated using the estimators after a Monte Carlo iteration. First, we import the necessary packages and set up a simulation (see [Setting Up the Simulation](../setup/index.rst)):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7a8bd905", + "metadata": {}, + "outputs": [], + "source": [ + "from tardis.io.configuration.config_reader import Configuration\n", + "from tardis.simulation import Simulation\n", + "from tardis.io.atom_data.util import download_atom_data\n", + "import numpy as np\n", + "from scipy.special import zeta\n", + "\n", + "from astropy import units as u, constants as const\n", + "\n", + "# We download the atomic data needed to run this notebook\n", + "download_atom_data('kurucz_cd23_chianti_H_He')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "259a7aa9", + "metadata": {}, + "outputs": [], + "source": [ + "tardis_config = Configuration.from_yaml('tardis_example.yml')\n", + "\n", + "# We manually put in the damping constants and t_inner_update_exponent for\n", + "# illustrative purposes:\n", + "damping_t_radiative = 0.5\n", + "damping_dilution_factor = 0.3\n", + "damping_t_inner = 0.7\n", + "t_inner_update_exponent = -0.5\n", + "\n", + "# We set the above values into the configuration:\n", + "tardis_config.montecarlo.convergence_strategy.t_rad.damping_constant = damping_t_radiative\n", + "tardis_config.montecarlo.convergence_strategy.w.damping_constant = damping_dilution_factor\n", + "tardis_config.montecarlo.convergence_strategy.t_inner.damping_constant = damping_t_inner\n", + "tardis_config.montecarlo.convergence_strategy.t_inner_update_exponent = t_inner_update_exponent" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bb37402c", + "metadata": {}, + "outputs": [], + "source": [ + "sim = Simulation.from_config(tardis_config)\n", + "\n", + "simulation_state = sim.simulation_state\n", + "plasma = sim.plasma\n", + "transport = sim.transport" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "cf13d946", + "metadata": {}, + "source": [ + "We show the initial radiative temperature and dilution factor in each shell, the initial inner boundary temperature, and the initial electron densities in each shell:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3f43f93", + "metadata": {}, + "outputs": [], + "source": [ + "simulation_state.t_radiative" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "90bb6147", + "metadata": {}, + "outputs": [], + "source": [ + "simulation_state.dilution_factor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "66209ff7", + "metadata": {}, + "outputs": [], + "source": [ + "simulation_state.t_inner" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b2ae7b4", + "metadata": {}, + "outputs": [], + "source": [ + "plasma.electron_densities" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "a248ff2c", + "metadata": {}, + "source": [ + "We set the number of packets and we run one iteration of the Monte Carlo simulation:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9f7eb44f", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "N_packets = 10000\n", + "\n", + "# Using the commented out code below, we can also get the number of packets\n", + "# from the configuration -- try it out:\n", + "#N_packets = tardis_config.montecarlo.no_of_packets\n", + "\n", + "sim.iterate(N_packets)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "d3d0074d", + "metadata": {}, + "source": [ + "We now show the values of the $J$ and $\\bar \\nu$ estimators, attaching their proper units (note that these are the raw estimators, and the factors of $\\frac{1}{4\\pi V \\Delta t}$ etc are not included):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21500ea8", + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "j_estimator = transport.transport_state.j_estimator * (u.erg * u.cm) \n", + "j_estimator" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fac91ee2", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "nu_bar_estimator = transport.transport_state.nu_bar_estimator * (u.erg * u.cm * u.Hz)\n", + "nu_bar_estimator" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "69c178d2", + "metadata": {}, + "source": [ + "We show the values of $J$ and $\\bar \\nu$ including the prefactor:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9500e34b", + "metadata": {}, + "outputs": [], + "source": [ + "V = simulation_state.volume\n", + "Delta_t = transport.transport_state.time_of_simulation\n", + "prefactor = 1 / (4 * np.pi * V * Delta_t)\n", + "J = prefactor * j_estimator\n", + "J" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a5720987", + "metadata": {}, + "outputs": [], + "source": [ + "nu_bar = prefactor * nu_bar_estimator\n", + "nu_bar" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "28d69ca6", + "metadata": {}, + "source": [ + "As mentioned [here](../montecarlo/estimators.rst#j-and-bar-nu-estimators), $\\bar \\nu$ is not truly the mean frequency (as you can see by units). We show the true mean frequency, which will, as expected, be in units of Hz." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "691cf2f6", + "metadata": {}, + "outputs": [], + "source": [ + "nu_bar/J" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "bcbf40d4", + "metadata": {}, + "source": [ + "We show the calculations of the estimated and updated $T_\\mathrm{rad}$ and $W$. Note that the ``decompose()`` method is used to simplify the units:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "50c639ea", + "metadata": {}, + "outputs": [], + "source": [ + "t_rad_estimated = ( (const.h.cgs / const.k_B.cgs) \n", + " * (np.pi**4 / (360 * zeta(5, 1)))\n", + " * (nu_bar_estimator / j_estimator) ).decompose()\n", + "t_rad_estimated" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b34674df", + "metadata": {}, + "outputs": [], + "source": [ + "t_rad_updated = simulation_state.t_radiative + damping_t_radiative * (t_rad_estimated - simulation_state.t_radiative)\n", + "t_rad_updated" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b48d8ada", + "metadata": {}, + "outputs": [], + "source": [ + "dilution_factor_estimated = ( j_estimator / (4 * const.sigma_sb.cgs * t_rad_estimated**4 * V * Delta_t) ).decompose()\n", + "dilution_factor_estimated" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22895e09", + "metadata": {}, + "outputs": [], + "source": [ + "dilution_factor_updated = simulation_state.dilution_factor + damping_dilution_factor * (dilution_factor_estimated - simulation_state.dilution_factor)\n", + "dilution_factor_updated" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7bfefce9", + "metadata": {}, + "source": [ + "We show the output and requested luminosities, and use these to calculate the estimated and updated $T_\\mathrm{inner}$:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "795dceb2", + "metadata": {}, + "outputs": [], + "source": [ + "# The output luminosity is calculated between the bounds specified below\n", + "nu_lower = 0\n", + "nu_upper = np.inf\n", + "\n", + "# Using the commented out code below, we can also get the frequency bounds\n", + "# from the configuration -- try it out (note we convert between wavelength\n", + "# and frequency, and thus the order switches):\n", + "#nu_lower = tardis_config.supernova.luminosity_wavelength_end.to(u.Hz, u.spectral)\n", + "#nu_upper = tardis_config.supernova.luminosity_wavelength_start.to(u.Hz, u.spectral)\n", + "\n", + "L_output = transport.transport_state.calculate_emitted_luminosity(0,np.inf)\n", + "L_output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b7028da2", + "metadata": {}, + "outputs": [], + "source": [ + "L_requested = sim.luminosity_requested\n", + "L_requested" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4a14111a", + "metadata": {}, + "outputs": [], + "source": [ + "t_inner_estimated = simulation_state.t_inner * (L_output / L_requested)**t_inner_update_exponent\n", + "t_inner_estimated" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8bd1062f", + "metadata": {}, + "outputs": [], + "source": [ + "t_inner_updated = simulation_state.t_inner + damping_t_inner * (t_inner_estimated - simulation_state.t_inner)\n", + "t_inner_updated" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "43b31d2f", + "metadata": {}, + "source": [ + "We now advance the state of the simulation based on the estimators. This will also display a summary of the updated values of $T_\\mathrm{rad}$ and $W$. Additionally, the ``advance_state()`` method checks for convergence and returns the convergence status as shown below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9676b22b", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "sim.advance_state()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "9619477d", + "metadata": {}, + "source": [ + "Finally, we show the full updated $T_\\mathrm{rad}$, $W$, and $T_\\mathrm{inner}$, as well as the updated electron densities which were updated along with the rest of the plasma based on the new values for $T_\\mathrm{rad}$, $W$, and $T_\\mathrm{inner}$. Compare these with our calculations above and with the initial values at the beginning of the code example!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fe0b9f40", + "metadata": {}, + "outputs": [], + "source": [ + "simulation_state.t_radiative" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8de89bb2", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "simulation_state.dilution_factor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4f78c4fe", + "metadata": {}, + "outputs": [], + "source": [ + "simulation_state.t_inner" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fcaf08ff", + "metadata": {}, + "outputs": [], + "source": [ + "plasma.electron_densities" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd488259", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + }, + "vscode": { + "interpreter": { + "hash": "c20eb03b6e6c860a5223c79131a5cfd0b7e61a9aa5d08c2b1400663bc6cc4e6d" + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/quickstart.ipynb b/docs/quickstart.ipynb index 2296860d836..da65fc1fb1b 100644 --- a/docs/quickstart.ipynb +++ b/docs/quickstart.ipynb @@ -1,23 +1,23 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "### Quickstart for TARDIS ###" + "# Quickstart for TARDIS" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "Every simulation run requires the atomic database (for more info refer to [atomic data](io/configuration/components/atomic/atomic_data.rst)) and a configuration file (more info at [configuration](io/configuration/index.rst)).\n", - "You can obtain a copy of the atomic database from the\n", - "(https://github.com/tardis-sn/tardis-refdata) repository\n", - "(`atom_data` subfolder). We recommended to use the\n", - "`kurucz_cd23_chianti_H_He.h5` dataset (which is auto-downloaded in the second cell already). The configuration file for this quickstart is `tardis_example.yml`, which can be downloaded [here](https://raw.githubusercontent.com/tardis-sn/tardis/master/docs/tardis_example.yml)), though this file is auto-downloaded in the third cell.\n", + "Every simulation run requires [atomic data](io/configuration/components/atomic/atomic_data.rst) and a [configuration file](io/configuration/index.rst). \n", "\n", - "After the [installation](installation.rst), start a Jupyter server executing `jupyter notebook` on the command line in a directory that contains this quickstart." + "## Atomic Data\n", + "\n", + "We recommend using the [kurucz_cd23_chianti_H_He.h5](https://dev.azure.com/tardis-sn/TARDIS/_apis/git/repositories/tardis-refdata/items?path=atom_data/kurucz_cd23_chianti_H_He.h5&resolveLfs=true) dataset." ] }, { @@ -26,32 +26,34 @@ "metadata": {}, "outputs": [], "source": [ - "from tardis import run_tardis\n", "from tardis.io.atom_data.util import download_atom_data" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, "metadata": {}, + "outputs": [], "source": [ - "#### Downloading the atomic data ####" + "download_atom_data('kurucz_cd23_chianti_H_He')" ] }, { - "cell_type": "code", - "execution_count": null, + "attachments": {}, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# The data are automatically downloaded\n", - "download_atom_data('kurucz_cd23_chianti_H_He')" + "You can also obtain a copy of the atomic data from the [tardis-refdata](https://github.com/tardis-sn/tardis-refdata/tree/master/atom_data) repository." ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "#### Downloading the example file ####" + "## Example Configuration File\n", + "\n", + "The configuration file [tardis_example.yml](https://github.com/tardis-sn/tardis/tree/master/docs/tardis_example.yml) is used throughout this Quickstart." ] }, { @@ -60,27 +62,26 @@ "metadata": {}, "outputs": [], "source": [ - "!curl -O https://raw.githubusercontent.com/tardis-sn/tardis/master/docs/tardis_example.yml" + "!wget -q -nc https://raw.githubusercontent.com/tardis-sn/tardis/master/docs/tardis_example.yml" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, "metadata": {}, + "outputs": [], "source": [ - "#### Running the simulation (long output) ####" + "!cat tardis_example.yml" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "<div class=\"alert alert-info\">\n", + "## Running the Simulation\n", "\n", - "Note\n", - " \n", - "The progress of the simulation can be tracked using progress bars which are displayed when the notebook is run, but are not displayed in the documentation. \n", - " \n", - "</div>" + "To run the simulation, import the `run_tardis` function and create the `sim` object. " ] }, { @@ -89,27 +90,64 @@ "metadata": {}, "outputs": [], "source": [ - "sim = run_tardis('tardis_example.yml')" + "from tardis import run_tardis" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "<div class=\"alert alert-info\">\n", - " \n", - "Note\n", "\n", - "When running this notebook locally or in interactive mode, a [convergence plot](io/visualization/convergence_plot.ipynb) will show up.\n", + "**Note:**\n", "\n", + "Get more information about the [progress bars](io/output/progress_bars.rst), [logging configuration](io/optional/tutorial_logging_configuration.ipynb), and [convergence plots](io/visualization/tutorial_convergence_plot.ipynb). \n", + " \n", "</div>" ] }, { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sim = run_tardis(\"tardis_example.yml\", \n", + " virtual_packet_logging=True,\n", + " show_convergence_plots=True,\n", + " export_convergence_plots=True,\n", + " log_level=\"INFO\") " + ] + }, + { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "#### Plotting the Spectrum ####" + "## Plotting the Spectrum\n", + "\n", + "Finally, plot the generated spectrum with `matplotlib`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "spectrum = sim.transport.transport_state.spectrum\n", + "spectrum_virtual = sim.transport.transport_state.spectrum_virtual\n", + "spectrum_integrated = sim.transport.transport_state.spectrum_integrated" ] }, { @@ -118,20 +156,19 @@ "metadata": {}, "outputs": [], "source": [ - "%pylab inline\n", + "%matplotlib inline\n", + "plt.figure(figsize=(10, 6.5))\n", "\n", - "spectrum = sim.runner.spectrum\n", - "spectrum_virtual = sim.runner.spectrum_virtual\n", - "spectrum_integrated = sim.runner.spectrum_integrated\n", + "spectrum.plot(label=\"Normal packets\")\n", + "spectrum_virtual.plot(label=\"Virtual packets\")\n", + "spectrum_integrated.plot(label='Formal integral')\n", "\n", - "figure(figsize=(10,6))\n", - "spectrum.plot(label='normal packets')\n", - "spectrum_virtual.plot(label='virtual packets')\n", - "spectrum_integrated.plot(label='formal integral')\n", - "xlabel('Wavelength [$\\AA$]')\n", - "ylabel('Luminosity Density [erg/s/$\\AA$]')\n", - "legend()\n", - "xlim(500, 9000)" + "plt.xlim(500, 9000)\n", + "plt.title(\"TARDIS example model spectrum\")\n", + "plt.xlabel(\"Wavelength [$\\AA$]\")\n", + "plt.ylabel(\"Luminosity density [erg/s/$\\AA$]\")\n", + "plt.legend()\n", + "plt.show()" ] } ], @@ -140,7 +177,8 @@ "hash": "14c438b85bc0c5441332c56c5d68185f391ef15672c5492b27fc26d9164316c1" }, "kernelspec": { - "display_name": "Python 3.7.10 64-bit ('tardis': conda)", + "display_name": "Python 3 (ipykernel)", + "language": "python", "name": "python3" }, "language_info": { @@ -153,9 +191,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.11.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/resources/code_comparison/plasma_compare/plasma_compare.ipynb b/docs/resources/code_comparison/plasma_compare/plasma_compare.ipynb index 85eadd65772..3e82c62b7f4 100644 --- a/docs/resources/code_comparison/plasma_compare/plasma_compare.ipynb +++ b/docs/resources/code_comparison/plasma_compare/plasma_compare.ipynb @@ -35,7 +35,7 @@ ], "source": [ "from tardis.simulation import Simulation\n", - "from tardis.io.config_reader import Configuration\n", + "from tardis.io.configuration.config_reader import Configuration\n", "from IPython.display import FileLinks" ] }, @@ -820,7 +820,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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", "text/plain": [ "<Figure size 720x720 with 1 Axes>" ] diff --git a/docs/resources/code_comparison/toy_models/reading blondin toymodel.ipynb b/docs/resources/code_comparison/toy_models/reading blondin toymodel.ipynb index 64bb0827889..77db25a9571 100644 --- a/docs/resources/code_comparison/toy_models/reading blondin toymodel.ipynb +++ b/docs/resources/code_comparison/toy_models/reading blondin toymodel.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -72,6 +73,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -126,6 +128,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -1802,8 +1805,8 @@ } ], "source": [ - "spectrum = pd.DataFrame(data = sim.runner.spectrum_integrated.frequency.value, columns=['frequency'])\n", - "spectrum['luminosity'] = sim.runner.spectrum_integrated.luminosity_density_nu.value\n", + "spectrum = pd.DataFrame(data = sim.transport.spectrum_integrated.frequency.value, columns=['frequency'])\n", + "spectrum['luminosity'] = sim.transport.spectrum_integrated.luminosity_density_nu.value\n", "\n", "create_df_download_link(spectrum, title='Download Spectrum', filename='spectrum.csv', type='csv')" ] @@ -1835,777 +1838,7 @@ }, { "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "window.mpl = {};\n", - "\n", - "\n", - "mpl.get_websocket_type = function() {\n", - " if (typeof(WebSocket) !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof(MozWebSocket) !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert('Your browser does not have WebSocket support.' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.');\n", - " };\n", - "}\n", - "\n", - "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = (this.ws.binaryType != undefined);\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById(\"mpl-warnings\");\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent = (\n", - " \"This browser does not support binary websocket messages. \" +\n", - " \"Performance may be slow.\");\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = $('<div/>');\n", - " this._root_extra_style(this.root)\n", - " this.root.attr('style', 'display: inline-block');\n", - "\n", - " $(parent_element).append(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", - " fig.send_message(\"send_image_mode\", {});\n", - " if (mpl.ratio != 1) {\n", - " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", - " }\n", - " fig.send_message(\"refresh\", {});\n", - " }\n", - "\n", - " this.imageObj.onload = function() {\n", - " if (fig.image_mode == 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function() {\n", - " fig.ws.close();\n", - " }\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "}\n", - "\n", - "mpl.figure.prototype._init_header = function() {\n", - " var titlebar = $(\n", - " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n", - " 'ui-helper-clearfix\"/>');\n", - " var titletext = $(\n", - " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n", - " 'text-align: center; padding: 3px;\"/>');\n", - " titlebar.append(titletext)\n", - " this.root.append(titlebar);\n", - " this.header = titletext[0];\n", - "}\n", - "\n", - "\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", - "\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._init_canvas = function() {\n", - " var fig = this;\n", - "\n", - " var canvas_div = $('<div/>');\n", - "\n", - " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", - "\n", - " function canvas_keyboard_event(event) {\n", - " return fig.key_event(event, event['data']);\n", - " }\n", - "\n", - " canvas_div.keydown('key_press', canvas_keyboard_event);\n", - " canvas_div.keyup('key_release', canvas_keyboard_event);\n", - " this.canvas_div = canvas_div\n", - " this._canvas_extra_style(canvas_div)\n", - " this.root.append(canvas_div);\n", - "\n", - " var canvas = $('<canvas/>');\n", - " canvas.addClass('mpl-canvas');\n", - " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", - "\n", - " this.canvas = canvas[0];\n", - " this.context = canvas[0].getContext(\"2d\");\n", - "\n", - " var backingStore = this.context.backingStorePixelRatio ||\n", - "\tthis.context.webkitBackingStorePixelRatio ||\n", - "\tthis.context.mozBackingStorePixelRatio ||\n", - "\tthis.context.msBackingStorePixelRatio ||\n", - "\tthis.context.oBackingStorePixelRatio ||\n", - "\tthis.context.backingStorePixelRatio || 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband = $('<canvas/>');\n", - " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", - "\n", - " var pass_mouse_events = true;\n", - "\n", - " canvas_div.resizable({\n", - " start: function(event, ui) {\n", - " pass_mouse_events = false;\n", - " },\n", - " resize: function(event, ui) {\n", - " fig.request_resize(ui.size.width, ui.size.height);\n", - " },\n", - " stop: function(event, ui) {\n", - " pass_mouse_events = true;\n", - " fig.request_resize(ui.size.width, ui.size.height);\n", - " },\n", - " });\n", - "\n", - " function mouse_event_fn(event) {\n", - " if (pass_mouse_events)\n", - " return fig.mouse_event(event, event['data']);\n", - " }\n", - "\n", - " rubberband.mousedown('button_press', mouse_event_fn);\n", - " rubberband.mouseup('button_release', mouse_event_fn);\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband.mousemove('motion_notify', mouse_event_fn);\n", - "\n", - " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", - " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", - "\n", - " canvas_div.on(\"wheel\", function (event) {\n", - " event = event.originalEvent;\n", - " event['data'] = 'scroll'\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " mouse_event_fn(event);\n", - " });\n", - "\n", - " canvas_div.append(canvas);\n", - " canvas_div.append(rubberband);\n", - "\n", - " this.rubberband = rubberband;\n", - " this.rubberband_canvas = rubberband[0];\n", - " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", - " this.rubberband_context.strokeStyle = \"#000000\";\n", - "\n", - " this._resize_canvas = function(width, height) {\n", - " // Keep the size of the canvas, canvas container, and rubber band\n", - " // canvas in synch.\n", - " canvas_div.css('width', width)\n", - " canvas_div.css('height', height)\n", - "\n", - " canvas.attr('width', width * mpl.ratio);\n", - " canvas.attr('height', height * mpl.ratio);\n", - " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", - "\n", - " rubberband.attr('width', width);\n", - " rubberband.attr('height', height);\n", - " }\n", - "\n", - " // Set the figure to an initial 600x600px, this will subsequently be updated\n", - " // upon first draw.\n", - " this._resize_canvas(600, 600);\n", - "\n", - " // Disable right mouse context menu.\n", - " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", - " return false;\n", - " });\n", - "\n", - " function set_focus () {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "}\n", - "\n", - "mpl.figure.prototype._init_toolbar = function() {\n", - " var fig = this;\n", - "\n", - " var nav_element = $('<div/>')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " // put a spacer in here.\n", - " continue;\n", - " }\n", - " var button = $('<button/>');\n", - " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n", - " 'ui-button-icon-only');\n", - " button.attr('role', 'button');\n", - " button.attr('aria-disabled', 'false');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - "\n", - " var icon_img = $('<span/>');\n", - " icon_img.addClass('ui-button-icon-primary ui-icon');\n", - " icon_img.addClass(image);\n", - " icon_img.addClass('ui-corner-all');\n", - "\n", - " var tooltip_span = $('<span/>');\n", - " tooltip_span.addClass('ui-button-text');\n", - " tooltip_span.html(tooltip);\n", - "\n", - " button.append(icon_img);\n", - " button.append(tooltip_span);\n", - "\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " var fmt_picker_span = $('<span/>');\n", - "\n", - " var fmt_picker = $('<select/>');\n", - " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n", - " fmt_picker_span.append(fmt_picker);\n", - " nav_element.append(fmt_picker_span);\n", - " this.format_dropdown = fmt_picker[0];\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = $(\n", - " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n", - " fmt_picker.append(option)\n", - " }\n", - "\n", - " // Add hover states to the ui-buttons\n", - " $( \".ui-button\" ).hover(\n", - " function() { $(this).addClass(\"ui-state-hover\");},\n", - " function() { $(this).removeClass(\"ui-state-hover\");}\n", - " );\n", - "\n", - " var status_bar = $('<span class=\"mpl-message\"/>');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "}\n", - "\n", - "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n", - "}\n", - "\n", - "mpl.figure.prototype.send_message = function(type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "}\n", - "\n", - "mpl.figure.prototype.send_draw_message = function() {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n", - " }\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "}\n", - "\n", - "\n", - "mpl.figure.prototype.handle_resize = function(fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1]);\n", - " fig.send_message(\"refresh\", {});\n", - " };\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0, 0, fig.canvas.width, fig.canvas.height);\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch(cursor)\n", - " {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_message = function(fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_draw = function(fig, msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "}\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function() {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message(\"ack\", {});\n", - "}\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function(fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = \"image/png\";\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src);\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data);\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig[\"handle_\" + msg_type];\n", - " } catch (e) {\n", - " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n", - " }\n", - " }\n", - " };\n", - "}\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function(e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e)\n", - " e = window.event;\n", - " if (e.target)\n", - " targ = e.target;\n", - " else if (e.srcElement)\n", - " targ = e.srcElement;\n", - " if (targ.nodeType == 3) // defeat Safari bug\n", - " targ = targ.parentNode;\n", - "\n", - " // jQuery normalizes the pageX and pageY\n", - " // pageX,Y are the mouse positions relative to the document\n", - " // offset() returns the position of the element relative to the document\n", - " var x = e.pageX - $(targ).offset().left;\n", - " var y = e.pageY - $(targ).offset().top;\n", - "\n", - " return {\"x\": x, \"y\": y};\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys (original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object')\n", - " obj[key] = original[key]\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function(event, name) {\n", - " var canvas_pos = mpl.findpos(event)\n", - "\n", - " if (name === 'button_press')\n", - " {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {x: x, y: y, button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event)});\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "}\n", - "\n", - "mpl.figure.prototype.key_event = function(event, name) {\n", - "\n", - " // Prevent repeat events\n", - " if (name == 'key_press')\n", - " {\n", - " if (event.which === this._key)\n", - " return;\n", - " else\n", - " this._key = event.which;\n", - " }\n", - " if (name == 'key_release')\n", - " this._key = null;\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which != 17)\n", - " value += \"ctrl+\";\n", - " if (event.altKey && event.which != 18)\n", - " value += \"alt+\";\n", - " if (event.shiftKey && event.which != 16)\n", - " value += \"shift+\";\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, {key: value,\n", - " guiEvent: simpleKeys(event)});\n", - " return false;\n", - "}\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n", - " if (name == 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message(\"toolbar_button\", {name: name});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function() {\n", - " comm.close()\n", - " };\n", - " ws.send = function(m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function(msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data'])\n", - " });\n", - " return ws;\n", - "}\n", - "\n", - "mpl.mpl_figure_comm = function(comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = $(\"#\" + id);\n", - " var ws_proxy = comm_websocket_adapter(comm)\n", - "\n", - " function ondownload(figure, format) {\n", - " window.open(figure.imageObj.src);\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy,\n", - " ondownload,\n", - " element.get(0));\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element.get(0);\n", - " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n", - " if (!fig.cell_info) {\n", - " console.error(\"Failed to find cell for figure\", id, fig);\n", - " return;\n", - " }\n", - "\n", - " var output_index = fig.cell_info[2]\n", - " var cell = fig.cell_info[0];\n", - "\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function(fig, msg) {\n", - " var width = fig.canvas.width/mpl.ratio\n", - " fig.root.unbind('remove')\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n", - " fig.close_ws(fig, msg);\n", - "}\n", - "\n", - "mpl.figure.prototype.close_ws = function(fig, msg){\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "}\n", - "\n", - "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width/mpl.ratio\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n", - "}\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function() {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message(\"ack\", {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () { fig.push_to_output() }, 1000);\n", - "}\n", - "\n", - "mpl.figure.prototype._init_toolbar = function() {\n", - " var fig = this;\n", - "\n", - " var nav_element = $('<div/>')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items){\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) { continue; };\n", - "\n", - " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n", - " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n", - " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", - " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", - " buttongrp.append(button);\n", - " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", - " titlebar.prepend(buttongrp);\n", - "}\n", - "\n", - "mpl.figure.prototype._root_extra_style = function(el){\n", - " var fig = this\n", - " el.on(\"remove\", function(){\n", - "\tfig.close_ws(fig, {});\n", - " });\n", - "}\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(el){\n", - " // this is important to make the div 'focusable\n", - " el.attr('tabindex', 0)\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " }\n", - " else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager)\n", - " manager = IPython.keyboard_manager;\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which == 13) {\n", - " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", - " }\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " fig.ondownload(fig, null);\n", - "}\n", - "\n", - "\n", - "mpl.find_output_cell = function(html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i=0; i<ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code'){\n", - " for (var j=0; j<cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] == html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "}\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel != null) {\n", - " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", - "}\n" - ], + "application/javascript": "/* Put everything inside the global mpl namespace */\nwindow.mpl = {};\n\n\nmpl.get_websocket_type = function() {\n if (typeof(WebSocket) !== 'undefined') {\n return WebSocket;\n } else if (typeof(MozWebSocket) !== 'undefined') {\n return MozWebSocket;\n } else {\n alert('Your browser does not have WebSocket support.' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.');\n };\n}\n\nmpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = (this.ws.binaryType != undefined);\n\n if (!this.supports_binary) {\n var warnings = document.getElementById(\"mpl-warnings\");\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent = (\n \"This browser does not support binary websocket messages. \" +\n \"Performance may be slow.\");\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = $('<div/>');\n this._root_extra_style(this.root)\n this.root.attr('style', 'display: inline-block');\n\n $(parent_element).append(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n fig.send_message(\"send_image_mode\", {});\n if (mpl.ratio != 1) {\n fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n }\n fig.send_message(\"refresh\", {});\n }\n\n this.imageObj.onload = function() {\n if (fig.image_mode == 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function() {\n fig.ws.close();\n }\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n}\n\nmpl.figure.prototype._init_header = function() {\n var titlebar = $(\n '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n 'ui-helper-clearfix\"/>');\n var titletext = $(\n '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n 'text-align: center; padding: 3px;\"/>');\n titlebar.append(titletext)\n this.root.append(titlebar);\n this.header = titletext[0];\n}\n\n\n\nmpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n\n}\n\n\nmpl.figure.prototype._root_extra_style = function(canvas_div) {\n\n}\n\nmpl.figure.prototype._init_canvas = function() {\n var fig = this;\n\n var canvas_div = $('<div/>');\n\n canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n\n function canvas_keyboard_event(event) {\n return fig.key_event(event, event['data']);\n }\n\n canvas_div.keydown('key_press', canvas_keyboard_event);\n canvas_div.keyup('key_release', canvas_keyboard_event);\n this.canvas_div = canvas_div\n this._canvas_extra_style(canvas_div)\n this.root.append(canvas_div);\n\n var canvas = $('<canvas/>');\n canvas.addClass('mpl-canvas');\n canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n\n this.canvas = canvas[0];\n this.context = canvas[0].getContext(\"2d\");\n\n var backingStore = this.context.backingStorePixelRatio ||\n\tthis.context.webkitBackingStorePixelRatio ||\n\tthis.context.mozBackingStorePixelRatio ||\n\tthis.context.msBackingStorePixelRatio ||\n\tthis.context.oBackingStorePixelRatio ||\n\tthis.context.backingStorePixelRatio || 1;\n\n mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n var rubberband = $('<canvas/>');\n rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n\n var pass_mouse_events = true;\n\n canvas_div.resizable({\n start: function(event, ui) {\n pass_mouse_events = false;\n },\n resize: function(event, ui) {\n fig.request_resize(ui.size.width, ui.size.height);\n },\n stop: function(event, ui) {\n pass_mouse_events = true;\n fig.request_resize(ui.size.width, ui.size.height);\n },\n });\n\n function mouse_event_fn(event) {\n if (pass_mouse_events)\n return fig.mouse_event(event, event['data']);\n }\n\n rubberband.mousedown('button_press', mouse_event_fn);\n rubberband.mouseup('button_release', mouse_event_fn);\n // Throttle sequential mouse events to 1 every 20ms.\n rubberband.mousemove('motion_notify', mouse_event_fn);\n\n rubberband.mouseenter('figure_enter', mouse_event_fn);\n rubberband.mouseleave('figure_leave', mouse_event_fn);\n\n canvas_div.on(\"wheel\", function (event) {\n event = event.originalEvent;\n event['data'] = 'scroll'\n if (event.deltaY < 0) {\n event.step = 1;\n } else {\n event.step = -1;\n }\n mouse_event_fn(event);\n });\n\n canvas_div.append(canvas);\n canvas_div.append(rubberband);\n\n this.rubberband = rubberband;\n this.rubberband_canvas = rubberband[0];\n this.rubberband_context = rubberband[0].getContext(\"2d\");\n this.rubberband_context.strokeStyle = \"#000000\";\n\n this._resize_canvas = function(width, height) {\n // Keep the size of the canvas, canvas container, and rubber band\n // canvas in synch.\n canvas_div.css('width', width)\n canvas_div.css('height', height)\n\n canvas.attr('width', width * mpl.ratio);\n canvas.attr('height', height * mpl.ratio);\n canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n\n rubberband.attr('width', width);\n rubberband.attr('height', height);\n }\n\n // Set the figure to an initial 600x600px, this will subsequently be updated\n // upon first draw.\n this._resize_canvas(600, 600);\n\n // Disable right mouse context menu.\n $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n return false;\n });\n\n function set_focus () {\n canvas.focus();\n canvas_div.focus();\n }\n\n window.setTimeout(set_focus, 100);\n}\n\nmpl.figure.prototype._init_toolbar = function() {\n var fig = this;\n\n var nav_element = $('<div/>')\n nav_element.attr('style', 'width: 100%');\n this.root.append(nav_element);\n\n // Define a callback function for later on.\n function toolbar_event(event) {\n return fig.toolbar_button_onclick(event['data']);\n }\n function toolbar_mouse_event(event) {\n return fig.toolbar_button_onmouseover(event['data']);\n }\n\n for(var toolbar_ind in mpl.toolbar_items) {\n var name = mpl.toolbar_items[toolbar_ind][0];\n var tooltip = mpl.toolbar_items[toolbar_ind][1];\n var image = mpl.toolbar_items[toolbar_ind][2];\n var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n if (!name) {\n // put a spacer in here.\n continue;\n }\n var button = $('<button/>');\n button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n 'ui-button-icon-only');\n button.attr('role', 'button');\n button.attr('aria-disabled', 'false');\n button.click(method_name, toolbar_event);\n button.mouseover(tooltip, toolbar_mouse_event);\n\n var icon_img = $('<span/>');\n icon_img.addClass('ui-button-icon-primary ui-icon');\n icon_img.addClass(image);\n icon_img.addClass('ui-corner-all');\n\n var tooltip_span = $('<span/>');\n tooltip_span.addClass('ui-button-text');\n tooltip_span.html(tooltip);\n\n button.append(icon_img);\n button.append(tooltip_span);\n\n nav_element.append(button);\n }\n\n var fmt_picker_span = $('<span/>');\n\n var fmt_picker = $('<select/>');\n fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n fmt_picker_span.append(fmt_picker);\n nav_element.append(fmt_picker_span);\n this.format_dropdown = fmt_picker[0];\n\n for (var ind in mpl.extensions) {\n var fmt = mpl.extensions[ind];\n var option = $(\n '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n fmt_picker.append(option)\n }\n\n // Add hover states to the ui-buttons\n $( \".ui-button\" ).hover(\n function() { $(this).addClass(\"ui-state-hover\");},\n function() { $(this).removeClass(\"ui-state-hover\");}\n );\n\n var status_bar = $('<span class=\"mpl-message\"/>');\n nav_element.append(status_bar);\n this.message = status_bar[0];\n}\n\nmpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n // which will in turn request a refresh of the image.\n this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n}\n\nmpl.figure.prototype.send_message = function(type, properties) {\n properties['type'] = type;\n properties['figure_id'] = this.id;\n this.ws.send(JSON.stringify(properties));\n}\n\nmpl.figure.prototype.send_draw_message = function() {\n if (!this.waiting) {\n this.waiting = true;\n this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n }\n}\n\n\nmpl.figure.prototype.handle_save = function(fig, msg) {\n var format_dropdown = fig.format_dropdown;\n var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n fig.ondownload(fig, format);\n}\n\n\nmpl.figure.prototype.handle_resize = function(fig, msg) {\n var size = msg['size'];\n if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n fig._resize_canvas(size[0], size[1]);\n fig.send_message(\"refresh\", {});\n };\n}\n\nmpl.figure.prototype.handle_rubberband = function(fig, msg) {\n var x0 = msg['x0'] / mpl.ratio;\n var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n var x1 = msg['x1'] / mpl.ratio;\n var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n x0 = Math.floor(x0) + 0.5;\n y0 = Math.floor(y0) + 0.5;\n x1 = Math.floor(x1) + 0.5;\n y1 = Math.floor(y1) + 0.5;\n var min_x = Math.min(x0, x1);\n var min_y = Math.min(y0, y1);\n var width = Math.abs(x1 - x0);\n var height = Math.abs(y1 - y0);\n\n fig.rubberband_context.clearRect(\n 0, 0, fig.canvas.width, fig.canvas.height);\n\n fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n}\n\nmpl.figure.prototype.handle_figure_label = function(fig, msg) {\n // Updates the figure title.\n fig.header.textContent = msg['label'];\n}\n\nmpl.figure.prototype.handle_cursor = function(fig, msg) {\n var cursor = msg['cursor'];\n switch(cursor)\n {\n case 0:\n cursor = 'pointer';\n break;\n case 1:\n cursor = 'default';\n break;\n case 2:\n cursor = 'crosshair';\n break;\n case 3:\n cursor = 'move';\n break;\n }\n fig.rubberband_canvas.style.cursor = cursor;\n}\n\nmpl.figure.prototype.handle_message = function(fig, msg) {\n fig.message.textContent = msg['message'];\n}\n\nmpl.figure.prototype.handle_draw = function(fig, msg) {\n // Request the server to send over a new figure.\n fig.send_draw_message();\n}\n\nmpl.figure.prototype.handle_image_mode = function(fig, msg) {\n fig.image_mode = msg['mode'];\n}\n\nmpl.figure.prototype.updated_canvas_event = function() {\n // Called whenever the canvas gets updated.\n this.send_message(\"ack\", {});\n}\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function(fig) {\n return function socket_on_message(evt) {\n if (evt.data instanceof Blob) {\n /* FIXME: We get \"Resource interpreted as Image but\n * transferred with MIME type text/plain:\" errors on\n * Chrome. But how to set the MIME type? It doesn't seem\n * to be part of the websocket stream */\n evt.data.type = \"image/png\";\n\n /* Free the memory for the previous frames */\n if (fig.imageObj.src) {\n (window.URL || window.webkitURL).revokeObjectURL(\n fig.imageObj.src);\n }\n\n fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n evt.data);\n fig.updated_canvas_event();\n fig.waiting = false;\n return;\n }\n else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n fig.imageObj.src = evt.data;\n fig.updated_canvas_event();\n fig.waiting = false;\n return;\n }\n\n var msg = JSON.parse(evt.data);\n var msg_type = msg['type'];\n\n // Call the \"handle_{type}\" callback, which takes\n // the figure and JSON message as its only arguments.\n try {\n var callback = fig[\"handle_\" + msg_type];\n } catch (e) {\n console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n return;\n }\n\n if (callback) {\n try {\n // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n callback(fig, msg);\n } catch (e) {\n console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n }\n }\n };\n}\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.findpos = function(e) {\n //this section is from http://www.quirksmode.org/js/events_properties.html\n var targ;\n if (!e)\n e = window.event;\n if (e.target)\n targ = e.target;\n else if (e.srcElement)\n targ = e.srcElement;\n if (targ.nodeType == 3) // defeat Safari bug\n targ = targ.parentNode;\n\n // jQuery normalizes the pageX and pageY\n // pageX,Y are the mouse positions relative to the document\n // offset() returns the position of the element relative to the document\n var x = e.pageX - $(targ).offset().left;\n var y = e.pageY - $(targ).offset().top;\n\n return {\"x\": x, \"y\": y};\n};\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * http://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys (original) {\n return Object.keys(original).reduce(function (obj, key) {\n if (typeof original[key] !== 'object')\n obj[key] = original[key]\n return obj;\n }, {});\n}\n\nmpl.figure.prototype.mouse_event = function(event, name) {\n var canvas_pos = mpl.findpos(event)\n\n if (name === 'button_press')\n {\n this.canvas.focus();\n this.canvas_div.focus();\n }\n\n var x = canvas_pos.x * mpl.ratio;\n var y = canvas_pos.y * mpl.ratio;\n\n this.send_message(name, {x: x, y: y, button: event.button,\n step: event.step,\n guiEvent: simpleKeys(event)});\n\n /* This prevents the web browser from automatically changing to\n * the text insertion cursor when the button is pressed. We want\n * to control all of the cursor setting manually through the\n * 'cursor' event from matplotlib */\n event.preventDefault();\n return false;\n}\n\nmpl.figure.prototype._key_event_extra = function(event, name) {\n // Handle any extra behaviour associated with a key event\n}\n\nmpl.figure.prototype.key_event = function(event, name) {\n\n // Prevent repeat events\n if (name == 'key_press')\n {\n if (event.which === this._key)\n return;\n else\n this._key = event.which;\n }\n if (name == 'key_release')\n this._key = null;\n\n var value = '';\n if (event.ctrlKey && event.which != 17)\n value += \"ctrl+\";\n if (event.altKey && event.which != 18)\n value += \"alt+\";\n if (event.shiftKey && event.which != 16)\n value += \"shift+\";\n\n value += 'k';\n value += event.which.toString();\n\n this._key_event_extra(event, name);\n\n this.send_message(name, {key: value,\n guiEvent: simpleKeys(event)});\n return false;\n}\n\nmpl.figure.prototype.toolbar_button_onclick = function(name) {\n if (name == 'download') {\n this.handle_save(this, null);\n } else {\n this.send_message(\"toolbar_button\", {name: name});\n }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n this.message.textContent = tooltip;\n};\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n // Create a \"websocket\"-like object which calls the given IPython comm\n // object with the appropriate methods. Currently this is a non binary\n // socket, so there is still some room for performance tuning.\n var ws = {};\n\n ws.close = function() {\n comm.close()\n };\n ws.send = function(m) {\n //console.log('sending', m);\n comm.send(m);\n };\n // Register the callback with on_msg.\n comm.on_msg(function(msg) {\n //console.log('receiving', msg['content']['data'], msg);\n // Pass the mpl event to the overridden (by mpl) onmessage function.\n ws.onmessage(msg['content']['data'])\n });\n return ws;\n}\n\nmpl.mpl_figure_comm = function(comm, msg) {\n // This is the function which gets called when the mpl process\n // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n var id = msg.content.data.id;\n // Get hold of the div created by the display call when the Comm\n // socket was opened in Python.\n var element = $(\"#\" + id);\n var ws_proxy = comm_websocket_adapter(comm)\n\n function ondownload(figure, format) {\n window.open(figure.imageObj.src);\n }\n\n var fig = new mpl.figure(id, ws_proxy,\n ondownload,\n element.get(0));\n\n // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n // web socket which is closed, not our websocket->open comm proxy.\n ws_proxy.onopen();\n\n fig.parent_element = element.get(0);\n fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n if (!fig.cell_info) {\n console.error(\"Failed to find cell for figure\", id, fig);\n return;\n }\n\n var output_index = fig.cell_info[2]\n var cell = fig.cell_info[0];\n\n};\n\nmpl.figure.prototype.handle_close = function(fig, msg) {\n var width = fig.canvas.width/mpl.ratio\n fig.root.unbind('remove')\n\n // Update the output cell to use the data from the current canvas.\n fig.push_to_output();\n var dataURL = fig.canvas.toDataURL();\n // Re-enable the keyboard manager in IPython - without this line, in FF,\n // the notebook keyboard shortcuts fail.\n IPython.keyboard_manager.enable()\n $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n fig.close_ws(fig, msg);\n}\n\nmpl.figure.prototype.close_ws = function(fig, msg){\n fig.send_message('closing', msg);\n // fig.ws.close()\n}\n\nmpl.figure.prototype.push_to_output = function(remove_interactive) {\n // Turn the data on the canvas into data in the output cell.\n var width = this.canvas.width/mpl.ratio\n var dataURL = this.canvas.toDataURL();\n this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n}\n\nmpl.figure.prototype.updated_canvas_event = function() {\n // Tell IPython that the notebook contents must change.\n IPython.notebook.set_dirty(true);\n this.send_message(\"ack\", {});\n var fig = this;\n // Wait a second, then push the new image to the DOM so\n // that it is saved nicely (might be nice to debounce this).\n setTimeout(function () { fig.push_to_output() }, 1000);\n}\n\nmpl.figure.prototype._init_toolbar = function() {\n var fig = this;\n\n var nav_element = $('<div/>')\n nav_element.attr('style', 'width: 100%');\n this.root.append(nav_element);\n\n // Define a callback function for later on.\n function toolbar_event(event) {\n return fig.toolbar_button_onclick(event['data']);\n }\n function toolbar_mouse_event(event) {\n return fig.toolbar_button_onmouseover(event['data']);\n }\n\n for(var toolbar_ind in mpl.toolbar_items){\n var name = mpl.toolbar_items[toolbar_ind][0];\n var tooltip = mpl.toolbar_items[toolbar_ind][1];\n var image = mpl.toolbar_items[toolbar_ind][2];\n var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n if (!name) { continue; };\n\n var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n button.click(method_name, toolbar_event);\n button.mouseover(tooltip, toolbar_mouse_event);\n nav_element.append(button);\n }\n\n // Add the status bar.\n var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n nav_element.append(status_bar);\n this.message = status_bar[0];\n\n // Add the close button to the window.\n var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n button.click(function (evt) { fig.handle_close(fig, {}); } );\n button.mouseover('Stop Interaction', toolbar_mouse_event);\n buttongrp.append(button);\n var titlebar = this.root.find($('.ui-dialog-titlebar'));\n titlebar.prepend(buttongrp);\n}\n\nmpl.figure.prototype._root_extra_style = function(el){\n var fig = this\n el.on(\"remove\", function(){\n\tfig.close_ws(fig, {});\n });\n}\n\nmpl.figure.prototype._canvas_extra_style = function(el){\n // this is important to make the div 'focusable\n el.attr('tabindex', 0)\n // reach out to IPython and tell the keyboard manager to turn it's self\n // off when our div gets focus\n\n // location in version 3\n if (IPython.notebook.keyboard_manager) {\n IPython.notebook.keyboard_manager.register_events(el);\n }\n else {\n // location in version 2\n IPython.keyboard_manager.register_events(el);\n }\n\n}\n\nmpl.figure.prototype._key_event_extra = function(event, name) {\n var manager = IPython.notebook.keyboard_manager;\n if (!manager)\n manager = IPython.keyboard_manager;\n\n // Check for shift+enter\n if (event.shiftKey && event.which == 13) {\n this.canvas_div.blur();\n event.shiftKey = false;\n // Send a \"J\" for go to next cell\n event.which = 74;\n event.keyCode = 74;\n manager.command_mode();\n manager.handle_keydown(event);\n }\n}\n\nmpl.figure.prototype.handle_save = function(fig, msg) {\n fig.ondownload(fig, null);\n}\n\n\nmpl.find_output_cell = function(html_output) {\n // Return the cell and output element which can be found *uniquely* in the notebook.\n // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n // IPython event is triggered only after the cells have been serialised, which for\n // our purposes (turning an active figure into a static one), is too late.\n var cells = IPython.notebook.get_cells();\n var ncells = cells.length;\n for (var i=0; i<ncells; i++) {\n var cell = cells[i];\n if (cell.cell_type === 'code'){\n for (var j=0; j<cell.output_area.outputs.length; j++) {\n var data = cell.output_area.outputs[j];\n if (data.data) {\n // IPython >= 3 moved mimebundle to data attribute of output\n data = data.data;\n }\n if (data['text/html'] == html_output) {\n return [cell, data, j];\n }\n }\n }\n }\n}\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel != null) {\n IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n}\n", "text/plain": [ "<IPython.core.display.Javascript object>" ] @@ -2639,14 +1872,15 @@ "source": [ "%pylab notebook\n", "\n", - "plot(sim.runner.spectrum_integrated.frequency, sim.runner.spectrum_integrated.luminosity_density_nu, label='TARDIS')\n", - "#plot(sim.runner.spectrum_integrated.wavelength, sim.runner.spectrum_integrated.luminosity_density_lambda)\n", + "plot(sim.transport.spectrum_integrated.frequency, sim.transport.spectrum_integrated.luminosity_density_nu, label='TARDIS')\n", + "#plot(sim.transport.spectrum_integrated.wavelength, sim.transport.spectrum_integrated.luminosity_density_lambda)\n", "plot(spec_artis_toy['nu'], spec_artis_toy.iloc[:,53] * np.pi * 4 * u.Mpc.to(u.cm)**2, label='ARTIS') \n", "legend()\n", "xlim(0, 1e15)\n" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -2682,6 +1916,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -4346,8 +3581,8 @@ } ], "source": [ - "spectrum = pd.DataFrame(data = sim.runner.spectrum_integrated.frequency.value, columns=['frequency'])\n", - "spectrum['luminosity'] = sim.runner.spectrum_integrated.luminosity_density_nu.value\n", + "spectrum = pd.DataFrame(data = sim.transport.spectrum_integrated.frequency.value, columns=['frequency'])\n", + "spectrum['luminosity'] = sim.transport.spectrum_integrated.luminosity_density_nu.value\n", "\n", "create_df_download_link(spectrum, title='Download Spectrum', filename='spectrum.csv', type='csv')" ] @@ -6392,4 +5627,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} \ No newline at end of file +} diff --git a/docs/resources/credits.rst b/docs/resources/credits.rst index c57155d375c..7b31bfd5a9c 100644 --- a/docs/resources/credits.rst +++ b/docs/resources/credits.rst @@ -4,6 +4,8 @@ Credits & Publication Policies ****************************** +|DOI_BADGE| + We provide TARDIS as a free, open-source tool. If you are using it, please adhere to a few policies and acknowledge the TARDIS Team. @@ -18,13 +20,13 @@ following paragraph to the Acknowledgement section: .. parsed-literal:: This research made use of \\textsc{tardis}, a community-developed software package for spectral - synthesis in supernovae \\citep{2014MNRAS.440..387K, |ZENODO|}. The + synthesis in supernovae \\citep{2014MNRAS.440..387K, |CITATION|}. The development of \\textsc{tardis} received support from GitHub, the Google Summer of Code initiative, and from ESA's Summer of Code in Space program. \\textsc{tardis} is a fiscally sponsored project of NumFOCUS. \\textsc{tardis} makes extensive use of Astropy and Pyne. If you use any of the full relativity treatments or use TARDIS for modelling -Type II supernovae, also add `Spectral modeling of type II supernovae. I. Dilution factors <https://ui.adsabs.harvard.edu/abs/2019A%26A...621A..29V>`_ +Type II supernovae, also add `Spectral modeling of type II supernovae. I. Dilution factors <https://ui.adsabs.harvard.edu/abs/2019A%26A...621A..29V>`_ to the Acknowledgement. .. parsed-literal:: @@ -72,4 +74,118 @@ The following BibTeX entries are needed for the references: adsnote = {Provided by the SAO/NASA Astrophysics Data System} } -.. include:: ZENODO.rst +.. |CITATION| replace:: kerzendorf_wolfgang_2023_8244935 + +.. |DOI_BADGE| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.8244935-blue + :target: https://doi.org/10.5281/zenodo.8244935 + +.. code-block:: bibtex + + @software{kerzendorf_wolfgang_2023_8244935, + author = {Kerzendorf, Wolfgang and + Sim, Stuart and + Vogl, Christian and + Williamson, Marc and + Pássaro, Ezequiel and + Flörs, Andreas and + Camacho, Yssa and + Jančauskas, Vytautas and + Harpole, Alice and + Nöbauer, Ulrich and + Lietzau, Stefan and + Mishin, Mikhail and + Tsamis, Fotis and + Boyle, Aoife and + Shingles, Luke and + Gupta, Vaibhav and + Desai, Karan and + Klauser, Michael and + Beaujean, Frederik and + Suban-Loewen, Adam and + Heringer, Epson and + Barna, Barnabás and + Gautam, Gaurav and + Fullard, Andrew and + Smith, Isaac and + Cawley, Kevin and + Singhal, Jaladh and + Arya, Atharva and + O'Brien, Jack and + Barbosa, Talytha and + Sondhi, Dhruv and + Yu, Jenny and + Patel, Maryam and + Varanasi, Kaushik and + Gillanders, James and + Rathi, Shikha and + Chitchyan, Sona and + Savel, Arjun and + Reinecke, Martin and + Eweis, Youssef and + Bylund, Tomas and + Bentil, Laud and + Black, William and + Shields, Joshua and + Eguren, Jordi and + Alam, Arib and + Kumar, Ansh and + Bartnik, Matthew and + Magee, Mark and + Singh, Shreyas and + Varma Buddaraju, Rohith and + Livneh, Ran and + Kambham, Satwik and + Rajagopalan, Srinath and + Daksh, Ayushi and + Mishra, Sashank and + Jain, Rinkle and + Reichenbach, John and + Floers, Andreas and + Actions, GitHub and + Holas, Alexander and + Singh, Sourav and + Brar, Antreev and + Chaumal, Aarya and + Bhakar, Jayant and + Selsing, Jonatan and + Kowalski, Nathan and + Kumar, Aman and + Patidar, Abhishek and + Talegaonkar, Chinmay and + Sofiatti, Caroline and + Venkat, Shashank and + Sharma, Sampark and + Sarafina, Nance and + Patel, Pratik and + Singh Rathore, Parikshit and + Patra, Nilesh and + Lu, Jing and + Zaheer, Musabbiha and + Sandler, Morgan and + Truong, Le and + Yap, Kevin and + Buchner, Johannes and + Gupta, Suyash and + Prasad, Shilpi and + Kolliboyina, Chaitanya and + Lemoine, Thom and + Wahi, Ujjwal and + Aggarwal, Yash and + Matsumura, Yuki and + Gupta, Harshul and + Volodin, Dmitry and + PATIDAR, ABHISHEK and + Martinez, Laureano and + Kharkar, Atharwa and + Nayak U, Ashwin and + Dasgupta, Debajyoti and + Kumar, Atul}, + title = {tardis-sn/tardis: TARDIS v2023.08.13}, + month = aug, + year = 2023, + publisher = {Zenodo}, + version = {release-2023.08.13}, + doi = {10.5281/zenodo.8244935}, + url = {https://doi.org/10.5281/zenodo.8244935} + } + diff --git a/docs/resources/credits_template.rst b/docs/resources/credits_template.rst new file mode 100644 index 00000000000..0a6d97af335 --- /dev/null +++ b/docs/resources/credits_template.rst @@ -0,0 +1,77 @@ +.. _tardiscredits: + +****************************** +Credits & Publication Policies +****************************** + +|DOI_BADGE| + +We provide TARDIS as a free, open-source tool. If you are using it, please +adhere to a few policies and acknowledge the TARDIS Team. + +Publication Policies +==================== + +If you use this code for any publications or presentations please acknowledge +it. Please cite `Kerzendorf & Sim 2014 +<http://adsabs.harvard.edu/abs/2014MNRAS.440..387K>`_ in the text and add the +following paragraph to the Acknowledgement section: + +.. parsed-literal:: + + This research made use of \\textsc{tardis}, a community-developed software package for spectral + synthesis in supernovae \\citep{2014MNRAS.440..387K, |CITATION|}. The + development of \\textsc{tardis} received support from GitHub, the Google Summer of Code + initiative, and from ESA's Summer of Code in Space program. \\textsc{tardis} is a fiscally + sponsored project of NumFOCUS. \\textsc{tardis} makes extensive use of Astropy and Pyne. + +If you use any of the full relativity treatments or use TARDIS for modelling +Type II supernovae, also add `Spectral modeling of type II supernovae. I. Dilution factors <https://ui.adsabs.harvard.edu/abs/2019A%26A...621A..29V>`_ +to the Acknowledgement. + +.. parsed-literal:: + + \citep{2019A&A...621A..29V} + +The following BibTeX entries are needed for the references: + +.. code-block:: bibtex + + @ARTICLE{2014MNRAS.440..387K, + author = {{Kerzendorf}, W.~E. and {Sim}, S.~A.}, + title = "{A spectral synthesis code for rapid modelling of supernovae}", + journal = {\mnras}, + archivePrefix = "arXiv", + eprint = {1401.5469}, + primaryClass = "astro-ph.SR", + keywords = {radiative transfer, methods: numerical, supernovae: general}, + year = 2014, + month = may, + volume = 440, + pages = {387-404}, + doi = {10.1093/mnras/stu055}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.440..387K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} + } + +.. code-block:: bibtex + + @ARTICLE{2019A&A...621A..29V, + author = {{Vogl}, C. and {Sim}, S.~A. and {Noebauer}, U.~M. and {Kerzendorf}, W.~E. and {Hillebrandt}, W.}, + title = "{Spectral modeling of type II supernovae. I. Dilution factors}", + journal = {\aap}, + keywords = {radiative transfer, methods: numerical, stars: distances, supernovae: general, supernovae: individual: SN1999em, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics}, + year = "2019", + month = "Jan", + volume = {621}, + eid = {A29}, + pages = {A29}, + doi = {10.1051/0004-6361/201833701}, + archivePrefix = {arXiv}, + eprint = {1811.02543}, + primaryClass = {astro-ph.HE}, + adsurl = {https://ui.adsabs.harvard.edu/abs/2019A&A...621A..29V}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} + } + +.. include:: zenodo.rst diff --git a/docs/tardis.bib b/docs/tardis.bib index c56b1b0b164..c324fb30456 100644 --- a/docs/tardis.bib +++ b/docs/tardis.bib @@ -285,3 +285,66 @@ @article{Weinberger2020 month = {Jun}, pages = {32} } + +@ARTICLE{Milne2004, + author = {{Milne}, P.~A. and {Hungerford}, A.~L. and {Fryer}, C.~L. and {Evans}, T.~M. and {Urbatsch}, T.~J. and {Boggs}, S.~E. and {Isern}, J. and {Bravo}, E. and {Hirschmann}, A. and {Kumagai}, S. and {Pinto}, P.~A. and {The}, L. -S.}, + title = "{Unified One-Dimensional Simulations of Gamma-Ray Line Emission from Type Ia Supernovae}", + journal = {\apj}, + keywords = {Gamma Rays: Observations, Gamma Rays: Theory, Stars: Supernovae: General, Astrophysics}, + year = 2004, + month = oct, + volume = {613}, + number = {2}, + pages = {1101-1119}, + doi = {10.1086/423235}, +archivePrefix = {arXiv}, + eprint = {astro-ph/0406173}, + primaryClass = {astro-ph}, + adsurl = {https://ui.adsabs.harvard.edu/abs/2004ApJ...613.1101M}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@book{Jauch1976, + address = {Berlin, Heidelberg}, + title = {The {Theory} of {Photons} and {Electrons}: the {Relativistic} {Quantum} {Field} {Theory} of {Charged} {Particles} with {Spin} {One}-half}, + isbn = {978-3-642-80951-4 978-3-642-80953-8}, + shorttitle = {The {Theory} of {Photons} and {Electrons}}, + url = {https://doi.org/10.1007/978-3-642-80951-4}, + language = {English}, + urldate = {2022-07-27}, + publisher = {Springer Berlin Heidelberg}, + author = {Jauch, J. M and Rohrlich, F}, + year = {1976}, + note = {OCLC: 840300942}, +} + +@ARTICLE{Ore1949, + author = {{Ore}, A. and {Powell}, J.~L.}, + title = "{Three-Photon Annihilation of an Electron-Positron Pair}", + journal = {Physical Review}, + year = 1949, + month = jun, + volume = {75}, + number = {11}, + pages = {1696-1699}, + doi = {10.1103/PhysRev.75.1696}, + adsurl = {https://ui.adsabs.harvard.edu/abs/1949PhRv...75.1696O}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{Boyle2017, + author = {{Boyle}, Aoife and {Sim}, Stuart A. and {Hachinger}, Stephan and {Kerzendorf}, Wolfgang}, + title = "{Helium in double-detonation models of type Ia supernovae}", + journal = {\aap}, + keywords = {supernovae: general, white dwarfs, radiative transfer, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics}, + year = 2017, + month = mar, + volume = {599}, + eid = {A46}, + doi = {10.1051/0004-6361/201629712}, +archivePrefix = {arXiv}, + eprint = {1611.05938}, + primaryClass = {astro-ph.HE}, + adsurl = {https://ui.adsabs.harvard.edu/abs/2017A&A...599A..46B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} diff --git a/docs/working_gamma_ray_test.ipynb b/docs/working_gamma_ray_test.ipynb new file mode 100644 index 00000000000..1a9977e0ff2 --- /dev/null +++ b/docs/working_gamma_ray_test.ipynb @@ -0,0 +1,514 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# General imports\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import astropy.constants as const\n", + "import astropy.units as u\n", + "\n", + "%config InlineBackend.figure_format ='retina'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/anirbandutta/Software/tardis/tardis/__init__.py:20: UserWarning: Astropy is already imported externally. Astropy should be imported after TARDIS.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "19f297a1888c4a9cb184672f8ddfaeed", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ca370adae49a41f9a83706e0560492de", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Packets: 0/? [00:00<?, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# TARDIS imports for the gamma-ray code\n", + "from tardis.io.atom_data import AtomData\n", + "from tardis.model import SimulationState\n", + "from tardis.plasma.base import BasePlasma\n", + "from tardis.io.configuration import config_reader\n", + "from tardis.energy_input.main_gamma_ray_loop import run_gamma_ray_loop\n", + "from tardis.plasma.properties import Density, Abundance, IsotopeAbundance, \\\n", + " IsotopeNumberDensity, AtomicData, AtomicMass, IsotopeMass, NumberDensity, \\\n", + " SelectedAtoms" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:tardis.io.atom_data.base:Reading Atom Data with: UUID = 6f7b09e887a311e7a06b246e96350010 MD5 = 864f1753714343c41f99cb065710cace \n", + "INFO:tardis.io.atom_data.base:Non provided Atomic Data: synpp_refs, photoionization_data, yg_data, two_photon_data, linelist\n" + ] + } + ], + "source": [ + "# Download the atom data file from tardis-refdata repo to run this cell.\n", + "atom_data_file = '/Users/anirbandutta/Software/tardis-refdata/atom_data/kurucz_cd23_chianti_H_He.h5'\n", + "atom_data = AtomData.from_hdf(atom_data_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the config file and create a configuration object\n", + "config = config_reader.Configuration.from_yaml(\"/Users/anirbandutta/Projects/gamma_ray_tardis/tardis_configv1_density_exponential_nebular_Ni_only.yml\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tardis.model.parse_input:Number of density points larger than number of shells. Assuming inner point irrelevant\n", + "WARNING:tardis.model.parse_input:Abundances have not been normalized to 1. - normalizing\n", + "INFO:tardis.model.matter.decay:Decaying abundances for 12960000.0 seconds\n", + "/Users/anirbandutta/Software/tardis/tardis/model/matter/composition.py:101: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '9.288214564694115e-23' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n", + " isotope_mass_df[isotope_tuple] = isotope_mass\n" + ] + } + ], + "source": [ + "# Create the model\n", + "model = SimulationState.from_config(config, atom_data)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th></th>\n", + " <th>0</th>\n", + " <th>1</th>\n", + " <th>2</th>\n", + " <th>3</th>\n", + " <th>4</th>\n", + " <th>5</th>\n", + " <th>6</th>\n", + " 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"source": [ + "# This shows the isotope abundances in the model before decay\n", + "model.composition.raw_isotope_abundance" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Construct the Plasma\n", + "\n", + "input = [Density, Abundance, IsotopeAbundance, AtomicData, AtomicMass, IsotopeNumberDensity, NumberDensity, SelectedAtoms, IsotopeMass]\n", + "\n", + "plasma = BasePlasma(plasma_properties=input, density = model.density, \n", + " abundance=model.abundance, isotope_abundance=model.composition.raw_isotope_abundance,\n", + " atomic_data = atom_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Define the number of MC packets\n", + "num_packets = 100000\n", + "\n", + "np.random.seed(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:tardis.energy_input.main_gamma_ray_loop:Total gamma-ray energy is 2.2720351391575986e+45\n", + "INFO:tardis.energy_input.main_gamma_ray_loop:Total number of packets is 100001\n", + "INFO:tardis.energy_input.main_gamma_ray_loop:Energy per packet is 2.272012419033408e+40\n", + "INFO:tardis.energy_input.main_gamma_ray_loop:Initializing packets\n", + "INFO:tardis.energy_input.gamma_ray_transport:Isotope packet count dataframe\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 7514\n", + "Ni-56 2327\n", + "Name: 0, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 6997\n", + "Ni-56 2167\n", + "Name: 1, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 6495\n", + "Ni-56 2011\n", + "Name: 2, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 6013\n", + "Ni-56 1862\n", + "Name: 3, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 5553\n", + "Ni-56 1719\n", + "Name: 4, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 5115\n", + "Ni-56 1584\n", + "Name: 5, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 4701\n", + "Ni-56 1456\n", + "Name: 6, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 4312\n", + "Ni-56 1335\n", + "Name: 7, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 3948\n", + "Ni-56 1222\n", + "Name: 8, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 3607\n", + "Ni-56 1117\n", + "Name: 9, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 3290\n", + "Ni-56 1019\n", + "Name: 10, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 2996\n", + "Ni-56 928\n", + "Name: 11, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 2725\n", + "Ni-56 844\n", + "Name: 12, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 2474\n", + "Ni-56 766\n", + "Name: 13, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 2243\n", + "Ni-56 695\n", + "Name: 14, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 2031\n", + "Ni-56 629\n", + "Name: 15, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 1837\n", + "Ni-56 569\n", + "Name: 16, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 1659\n", + "Ni-56 514\n", + "Name: 17, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 1497\n", + "Ni-56 463\n", + "Name: 18, dtype: int64\n", + "INFO:tardis.energy_input.gamma_ray_transport:element\n", + "Co-56 1349\n", + "Ni-56 418\n", + "Name: 19, dtype: int64\n", + "INFO:tardis.energy_input.main_gamma_ray_loop:Total cmf energy is 2.2719989296946167e+45\n", + "INFO:tardis.energy_input.main_gamma_ray_loop:Total rf energy is 2.2741126621166735e+45\n", + "/Users/anirbandutta/Software/tardis/tardis/energy_input/gamma_packet_loop.py:131: NumbaPerformanceWarning: \u001b[1m\u001b[1m\u001b[1mnp.dot() is faster on contiguous arrays, called on (Array(float64, 1, 'A', False, aligned=True), Array(float64, 1, 'C', False, aligned=True))\u001b[0m\u001b[0m\u001b[0m\n", + " doppler_factor = doppler_factor_3d(\n", + "/Users/anirbandutta/Software/tardis/tardis/energy_input/gamma_packet_loop.py:202: NumbaPerformanceWarning: \u001b[1m\u001b[1m\u001b[1m\u001b[1mnp.dot() is faster on contiguous arrays, called on (Array(float64, 1, 'C', False, aligned=True), Array(float64, 1, 'A', False, aligned=True))\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n", + " ) = distance_trace(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Entering gamma ray loop for 100001 packets\n", + "Escaped packets: 39018\n", + "Scattered packets: 9792\n" + ] + } + ], + "source": [ + "# Execute this cell to run the simulation\n", + "energy_df, energy_plot_df, escape_energy, decayed_packet_count, energy_plot_positrons, \\\n", + " energy_estimated_deposition, packets_df = run_gamma_ray_loop(model, plasma, num_decays=num_packets, \n", + " time_start=0.0011574074, time_end=20.0, time_space=\"log\", \n", + " time_steps=50, seed=1, positronium_fraction=0.0,\n", + " spectrum_bins=1000, grey_opacity=-1, \n", + " path_to_decay_data=atom_data_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# To construct the gamma-ray spectrum, we need to collect the packets that escaped the ejecta\n", + "# escaped packets ahve status '5'\n", + "\n", + "packets_df_escaped = packets_df[(packets_df['status'] == 5)]" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# See Noebauer and Sim (2019) for more details\n", + "\n", + "H_CGS_KEV = const.h.to(\"keV s\").value\n", + "freq_start = packets_df_escaped['nu_rf'].min()\n", + "freq_stop = packets_df_escaped['nu_rf'].max()\n", + "N = 500\n", + "spectrum_frequency = np.linspace(freq_start, freq_stop, N+1)\n", + "\n", + "emitted_luminosity_hist = np.histogram(packets_df_escaped['nu_rf'],\n", + " weights=packets_df_escaped['lum_rf'],\n", + " bins=spectrum_frequency)[0]\n", + "\n", + "spectrum_frequency = spectrum_frequency[:-1]\n", + "delta_frequency = spectrum_frequency[1] - spectrum_frequency[0] \n", + "\n", + "luminosity_density = emitted_luminosity_hist / delta_frequency\n", + "flux = luminosity_density / (4. * np.pi * (10.0 * u.pc).to(\"cm\").value ** 2.0)\n", + "photon_energy = spectrum_frequency * H_CGS_KEV * 0.001\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.07, 9)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": { + "image/png": { + "height": 433, + "width": 587 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(photon_energy, flux, label='TARDIS spectrum')\n", + "#plt.plot(hesma_model_vm.index, hesma_model_vm['30.10'], label='Hesma 30.10', alpha=0.7)\n", + "\n", + "plt.loglog()\n", + "plt.xlabel(\"Energy (MeV)\")\n", + "plt.ylabel(r\"flux (erg/s/Hz/cm$^{2}$) @ 10 pc\")\n", + "\n", + "plt.legend(loc='best')\n", + "plt.xlim(0.07, 9)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "tardis", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pyproject.toml b/pyproject.toml index 64ef7f2190f..5324634e81f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,11 +22,118 @@ exclude = ''' | buck-out | build | dist - | model # temporary - to remove later - | montecarlo # temporary )/ | setup.py | docs/conf.py | _astropy_init.py ) -''' \ No newline at end of file +''' + +[tool.interrogate] +color = true +#exclude = ["setup.py", "docs", "build"] +#fail-under = 90 +ignore-init-method = true +ignore-init-module = true +ignore-magic = true +ignore-module = true +ignore-nested-functions = false +ignore-nested-classes = true +ignore-private = true +ignore-property-decorators = true +ignore-regex = ["^test"] +ignore-semiprivate = true +ignore-setters = true +omit-covered-files = false +quiet = false +verbose = 0 +#whitelist-regex = [] + +[tool.ruff] +line-length = 80 +lint.select = ["ALL"] +exclude=[] +lint.ignore = [ # NOTE: non-permanent exclusions should be added to `.ruff.toml` instead. + + # flake8-builtins (A) : shadowing a Python built-in. + # New ones should be avoided and is up to maintainers to enforce. + "A00", + + # flake8-annotations (ANN) + "ANN101", # No annotation for `self`. + "ANN102", # No annotation for `cls`. + + # flake8-bugbear (B) + "B008", # FunctionCallArgumentDefault + + # flake8-commas (COM) + "COM812", # TrailingCommaMissing + "COM819", # TrailingCommaProhibited + + # pydocstyle (D) + # Missing Docstrings + "D102", # Missing docstring in public method. Don't check b/c docstring inheritance. + "D105", # Missing docstring in magic method. Don't check b/c class docstring. + # Whitespace Issues + "D200", # FitsOnOneLine + # Docstring Content Issues + "D410", # BlankLineAfterSection. Using D412 instead. + "D400", # EndsInPeriod. NOTE: might want to revisit this. + + # pycodestyle (E, W) + "E711", # NoneComparison (see unfixable) + "E741", # AmbiguousVariableName. Physics variables are often poor code variables + + # flake8-fixme (FIX) + "FIX002", # Line contains TODO | notes for improvements are OK iff the code works + + # ISC001 shouldn't be used with ruff format + # https://docs.astral.sh/ruff/formatter/#conflicting-lint-rules + "ISC001", + + # pep8-naming (N) + "N803", # invalid-argument-name. Physics variables are often poor code variables + "N806", # non-lowercase-variable-in-function. Physics variables are often poor code variables + + # pandas-vet (PD) + "PD", + + # flake8-self (SLF) + "SLF001", # private member access + + # flake8-todos (TD) + "TD002", # Missing author in TODO + + # Ruff-specific rules (RUF) + "RUF005", # unpack-instead-of-concatenating-to-collection-literal -- it's not clearly faster. +] + +[tool.ruff.lint.extend-per-file-ignores] +"setup.py" = ["INP001"] # Part of configuration, not a package. +".github/workflows/*.py" = ["INP001"] +"test_*.py" = [ + "B018", # UselessExpression + "D", # pydocstyle + "S101", # Use of assert detected +] +".pyinstaller/*.py" = ["INP001"] # Not a package. +"conftest.py" = ["INP001"] # Part of configuration, not a package. +"docs/*.py" = [ + "INP001", # implicit-namespace-package. The examples are not a package. +] + +[tool.ruff.lint.flake8-annotations] +ignore-fully-untyped = true +mypy-init-return = true + +[tool.ruff.lint.flake8-comprehensions] +allow-dict-calls-with-keyword-arguments = true + +[tool.ruff.lint.flake8-type-checking] +exempt-modules = [] + +[tool.ruff.lint.isort] +known-first-party = ["tardis", "carsus", "stardis"] + +[tool.ruff.lint.pydocstyle] +convention = "numpy" diff --git a/setup.cfg b/setup.cfg index 33f668a2ecb..b22542f996b 100644 --- a/setup.cfg +++ b/setup.cfg @@ -26,14 +26,22 @@ docs = sphinx-astropy [options.package_data] -tardis = data/* -tardis.io = schemas/*.yml -tardis.io.tests = data/* +tardis = + data/* +tardis.grid = + tests/data/* + ./* +tardis.io = + configuration/schemas/* + configuration/tests/data/* + model/readers/tests/data/* tardis.model.tests = data/* tardis.montecarlo.tests = data/* tardis.plasma.tests = data/* tardis.scripts = debug/* tardis.tests.integration_tests = **/* +tardis.visualization = + tools/tests/data/* [tool:pytest] testpaths = "tardis" # "docs" diff --git a/tardis/__init__.py b/tardis/__init__.py index 820cffad225..5d2ec94e90b 100644 --- a/tardis/__init__.py +++ b/tardis/__init__.py @@ -12,18 +12,22 @@ # ---------------------------------------------------------------------------- import sys -import pyne.data +import warnings # ---------------------------------------------------------------------------- -from tardis.base import run_tardis -from tardis.io.util import yaml_load_config_file as yaml_load +if ("astropy.units" in sys.modules) or ("astropy.constants" in sys.modules): + warnings.warn( + "Astropy is already imported externally. Astropy should be imported" + " after TARDIS." + ) +else: + from astropy import physical_constants, astronomical_constants + physical_constants.set("codata2014") + astronomical_constants.set("iau2012") # ---------------------------------------------------------------------------- -# pyne holds Python 3.7 on macOS, but refdata is pickled with protocol 5 (3.8.3) - -if sys.version_info < (3, 8, 3): - import pickle5 - sys.modules["pickle"] = pickle5 +from tardis.base import run_tardis +from tardis.io.util import yaml_load_file as yaml_load diff --git a/tardis/analysis.py b/tardis/analysis.py index c2f469ed8b7..5c1ceef1e26 100644 --- a/tardis/analysis.py +++ b/tardis/analysis.py @@ -1,24 +1,29 @@ -# codes to for analyse the model. +""" +Code to analyse the model. +""" import re -import os -from astropy import units as u -from tardis import constants import numpy as np import pandas as pd +from astropy import units as u + +from tardis import constants +INVALID_ION_ERROR_MSG = "Atomic number, ion_number pair not present in model" -class LastLineInteraction(object): + +class LastLineInteraction: @classmethod - def from_model(cls, model, packet_filter_mode="packet_out_nu"): + def from_simulation(cls, simulation, packet_filter_mode="packet_out_nu"): + transport_state = simulation.transport.transport_state return cls( - model.runner.last_line_interaction_in_id, - model.runner.last_line_interaction_out_id, - model.runner.last_line_interaction_shell_id, - model.runner.output_nu, - model.runner.last_interaction_in_nu, - model.plasma.atomic_data.lines, + transport_state.last_line_interaction_in_id, + transport_state.last_line_interaction_out_id, + transport_state.last_line_interaction_shell_id, + transport_state.packet_collection.output_nus, + transport_state.last_interaction_in_nu, + simulation.plasma.atomic_data.lines, packet_filter_mode, ) @@ -52,6 +57,7 @@ def __init__( self._wavelength_end = np.inf * u.angstrom self._atomic_number = None self._ion_number = None + self._shell = None self.packet_filter_mode = packet_filter_mode self.update_last_interaction_filter() @@ -83,8 +89,13 @@ def atomic_number(self): @atomic_number.setter def atomic_number(self, value): - self._atomic_number = value - self.update_last_interaction_filter() + old_atomic_number = self._atomic_number + try: + self._atomic_number = value + self.update_last_interaction_filter() + except: + self._atomic_number = old_atomic_number + raise ValueError(INVALID_ION_ERROR_MSG) @property def ion_number(self): @@ -92,8 +103,39 @@ def ion_number(self): @ion_number.setter def ion_number(self, value): - self._ion_number = value - self.update_last_interaction_filter() + old_ion_number = self._ion_number + try: + self._ion_number = value + self.update_last_interaction_filter() + except: + self._ion_number = old_ion_number + raise ValueError(INVALID_ION_ERROR_MSG) + + def set_ion(self, atomic_number, ion_number): + old_atomic_number = self._atomic_number + old_ion_number = self._ion_number + try: + self._atomic_number = atomic_number + self._ion_number = ion_number + self.update_last_interaction_filter() + except: + self._atomic_number = old_atomic_number + self._ion_number = old_ion_number + raise ValueError(INVALID_ION_ERROR_MSG) + + @property + def shell(self): + return self._shell + + @shell.setter + def shell(self, value): + old_shell = self._shell + try: + self._shell = value + self.update_last_interaction_filter() + except: + self._shell = old_shell + raise ValueError("Invalid shell number") def update_last_interaction_filter(self): if self.packet_filter_mode == "packet_out_nu": @@ -120,29 +162,37 @@ def update_last_interaction_filter(self): "allowed are: packet_out_nu, packet_in_nu, line_in_nu" ) - self.last_line_in = self.lines.iloc[ + if self.shell is not None: + packet_filter = packet_filter & ( + self.last_line_interaction_shell_id == self.shell + ) + + last_line_in = self.lines.iloc[ self.last_line_interaction_in_id[packet_filter] ] - self.last_line_out = self.lines.iloc[ + last_line_out = self.lines.iloc[ self.last_line_interaction_out_id[packet_filter] ] if self.atomic_number is not None: - self.last_line_in = self.last_line_in.xs( + last_line_in = last_line_in.xs( self.atomic_number, level="atomic_number", drop_level=False ) - self.last_line_out = self.last_line_out.xs( + last_line_out = last_line_out.xs( self.atomic_number, level="atomic_number", drop_level=False ) if self.ion_number is not None: - self.last_line_in = self.last_line_in.xs( + last_line_in = last_line_in.xs( self.ion_number, level="ion_number", drop_level=False ) - self.last_line_out = self.last_line_out.xs( + last_line_out = last_line_out.xs( self.ion_number, level="ion_number", drop_level=False ) + self.last_line_in = last_line_in + self.last_line_out = last_line_out + last_line_in_count = self.last_line_in.line_id.value_counts() last_line_out_count = self.last_line_out.line_id.value_counts() @@ -211,7 +261,7 @@ def onpress(event): fig.canvas.mpl_connect("on_press", onpress) -class TARDISHistory(object): +class TARDISHistory: """ Records the history of the model """ diff --git a/tardis/analysis_tools/line_ID.py b/tardis/analysis_tools/line_ID.py new file mode 100644 index 00000000000..b19fd610cee --- /dev/null +++ b/tardis/analysis_tools/line_ID.py @@ -0,0 +1,282 @@ +""" This module provides a line identification tool that allows the user to +extract a summary of the most prominent transitions in a TARDIS simulation. """ + +import numpy as np +import pandas as pd +import astropy.units as u + +import matplotlib.pyplot as plt +import matplotlib.ticker as tck + +from tardis.util.base import ( + atomic_number2element_symbol, + int_to_roman, +) + +# Import the SDECData class from the sdec_plot module +from tardis.visualization.tools.sdec_plot import SDECData + + +class LineIdentifier(object): + def __init__(self, data): + """ + Initialize line_identifier with required data of simulation model. + + Parameters + ---------- + data : dict of SDECData + Dictionary to store data required for SDEC plot, for both packet + modes i.e. real and virtual + """ + self.data = data + + @classmethod + def from_simulation(cls, sim): + """ + Create an instance of line_identifier from a TARDIS simulation object. + + Parameters + ---------- + sim : tardis.simulation.Simulation + TARDIS Simulation object produced by running a simulation + + Returns + ------- + line_identifier + """ + if sim.transport.enable_vpacket_tracking: + return cls(SDECData.from_simulation(sim, "virtual")) + else: + return cls(SDECData.from_simulation(sim, "real")) + + def _reset_cache(self): + self._reset_lam_min() + self._reset_lam_max() + self._reset_derived_quantities() + + def _reset_lam_min(self): + self._lam_min = None + + def _reset_lam_max(self): + self._lam_max = None + + def _reset_derived_quantities(self): + self._line_mask = None + self._lam_in = None + self._lines_info_unique = None + self._lines_count = None + self._lines_ids = None + self._lines_ids_unique = None + + @property + def lam_min(self): + if self._lam_min is None: + raise ValueError("lam_min not set") + return self._lam_min + + @lam_min.setter + def lam_min(self, val): + self._reset_derived_quantities() + try: + self._lam_min = val.to(u.AA) + except AttributeError: + self._lam_min = val * u.AA + + @property + def lam_max(self): + if self._lam_max is None: + raise ValueError("lam_max not set") + return self._lam_max + + @lam_max.setter + def lam_max(self, val): + self._reset_derived_quantities() + try: + self._lam_max = val.to(u.AA) + except AttributeError: + self._lam_max = val * u.AA + + @property + def lam_in(self): + if self._lam_in is None: + self._lam_in = u.Quantity( + self.data.packets_df.last_line_interaction_in_nu, u.Hz + ).to(u.AA, equivalencies=u.spectral()) + return self._lam_in + + @property + def line_mask(self): + if self._line_mask is None: + self._line_mask = (self.lam_in >= self.lam_min) * ( + self.lam_in <= self.lam_max + ) + return self._line_mask + + @property + def lines_ids(self): + if self._lines_ids is None: + ids = self.data.packets_df.last_line_interaction_in_id[ + self.line_mask + ].values + self._lines_ids = self.data.lines_df.iloc[ids].index + return self._lines_ids + + @property + def lines_ids_unique(self): + if self._lines_ids_unique is None: + self._lines_ids_unique = np.unique(self.lines_ids) + return self._lines_ids_unique + + @property + def lines_info_unique(self): + if self._lines_info_unique is None: + self._lines_info_unique = self.data.lines_df.loc[ + self.lines_ids_unique + ] + return self._lines_info_unique + + @property + def lines_count(self): + if self._lines_count is None: + counts = np.bincount(self.lines_ids) + self._lines_count = counts[counts > 0] + return self._lines_count + + def identify(self, lam_min, lam_max): + self.lam_min = lam_min + self.lam_max = lam_max + + def plot_summary( + self, nlines=None, lam_min=None, lam_max=None, output_filename=None + ): + + fig = plt.figure() + ax = fig.add_subplot() + fig.subplots_adjust(left=0.2) + + ax.tick_params( + axis="x", direction="in", top=True, bottom=True, which="both" + ) + ax.xaxis.set_minor_locator(tck.AutoMinorLocator()) + + if lam_min is None: + self.lam_min = np.min(self.data.spectrum_wavelength).value + else: + self.lam_min = lam_min + + if lam_max is None: + self.lam_max = np.max(self.data.spectrum_wavelength).value + else: + self.lam_max = lam_max + + _lines_count = self.lines_count[np.argsort(self.lines_count)][::-1] + + _lines_fraction = self.lines_count[np.argsort(self.lines_count)][ + ::-1 + ] / float(self.lines_count.sum()) + + _lines_ids = self.lines_ids_unique[np.argsort(self.lines_count)][::-1] + + if nlines is None: + if len(_lines_count) > 20: + self.nlines = 20 + else: + self.nlines = len(_lines_count) + else: + if len(_lines_count) > nlines: + self.nlines = nlines + else: + self.nlines = len(_lines_count) + + species = [] + wavelengths = [] + labels = [] + + for line_id in _lines_ids: + chemical_symbol = atomic_number2element_symbol( + self.lines_info_unique.loc[line_id].atomic_number + ) + + ionisation_level = int_to_roman( + int(self.lines_info_unique.loc[line_id].ion_number) + 1 + ) + + species.append(f"{chemical_symbol} {ionisation_level}") + + wavelengths.append( + f"{self.lines_info_unique.loc[line_id].wavelength:.3f}" + ) + + labels.append( + f"{chemical_symbol}$\,${ionisation_level} $\lambda${self.lines_info_unique.loc[line_id].wavelength:.3f}" + ) + + # Parameters for the output plot + ax.set_title( + f"Line transitions for ${self.lam_min.value:.1f} \leq \lambda (\mathrm{{\AA}}) \leq {self.lam_max.value:.1f}$" + ) + + ax.barh(np.arange(self.nlines), _lines_fraction[: self.nlines][::-1]) + + ax.set_xlabel("Fraction of total line transitions in wavelength range") + + ax.set_yticks(np.arange(len(_lines_fraction[: self.nlines][::-1]))) + ax.set_yticklabels(labels[: self.nlines][::-1], size="medium") + + ax.annotate( + f"{self.nlines}/{len(self.lines_count)} lines displayed\n {np.sum(_lines_count[:self.nlines])}/{len(self.lines_ids)} interacting and\n escaping r-packets displayed", + xy=(0.95, 0.05), + xycoords="axes fraction", + horizontalalignment="right", + verticalalignment="bottom", + ) + + """ Below we export the compiled line information to output .csv files, + IF the user specifies an output filename for them. """ + + # This gives output file for contributions of lines + if output_filename != None: + dataframe = pd.DataFrame( + { + "Species": species, + "Wavelength(AA)": wavelengths, + "Total_no_transitions": _lines_count, + "Fraction_total_transitions": _lines_fraction, + } + ) + + with open(output_filename, "w") as file: + file.write( + f"# Line transitions in wavelength range {self.lam_min.value:.1f}-{self.lam_max.value:.1f} Angstroms \n" + ) + + dataframe.to_csv(file, sep="\t", index=False) + + # This gives collapsed contributions for species summed across all lines + if output_filename != None: + dataframe = pd.DataFrame( + { + "Species": species, + "Wavelength(AA)": wavelengths, + "Total_no_transitions": _lines_count, + "Fraction_total_transitions": _lines_fraction, + } + ) + + dataframe_collapsed = dataframe.groupby(["Species"]).sum() + dataframe_collapsed = dataframe_collapsed.drop( + columns=["Wavelength(AA)"] + ) + + dataframe_collapsed = dataframe_collapsed.sort_values( + by=["Total_no_transitions"], ascending=False + ) + + with open( + f"{output_filename[:-4]}_collapsed{output_filename[-4:]}", "w" + ) as file: + file.write( + f"# Line transitions in wavelength range {self.lam_min.value:.1f}-{self.lam_max.value:.1f} Angstroms \n" + ) + + dataframe_collapsed.to_csv(file, sep="\t", index=True) diff --git a/tardis/analysis/opacities.py b/tardis/analysis_tools/opacities.py similarity index 98% rename from tardis/analysis/opacities.py rename to tardis/analysis_tools/opacities.py index 09d4f04c8db..35044c6b507 100644 --- a/tardis/analysis/opacities.py +++ b/tardis/analysis_tools/opacities.py @@ -1,11 +1,14 @@ """This module provides an opacity calculator class with which the opacities and optical depth information may be extracted from Tardis runs.""" + import logging import numpy as np + import astropy.units as units -import astropy.constants as csts from astropy.modeling.blackbody import blackbody_nu +from tardis import constants as const + logger = logging.getLogger(__name__) @@ -320,7 +323,7 @@ def _calc_expansion_opacity(self): tmp * self.nu_bins[i] / (self.nu_bins[i + 1] - self.nu_bins[i]) - / (csts.c * self.t_exp) + / (const.c * self.t_exp) ) return kappa_exp.to("1/cm") @@ -339,10 +342,10 @@ def _calc_thomson_scattering_opacity(self): """ try: - sigma_T = csts.sigma_T + sigma_T = const.sigma_T except AttributeError: logger.warning("using astropy < 1.1.1: setting sigma_T manually") - sigma_T = 6.65245873e-29 * units.m ** 2 + sigma_T = 6.65245873e-29 * units.m**2 edens = self.mdl.plasma.electron_densities.values @@ -350,7 +353,7 @@ def _calc_thomson_scattering_opacity(self): edens.to("1/cm^3") except AttributeError: logger.info("setting electron density units by hand (cm^-3)") - edens = edens / units.cm ** 3 + edens = edens / units.cm**3 kappa_thom = edens * sigma_T diff --git a/tardis/base.py b/tardis/base.py index b404145f296..aafdb593abb 100644 --- a/tardis/base.py +++ b/tardis/base.py @@ -1,4 +1,6 @@ -# Functions that are important for the general usage of TARDIS. +""" +Functions that are important for the general usage of TARDIS. +""" import logging @@ -12,7 +14,7 @@ def run_tardis( packet_source=None, simulation_callbacks=[], virtual_packet_logging=False, - show_convergence_plots=True, + show_convergence_plots=False, log_level=None, specific_log_level=None, show_progress_bars=True, @@ -32,7 +34,7 @@ def run_tardis( the atomic data. Atomic data to use for this TARDIS simulation. If set to None (i.e. default), the atomic data will be loaded according to keywords set in the configuration packet_source : class, optional - A custom packet source class or a child class of `tardis.montecarlo.packet_source` + A custom packet source class or a child class of `tardis.transport.montecarlo.packet_source` used to override the TARDIS `BasePacketSource` class. simulation_callbacks : list of lists, default: `[]`, optional Set of callbacks to call at the end of every iteration of the Simulation. @@ -51,7 +53,7 @@ def run_tardis( If True, only show the log messages from a particular log level, set by `log_level`. If False, the logger shows log messages belonging to the level set and all levels above it in severity. The default value None means that the `specific_log_level` specified in the configuration file will be used. - show_convergence_plots : bool, default: True, optional + show_convergence_plots : bool, default: False, optional Option to enable tardis convergence plots. show_progress_bars : bool, default: True, optional Option to enable the progress bar. @@ -69,7 +71,7 @@ def run_tardis( Please see the `logging tutorial <https://tardis-sn.github.io/tardis/io/optional/logging_configuration.html>`_ to know more about `log_level` and `specific` options. """ from tardis.io.logger.logger import logging_state - from tardis.io.config_reader import Configuration + from tardis.io.configuration.config_reader import Configuration from tardis.io.atom_data.base import AtomData from tardis.simulation import Simulation @@ -110,6 +112,7 @@ def run_tardis( for cb in simulation_callbacks: simulation.add_callback(*cb) - simulation.run() + simulation.run_convergence() + simulation.run_final() return simulation diff --git a/tardis/conftest.py b/tardis/conftest.py index 86924c02e44..42530086111 100644 --- a/tardis/conftest.py +++ b/tardis/conftest.py @@ -1,3 +1,19 @@ +import os +from pathlib import Path + +import pandas as pd +import pytest +from astropy.version import version as astropy_version + +from tardis.io.configuration.config_reader import Configuration +from tardis.io.util import YAMLLoader, yaml_load_file +from tardis.simulation import Simulation +from tardis.tests.fixtures.atom_data import * +from tardis.tests.fixtures.regression_data import regression_data + +# ensuring that regression_data is not removed by ruff +assert regression_data is not None + """Configure Test Suite. This file is used to configure the behavior of pytest when using the Astropy @@ -7,9 +23,6 @@ """ -import os - -from astropy.version import version as astropy_version # For Astropy 3.0 and later, we can use the standalone pytest plugin if astropy_version < "3.0": @@ -38,7 +51,6 @@ def pytest_configure(config): """ if ASTROPY_HEADER: - config.option.astropy_header = True # Customize the following lines to add/remove entries from the list of @@ -51,6 +63,14 @@ def pytest_configure(config): packagename = os.path.basename(os.path.dirname(__file__)) TESTED_VERSIONS[packagename] = __version__ + # Create a marker to ignore the `--generate-reference` flag. A use case for this + # marker is when there is data in the reference data repository that can't be + # generated by TARDIS, like the Arepo snapshots. + config.addinivalue_line( + "markers", + "ignore_generate: mark test to not generate new reference data", + ) + # Uncomment the last two lines in this block to treat all DeprecationWarnings as # exceptions. For Astropy v2.0 or later, there are 2 additional keywords, @@ -62,24 +82,24 @@ def pytest_configure(config): # To ignore some specific deprecation warning messages for Python version # MAJOR.MINOR or later, add: # warnings_to_ignore_by_pyver={(MAJOR, MINOR): ['Message to ignore']} -# from astropy.tests.helper import enable_deprecations_as_exceptions # noqa +# from astropy.tests.helper import enable_deprecations_as_exceptions # enable_deprecations_as_exceptions() # ------------------------------------------------------------------------- # Here the TARDIS testing stuff begins # ------------------------------------------------------------------------- -import pytest -import pandas as pd -from tardis.io.util import yaml_load_config_file -from tardis.io.config_reader import Configuration -from tardis.simulation import Simulation - def pytest_addoption(parser): parser.addoption( "--tardis-refdata", default=None, help="Path to Tardis Reference Folder" ) + parser.addoption( + "--tardis-regression-data", + default=None, + help="Path to the TARDIS regression data directory", + ) + parser.addoption( "--integration-tests", dest="integration-tests", @@ -100,6 +120,17 @@ def pytest_addoption(parser): ) +# Required by the `ignore_generate` marker +def pytest_collection_modifyitems(config, items): + if config.getoption("--generate-reference"): + skip_generate = pytest.mark.skip(reason="Skip generate reference data") + for item in items: + if "ignore_generate" in item.keywords: + item.add_marker(skip_generate) + # automatically set update snapshots to true + config.option.update_snapshots = True + + # ------------------------------------------------------------------------- # project specific fixtures # ------------------------------------------------------------------------- @@ -120,10 +151,18 @@ def tardis_ref_path(request): if tardis_ref_path is None: pytest.skip("--tardis-refdata was not specified") else: - return os.path.expandvars(os.path.expanduser(tardis_ref_path)) + return Path(os.path.expandvars(os.path.expanduser(tardis_ref_path))) -from tardis.tests.fixtures.atom_data import * +@pytest.fixture(scope="session") +def tardis_snapshot_path(request): + tardis_snapshot_path = request.config.getoption("--tardis-snapshot-data") + if tardis_snapshot_path is None: + pytest.skip("--tardis-snapshot-data was not specified") + else: + return Path( + os.path.expandvars(os.path.expanduser(tardis_snapshot_path)) + ) @pytest.yield_fixture(scope="session") @@ -132,16 +171,23 @@ def tardis_ref_data(tardis_ref_path, generate_reference): mode = "w" else: mode = "r" - with pd.HDFStore( - os.path.join(tardis_ref_path, "unit_test_data.h5"), mode=mode - ) as store: + with pd.HDFStore(tardis_ref_path / "unit_test_data.h5", mode=mode) as store: yield store -@pytest.fixture +@pytest.fixture(scope="function") def tardis_config_verysimple(): - return yaml_load_config_file( - "tardis/io/tests/data/tardis_configv1_verysimple.yml" + return yaml_load_file( + "tardis/io/configuration/tests/data/tardis_configv1_verysimple.yml", + YAMLLoader, + ) + + +@pytest.fixture(scope="function") +def tardis_config_verysimple_nlte(): + return yaml_load_file( + "tardis/io/configuration/tests/data/tardis_configv1_nlte.yml", + YAMLLoader, ) @@ -157,11 +203,27 @@ def hdf_file_path(tmpdir_factory): @pytest.fixture(scope="session") -def config_verysimple(): - filename = "tardis_configv1_verysimple.yml" - path = os.path.abspath(os.path.join("tardis/io/tests/data/", filename)) - config = Configuration.from_yaml(path) - return config +def example_model_file_dir(): + return Path("tardis/io/model/readers/tests/data") + + +@pytest.fixture(scope="session") +def example_configuration_dir(): + return Path("tardis/io/configuration/tests/data") + + +@pytest.fixture(scope="session") +def config_verysimple(example_configuration_dir): + return Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_verysimple.yml" + ) + + +@pytest.fixture(scope="function") +def config_montecarlo_1e5_verysimple(example_configuration_dir): + return Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_verysimple.yml" + ) @pytest.fixture(scope="session") @@ -170,3 +232,14 @@ def simulation_verysimple(config_verysimple, atomic_dataset): sim = Simulation.from_config(config_verysimple, atom_data=atomic_data) sim.iterate(4000) return sim + + +@pytest.fixture(scope="session") +def simulation_verysimple_vpacket_tracking(config_verysimple, atomic_dataset): + atomic_data = deepcopy(atomic_dataset) + sim = Simulation.from_config( + config_verysimple, atom_data=atomic_data, virtual_packet_logging=True + ) + sim.last_no_of_packets = 4000 + sim.run_final() + return sim diff --git a/tardis/data/atomic_data_repo.yml b/tardis/data/atomic_data_repo.yml index 3a824a4c47f..334084b121f 100644 --- a/tardis/data/atomic_data_repo.yml +++ b/tardis/data/atomic_data_repo.yml @@ -2,4 +2,8 @@ default: kurucz_cd23_chianti_H_He kurucz_cd23_chianti_H_He: url: https://media.githubusercontent.com/media/tardis-sn/tardis-refdata/master/atom_data/kurucz_cd23_chianti_H_He.h5 + mirrors: + - https://dev.azure.com/tardis-sn/TARDIS/_apis/git/repositories/tardis-refdata/items?path=atom_data/kurucz_cd23_chianti_H_He.h5&resolveLfs=true + - https://media.githubusercontent.com/media/tardis-sn/tardis-refdata/master/atom_data/kurucz_cd23_chianti_H_He.h5 uuid: NA + md5: b95b862ef9f06ac20ad4fa70070af59d diff --git a/tardis/energy_input/GXPacket.py b/tardis/energy_input/GXPacket.py new file mode 100644 index 00000000000..dd8792876bc --- /dev/null +++ b/tardis/energy_input/GXPacket.py @@ -0,0 +1,242 @@ +from enum import IntEnum +import numpy as np +from numba import int64, float64 +from numba.experimental import jitclass + +from tardis.energy_input.samplers import sample_decay_time, sample_energy +from tardis.energy_input.util import ( + get_index, + get_random_unit_vector, + doppler_factor_3d, + H_CGS_KEV, +) + + +class GXPacketStatus(IntEnum): + BETA_DECAY = -1 + COMPTON_SCATTER = 0 + PHOTOABSORPTION = 1 + PAIR_CREATION = 2 + IN_PROCESS = 3 + END = 4 + ESCAPED = 5 + + +gxpacket_spec = [ + ("location", float64[:]), + ("direction", float64[:]), + ("energy_rf", float64), + ("energy_cmf", float64), + ("nu_rf", float64), + ("nu_cmf", float64), + ("status", int64), + ("shell", int64), + ("time_current", float64), + ("tau", float64), +] + + +@jitclass(gxpacket_spec) +class GXPacket(object): + """ + Indivisible gamma-ray packet + """ + + def __init__( + self, + location, + direction, + energy_rf, + energy_cmf, + nu_rf, + nu_cmf, + status, + shell, + time_current, + ): + self.location = location + self.direction = direction + self.energy_rf = energy_rf + self.energy_cmf = energy_cmf + self.nu_rf = nu_rf + self.nu_cmf = nu_cmf + self.status = status + self.shell = shell + self.time_current = time_current + # TODO: rename to tau_event + self.tau = -np.log(np.random.random()) + + def get_location_r(self): + """Calculate radius of the packet + + Returns: + float: packet radius + """ + return np.sqrt( + self.location[0] ** 2.0 + + self.location[1] ** 2.0 + + self.location[2] ** 2.0 + ) + + +class GXPacketCollection: + """ + Gamma-ray packet collection + """ + + def __init__( + self, + location, + direction, + energy_rf, + energy_cmf, + nu_rf, + nu_cmf, + status, + shell, + time_current, + ): + self.location = location + self.direction = direction + self.energy_rf = energy_rf + self.energy_cmf = energy_cmf + self.nu_rf = nu_rf + self.nu_cmf = nu_cmf + self.status = status + self.shell = shell + self.time_current = time_current + self.number_of_packets = len(self.energy_rf) + self.tau = -np.log(np.random.random(self.number_of_packets)) + + +# @njit(**njit_dict_no_parallel) +def initialize_packet_properties( + isotope_energy, + isotope_intensity, + positronium_energy, + positronium_intensity, + positronium_fraction, + packet_energy, + k, + tau_start, + tau_end, + initial_radius, + times, + effective_times, + average_power_per_mass, + uniform_packet_energies=True, +): + """Initialize the properties of an individual packet + + Parameters + ---------- + isotope_energy : numpy array + _description_ + isotope_intensity : numpy array + _description_ + positronium_energy : numpy array + _description_ + positronium_intensity : numpy array + _description_ + positronium_fraction : float + _description_ + packet_energy : float + _description_ + k : int + _description_ + tau_start : float + _description_ + tau_end : float + _description_ + initial_radius : float + _description_ + times : numpy array + _description_ + effective_times : numpy array + _description_ + + Returns + ------- + _type_ + _description_ + """ + decay_time = np.inf + + # packets sampled uniformly in time + if not uniform_packet_energies: + z = np.random.random() + decay_time = z * times[0] + (1 - z) * times[-1] + else: + decay_time = sample_decay_time( + tau_start, + end_tau=tau_end, + decay_time_min=0, + decay_time_max=times[-1], + ) + + decay_time_index = get_index(decay_time, times) + + cmf_energy = sample_energy(isotope_energy, isotope_intensity) + + z = np.random.random() + if z < positronium_fraction: + z = np.random.random() + if cmf_energy == 511 and z > 0.25: + cmf_energy = sample_energy( + positronium_energy, positronium_intensity + ) + + energy_factor = 1.0 + if decay_time < times[0]: + energy_factor = decay_time / times[0] + decay_time = times[0] + + # compute the new energy factor based on the ratio of the end-chain decay power + # to the average decay power + if not uniform_packet_energies: + energy_factor = ( + get_chain_decay_power_per_ejectamass( + inventory, + decay_time, + times[0], + isotope_energy * isotope_intensity / 100, + positronium_energy * positronium_intensity / 100, + tau_end, + ) + / average_power_per_mass + ) + + scaled_r = initial_radius * effective_times[decay_time_index] + + initial_location = scaled_r * get_random_unit_vector() + initial_direction = get_random_unit_vector() + initial_energy = packet_energy * energy_factor + + # draw a random gamma-ray in shell + packet = GXPacket( + initial_location, + initial_direction, + 1.0, + initial_energy, + 0.0, + 0.0, + GXPacketStatus.IN_PROCESS, + k, + decay_time, + ) + + packet.energy_rf = packet.energy_cmf / doppler_factor_3d( + packet.direction, + packet.location, + packet.time_current, + ) + + packet.nu_cmf = cmf_energy / H_CGS_KEV + + packet.nu_rf = packet.nu_cmf / doppler_factor_3d( + packet.direction, + packet.location, + packet.time_current, + ) + + return packet, decay_time_index diff --git a/tardis/energy_input/__init__.py b/tardis/energy_input/__init__.py new file mode 100644 index 00000000000..4211b689089 --- /dev/null +++ b/tardis/energy_input/__init__.py @@ -0,0 +1,3 @@ +""" +Contains classes and functions to handle energy deposition and transport. +""" diff --git a/tardis/energy_input/energy_source.py b/tardis/energy_input/energy_source.py new file mode 100644 index 00000000000..4fa33734944 --- /dev/null +++ b/tardis/energy_input/energy_source.py @@ -0,0 +1,224 @@ +import numpy as np +import pandas as pd +import radioactivedecay as rd + +from tardis.util.base import ( + atomic_number2element_symbol, +) +from tardis.energy_input.util import ( + convert_half_life_to_astropy_units, + ELECTRON_MASS_ENERGY_KEV, +) + + +def setup_input_energy(nuclear_data, source): + """Sets up energy distribution and CDF for a + source of decay radiation. + + Parameters + ---------- + nuclear_data : Pandas dataframe + Dataframe of nuclear decay properties + source : str + Type of decay radiation + + Returns + ------- + One-dimensional Numpy Array, dtype float + Sorted energy array + One-dimensional Numpy Array, dtype float + CDF where each index corresponds to the energy in + the sorted array + """ + intensity = nuclear_data[nuclear_data.Radiation == source]["Rad Intensity"] + energy = nuclear_data[nuclear_data.Radiation == source]["Rad Energy"] + + intensity /= 100 # = [i / 100 if i > 1 else i for i in intensity] + + return energy, intensity + + +def intensity_ratio(nuclear_data, source_1, source_2): + """Determined the ratio of intensities between two + sources of decay radiation + + Parameters + ---------- + nuclear_data : pandas.Dataframe + Dataframe of nuclear decay properties + source_1 : str + Type of decay radiation to compare + source_2 : str + Type of decay radiation to compare + + Returns + ------- + float + Fractional intensity of source_1 + float + Fractional intensity of source_2 + float + Number of decay products per decay + """ + intensity_1 = nuclear_data.query("type==" + source_1)["intensity"].values + intensity_2 = nuclear_data.query("type==" + source_2)["intensity"].values + total_intensity = np.sum(intensity_1) + np.sum(intensity_2) + # Factor of 100 is because intensities are in percent + scale_factor = total_intensity / 100 + return ( + np.sum(intensity_1) / total_intensity, + np.sum(intensity_2) / total_intensity, + scale_factor, + ) + + +def get_all_isotopes(abundances): + """Get the possible isotopes present over time + for a given starting abundance + + Parameters + ---------- + abundances : DataFrame + Current isotope abundances + + Returns + ------- + list + List of isotope names + """ + progenitors = [ + f"{rd.utils.Z_DICT[i[0]]}-{i[1]}" for i in abundances.T.columns + ] + + isotopes = set(progenitors) + check = True + + while check == True: + progeny = set(isotopes) + + for i in isotopes: + for p in rd.Nuclide(i).progeny(): + if ( + p != "SF" + and rd.Nuclide(p).half_life("readable") != "stable" + ): + progeny.add(p) + + if progeny == isotopes: + check = False + else: + isotopes |= progeny + + isotopes = [i for i in isotopes] + return isotopes + + +def get_tau(meta, isotope_string): + """Calculate the mean lifetime of an isotope + + Parameters + ---------- + meta : DataFrame + Isotope metadata + isotope_string : str + Isotope of interest + + Returns + ------- + float + Mean lifetime of isotope + """ + isotope_meta = meta.loc[isotope_string] + half_life = isotope_meta.loc[isotope_meta["key"] == "Parent T1/2 value"][ + "value" + ].values[0] + half_life = convert_half_life_to_astropy_units(half_life) + return half_life / np.log(2) + + +def get_isotope_string(atom_number, atom_mass): + """Get the isotope string in the format e.g. Ni56 + + Parameters + ---------- + atom_number : int + Atomic number + atom_mass : int + Atomic mass + + Returns + ------- + str + Isotope string in the format e.g. Ni56 + """ + return atomic_number2element_symbol(atom_number) + str(atom_mass) + + +def read_artis_lines(isotope, path_to_data): + """Reads lines of ARTIS format + + Parameters + ---------- + isotope : string + Isotope to read e.g. Ni56 + + Returns + ------- + pd.DataFrame + Energies and intensities of the isotope lines + """ + return pd.read_csv( + path_to_data + isotope + ".txt", + names=["energy", "intensity"], + sep=" ", + index_col=False, + ) + + +def get_nuclear_lines_database( + path, +): + """Load the nuclear decay line data set + + Parameters + ---------- + path : str + Path to the data set HDF file + + Returns + ------- + pandas DataFrame + The decay radiation lines + """ + decay_radiation_db = pd.read_hdf(path, "decay_radiation_data") + return decay_radiation_db + + +def positronium_continuum(): + """Produces a continuum of positronium decay energy + using the function defined by Ore and Powell 1949 + and adapted by Leung 2022 to be in terms of electron + rest mass energy + + Returns + ------- + energy + An array of photon energies in keV + intensity + An array of intensities between 0 and 1 + """ + + energy = np.linspace(1, ELECTRON_MASS_ENERGY_KEV, num=100, endpoint=False) + + x = energy / ELECTRON_MASS_ENERGY_KEV + + one_minus_x = 1 - x + + term_1 = (x * one_minus_x) / (2 - x) ** 2 + term_2 = (2 * one_minus_x**2) / (2 - x) ** 3 * np.log(one_minus_x) + term_3 = (2 - x) / x + term_4 = (2 * one_minus_x) / x**2 * np.log(one_minus_x) + + intensity = 2 * (term_1 - term_2 + term_3 + term_4) + + return energy, intensity / np.max(intensity) diff --git a/tardis/energy_input/gamma_packet_loop.py b/tardis/energy_input/gamma_packet_loop.py new file mode 100644 index 00000000000..385febda679 --- /dev/null +++ b/tardis/energy_input/gamma_packet_loop.py @@ -0,0 +1,376 @@ +import numpy as np +from numba import njit + +from tardis.energy_input.gamma_ray_estimators import deposition_estimator_kasen +from tardis.energy_input.gamma_ray_grid import ( + distance_trace, + move_packet, +) +from tardis.energy_input.gamma_ray_interactions import ( + compton_scatter, + get_compton_fraction_artis, + pair_creation_packet, + scatter_type, +) +from tardis.energy_input.GXPacket import GXPacketStatus +from tardis.energy_input.util import ( + C_CGS, + H_CGS_KEV, + doppler_factor_3d, + get_index, +) +from tardis.opacities.opacities import ( + SIGMA_T, + compton_opacity_calculation, + kappa_calculation, + pair_creation_opacity_artis, + pair_creation_opacity_calculation, + photoabsorption_opacity_calculation, +) +from tardis.transport.montecarlo import njit_dict_no_parallel + + +@njit(**njit_dict_no_parallel) +def gamma_packet_loop( + packets, + grey_opacity, + photoabsorption_opacity_type, + pair_creation_opacity_type, + electron_number_density_time, + mass_density_time, + inv_volume_time, + iron_group_fraction_per_shell, + inner_velocities, + outer_velocities, + times, + dt_array, + effective_time_array, + energy_bins, + energy_df_rows, + energy_plot_df_rows, + energy_out, + packets_info_array, +): + """Propagates packets through the simulation + + Parameters + ---------- + packets : list + List of GXPacket objects + grey_opacity : float + Grey opacity value in cm^2/g + electron_number_density_time : array float64 + Electron number densities with time + mass_density_time : array float64 + Mass densities with time + inv_volume_time : array float64 + Inverse volumes with time + iron_group_fraction_per_shell : array float64 + Iron group fraction per shell + inner_velocities : array float64 + Inner velocities of the shells + outer_velocities : array float64 + Inner velocities of the shells + times : array float64 + Simulation time steps + dt_array : array float64 + Simulation delta-time steps + effective_time_array : array float64 + Simulation middle time steps + energy_bins : array float64 + Bins for escaping gamma-rays + energy_df_rows : array float64 + Energy output + energy_plot_df_rows : array float64 + Energy output for plotting + energy_out : array float64 + Escaped energy array + + Returns + ------- + array float64 + Energy output + array float64 + Energy output for plotting + array float64 + Escaped energy array + + Raises + ------ + ValueError + Packet time index less than zero + """ + escaped_packets = 0 + scattered_packets = 0 + packet_count = len(packets) + print("Entering gamma ray loop for " + str(packet_count) + " packets") + + deposition_estimator = np.zeros_like(energy_df_rows) + + for i in range(packet_count): + packet = packets[i] + time_index = get_index(packet.time_current, times) + + if time_index < 0: + print(packet.time_current, time_index) + raise ValueError("Packet time index less than 0!") + + scattered = False + + initial_energy = packet.energy_cmf + + while packet.status == GXPacketStatus.IN_PROCESS: + # Get delta-time value for this step + dt = dt_array[time_index] + # Calculate packet comoving energy for opacities + comoving_energy = H_CGS_KEV * packet.nu_cmf + + if grey_opacity < 0: + doppler_factor = doppler_factor_3d( + packet.direction, + packet.location, + effective_time_array[time_index], + ) + + kappa = kappa_calculation(comoving_energy) + + # artis threshold for Thomson scattering + if kappa < 1e-2: + compton_opacity = ( + SIGMA_T + * electron_number_density_time[packet.shell, time_index] + ) + else: + compton_opacity = compton_opacity_calculation( + comoving_energy, + electron_number_density_time[packet.shell, time_index], + ) + + if photoabsorption_opacity_type == "kasen": + # currently not functional, requires proton count and + # electron count per isotope + photoabsorption_opacity = 0 + # photoabsorption_opacity_calculation_kasen() + elif photoabsorption_opacity_type == "tardis": + photoabsorption_opacity = ( + photoabsorption_opacity_calculation( + comoving_energy, + mass_density_time[packet.shell, time_index], + iron_group_fraction_per_shell[packet.shell], + ) + ) + else: + raise ValueError("Invalid photoabsorption opacity type!") + + if pair_creation_opacity_type == "artis": + pair_creation_opacity = pair_creation_opacity_artis( + comoving_energy, + mass_density_time[packet.shell, time_index], + iron_group_fraction_per_shell[packet.shell], + ) + elif pair_creation_opacity_type == "tardis": + pair_creation_opacity = pair_creation_opacity_calculation( + comoving_energy, + mass_density_time[packet.shell, time_index], + iron_group_fraction_per_shell[packet.shell], + ) + else: + raise ValueError("Invalid pair creation opacity type!") + else: + compton_opacity = 0.0 + pair_creation_opacity = 0.0 + photoabsorption_opacity = ( + grey_opacity * mass_density_time[packet.shell, time_index] + ) + + # convert opacities to rest frame + total_opacity = ( + compton_opacity + + photoabsorption_opacity + + pair_creation_opacity + ) * doppler_factor + + packet.tau = -np.log(np.random.random()) + + ( + distance_interaction, + distance_boundary, + distance_time, + shell_change, + ) = distance_trace( + packet, + inner_velocities, + outer_velocities, + total_opacity, + effective_time_array[time_index], + times[time_index + 1], + ) + + distance = min( + distance_interaction, distance_boundary, distance_time + ) + + packet.time_current += distance / C_CGS + + packet = move_packet(packet, distance) + + deposition_estimator[packet.shell, time_index] += ( + (initial_energy * 1000) + * distance + * (packet.energy_cmf / initial_energy) + * deposition_estimator_kasen( + comoving_energy, + mass_density_time[packet.shell, time_index], + iron_group_fraction_per_shell[packet.shell], + ) + ) + + if distance == distance_time: + time_index += 1 + + if time_index > len(effective_time_array) - 1: + # Packet ran out of time + packet.status = GXPacketStatus.END + else: + packet.shell = get_index( + packet.get_location_r(), + inner_velocities * effective_time_array[time_index], + ) + + elif distance == distance_interaction: + packet.status = scatter_type( + compton_opacity, + photoabsorption_opacity, + total_opacity, + ) + + packet, ejecta_energy_gained = process_packet_path(packet) + + # Save packets to dataframe rows + # convert KeV to eV / s / cm^3 + energy_df_rows[packet.shell, time_index] += ( + ejecta_energy_gained * 1000 + ) + + energy_plot_df_rows[i] = np.array( + [ + i, + ejecta_energy_gained * 1000 + # * inv_volume_time[packet.shell, time_index] + / dt, + packet.get_location_r(), + packet.time_current, + packet.shell, + compton_opacity, + photoabsorption_opacity, + pair_creation_opacity, + ] + ) + + if packet.status == GXPacketStatus.PHOTOABSORPTION: + # Packet destroyed, go to the next packet + break + else: + packet.status = GXPacketStatus.IN_PROCESS + scattered = True + + else: + packet.shell += shell_change + + if packet.shell > len(mass_density_time[:, 0]) - 1: + rest_energy = packet.nu_rf * H_CGS_KEV + lum_rf = (packet.energy_rf * 1.6022e-9) / dt + bin_index = get_index(rest_energy, energy_bins) + bin_width = ( + energy_bins[bin_index + 1] - energy_bins[bin_index] + ) + energy_out[bin_index, time_index] += rest_energy / ( + bin_width * dt + ) + packet.status = GXPacketStatus.ESCAPED + escaped_packets += 1 + if scattered: + scattered_packets += 1 + elif packet.shell < 0: + packet.energy_rf = 0.0 + packet.energy_cmf = 0.0 + packet.status = GXPacketStatus.END + + packets_info_array[i] = np.array( + [ + i, + packet.status, + packet.nu_cmf, + packet.nu_rf, + packet.energy_cmf, + lum_rf, + packet.energy_rf, + packet.shell, + ] + ) + + print("Escaped packets:", escaped_packets) + print("Scattered packets:", scattered_packets) + + return ( + energy_df_rows, + energy_plot_df_rows, + energy_out, + deposition_estimator, + bin_width, + packets_info_array, + ) + + +@njit(**njit_dict_no_parallel) +def process_packet_path(packet): + """Move the packet through interactions + + Parameters + ---------- + packet : GXPacket + Packet for processing + + Returns + ------- + GXPacket + Packet after processing + float + Energy injected into the ejecta + """ + if packet.status == GXPacketStatus.COMPTON_SCATTER: + comoving_freq_energy = packet.nu_cmf * H_CGS_KEV + + compton_angle, compton_fraction = get_compton_fraction_artis( + comoving_freq_energy + ) + + # Packet is no longer a gamma-ray, destroy it + if np.random.random() < 1 / compton_fraction: + packet.nu_cmf = packet.nu_cmf / compton_fraction + + packet.direction = compton_scatter(packet, compton_angle) + + # Calculate rest frame frequency after scaling by the fraction that remains + doppler_factor = doppler_factor_3d( + packet.direction, + packet.location, + packet.time_current, + ) + + packet.nu_rf = packet.nu_cmf / doppler_factor + packet.energy_rf = packet.energy_cmf / doppler_factor + + ejecta_energy_gained = 0.0 + else: + packet.status = GXPacketStatus.PHOTOABSORPTION + + if packet.status == GXPacketStatus.PAIR_CREATION: + packet = pair_creation_packet(packet) + ejecta_energy_gained = 0.0 + + if packet.status == GXPacketStatus.PHOTOABSORPTION: + # Ejecta gains comoving energy + ejecta_energy_gained = packet.energy_cmf + + return packet, ejecta_energy_gained diff --git a/tardis/energy_input/gamma_ray_channel.py b/tardis/energy_input/gamma_ray_channel.py new file mode 100644 index 00000000000..6bbb7a9685a --- /dev/null +++ b/tardis/energy_input/gamma_ray_channel.py @@ -0,0 +1,169 @@ +import logging +import numpy as np +import pandas as pd +import astropy.units as u +import radioactivedecay as rd + +from tardis.energy_input.util import KEV2ERG + +logger = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO) + + +def create_isotope_dicts(raw_isotope_abundance, cell_masses): + """ + Function to create a dictionary of isotopes for each shell with their masses. + + Parameters + ---------- + raw_isotope_abundance : pd.DataFrame + isotope abundance in mass fractions. + cell_masses : numpy.ndarray + shell masses in units of g + + Returns + ------- + isotope_dicts : Dict + dictionary of isotopes for each shell with their ``masses``. + Each value is abundance * cell masses. + For eg: {0: {'Ni56': 0.1, 'Fe52': 0.2, 'Cr48': 0.3}, + {1: {'Ni56': 0.1, 'Fe52': 0.2, 'Cr48': 0.3}} etc + """ + isotope_dicts = {} + for i in range(len(raw_isotope_abundance.columns)): + isotope_dicts[i] = {} + for ( + atomic_number, + mass_number, + ), abundances in raw_isotope_abundance.iterrows(): + nuclear_symbol = f"{rd.utils.Z_to_elem(atomic_number)}{mass_number}" + isotope_dicts[i][nuclear_symbol] = ( + abundances[i] * cell_masses[i].to(u.g).value + ) + + return isotope_dicts + + +def create_inventories_dict(isotope_dict): + """Function to create dictionary of inventories for each shell + + Parameters + ---------- + isotope_dict : Dict + dictionary of isotopes for each shell with their ``masses``. + Returns + ------- + inv : Dict + dictionary of inventories for each shell + {0: <radioactivedecay.inventory.Inventory object at 0x7f8b1c1b3d90>, + 1: <radioactivedecay.inventory.Inventory object at 0x7f8b1c1b3d90>} + + """ + inventories = {} + for shell, isotopes in isotope_dict.items(): + inventories[shell] = rd.Inventory(isotopes, "g") + + return inventories + + +def calculate_total_decays(inventories, time_delta): + """Function to create inventories of isotope for the entire simulation time. + + Parameters + ---------- + inventories : Dict + dictionary of inventories for each shell + + time_end : float + End time of simulation in days. + + + Returns + ------- + cumulative_decay_df : pd.DataFrame + total decays for x g of isotope for time 't' + """ + time_delta = u.Quantity(time_delta, u.s) + total_decays = {} + for shell, inventory in inventories.items(): + total_decays[shell] = inventory.cumulative_decays(time_delta.value) + + flattened_dict = {} + + for shell, isotope_dict in total_decays.items(): + for isotope, num_of_decays in isotope_dict.items(): + new_key = isotope.replace("-", "") + flattened_dict[(shell, new_key)] = num_of_decays + + indices = pd.MultiIndex.from_tuples( + flattened_dict.keys(), names=["shell_number", "isotope"] + ) + cumulative_decay_df = pd.DataFrame( + list(flattened_dict.values()), + index=indices, + columns=["number_of_decays"], + ) + + return cumulative_decay_df + + +def create_isotope_decay_df(cumulative_decay_df, gamma_ray_lines): + """ + Function to create a dataframe of isotopes for each shell with their decay mode, number of decays, radiation type, + radiation energy and radiation intensity. + + Parameters + ---------- + cumulative_decay_df : pd.DataFrame + total decays for x g of isotope for time 't' + gamma_ray_lines : pd.DataFrame + gamma ray lines from nndc stored as a pandas dataframe. + + Returns + ------- + isotope_decay_df : pd.DataFrame + dataframe of isotopes for each shell with their decay mode, number of decays, radiation type, + radiation energy and radiation intensity. + """ + + gamma_ray_lines = gamma_ray_lines.rename_axis( + "isotope" + ) # renaming "Isotope" in nndc to "isotope" + gamma_ray_lines.drop(columns=["A", "Z"]) + gamma_ray_lines_df = gamma_ray_lines[ + ["Decay Mode", "Radiation", "Rad Energy", "Rad Intensity"] + ] # selecting from existing dataframe + + columns = [ + "decay_mode", + "radiation", + "radiation_energy_keV", + "radiation_intensity", + ] + gamma_ray_lines_df.columns = columns + isotope_decay_df = pd.merge( + cumulative_decay_df.reset_index(), + gamma_ray_lines_df.reset_index(), + on=["isotope"], + ) + isotope_decay_df = isotope_decay_df.set_index(["shell_number", "isotope"]) + isotope_decay_df["decay_mode"] = isotope_decay_df["decay_mode"].astype( + "category" + ) + isotope_decay_df["radiation"] = isotope_decay_df["radiation"].astype( + "category" + ) + isotope_decay_df["energy_per_channel_keV"] = ( + isotope_decay_df["radiation_intensity"] + / 100.0 + * isotope_decay_df["radiation_energy_keV"] + ) + isotope_decay_df["decay_energy_keV"] = ( + isotope_decay_df["energy_per_channel_keV"] + * isotope_decay_df["number_of_decays"] + ) + isotope_decay_df["decay_energy_erg"] = ( + isotope_decay_df["decay_energy_keV"] * KEV2ERG + ) + + return isotope_decay_df diff --git a/tardis/energy_input/gamma_ray_estimators.py b/tardis/energy_input/gamma_ray_estimators.py new file mode 100644 index 00000000000..e28ba5029ff --- /dev/null +++ b/tardis/energy_input/gamma_ray_estimators.py @@ -0,0 +1,138 @@ +import numpy as np +from numba import njit + +from tardis.energy_input.util import ( + ELECTRON_MASS_ENERGY_KEV, + H_CGS_KEV, + angle_aberration_gamma, + doppler_factor_3d, +) +from tardis.opacities.opacities import ( + SIGMA_T, + compton_opacity_calculation, + kappa_calculation, + photoabsorption_opacity_calculation, +) +from tardis.transport.montecarlo import njit_dict_no_parallel + + +def compton_emissivity_estimator(packet, distance): + """Compton scattering emissivity estimator for integral + calculations + + Parameters + ---------- + packet : GXPacket + Packet that needs its emissivity calculated + distance : float64 + Distance packet has travelled + + Returns + ------- + float64, int + Unnormalized emissivity estimator, line index + """ + cmf_direction = angle_aberration_gamma( + packet.get_direction_vector(), packet.location_r + ) + + cmf_angle = np.dot(cmf_direction, [1, 0, 0]) + + frequency_factor = ( + 1 + + H_CGS_KEV * packet.nu_cmf / ELECTRON_MASS_ENERGY_KEV + + (1.0 - cmf_angle) + ) + + line_index = GET_NEAREST_LINE_REDWARD_FUNCTION( + packet.nu_cmf / frequency_factor + ) + + partial_cross_section = ( + 3.0 + / 16.0 + / np.pi + * SIGMA_T + / frequency_factor + / frequency_factor + * (frequency_factor + (1.0 / frequency_factor) + cmf_angle**2.0 - 1.0) + ) + + doppler_factor = doppler_factor_3d( + packet.get_direction_vector(), packet.location_r + ) + + emissivity = ( + packet.energy_rf + * partial_cross_section + * distance + * doppler_factor**2.0 + / frequency_factor + ) + + return emissivity, line_index + + +def pair_creation_estimator(packet, pair_creation_opacity, distance): + """Calculates the emissivity for pair creation gamma-rays + + Parameters + ---------- + packet : GXPacket + Packet that needs its emissivity calculated + pair_creation_opacity : float64 + Opacity of the pair creation process + distance : float64 + Distance packet has travelled + + Returns + ------- + float64 + Emissivity estimator + """ + normalized_energy = ( + 2 * ELECTRON_MASS_ENERGY_KEV / (H_CGS_KEV * packet.nu_cmf) + ) + + emissivity = ( + pair_creation_opacity * normalized_energy * packet.energy_rf * distance + ) + + return emissivity + + +@njit(**njit_dict_no_parallel) +def get_average_compton_fraction(energy): + def f(x, mu): + return 1.0 / (1.0 + x * (1.0 - mu)) + + def cross_section(x, mu): + return ( + (3.0 * SIGMA_T) + / (16.0 * np.pi) + * f(x, mu) ** 2.0 + * (f(x, mu) + 1.0 / f(x, mu) - (1.0 - mu**2)) + ) + + x = kappa_calculation(energy) + mus = np.linspace(-1, 1, 100) + dmu = mus[1] - mus[0] + sum = 0 + norm = 0 + + for mu in mus: + sum += cross_section(x, mu) * f(x, mu) * dmu + norm += cross_section(x, mu) * dmu + + integral = 1.0 - sum / norm + + return 1 - integral + + +@njit(**njit_dict_no_parallel) +def deposition_estimator_kasen(energy, ejecta_density, iron_group_fraction): + return get_average_compton_fraction(energy) * compton_opacity_calculation( + energy, ejecta_density + ) + photoabsorption_opacity_calculation( + energy, ejecta_density, iron_group_fraction + ) diff --git a/tardis/energy_input/gamma_ray_grid.py b/tardis/energy_input/gamma_ray_grid.py new file mode 100644 index 00000000000..1f86be634af --- /dev/null +++ b/tardis/energy_input/gamma_ray_grid.py @@ -0,0 +1,144 @@ +import numpy as np +from numba import njit + +from tardis.transport.montecarlo import njit_dict_no_parallel +from tardis.energy_input.util import ( + doppler_factor_3d, + solve_quadratic_equation, + C_CGS, +) + + +@njit(**njit_dict_no_parallel) +def calculate_distance_radial(photon, r_inner, r_outer): + """ + Calculates 3D distance to shell from gamma ray position + + Parameters + ---------- + photon : GXPhoton object + r_inner : float + r_outer : float + + Returns + ------- + distance : float + + """ + + # solve the quadratic distance equation for the inner and + # outer shell boundaries + inner_1, inner_2 = solve_quadratic_equation( + photon.location, photon.direction, r_inner + ) + outer_1, outer_2 = solve_quadratic_equation( + photon.location, photon.direction, r_outer + ) + + final_position_inner_1 = photon.location + photon.direction * inner_1 + final_position_inner_2 = photon.location + photon.direction * inner_2 + final_position_outer_1 = photon.location + photon.direction * outer_1 + final_position_outer_2 = photon.location + photon.direction * outer_2 + + if np.dot(final_position_inner_1, photon.direction) > 0: + inner_1 = -1 + if np.dot(final_position_inner_2, photon.direction) > 0: + inner_2 = -1 + if np.dot(final_position_outer_1, photon.direction) < 0: + outer_1 = -1 + if np.dot(final_position_outer_2, photon.direction) < 0: + outer_2 = -1 + + distances = np.array([inner_1, inner_2, outer_1, outer_2]) + + # the correct distance is the shortest positive distance + distance_list = [i for i in distances if i > 0] + + if not distance_list: + print(photon.get_location_r() - r_inner) + print(photon.get_location_r() - r_outer) + print(photon.get_location_r()) + print(photon.location, photon.direction, r_inner, r_outer) + print(distances) + print(photon.shell) + raise ValueError("No root found for distance calculation!") + + shortest = min(distance_list) + shell_change = 1 + + if shortest == (inner_1 or inner_2): + shell_change = -1 + + return shortest, shell_change + + +@njit(**njit_dict_no_parallel) +def distance_trace( + photon, + inner_velocity, + outer_velocity, + total_opacity, + current_time, + next_time, +): + """ + Traces distance traveled by gamma ray and finds distance to + next interaction and boundary + + Parameters + ---------- + photon : GXPhoton object + inner_velocity : One dimensional Numpy array, dtype float + outer_velocity : One dimensional Numpy array, dtype float + total_opacity : float + current_time : float + next_time : float + + Returns + ------- + distance_interaction : float + distance_boundary : float + distance_time : float + shell_change : int + """ + distance_boundary, shell_change = calculate_distance_radial( + photon, + inner_velocity[photon.shell] * current_time, + outer_velocity[photon.shell] * current_time, + ) + + distance_interaction = photon.tau / total_opacity + distance_time = (next_time - photon.time_current) * C_CGS + return distance_interaction, distance_boundary, distance_time, shell_change + + +@njit(**njit_dict_no_parallel) +def move_packet(packet, distance): + """ + Moves packet a distance along its direction vector + + Parameters + ---------- + packet : GXPacket object + distance : float + + Returns + ------- + packet : GXPacket object + + """ + location_old = packet.location + direction = packet.direction + + location_new = location_old + distance * direction + + packet.location = location_new + + doppler_factor = doppler_factor_3d( + packet.direction, packet.location, packet.time_current + ) + + packet.nu_cmf = packet.nu_rf * doppler_factor + packet.energy_cmf = packet.energy_rf * doppler_factor + + return packet diff --git a/tardis/energy_input/gamma_ray_interactions.py b/tardis/energy_input/gamma_ray_interactions.py new file mode 100644 index 00000000000..649a526af72 --- /dev/null +++ b/tardis/energy_input/gamma_ray_interactions.py @@ -0,0 +1,310 @@ +import numpy as np +from numba import njit + +from tardis.energy_input.GXPacket import GXPacketStatus +from tardis.energy_input.util import ( + ELECTRON_MASS_ENERGY_KEV, + H_CGS_KEV, + angle_aberration_gamma, + compton_theta_distribution, + doppler_factor_3d, + euler_rodrigues, + get_perpendicular_vector, + get_random_unit_vector, +) +from tardis.opacities.opacities import ( + compton_opacity_partial, + kappa_calculation, +) +from tardis.transport.montecarlo import njit_dict_no_parallel + + +@njit(**njit_dict_no_parallel) +def get_compton_angle(energy): + """ + Computes the compton angle from the Klein-Nishina equation. + Computes the lost energy due to this angle + + Parameters + ---------- + energy : float + Photon energy + + Returns + ------- + compton_angle : float + Compton scattering angle + lost_energy : float + Energy lost based on angle + new_energy : float + Photon energy + """ + theta_angles, theta_distribution = compton_theta_distribution(energy) + + z = np.random.random() + + # get Compton scattering angle + compton_angle = np.interp(z, theta_distribution, theta_angles) + # Energy calculations + new_energy = energy / ( + 1.0 + kappa_calculation(energy) * (1.0 - np.cos(compton_angle)) + ) + lost_energy = energy - new_energy + + return compton_angle, lost_energy, new_energy + + +@njit(**njit_dict_no_parallel) +def get_compton_fraction(energy): + """ + Computes the compton angle from the Klein-Nishina equation. + Determines the probability of absorption from this angle. + + Parameters + ---------- + energy : float + Photon energy + + Returns + ------- + compton_angle : float + Compton scattering angle + compton_fraction : float + Fraction of energy lost + """ + theta_angles, theta_distribution = compton_theta_distribution(energy) + + z = np.random.random() + + # get Compton scattering angle + compton_angle = np.interp(z, theta_distribution, theta_angles) + # Energy calculations + fraction = 1 / ( + 1.0 + kappa_calculation(energy) * (1.0 - np.cos(compton_angle)) + ) + + return compton_angle, fraction + + +@njit(**njit_dict_no_parallel) +def get_compton_fraction_artis(energy): + """Gets the Compton scattering/absorption fraction + and angle following the scheme in ARTIS + + Parameters + ---------- + energy : float + Energy of the gamma-ray + + Returns + ------- + float + Scattering angle + float + Compton scattering fraction + """ + energy_norm = kappa_calculation(energy) + + fraction_max = 1.0 + 2.0 * energy_norm + fraction_min = 1.0 + + normalization = np.random.random() * compton_opacity_partial( + energy_norm, fraction_max + ) + + epsilon = 1.0e20 + count = 0 + + while epsilon > 1.0e-4: + fraction_try = (fraction_max + fraction_min) / 2.0 + sigma_try = compton_opacity_partial(energy_norm, fraction_try) + + if sigma_try > normalization: + fraction_max = fraction_try + epsilon = (sigma_try - normalization) / normalization + else: + fraction_min = fraction_try + epsilon = (normalization - sigma_try) / normalization + + count += 1 + if count > 1000: + print("Error, failure to get a Compton fraction") + break + + angle = np.arccos(1.0 - ((fraction_try - 1) / energy_norm)) + + return angle, fraction_try + + +@njit(**njit_dict_no_parallel) +def get_compton_fraction_urilight(energy): + """Gets the Compton scattering/absorption fraction + and angle following the scheme in Urilight + + Parameters + ---------- + energy : float + Energy of the gamma-ray + + Returns + ------- + float + Scattering angle + float + Compton scattering fraction + """ + E0 = kappa_calculation(energy) + + x0 = 1.0 / (1.0 + 2.0 * E0) + + accept = False + while not accept: + z = np.random.random(3) + alpha1 = np.log(1.0 / x0) + alpha2 = (1.0 - x0**2.0) / 2.0 + if z[1] < alpha1 / (alpha1 + alpha2): + x = x0 ** z[2] + else: + x = np.sqrt(x0**2.0 + (1.0 - x0**2.0) * z[2]) + + f = (1.0 - x) / x / E0 + sin2t = f * (2.0 - f) + ge = 1.0 - x / (1 + x**2.0) * sin2t + if ge > z[3]: + accept = True + + cost = 1.0 - f + + return np.arccos(cost), x + + +@njit(**njit_dict_no_parallel) +def compton_scatter(photon, compton_angle): + """ + Changes the direction of the gamma-ray by the Compton scattering angle + + Parameters + ---------- + photon : GXPhoton object + compton_angle : float + + Returns + ------- + float64 + Photon theta direction + float64 + Photon phi direction + """ + # get comoving frame direction + comov_direction = angle_aberration_gamma( + photon.direction, photon.location, photon.time_current + ) + + # compute an arbitrary perpendicular vector to the comoving direction + orthogonal_vector = get_perpendicular_vector(comov_direction) + # determine a random vector with compton_angle to the comoving direction + new_vector = np.dot( + euler_rodrigues(compton_angle, orthogonal_vector), + comov_direction, + ) + + # draw a random angle from [0,2pi] + phi = 2.0 * np.pi * np.random.random() + # rotate the vector with compton_angle around the comoving direction + final_compton_scattered_vector = np.dot( + euler_rodrigues(phi, comov_direction), new_vector + ) + + norm_phi = np.dot( + final_compton_scattered_vector, final_compton_scattered_vector + ) + + norm_theta = np.dot(final_compton_scattered_vector, comov_direction) + + assert ( + np.abs(norm_phi - 1) < 1e-8 + ), "Error, norm of Compton scatter vector is not 1!" + + assert ( + np.abs(norm_theta - np.cos(compton_angle)) < 1e-8 + ), "Error, difference between new vector angle and Compton angle is more than 0!" + + # Calculate the angle aberration of the final direction + final_direction = angle_aberration_gamma( + final_compton_scattered_vector, photon.location, photon.time_current + ) + + return final_direction + + +@njit(**njit_dict_no_parallel) +def pair_creation_packet(packet): + """ + Pair creation randomly scatters the packet + or destroys it, based on the frequency + + Parameters + ---------- + packet : GXPacket + incoming packet + + Returns + ------- + GXPacket + outgoing packet + """ + probability_gamma = ( + 2 * ELECTRON_MASS_ENERGY_KEV / (H_CGS_KEV * packet.nu_cmf) + ) + + if np.random.random() > probability_gamma: + packet.status = GXPacketStatus.PHOTOABSORPTION + return packet + + new_direction = get_random_unit_vector() + + # Calculate aberration of the random angle for the rest frame + final_direction = angle_aberration_gamma( + new_direction, packet.location, -1 * packet.time_current + ) + + packet.direction = final_direction + + doppler_factor = doppler_factor_3d( + packet.direction, packet.location, packet.time_current + ) + + packet.nu_cmf = ELECTRON_MASS_ENERGY_KEV / H_CGS_KEV + packet.nu_rf = packet.nu_cmf / doppler_factor + packet.energy_rf = packet.energy_cmf / doppler_factor + + return packet + + +@njit(**njit_dict_no_parallel) +def scatter_type(compton_opacity, photoabsorption_opacity, total_opacity): + """ + Determines the scattering type based on process opacities + + Parameters + ---------- + compton_opacity : float + photoabsorption_opacity : float + total_opacity : float + + Returns + ------- + status : GXPacketStatus + Scattering process the photon encounters + + """ + z = np.random.random() + + if z <= (compton_opacity / total_opacity): + status = GXPacketStatus.COMPTON_SCATTER + elif z <= (compton_opacity + photoabsorption_opacity) / total_opacity: + status = GXPacketStatus.PHOTOABSORPTION + else: + status = GXPacketStatus.PAIR_CREATION + + return status diff --git a/tardis/energy_input/gamma_ray_packet_source.py b/tardis/energy_input/gamma_ray_packet_source.py new file mode 100644 index 00000000000..c880bdf3632 --- /dev/null +++ b/tardis/energy_input/gamma_ray_packet_source.py @@ -0,0 +1,855 @@ +import numpy as np +import pandas as pd + +from tardis.energy_input.energy_source import ( + positronium_continuum, +) +from tardis.energy_input.GXPacket import ( + GXPacketCollection, +) +from tardis.energy_input.samplers import sample_energy +from tardis.energy_input.util import ( + H_CGS_KEV, + doppler_factor_3d, + get_index, + get_random_unit_vector, +) +from tardis.transport.montecarlo.packet_source import BasePacketSource + + +class RadioactivePacketSource(BasePacketSource): + def __init__( + self, + packet_energy, + gamma_ray_lines, + positronium_fraction, + inner_velocities, + outer_velocities, + inv_volume_time, + times, + energy_df_rows, + effective_times, + taus, + parents, + average_positron_energies, + average_power_per_mass, + **kwargs, + ): + self.packet_energy = packet_energy + self.gamma_ray_lines = gamma_ray_lines + self.positronium_fraction = positronium_fraction + self.inner_velocities = inner_velocities + self.outer_velocities = outer_velocities + self.inv_volume_time = inv_volume_time + self.times = times + self.energy_df_rows = energy_df_rows + self.effective_times = effective_times + self.taus = taus + self.parents = parents + self.average_positron_energies = average_positron_energies + self.average_power_per_mass = average_power_per_mass + self.energy_plot_positron_rows = np.empty(0) + super().__init__(**kwargs) + + def create_packet_mus(self, no_of_packets, *args, **kwargs): + return super().create_packet_mus(no_of_packets, *args, **kwargs) + + def create_packet_radii( + self, no_of_packets, inner_velocity, outer_velocity + ): + """Initialize the random radii of packets in a shell + + Parameters + ---------- + packet_count : int + Number of packets in the shell + inner_velocity : float + Inner velocity of the shell + outer_velocity : float + Outer velocity of the shell + + Returns + ------- + array + Array of length packet_count of random locations in the shell + """ + z = np.random.random(no_of_packets) + initial_radii = ( + z * inner_velocity**3.0 + (1.0 - z) * outer_velocity**3.0 + ) ** (1.0 / 3.0) + + return initial_radii + + def create_packet_nus( + self, + no_of_packets, + energy, + intensity, + positronium_fraction, + positronium_energy, + positronium_intensity, + ): + """Create an array of packet frequency-energies (i.e. E = h * nu) + + Parameters + ---------- + no_of_packets : int + Number of packets to produce frequency-energies for + energy : One-dimensional Numpy Array, dtype float + Array of frequency-energies to sample + intensity : One-dimensional Numpy Array, dtype float + Array of intensities to sample + positronium_fraction : float + The fraction of positrons that form positronium + positronium_energy : array + Array of positronium frequency-energies to sample + positronium_intensity : array + Array of positronium intensities to sample + + Returns + ------- + array + Array of sampled frequency-energies + array + Positron creation mask + """ + nu_energies = np.zeros(no_of_packets) + positrons = np.zeros(no_of_packets) + zs = np.random.random(no_of_packets) + for i in range(no_of_packets): + nu_energies[i] = sample_energy(energy, intensity) + # positron + if nu_energies[i] == 511: + # positronium formation 25% of the time if fraction is 1 + if zs[i] < positronium_fraction and np.random.random() < 0.25: + nu_energies[i] = sample_energy( + positronium_energy, positronium_intensity + ) + positrons[i] = 1 + + return nu_energies, positrons + + def create_packet_directions(self, no_of_packets): + """Create an array of random directions + + Parameters + ---------- + no_of_packets : int + Number of packets to produce directions for + + Returns + ------- + array + Array of direction vectors + """ + directions = np.zeros((3, no_of_packets)) + for i in range(no_of_packets): + directions[:, i] = get_random_unit_vector() + + return directions + + def create_packet_energies(self, no_of_packets, energy): + """Create the uniform packet energy for a number of packets + + Parameters + ---------- + no_of_packets : int + Number of packets + energy : float + The packet energy + + Returns + ------- + array + Array of packet energies + """ + return np.ones(no_of_packets) * energy + + def create_packet_times_uniform_time(self, no_of_packets, start, end): + """Samples decay time uniformly (needs non-uniform packet energies) + + Parameters + ---------- + no_of_packets : int + Number of packets + start : float + Start time + end : float + End time + + Returns + ------- + array + Array of packet decay times + """ + z = np.random.random(no_of_packets) + decay_times = z * start + (1 - z) * end + return decay_times + + def create_packet_times_uniform_energy( + self, + no_of_packets, + start_tau, + end_tau=0.0, + decay_time_min=0.0, + decay_time_max=0.0, + ): + """Samples the decay time from the mean lifetime of the isotopes + + Parameters + ---------- + no_of_packets : int + Number of packets + start_tau : float + Initial isotope mean lifetime + end_tau : float, optional + Ending mean lifetime, by default 0.0 for single decays + decay_time_min : float, optional + Minimum time to decay, by default 0.0 + decay_time_max : float, optional + Maximum time to decay, by default 0.0 + + Returns + ------- + array + Array of decay times + """ + decay_times = np.ones(no_of_packets) * decay_time_min + for i in range(no_of_packets): + # rejection sampling + while (decay_times[i] <= decay_time_min) or ( + decay_times[i] >= decay_time_max + ): + decay_times[i] = -start_tau * np.log( + np.random.random() + ) - end_tau * np.log(np.random.random()) + return decay_times + + def calculate_energy_factors(self, no_of_packets, start_time, decay_times): + """Calculates the factors that adjust the energy of packets emitted + before the first time step and moves those packets to the earliest + possible time + + Parameters + ---------- + no_of_packets : int + Number of packets + start_time : float + First time step + decay_times : array + Packet decay times + + Returns + ------- + array + Energy factors + array + Adjusted decay times + """ + energy_factors = np.ones(no_of_packets) + for i in range(no_of_packets): + if decay_times[i] < start_time: + energy_factors[i] = decay_times[i] / start_time + decay_times[i] = start_time + return energy_factors, decay_times + + def create_packets(self, decays_per_isotope, *args, **kwargs): + """Initialize a collection of GXPacket objects for the simulation + to operate on. + + Parameters + ---------- + decays_per_isotope : array int64 + Number of decays per simulation shell per isotope + + Returns + ------- + list + List of GXPacket objects + array + Array of main output dataframe rows + array + Array of plotting output dataframe rows + array + Array of positron output dataframe rows + """ + number_of_packets = decays_per_isotope.sum().sum() + decays_per_shell = decays_per_isotope.sum().values + + locations = np.zeros((3, number_of_packets)) + directions = np.zeros((3, number_of_packets)) + packet_energies_rf = np.zeros(number_of_packets) + packet_energies_cmf = np.zeros(number_of_packets) + nus_rf = np.zeros(number_of_packets) + nus_cmf = np.zeros(number_of_packets) + shells = np.zeros(number_of_packets) + times = np.zeros(number_of_packets) + # set packets to IN_PROCESS status + statuses = np.ones(number_of_packets, dtype=np.int64) * 3 + + positronium_energy, positronium_intensity = positronium_continuum() + + self.energy_plot_positron_rows = np.zeros((number_of_packets, 4)) + + packet_index = 0 + # go through each shell + for shell_number, pkts in enumerate(decays_per_shell): + isotope_packet_count_df = decays_per_isotope.T.iloc[shell_number] + + for isotope_name, isotope_packet_count in zip( + self.gamma_ray_lines.keys(), isotope_packet_count_df.values + ): + isotope_energy = self.gamma_ray_lines[isotope_name][0, :] + isotope_intensity = self.gamma_ray_lines[isotope_name][1, :] + isotope_positron_fraction = self.calculate_positron_fraction( + self.average_positron_energies[isotope_name], + isotope_energy, + isotope_intensity, + ) + tau_start = self.taus[isotope_name] + + if isotope_name in self.parents: + tau_end = self.taus[self.parents[isotope_name]] + else: + tau_end = 0 + + # sample radii at time = 0 + initial_radii = self.create_packet_radii( + isotope_packet_count, + self.inner_velocities[shell_number], + self.outer_velocities[shell_number], + ) + + # sample directions (valid at all times) + initial_directions = self.create_packet_directions( + isotope_packet_count + ) + + # packet decay time + initial_times = self.create_packet_times_uniform_energy( + isotope_packet_count, + tau_start, + tau_end, + decay_time_min=0, + decay_time_max=self.times[-1], + ) + + # get the time step index of the packets + initial_time_indexes = np.array( + [ + get_index(decay_time, self.times) + for decay_time in initial_times + ] + ) + + # get the time of the middle of the step for each packet + packet_effective_times = np.array( + [self.effective_times[i] for i in initial_time_indexes] + ) + + # scale radius by packet decay time. This could be replaced with + # Geometry object calculations. Note that this also adds a random + # unit vector multiplication for 3D. May not be needed. + initial_locations = ( + initial_radii + * packet_effective_times + * self.create_packet_directions(isotope_packet_count) + ) + + # get the packet shell index + initial_shells = np.ones(isotope_packet_count) * shell_number + + # the individual gamma-ray energies that make up a packet + # co-moving frame, including positronium formation + initial_nu_energies_cmf, positron_mask = self.create_packet_nus( + isotope_packet_count, + isotope_energy, + isotope_intensity, + self.positronium_fraction, + positronium_energy, + positronium_intensity, + ) + + # equivalent frequencies + initial_nus_cmf = initial_nu_energies_cmf / H_CGS_KEV + + # compute scaling factor for packets emitted before start time + # and move packets to start at that time + # probably not necessary- we have rejection sampling in the + # create_packet_times_uniform_energy method + energy_factors, initial_times = self.calculate_energy_factors( + isotope_packet_count, self.times[0], initial_times + ) + + # the CMF energy of a packet scaled by the "early energy factor" + initial_packet_energies_cmf = ( + self.create_packet_energies( + isotope_packet_count, self.packet_energy + ) + * energy_factors + ) + + # rest frame gamma-ray energy and frequency + # this probably works fine without the loop + initial_packet_energies_rf = np.zeros(isotope_packet_count) + initial_nus_rf = np.zeros(isotope_packet_count) + for i in range(isotope_packet_count): + doppler_factor = doppler_factor_3d( + initial_directions[:, i], + initial_locations[:, i], + initial_times[i], + ) + initial_packet_energies_rf[i] = ( + initial_packet_energies_cmf[i] / doppler_factor + ) + initial_nus_rf[i] = initial_nus_cmf[i] / doppler_factor + + self.energy_plot_positron_rows[i] = np.array( + [ + packet_index, + isotope_positron_fraction * self.packet_energy, + # * inv_volume_time[packet.shell, decay_time_index], + initial_radii[i], + initial_times[i], + ] + ) + + packet_index += 1 + + # deposit positron energy + for time in initial_time_indexes: + self.energy_df_rows[shell_number, time] += ( + isotope_positron_fraction * self.packet_energy + ) + + # collect packet properties + locations[ + :, packet_index - isotope_packet_count : packet_index + ] = initial_locations + directions[ + :, packet_index - isotope_packet_count : packet_index + ] = initial_directions + packet_energies_rf[ + packet_index - isotope_packet_count : packet_index + ] = initial_packet_energies_rf + packet_energies_cmf[ + packet_index - isotope_packet_count : packet_index + ] = initial_packet_energies_cmf + nus_rf[ + packet_index - isotope_packet_count : packet_index + ] = initial_nus_rf + nus_cmf[ + packet_index - isotope_packet_count : packet_index + ] = initial_nus_cmf + shells[ + packet_index - isotope_packet_count : packet_index + ] = initial_shells + times[ + packet_index - isotope_packet_count : packet_index + ] = initial_times + + return GXPacketCollection( + locations, + directions, + packet_energies_rf, + packet_energies_cmf, + nus_rf, + nus_cmf, + statuses, + shells, + times, + ) + + def calculate_positron_fraction( + self, positron_energy, isotope_energy, isotope_intensity + ): + """Calculate the fraction of energy that an isotope + releases as positron kinetic energy + + Parameters + ---------- + positron_energy : float + Average kinetic energy of positrons from decay + isotope_energy : numpy array + Photon energies released by the isotope + isotope_intensity : numpy array + Intensity of photon energy release + + Returns + ------- + float + Fraction of energy released as positron kinetic energy + """ + return positron_energy / np.sum(isotope_energy * isotope_intensity) + + +class GammaRayPacketSource(BasePacketSource): + def __init__( + self, + packet_energy, + gamma_ray_lines, + positronium_fraction, + inner_velocities, + outer_velocities, + inv_volume_time, + times, + energy_df_rows, + effective_times, + taus, + parents, + average_positron_energies, + average_power_per_mass, + **kwargs, + ): + self.packet_energy = packet_energy + self.gamma_ray_lines = gamma_ray_lines + self.positronium_fraction = positronium_fraction + self.inner_velocities = inner_velocities + self.outer_velocities = outer_velocities + self.inv_volume_time = inv_volume_time + self.times = times + self.energy_df_rows = energy_df_rows + self.effective_times = effective_times + self.taus = taus + self.parents = parents + self.average_positron_energies = average_positron_energies + self.average_power_per_mass = average_power_per_mass + self.energy_plot_positron_rows = np.empty(0) + super().__init__(**kwargs) + + def create_packet_mus(self, no_of_packets, *args, **kwargs): + return super().create_packet_mus(no_of_packets, *args, **kwargs) + + def create_packet_radii(self, sampled_packets_df): + """Initialize the random radii of packets in a shell + + Parameters + ---------- + packet_count : int + Number of packets in the shell + sampled_packets_df : pd.DataFrame + Dataframe where each row is a packet + + Returns + ------- + array + Array of length packet_count of random locations in the shell + """ + z = np.random.random(len(sampled_packets_df)) + initial_radii = ( + z * sampled_packets_df["inner_velocity"] ** 3.0 + + (1.0 - z) * sampled_packets_df["outer_velocity"] ** 3.0 + ) ** (1.0 / 3.0) + + return initial_radii + + def create_packet_nus( + self, + no_of_packets, + packets, + positronium_fraction, + positronium_energy, + positronium_intensity, + ): + """Create an array of packet frequency-energies (i.e. E = h * nu) + + Parameters + ---------- + no_of_packets : int + Number of packets to produce frequency-energies for + packets : pd.DataFrame + DataFrame of packets + positronium_fraction : float + The fraction of positrons that form positronium + positronium_energy : array + Array of positronium frequency-energies to sample + positronium_intensity : array + Array of positronium intensities to sample + + Returns + ------- + array + Array of sampled frequency-energies + """ + energy_array = np.zeros(no_of_packets) + zs = np.random.random(no_of_packets) + for i in range(no_of_packets): + # positron + if packets.iloc[i]["decay_type"] == "bp": + # positronium formation 75% of the time if fraction is 1 + if zs[i] < positronium_fraction and np.random.random() < 0.75: + energy_array[i] = sample_energy( + positronium_energy, positronium_intensity + ) + else: + energy_array[i] = 511 + else: + energy_array[i] = packets.iloc[i]["radiation_energy_kev"] + + return energy_array + + def create_packet_directions(self, no_of_packets): + """Create an array of random directions + + Parameters + ---------- + no_of_packets : int + Number of packets to produce directions for + + Returns + ------- + array + Array of direction vectors + """ + directions = np.zeros((3, no_of_packets)) + for i in range(no_of_packets): + directions[:, i] = get_random_unit_vector() + + return directions + + def create_packet_energies(self, no_of_packets, energy): + """Create the uniform packet energy for a number of packets + + Parameters + ---------- + no_of_packets : int + Number of packets + energy : float + The packet energy + + Returns + ------- + array + Array of packet energies + """ + return np.ones(no_of_packets) * energy + + def create_packet_times_uniform_time(self, no_of_packets, start, end): + """Samples decay time uniformly (needs non-uniform packet energies) + + Parameters + ---------- + no_of_packets : int + Number of packets + start : float + Start time + end : float + End time + + Returns + ------- + array + Array of packet decay times + """ + z = np.random.random(no_of_packets) + decay_times = z * start + (1 - z) * end + return decay_times + + def create_packet_times_uniform_energy( + self, no_of_packets, isotopes, decay_time + ): + """Samples the decay time from the mean lifetime of the isotopes + + Parameters + ---------- + no_of_packets : int + Number of packets + isotopes : pd.Series + Series of packet parent isotopes + decay_time : array + Series of packet decay time index + + Returns + ------- + array + Array of decay times + """ + decay_times = np.zeros(len(no_of_packets)) + for i, isotope in enumerate(isotopes.to_numpy()): + decay_time_min = self.times[decay_time[i]] + if decay_time_min == self.times[-1]: + decay_time_max = self.effective_times[-1] + else: + decay_time_max = self.times[decay_time[i] + 1] + # rejection sampling + while (decay_times[i] <= decay_time_min) or ( + decay_times[i] >= decay_time_max + ): + decay_times[i] = -self.taus[isotope] * np.log( + np.random.random() + ) + return decay_times + + def create_packets( + self, decays_per_isotope, number_of_packets, *args, **kwargs + ): + """Initialize a collection of GXPacket objects for the simulation + to operate on. + + Parameters + ---------- + decays_per_isotope : array int64 + Probability of decays per simulation shell per isotope per time step + number_of_packets : int + Number of packets to create + + Returns + ------- + GXPacketCollection + """ + # initialize arrays for most packet properties + locations = np.zeros((3, number_of_packets)) + directions = np.zeros((3, number_of_packets)) + packet_energies_rf = np.zeros(number_of_packets) + packet_energies_cmf = np.zeros(number_of_packets) + nus_rf = np.zeros(number_of_packets) + nus_cmf = np.zeros(number_of_packets) + times = np.zeros(number_of_packets) + # set packets to IN_PROCESS status + statuses = np.ones(number_of_packets, dtype=np.int64) * 3 + + self.energy_plot_positron_rows = np.zeros((number_of_packets, 4)) + + # compute positronium continuum + positronium_energy, positronium_intensity = positronium_continuum() + + # sample packets from dataframe, returning a dataframe where each row is + # a sampled packet + sampled_packets_df = decays_per_isotope.sample( + n=number_of_packets, + weights="decay_energy_erg", + replace=True, + random_state=np.random.RandomState(self.base_seed), + ) + # get unique isotopes that have produced packets + isotopes = pd.unique(sampled_packets_df.index.get_level_values(2)) + + # compute the positron fraction for unique isotopes + isotope_positron_fraction = self.calculate_positron_fraction(isotopes) + + # get the packet shell index + shells = sampled_packets_df.index.get_level_values(1) + + # get the inner and outer velocity boundaries for each packet to compute + # the initial radii + sampled_packets_df["inner_velocity"] = self.inner_velocities[shells] + sampled_packets_df["outer_velocity"] = self.outer_velocities[shells] + + # sample radii at time = 0 + initial_radii = self.create_packet_radii(sampled_packets_df) + + # get the time step index of the packets + initial_time_indexes = sampled_packets_df.index.get_level_values(0) + + # get the time of the middle of the step for each packet + packet_effective_times = np.array( + [self.effective_times[i] for i in initial_time_indexes] + ) + + # packet decay time + times = self.create_packet_times_uniform_energy( + number_of_packets, + sampled_packets_df.index.get_level_values(2), + packet_effective_times, + ) + + # scale radius by packet decay time. This could be replaced with + # Geometry object calculations. Note that this also adds a random + # unit vector multiplication for 3D. May not be needed. + locations = ( + initial_radii + * packet_effective_times + * self.create_packet_directions(number_of_packets) + ) + + # sample directions (valid at all times), non-relativistic + directions = self.create_packet_directions(number_of_packets) + + # the individual gamma-ray energy that makes up a packet + # co-moving frame, including positronium formation + nu_energies_cmf = self.create_packet_nus( + number_of_packets, + sampled_packets_df, + self.positronium_fraction, + positronium_energy, + positronium_intensity, + ) + + # equivalent frequencies + nus_cmf = nu_energies_cmf / H_CGS_KEV + + # per packet co-moving frame total energy + packet_energies_cmf = self.create_packet_energies( + number_of_packets, self.packet_energy + ) + + # rest frame gamma-ray energy and frequency + # this probably works fine without the loop + # non-relativistic + packet_energies_rf = np.zeros(number_of_packets) + nus_rf = np.zeros(number_of_packets) + for i in range(number_of_packets): + doppler_factor = doppler_factor_3d( + directions[:, i], + locations[:, i], + times[i], + ) + packet_energies_rf[i] = packet_energies_cmf[i] / doppler_factor + nus_rf[i] = nus_cmf[i] / doppler_factor + + # deposit positron energy in both output arrays + # this is an average across all packets that are created + # it could be changed to be only for packets that are from positrons + self.energy_plot_positron_rows[i] = np.array( + [ + i, + isotope_positron_fraction[sampled_packets_df["isotopes"][i]] + * packet_energies_cmf[i], + # this needs to be sqrt(sum of squares) to get radius + np.linalg.norm(locations[i]), + times[i], + ] + ) + + # this is an average across all packets that are created + # it could be changed to be only for packets that are from positrons + self.energy_df_rows[shells[i], times[i]] += ( + isotope_positron_fraction[sampled_packets_df["isotopes"][i]] + * packet_energies_cmf[i] + ) + + return GXPacketCollection( + locations, + directions, + packet_energies_rf, + packet_energies_cmf, + nus_rf, + nus_cmf, + statuses, + shells, + times, + ) + + def calculate_positron_fraction(self, isotopes): + """Calculate the fraction of energy that an isotope + releases as positron kinetic energy + + Parameters + ---------- + isotopes : array + Array of isotope names as strings + + Returns + ------- + dict + Fraction of energy released as positron kinetic energy per isotope + """ + positron_fraction = {} + + for isotope in isotopes: + isotope_energy = self.gamma_ray_lines[isotope][0, :] + isotope_intensity = self.gamma_ray_lines[isotope][1, :] + positron_fraction[isotope] = self.average_positron_energies[ + isotope + ] / np.sum(isotope_energy * isotope_intensity) + return positron_fraction diff --git a/tardis/energy_input/gamma_ray_transport.py b/tardis/energy_input/gamma_ray_transport.py new file mode 100644 index 00000000000..bd769191195 --- /dev/null +++ b/tardis/energy_input/gamma_ray_transport.py @@ -0,0 +1,488 @@ +import logging + +import astropy.units as u +import numpy as np +import pandas as pd +import radioactivedecay as rd + +from tardis.energy_input.energy_source import ( + get_all_isotopes, + setup_input_energy, +) +from tardis.opacities.opacities import M_P + +# Energy: keV, exported as eV for SF solver +# distance: cm +# mass: g +# time: s +logger = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO) + + +def get_nuclide_atomic_number(nuclide): + return rd.Nuclide(nuclide).Z + + +def get_chain_decay_power_per_ejectamass( + inventory, + time, + time_start, + average_energies, + average_positron_energies, + tau_end, +): + # total decay power per mass [erg/s/g] for a given decaypath + # only decays at the end of the chain contributed from the initial abundance of the top of the chain are counted + # (these can be can be same for a chain of length one) + + # need to find a way to connect inventory_start with inventory_end to obtain start and end of chains + # hopefully can just do it all at once + + # start_isotope is e.g. Ni56 while end_isotope would be e.g. Fe56 + inventory_end = inventory.decay(time - time_start) + # contribution to the end nuclide abundance from the top of chain (could be a length-one chain Z,A_top = Z,A_end + # so contribution would be from init abundance only) + + decaypower = [] + progeny = inventory.progeny() + + for start_isotope in progeny: + # ignore branching probs for now + end_isotope = progeny[start_isotope][0] + + if rd.Nuclide(end_isotope).half_life("readable") == "stable": + end_isotope = start_isotope + + # i.e. need to get end_isotope(s) by finding out which ones have no progeny left + # this should be the total number of "end chain" isotopes after (time - time_start) + endnucabund = inventory_end.mass_fractions()[end_isotope] + + # this is the total decay energy from gamma-rays and positrons for the end of chain isotope + # endecay = get_decaypath_lastnucdecayenergy(decaypathindex) + endecay = ( + average_energies[end_isotope] + + average_positron_energies[end_isotope] + ) + + print("Decay energy, abundance, tau") + print(endecay) + print(endnucabund) + print(tau_end) + + decaypower.append( + endecay + * endnucabund + / tau_end + / (rd.Nuclide(start_isotope).atomic_mass * M_P) + ) + + return decaypower + + +def calculate_ejecta_velocity_volume(model): + outer_velocities = model.v_outer.to("cm/s").value + inner_velocities = model.v_inner.to("cm/s").value + ejecta_velocity_volume = ( + 4 * np.pi / 3 * (outer_velocities**3.0 - inner_velocities**3.0) + ) + + return ejecta_velocity_volume + + +def calculate_total_decays_old(inventories, time_delta): + """Function to create inventories of isotope + + Parameters + ---------- + model : tardis.Radial1DModel + The tardis model to calculate gamma ray propagation through + + time_end : float + End time of simulation in days + + Returns + ------- + Total decay list : List + list of total decays for x g of isotope for time 't' + """ + time_delta = u.Quantity(time_delta, u.s) + total_decays = {} + for shell, isotopes in inventories.items(): + total_decays[shell] = {} + for isotope, name in isotopes.items(): + # decays = name.decay(time_delta.value, "s") + total_decays[shell][isotope] = name.cumulative_decays( + time_delta.value + ) + return total_decays + + +def create_isotope_dicts_old(raw_isotope_abundance, cell_masses): + """ + Function to create a dictionary of isotopes for each shell with their masses. + + Parameters + ---------- + raw_isotope_abundance : pd.DataFrame + isotope abundance in mass fractions. + cell_masses : numpy.ndarray + shell masses in units of g + + Returns + ------- + isotope_dicts : Dict + dictionary of isotopes for each shell with their ``masses``. + For eg: {0: {(28, 56): {'Ni56': 0.0001}, (27, 57): {'Co56': 0.0001}} + {1: {(28, 56): {'Ni56': 0.0001}, (27, 57): {'Co56': 0.0001}}} etc + + """ + isotope_dicts = {} + for i in range(len(raw_isotope_abundance.columns)): + isotope_dicts[i] = {} + for ( + atomic_number, + mass_number, + ), abundances in raw_isotope_abundance.iterrows(): + isotope_dicts[i][atomic_number, mass_number] = {} + nuclear_symbol = f"{rd.utils.Z_to_elem(atomic_number)}{mass_number}" + isotope_dicts[i][atomic_number, mass_number][nuclear_symbol] = ( + abundances[i] * cell_masses[i].to(u.g).value + ) + + return isotope_dicts + + +def create_inventories_dict_old(isotope_dict): + """Function to create dictionary of inventories for each shell + + Parameters + ---------- + isotope_dict : Dict + dictionary of isotopes for each shell with their ``masses``. + + Returns + ------- + inv : Dict + dictionary of inventories for each shell + For eg: {0: {'Ni56': <radioactivedecay.Inventory at 0x7f7d2c0d0e50>, + 'Co56': <radioactivedecay.Inventory at 0x7f7d2c0d0e50>}, + {1: {'Ni56': <radioactivedecay.Inventory at 0x7f7d2c0d0e50>, + 'Co56': <radioactivedecay.Inventory at 0x7f7d2c0d0e50>}} etc + """ + inv = {} + for shell, isotopes in isotope_dict.items(): + inv[shell] = {} + for isotope, name in isotopes.items(): + inv[shell][isotope] = rd.Inventory(name, "g") + + return inv + + +def calculate_average_energies(raw_isotope_abundance, gamma_ray_lines): + """ + Function to calculate average energies of positrons and gamma rays + from a list of gamma ray lines from nndc. + + Parameters + ---------- + raw_isotope_abundance : pd.DataFrame + isotope abundance in mass fractions + gamma_ray_lines : pd.DataFrame + decay data + + Returns + ------- + average_energies_list : List + list of gamma ray energies + average_positron_energies_list : List + list of positron energies + gamma_ray_line_array_list : List + list of gamma ray lines + + """ + all_isotope_names = get_all_isotopes(raw_isotope_abundance) + all_isotope_names.sort() + + gamma_ray_line_array_list = [] + average_energies_list = [] + average_positron_energies_list = [] + + gamma_ray_line_dict = {} + average_energies = {} + average_positron_energies = {} + + for i, isotope in enumerate(all_isotope_names): + energy, intensity = setup_input_energy( + gamma_ray_lines[gamma_ray_lines.index == isotope.replace("-", "")], + "g", + ) + average_energies_list.append(np.sum(energy * intensity)) # keV + gamma_ray_line_array_list.append(np.stack([energy, intensity])) + + positron_energy, positron_intensity = setup_input_energy( + gamma_ray_lines[gamma_ray_lines.index == isotope.replace("-", "")], + "bp", + ) + average_positron_energies_list.append( + np.sum(positron_energy * positron_intensity) + ) + + for iso, lines in zip(all_isotope_names, gamma_ray_line_array_list): + gamma_ray_line_dict[iso] = lines + + for iso, energy, positron_energy in zip( + all_isotope_names, average_energies_list, average_positron_energies_list + ): + average_energies[iso] = energy + average_positron_energies[iso] = positron_energy + + return ( + average_energies, + average_positron_energies, + gamma_ray_line_dict, + ) + + +def get_taus(raw_isotope_abundance): + """ + Function to calculate taus for each isotope + + Parameters + ---------- + raw_isotope_abundance : pd.DataFrame + isotope abundance in mass fractions + + Returns + ------- + taus : Dict + dictionary of taus for each isotope + parents : Dict + dictionary of parents for each isotope + """ + all_isotope_names = get_all_isotopes(raw_isotope_abundance) + all_isotope_names.sort() + + taus = {} + parents = {} + for isotope in all_isotope_names: + nuclide = rd.Nuclide(isotope) + taus[isotope] = nuclide.half_life() / np.log(2) + child = nuclide.progeny() + if child is not None: + for c in child: + if rd.Nuclide(c).half_life("readable") != "stable": + # this is a dict of child: parent intended to find + # the parents of a given isotope. + # if there is no parent, there is no item. + parents[c] = isotope + + return taus, parents + + +def decay_chain_energies( + average_energies, + total_decays, +): + """ + Function to calculate decay chain energies. + + Parameters + ---------- + raw_isotope_abundance : pd.DataFrame + isotope abundance in mass fractions + average_energies_list : List + list of gamma ray energies + average_positron_energies_list : List + list of positron energies + gamma_ray_line_array_list : List + list of gamma ray lines + total_decays : Dict + dictionary of total decays for each isotope in each shell + + Returns + ------- + decay_energy : Dict + dictionary of decay chain energies for each isotope in each shell + + """ + decay_energy = {} + for shell, isotopes in total_decays.items(): + decay_energy[shell] = {} + for name, isotope in isotopes.items(): + decay_energy[shell][name] = {} + for iso, dps in isotope.items(): + decay_energy[shell][name][iso] = dps * average_energies[iso] + + return decay_energy + + +def fractional_decay_energy(decay_energy): + """Function to calculate fractional decay energy + + Parameters + ---------- + decay_energy : Dict + dictionary of decay chain energies for each isotope in each shell + + Returns + ------- + fractional_decay_energy : Dict + dictionary of fractional decay chain energies for each isotope in each shell + """ + fractional_decay_energy = { + shell: { + parent_isotope: { + isotopes: ( + decay_energy[shell][parent_isotope][isotopes] + / sum(decay_energy[shell][parent_isotope].values()) + if decay_energy[shell][parent_isotope][isotopes] != 0.0 + else 0.0 + ) + for isotopes in decay_energy[shell][parent_isotope] + } + for parent_isotope in decay_energy[shell] + } + for shell in decay_energy + } + + return fractional_decay_energy + + +def calculate_energy_per_mass(decay_energy, raw_isotope_abundance, cell_masses): + """ + Function to calculate decay energy per mass for each isotope chain. + + Parameters + ---------- + decay_energy : Dict + dictionary of decay chain energies for each isotope in each shell + raw_isotope_abundance : pd.DataFrame + isotope abundance in mass fractions. + cell_masses : numpy.ndarray + shell masses in units of g + + Returns + ------- + energy_per_mass : pd.DataFrame + decay energy per mass for each isotope chain + For e.g Ni56 has 2 decay chains: + Ni56 -> Co56 -> Fe56. It will calculate the decay energy per mass for each chain + and store as a dataframe. + """ + energy_dict = {} + for shell, isotopes in decay_energy.items(): + energy_dict[shell] = {} + for name, isotope in isotopes.items(): + energy_dict[shell][name] = sum(isotope.values()) + + energy_list = [] + for shell, isotopes in energy_dict.items(): + for isotope, energy in isotopes.items(): + energy_list.append( + { + "shell": shell, + "atomic_number": isotope[0], + "mass_number": isotope[1], + "value": energy, + } + ) + + df = pd.DataFrame(energy_list) + energy_df = pd.pivot_table( + df, + values="value", + index=["atomic_number", "mass_number"], + columns="shell", + ) + + energy_per_mass = energy_df.divide( + (raw_isotope_abundance * cell_masses).to_numpy(), axis=0 + ) + + return energy_per_mass, energy_df + + +def distribute_packets(decay_energy, total_energy, num_packets): + packets_per_isotope = {} + for shell, isotopes in decay_energy.items(): + packets_per_isotope[shell] = {} + for name, isotope in isotopes.items(): + packets_per_isotope[shell][name] = {} + for line, energy in isotope.items(): + packets_per_isotope[shell][name][line] = int( + energy / total_energy * num_packets + ) + + packets_per_isotope_list = [] + for shell, parent_isotope in packets_per_isotope.items(): + for isotopes, isotope_dict in parent_isotope.items(): + for name, value in isotope_dict.items(): + packets_per_isotope_list.append( + { + "shell": shell, + "element": name, + "value": value, + } + ) + + df = pd.DataFrame(packets_per_isotope_list) + packets_per_isotope_df = pd.pivot_table( + df, + values="value", + index="element", + columns="shell", + ) + + return packets_per_isotope_df + + +def packets_per_isotope(fractional_decay_energy, decayed_packet_count_dict): + packets_per_isotope = { + shell: { + parent_isotope: { + isotopes: fractional_decay_energy[shell][parent_isotope][ + isotopes + ] + * decayed_packet_count_dict[shell][parent_isotope] + for isotopes in fractional_decay_energy[shell][parent_isotope] + } + for parent_isotope in fractional_decay_energy[shell] + } + for shell in fractional_decay_energy + } + + packets_per_isotope_list = [] + for shell, parent_isotope in packets_per_isotope.items(): + for isotopes, isotope_dict in parent_isotope.items(): + for name, value in isotope_dict.items(): + packets_per_isotope_list.append( + { + "shell": shell, + "element": name, + "value": value, + } + ) + + df = pd.DataFrame(packets_per_isotope_list) + packets_per_isotope_df = pd.pivot_table( + df, + values="value", + index="element", + columns="shell", + ) + + return packets_per_isotope_df + + +def calculate_average_power_per_mass(energy_per_mass, time_delta): + # Time averaged energy per mass for constant packet count + average_power_per_mass = energy_per_mass / (time_delta) + + return average_power_per_mass + + +def iron_group_fraction_per_shell(model): + # Taking iron group to be elements 21-30 + # Used as part of the approximations for photoabsorption and pair creation + # Dependent on atomic data + return model.abundance.loc[(21):(30)].sum(axis=0) diff --git a/tardis/energy_input/main_gamma_ray_loop.py b/tardis/energy_input/main_gamma_ray_loop.py new file mode 100644 index 00000000000..654656300ad --- /dev/null +++ b/tardis/energy_input/main_gamma_ray_loop.py @@ -0,0 +1,288 @@ +import logging + +import astropy.units as u +import numpy as np +import pandas as pd + +from tardis.energy_input.energy_source import ( + get_nuclear_lines_database, +) +from tardis.energy_input.gamma_packet_loop import gamma_packet_loop +from tardis.energy_input.gamma_ray_channel import ( + calculate_total_decays, + create_inventories_dict, + create_isotope_dicts, +) + +from tardis.energy_input.gamma_ray_transport import ( + calculate_total_decays_old, + create_isotope_dicts_old, + create_inventories_dict_old, +) +from tardis.energy_input.gamma_ray_packet_source import RadioactivePacketSource +from tardis.energy_input.gamma_ray_transport import ( + calculate_average_energies, + calculate_average_power_per_mass, + calculate_ejecta_velocity_volume, + calculate_energy_per_mass, + decay_chain_energies, + distribute_packets, + get_taus, + iron_group_fraction_per_shell, +) +from tardis.energy_input.GXPacket import GXPacket + +logger = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO) + + +def run_gamma_ray_loop( + model, + plasma, + num_decays, + time_start, + time_end, + time_space, + time_steps, + seed, + positronium_fraction, + path_to_decay_data, + spectrum_bins, + grey_opacity, + photoabsorption_opacity="tardis", + pair_creation_opacity="tardis", +): + """ + Main loop to determine the gamma-ray propagation through the ejecta. + """ + np.random.seed(seed) + time_explosion = model.time_explosion.to(u.s).value + inner_velocities = model.v_inner.to("cm/s").value + outer_velocities = model.v_outer.to("cm/s").value + ejecta_volume = model.volume.to("cm^3").value + number_of_shells = model.no_of_shells + shell_masses = model.volume * model.density + raw_isotope_abundance = model.composition.raw_isotope_abundance.sort_values( + by=["atomic_number", "mass_number"], ascending=False + ) + time_start *= u.d.to(u.s) + time_end *= u.d.to(u.s) + + assert time_start < time_end, "time_start must be smaller than time_end!" + if time_space == "log": + times = np.geomspace(time_start, time_end, time_steps + 1) + effective_time_array = np.sqrt(times[:-1] * times[1:]) + else: + times = np.linspace(time_start, time_end, time_steps + 1) + effective_time_array = 0.5 * (times[:-1] + times[1:]) + + dt_array = np.diff(times) + + ejecta_velocity_volume = calculate_ejecta_velocity_volume(model) + + inv_volume_time = ( + 1.0 / ejecta_velocity_volume[:, np.newaxis] + ) / effective_time_array**3.0 + + energy_df_rows = np.zeros((number_of_shells, time_steps)) + # Use isotopic number density + for atom_number in plasma.isotope_number_density.index.get_level_values(0): + values = plasma.isotope_number_density.loc[atom_number].values + if values.shape[0] > 1: + plasma.isotope_number_density.loc[atom_number].update = np.sum( + values, axis=0 + ) + else: + plasma.isotope_number_density.loc[atom_number].update = values + + # Electron number density + electron_number_density = plasma.number_density.mul( + plasma.number_density.index, axis=0 + ).sum() + taus, parents = get_taus(raw_isotope_abundance) + # inventories = raw_isotope_abundance.to_inventories() + electron_number = np.array(electron_number_density * ejecta_volume) + electron_number_density_time = ( + electron_number[:, np.newaxis] * inv_volume_time + ) + + # Calculate decay chain energies + + mass_density_time = shell_masses[:, np.newaxis] * inv_volume_time + gamma_ray_lines = get_nuclear_lines_database(path_to_decay_data) + isotope_dict = create_isotope_dicts_old(raw_isotope_abundance, shell_masses) + inventories_dict = create_inventories_dict_old(isotope_dict) + total_decays = calculate_total_decays_old( + inventories_dict, time_end - time_start + ) + + ( + average_energies, + average_positron_energies, + gamma_ray_line_dict, + ) = calculate_average_energies(raw_isotope_abundance, gamma_ray_lines) + + decayed_energy = decay_chain_energies( + average_energies, + total_decays, + ) + energy_per_mass, energy_df = calculate_energy_per_mass( + decayed_energy, raw_isotope_abundance, shell_masses + ) + average_power_per_mass = calculate_average_power_per_mass( + energy_per_mass, time_end - time_start + ) + number_of_isotopes = plasma.isotope_number_density * ejecta_volume + total_isotope_number = number_of_isotopes.sum().sum() + decayed_packet_count = num_decays * number_of_isotopes.divide( + total_isotope_number, axis=0 + ) + + total_energy = energy_df.sum().sum() + energy_per_packet = total_energy / num_decays + packets_per_isotope_df = ( + distribute_packets(decayed_energy, total_energy, num_decays) + .round() + .fillna(0) + .astype(int) + ) + + total_energy = total_energy * u.eV.to("erg") + + logger.info(f"Total gamma-ray energy is {total_energy}") + + iron_group_fraction = iron_group_fraction_per_shell(model) + number_of_packets = packets_per_isotope_df.sum().sum() + logger.info(f"Total number of packets is {number_of_packets}") + individual_packet_energy = total_energy / number_of_packets + logger.info(f"Energy per packet is {individual_packet_energy}") + + logger.info("Initializing packets") + + packet_source = RadioactivePacketSource( + individual_packet_energy, + gamma_ray_line_dict, + positronium_fraction, + inner_velocities, + outer_velocities, + inv_volume_time, + times, + energy_df_rows, + effective_time_array, + taus, + parents, + average_positron_energies, + average_power_per_mass, + ) + + packet_collection = packet_source.create_packets(packets_per_isotope_df) + + energy_df_rows = packet_source.energy_df_rows + energy_plot_df_rows = np.zeros((number_of_packets, 8)) + + logger.info("Creating packet list") + packets = [] + total_cmf_energy = packet_collection.energy_cmf.sum() + total_rf_energy = packet_collection.energy_rf.sum() + for i in range(number_of_packets): + packet = GXPacket( + packet_collection.location[:, i], + packet_collection.direction[:, i], + packet_collection.energy_rf[i], + packet_collection.energy_cmf[i], + packet_collection.nu_rf[i], + packet_collection.nu_cmf[i], + packet_collection.status[i], + packet_collection.shell[i], + packet_collection.time_current[i], + ) + packets.append(packet) + energy_plot_df_rows[i] = np.array( + [ + i, + packet.energy_rf, + packet.get_location_r(), + packet.time_current, + int(packet.status), + 0, + 0, + 0, + ] + ) + + logger.info(f"Total cmf energy is {total_cmf_energy}") + logger.info(f"Total rf energy is {total_rf_energy}") + + energy_bins = np.logspace(2, 3.8, spectrum_bins) + energy_out = np.zeros((len(energy_bins - 1), time_steps)) + packets_info_array = np.zeros((int(num_decays), 8)) + + ( + energy_df_rows, + energy_plot_df_rows, + energy_out, + deposition_estimator, + bin_width, + packets_array, + ) = gamma_packet_loop( + packets, + grey_opacity, + photoabsorption_opacity, + pair_creation_opacity, + electron_number_density_time, + mass_density_time, + inv_volume_time, + iron_group_fraction.to_numpy(), + inner_velocities, + outer_velocities, + times, + dt_array, + effective_time_array, + energy_bins, + energy_df_rows, + energy_plot_df_rows, + energy_out, + packets_info_array, + ) + + energy_plot_df = pd.DataFrame( + data=energy_plot_df_rows, + columns=[ + "packet_index", + "energy_input", + "energy_input_r", + "energy_input_time", + "energy_input_type", + "compton_opacity", + "photoabsorption_opacity", + "total_opacity", + ], + ) + + energy_plot_positrons = pd.DataFrame( + data=packet_source.energy_plot_positron_rows, + columns=[ + "packet_index", + "energy_input", + "energy_input_r", + "energy_input_time", + ], + ) + + energy_estimated_deposition = ( + pd.DataFrame(data=deposition_estimator, columns=times[:-1]) + ) / dt_array + + energy_df = pd.DataFrame(data=energy_df_rows, columns=times[:-1]) / dt_array + escape_energy = pd.DataFrame( + data=energy_out, columns=times[:-1], index=energy_bins + ) + + return ( + energy_df, + energy_plot_df, + escape_energy, + decayed_packet_count, + energy_plot_positrons, + energy_estimated_deposition, + ) diff --git a/tardis/energy_input/nuclear_energy_source.py b/tardis/energy_input/nuclear_energy_source.py new file mode 100644 index 00000000000..ca4c3f83cb6 --- /dev/null +++ b/tardis/energy_input/nuclear_energy_source.py @@ -0,0 +1,53 @@ +from nuclear.ejecta import Ejecta +from nuclear.io.nndc import get_decay_radiation_database, store_decay_radiation + + +def decay_nuclides(shell_mass, initial_composition, epoch): + """Decay model + + Parameters + ---------- + shell_mass : float + Mass of the shell in grams + initial_composition : DataFrame + Initial ejecta composition + epoch : float + Time in days + + Returns + ------- + DataFrame + New composition at time epoch + """ + decay_model = Ejecta(shell_mass, initial_composition) + + new_fractions = decay_model.decay(epoch) + return new_fractions + + +def get_decay_database( + isotope_abundance, +): + """Gets the decay radiation database for a set + of isotopes + + Parameters + ---------- + isotope_abundance : DataFrame + DataFrame of simulation isotope masses per shell + + Returns + ------- + DataFrame + Decay radiation database + DataFrame + Metadata for the decay radiation database + """ + for column in isotope_abundance: + if column == "Fe56": + continue + store_decay_radiation(column, force_update=False) + + decay_rad_db, meta = get_decay_radiation_database() + + return decay_rad_db, meta diff --git a/tardis/energy_input/samplers.py b/tardis/energy_input/samplers.py new file mode 100644 index 00000000000..674345c649f --- /dev/null +++ b/tardis/energy_input/samplers.py @@ -0,0 +1,140 @@ +import numpy as np +from numba import njit + +from tardis.transport.montecarlo import njit_dict_no_parallel + + +@njit(**njit_dict_no_parallel) +def sample_mass(masses, inner_radius, outer_radius): + """Samples location weighted by mass + + Parameters + ---------- + masses : array + Shell masses + inner_radius : array + Inner radii + outer_radius : array + Outer radii + + Returns + ------- + float + Sampled radius + int + Sampled shell index + """ + norm_mass = masses / np.sum(masses) + cdf = np.cumsum(norm_mass) + shell = np.searchsorted(cdf, np.random.random()) + + z = np.random.random() + radius = ( + z * inner_radius[shell] ** 3.0 + (1.0 - z) * outer_radius[shell] ** 3.0 + ) ** (1.0 / 3.0) + + return radius, shell + + +@njit(**njit_dict_no_parallel) +def create_energy_cdf(energy, intensity): + """Creates a CDF of given intensities + + Parameters + ---------- + energy : One-dimensional Numpy Array, dtype float + Array of energies + intensity : One-dimensional Numpy Array, dtype float + Array of intensities + + Returns + ------- + One-dimensional Numpy Array, dtype float + Sorted energy array + One-dimensional Numpy Array, dtype float + CDF where each index corresponds to the energy in + the sorted array + """ + energy.sort() + sorted_indices = np.argsort(energy) + sorted_intensity = intensity[sorted_indices] + norm_intensity = sorted_intensity / np.sum(sorted_intensity) + cdf = np.cumsum(norm_intensity) + + return energy, cdf + + +@njit(**njit_dict_no_parallel) +def sample_energy_distribution(energy_sorted, cdf): + """Randomly samples a CDF of energies + + Parameters + ---------- + energy_sorted : One-dimensional Numpy Array, dtype float + Sorted energy array + cdf : One-dimensional Numpy Array, dtype float + CDF + + Returns + ------- + float + Sampled energy + """ + index = np.searchsorted(cdf, np.random.random()) + + return energy_sorted[index] + + +@njit(**njit_dict_no_parallel) +def sample_energy(energy, intensity): + """Samples energy from energy and intensity + + Parameters + ---------- + energy : One-dimensional Numpy Array, dtype float + Array of energies + intensity : One-dimensional Numpy Array, dtype float + Array of intensities + + Returns + ------- + float + Energy + """ + z = np.random.random() + + average = (energy * intensity).sum() + total = 0 + for e, i in zip(energy, intensity): + total += e * i / average + if z <= total: + return e + + return False + + +@njit(**njit_dict_no_parallel) +def sample_decay_time( + start_tau, end_tau=0.0, decay_time_min=0.0, decay_time_max=0.0 +): + """Samples the decay time from the mean lifetime + of the isotopes (needs restructuring for more isotopes) + + Parameters + ---------- + start_tau : float64 + Initial isotope mean lifetime + end_tau : float64, optional + Ending mean lifetime, by default 0 for single decays + + Returns + ------- + float64 + Sampled decay time + """ + decay_time = decay_time_min + while (decay_time <= decay_time_min) or (decay_time >= decay_time_max): + decay_time = -start_tau * np.log(np.random.random()) - end_tau * np.log( + np.random.random() + ) + return decay_time diff --git a/tardis/energy_input/tests/__init__.py b/tardis/energy_input/tests/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/energy_input/tests/conftest.py b/tardis/energy_input/tests/conftest.py new file mode 100644 index 00000000000..b36623ef660 --- /dev/null +++ b/tardis/energy_input/tests/conftest.py @@ -0,0 +1,26 @@ +import pytest +import numpy as np + +from tardis.energy_input.GXPacket import GXPacket, GXPacketStatus +from tardis.energy_input.util import H_CGS_KEV + + +@pytest.fixture(scope="function") +def basic_gamma_ray(): + """basic gamma ray fixture + + Returns + ------- + GXPacket + """ + return GXPacket( + location=np.array([1.36375693e13, 4.10589818e14, 9.11718168e14]), + direction=np.array([-0.97113853, 0.23134328, -0.05805379]), + energy_rf=1e52, + energy_cmf=1e52, + nu_rf=1000.0e3 / H_CGS_KEV, + nu_cmf=1000.0e3 / H_CGS_KEV, + status=GXPacketStatus.IN_PROCESS, + shell=1, + time_current=1000, + ) diff --git a/tardis/energy_input/tests/test_energy_source.py b/tardis/energy_input/tests/test_energy_source.py new file mode 100644 index 00000000000..106124f1a68 --- /dev/null +++ b/tardis/energy_input/tests/test_energy_source.py @@ -0,0 +1,47 @@ +import numpy as np +import numpy.testing as npt +import pytest + +from tardis.energy_input.samplers import ( + create_energy_cdf, +) + + +@pytest.mark.parametrize( + ["energy", "intensity", "expected_cdf"], + [ + (np.array([100.0, 50.0]), np.array([1.0, 1.0]), np.array([0.5, 1.0])), + (np.array([50.0, 100.0]), np.array([0.0, 1.0]), np.array([0.0, 1.0])), + ], +) +def test_create_energy_cdf(energy, intensity, expected_cdf): + """ + Parameters + ---------- + energy : One-dimensional Numpy Array, dtype float + intensity : One-dimensional Numpy Array, dtype float + expected_cdf : One-dimensional Numpy Array, dtype float + """ + actual_energy, actual_cdf = create_energy_cdf(energy, intensity) + expected_energy = np.sort(energy) + + npt.assert_array_almost_equal_nulp(actual_cdf, expected_cdf) + npt.assert_array_almost_equal_nulp(actual_energy, expected_energy) + + +@pytest.mark.xfail(reason="To be implemented") +def test_sample_energy_distribution(): + """To test the energy distribution sample""" + assert False + + +@pytest.mark.xfail(reason="To be implemented") +def test_setup_input_energy(): + """To test setting up the input energy""" + assert False + + +@pytest.mark.xfail(reason="To be implemented") +def test_intensity_ratio(): + """To test the intensity ratio""" + assert False diff --git a/tardis/energy_input/tests/test_gamma_ray_channel.py b/tardis/energy_input/tests/test_gamma_ray_channel.py new file mode 100644 index 00000000000..5842ba67783 --- /dev/null +++ b/tardis/energy_input/tests/test_gamma_ray_channel.py @@ -0,0 +1,236 @@ +import pytest +import numpy as np +from pathlib import Path +import astropy.units as u +import numpy.testing as npt +import radioactivedecay as rd +import astropy.constants as const +from radioactivedecay import converters + +from tardis.model import SimulationState +from tardis.io.configuration import config_reader +from tardis.energy_input.energy_source import ( + get_nuclear_lines_database, +) +from tardis.energy_input.gamma_ray_channel import ( + create_isotope_dicts, + create_inventories_dict, + calculate_total_decays, + create_isotope_decay_df, +) + + +@pytest.fixture(scope="module") +def gamma_ray_config(example_configuration_dir: Path): + """ + Parameters + ---------- + example_configuration_dir: Path to the configuration directory. + + Returns + ------- + Tardis configuration + """ + + yml_path = ( + example_configuration_dir + / "tardis_configv1_density_exponential_nebular_multi_isotope.yml" + ) + + return config_reader.Configuration.from_yaml(yml_path) + + +@pytest.fixture(scope="module") +def gamma_ray_simulation_state(gamma_ray_config, atomic_dataset): + """ + Parameters + ---------- + gamma_ray_config: Tardis configuration + atomic_dataset: Tardis atomic-nuclear dataset + + Returns + ------- + Tardis simulation state + """ + + gamma_ray_config.model.structure.velocity.start = 1.0 * u.km / u.s + gamma_ray_config.model.structure.density.rho_0 = 5.0e2 * u.g / u.cm**3 + gamma_ray_config.supernova.time_explosion = 150 * u.d + + return SimulationState.from_config( + gamma_ray_config, atom_data=atomic_dataset + ) + + +@pytest.fixture(scope="module") +def gamma_ray_test_composition(gamma_ray_simulation_state): + """ + Parameters + ---------- + gamma_ray_simulation_state: Tardis simulation state + + Returns + ------- + raw_isotopic_mass_fraction: Raw isotopic mass fraction + cell_masses: Mass of the cell + """ + + raw_isotopic_mass_fraction = ( + gamma_ray_simulation_state.composition.raw_isotope_abundance + ) + composition = gamma_ray_simulation_state.composition + cell_masses = composition.calculate_cell_masses( + gamma_ray_simulation_state.geometry.volume + ) + + return raw_isotopic_mass_fraction, cell_masses + + +def test_calculate_cell_masses(gamma_ray_simulation_state): + """Function to test calculation of shell masses. + Parameters + ---------- + gamma_ray_simulation_state: Tardis simulation state. + """ + volume = 2.70936170e39 * u.cm**3 + density = 5.24801665e-09 * u.g / u.cm**3 + desired = volume * density + + shell_masses = gamma_ray_simulation_state.composition.calculate_cell_masses( + gamma_ray_simulation_state.geometry.volume + ) + + npt.assert_allclose(shell_masses[0], desired) + + +@pytest.mark.parametrize("nuclide_name", ["Ni56", "Fe52", "Cr48"]) +def test_isotope_dicts(gamma_ray_test_composition, nuclide_name): + """ + Function to test if the right names for the isotopes are present as dictionary keys. + Parameters + ---------- + gamma_ray_test_composition: Function holding the composition. + nuclide_name: Name of the nuclide. + """ + raw_isotopic_mass_fraction, cell_masses = gamma_ray_test_composition + isotope_dict = create_isotope_dicts(raw_isotopic_mass_fraction, cell_masses) + + for isotope_dict in isotope_dict.values(): + assert nuclide_name in isotope_dict.keys() + + +@pytest.mark.parametrize("nuclide_name", ["Ni-56", "Fe-52", "Cr-48"]) +def test_inventories_dict(gamma_ray_test_composition, nuclide_name): + """ + Function to test if the inventories dictionary is created correctly. + Parameters + ---------- + gamma_ray_test_composition: Function holding the composition. + nuclide_name: Name of the nuclide. + """ + + nuclide = rd.Nuclide(nuclide_name) + raw_isotopic_mass_fraction, cell_masses = gamma_ray_test_composition + isotope_dict = create_isotope_dicts(raw_isotopic_mass_fraction, cell_masses) + inventories_dict = create_inventories_dict(isotope_dict) + + Z, A = nuclide.Z, nuclide.A + raw_isotope_mass = raw_isotopic_mass_fraction.apply( + lambda x: x * cell_masses, axis=1 + ) + + mass = raw_isotope_mass.loc[Z, A][0] + isotope_inventory = rd.Inventory({nuclide.nuclide: mass}, "g") + + if nuclide_name in inventories_dict[0].contents: + assert ( + inventories_dict[0].contents[nuclide_name] + == isotope_inventory.contents[nuclide_name] + ) + + +@pytest.mark.parametrize("nuclide_name", ["Ni-56"]) +def test_mass_energy_conservation( + gamma_ray_test_composition, atomic_dataset, nuclide_name +): + """ + Function to test if the mass-energy conservation is satisfied. + Parameters + ---------- + gamma_ray_test_composition: Function holding the composition. + atomic_dataset: Tardis atomic-nuclear dataset + nuclide_name: Name of the nuclide.""" + + raw_isotopic_mass_fraction, cell_masses = gamma_ray_test_composition + gamma_ray_lines = atomic_dataset.decay_radiation_data + isotope_dict = create_isotope_dicts(raw_isotopic_mass_fraction, cell_masses) + inventories_dict = create_inventories_dict(isotope_dict) + total_decays = calculate_total_decays(inventories_dict, 1 * u.d) + isotope_decay_df = create_isotope_decay_df(total_decays, gamma_ray_lines) + + grouped_isotope_df = isotope_decay_df.groupby( + level=["shell_number", "isotope"] + ) + + parent_isotope_energy = ( + grouped_isotope_df.get_group((0, nuclide_name.replace("-", "")))[ + "energy_per_channel_keV" + ].sum() + * (u.keV).to(u.MeV) + * u.MeV + ) + + neutrino_energy = 0.41 * u.MeV + + total_energy_actual = parent_isotope_energy + neutrino_energy + + c2 = const.c.to("cm/s") ** 2 + + # calculate mass of 56Ni + parent_isotope = rd.Nuclide(nuclide_name.replace("-", "")) + parent_atomic_mass = parent_isotope.atomic_mass * (u.u).to(u.g) * u.g + + # calculate mass of 56Co + daughter_isotope = parent_isotope.progeny()[0] + + daughter_atomic_mass = ( + rd.Nuclide(daughter_isotope).atomic_mass * (u.u).to(u.g) * u.g + ) + + Q = (parent_atomic_mass - daughter_atomic_mass) * c2 * u.erg.to(u.MeV) + + np.testing.assert_allclose(total_energy_actual.value, Q.value, rtol=0.01) + + +@pytest.mark.parametrize("nuclide_name", ["Ni-56", "Fe-52", "Cr-48"]) +def test_activity(gamma_ray_test_composition, nuclide_name): + """ + Function to test the decay of an atom in radioactivedecay with an analytical solution. + Parameters + ---------- + gamma_ray_test_composition: Function holding the composition. + nuclide_name: Name of the nuclide. + """ + # setup of decay test + nuclide = rd.Nuclide(nuclide_name) + t_half = nuclide.half_life() * u.s + decay_constant = np.log(2) / t_half + time_delta = 1.0 * u.s + + # calculating necessary values + raw_isotopic_mass_fraction, cell_masses = gamma_ray_test_composition + isotopic_masses = raw_isotopic_mass_fraction * cell_masses + test_mass = isotopic_masses.loc[(nuclide.Z, nuclide.A), 0] * u.g + isotope_dict = create_isotope_dicts(raw_isotopic_mass_fraction, cell_masses) + inventories_dict = create_inventories_dict(isotope_dict) + + total_decays = calculate_total_decays(inventories_dict, time_delta) + actual = total_decays.loc[ + (0, nuclide_name.replace("-", "")), "number_of_decays" + ] + + isotope_mass = nuclide.atomic_mass * u.u + number_of_atoms = (test_mass / isotope_mass).to(u.dimensionless_unscaled) + expected = number_of_atoms * (1 - np.exp(-decay_constant * time_delta)) + + npt.assert_allclose(actual, expected) diff --git a/tardis/energy_input/tests/test_gamma_ray_grid.py b/tardis/energy_input/tests/test_gamma_ray_grid.py new file mode 100644 index 00000000000..11a6f394ae5 --- /dev/null +++ b/tardis/energy_input/tests/test_gamma_ray_grid.py @@ -0,0 +1,38 @@ +import pytest +import numpy.testing as npt +import numpy as np + +from tardis.energy_input.gamma_ray_grid import ( + calculate_distance_radial, + distance_trace, + move_packet, +) + + +@pytest.mark.xfail(reason="To be implemented") +def test_calculate_distance_radial(): + """Test the radial distance calculation""" + assert False + + +@pytest.mark.xfail(reason="To be implemented") +def test_distance_trace(): + """Test the distance trace""" + assert False + + +def test_move_packet(basic_gamma_ray): + """ + + Parameters + ---------- + basic_gamma_ray : GammaRay object + """ + packet = basic_gamma_ray + distance = 1.0e15 + + new = packet.location + distance * packet.direction + + actual = move_packet(packet, distance) + + npt.assert_almost_equal(actual.location, new) diff --git a/tardis/energy_input/tests/test_gamma_ray_interactions.py b/tardis/energy_input/tests/test_gamma_ray_interactions.py new file mode 100644 index 00000000000..fedc16d9619 --- /dev/null +++ b/tardis/energy_input/tests/test_gamma_ray_interactions.py @@ -0,0 +1,72 @@ +import pytest +import numpy as np +import numpy.testing as npt + +from tardis.energy_input.gamma_ray_interactions import ( + compton_scatter, + pair_creation_packet, + scatter_type, +) +from tardis.energy_input.util import ELECTRON_MASS_ENERGY_KEV, H_CGS_KEV + +from tardis.energy_input.GXPacket import GXPacketStatus + + +@pytest.mark.xfail(reason="To be implemented") +def test_get_compton_angle(): + """Test the Compton angle calculation""" + assert False + + +@pytest.mark.xfail(reason="To be implemented") +def test_compton_scatter(): + """Test Compton scattering""" + assert False + + +def test_pair_creation(basic_gamma_ray): + """ + + Parameters + ---------- + basic_gamma_ray : GammaRay object + """ + np.random.seed(2) + + initial_direction = basic_gamma_ray.direction + basic_gamma_ray.nu_cmf = 2 * ELECTRON_MASS_ENERGY_KEV / H_CGS_KEV + + pair_creation_packet(basic_gamma_ray) + + npt.assert_almost_equal( + basic_gamma_ray.nu_cmf, ELECTRON_MASS_ENERGY_KEV / H_CGS_KEV + ) + for i, j in zip(initial_direction, basic_gamma_ray.direction): + assert i != j + + +@pytest.mark.parametrize( + ["compton_opacity", "photoabsorption_opacity", "total_opacity", "expected"], + [ + (1, 0, 1, GXPacketStatus.COMPTON_SCATTER), + (0, 1, 1, GXPacketStatus.PHOTOABSORPTION), + (0, 0, 1, GXPacketStatus.PAIR_CREATION), + ], +) +def test_scatter_type( + compton_opacity, photoabsorption_opacity, total_opacity, expected +): + """Test the scattering type + + Parameters + ---------- + compton_opacity : float + photoabsorption_opacity : float + total_opacity : float + expected : list + Expected parameters + """ + actual = scatter_type( + compton_opacity, photoabsorption_opacity, total_opacity + ) + assert actual == expected diff --git a/tardis/energy_input/tests/test_gamma_ray_packet_source.py b/tardis/energy_input/tests/test_gamma_ray_packet_source.py new file mode 100644 index 00000000000..ff5fd9e8012 --- /dev/null +++ b/tardis/energy_input/tests/test_gamma_ray_packet_source.py @@ -0,0 +1,77 @@ +import numpy as np +import pytest + +from tardis.energy_input.gamma_ray_packet_source import RadioactivePacketSource + + +@pytest.mark.skip(reason="Packet source init is very complex") +class TestGammaRayPacketSource: + @pytest.fixture(scope="class") + def radioactivepacketsource(self, request): + """ + Create RadioactivePacketSource instance. + + Yields + ------- + tardis.energy_input.gamma_ray_packet_source.RadioactivePacketSource + """ + cls = type(self) + cls.packet_source = RadioactivePacketSource(base_seed=1963) + yield cls.packet_source + + def test_create_packet_radii( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.create_packet_radii() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_create_packet_nus(self, regression_data, radioactivepacketsource): + actual = self.packet_source.create_packet_nus() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_create_packet_directions( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.create_packet_directions() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_create_packet_energies( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.create_packet_energies() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_create_packet_times_uniform_time( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.create_packet_times_uniform_time() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_create_packet_times_uniform_energy( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.create_packet_times_uniform_energy() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_calculate_energy_factors( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.calculate_energy_factors() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) + + def test_create_packets(self, regression_data, radioactivepacketsource): + assert True + + def test_calculate_positron_fraction( + self, regression_data, radioactivepacketsource + ): + actual = self.packet_source.calculate_positron_fraction() + expected = regression_data.sync_ndarray(actual) + assert np.all(np.isclose(actual, expected)) diff --git a/tardis/energy_input/tests/test_gamma_ray_transport.py b/tardis/energy_input/tests/test_gamma_ray_transport.py new file mode 100644 index 00000000000..c7b05308b1f --- /dev/null +++ b/tardis/energy_input/tests/test_gamma_ray_transport.py @@ -0,0 +1,78 @@ +from pathlib import Path + +import astropy.units as u +import numpy as np +import numpy.testing as npt +import pytest +import radioactivedecay as rd +from radioactivedecay import converters + +from tardis.energy_input.gamma_ray_channel import ( + calculate_total_decays, + create_inventories_dict, + create_isotope_dicts, +) +from tardis.io.configuration import config_reader +from tardis.model import SimulationState + + +@pytest.fixture(scope="module") +def gamma_ray_config(example_configuration_dir: Path): + """ + Parameters + ---------- + example_configuration_dir: Path to the configuration directory. + + Returns + ------- + Tardis configuration + """ + yml_path = ( + example_configuration_dir + / "tardis_configv1_density_exponential_nebular_multi_isotope.yml" + ) + + return config_reader.Configuration.from_yaml(yml_path) + + +@pytest.fixture(scope="module") +def gamma_ray_simulation_state(gamma_ray_config, atomic_dataset): + """ + Parameters + ---------- + gamma_ray_config: + + Returns + ------- + Tardis model + """ + gamma_ray_config.model.structure.velocity.start = 1.0 * u.km / u.s + gamma_ray_config.model.structure.density.rho_0 = 5.0e2 * u.g / u.cm**3 + gamma_ray_config.supernova.time_explosion = 150 * u.d + + return SimulationState.from_config( + gamma_ray_config, atom_data=atomic_dataset + ) + + +@pytest.fixture(scope="module") +def gamma_ray_model_state(gamma_ray_simulation_state): + """ + Parameters + ---------- + gamma_ray_simulation_state: Tardis simulation state + + Returns + ------- + Tardis model state + """ + + raw_isotope_abundance = ( + gamma_ray_simulation_state.composition.raw_isotope_abundance + ) + composition = gamma_ray_simulation_state.composition + cell_masses = composition.calculate_cell_masses( + gamma_ray_simulation_state.geometry.volume + ) + + return raw_isotope_abundance, cell_masses diff --git a/tardis/energy_input/tests/test_util.py b/tardis/energy_input/tests/test_util.py new file mode 100644 index 00000000000..052a68efc20 --- /dev/null +++ b/tardis/energy_input/tests/test_util.py @@ -0,0 +1,104 @@ +import numpy as np +import numpy.testing as npt +import pytest + +from tardis.energy_input.util import ( + R_ELECTRON_SQUARED, + get_perpendicular_vector, + klein_nishina, + spherical_to_cartesian, +) +from tardis.opacities.opacities import ( + kappa_calculation, +) + + +@pytest.mark.parametrize( + ["r", "theta", "phi", "expected_x", "expected_y", "expected_z"], + [ + (1, 0, 0, 0, 0, 1), + (1, np.pi, 0, 0, 0, -1), + (1, np.pi / 2, 0, 1, 0, 0), + (1, np.pi / 2, np.pi, -1, 0, 0), + (1, np.pi / 2, np.pi / 2, 0, 1, 0), + ], +) +def test_spherical_to_cartesian( + r, theta, phi, expected_x, expected_y, expected_z +): + actual_x, actual_y, actual_z = spherical_to_cartesian(r, theta, phi) + npt.assert_almost_equal(actual_x, expected_x) + npt.assert_almost_equal(actual_y, expected_y) + npt.assert_almost_equal(actual_z, expected_z) + + +@pytest.mark.xfail(reason="To be removed") +def test_doppler_gamma(): + """Test the doppler shift""" + assert False + + +@pytest.mark.xfail(reason="To be removed") +def test_angle_aberration_gamma(): + """Test the angle aberration equation""" + assert False + + +@pytest.mark.xfail(reason="To be removed") +def test_euler_rodrigues(): + """Test Euler-Rodrigues rotation""" + assert False + + +@pytest.mark.xfail(reason="To be implemented") +def test_solve_quadratic_equation(): + """Test the quadratic solver""" + assert False + + +@pytest.mark.parametrize( + ["energy", "theta_C"], + [ + (511.0e3, 1.0), + (255.5e3, np.pi), + (0.0, 2.0 * np.pi), + (511.0e10, np.pi / 2.0), + ], +) +def test_klein_nishina(energy, theta_C): + """ + + Parameters + ---------- + energy : float + theta_C : float + In radians + """ + actual = klein_nishina(energy, theta_C) + + kappa = kappa_calculation(energy) + + expected = ( + R_ELECTRON_SQUARED + / 2 + * (1.0 + kappa * (1.0 - np.cos(theta_C))) ** -2.0 + * ( + 1.0 + + np.cos(theta_C) ** 2.0 + + (kappa**2.0 * (1.0 - np.cos(theta_C)) ** 2.0) + / (1.0 + kappa * (1.0 - np.cos(theta_C))) + ) + ) + + npt.assert_almost_equal(actual, expected) + + +def test_get_perpendicular_vector(): + """Test the perpendicular vector calculation""" + input_vector = np.array([0.3, 0.4, 0.5]) + + random_perpendicular_vector = get_perpendicular_vector(input_vector) + + dot_product = np.dot(input_vector, random_perpendicular_vector) + + npt.assert_almost_equal(dot_product, 0.0) diff --git a/tardis/energy_input/util.py b/tardis/energy_input/util.py new file mode 100644 index 00000000000..061017158b7 --- /dev/null +++ b/tardis/energy_input/util.py @@ -0,0 +1,390 @@ +import astropy.units as u +import numpy as np +from numba import njit + +import tardis.constants as const +from tardis.opacities.opacities import kappa_calculation +from tardis.transport.montecarlo import njit_dict_no_parallel + +R_ELECTRON_SQUARED = (const.a0.cgs.value * const.alpha.cgs.value**2.0) ** 2.0 +ELECTRON_MASS_ENERGY_KEV = (const.m_e * const.c**2.0).to("keV").value +BOUNDARY_THRESHOLD = 1e-7 +KEV2ERG = (1000 * u.eV).to("erg").value +C_CGS = const.c.cgs.value +H_CGS_KEV = const.h.to("keV s").value + + +@njit(**njit_dict_no_parallel) +def spherical_to_cartesian(r, theta, phi): + """Converts spherical coordinates to Cartesian + + Parameters + ---------- + r : float64 + Radius + theta : float64 + Theta angle in radians + phi : float64 + Phi angle in radians + + Returns + ------- + array + x, y, z coordinates + """ + x = r * np.cos(phi) * np.sin(theta) + y = r * np.sin(phi) * np.sin(theta) + z = r * np.cos(theta) + return np.array([x, y, z]) + + +@njit(**njit_dict_no_parallel) +def get_random_unit_vector(): + """Generate a random unit vector + + Returns + ------- + array: random unit vector + """ + theta = get_random_theta_photon() + phi = get_random_phi_photon() + + vector = spherical_to_cartesian(1, theta, phi) + + return normalize_vector(vector) + + +@njit(**njit_dict_no_parallel) +def doppler_factor_3d(direction_vector, position_vector, time): + """Doppler shift for photons in 3D + + Parameters + ---------- + direction_vector : array + position_vector : array + time : float + + Returns + ------- + float + Doppler factor + """ + velocity_vector = position_vector / time + return 1 - (np.dot(direction_vector, velocity_vector) / C_CGS) + + +@njit(**njit_dict_no_parallel) +def angle_aberration_gamma(direction_vector, position_vector, time): + """Angle aberration formula for photons in 3D + + Parameters + ---------- + direction_vector : array + position_vector : array + time : float + + Returns + ------- + array + New direction after aberration + """ + velocity_vector = position_vector / time + direction_dot_velocity = np.dot(direction_vector, velocity_vector) + + gamma = 1.0 / np.sqrt( + 1.0 - (np.dot(velocity_vector, velocity_vector) / (C_CGS**2.0)) + ) + + factor_a = gamma * (1.0 - direction_dot_velocity / C_CGS) + + factor_b = ( + gamma - (gamma**2.0 * direction_dot_velocity / (gamma + 1.0) / C_CGS) + ) / C_CGS + + output_vector = (direction_vector - (velocity_vector * factor_b)) / factor_a + + return output_vector + + +@njit(**njit_dict_no_parallel) +def euler_rodrigues(theta, direction): + """ + Calculates the Euler-Rodrigues rotation matrix + + Parameters + ---------- + theta : float + angle of rotation in radians + direction : One dimensional Numpy array, dtype float + x, y, z direction vector + + Returns + ------- + rotation matrix : Two dimensional Numpy array, dtype float + + """ + a = np.cos(theta / 2) + b = direction[0] * np.sin(theta / 2) + c = direction[1] * np.sin(theta / 2) + d = direction[2] * np.sin(theta / 2) + + er11 = a**2.0 + b**2.0 - c**2.0 - d**2.0 + er12 = 2.0 * (b * c - a * d) + er13 = 2.0 * (b * d + a * c) + + er21 = 2.0 * (b * c + a * d) + er22 = a**2.0 + c**2.0 - b**2.0 - d**2.0 + er23 = 2.0 * (c * d - a * b) + + er31 = 2.0 * (b * d - a * c) + er32 = 2.0 * (c * d + a * b) + er33 = a**2.0 + d**2.0 - b**2.0 - c**2.0 + + return np.array( + [[er11, er12, er13], [er21, er22, er23], [er31, er32, er33]] + ) + + +@njit(**njit_dict_no_parallel) +def solve_quadratic_equation(position, direction, radius): + """ + Solves the quadratic equation for the distance to the shell boundary + + Parameters + ---------- + position : array + direction : array + radius : float + + Returns + ------- + solution_1 : float + solution_2 : float + + """ + a = np.sum(direction**2) + b = 2.0 * np.sum(position * direction) + c = -(radius**2) + np.sum(position**2) + root = b**2 - 4 * a * c + solution_1 = -np.inf + solution_2 = -np.inf + if root > 0.0: + solution_1 = (-b + np.sqrt(root)) / (2 * a) + solution_2 = (-b - np.sqrt(root)) / (2 * a) + elif root == 0: + solution_1 = -b / (2 * a) + + return solution_1, solution_2 + + +@njit(**njit_dict_no_parallel) +def solve_quadratic_equation_expanding(position, direction, time, radius): + """ + Solves the quadratic equation for the distance to an expanding shell boundary + + Parameters + ---------- + position : array + direction : array + time : float + radius : float + + Returns + ------- + solution_1 : float + solution_2 : float + + """ + light_distance = time * C_CGS + a = np.dot(direction, direction) - (radius / light_distance) ** 2.0 + b = 2.0 * (np.dot(position, direction) - radius**2.0 / light_distance) + c = np.dot(position, position) - radius**2.0 + root = b**2.0 - 4.0 * a * c + solution_1 = -np.inf + solution_2 = -np.inf + if root > 0.0: + solution_1 = (-b + np.sqrt(root)) / (2.0 * a) + solution_2 = (-b - np.sqrt(root)) / (2.0 * a) + elif root == 0: + solution_1 = -b / (2.0 * a) + + return solution_1, solution_2 + + +@njit(**njit_dict_no_parallel) +def klein_nishina(energy, theta_C): + """ + Calculates the Klein-Nishina equation + + https://en.wikipedia.org/wiki/Klein%E2%80%93Nishina_formula + + .. math:: + \frac{r_e}{2} [1 + \\kappa (1 - \\cos\theta_C)]^{-2} \\left( 1 + \\cos^2\theta_C + \frac{\\kappa^2 (1 - \\cos\theta_C)^2}{1 + \\kappa(1 - \\cos\theta_C)}\right) + + where :math:`\\kappa = E / (m_e c^2)` + + Parameters + ---------- + energy : float + Packet energy + theta_C : float + Compton angle + + Returns + ------- + float + Klein-Nishina solution + """ + kappa = kappa_calculation(energy) + return ( + R_ELECTRON_SQUARED + / 2 + * (1.0 + kappa * (1.0 - np.cos(theta_C))) ** -2.0 + * ( + 1.0 + + np.cos(theta_C) ** 2.0 + + (kappa**2.0 * (1.0 - np.cos(theta_C)) ** 2.0) + / (1.0 + kappa * (1.0 - np.cos(theta_C))) + ) + ) + + +@njit(**njit_dict_no_parallel) +def compton_theta_distribution(energy, sample_resolution=100): + """ + Calculates the cumulative distribution function of theta angles + for Compton Scattering + + Parameters + ---------- + energy : float + sample_resolution : int + + Returns + ------- + theta_angles : One dimensional Numpy array, dtype float + norm_theta_distribution : One dimensional Numpy array, dtype float + + """ + theta_angles = np.linspace(0, np.pi, sample_resolution) + + theta_distribution = np.cumsum(klein_nishina(energy, theta_angles)) + norm_theta_distribution = theta_distribution / np.max(theta_distribution) + + return theta_angles, norm_theta_distribution + + +@njit(**njit_dict_no_parallel) +def get_random_theta_photon(): + """Get a random theta direction between 0 and pi + + Returns + ------- + float + Random theta direction + """ + return np.arccos(1.0 - 2.0 * np.random.random()) + + +@njit(**njit_dict_no_parallel) +def get_random_phi_photon(): + """Get a random phi direction between 0 and 2 * pi + + Returns + ------- + float + Random phi direction + """ + return 2.0 * np.pi * np.random.random() + + +def convert_half_life_to_astropy_units(half_life_string): + """Converts input half-life to use astropy units + + Parameters + ---------- + half_life_string : str + Half-life as a string + + Returns + ------- + astropy Quantity + Half-life in seconds + """ + value, unit = half_life_string.split(" ") + try: + nominal_value, magnitude = value.split("×") + base, exponent = magnitude.split("+") + nominal_value = float(nominal_value) * float(base) ** float(exponent) + except ValueError: + nominal_value = float(value) + if unit == "y": + unit = "yr" + half_life_with_unit = nominal_value * u.Unit(unit) + return half_life_with_unit.to(u.s) + + +@njit(**njit_dict_no_parallel) +def normalize_vector(vector): + """ + Normalizes a vector in Cartesian coordinates + + Parameters + ---------- + vector : One-dimensional Numpy Array, dtype float + Input vector + + Returns + ------- + One-dimensional Numpy Array, dtype float + Normalized vector + """ + return vector / np.linalg.norm(vector) + + +@njit(**njit_dict_no_parallel) +def get_perpendicular_vector(original_direction): + """ + Computes a random vector which is perpendicular to the input vector + + Parameters + ---------- + original_direction : array + + Returns + ------- + numpy.ndarray + Perpendicular vector to the input + """ + random_vector = get_random_unit_vector() + perpendicular_vector = np.cross(original_direction, random_vector) + return normalize_vector(perpendicular_vector) + + +@njit(**njit_dict_no_parallel) +def get_index(value, array): + """Get the index that places a value + at array[i] < array <= vec[i+1] + + Parameters + ---------- + value : float + Value to locate + array : array + Array to search + + Returns + ------- + int + Index + """ + if value <= array[0]: + return 0 + elif value > array[-1]: + return len(array) - 1 + + i = 0 + while value > array[i + 1]: + i += 1 + + return i diff --git a/tardis/grid/__init__.py b/tardis/grid/__init__.py index eb8bb8410b2..1b5b3213ca9 100644 --- a/tardis/grid/__init__.py +++ b/tardis/grid/__init__.py @@ -1 +1,7 @@ +""" +Storing a grid of TARDIS parameters that +facilitates running large numbers of +simulations easily. +""" + from tardis.grid.base import * diff --git a/tardis/grid/base.py b/tardis/grid/base.py index 28ac97bf864..d0090ab493e 100644 --- a/tardis/grid/base.py +++ b/tardis/grid/base.py @@ -3,8 +3,9 @@ import copy import tardis -from tardis.io.config_reader import Configuration -from tardis.model import Radial1DModel +from tardis.io.configuration.config_reader import Configuration +from tardis.io.atom_data import AtomData +from tardis.model import SimulationState def _set_tardis_config_property(tardis_config, key, value): @@ -93,9 +94,9 @@ def grid_row_to_config(self, row_index): _set_tardis_config_property(tmp_config, colname, value) return tmp_config - def grid_row_to_model(self, row_index): + def grid_row_to_simulation_state(self, row_index, atomic_data): """ - Generates a TARDIS Radial1DModel object using the base + Generates a TARDIS SimulationState object using the base self.config modified by the specified grid row. Parameters @@ -105,11 +106,13 @@ def grid_row_to_model(self, row_index): Returns ------- - model : tardis.model.base.Radial1DModel + model : tardis.model.base.SimulationState """ rowconfig = self.grid_row_to_config(row_index) - model = Radial1DModel.from_config(rowconfig) - return model + simulation_state = SimulationState.from_config( + rowconfig, atom_data=atomic_data + ) + return simulation_state def run_sim_from_grid(self, row_index, **tardiskwargs): """ diff --git a/tardis/grid/tests/test_grid.py b/tardis/grid/tests/test_grid.py index 5676c6782fb..4a793c7e9a4 100644 --- a/tardis/grid/tests/test_grid.py +++ b/tardis/grid/tests/test_grid.py @@ -1,25 +1,28 @@ -import pandas as pd +from pathlib import Path + import numpy as np +import pandas as pd + import tardis -import os -import pytest + +from pathlib import Path import tardis.grid as grid -DATA_PATH = os.path.join(tardis.__path__[0], "grid", "tests", "data") +DATA_PATH = Path(tardis.__path__[0]) / "grid" / "tests" / "data" -def test_grid(): +def test_grid(atomic_dataset): """Tests the basic functionality of the TARDIS grid module.""" - dfpath = os.path.join(DATA_PATH, "example_grid.txt") - ymlpath = os.path.join(DATA_PATH, "example.yml") + dfpath = DATA_PATH / "example_grid.txt" + ymlpath = DATA_PATH / "example.yml" axesdict = { "model.structure.velocity.start": np.arange(10000, 15000, 1000), "model.abundances.He": np.arange(0, 1, 0.1), "model.abundances.H": np.arange(0, 1, 0.25), } - df = pd.read_csv(os.path.join(dfpath)) + df = pd.read_csv(dfpath) g = grid.tardisGrid(configFile=ymlpath, gridFrame=df) g2 = grid.tardisGrid.from_axes(configFile=ymlpath, axesdict=axesdict) @@ -35,8 +38,10 @@ def test_grid(): assert g.config != newconf # Verify that a model can be returned. - model = g.grid_row_to_model(row_index=0) + simulation_state = g.grid_row_to_simulation_state( + row_index=0, atomic_data=atomic_dataset + ) assert ( - model.velocity[0].to("km/s").value + simulation_state.velocity[0].to("km/s").value == df.iloc[0]["model.structure.velocity.start"] ) diff --git a/tardis/gui/__init__.py b/tardis/gui/__init__.py new file mode 100644 index 00000000000..a22e23fccfd --- /dev/null +++ b/tardis/gui/__init__.py @@ -0,0 +1,9 @@ +""" +Creation of the basic framework for the TARDIS GUI. + +The data that should be displayed in the GUI is put into +respective data structures (either a tree or a table), such +that they can be used in the widgets. These widgets are +used to form the building blocks of the basic framework for +the GUI. +""" diff --git a/tardis/gui/tests/test_gui.py b/tardis/gui/tests/test_gui.py index d5a7de98e0d..2cc05187376 100644 --- a/tardis/gui/tests/test_gui.py +++ b/tardis/gui/tests/test_gui.py @@ -1,23 +1,15 @@ -from PyQt5 import QtWidgets import os import pytest -from tardis.io.config_reader import Configuration +from tardis.io.configuration.config_reader import Configuration from tardis.simulation import Simulation import astropy.units as u if "QT_API" in os.environ: + from PyQt5 import QtWidgets from tardis.gui.widgets import Tardis from tardis.gui.datahandler import SimpleTableModel -@pytest.fixture(scope="module") -def refdata(tardis_ref_data): - def get_ref_data(key): - return tardis_ref_data[os.path.join("test_simulation", key)] - - return get_ref_data - - @pytest.fixture(scope="module") def config(): return Configuration.from_yaml( @@ -35,7 +27,8 @@ def simulation_one_loop( config.montecarlo.last_no_of_packets = int(4e4) simulation = Simulation.from_config(config) - simulation.run() + simulation.run_convergence() + simulation.run_final() return simulation diff --git a/tardis/gui/widgets.py b/tardis/gui/widgets.py index 5608a42065d..f79075dfea5 100644 --- a/tardis/gui/widgets.py +++ b/tardis/gui/widgets.py @@ -162,8 +162,8 @@ def shell_picker(self, shell, mouseevent): """Enable picking shells in the shell plot.""" if mouseevent.xdata is None: return False, dict() - mouse_r2 = mouseevent.xdata ** 2 + mouseevent.ydata ** 2 - if shell.r_inner ** 2 < mouse_r2 < shell.r_outer ** 2: + mouse_r2 = mouseevent.xdata**2 + mouseevent.ydata**2 + if shell.r_inner**2 < mouse_r2 < shell.r_outer**2: return True, dict() return False, dict() @@ -310,8 +310,6 @@ def __init__(self, yamlconfigfile, parent=None): }, "last_no_of_packets": [False, -1], "no_of_virtual_packets": [False, 0], - "enable_reflective_inner_boundary": [False, False], - "inner_boundary_albedo": [False, 0.0], "convergence_strategy": { "type": [ True, @@ -406,7 +404,6 @@ def match_dicts(self, dict1, dict2): # dict1<=dict2 elif isinstance(dict2[key], list): if isinstance(dict2[key][1], list): - # options = dict2[key][1] #This is passed by reference. # So copy the list manually. options = [ @@ -539,9 +536,9 @@ def fill_output_label(self): ) labeltext = f"Iterations requested: {self.model.iterations} <br/> Iterations executed: {self.model.iterations_executed}<br/>\ - Model converged : {model_converged} <br/> Simulation Time : {self.model.runner.time_of_simulation.value} s <br/>\ + Model converged : {model_converged} <br/> Simulation Time : {self.model.transport.time_of_simulation.value} s <br/>\ Inner Temperature : {self.model.model.t_inner.value} K <br/> Number of packets : {self.model.last_no_of_packets}<br/>\ - Inner Luminosity : {self.model.runner.calculate_luminosity_inner(self.model.model)}" + Inner Luminosity : {self.model.transport.calculate_luminosity_inner(self.model.model)}" self.outputLabel.setText(labeltext) @@ -642,13 +639,16 @@ def change_model(self, model): def change_spectrum_to_spec_virtual_flux_angstrom(self): """Change the spectrum data to the virtual spectrum.""" - if self.model.runner.spectrum_virtual.luminosity_density_lambda is None: + if ( + self.model.transport.spectrum_virtual.luminosity_density_lambda + is None + ): luminosity_density_lambda = np.zeros_like( - self.model.runner.spectrum_virtual.wavelength + self.model.transport.spectrum_virtual.wavelength ) else: luminosity_density_lambda = ( - self.model.runner.spectrum_virtual.luminosity_density_lambda.value + self.model.transport.spectrum_virtual.luminosity_density_lambda.value ) self.change_spectrum(luminosity_density_lambda, "spec_flux_angstrom") @@ -656,13 +656,13 @@ def change_spectrum_to_spec_virtual_flux_angstrom(self): def change_spectrum_to_spec_flux_angstrom(self): """Change spectrum data back from virtual spectrum. (See the method above).""" - if self.model.runner.spectrum.luminosity_density_lambda is None: + if self.model.transport.spectrum.luminosity_density_lambda is None: luminosity_density_lambda = np.zeros_like( - self.model.runner.spectrum.wavelength + self.model.transport.spectrum.wavelength ) else: luminosity_density_lambda = ( - self.model.runner.spectrum.luminosity_density_lambda.value + self.model.transport.spectrum.luminosity_density_lambda.value ) self.change_spectrum(luminosity_density_lambda, "spec_flux_angstrom") @@ -683,12 +683,12 @@ def plot_spectrum(self): self.spectrum.ax.set_title("Spectrum") self.spectrum.ax.set_xlabel("Wavelength (A)") self.spectrum.ax.set_ylabel("Intensity") - wavelength = self.model.runner.spectrum.wavelength.value - if self.model.runner.spectrum.luminosity_density_lambda is None: + wavelength = self.model.transport.spectrum.wavelength.value + if self.model.transport.spectrum.luminosity_density_lambda is None: luminosity_density_lambda = np.zeros_like(wavelength) else: luminosity_density_lambda = ( - self.model.runner.spectrum.luminosity_density_lambda.value + self.model.transport.spectrum.luminosity_density_lambda.value ) self.spectrum.dataplot = self.spectrum.ax.plot( @@ -934,8 +934,8 @@ def __init__(self, parent, wavelength_start, wavelength_end, tablecreator): f"Line Interaction: {wavelength_start:.2f} - {wavelength_end:.2f} (A) " ) self.layout = QtWidgets.QVBoxLayout() - packet_nu_line_interaction = analysis.LastLineInteraction.from_model( - self.parent.model + packet_nu_line_interaction = ( + analysis.LastLineInteraction.from_simulation(self.parent.model) ) packet_nu_line_interaction.packet_filter_mode = "packet_nu" packet_nu_line_interaction.wavelength_start = ( @@ -943,8 +943,8 @@ def __init__(self, parent, wavelength_start, wavelength_end, tablecreator): ) packet_nu_line_interaction.wavelength_end = wavelength_end * u.angstrom - line_in_nu_line_interaction = analysis.LastLineInteraction.from_model( - self.parent.model + line_in_nu_line_interaction = ( + analysis.LastLineInteraction.from_simulation(self.parent.model) ) line_in_nu_line_interaction.packet_filter_mode = "line_in_nu" line_in_nu_line_interaction.wavelength_start = ( diff --git a/tardis/io/__init__.py b/tardis/io/__init__.py index ca4d671e64b..e4e678f32e4 100644 --- a/tardis/io/__init__.py +++ b/tardis/io/__init__.py @@ -1,8 +1,18 @@ +""" +A collection of subpackages and submodules to handle input and output data. +""" + +from tardis.io.configuration.config_internal import ( + get_internal_configuration, + get_data_dir, +) + # readin model_data -from tardis.io.model_reader import ( - read_simple_ascii_density, + +from tardis.io.model.readers.generic_readers import ( read_simple_ascii_abundances, - read_density_file, ) - -from tardis.io.config_internal import get_internal_configuration, get_data_dir +from tardis.io.model.readers.generic_readers import ( + read_simple_ascii_density, +) +from tardis.io.model.readers.base import read_density_file diff --git a/tardis/io/atom_data/__init__.py b/tardis/io/atom_data/__init__.py index 5fd5f11b1ce..39d2bbdfef1 100644 --- a/tardis/io/atom_data/__init__.py +++ b/tardis/io/atom_data/__init__.py @@ -1,2 +1,6 @@ +""" +Getting and handling the atomic data. +""" + from tardis.io.atom_data.base import AtomData from tardis.io.atom_data.atom_web_download import download_atom_data diff --git a/tardis/io/atom_data/atom_web_download.py b/tardis/io/atom_data/atom_web_download.py index 45bcd0731ba..a652f8efdf5 100644 --- a/tardis/io/atom_data/atom_web_download.py +++ b/tardis/io/atom_data/atom_web_download.py @@ -1,10 +1,10 @@ -import os import logging -from tardis.io.util import get_internal_data_path, download_from_url -from tardis.io.config_internal import get_data_dir import yaml +from tardis.io.configuration.config_internal import get_data_dir +from tardis.io.util import download_from_url, get_internal_data_path + logger = logging.getLogger(__name__) @@ -16,12 +16,11 @@ def get_atomic_repo_config(): ------- : dict """ - atomic_repo_fname = get_internal_data_path("atomic_data_repo.yml") return yaml.load(open(atomic_repo_fname), Loader=yaml.CLoader) -def download_atom_data(atomic_data_name=None): +def download_atom_data(atomic_data_name=None, force_download=False): """ Download the atomic data from the repository @@ -30,6 +29,9 @@ def download_atom_data(atomic_data_name=None): atomic_data_name : str if None + force_download : bool + if True, force download even if file exists + Returns ------- : None @@ -41,7 +43,17 @@ def download_atom_data(atomic_data_name=None): if atomic_data_name not in atomic_repo: raise ValueError(f"Atomic Data name {atomic_data_name} not known") - dst_dir = os.path.join(get_data_dir(), f"{atomic_data_name}.h5") + + dst_fname = get_data_dir() / f"{atomic_data_name}.h5" + + if dst_fname.exists() and not force_download: + logger.warning( + f"Atomic Data {atomic_data_name} already exists in {dst_fname}. Will not download - override with force_download=True." + ) + return src_url = atomic_repo[atomic_data_name]["url"] - logger.info(f"Downloading atomic data from {src_url} to {dst_dir}") - download_from_url(src_url, dst_dir) + mirrors = tuple(atomic_repo[atomic_data_name]["mirrors"]) + checksum = atomic_repo[atomic_data_name]["md5"] + + logger.info(f"Downloading atomic data from {src_url} to {dst_fname}") + download_from_url(src_url, dst_fname, checksum, mirrors) diff --git a/tardis/io/atom_data/base.py b/tardis/io/atom_data/base.py index 86c41bf0027..90628b0ec72 100644 --- a/tardis/io/atom_data/base.py +++ b/tardis/io/atom_data/base.py @@ -1,16 +1,17 @@ -# atomic model - - import logging +from collections import OrderedDict + import numpy as np import pandas as pd - -from scipy import interpolate -from collections import OrderedDict from astropy import units as u -from tardis import constants as const from astropy.units import Quantity +from scipy import interpolate + +from tardis import constants as const from tardis.io.atom_data.util import resolve_atom_data_fname +from tardis.plasma.properties.continuum_processes import ( + get_ground_state_multi_index, +) class AtomDataNotPreparedError(Exception): @@ -24,7 +25,7 @@ class AtomDataMissingError(Exception): logger = logging.getLogger(__name__) -class AtomData(object): +class AtomData: """ Class for storing atomic data @@ -93,6 +94,12 @@ class AtomData(object): index: atomic_number, ion_number, level_number_lower, level_number_upper columns: A_ul[1/s], nu0[Hz], alpha, beta, gamma + decay_radiation_data : pandas.DataFrame + A dataframe containing the *decay radiation data* with: + index: Isotope names + columns: atomic_number, element, Rad energy, Rad intensity decay mode. + Curated from nndc + Attributes ---------- prepared : bool @@ -108,6 +115,7 @@ class AtomData(object): atomic_number2symbol : OrderedDict photoionization_data : pandas.DataFrame two_photon_data : pandas.DataFrame + decay_radiation_data : pandas.DataFrame Methods ------- @@ -138,6 +146,8 @@ class AtomData(object): "photoionization_data", "yg_data", "two_photon_data", + "linelist", + "decay_radiation_data", ] # List of tuples of the related dataframes. @@ -154,11 +164,10 @@ def from_hdf(cls, fname=None): Parameters ---------- - fname : str, optional + fname : Path, optional Path to the HDFStore file or name of known atom data file (default: None) """ - dataframes = dict() nonavailable = list() @@ -167,15 +176,59 @@ def from_hdf(cls, fname=None): with pd.HDFStore(fname, "r") as store: for name in cls.hdf_names: try: - dataframes[name] = store[name] + dataframes[name] = store.select(name) except KeyError: - logger.debug("Dataframe does not contain NAME column") + logger.debug(f"Dataframe does not contain {name} column") nonavailable.append(name) + if "metadata" in store: + carsus_version_str = ( + store["metadata"].loc[("format", "version")].value + ) + carsus_version = tuple(map(int, carsus_version_str.split("."))) + if carsus_version == (1, 0): + # Checks for various collisional data from Carsus files + if "collisions_data" in store: + try: + dataframes["collision_data_temperatures"] = store[ + "collisions_metadata" + ].temperatures + if "cmfgen" in store["collisions_metadata"].dataset: + dataframes["yg_data"] = store["collisions_data"] + dataframes["collision_data"] = "dummy value" + elif ( + "chianti" + in store["collisions_metadata"].dataset + ): + dataframes["collision_data"] = store[ + "collisions_data" + ] + else: + raise KeyError( + "Atomic Data Collisions Not a Valid Chanti or CMFGEN Carsus Data File" + ) + except KeyError as e: + logger.warning( + "Atomic Data is not a Valid Carsus Atomic Data File" + ) + raise + dataframes["levels"] = store["levels_data"] + dataframes["lines"] = store["lines_data"] + else: + raise ValueError( + f"Current carsus version, {carsus_version}, is not supported." + ) + if "linelist" in store: + dataframes["linelist"] = store["linelist"] + atom_data = cls(**dataframes) try: - atom_data.uuid1 = store.root._v_attrs["uuid1"].decode("ascii") + atom_data.uuid1 = store.root._v_attrs["uuid1"] + if hasattr(atom_data.uuid1, "decode"): + atom_data.uuid1 = store.root._v_attrs["uuid1"].decode( + "ascii" + ) except KeyError: logger.debug( "UUID not available for Atom Data. Setting value to None" @@ -183,7 +236,9 @@ def from_hdf(cls, fname=None): atom_data.uuid1 = None try: - atom_data.md5 = store.root._v_attrs["md5"].decode("ascii") + atom_data.md5 = store.root._v_attrs["md5"] + if hasattr(atom_data.md5, "decode"): + atom_data.md5 = store.root._v_attrs["md5"].decode("ascii") except KeyError: logger.debug( "MD5 not available for Atom Data. Setting value to None" @@ -198,7 +253,7 @@ def from_hdf(cls, fname=None): ) atom_data.version = None - # ToDo: strore data sources as attributes in carsus + # TODO: strore data sources as attributes in carsus logger.info( f"Reading Atom Data with: UUID = {atom_data.uuid1} MD5 = {atom_data.md5} " @@ -227,8 +282,9 @@ def __init__( photoionization_data=None, yg_data=None, two_photon_data=None, + linelist=None, + decay_radiation_data=None, ): - self.prepared = False # CONVERT VALUES TO CGS UNITS @@ -241,25 +297,33 @@ def __init__( if u.u.cgs == const.u.cgs: atom_data.loc[:, "mass"] = Quantity( atom_data["mass"].values, "u" - ).cgs + ).cgs.value else: - atom_data.loc[:, "mass"] = atom_data["mass"].values * const.u.cgs + atom_data.loc[:, "mass"] = ( + atom_data["mass"].values * const.u.cgs.value + ) # Convert ionization energies to CGS ionization_data = ionization_data.squeeze() - ionization_data[:] = Quantity(ionization_data[:], "eV").cgs + ionization_data[:] = Quantity(ionization_data[:], "eV").cgs.value # Convert energy to CGS - levels.loc[:, "energy"] = Quantity(levels["energy"].values, "eV").cgs + levels.loc[:, "energy"] = Quantity( + levels["energy"].values, "eV" + ).cgs.value # Create a new columns with wavelengths in the CGS units - lines["wavelength_cm"] = Quantity(lines["wavelength"], "angstrom").cgs + lines["wavelength_cm"] = Quantity( + lines["wavelength"], "angstrom" + ).cgs.value # SET ATTRIBUTES self.atom_data = atom_data self.ionization_data = ionization_data self.levels = levels + # Not sure why this is need - WEK 17 Sep 2023 + self.levels.energy = self.levels.energy.astype(np.float64) self.lines = lines # Rename these (drop "_all") when `prepare_atom_data` is removed! @@ -279,6 +343,11 @@ def __init__( self.two_photon_data = two_photon_data + if linelist is not None: + self.linelist = linelist + + if decay_radiation_data is not None: + self.decay_radiation_data = decay_radiation_data self._check_related() self.symbol2atomic_number = OrderedDict( @@ -304,8 +373,9 @@ def _check_related(self): def prepare_atom_data( self, selected_atomic_numbers, - line_interaction_type="scatter", - nlte_species=[], + line_interaction_type, + nlte_species, + continuum_interaction_species, ): """ Prepares the atom data to set the lines, levels and if requested macro @@ -330,12 +400,6 @@ def prepare_atom_data( self.nlte_species = nlte_species - self.levels = self.levels[ - self.levels.index.isin( - self.selected_atomic_numbers, level="atomic_number" - ) - ] - self.levels_index = pd.Series( np.arange(len(self.levels), dtype=int), index=self.levels.index ) @@ -374,11 +438,88 @@ def prepare_atom_data( .values ) + self.prepare_macro_atom_data( + line_interaction_type, + tmp_lines_lower2level_idx, + tmp_lines_upper2level_idx, + ) + if len(continuum_interaction_species) > 0: + self.prepare_continuum_interaction_data( + continuum_interaction_species + ) + + self.nlte_data = NLTEData(self, nlte_species) + + def prepare_continuum_interaction_data(self, continuum_interaction_species): + """ + Prepares the atom data for the continuum interaction + + Parameters + ---------- + continuum_interaction : ContinuumInteraction + The continuum interaction object + """ + # photoionization_data = atomic_data.photoionization_data.set_index( + # ["atomic_number", "ion_number", "level_number"] + # ) + mask_selected_species = self.photoionization_data.index.droplevel( + "level_number" + ).isin(continuum_interaction_species) + self.photoionization_data = self.photoionization_data[ + mask_selected_species + ] + self.photo_ion_block_references = np.pad( + self.photoionization_data.nu.groupby(level=[0, 1, 2]) + .count() + .values.cumsum(), + [1, 0], + ) + self.photo_ion_unique_index = self.photoionization_data.index.unique() + self.nu_ion_threshold = ( + self.photoionization_data.groupby(level=[0, 1, 2]).first().nu + ) + self.energy_photo_ion_lower_level = self.levels.loc[ + self.photo_ion_unique_index + ].energy + + source_idx = self.macro_atom_references.loc[ + self.photo_ion_unique_index + ].references_idx + destination_idx = self.macro_atom_references.loc[ + get_ground_state_multi_index(self.photo_ion_unique_index) + ].references_idx + self.photo_ion_levels_idx = pd.DataFrame( + { + "source_level_idx": source_idx.values, + "destination_level_idx": destination_idx.values, + }, + index=self.photo_ion_unique_index, + ) + + self.level2continuum_edge_idx = pd.Series( + np.arange(len(self.nu_ion_threshold)), + self.nu_ion_threshold.sort_values(ascending=False).index, + name="continuum_idx", + ) + + level_idxs2continuum_idx = self.photo_ion_levels_idx.copy() + level_idxs2continuum_idx[ + "continuum_idx" + ] = self.level2continuum_edge_idx + self.level_idxs2continuum_idx = level_idxs2continuum_idx.set_index( + ["source_level_idx", "destination_level_idx"] + ) + + def prepare_macro_atom_data( + self, + line_interaction_type, + tmp_lines_lower2level_idx, + tmp_lines_upper2level_idx, + ): if ( self.macro_atom_data_all is not None and not line_interaction_type == "scatter" ): - self.macro_atom_data = self.macro_atom_data_all.loc[ self.macro_atom_data_all["atomic_number"].isin( self.selected_atomic_numbers @@ -443,6 +584,13 @@ def prepare_atom_data( ) if line_interaction_type == "macroatom": + self.lines_lower2macro_reference_idx = ( + self.macro_atom_references.loc[ + tmp_lines_lower2level_idx, "references_idx" + ] + .astype(np.int64) + .values + ) # Sets all tmp_macro_destination_level_idx = pd.MultiIndex.from_arrays( [ @@ -482,9 +630,9 @@ def prepare_atom_data( self.macro_atom_data.loc[:, "destination_level_idx"] = -1 if self.yg_data is not None: - self.yg_data = self.yg_data.loc[self.selected_atomic_numbers] - - self.nlte_data = NLTEData(self, nlte_species) + self.yg_data = self.yg_data.reindex( + self.selected_atomic_numbers, level=0 + ) def _check_selected_atomic_numbers(self): selected_atomic_numbers = self.selected_atomic_numbers @@ -507,7 +655,7 @@ def __repr__(self): return f"<Atomic Data UUID={self.uuid1} MD5={self.md5} Lines={self.lines.line_id.count():d} Levels={self.levels.energy.count():d}>" -class NLTEData(object): +class NLTEData: def __init__(self, atom_data, nlte_species): self.atom_data = atom_data self.lines = atom_data.lines.reset_index() diff --git a/tardis/io/atom_data/util.py b/tardis/io/atom_data/util.py index dd0b03fb26d..ce4b2765bce 100644 --- a/tardis/io/atom_data/util.py +++ b/tardis/io/atom_data/util.py @@ -1,7 +1,8 @@ import os import logging +from pathlib import Path -from tardis.io.config_internal import get_data_dir +from tardis.io.configuration.config_internal import get_data_dir from tardis.io.atom_data.atom_web_download import ( get_atomic_repo_config, download_atom_data, @@ -16,26 +17,28 @@ def resolve_atom_data_fname(fname): Parameters ---------- - fname : str + fname : Path name or path of atom data HDF file Returns ------- - : str + : Path resolved fpath """ + fname = Path(fname) if os.path.exists(fname): return fname - fpath = os.path.join(os.path.join(get_data_dir(), fname)) + fname = Path(fname.stem).with_suffix(".h5") + fpath = Path(os.path.join(get_data_dir(), fname)) if os.path.exists(fpath): logger.info( - f"Atom Data {fname} not found in local path.\n\tExists in TARDIS Data repo {fpath}" + f"\n\tAtom Data {fname} not found in local path.\n\tExists in TARDIS Data repo {fpath}" ) return fpath - atom_data_name = fname.replace(".h5", "") + atom_data_name = fname.stem atom_repo_config = get_atomic_repo_config() if atom_data_name in atom_repo_config: raise IOError( diff --git a/tardis/io/configuration/__init__.py b/tardis/io/configuration/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/io/config_internal.py b/tardis/io/configuration/config_internal.py similarity index 73% rename from tardis/io/config_internal.py rename to tardis/io/configuration/config_internal.py index 197b2a3af16..5c622be66ae 100644 --- a/tardis/io/config_internal.py +++ b/tardis/io/configuration/config_internal.py @@ -1,22 +1,23 @@ -from tardis import __path__ as TARDIS_PATH -import os, logging, shutil +import logging, shutil import yaml +import os +from pathlib import Path +from tardis import __path__ as TARDIS_PATH from astropy.config import get_config_dir -TARDIS_PATH = TARDIS_PATH[0] -DEFAULT_CONFIG_PATH = os.path.join( - TARDIS_PATH, "data", "default_tardis_internal_config.yml" -) -DEFAULT_DATA_DIR = os.path.join( - os.path.expanduser("~"), "Downloads", "tardis-data" +TARDIS_PATH = Path(TARDIS_PATH[0]) +DEFAULT_CONFIG_PATH = ( + TARDIS_PATH / "data" / "default_tardis_internal_config.yml" ) + +DEFAULT_DATA_DIR = Path(os.path.expanduser("~")) / "Downloads" / "tardis-data" + logger = logging.getLogger(__name__) def get_internal_configuration(): - - config_fpath = os.path.join(get_config_dir(), "tardis_internal_config.yml") + config_fpath = Path(get_config_dir()) / "tardis_internal_config.yml" if not os.path.exists(config_fpath): logger.warning( f"Configuration File {config_fpath} does not exist - creating new one from default" @@ -27,13 +28,10 @@ def get_internal_configuration(): def get_data_dir(): - config = get_internal_configuration() data_dir = config.get("data_dir", None) if data_dir is None: - config_fpath = os.path.join( - get_config_dir(), "tardis_internal_config.yml" - ) + config_fpath = Path(get_config_dir()) / "tardis_internal_config.yml" logging.critical( f"\n{'*' * 80}\n\nTARDIS will download different kinds of data (e.g. atomic) to its data directory {DEFAULT_DATA_DIR}\n\n" f"TARDIS DATA DIRECTORY not specified in {config_fpath}:\n\n" @@ -41,7 +39,7 @@ def get_data_dir(): f"YOU CAN CHANGE THIS AT ANY TIME IN {config_fpath} \n\n" f"{'*' * 80} \n\n" ) - if not os.path.exists(DEFAULT_DATA_DIR): + if not DEFAULT_DATA_DIR.exists(): os.makedirs(DEFAULT_DATA_DIR) config["data_dir"] = DEFAULT_DATA_DIR yaml.dump(config, open(config_fpath, "w"), default_flow_style=False) @@ -50,4 +48,4 @@ def get_data_dir(): if not os.path.exists(data_dir): raise IOError(f"Data directory specified in {data_dir} does not exist") - return data_dir + return Path(data_dir) diff --git a/tardis/io/config_reader.py b/tardis/io/configuration/config_reader.py similarity index 64% rename from tardis/io/config_reader.py rename to tardis/io/configuration/config_reader.py index 4a53d75a89b..bc67fe0324f 100644 --- a/tardis/io/config_reader.py +++ b/tardis/io/configuration/config_reader.py @@ -1,55 +1,25 @@ -import os -import logging import copy +import logging +import os import pprint -import yaml + import pandas as pd +import yaml from astropy import units as u -import tardis -from tardis.io import config_validator -from tardis.io.util import YAMLLoader, yaml_load_file, HDFWriterMixin -from tardis.io.parsers.csvy import load_yaml_from_csvy +from tardis.io.configuration import config_validator +from tardis.io.model.readers.csvy import load_yaml_from_csvy +from tardis.io.util import HDFWriterMixin, YAMLLoader, yaml_load_file pp = pprint.PrettyPrinter(indent=4) logger = logging.getLogger(__name__) -data_dir = os.path.abspath(os.path.join(tardis.__path__[0], "data")) - class ConfigurationError(ValueError): pass -def parse_convergence_section(convergence_section_dict): - """ - Parse the convergence section dictionary - - Parameters - ---------- - convergence_section_dict : dict - dictionary - """ - - convergence_parameters = ["damping_constant", "threshold"] - - for convergence_variable in ["t_inner", "t_rad", "w"]: - if convergence_variable not in convergence_section_dict: - convergence_section_dict[convergence_variable] = {} - convergence_variable_section = convergence_section_dict[ - convergence_variable - ] - for param in convergence_parameters: - if convergence_variable_section.get(param, None) is None: - if param in convergence_section_dict: - convergence_section_dict[convergence_variable][ - param - ] = convergence_section_dict[param] - - return convergence_section_dict - - class ConfigurationNameSpace(dict): """ The configuration name space class allows to wrap a dictionary and adds @@ -79,7 +49,7 @@ def from_yaml(cls, fname): """ try: yaml_dict = yaml_load_file(fname) - except IOError as e: + except OSError as e: logger.critical(f"No config file named: {fname}") raise e @@ -99,7 +69,6 @@ def from_config_dict(cls, config_dict): ------- `tardis.config_reader.Configuration` """ - return cls(config_validator.validate_dict(config_dict)) def __init__(self, value=None): @@ -194,7 +163,6 @@ def set_config_item(self, config_item_string, value): value : value to set the parameter with it """ - config_item_path = config_item_string.split(".") if len(config_item_path) == 1: self[config_item_path[0]] = value @@ -246,7 +214,7 @@ def from_yaml(cls, fname, *args, **kwargs): yaml_dict = yaml_load_file( fname, loader=kwargs.pop("loader", YAMLLoader) ) - except IOError as e: + except OSError as e: logger.critical(f"No config file named: {fname}") raise e @@ -276,7 +244,6 @@ def from_config_dict(cls, config_dict, validate=True, config_dirname=""): ------- `tardis.config_reader.Configuration` """ - if validate: validated_config_dict = config_validator.validate_dict(config_dict) else: @@ -284,118 +251,14 @@ def from_config_dict(cls, config_dict, validate=True, config_dirname=""): validated_config_dict["config_dirname"] = config_dirname - # Montecarlo Section Implementation montecarlo_section = validated_config_dict["montecarlo"] - if montecarlo_section["convergence_strategy"]["type"] == "damped": - montecarlo_section[ - "convergence_strategy" - ] = parse_convergence_section( - montecarlo_section["convergence_strategy"] - ) - elif montecarlo_section["convergence_strategy"]["type"] == "custom": - raise NotImplementedError( - 'convergence_strategy is set to "custom"; ' - "you need to implement your specific convergence treatment" - ) - else: - raise ValueError( - 'convergence_strategy is not "damped" ' 'or "custom"' - ) - - enable_full_relativity = montecarlo_section["enable_full_relativity"] - spectrum_integrated = ( - validated_config_dict["spectrum"]["method"] == "integrated" - ) - if enable_full_relativity and spectrum_integrated: - raise NotImplementedError( - "The spectrum method is set to 'integrated' and " - "enable_full_relativity to 'True'.\n" - "The FormalIntegrator is not yet implemented for the full " - "relativity mode. " - ) + Configuration.validate_montecarlo_section(montecarlo_section) if "csvy_model" in validated_config_dict.keys(): pass elif "model" in validated_config_dict.keys(): - - # Model Section Validation model_section = validated_config_dict["model"] - - if model_section["structure"]["type"] == "specific": - start_velocity = model_section["structure"]["velocity"]["start"] - stop_velocity = model_section["structure"]["velocity"]["stop"] - if stop_velocity.value < start_velocity.value: - raise ValueError( - "Stop Velocity Cannot Be Less than Start Velocity. \n" - f"Start Velocity = {start_velocity} \n" - f"Stop Velocity = {stop_velocity}" - ) - elif model_section["structure"]["type"] == "file": - v_inner_boundary = model_section["structure"][ - "v_inner_boundary" - ] - v_outer_boundary = model_section["structure"][ - "v_outer_boundary" - ] - if v_outer_boundary.value < v_inner_boundary.value: - raise ValueError( - "Outer Boundary Velocity Cannot Be Less than Inner Boundary Velocity. \n" - f"Inner Boundary Velocity = {v_inner_boundary} \n" - f"Outer Boundary Velocity = {v_outer_boundary}" - ) - if "density" in model_section["structure"].keys(): - if ( - model_section["structure"]["density"]["type"] - == "exponential" - ): - rho_0 = model_section["structure"]["density"]["rho_0"] - v_0 = model_section["structure"]["density"]["v_0"] - if not rho_0.value > 0: - raise ValueError( - f"Density Specified is Invalid, {rho_0}" - ) - if not v_0.value > 0: - raise ValueError( - f"Velocity Specified is Invalid, {v_0}" - ) - if "time_0" in model_section["structure"]["density"].keys(): - time_0 = model_section["structure"]["density"]["time_0"] - if not time_0.value > 0: - raise ValueError( - f"Time Specified is Invalid, {time_0}" - ) - elif ( - model_section["structure"]["density"]["type"] == "power_law" - ): - rho_0 = model_section["structure"]["density"]["rho_0"] - v_0 = model_section["structure"]["density"]["v_0"] - if not rho_0.value > 0: - raise ValueError( - f"Density Specified is Invalid, {rho_0}" - ) - if not v_0.value > 0: - raise ValueError( - f"Velocity Specified is Invalid, {v_0}" - ) - if "time_0" in model_section["structure"]["density"].keys(): - time_0 = model_section["structure"]["density"]["time_0"] - if not time_0.value > 0: - raise ValueError( - f"Time Specified is Invalid, {time_0}" - ) - elif model_section["structure"]["density"]["type"] == "uniform": - value = model_section["structure"]["density"]["value"] - if not value.value > 0: - raise ValueError( - f"Density Value Specified is Invalid, {value}" - ) - if "time_0" in model_section["structure"]["density"].keys(): - time_0 = model_section["structure"]["density"]["time_0"] - if not time_0.value > 0: - raise ValueError( - f"Time Specified is Invalid, {time_0}" - ) - + Configuration.validate_model_section(model_section) # SuperNova Section Validation supernova_section = validated_config_dict["supernova"] @@ -406,7 +269,7 @@ def from_config_dict(cls, config_dict, validate=True, config_dirname=""): luminosity_wavelength_end = supernova_section[ "luminosity_wavelength_end" ] - if not time_explosion.value > 0: + if time_explosion.value <= 0: raise ValueError( f"Time Of Explosion is Invalid, {time_explosion}" ) @@ -425,28 +288,163 @@ def from_config_dict(cls, config_dict, validate=True, config_dirname=""): initial_t_inner = plasma_section["initial_t_inner"] initial_t_rad = plasma_section["initial_t_rad"] - if not initial_t_inner.value >= -1: + if initial_t_inner.value < -1: raise ValueError( f"Initial Temperature of Inner Boundary Black Body is Invalid, {initial_t_inner}" ) - if not initial_t_rad.value >= -1: + if initial_t_rad.value < -1: raise ValueError( - f"Initial Radiative Temperature is Invalid, {initial_t_inner}" + f"Initial Radiative Temperature is Invalid, {initial_t_rad}" ) - # Spectrum Section Validation - spectrum_section = validated_config_dict["spectrum"] + spectrum_section = validated_config_dict["spectrum"] + Configuration.validate_spectrum_section( + spectrum_section, montecarlo_section["enable_full_relativity"] + ) + + return cls(validated_config_dict) + + @staticmethod + def validate_spectrum_section( + spectrum_section, enable_full_relativity=False + ): + """ + Validate the spectrum section dictionary + + Parameters + ---------- + spectrum_section : dict + """ + # Spectrum Section Validation + + start = spectrum_section["start"] + stop = spectrum_section["stop"] + if start.value > stop.value: + raise ValueError( + "Start Value of Spectrum Cannot be Greater than Stop Value. \n" + f"Start : {start} \n" + f"Stop : {stop}" + ) + + spectrum_integrated = spectrum_section["method"] == "integrated" + if enable_full_relativity and spectrum_integrated: + raise NotImplementedError( + "The spectrum method is set to 'integrated' and " + "enable_full_relativity to 'True'.\n" + "The FormalIntegrator is not yet implemented for the full " + "relativity mode. " + ) + + @staticmethod + def validate_model_section(model_section): + """ + Parse the model section dictionary - start = spectrum_section["start"] - stop = spectrum_section["stop"] - if start.value > stop.value: + Parameters + ---------- + model_section : dict + """ + if model_section["structure"]["type"] == "specific": + start_velocity = model_section["structure"]["velocity"]["start"] + stop_velocity = model_section["structure"]["velocity"]["stop"] + if stop_velocity.value < start_velocity.value: raise ValueError( - "Start Value of Spectrum Cannot be Greater than Stop Value. \n" - f"Start : {start} \n" - f"Stop : {stop}" + "Stop Velocity Cannot Be Less than Start Velocity. \n" + f"Start Velocity = {start_velocity} \n" + f"Stop Velocity = {stop_velocity}" ) + elif model_section["structure"]["type"] == "file": + v_inner_boundary = model_section["structure"]["v_inner_boundary"] + v_outer_boundary = model_section["structure"]["v_outer_boundary"] + if v_outer_boundary.value < v_inner_boundary.value: + raise ValueError( + "Outer Boundary Velocity Cannot Be Less than Inner Boundary Velocity. \n" + f"Inner Boundary Velocity = {v_inner_boundary} \n" + f"Outer Boundary Velocity = {v_outer_boundary}" + ) + if "density" in model_section["structure"].keys(): + if model_section["structure"]["density"]["type"] == "exponential": + rho_0 = model_section["structure"]["density"]["rho_0"] + v_0 = model_section["structure"]["density"]["v_0"] + if rho_0.value <= 0: + raise ValueError(f"Density Specified is Invalid, {rho_0}") + if v_0.value <= 0: + raise ValueError(f"Velocity Specified is Invalid, {v_0}") + if "time_0" in model_section["structure"]["density"].keys(): + time_0 = model_section["structure"]["density"]["time_0"] + if time_0.value <= 0: + raise ValueError(f"Time Specified is Invalid, {time_0}") + elif model_section["structure"]["density"]["type"] == "power_law": + rho_0 = model_section["structure"]["density"]["rho_0"] + v_0 = model_section["structure"]["density"]["v_0"] + if rho_0.value <= 0: + raise ValueError(f"Density Specified is Invalid, {rho_0}") + if v_0.value <= 0: + raise ValueError(f"Velocity Specified is Invalid, {v_0}") + if "time_0" in model_section["structure"]["density"].keys(): + time_0 = model_section["structure"]["density"]["time_0"] + if time_0.value <= 0: + raise ValueError(f"Time Specified is Invalid, {time_0}") + elif model_section["structure"]["density"]["type"] == "uniform": + density = model_section["structure"]["density"]["value"] + if density.value <= 0: + raise ValueError( + f"Density Value Specified is Invalid, {density}" + ) + if "time_0" in model_section["structure"]["density"].keys(): + time_0 = model_section["structure"]["density"]["time_0"] + if time_0.value <= 0: + raise ValueError(f"Time Specified is Invalid, {time_0}") - return cls(validated_config_dict) + @staticmethod + def validate_montecarlo_section(montecarlo_section): + """ + Validate the montecarlo section dictionary + + Parameters + ---------- + montecarlo_section : dict + """ + if montecarlo_section["convergence_strategy"]["type"] == "damped": + montecarlo_section[ + "convergence_strategy" + ] = Configuration.parse_convergence_section( + montecarlo_section["convergence_strategy"] + ) + elif montecarlo_section["convergence_strategy"]["type"] == "custom": + raise NotImplementedError( + 'convergence_strategy is set to "custom"; ' + "you need to implement your specific convergence treatment" + ) + else: + raise ValueError('convergence_strategy is not "damped" or "custom"') + + @staticmethod + def parse_convergence_section(convergence_section_dict): + """ + Parse the convergence section dictionary + + Parameters + ---------- + convergence_section_dict : dict + dictionary + """ + convergence_parameters = ["damping_constant", "threshold", "type"] + + for convergence_variable in ["t_inner", "t_rad", "w"]: + if convergence_variable not in convergence_section_dict: + convergence_section_dict[convergence_variable] = {} + convergence_variable_section = convergence_section_dict[ + convergence_variable + ] + for param in convergence_parameters: + if convergence_variable_section.get(param, None) is None: + if param in convergence_section_dict: + convergence_section_dict[convergence_variable][ + param + ] = convergence_section_dict[param] + + return convergence_section_dict def __init__(self, config_dict): super(Configuration, self).__init__(config_dict) diff --git a/tardis/io/config_validator.py b/tardis/io/configuration/config_validator.py similarity index 66% rename from tardis/io/config_validator.py rename to tardis/io/configuration/config_validator.py index 5ca05fdfd3a..5205ac9d205 100644 --- a/tardis/io/config_validator.py +++ b/tardis/io/configuration/config_validator.py @@ -1,13 +1,15 @@ -import os -import yaml from copy import deepcopy -from jsonschema import Draft4Validator, RefResolver, validators +from pathlib import Path + +import yaml from astropy.units.quantity import Quantity +from jsonschema import Draft4Validator, RefResolver, validators + from tardis.io.util import YAMLLoader -base_dir = os.path.abspath(os.path.dirname(__file__)) -schema_dir = os.path.join(base_dir, "schemas") -config_schema_file = os.path.join(schema_dir, "base.yml") +CONFIGURATION_DIR = Path(__file__).resolve().parent +SCHEMA_DIR = CONFIGURATION_DIR / "schemas" +CONFIG_SCHEMA_FNAME = SCHEMA_DIR / "base.yml" def extend_with_default(validator_class): @@ -62,23 +64,51 @@ def _yaml_handler(path): return yaml.load(f, Loader=YAMLLoader) +def is_quantity(checker, instance): + """ + Check if the provided instance is of type astropy.units.quantity.Quantity + + Parameters + ---------- + checker: + Object of `TypeChecker`. Passed by jsonschema internally. + + instance: + The instance to be checked. + + Returns + ------- + bool: True if the instance is of type astropy.units.quantity.Quantity else False + """ + return isinstance(instance, Quantity) + + def validate_dict( - config_dict, schemapath=config_schema_file, validator=DefaultDraft4Validator + config_dict, + schemapath=CONFIG_SCHEMA_FNAME, + validator=DefaultDraft4Validator, ): with open(schemapath) as f: schema = yaml.load(f, Loader=YAMLLoader) - schemaurl = "file://" + schemapath + schemaurl = f"file://{schemapath}" handlers = {"file": _yaml_handler} resolver = RefResolver(schemaurl, schema, handlers=handlers) validated_dict = deepcopy(config_dict) - validator( - schema=schema, types={"quantity": (Quantity,)}, resolver=resolver + custom_type_checker = validator.TYPE_CHECKER.redefine( + "quantity", is_quantity + ) + custom_validator = validators.extend( + validator, type_checker=custom_type_checker + ) + custom_validator( + schema=schema, + resolver=resolver, ).validate(validated_dict) return validated_dict def validate_yaml( - configpath, schemapath=config_schema_file, validator=DefaultDraft4Validator + configpath, schemapath=CONFIG_SCHEMA_FNAME, validator=DefaultDraft4Validator ): with open(configpath) as f: config = yaml.load(f, Loader=YAMLLoader) diff --git a/tardis/io/schemas/base.yml b/tardis/io/configuration/schemas/base.yml similarity index 100% rename from tardis/io/schemas/base.yml rename to tardis/io/configuration/schemas/base.yml diff --git a/tardis/io/schemas/csvy_model.yml b/tardis/io/configuration/schemas/csvy_model.yml similarity index 100% rename from tardis/io/schemas/csvy_model.yml rename to tardis/io/configuration/schemas/csvy_model.yml diff --git a/tardis/io/schemas/debug.yml b/tardis/io/configuration/schemas/debug.yml similarity index 100% rename from tardis/io/schemas/debug.yml rename to tardis/io/configuration/schemas/debug.yml diff --git a/tardis/io/schemas/model.yml b/tardis/io/configuration/schemas/model.yml similarity index 100% rename from tardis/io/schemas/model.yml rename to tardis/io/configuration/schemas/model.yml diff --git a/tardis/io/schemas/model_definitions.yml b/tardis/io/configuration/schemas/model_definitions.yml similarity index 95% rename from tardis/io/schemas/model_definitions.yml rename to tardis/io/configuration/schemas/model_definitions.yml index 41b6601e08e..d8df51735bb 100644 --- a/tardis/io/schemas/model_definitions.yml +++ b/tardis/io/configuration/schemas/model_definitions.yml @@ -161,6 +161,7 @@ definitions: - velocity - density abundances: + file: $$target: 'model_definitions.yml#/definitions/abundances/file' $$description: One can use a file referenced in the model configuration @@ -178,6 +179,11 @@ definitions: filename: type: string description: filename + model_isotope_time_0: + type: quantity + default: 0 s + description: Initial time for isotope decay + required: - filetype - filename @@ -191,7 +197,15 @@ definitions: type: enum: - uniform + model_isotope_time_0: + type: quantity + default: 0 s + description: Initial time for isotope decay additionalProperties: type: number minimum: 0 maximum: 1 + required: + - model_isotope_time_0 + + diff --git a/tardis/io/schemas/montecarlo.yml b/tardis/io/configuration/schemas/montecarlo.yml similarity index 86% rename from tardis/io/schemas/montecarlo.yml rename to tardis/io/configuration/schemas/montecarlo.yml index 4a31f5228c5..1baa9f37dac 100644 --- a/tardis/io/schemas/montecarlo.yml +++ b/tardis/io/configuration/schemas/montecarlo.yml @@ -17,7 +17,7 @@ properties: no_of_packets: type: number multipleOf: 1.0 - description: Seed for the random number generator + description: The number of packets used in each iteration. iterations: type: number multipleOf: 1.0 @@ -45,14 +45,6 @@ properties: default: inf angstrom description: Limits of virtual packet spawn spectrum (giving maximum and minimum packet frequency) - enable_reflective_inner_boundary: - type: boolean - default: false - description: experimental feature to enable a reflective boundary. - inner_boundary_albedo: - type: number - default: 0.0 - description: albedo of the reflective boundary convergence_strategy: oneOf: - $ref: 'montecarlo_definitions.yml#/definitions/convergence_strategy/damped' @@ -64,6 +56,10 @@ properties: default: false description: Enables a more complete treatment of relativitic effects. This includes angle aberration as well as use of the fully general Doppler formula. + enable_nonhomologous_expansion: + type: boolean + default: false + description: Enables nonhomologous expansion. Treats shells as piece-wise homologous areas for velocity-radius dependence. tracking: type: object default: {} @@ -86,11 +82,6 @@ properties: type: number default: 1 description: Provides option to not log every line. - single_packet_seed: - type: - - number - default: -1 - description: If debug_packets is true, this is the seed for the only packet. required: - no_of_packets diff --git a/tardis/io/schemas/montecarlo_definitions.yml b/tardis/io/configuration/schemas/montecarlo_definitions.yml similarity index 100% rename from tardis/io/schemas/montecarlo_definitions.yml rename to tardis/io/configuration/schemas/montecarlo_definitions.yml diff --git a/tardis/io/schemas/plasma.yml b/tardis/io/configuration/schemas/plasma.yml similarity index 84% rename from tardis/io/schemas/plasma.yml rename to tardis/io/configuration/schemas/plasma.yml index 53274eec72e..47189725bc0 100644 --- a/tardis/io/schemas/plasma.yml +++ b/tardis/io/configuration/schemas/plasma.yml @@ -107,6 +107,25 @@ properties: type: string default: none description: Path to file containing heating rate/light curve data. + link_t_rad_t_electron: + type: number + default: 0.9 + description: Value used for estimating the electron temperature from radiation temperature. + nlte_ionization_species: + type: array + default: [] + description: List of species treated with nlte ionization. In the format ["H I", "He II"] etc. + nlte_excitation_species: + type: array + default: [] + description: List of species treated with nlte excitation. In the format ["H I", "He II"] etc. + nlte_solver: + type: string + default: root + enum: + - root + - lu + description: Selects NLTE population equation solver approach. required: - ionization - excitation diff --git a/tardis/io/schemas/spectrum.yml b/tardis/io/configuration/schemas/spectrum.yml similarity index 76% rename from tardis/io/schemas/spectrum.yml rename to tardis/io/configuration/schemas/spectrum.yml index f3e0a0bc7d4..d6afea03106 100644 --- a/tardis/io/schemas/spectrum.yml +++ b/tardis/io/configuration/schemas/spectrum.yml @@ -36,6 +36,21 @@ properties: integral quantities are interpolated. For -1 no interpolation is used. The default is to use twice the number of computational shells but at least 80. + compute: + type: string + default: "CPU" + description: Which method the formal_integral will be computed with. + It defaults to the Numba version, but it can be run on NVIDIA Cuda + GPUs. GPU will make it only run on a NVIDIA Cuda GPU, so if one is + not available it will raise an error. Automatic first tries to find + an acceptable GPU, and if none is found it will run on the CPU. + properties: + type: + enum: + - "CPU" + - "GPU" + - "Automatic" + virtual: type: object default: {} diff --git a/tardis/io/schemas/supernova.yml b/tardis/io/configuration/schemas/supernova.yml similarity index 100% rename from tardis/io/schemas/supernova.yml rename to tardis/io/configuration/schemas/supernova.yml diff --git a/tardis/io/tests/data/paper1_tardis_configv1.yml b/tardis/io/configuration/tests/data/paper1_tardis_configv1.yml similarity index 100% rename from tardis/io/tests/data/paper1_tardis_configv1.yml rename to tardis/io/configuration/tests/data/paper1_tardis_configv1.yml diff --git a/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_nebular.yml b/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_nebular.yml new file mode 100644 index 00000000000..64bacc62ffa --- /dev/null +++ b/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_nebular.yml @@ -0,0 +1,50 @@ +tardis_config_version: v1.0 + +supernova: + luminosity_requested: 9.44 log_lsun + time_explosion: 150 day + +atom_data: kurucz_atom_pure.h5 + +model: + structure: + type: specific + + velocity: + start: 1.1e4 km/s + stop: 20000 km/s + num: 20 + + density: + type: exponential + time_0: 20. second + rho_0: 3.e2 g/cm^3 + v_0: 3000. km/s + + abundances: + type: uniform + O: 0.19 + Mg: 0.03 + Si: 0.12 + S: 0.09 + Ar: 0.04 + Ca: 0.03 + Ni56: 0.5 + +plasma: + ionization: nebular + excitation: dilute-lte + radiative_rates_type: dilute-blackbody + line_interaction_type: scatter + +montecarlo: + seed: 23111963 + no_of_packets: 2.0e+5 + iterations: 30 + last_no_of_packets: 5.0e+5 + no_of_virtual_packets: 5 + +spectrum: + start: 500 angstrom + stop: 20000 angstrom + num: 10000 diff --git a/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_nebular_multi_isotope.yml b/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_nebular_multi_isotope.yml new file mode 100644 index 00000000000..4786784264a --- /dev/null +++ b/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_nebular_multi_isotope.yml @@ -0,0 +1,52 @@ +tardis_config_version: v1.0 + +supernova: + luminosity_requested: 9.44 log_lsun + time_explosion: 150 day + +atom_data: kurucz_atom_pure.h5 + +model: + structure: + type: specific + + velocity: + start: 1.1e4 km/s + stop: 20000 km/s + num: 20 + + density: + type: exponential + time_0: 20. second + rho_0: 3.e2 g/cm^3 + v_0: 3000. km/s + + abundances: + type: uniform + O: 0.19 + Mg: 0.03 + Si: 0.12 + S: 0.09 + Ar: 0.02 + Ca: 0.03 + Ni56: 0.5 + Fe52: 0.01 + Cr48: 0.01 + +plasma: + ionization: nebular + excitation: dilute-lte + radiative_rates_type: dilute-blackbody + line_interaction_type: scatter + +montecarlo: + seed: 23111963 + no_of_packets: 2.0e+5 + iterations: 30 + last_no_of_packets: 5.0e+5 + no_of_virtual_packets: 5 + +spectrum: + start: 500 angstrom + stop: 20000 angstrom + num: 10000 diff --git a/tardis/io/tests/data/tardis_configv1_density_exponential_test.yml b/tardis/io/configuration/tests/data/tardis_configv1_density_exponential_test.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_density_exponential_test.yml rename to tardis/io/configuration/tests/data/tardis_configv1_density_exponential_test.yml diff --git a/tardis/io/tests/data/tardis_configv1_density_power_law_test.yml b/tardis/io/configuration/tests/data/tardis_configv1_density_power_law_test.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_density_power_law_test.yml rename to tardis/io/configuration/tests/data/tardis_configv1_density_power_law_test.yml diff --git a/tardis/io/configuration/tests/data/tardis_configv1_nlte.yml b/tardis/io/configuration/tests/data/tardis_configv1_nlte.yml new file mode 100644 index 00000000000..9e232f3c140 --- /dev/null +++ b/tardis/io/configuration/tests/data/tardis_configv1_nlte.yml @@ -0,0 +1,71 @@ +tardis_config_version: v1.0 + +supernova: + luminosity_requested: 9.05 log_lsun + time_explosion: 16 day + +atom_data: TestNLTE_Ti.h5 + +model: + structure: + type: specific + velocity: + start: 6395 km/s + stop: 12500 km/s + num: 5 + density: + type : power_law + time_0: 16.0 day + rho_0: 1.948e-14 g/cm^3 + v_0: 8000 km/s + exponent: -10 + + abundances: + type: uniform + H: 0.9 + He: 0.099 + Ti: 1e-3 + +plasma: + disable_electron_scattering: no + ionization: lte + excitation: lte + radiative_rates_type: dilute-blackbody + line_interaction_type: macroatom + initial_t_inner: 12000 K + link_t_rad_t_electron: 1.0 + nlte_ionization_species: [H I, He II, Ti II] + nlte_solver: root + + continuum_interaction: + species: + - H I + - Ti II + - He II + + enable_adiabatic_cooling: True + + + +montecarlo: + seed: 23111963 + no_of_packets: 100000 + iterations: 1 + nthreads: 1 + + last_no_of_packets: 1000 + no_of_virtual_packets: 0 + + convergence_strategy: + type: damped + damping_constant: 0.5 + threshold: 0.05 + fraction: 0.8 + hold_iterations: 3 + +spectrum: + start: 250 angstrom + stop: 10000 angstrom + num: 10000 + method: integrated + compute: Automatic diff --git a/tardis/io/tests/data/tardis_configv1_uniform_density.yml b/tardis/io/configuration/tests/data/tardis_configv1_uniform_density.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_uniform_density.yml rename to tardis/io/configuration/tests/data/tardis_configv1_uniform_density.yml diff --git a/tardis/io/tests/data/tardis_configv1_verysimple.yml b/tardis/io/configuration/tests/data/tardis_configv1_verysimple.yml similarity index 96% rename from tardis/io/tests/data/tardis_configv1_verysimple.yml rename to tardis/io/configuration/tests/data/tardis_configv1_verysimple.yml index 074f7764fa5..f165578f493 100644 --- a/tardis/io/tests/data/tardis_configv1_verysimple.yml +++ b/tardis/io/configuration/tests/data/tardis_configv1_verysimple.yml @@ -4,7 +4,7 @@ supernova: luminosity_requested: 2.8e9 solLum time_explosion: 13 day -atom_data: kurucz_atom_pure_simple.h5 +atom_data: kurucz_cd23_chianti_H_He.h5 model: structure: diff --git a/tardis/io/tests/data/tardis_configv1_verysimple_logger.yml b/tardis/io/configuration/tests/data/tardis_configv1_verysimple_logger.yml similarity index 99% rename from tardis/io/tests/data/tardis_configv1_verysimple_logger.yml rename to tardis/io/configuration/tests/data/tardis_configv1_verysimple_logger.yml index 054deb5dd62..1c4110dac0a 100644 --- a/tardis/io/tests/data/tardis_configv1_verysimple_logger.yml +++ b/tardis/io/configuration/tests/data/tardis_configv1_verysimple_logger.yml @@ -5,6 +5,7 @@ supernova: time_explosion: 13 day atom_data: kurucz_atom_pure_simple.h5 + model: structure: type: specific diff --git a/tardis/io/configuration/tests/test_config_reader.py b/tardis/io/configuration/tests/test_config_reader.py new file mode 100644 index 00000000000..f525557ca63 --- /dev/null +++ b/tardis/io/configuration/tests/test_config_reader.py @@ -0,0 +1,288 @@ +# tests for the config reader module +import os +from attr import validate +import pytest +import pandas as pd +from numpy.testing import assert_almost_equal +from jsonschema.exceptions import ValidationError + +from tardis.io.configuration import config_reader +from astropy.units import Quantity +from tardis.io.configuration.config_reader import Configuration +from tardis.plasma.exceptions import PlasmaConfigError +from tardis.plasma.standard_plasmas import assemble_plasma + + +def test_convergence_section_parser(): + test_convergence_section = { + "type": "damped", + "lock_t_inner_cyles": 1, + "t_inner_update_exponent": -0.5, + "damping_constant": 0.5, + "threshold": 0.05, + "fraction": 0.8, + "hold_iterations": 3, + "t_rad": {"damping_constant": 1.0}, + } + + parsed_convergence_section = ( + config_reader.Configuration.parse_convergence_section( + test_convergence_section + ) + ) + + assert_almost_equal( + parsed_convergence_section["t_rad"]["damping_constant"], 1.0 + ) + + assert_almost_equal( + parsed_convergence_section["w"]["damping_constant"], 0.5 + ) + + +def test_from_config_dict(tardis_config_verysimple): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + assert conf.config_dirname == "test" + + assert_almost_equal( + conf.spectrum.start.value, + tardis_config_verysimple["spectrum"]["start"].value, + ) + + assert_almost_equal( + conf.spectrum.stop.value, + tardis_config_verysimple["spectrum"]["stop"].value, + ) + + tardis_config_verysimple["spectrum"]["start"] = "Invalid" + with pytest.raises(ValidationError): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + + +def test_config_hdf(hdf_file_path, tardis_config_verysimple): + expected = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + expected.to_hdf(hdf_file_path, overwrite=True) + actual = pd.read_hdf(hdf_file_path, key="/simulation/config") + expected = expected.get_properties()["config"] + assert actual[0] == expected[0] + + +def test_model_section_config(tardis_config_verysimple): + """ + Configuration Validation Test for Model Section of the Tardis Config YAML File + + Validates: + Density: branch85_w7 + Velocity (Start < End) + + Parameter + --------- + `tardis_config_verysimple` : YAML File + + Result + ------ + Assertion based on validation for specified values + """ + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + + assert conf.model.structure.density.type == "branch85_w7" + + tardis_config_verysimple["model"]["structure"]["velocity"][ + "start" + ] = Quantity("2.0e4 km/s") + tardis_config_verysimple["model"]["structure"]["velocity"][ + "stop" + ] = Quantity("1.1e4 km/s") + + with pytest.raises(ValueError): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + + +def test_supernova_section_config(tardis_config_verysimple): + """ + Configuration Validation Test for Supernova Section of the Tardis Config YAML File + + Validates: + Time of Explosion (Must always be positive) + Luminosity Wavelength Limits (Start < End) + + Parameter + --------- + `tardis_config_verysimple` : YAML File + + Result + ------ + Assertion based on validation for specified values + """ + tardis_config_verysimple["supernova"]["time_explosion"] = Quantity( + "-10 day" + ) + with pytest.raises(ValueError): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + + tardis_config_verysimple["supernova"]["time_explosion"] = Quantity("10 day") + tardis_config_verysimple["supernova"][ + "luminosity_wavelength_start" + ] = Quantity("15 angstrom") + tardis_config_verysimple["supernova"][ + "luminosity_wavelength_end" + ] = Quantity("0 angstrom") + with pytest.raises(ValueError): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + + +@pytest.mark.parametrize("key", ["initial_t_inner", "initial_t_rad"]) +def test_plasma_section_config(key, tardis_config_verysimple): + """ + Configuration Validation Test for Plasma Section of the Tardis Config YAML File + + Validates: + Initial temperature inner (must be greater than -1K) + Initial radiative temperature (must be greater than -1K) + + Parameter + --------- + `tardis_config_verysimple` : YAML File + + Result + ------ + Assertion based on validation for specified values + """ + tardis_config_verysimple["plasma"][key] = Quantity("-100 K") + with pytest.raises(ValueError): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) + + +def test_plasma_nlte_section_root_config( + tardis_config_verysimple_nlte, + nlte_raw_model_root, + nlte_atom_data, +): + """ + Configuration Validation Test for Plasma Section of the Tardis Config YAML File. + + Validates: + nlte_ionization_species: should be included in continuum_interaction + + Parameter + --------- + `tardis_config_verysimple_nlte_root` : YAML File + `nlte_raw_model` : A simple model + `nlte_atom_data` : An example atomic dataset + + Result + ------ + Assertion based on validation for specified values + """ + tardis_config_verysimple_nlte["plasma"]["continuum_interaction"][ + "species" + ] = [ + "He I", + ] + tardis_config_verysimple_nlte["plasma"]["nlte_ionization_species"] = ["H I"] + config = Configuration.from_config_dict(tardis_config_verysimple_nlte) + with pytest.raises(PlasmaConfigError) as ve: + assemble_plasma(config, nlte_raw_model_root, nlte_atom_data) + + +def test_plasma_nlte_section_lu_config( + tardis_config_verysimple_nlte, + nlte_raw_model_lu, + nlte_atom_data, +): + """ + Configuration Validation Test for Plasma Section of the Tardis Config YAML File. + + Validates: + nlte_ionization_species: should be included in continuum_interaction + + Parameter + --------- + `tardis_config_verysimple_nlte_root` : YAML File + `nlte_raw_model` : A simple model + `nlte_atom_data` : An example atomic dataset + + Result + ------ + Assertion based on validation for specified values + """ + tardis_config_verysimple_nlte["plasma"]["continuum_interaction"][ + "species" + ] = [ + "He I", + ] + tardis_config_verysimple_nlte["plasma"]["nlte_ionization_species"] = ["H I"] + tardis_config_verysimple_nlte["plasma"]["nlte_solver"] = "lu" + config = Configuration.from_config_dict(tardis_config_verysimple_nlte) + with pytest.raises(PlasmaConfigError) as ve: + assemble_plasma(config, nlte_raw_model_lu, nlte_atom_data) + + +def test_plasma_nlte_root_exc_section_config( + tardis_config_verysimple_nlte, nlte_raw_model_root, nlte_atom_data +): + """ + Configuration Validation Test for Plasma Section of the Tardis Config YAML File. + + Validates: + nlte_excitation_species: should be included in continuum_interaction + + Parameter + --------- + `tardis_config_verysimple_nlte_root` : YAML File + `nlte_raw_model` : A simple model + `nlte_atom_data` : An example atomic dataset + + Result + ------ + Assertion based on validation for specified values + """ + tardis_config_verysimple_nlte["plasma"]["continuum_interaction"][ + "species" + ] = [ + "He I", + ] + tardis_config_verysimple_nlte["plasma"]["nlte_excitation_species"] = ["H I"] + tardis_config_verysimple_nlte["plasma"]["nlte_solver"] = "root" + config = Configuration.from_config_dict(tardis_config_verysimple_nlte) + with pytest.raises(PlasmaConfigError): + plasma = assemble_plasma(config, nlte_raw_model_root, nlte_atom_data) + + +def test_spectrum_section_config(tardis_config_verysimple): + """ + Configuration Validation Test for Plasma Section of the Tardis Config YAML File + + Validates: + Spectrum Start & End Limits (Start < End) + + Parameter + --------- + `tardis_config_verysimple` : YAML File + + Result + ------ + Assertion based on validation for specified values + """ + tardis_config_verysimple["spectrum"]["start"] = Quantity("2500 angstrom") + tardis_config_verysimple["spectrum"]["stop"] = Quantity("500 angstrom") + with pytest.raises(ValueError): + conf = Configuration.from_config_dict( + tardis_config_verysimple, validate=True, config_dirname="test" + ) diff --git a/tardis/io/tests/test_config_validator.py b/tardis/io/configuration/tests/test_config_validator.py similarity index 100% rename from tardis/io/tests/test_config_validator.py rename to tardis/io/configuration/tests/test_config_validator.py diff --git a/tardis/io/tests/test_configuration_namespace.py b/tardis/io/configuration/tests/test_configuration_namespace.py similarity index 96% rename from tardis/io/tests/test_configuration_namespace.py rename to tardis/io/configuration/tests/test_configuration_namespace.py index 0a955ea9d2c..c9445c8f1ec 100644 --- a/tardis/io/tests/test_configuration_namespace.py +++ b/tardis/io/configuration/tests/test_configuration_namespace.py @@ -1,4 +1,4 @@ -from tardis.io.config_reader import ConfigurationNameSpace +from tardis.io.configuration.config_reader import ConfigurationNameSpace import pytest from astropy import units as u import os diff --git a/tardis/io/logger/__init__.py b/tardis/io/logger/__init__.py index e69de29bb2d..78bc5622358 100644 --- a/tardis/io/logger/__init__.py +++ b/tardis/io/logger/__init__.py @@ -0,0 +1,3 @@ +""" +Managing the logging output. +""" diff --git a/tardis/io/logger/colored_logger.py b/tardis/io/logger/colored_logger.py index f45a7c423e3..a03d88a1fac 100644 --- a/tardis/io/logger/colored_logger.py +++ b/tardis/io/logger/colored_logger.py @@ -6,6 +6,9 @@ http://stackoverflow.com/questions/384076/how-can-i-color-python-logging-output """ +FORMAT = "[$BOLD{name:20s}$RESET][{levelname:18s}] \n\t{message:s} ($BOLD{filename:s}$RESET:{lineno:d})" +DEBUG_FORMAT = "[$BOLD{name:20s}$RESET][{levelname:18s}] {message:s} ($BOLD{filename:s}$RESET:{lineno:d})" + def formatter_message(message, use_color=True): """ @@ -28,8 +31,10 @@ class ColoredFormatter(logging.Formatter): Custom logger class for changing levels color """ - def __init__(self, msg, use_color=True): - logging.Formatter.__init__(self, msg) + def __init__(self, use_color=True): + self.non_debug = formatter_message(FORMAT, True) + self.debug = formatter_message(DEBUG_FORMAT, True) + logging.Formatter.__init__(self, self.non_debug, style="{") self.use_color = use_color def format(self, record): @@ -43,12 +48,19 @@ def format(self, record): "CRITICAL": YELLOW, "ERROR": RED, } + levelname = record.levelname if self.use_color and levelname in COLORS: levelname_color = ( COLOR_SEQ % (30 + COLORS[levelname]) + levelname + RESET_SEQ ) record.levelname = levelname_color + + if record.levelno == logging.DEBUG: + self._style._fmt = self.debug + else: + self._style._fmt = self.non_debug + return logging.Formatter.format(self, record) @@ -57,7 +69,6 @@ class ColoredLogger(logging.Logger): Custom logger class with multiple destinations """ - FORMAT = "[$BOLD%(name)-20s$RESET][%(levelname)-18s] %(message)s ($BOLD%(filename)s$RESET:%(lineno)d)" COLOR_FORMAT = formatter_message(FORMAT, True) def __init__(self, name): diff --git a/tardis/io/logger/logger.py b/tardis/io/logger/logger.py index e3e3b1cc69f..70fcabcc4e9 100644 --- a/tardis/io/logger/logger.py +++ b/tardis/io/logger/logger.py @@ -1,21 +1,13 @@ import logging import sys -import warnings -import pyne.data from tardis.io.logger.colored_logger import ColoredFormatter, formatter_message -warnings.filterwarnings("ignore", category=pyne.utils.QAWarning) - -FORMAT = "[$BOLD%(name)-20s$RESET][%(levelname)-18s] %(message)s ($BOLD%(filename)s$RESET:%(lineno)d)" -COLOR_FORMAT = formatter_message(FORMAT, True) - logging.captureWarnings(True) logger = logging.getLogger("tardis") -logger.setLevel(logging.INFO) console_handler = logging.StreamHandler(sys.stdout) -console_formatter = ColoredFormatter(COLOR_FORMAT) +console_formatter = ColoredFormatter() console_handler.setFormatter(console_formatter) logger.addHandler(console_handler) diff --git a/tardis/io/logger/tests/test_logging.py b/tardis/io/logger/tests/test_logging.py index 05bac5bce54..7ab6d8e638b 100644 --- a/tardis/io/logger/tests/test_logging.py +++ b/tardis/io/logger/tests/test_logging.py @@ -1,10 +1,15 @@ import pytest import logging -from tardis.io.config_reader import Configuration +from tardis.io.configuration.config_reader import Configuration from tardis.simulation import Simulation from tardis.io.logger.logger import LOGGING_LEVELS from tardis import run_tardis +import pytest + +pytestmark = pytest.mark.skip( + reason="logging testing slow and disabled for now" +) def test_logging_simulation(atomic_data_fname, caplog): @@ -18,7 +23,8 @@ def test_logging_simulation(atomic_data_fname, caplog): simulation = Simulation.from_config(config) - simulation.run() + simulation.run_convergence() + simulation.run_final() for record in caplog.records: assert record.levelno >= logging.INFO diff --git a/tardis/io/model/__init__.py b/tardis/io/model/__init__.py new file mode 100644 index 00000000000..25d3a7257a6 --- /dev/null +++ b/tardis/io/model/__init__.py @@ -0,0 +1,4 @@ +from tardis.io.model.readers.stella import read_stella_model + +# from tardis.io.model.stella import read_stella_model +from tardis.io.model.cmfgen import read_cmfgen_model diff --git a/tardis/io/model/cmfgen.py b/tardis/io/model/cmfgen.py new file mode 100644 index 00000000000..0c4364541d3 --- /dev/null +++ b/tardis/io/model/cmfgen.py @@ -0,0 +1,75 @@ +import re +import pandas as pd +from astropy import units as u +from pathlib import Path +import dataclasses + + +@dataclasses.dataclass +class CMFGENModel: + metadata: dict + data: pd.DataFrame + + +HEADER_RE_STR = [ + ("t0:\s+(\d+\.\d+)+\s+day", "t0"), +] + +COLUMN_ROW = 1 +UNIT_ROW = 2 +DATA_START_ROW = 3 + + +def read_cmfgen_model(fname): + """ + Read in a CMFGEN model file and return the data and model + + Parameters + ---------- + + fname : str + + Returns + ------- + model : CMFGENModel + + """ + header_re = [re.compile(re_str[0]) for re_str in HEADER_RE_STR] + metadata = {} + with open(fname) as fh: + for i, line in enumerate(fh): + if i < len(HEADER_RE_STR): + header_re_match = header_re[i].match(line) + metadata[HEADER_RE_STR[i][1]] = header_re_match.group(1) + elif i == COLUMN_ROW: + if "Index" in line: + column_names = re.split(r"\s", line.strip()) + column_names = [ + col.lower().replace(" ", "_") for col in column_names + ] + column_names = column_names[ + 1: + ] # Remove Index from column names + else: + raise ValueError( + '"Index" is required in the Cmfgen input file to infer columns' + ) + elif i == UNIT_ROW: + units = re.split(r"\s", line.strip()) + units = units[1:] # Remove index column + for col, unit in zip(column_names, units): + if u.Unit(unit) == "": # dimensionless + continue + metadata[f"{col}_unit"] = u.Unit(unit) + break + + metadata["t0"] = float(metadata["t0"]) * u.day + data = pd.read_csv( + fname, + delim_whitespace=True, + skiprows=DATA_START_ROW, + header=None, + index_col=0, + ) + data.columns = column_names + return CMFGENModel(metadata, data) diff --git a/tardis/io/model/density.py b/tardis/io/model/density.py new file mode 100644 index 00000000000..c9048e0112c --- /dev/null +++ b/tardis/io/model/density.py @@ -0,0 +1,187 @@ +import numpy as np +from astropy import units as u + +from tardis.io.configuration.config_reader import Configuration +from tardis.util.base import quantity_linspace + + +def parse_density_section( + density_configuration: Configuration, + v_middle: u.Quantity, + time_explosion: u.Quantity, +): + if density_configuration.type == "branch85_w7": + density_0 = calculate_power_law_density( + v_middle, + density_configuration.w7_v_0, + density_configuration.w7_rho_0, + -7, + ) + time_0 = density_configuration.w7_time_0 + elif density_configuration.type == "uniform": + density_0 = density_configuration.value.to("g cm^-3") * np.ones_like( + v_middle.value + ) + time_0 = density_configuration.get("time_0", time_explosion) + elif density_configuration.type == "power_law": + density_0 = calculate_power_law_density( + v_middle, + density_configuration.v_0, + density_configuration.rho_0, + density_configuration.exponent, + ) + time_0 = density_configuration.get("time_0", time_explosion) + elif density_configuration.type == "exponential": + density_0 = calculate_exponential_density( + v_middle, density_configuration.v_0, density_configuration.rho_0 + ) + time_0 = density_configuration.get("time_0", time_explosion) + else: + raise ValueError( + f"Unrecognized density type " f"'{density_configuration.type}'" + ) + return density_0, time_0 + + +def parse_config_v1_density(config: Configuration) -> u.Quantity: + """ + Create a new HomologousDensity instance from a Configuration object. + + Parameters + ---------- + config : tardis.io.config_reader.Configuration + + Returns + ------- + HomologousDensity + + """ + + velocity = quantity_linspace( + config.model.structure.velocity.start, + config.model.structure.velocity.stop, + config.model.structure.velocity.num + 1, + ).cgs + + adjusted_velocity = velocity.insert(0, 0) + v_middle = adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5 + time_explosion = config.supernova.time_explosion.cgs + d_conf = config.model.structure.density + density_0, time_0 = parse_density_section(d_conf, v_middle, time_explosion) + + return calculate_density_after_time(density_0, time_0, time_explosion) + + +def parse_csvy_density(csvy_model_config, time_explosion: u.Quantity): + """ + Create a new HomologousDensity instance from a base + Configuration object and a csvy model Configuration object. + + Parameters + ---------- + config : tardis.io.config_reader.Configuration + csvy_model_config : tardis.io.config_reader.Configuration + + Returns + ------- + HomologousDensity + + """ + if hasattr(csvy_model_config, "velocity"): + velocity = quantity_linspace( + csvy_model_config.velocity.start, + csvy_model_config.velocity.stop, + csvy_model_config.velocity.num + 1, + ).cgs + else: + velocity_field_index = [ + field.name for field in csvy_model_config.datatype.fields + ].index("velocity") + velocity_unit = u.Unit( + csvy_model_config.datatype.fields[velocity_field_index].unit + ) + velocity = csvy_model_config.velocity.values * velocity_unit + + adjusted_velocity = velocity.insert(0, 0) + v_middle = adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5 + no_of_shells = len(adjusted_velocity) - 1 + + if hasattr(csvy_model_config, "density"): + density_0, time_0 = parse_density_section( + csvy_model_config.density, v_middle, time_explosion + ) + return calculate_density_after_time(density_0, time_0, time_explosion) + + +def calculate_power_law_density(velocities, velocity_0, rho_0, exponent): + """ + + This function computes a descret exponential density profile. + :math:`\\rho = \\rho_0 \\times \\left( \\frac{v}{v_0} \\right)^n` + + Parameters + ---------- + velocities : astropy.Quantity + Array like velocity profile + velocity_0 : astropy.Quantity + reference velocity + rho_0 : astropy.Quantity + reference density + exponent : float + exponent used in the powerlaw + + Returns + ------- + densities : astropy.Quantity + + """ + densities = rho_0 * np.power((velocities / velocity_0), exponent) + return densities + + +def calculate_exponential_density(velocities, velocity_0, rho_0): + """ + This function computes the exponential density profile. + :math:`\\rho = \\rho_0 \\times \\exp \\left( -\\frac{v}{v_0} \\right)` + + Parameters + ---------- + velocities : astropy.Quantity + Array like velocity profile + velocity_0 : astropy.Quantity + reference velocity + rho_0 : astropy.Quantity + reference density + + Returns + ------- + densities : astropy.Quantity + + """ + densities = rho_0 * np.exp(-(velocities / velocity_0)) + return densities + + +def calculate_density_after_time( + densities: u.Quantity, time_0: u.Quantity, time_explosion: u.Quantity +) -> u.Quantity: + """ + scale the density from an initial time of the model to the + time of the explosion by ^-3 + + Parameters + ---------- + densities : astropy.units.Quantity + densities + time_0 : astropy.units.Quantity + time of the model + time_explosion : astropy.units.Quantity + time to be scaled to + + Returns + ------- + scaled_density : astropy.units.Quantity + in g / cm^3 + """ + + return (densities * (time_explosion / time_0) ** -3).to(u.g / (u.cm**3)) diff --git a/tardis/io/model/parse_density_configuration.py b/tardis/io/model/parse_density_configuration.py new file mode 100644 index 00000000000..d70046b5e79 --- /dev/null +++ b/tardis/io/model/parse_density_configuration.py @@ -0,0 +1,222 @@ +import numpy as np +from astropy import units as u + +from tardis.io.configuration.config_reader import ( + ConfigurationNameSpace, + Configuration, +) +from tardis.util.base import quantity_linspace + +from typing import Tuple + + +def parse_density_section( + density_configuration: ConfigurationNameSpace, + v_middle: u.Quantity, + time_explosion: u.Quantity, +) -> Tuple[u.Quantity, u.Quantity]: + """ + Parse the density section of the configuration file and produce a density at + time_explosion. + + Parameters + ---------- + + density_configuration : tardis.io.config_reader.Configuration + v_middle : astropy.Quantity + middle of the velocity bins + time_explosion : astropy.Quantity + time of the explosion + + Returns + ------- + density_0 : astropy.Quantity + density at time_0 + time_0 : astropy.Quantity + time of the density profile + """ + if density_configuration.type == "branch85_w7": + density_0 = calculate_power_law_density( + v_middle, + density_configuration.w7_v_0, + density_configuration.w7_rho_0, + -7, + ) + time_0 = density_configuration.w7_time_0 + elif density_configuration.type == "uniform": + density_0 = density_configuration.value.to("g cm^-3") * np.ones_like( + v_middle.value + ) + time_0 = density_configuration.get("time_0", time_explosion) + elif density_configuration.type == "power_law": + density_0 = calculate_power_law_density( + v_middle, + density_configuration.v_0, + density_configuration.rho_0, + density_configuration.exponent, + ) + time_0 = density_configuration.get("time_0", time_explosion) + elif density_configuration.type == "exponential": + density_0 = calculate_exponential_density( + v_middle, density_configuration.v_0, density_configuration.rho_0 + ) + time_0 = density_configuration.get("time_0", time_explosion) + else: + raise ValueError( + f"Unrecognized density type " f"'{density_configuration.type}'" + ) + return density_0, time_0 + + +def parse_config_v1_density(config: Configuration) -> u.Quantity: + """ + Parse the configuration file and produce a density at + time_explosion. + + Parameters + ---------- + config : tardis.io.config_reader.Configuration + + Returns + ------- + density: u.Quantity + + """ + + velocity = quantity_linspace( + config.model.structure.velocity.start, + config.model.structure.velocity.stop, + config.model.structure.velocity.num + 1, + ).cgs + + adjusted_velocity = velocity.insert(0, 0) + v_middle = adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5 + time_explosion = config.supernova.time_explosion.cgs + d_conf = config.model.structure.density + density_0, time_0 = parse_density_section(d_conf, v_middle, time_explosion) + + return calculate_density_after_time(density_0, time_0, time_explosion) + + +def parse_csvy_density( + csvy_model_config: Configuration, time_explosion: u.Quantity +) -> u.Quantity: + """ + Parse the density section of the csvy file and produce a density at + time_explosion. + + Parameters + ---------- + config : tardis.io.config_reader.Configuration + csvy_model_config : tardis.io.config_reader.Configuration + + Returns + ------- + density: u.Quantity + + """ + if hasattr(csvy_model_config, "velocity"): + velocity = quantity_linspace( + csvy_model_config.velocity.start, + csvy_model_config.velocity.stop, + csvy_model_config.velocity.num + 1, + ).cgs + else: + velocity_field_index = [ + field.name for field in csvy_model_config.datatype.fields + ].index("velocity") + velocity_unit = u.Unit( + csvy_model_config.datatype.fields[velocity_field_index].unit + ) + velocity = csvy_model_config.velocity.values * velocity_unit + + adjusted_velocity = velocity.insert(0, 0) + v_middle = adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5 + no_of_shells = len(adjusted_velocity) - 1 + + if hasattr(csvy_model_config, "density"): + density_0, time_0 = parse_density_section( + csvy_model_config.density, v_middle, time_explosion + ) + return calculate_density_after_time(density_0, time_0, time_explosion) + + +def calculate_power_law_density( + velocities: u.Quantity, + velocity_0: u.Quantity, + rho_0: u.Quantity, + exponent: float, +) -> u.Quantity: + """ + + This function computes a descret exponential density profile. + :math:`\\rho = \\rho_0 \\times \\left( \\frac{v}{v_0} \\right)^n` + + Parameters + ---------- + velocities : astropy.Quantity + Array like velocity profile + velocity_0 : astropy.Quantity + reference velocity + rho_0 : astropy.Quantity + reference density + exponent : float + exponent used in the powerlaw + + Returns + ------- + densities : astropy.Quantity + + """ + densities = rho_0 * np.power((velocities / velocity_0), exponent) + return densities + + +def calculate_exponential_density( + velocities: u.Quantity, velocity_0: u.Quantity, rho_0: u.Quantity +) -> u.Quantity: + """ + This function computes the exponential density profile. + :math:`\\rho = \\rho_0 \\times \\exp \\left( -\\frac{v}{v_0} \\right)` + + Parameters + ---------- + velocities : astropy.Quantity + Array like velocity profile + velocity_0 : astropy.Quantity + reference velocity + rho_0 : astropy.Quantity + reference density + + Returns + ------- + densities : astropy.Quantity + + """ + densities = rho_0 * np.exp(-(velocities / velocity_0)) + return densities + + +def calculate_density_after_time( + densities: u.Quantity, time_0: u.Quantity, time_explosion: u.Quantity +) -> u.Quantity: + """ + scale the density from an initial time of the model to the + time of the explosion by ^-3 + + Parameters + ---------- + densities : astropy.units.Quantity + densities + time_0 : astropy.units.Quantity + time of the model + time_explosion : astropy.units.Quantity + time to be scaled to + + Returns + ------- + scaled_density : astropy.units.Quantity + in g / cm^3 + """ + + return (densities * (time_explosion / time_0) ** -3).to(u.g / (u.cm**3)) diff --git a/tardis/io/model/readers/__init__.py b/tardis/io/model/readers/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/io/parsers/arepo.py b/tardis/io/model/readers/arepo.py similarity index 63% rename from tardis/io/parsers/arepo.py rename to tardis/io/model/readers/arepo.py index 9e6b4384124..a60acd983a8 100644 --- a/tardis/io/parsers/arepo.py +++ b/tardis/io/model/readers/arepo.py @@ -1,11 +1,8 @@ import os -import sys import argparse -import warnings import numpy as np import matplotlib.pyplot as plt -import pandas as pd from scipy import stats @@ -18,9 +15,6 @@ def __init__( alpha=0.0, beta=0.0, gamma=0.0, - boxsize=1e12, - resolution=512, - numthreads=4, ): """ Loads relevant data for conversion from Arepo snapshot to a @@ -50,21 +44,10 @@ def __init__( Euler angle gamma for rotation of the desired line- of-sight to the x-axis. Only usable with snapshots. Default: 0.0 - boxsize : float - Size of the box (in cm) from which data is mapped - to a Cartesian grid. Only usable with snapshots. - Default: 1e12 - resolution : int - Resolution of the Cartesian grid. Only usable - with snapshots. Default: 512 - numthreads : int - Number of threads with which Cartesian mapping - is done. Default: 4 """ try: import gadget_snap - import calcGrid except ModuleNotFoundError: raise ImportError( "Please make sure you have arepo-snap-util installed if you want to directly import Arepo snapshots." @@ -83,6 +66,7 @@ def __init__( hdf5=True, quiet=True, lazy_load=True, + loadonlytype=[0], ) rz_yaw = np.array( @@ -112,162 +96,27 @@ def __init__( self.s.rotateto(rotmat[0], dir2=rotmat[1], dir3=rotmat[2]) self.time = self.s.time - - self.pos = np.array( - self.s.mapOnCartGrid( - "pos", - box=[boxsize, boxsize, boxsize], - center=self.s.centerofmass(), - res=resolution, - numthreads=numthreads, - ) - ) + self.pos = np.array(self.s.data["pos"]) + self.pos = self.pos.T + # Update position to CoM frame for i in range(3): self.pos[i] -= self.s.centerofmass()[i] - - self.rho = np.array( - self.s.mapOnCartGrid( - "rho", - box=[boxsize, boxsize, boxsize], - center=self.s.centerofmass(), - res=resolution, - numthreads=numthreads, - ) - ) - - self.vel = np.array( - self.s.mapOnCartGrid( - "vel", - box=[boxsize, boxsize, boxsize], - center=self.s.centerofmass(), - res=resolution, - numthreads=numthreads, - ) - ) - + self.rho = np.array(self.s.data["rho"]) + self.mass = np.array(self.s.data["mass"]) + self.vel = np.array(self.s.data["vel"]) + self.vel = self.vel.T self.nuc_dict = {} for i, spec in enumerate(self.species): self.nuc_dict[spec] = np.array( - self.nucMapOnCartGrid( - self.s, - spec, - self.spec_ind[i], - box=[boxsize, boxsize, boxsize], - res=resolution, - center=self.s.centerofmass(), - numthreads=numthreads, - ) + self.s.data["xnuc"][:, self.spec_ind[i]] ) - def nucMapOnCartGrid( - self, - snapshot, - species, - ind, - box, - res=512, - numthreads=1, - value="xnuc", - center=False, - saveas=False, - use_only_cells=None, - ): - """ - Helper funciton to extract nuclear composition from snapshots - """ - - try: - import pylab - import calcGrid - except ModuleNotFoundError: - raise ImportError( - "Please make sure you have arepo-snap-util installed if you want to directly import Arepo snapshots." - ) - if type(center) == list: - center = pylab.array(center) - elif type(center) != np.ndarray: - center = snapshot.center - - if type(box) == list: - box = pylab.array(box) - elif type(box) != np.ndarray: - box = np.array( - [snapshot.boxsize, snapshot.boxsize, snapshot.boxsize] - ) - - if type(res) == list: - res = pylab.array(res) - elif type(res) != np.ndarray: - res = np.array([res] * 3) - - if use_only_cells is None: - use_only_cells = np.arange(snapshot.nparticlesall[0], dtype="int32") - - pos = snapshot.pos[use_only_cells, :].astype("float64") - px = np.abs(pos[:, 0] - center[0]) - py = np.abs(pos[:, 1] - center[1]) - pz = np.abs(pos[:, 2] - center[2]) - - (pp,) = np.where( - (px < 0.5 * box[0]) & (py < 0.5 * box[1]) & (pz < 0.5 * box[2]) - ) - print("Selected %d of %d particles." % (pp.size, snapshot.npart)) - - posdata = pos[pp] - valdata = snapshot.data[value][use_only_cells, ind][pp].astype( - "float64" - ) - - if valdata.ndim == 1: - data = calcGrid.calcASlice( - posdata, - valdata, - nx=res[0], - ny=res[1], - nz=res[2], - boxx=box[0], - boxy=box[1], - boxz=box[2], - centerx=center[0], - centery=center[1], - centerz=center[2], - grid3D=True, - numthreads=numthreads, - ) - grid = data["grid"] - else: - # We are going to generate ndim 3D grids and stack them together - # in a grid of shape (valdata.shape[1],res,res,res) - grid = [] - for dim in range(valdata.shape[1]): - data = calcGrid.calcASlice( - posdata, - valdata[:, dim], - nx=res[0], - ny=res[1], - nz=res[2], - boxx=box[0], - boxy=box[1], - boxz=box[2], - centerx=center[0], - centery=center[1], - centerz=center[2], - grid3D=True, - numthreads=numthreads, - ) - grid.append(data["grid"]) - grid = np.stack([subgrid for subgrid in grid]) - if saveas: - grid.tofile(saveas) - - return grid - def get_grids(self): """ Returns all relevant data to create Profile objects """ - return self.pos, self.vel, self.rho, self.nuc_dict, self.time + return self.pos, self.vel, self.rho, self.mass, self.nuc_dict, self.time class Profile: @@ -276,10 +125,10 @@ class Profile: e.g. for plotting and export. """ - def __init__(self, pos, vel, rho, xnuc, time): + def __init__(self, pos, vel, rho, mass, xnuc, time): """ Parameters - ----- + ---------- pos : list of float Meshgrid of positions in center of mass frames in Cartesian coordinates @@ -287,6 +136,8 @@ def __init__(self, pos, vel, rho, xnuc, time): Meshgrid of velocities/ velocity vectors rho : list of float Meshgrid of density + mass : list of float + Meshgrid of masses. xnuc : dict Dictonary containing all the nuclear fraction meshgrids of the relevant species. @@ -300,7 +151,8 @@ def __init__(self, pos, vel, rho, xnuc, time): self.rho = rho self.xnuc = xnuc self.time = time - + self.mass = mass + self.vol = self.mass / self.rho self.species = list(self.xnuc.keys()) # Empty values to be filled with the create_profile function @@ -310,6 +162,12 @@ def __init__(self, pos, vel, rho, xnuc, time): self.vel_prof_p = None self.vel_prof_n = None + self.vol_prof_p = None + self.vol_prof_n = None + + self.mass_prof_p = None + self.mass_prof_n = None + self.rho_prof_p = None self.rho_prof_n = None @@ -321,7 +179,7 @@ def plot_profile(self, save=None, dpi=600, **kwargs): Plots profile, both in the positive and negative direction. Parameters - ----- + ---------- save : str Path under which the figure is to be saved. Default: None dpi : int @@ -329,7 +187,7 @@ def plot_profile(self, save=None, dpi=600, **kwargs): **kwargs : keywords passable to matplotlib.pyplot.plot() Returns - ----- + ------- fig : matplotlib figure object """ @@ -360,7 +218,7 @@ def plot_profile(self, save=None, dpi=600, **kwargs): ax1.set_ylabel("Profile (arb. unit)") ax1.set_title("Profiles along the positive axis") - # Positive direction plots + # Negative direction plots ax2.plot( self.pos_prof_n, self.rho_prof_n / max(self.rho_prof_n), @@ -383,8 +241,8 @@ def plot_profile(self, save=None, dpi=600, **kwargs): ax2.grid() ax2.set_ylabel("Profile (arb. unit)") - ax2.set_xlabel("Radial position (cm)") # TODO astropy unit support - ax2.set_title("Profiles along the positive axis") + ax2.set_xlabel("Radial position (cm)") + ax2.set_title("Profiles along the negative axis") # Some styling fig.tight_layout() @@ -406,64 +264,106 @@ def plot_profile(self, save=None, dpi=600, **kwargs): return fig - def rebin(self, nshells, statistic="mean"): + def rebin(self, nshells): """ Rebins the data to nshells. Uses the scipy.stats.binned_statistic to bin the data. The standard deviation of each bin can be obtained by passing the statistics="std" keyword. Parameters - ----- + ---------- nshells : int Number of bins of new data. - statistic : str - Scipy keyword for scipy.stats.binned_statistic. Default: mean Returns - ----- + ------- self : Profile object """ self.vel_prof_p, bins_p = stats.binned_statistic( self.pos_prof_p, - self.vel_prof_p, - statistic=statistic, + self.vel_prof_p * self.mass_prof_p, + statistic="mean", bins=nshells, )[:2] + self.vel_prof_p /= stats.binned_statistic( + self.pos_prof_p, + self.mass_prof_p, + statistic="mean", + bins=nshells, + )[0] self.vel_prof_n, bins_n = stats.binned_statistic( self.pos_prof_n, - self.vel_prof_n, - statistic=statistic, + self.vel_prof_n * self.mass_prof_n, + statistic="mean", bins=nshells, )[:2] + self.vel_prof_n /= stats.binned_statistic( + self.pos_prof_n, + self.mass_prof_n, + statistic="mean", + bins=nshells, + )[0] - self.rho_prof_p = stats.binned_statistic( + for spec in self.species: + self.xnuc_prof_p[spec] = ( + stats.binned_statistic( + self.pos_prof_p, + self.xnuc_prof_p[spec] * self.mass_prof_p, + statistic="mean", + bins=nshells, + )[0] + / stats.binned_statistic( + self.pos_prof_p, + self.mass_prof_p, + statistic="mean", + bins=nshells, + )[0] + ) + self.xnuc_prof_n[spec] = ( + stats.binned_statistic( + self.pos_prof_n, + self.xnuc_prof_n[spec] * self.mass_prof_n, + statistic="mean", + bins=nshells, + )[0] + / stats.binned_statistic( + self.pos_prof_n, + self.mass_prof_n, + statistic="mean", + bins=nshells, + )[0] + ) + + self.vol_prof_p = np.array( + [ + 4 / 3 * np.pi * (bins_p[i + 1] ** 3 - bins_p[i] ** 3) + for i in range(len(bins_p) - 1) + ] + ) + self.vol_prof_n = np.array( + [ + 4 / 3 * np.pi * (bins_n[i + 1] ** 3 - bins_n[i] ** 3) + for i in range(len(bins_n) - 1) + ] + ) + + self.mass_prof_p = stats.binned_statistic( self.pos_prof_p, - self.rho_prof_p, - statistic=statistic, + self.mass_prof_p, + statistic="sum", bins=nshells, )[0] - self.rho_prof_n = stats.binned_statistic( + self.mass_prof_n = stats.binned_statistic( self.pos_prof_n, - self.rho_prof_n, - statistic=statistic, + self.mass_prof_n, + statistic="sum", bins=nshells, )[0] - for spec in self.species: - self.xnuc_prof_p[spec] = stats.binned_statistic( - self.pos_prof_p, - self.xnuc_prof_p[spec], - statistic=statistic, - bins=nshells, - )[0] - self.xnuc_prof_n[spec] = stats.binned_statistic( - self.pos_prof_n, - self.xnuc_prof_n[spec], - statistic=statistic, - bins=nshells, - )[0] + self.rho_prof_p = self.mass_prof_p / self.vol_prof_p + self.rho_prof_n = self.mass_prof_n / self.vol_prof_n self.pos_prof_p = np.array( [(bins_p[i] + bins_p[i + 1]) / 2 for i in range(len(bins_p) - 1)] @@ -474,15 +374,21 @@ def rebin(self, nshells, statistic="mean"): return self - def export(self, nshells, filename, direction="pos", statistic="mean"): + def export( + self, + nshells, + filename, + direction="pos", + overwrite=False, + ): """ Function to export a profile as csvy file. Either the - positive or negative direction can be exported. Does - not overwrite existing files, saves to *(<n>).csvy + positive or negative direction can be exported. By default + does not overwrite existing files, saves to <filename>_<number>.csvy file instead. Parameters - ----- + ---------- nshells : int Number of shells to be exported. filename : str @@ -491,27 +397,27 @@ def export(self, nshells, filename, direction="pos", statistic="mean"): Specifies if either the positive or negative direction is to be exported. Available options: ['pos', 'neg']. Default: pos - statistic : str - Scipy keyword for scipy.stats.binned_statistic. If - statistic=None, data is not rebinned. Default: "mean" + overwrite: bool + If true, will overwrite if a file of the same name exists. + By default False. Returns - ----- + ------- filename : str Name of the actual saved file """ # Find a free filename - if filename.endswith(".csvy"): - filename = filename.replace(".csvy", "") + if str(filename).endswith(".csvy"): + filename = str(filename).replace(".csvy", "") - if os.path.exists("%s.csvy" % filename): + if os.path.exists(f"{filename}.csvy") and not overwrite: i = 0 - while os.path.exists("%s_%s.csvy" % (filename, i)): + while os.path.exists(f"{filename}_{i}.csvy"): i += 1 - filename = "%s_%s.csvy" % (filename, i) + filename = f"{filename}_{i}.csvy" else: - filename = "%s.csvy" % filename + filename = f"{filename}.csvy" with open(filename, "w") as f: # WRITE HEADER @@ -568,8 +474,7 @@ def export(self, nshells, filename, direction="pos", statistic="mean"): f.write("".join(datastring)) # Rebin data to nshells - if statistic is not None: - self.rebin(nshells, statistic=statistic) + self.rebin(nshells) if direction == "pos": exp = [ @@ -598,7 +503,7 @@ def export(self, nshells, filename, direction="pos", statistic="mean"): return filename - def get_profiles(): + def get_profiles(self): """Returns all profiles for manual post_processing etc.""" return ( self.pos_prof_p, @@ -607,151 +512,13 @@ def get_profiles(): self.vel_prof_n, self.rho_prof_p, self.rho_prof_n, + self.mass_prof_p, + self.mass_prof_n, self.xnuc_prof_p, self.xnuc_prof_n, ) -class LineProfile(Profile): - """ - Class for profiles extrected along a line, i.e. the x-axis. - Extends Profile. - """ - - def create_profile( - self, - inner_radius=None, - outer_radius=None, - show_plot=True, - save_plot=None, - plot_dpi=600, - ): - """ - Creates a profile along the x-axis - - Parameters - ----- - inner_radius : float - Inner radius where the profiles will be cut off. Default: None - outer_radius : float - Outer radius where the profiles will be cut off. Default: None - show_plot : bool - Specifies if a plot is to be shown after the creation of the - profile. Default: True - save_plot : str - Location where the plot is being saved. Default: None - plot_dpi : int - Dpi of the saved plot. Default: 600 - - Returns - ----- - profile : LineProfile object - - """ - - midpoint = int(np.ceil(len(self.rho) / 2)) - - # Extract radialprofiles - pos_p = np.sqrt( - (self.pos[0, midpoint, midpoint:, midpoint]) ** 2 - + (self.pos[1, midpoint, midpoint:, midpoint]) ** 2 - + (self.pos[2, midpoint, midpoint:, midpoint]) ** 2 - ) - pos_n = np.sqrt( - self.pos[0, midpoint, :midpoint, midpoint] ** 2 - + self.pos[1, midpoint, :midpoint, midpoint] ** 2 - + self.pos[2, midpoint, :midpoint, midpoint] ** 2 - ) - - vel_p = np.sqrt( - self.vel[0, midpoint, midpoint:, midpoint] ** 2 - + self.vel[1, midpoint, midpoint:, midpoint] ** 2 - + self.vel[2, midpoint, midpoint:, midpoint] ** 2 - ) - vel_n = np.sqrt( - self.vel[0, midpoint, :midpoint, midpoint] ** 2 - + self.vel[1, midpoint, :midpoint, midpoint] ** 2 - + self.vel[2, midpoint, :midpoint, midpoint] ** 2 - ) - - rho_p = self.rho[midpoint, midpoint:, midpoint] - rho_n = self.rho[midpoint, :midpoint, midpoint] - - spec_p = {} - spec_n = {} - - for spec in self.species: - spec_p[spec] = self.xnuc[spec][midpoint, midpoint:, midpoint] - spec_n[spec] = self.xnuc[spec][midpoint, :midpoint, midpoint] - - self.pos_prof_p = np.sort(pos_p) - self.pos_prof_n = np.sort(pos_n) - - if outer_radius is None: - maxradius_p = max(self.pos_prof_p) - maxradius_n = max(self.pos_prof_n) - else: - maxradius_p = outer_radius - maxradius_n = outer_radius - - if inner_radius is None: - minradius_p = min(self.pos_prof_p) - minradius_n = min(self.pos_prof_n) - else: - minradius_p = inner_radius - minradius_n = inner_radius - - mask_p = np.logical_and( - self.pos_prof_p >= minradius_p, self.pos_prof_p <= maxradius_p - ) - mask_n = np.logical_and( - self.pos_prof_n >= minradius_n, self.pos_prof_n <= maxradius_n - ) - - if not mask_p.any() or not mask_n.any(): - raise ValueError("No points left between inner and outer radius.") - - self.rho_prof_p = np.array( - [x for _, x in sorted(zip(pos_p, rho_p), key=lambda pair: pair[0])] - )[mask_p] - self.rho_prof_n = np.array( - [x for _, x in sorted(zip(pos_n, rho_n), key=lambda pair: pair[0])] - )[mask_n] - - self.vel_prof_p = np.array( - [x for _, x in sorted(zip(pos_p, vel_p), key=lambda pair: pair[0])] - )[mask_p] - self.vel_prof_n = np.array( - [x for _, x in sorted(zip(pos_n, vel_n), key=lambda pair: pair[0])] - )[mask_n] - - for spec in self.species: - self.xnuc_prof_p[spec] = np.array( - [ - x - for _, x in sorted( - zip(pos_p, spec_p[spec]), key=lambda pair: pair[0] - ) - ] - )[mask_p] - self.xnuc_prof_n[spec] = np.array( - [ - x - for _, x in sorted( - zip(pos_n, spec_n[spec]), key=lambda pair: pair[0] - ) - ] - )[mask_n] - - self.pos_prof_p = self.pos_prof_p[mask_p] - self.pos_prof_n = self.pos_prof_n[mask_n] - - if show_plot: - self.plot_profile(save=save_plot, dpi=plot_dpi) - - return self - - class ConeProfile(Profile): """ Class for profiles extracted inside a cone around the x-axis. @@ -771,7 +538,7 @@ def create_profile( Creates a profile along the x-axis without any averaging Parameters - ----- + ---------- opening_angle : float Opening angle (in degrees) of the cone from which the data is extracted. Refers to the total opening angle, not @@ -780,17 +547,10 @@ def create_profile( Inner radius where the profiles will be cut off. Default: None outer_radius : float Outer radius where the profiles will be cut off. Default: None - show_plot : bool - Specifies if a plot is to be shown after the creation of the - profile. Default: True - save_plot : str - Location where the plot is being saved. Default: None - plot_dpi : int - Dpi of the saved plot. Default: 600 Returns - ----- - profile : LineProfile object + ------- + profile : ConeProfile object """ @@ -834,6 +594,12 @@ def create_profile( + self.vel[2][cmask_n] ** 2 ) + vol_p = self.vol[cmask_p] + vol_n = self.vol[cmask_n] + + mass_p = self.mass[cmask_p] + mass_n = self.mass[cmask_n] + rho_p = self.rho[cmask_p] rho_n = self.rho[cmask_n] @@ -871,6 +637,20 @@ def create_profile( if not mask_p.any() or not mask_n.any(): raise ValueError("No points left between inner and outer radius.") + self.vol_prof_p = np.array( + [x for _, x in sorted(zip(pos_p, vol_p), key=lambda pair: pair[0])] + )[mask_p] + self.vol_prof_n = np.array( + [x for _, x in sorted(zip(pos_n, vol_n), key=lambda pair: pair[0])] + )[mask_n] + + self.mass_prof_p = np.array( + [x for _, x in sorted(zip(pos_p, mass_p), key=lambda pair: pair[0])] + )[mask_p] + self.mass_prof_n = np.array( + [x for _, x in sorted(zip(pos_n, mass_n), key=lambda pair: pair[0])] + )[mask_n] + self.rho_prof_p = np.array( [x for _, x in sorted(zip(pos_p, rho_p), key=lambda pair: pair[0])] )[mask_p] @@ -906,9 +686,6 @@ def create_profile( self.pos_prof_p = self.pos_prof_p[mask_p] self.pos_prof_n = self.pos_prof_n[mask_n] - if show_plot: - self.plot_profile(save=save_plot, dpi=plot_dpi) - return self @@ -932,22 +709,15 @@ def create_profile( direction are identical. Parameters - ----- + ---------- inner_radius : float Inner radius where the profiles will be cut off. Default: None outer_radius : float Outer radius where the profiles will be cut off. Default: None - show_plot : bool - Specifies if a plot is to be shown after the creation of the - profile. Default: True - save_plot : str - Location where the plot is being saved. Default: None - plot_dpi : int - Dpi of the saved plot. Default: 600 Returns - ----- - profile : LineProfile object + ------- + profile : FullProfile object """ @@ -965,6 +735,12 @@ def create_profile( self.vel[0] ** 2 + self.vel[1] ** 2 + self.vel[2] ** 2 ).flatten() + vol_p = self.vol.flatten() + vol_n = self.vol.flatten() + + mass_p = self.mass.flatten() + mass_n = self.mass.flatten() + rho_p = self.rho.flatten() rho_n = self.rho.flatten() @@ -1002,6 +778,20 @@ def create_profile( if not mask_p.any() or not mask_n.any(): raise ValueError("No points left between inner and outer radius.") + self.vol_prof_p = np.array( + [x for _, x in sorted(zip(pos_p, vol_p), key=lambda pair: pair[0])] + )[mask_p] + self.vol_prof_n = np.array( + [x for _, x in sorted(zip(pos_n, vol_n), key=lambda pair: pair[0])] + )[mask_n] + + self.mass_prof_p = np.array( + [x for _, x in sorted(zip(pos_p, mass_p), key=lambda pair: pair[0])] + )[mask_p] + self.mass_prof_n = np.array( + [x for _, x in sorted(zip(pos_n, mass_n), key=lambda pair: pair[0])] + )[mask_n] + self.rho_prof_p = np.array( [x for _, x in sorted(zip(pos_p, rho_p), key=lambda pair: pair[0])] )[mask_p] @@ -1037,9 +827,6 @@ def create_profile( self.pos_prof_p = self.pos_prof_p[mask_p] self.pos_prof_n = self.pos_prof_n[mask_n] - if show_plot: - self.plot_profile(save=save_plot, dpi=plot_dpi) - return self @@ -1120,29 +907,14 @@ def create_profile( ) parser.add_argument( "--profile", - help="How to build profile. Available options: [line, cone, full]. Default: cone", + help="How to build profile. Available options: [cone, full]. Default: cone", default="cone", - choices=["line", "cone", "full"], - ) - parser.add_argument( - "--resolution", - help="Resolution of Cartesian grid extracted from snapshot. Default: 512", - type=int, - default=512, + choices=["cone", "full"], ) - parser.add_argument( - "--numthreads", - help="Number of threads used in snapshot tree walk. Default: 4", - type=int, - default=4, - ) - parser.add_argument("--save_plot", help="File name of saved plot.") + parser.add_argument("--plot", help="File name of saved plot.") parser.add_argument( "--dpi", help="Dpi of saved plot. Default: 600", type=int, default=600 ) - parser.add_argument( - "--plot_rebinned", help="File name of plot after rebinning" - ) args = parser.parse_args() @@ -1158,32 +930,26 @@ def create_profile( numthreads=args.numthreads, ) - pos, vel, rho, xnuc, time = snapshot.get_grids() + pos, vel, rho, mass, xnuc, time = snapshot.get_grids() - if args.profile == "line": - profile = LineProfile(pos, vel, rho, xnuc, time) - elif args.profile == "cone": - profile = ConeProfile(pos, vel, rho, xnuc, time) + if args.profile == "cone": + profile = ConeProfile(pos, vel, rho, xnuc, time, mass=mass) elif args.profile == "full": - profile = FullProfile(pos, vel, rho, xnuc, time) + profile = FullProfile(pos, vel, rho, xnuc, time, mass=mass) if args.profile == "cone": profile.create_profile( opening_angle=args.opening_angle, inner_radius=args.inner_radius, outer_radius=args.outer_radius, - save_plot=args.save_plot, - plot_dpi=args.dpi, ) else: profile.create_profile( inner_radius=args.inner_radius, outer_radius=args.outer_radius, - save_plot=args.save_plot, - plot_dpi=args.dpi, ) profile.export(args.nshells, args.save) - if args.plot_rebinned: - profile.plot_profile(save=args.plot_rebinned, dpi=args.dpi) + if args.plot: + profile.plot_profile(save=args.plot, dpi=args.dpi) diff --git a/tardis/io/model/readers/artis.py b/tardis/io/model/readers/artis.py new file mode 100644 index 00000000000..21a353d0d94 --- /dev/null +++ b/tardis/io/model/readers/artis.py @@ -0,0 +1,65 @@ +import numpy as np +from astropy import units as u +import pandas as pd + + +def read_artis_density(fname): + """ + Reading a density file of the following structure (example; lines starting with a hash will be ignored): + The first density describes the mean density in the center of the model and is not used. + 5 + #index velocity [km/s] log10(density) [log10(g/cm^3)] + 0 1.1e4 1.6e8 + 1 1.2e4 1.7e8 + + Parameters + ---------- + fname : str + filename or path with filename + + Returns + ------- + time_of_model : astropy.units.Quantity + time at which the model is valid + data : pandas.DataFrame + data frame containing index, velocity (in km/s) and density + """ + + with open(fname) as fh: + for i, line in enumerate(open(fname)): + if i == 0: + no_of_shells = np.int64(line.strip()) + elif i == 1: + time_of_model = u.Quantity(float(line.strip()), "day").to("s") + elif i == 2: + break + + artis_model_columns = [ + "index", + "velocities", + "mean_densities_0", + "ni56_fraction", + "co56_fraction", + "fe52_fraction", + "cr48_fraction", + ] + + artis_model = pd.read_csv( + fname, + skiprows=2, + usecols=(0, 1, 2, 4, 5, 6, 7), + dtype={item: np.float64 for item in artis_model_columns}, + names=artis_model_columns, + # The argument `delim_whitespace` was changed to `sep` + # because the first one is deprecated since version 2.2.0. + # The regular expression means: the separation is one or + # more spaces together (simple space, tabs, new lines). + sep=r"\s+", + ).to_records(index=False) + + velocity = u.Quantity(artis_model["velocities"], "km/s").to("cm/s") + mean_density = u.Quantity(10 ** artis_model["mean_densities_0"], "g/cm^3")[ + 1: + ] + + return time_of_model, velocity, mean_density diff --git a/tardis/io/model/readers/base.py b/tardis/io/model/readers/base.py new file mode 100644 index 00000000000..c66da4b2b03 --- /dev/null +++ b/tardis/io/model/readers/base.py @@ -0,0 +1,133 @@ +from tardis.io.model.readers.cmfgen import ( + read_cmfgen_composition, + read_cmfgen_density, +) +from tardis.io.model.readers.generic_readers import ( + ConfigurationError, + read_csv_composition, + read_simple_ascii_abundances, + read_simple_ascii_density, +) + + +import numpy as np +import pandas as pd + +from tardis.io.model.readers.artis import read_artis_density + + +def read_abundances_file( + abundance_filename, + abundance_filetype, + inner_boundary_index=None, + outer_boundary_index=None, +): + """ + read different density file formats + + Parameters + ---------- + abundance_filename : str + filename or path of the density file + abundance_filetype : str + type of the density file + inner_boundary_index : int + index of the inner shell, default None + outer_boundary_index : int + index of the outer shell, default None + """ + + file_parsers = { + "simple_ascii": read_simple_ascii_abundances, + "artis": read_simple_ascii_abundances, + "cmfgen_model": read_cmfgen_composition, + "custom_composition": read_csv_composition, + } + + isotope_abundance = pd.DataFrame() + if abundance_filetype in ["cmfgen_model", "custom_composition"]: + index, abundances, isotope_abundance = file_parsers[abundance_filetype]( + abundance_filename + ) + else: + index, abundances = file_parsers[abundance_filetype](abundance_filename) + + if outer_boundary_index is not None: + outer_boundary_index_m1 = outer_boundary_index - 1 + else: + outer_boundary_index_m1 = None + index = index[inner_boundary_index:outer_boundary_index] + abundances = abundances.loc[ + :, slice(inner_boundary_index, outer_boundary_index_m1) + ] + abundances.columns = np.arange(len(abundances.columns)) + return index, abundances, isotope_abundance + + +def read_density_file(filename, filetype): + """ + read different density file formats + + Parameters + ---------- + filename : str + filename or path of the density file + filetype : str + type of the density file + + Returns + ------- + time_of_model : astropy.units.Quantity + time at which the model is valid + velocity : np.ndarray + the array containing the velocities + unscaled_mean_densities : np.ndarray + the array containing the densities + """ + file_parsers = { + "artis": read_artis_density, + "simple_ascii": read_simple_ascii_density, + "cmfgen_model": read_cmfgen_density, + } + + electron_densities = None + temperature = None + if filetype == "cmfgen_model": + ( + time_of_model, + velocity, + unscaled_mean_densities, + electron_densities, + temperature, + ) = read_cmfgen_density(filename) + else: + (time_of_model, velocity, unscaled_mean_densities) = file_parsers[ + filetype + ](filename) + + v_inner = velocity[:-1] + v_outer = velocity[1:] + + invalid_volume_mask = (v_outer - v_inner) <= 0 + if invalid_volume_mask.sum() > 0: + message = "\n".join( + [ + f"cell {i:d}: v_inner {v_inner_i:s}, v_outer " f"{v_outer_i:s}" + for i, v_inner_i, v_outer_i in zip( + np.arange(len(v_outer))[invalid_volume_mask], + v_inner[invalid_volume_mask], + v_outer[invalid_volume_mask], + ) + ] + ) + raise ConfigurationError( + "Invalid volume of following cell(s):\n" f"{message:s}" + ) + + return ( + time_of_model, + velocity, + unscaled_mean_densities, + electron_densities, + temperature, + ) diff --git a/tardis/io/parsers/blondin_toymodel.py b/tardis/io/model/readers/blondin_toymodel.py similarity index 92% rename from tardis/io/parsers/blondin_toymodel.py rename to tardis/io/model/readers/blondin_toymodel.py index be2437e9b9e..d58ba5d2250 100644 --- a/tardis/io/parsers/blondin_toymodel.py +++ b/tardis/io/model/readers/blondin_toymodel.py @@ -1,10 +1,8 @@ import re -import yaml - import numpy as np import pandas as pd - +import yaml from astropy import units as u from tardis.util.base import parse_quantity @@ -44,7 +42,15 @@ def read_blondin_toymodel(fname): ] raw_blondin_csv = pd.read_csv( - fname, delim_whitespace=True, comment="#", header=None, names=columns + fname, + # The argument `delim_whitespace` was changed to `sep` + # because the first one is deprecated since version 2.2.0. + # The regular expression means: the separation is one or + # more spaces together (simple space, tabs, new lines). + sep=r"\s+", + comment="#", + header=None, + names=columns, ) raw_blondin_csv.set_index("idx", inplace=True) diff --git a/tardis/io/model/readers/cmfgen.py b/tardis/io/model/readers/cmfgen.py new file mode 100644 index 00000000000..d11abbb0c9b --- /dev/null +++ b/tardis/io/model/readers/cmfgen.py @@ -0,0 +1,91 @@ +from tardis.io.model.readers.util import read_csv_isotope_abundances +from tardis.util.base import parse_quantity + + +import pandas as pd +from astropy import units as u + + +import warnings + + +def read_cmfgen_density(fname: str): + """ + Reading a density file of the following structure (example; lines starting with a hash will be ignored): + The first density describes the mean density in the center of the model and is not used. + The file consists of a header row and next row contains unit of the respective attributes + Note that the first column has to contain a running index + + Example: + + index velocity densities electron_densities temperature + - km/s g/cm^3 /cm^3 K + 0 871.66905 4.2537191e-09 2.5953807e+14 7.6395577 + 1 877.44269 4.2537191e-09 2.5953807e+14 7.6395577 + + Rest columns contain abundances of elements and isotopes + + Parameters + ---------- + fname : str + filename or path with filename + + Returns + ------- + time_of_model : astropy.units.Quantity + time at which the model is valid + velocity : np.ndarray + mean_density : np.ndarray + electron_densities : np.ndarray + temperature : np.ndarray + """ + warnings.warn( + "The current CMFGEN model parser is deprecated", DeprecationWarning + ) + + df = pd.read_csv(fname, comment="#", delimiter=r"\s+", skiprows=[0, 2]) + + with open(fname) as fh: + for row_index, line in enumerate(fh): + if row_index == 0: + time_of_model_string = line.strip().replace("t0:", "") + time_of_model = parse_quantity(time_of_model_string) + elif row_index == 2: + quantities = line.split() + + velocity = u.Quantity(df["velocity"].values, quantities[1]).to("cm/s") + temperature = u.Quantity(df["temperature"].values, quantities[2])[1:] + mean_density = u.Quantity(df["densities"].values, quantities[3])[1:] + electron_densities = u.Quantity( + df["electron_densities"].values, quantities[4] + )[1:] + + return ( + time_of_model, + velocity, + mean_density, + electron_densities, + temperature, + ) + + +def read_cmfgen_composition(fname, delimiter=r"\s+"): + """Read composition from a CMFGEN model file + + The CMFGEN file format contains information about the ejecta state in the + first four columns and the following ones contain elemental and isotopic + abundances. + + WARNING : deprecated + + fname : str + filename of the csv file + """ + + warnings.warn( + "The current CMFGEN model parser is deprecated", DeprecationWarning + ) + + return read_csv_isotope_abundances( + fname, delimiter=delimiter, skip_columns=4, skip_rows=[0, 2, 3] + ) diff --git a/tardis/io/parsers/csvy.py b/tardis/io/model/readers/csvy.py similarity index 57% rename from tardis/io/parsers/csvy.py rename to tardis/io/model/readers/csvy.py index 97e7a9eec95..fa6f350497e 100644 --- a/tardis/io/parsers/csvy.py +++ b/tardis/io/model/readers/csvy.py @@ -1,7 +1,11 @@ import logging +import numpy as np +from radioactivedecay import Nuclide +from radioactivedecay.utils import Z_DICT, elem_to_Z import yaml import pandas as pd from tardis.io.util import YAMLLoader +from tardis.util.base import is_valid_nuclide_or_elem YAML_DELIMITER = "---" @@ -40,7 +44,7 @@ def load_csvy(fname): try: data = pd.read_csv(fname, skiprows=yaml_end_ind + 1) except pd.errors.EmptyDataError as e: - logger.debug(f"Could not Read CSV. Setting Dataframe to None") + logger.debug("Could not Read CSV. Setting Dataframe to None") data = None return yaml_dict, data @@ -90,3 +94,53 @@ def load_csv_from_csvy(fname): """ yaml_dict, data = load_csvy(fname) return data + + +def parse_csv_abundances(csvy_data): + """ + A parser for the csv data part of a csvy model file. This function filters out columns that are not abundances. + + Parameters + ---------- + csvy_data : pandas.DataFrame + + Returns + ------- + index : np.ndarray + abundances : pandas.DataFrame + isotope_abundance : pandas.MultiIndex + """ + + abundance_col_names = [ + name for name in csvy_data.columns if is_valid_nuclide_or_elem(name) + ] + df = csvy_data.loc[:, abundance_col_names] + + df = df.transpose() + + abundance = pd.DataFrame( + columns=np.arange(df.shape[1]), + index=pd.Index([], name="atomic_number"), + dtype=np.float64, + ) + + isotope_index = pd.MultiIndex( + [[]] * 2, [[]] * 2, names=["atomic_number", "mass_number"] + ) + isotope_abundance = pd.DataFrame( + columns=np.arange(df.shape[1]), index=isotope_index, dtype=np.float64 + ) + + for element_symbol_string in df.index[0:]: + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) + abundance.loc[z, :] = df.loc[element_symbol_string].tolist() + else: + nuc = Nuclide(element_symbol_string) + z = nuc.Z + mass_no = nuc.A + isotope_abundance.loc[(z, mass_no), :] = df.loc[ + element_symbol_string + ].tolist() + + return abundance.index, abundance, isotope_abundance diff --git a/tardis/io/model/readers/generic_readers.py b/tardis/io/model/readers/generic_readers.py new file mode 100644 index 00000000000..6f037522127 --- /dev/null +++ b/tardis/io/model/readers/generic_readers.py @@ -0,0 +1,158 @@ +from astropy import units as u +from typing import Any, Tuple +from numpy import recfromtxt +import pandas as pd +from radioactivedecay import Nuclide +from radioactivedecay.utils import Z_DICT, elem_to_Z +from pathlib import Path + +import numpy as np +from tardis.io.model.readers.util import read_csv_isotope_abundances + +from tardis.util.base import parse_quantity + + +class ConfigurationError(Exception): + pass + + +def read_simple_ascii_density( + fname: Any, +) -> Tuple[u.Quantity, u.Quantity, u.Quantity]: + """ + Reading a density file of the following structure (example; lines starting with a hash will be ignored): + The first density describes the mean density in the center of the model and is not used. + 5 s + #index velocity [km/s] density [g/cm^3] + 0 1.1e4 1.6e8 + 1 1.2e4 1.7e8 + + Parameters + ---------- + fname : str + filename or path with filename + + Returns + ------- + time_of_model : astropy.units.Quantity + time at which the model is valid + velocity : u.Quantity + velocity + mean_density: u.Quantity + mean density + """ + + with open(fname) as fh: + time_of_model_string = fh.readline().strip() + time_of_model = parse_quantity(time_of_model_string) + + data = recfromtxt( + fname, + skip_header=1, + names=("index", "velocity", "density"), + dtype=(int, float, float), + ) + velocity = (data["velocity"] * u.km / u.s).to("cm/s") + mean_density = (data["density"] * u.Unit("g/cm^3"))[1:] + + return time_of_model, velocity, mean_density + + +def read_csv_composition(fname, delimiter=r"\s+"): + """Read composition from a simple CSV file + + The CSV file can contain specific isotopes or elemental abundances in the + different columns. The first row must contain the header in which the + contents of each column is specified by the elemental symbol (for elemental + abundances) or by the symbol plus mass number (for isotopic abundances). + + Example: C O Fe Ni56 Co + + The i-th row specifies the composition in the i-th shell + + fname : str + filename of the csv file + """ + + return read_csv_isotope_abundances( + fname, delimiter=delimiter, skip_columns=0, skip_rows=[1] + ) + + +def read_simple_ascii_abundances(fname): + """ + Reading an abundance file of the following structure (example; lines starting with hash will be ignored): + The first line of abundances describe the abundances in the center of the model and are not used. + #index element1, element2, ..., element30 + 0 0.4 0.3, .. 0.2 + + Parameters + ---------- + fname : str + filename or path with filename + + Returns + ------- + index : np.ndarray + containing the indices + abundances : pandas.DataFrame + data frame containing index, element1 - element30 and columns according to the shells + """ + data = np.loadtxt(fname) + + index = data[1:, 0].astype(int) + abundances = pd.DataFrame( + data[1:, 1:].transpose(), index=np.arange(1, data.shape[1]) + ) + + return index, abundances + + +def read_uniform_abundances(abundances_section, no_of_shells): + """ + Parameters + ---------- + abundances_section : config.model.abundances + no_of_shells : int + + Returns + ------- + abundance : pandas.DataFrame + isotope_abundance : pandas.DataFrame + """ + abundance = pd.DataFrame( + columns=np.arange(no_of_shells), + index=pd.Index(np.arange(1, 120), name="atomic_number"), + dtype=np.float64, + ) + + isotope_index = pd.MultiIndex( + [[]] * 2, [[]] * 2, names=["atomic_number", "mass_number"] + ) + isotope_abundance = pd.DataFrame( + columns=np.arange(no_of_shells), index=isotope_index, dtype=np.float64 + ) + + for element_symbol_string in abundances_section: + if element_symbol_string in ["type", "model_isotope_time_0"]: + continue + try: + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) + abundance.loc[z] = float( + abundances_section[element_symbol_string] + ) + else: + nuc = Nuclide(element_symbol_string) + mass_no = nuc.A + z = nuc.Z + isotope_abundance.loc[(z, mass_no), :] = float( + abundances_section[element_symbol_string] + ) + + except RuntimeError as err: + raise RuntimeError( + f"Abundances are not defined properly in config file : {err.args}" + ) + + return abundance, isotope_abundance diff --git a/tardis/io/model/readers/stella.py b/tardis/io/model/readers/stella.py new file mode 100644 index 00000000000..e314e716e3b --- /dev/null +++ b/tardis/io/model/readers/stella.py @@ -0,0 +1,87 @@ +import re +from dataclasses import dataclass + +import pandas as pd +from astropy import units as u + + +@dataclass +class STELLAModel: + metadata: dict + data: pd.DataFrame + + +HEADER_RE_STR = [ + ("\s+days post max Lbol\s+(\d+\.\d*)", "t_max"), + ("\s+zones\s+(\d+)", "zones"), + ( + "\s+inner boundary mass\s+(\d+\.\d+E[+-]\d+)\s+\d+\.\d+E[+-]\d+", + "inner_boundary_mass", + ), + ("\s+total mass\s+(\d+\.\d+E[+-]\d+)\s+\d+\.\d+E[+-]\d+", "total_mass"), +] + +DATA_START_ROW = 5 +COLUMN_WITH_UNIT_RE = re.compile("(.+)\s+\((.+)\)") + + +def read_stella_model(fname): + """ + Read in a STELLA model file and return the data and model + + Parameters + ---------- + + fname : str + + Returns + ------- + model : STELLAModel + + """ + header_re = [re.compile(re_str[0]) for re_str in HEADER_RE_STR] + metadata = {} + with open(fname) as fh: + for i, line in enumerate(fh): + if i < len(HEADER_RE_STR): + header_re_match = header_re[i].match(line) + metadata[HEADER_RE_STR[i][1]] = header_re_match.group(1) + elif i == DATA_START_ROW: + if "mass of cell" in line: + column_names_raw = re.split(r"\s{3,}", line.strip()) + break + else: + raise ValueError( + '"mass of cell" is required in the Stella input file to infer columns' + ) + + metadata["t_max"] = float(metadata["t_max"]) * u.day + metadata["zones"] = int(metadata["zones"]) + metadata["inner_boundary_mass"] = ( + float(metadata["inner_boundary_mass"]) * u.g + ) + metadata["total_mass"] = float(metadata["total_mass"]) * u.g + column_names = [] + for column_name in column_names_raw: + if (column_match := COLUMN_WITH_UNIT_RE.match(column_name)) is not None: + column_name, column_unit = column_match.groups() + column_name = column_name.lower().replace(" ", "_") + metadata[f"{column_name}_unit"] = u.Unit(column_unit) + else: + column_name = column_name.lower().replace(" ", "_") + column_names.append(column_name) + # +1 because there is a missing line between columns + # and the actual data + data = pd.read_csv( + fname, + # The argument `delim_whitespace` was changed to `sep` + # because the first one is deprecated since version 2.2.0. + # The regular expression means: the separation is one or + # more spaces together (simple space, tabs, new lines). + sep=r"\s+", + skiprows=DATA_START_ROW + 1, + header=None, + index_col=0, + ) + data.columns = column_names + return STELLAModel(metadata, data) diff --git a/tardis/io/tests/data/abund.dat b/tardis/io/model/readers/tests/data/abund.dat similarity index 100% rename from tardis/io/tests/data/abund.dat rename to tardis/io/model/readers/tests/data/abund.dat diff --git a/tardis/io/model/readers/tests/data/arepo_cone_reference_model.csvy b/tardis/io/model/readers/tests/data/arepo_cone_reference_model.csvy new file mode 100644 index 00000000000..839679159ec --- /dev/null +++ b/tardis/io/model/readers/tests/data/arepo_cone_reference_model.csvy @@ -0,0 +1,41 @@ +--- +name: csvy_full +model_density_time_0: 0.00115628 day +model_isotope_time_0: 0.666016 day +description: Config file for TARDIS from Arepo snapshot. +tardis_model_config_version: v1.0 +datatype: + fields: + - name: velocity + unit: cm/s + desc: velocities of shell outer bounderies. + - name: density + unit: g/cm^3 + desc: density of shell. + - name: Ni56 + desc: fractional Ni56 abundance. + - name: Si28 + desc: fractional Si28 abundance. + +--- +velocity,density,Ni56,Si28 +1.02744e+09,0.039332,0.784383,0.0458134 +1.07784e+09,0.0360818,0.608716,0.113525 +1.12803e+09,0.0334366,0.369558,0.231707 +1.1779e+09,0.0300155,0.190785,0.348145 +1.2279e+09,0.0256713,0.121151,0.408203 +1.2781e+09,0.0212718,0.0992874,0.431875 +1.32831e+09,0.0178633,0.0794732,0.455453 +1.37856e+09,0.0149001,0.0573543,0.462553 +1.42874e+09,0.0120893,0.028824,0.44569 +1.47872e+09,0.00986893,0.00774774,0.437655 +1.52935e+09,0.00835016,0.000694398,0.465911 +1.58016e+09,0.0081748,1.77478e-05,0.476364 +1.62958e+09,0.00811114,4.8074e-07,0.415122 +1.67864e+09,0.00625829,2.06007e-08,0.313869 +1.72832e+09,0.00423129,1.79194e-09,0.255375 +1.77909e+09,0.00278635,3.505e-10,0.235798 +1.82952e+09,0.00188048,1.06163e-10,0.227405 +1.87985e+09,0.00137231,4.77628e-11,0.218543 +1.93045e+09,0.00100844,2.41338e-11,0.204091 +1.98087e+09,0.000773981,1.42833e-11,0.182151 \ No newline at end of file diff --git a/tardis/io/model/readers/tests/data/arepo_full_reference_model.csvy b/tardis/io/model/readers/tests/data/arepo_full_reference_model.csvy new file mode 100644 index 00000000000..7190f69f071 --- /dev/null +++ b/tardis/io/model/readers/tests/data/arepo_full_reference_model.csvy @@ -0,0 +1,41 @@ +--- +name: csvy_full +model_density_time_0: 0.00115628 day +model_isotope_time_0: 0.666016 day +description: Config file for TARDIS from Arepo snapshot. +tardis_model_config_version: v1.0 +datatype: + fields: + - name: velocity + unit: cm/s + desc: velocities of shell outer bounderies. + - name: density + unit: g/cm^3 + desc: density of shell. + - name: Ni56 + desc: fractional Ni56 abundance. + - name: Si28 + desc: fractional Si28 abundance. + +--- +velocity,density,Ni56,Si28 +1.02747e+09,0.13239,0.77535,0.0488426 +1.07785e+09,0.121578,0.595052,0.119454 +1.12801e+09,0.112464,0.357839,0.238383 +1.17797e+09,0.101018,0.187417,0.35065 +1.22799e+09,0.0859403,0.122805,0.406581 +1.27824e+09,0.0715324,0.0987663,0.432529 +1.32838e+09,0.0599251,0.0793296,0.455739 +1.37854e+09,0.0500307,0.0578175,0.462666 +1.42874e+09,0.0409597,0.029732,0.446131 +1.47883e+09,0.0333024,0.00843821,0.437218 +1.52929e+09,0.0278937,0.000858721,0.463055 +1.58012e+09,0.0273047,2.49168e-05,0.478132 +1.62976e+09,0.027074,6.84567e-07,0.424118 +1.67886e+09,0.021613,3.11138e-08,0.325808 +1.72867e+09,0.0147779,2.6524e-09,0.260981 +1.77903e+09,0.00987771,4.84336e-10,0.238098 +1.82971e+09,0.00685711,1.42244e-10,0.228703 +1.88009e+09,0.00488457,5.92117e-11,0.220137 +1.93084e+09,0.00369041,3.0944e-11,0.206345 +1.98142e+09,0.00271805,1.68858e-11,0.18518 \ No newline at end of file diff --git a/tardis/io/tests/data/artis_abundances.dat b/tardis/io/model/readers/tests/data/artis_abundances.dat similarity index 100% rename from tardis/io/tests/data/artis_abundances.dat rename to tardis/io/model/readers/tests/data/artis_abundances.dat diff --git a/tardis/io/tests/data/artis_model.dat b/tardis/io/model/readers/tests/data/artis_model.dat similarity index 100% rename from tardis/io/tests/data/artis_model.dat rename to tardis/io/model/readers/tests/data/artis_model.dat diff --git a/tardis/io/tests/data/cmfgen_model.csv b/tardis/io/model/readers/tests/data/cmfgen_model.csv similarity index 100% rename from tardis/io/tests/data/cmfgen_model.csv rename to tardis/io/model/readers/tests/data/cmfgen_model.csv diff --git a/tardis/io/tests/data/conf_def.yml b/tardis/io/model/readers/tests/data/conf_def.yml similarity index 100% rename from tardis/io/tests/data/conf_def.yml rename to tardis/io/model/readers/tests/data/conf_def.yml diff --git a/tardis/io/tests/data/conf_tes.yml b/tardis/io/model/readers/tests/data/conf_tes.yml similarity index 100% rename from tardis/io/tests/data/conf_tes.yml rename to tardis/io/model/readers/tests/data/conf_tes.yml diff --git a/tardis/io/tests/data/csv_composition.csv b/tardis/io/model/readers/tests/data/csv_composition.csv similarity index 100% rename from tardis/io/tests/data/csv_composition.csv rename to tardis/io/model/readers/tests/data/csv_composition.csv diff --git a/tardis/io/tests/data/csvy_full.csvy b/tardis/io/model/readers/tests/data/csvy_full.csvy similarity index 100% rename from tardis/io/tests/data/csvy_full.csvy rename to tardis/io/model/readers/tests/data/csvy_full.csvy diff --git a/tardis/io/tests/data/csvy_missing.csvy b/tardis/io/model/readers/tests/data/csvy_missing.csvy similarity index 100% rename from tardis/io/tests/data/csvy_missing.csvy rename to tardis/io/model/readers/tests/data/csvy_missing.csvy diff --git a/tardis/io/tests/data/csvy_nocsv.csvy b/tardis/io/model/readers/tests/data/csvy_nocsv.csvy similarity index 100% rename from tardis/io/tests/data/csvy_nocsv.csvy rename to tardis/io/model/readers/tests/data/csvy_nocsv.csvy diff --git a/tardis/io/tests/data/csvy_test_config.yml b/tardis/io/model/readers/tests/data/csvy_test_config.yml similarity index 100% rename from tardis/io/tests/data/csvy_test_config.yml rename to tardis/io/model/readers/tests/data/csvy_test_config.yml diff --git a/tardis/io/tests/data/density.dat b/tardis/io/model/readers/tests/data/density.dat similarity index 100% rename from tardis/io/tests/data/density.dat rename to tardis/io/model/readers/tests/data/density.dat diff --git a/tardis/io/tests/data/invalid_artis_model.dat b/tardis/io/model/readers/tests/data/invalid_artis_model.dat similarity index 100% rename from tardis/io/tests/data/invalid_artis_model.dat rename to tardis/io/model/readers/tests/data/invalid_artis_model.dat diff --git a/tardis/io/model/readers/tests/data/mesa.stella.dat b/tardis/io/model/readers/tests/data/mesa.stella.dat new file mode 100644 index 00000000000..0e0b4e74ca0 --- /dev/null +++ b/tardis/io/model/readers/tests/data/mesa.stella.dat @@ -0,0 +1,407 @@ + days post max Lbol 50.0 + zones 400 + inner boundary mass 5.190242521200000E+33 2.609211000000000E+00 + total mass 2.618867335600000E+34 1.316543000000000E+01 + + mass of cell (g) cell center m (g) cell center R (cm) cell center v (cm/s) avg density radiation pressure avg temperature radiation temperature avg opacity tau outer edge m (g) outer edge r (cm) h1 he3 he4 c12 n14 o16 ne20 na23 mg24 si28 s32 ar36 ca40 ti44 cr48 cr60 fe52 fe54 fe56 co56 ni56 luminosity n_bar n_e + + 1 6.006769337200000E+29 5.190242521200000E+33 2.517208995922069E+13 3.930633463858500E+06 1.005529258105087E-11 1.123795450558407E+04 4.594345302259182E+04 4.594345302259182E+04 1.627115175247000E-01 5.403504880532457E+03 5.190874092200000E+33 2.743917483671189E+13 3.464691000000000E-05 0.000000000000000E+00 5.800994000000000E-01 1.190353000000000E-01 7.025597000000000E-07 2.461590000000000E-01 6.333397000000000E-03 3.274956000000000E-08 7.388660000000000E-03 3.112645000000000E-02 5.069225000000000E-03 4.829527000000000E-04 1.696820000000000E-04 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 2.070970000000000E-05 0.000000000000000E+00 4.079500000000000E-03 7.648868494018999E+38 6.055413236609000E+12 2.412188329693000E+12 + 2 1.262405996000000E+30 5.191505663200000E+33 2.970625971420310E+13 5.050403113364500E+06 2.928088214842606E-11 1.123654402180205E+04 4.594218222923182E+04 4.594218222923182E+04 1.644115175247000E-01 5.381678444417913E+03 5.192138228800000E+33 3.084752490934893E+13 3.464691000000000E-05 0.000000000000000E+00 5.800994000000000E-01 1.190353000000000E-01 7.025597000000000E-07 2.461590000000000E-01 6.333397000000000E-03 3.274956000000000E-08 7.388660000000000E-03 3.112645000000000E-02 5.069225000000000E-03 4.829527000000000E-04 1.696820000000000E-04 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 2.070970000000000E-05 0.000000000000000E+00 4.079500000000000E-03 9.609214019760001E+38 1.762303504940000E+13 6.969789895995001E+12 + 3 1.264623556160000E+30 5.192770794400000E+33 3.198879010449477E+13 5.680287938117499E+06 4.619658874727153E-11 1.113352676699529E+04 4.583651814225193E+04 4.583651814225193E+04 1.650115175247000E-01 5.364280083814479E+03 5.193402365400000E+33 3.278004423770521E+13 3.464691000000000E-05 0.000000000000000E+00 5.800994000000000E-01 1.190353000000000E-01 7.025597000000000E-07 2.461590000000000E-01 6.333397000000000E-03 3.274956000000000E-08 7.388660000000000E-03 3.112645000000000E-02 5.069225000000000E-03 4.829527000000000E-04 1.696820000000000E-04 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 2.070970000000000E-05 0.000000000000000E+00 4.079500000000000E-03 1.050921401976000E+39 2.783915958398000E+13 1.091727628705000E+13 + 4 1.263066609320000E+30 5.194033936400000E+33 3.357129837091565E+13 6.135230350494000E+06 5.896887289487248E-11 1.113352676699529E+04 4.583651814225193E+04 4.583651814225193E+04 1.653103657722300E-01 5.348854703681713E+03 5.194663518200000E+33 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4.355470000000000E-04 4.752008000000000E-05 8.485651000000001E-04 1.426982000000000E-04 9.610558000000000E-05 1.879377000000000E-05 1.454367000000000E-05 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 0.000000000000000E+00 1.731241000000000E-05 0.000000000000000E+00 1.108306000000000E-14 3.679884824753000E+41 4.606795339573000E+08 2.123224906916000E+04 diff --git a/tardis/io/model/readers/tests/data/non_uniform_isotope_abundance.dat b/tardis/io/model/readers/tests/data/non_uniform_isotope_abundance.dat new file mode 100644 index 00000000000..9ff972158ad --- /dev/null +++ b/tardis/io/model/readers/tests/data/non_uniform_isotope_abundance.dat @@ -0,0 +1,4 @@ +Index H He Ni56 Ni58 + +0 0.0 0.91 0.06 0.03 +1 0.4 0.51 0.05 0.04 diff --git a/tardis/io/tests/data/tardis_configv1_artis_density.yml b/tardis/io/model/readers/tests/data/tardis_configv1_artis_density.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_artis_density.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_artis_density.yml diff --git a/tardis/io/tests/data/tardis_configv1_artis_density_v_slice.yml b/tardis/io/model/readers/tests/data/tardis_configv1_artis_density_v_slice.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_artis_density_v_slice.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_artis_density_v_slice.yml diff --git a/tardis/io/tests/data/tardis_configv1_ascii_density.yml b/tardis/io/model/readers/tests/data/tardis_configv1_ascii_density.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_ascii_density.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_ascii_density.yml diff --git a/tardis/io/tests/data/tardis_configv1_ascii_density_abund.yml b/tardis/io/model/readers/tests/data/tardis_configv1_ascii_density_abund.yml similarity index 99% rename from tardis/io/tests/data/tardis_configv1_ascii_density_abund.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_ascii_density_abund.yml index 235546bbf41..99d8f1eb7b9 100644 --- a/tardis/io/tests/data/tardis_configv1_ascii_density_abund.yml +++ b/tardis/io/model/readers/tests/data/tardis_configv1_ascii_density_abund.yml @@ -11,7 +11,6 @@ supernova: atom_data: kurucz_atom_pure_simple.h5 model: - structure: type: file filename: density.dat diff --git a/tardis/io/tests/data/tardis_configv1_ascii_density_uniabund.yml b/tardis/io/model/readers/tests/data/tardis_configv1_ascii_density_uniabund.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_ascii_density_uniabund.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_ascii_density_uniabund.yml diff --git a/tardis/io/model/readers/tests/data/tardis_configv1_isotope_iabund.yml b/tardis/io/model/readers/tests/data/tardis_configv1_isotope_iabund.yml new file mode 100644 index 00000000000..7040021ecd9 --- /dev/null +++ b/tardis/io/model/readers/tests/data/tardis_configv1_isotope_iabund.yml @@ -0,0 +1,45 @@ +tardis_config_version: v1.0 + +supernova: + luminosity_requested: 2.8e9 solLum + time_explosion: 13 day + +atom_data: kurucz_atom_pure_simple.h5 + +model: + structure: + type: specific + velocity: + start: 1.1e4 km/s + stop: 2.0e4 km/s + num: 2 + density: + type: branch85_w7 + abundances: + type: file + filename: non_uniform_isotope_abundance.dat + filetype: custom_composition + +plasma: + ionization: lte + excitation: lte + radiative_rates_type: dilute-blackbody + line_interaction_type: macroatom + +montecarlo: + seed: 23111963 + no_of_packets: 2.0e+5 + iterations: 5 + last_no_of_packets: 5.0e+5 + no_of_virtual_packets: 5 + convergence_strategy: + type: damped + damping_constant: 0.5 + threshold: 0.05 + lock_t_inner_cycles: 1 + t_inner_update_exponent: -0.5 + +spectrum: + start: 500 angstrom + stop: 20000 angstrom + num: 10000 diff --git a/tardis/io/tests/data/tardis_configv1_isotope_uniabund.yml b/tardis/io/model/readers/tests/data/tardis_configv1_isotope_uniabund.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_isotope_uniabund.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_isotope_uniabund.yml index 02d2f7f9a60..7f1c583a2f9 100755 --- a/tardis/io/tests/data/tardis_configv1_isotope_uniabund.yml +++ b/tardis/io/model/readers/tests/data/tardis_configv1_isotope_uniabund.yml @@ -5,8 +5,8 @@ supernova: time_explosion: 13 day atom_data: kurucz_atom_pure_simple.h5 -model: +model: structure: type: specific velocity: diff --git a/tardis/io/tests/data/tardis_configv1_tardis_model_format.yml b/tardis/io/model/readers/tests/data/tardis_configv1_tardis_model_format.yml similarity index 100% rename from tardis/io/tests/data/tardis_configv1_tardis_model_format.yml rename to tardis/io/model/readers/tests/data/tardis_configv1_tardis_model_format.yml diff --git a/tardis/io/tests/data/tardis_simple_ascii_density_test.dat b/tardis/io/model/readers/tests/data/tardis_simple_ascii_density_test.dat similarity index 100% rename from tardis/io/tests/data/tardis_simple_ascii_density_test.dat rename to tardis/io/model/readers/tests/data/tardis_simple_ascii_density_test.dat diff --git a/tardis/io/model/readers/tests/test_arepo_parser.py b/tardis/io/model/readers/tests/test_arepo_parser.py new file mode 100644 index 00000000000..d205d9d90ed --- /dev/null +++ b/tardis/io/model/readers/tests/test_arepo_parser.py @@ -0,0 +1,124 @@ +from pathlib import Path +from tardis.io.model.readers import arepo +import pytest +import numpy as np +import os +import json + + +@pytest.fixture() +def arepo_snapshot_fname(tardis_ref_path): + return Path(tardis_ref_path) / "arepo_data" / "arepo_snapshot.json" + + +@pytest.fixture +def get_cone_csvy_model(arepo_snapshot_fname, example_model_file_dir): + with open(arepo_snapshot_fname, "r") as json_file: + data = json.loads(json.load(json_file)) + + pos, vel, rho, mass, nucs, time = ( + data["pos"], + data["vel"], + data["rho"], + data["mass"], + data["xnuc"], + data["time"], + ) + pos = np.array(pos) + vel = np.array(vel) + rho = np.array(rho) + mass = np.array(mass) + + # The nuclear data should be in a dict where each element has its own entry (with the key being the element name) + xnuc = { + "ni56": np.array(nucs[0]), + "si28": np.array(nucs[1]), + } + + profile = arepo.ConeProfile(pos, vel, rho, mass, xnuc, time) + + profile.create_profile( + opening_angle=40, inner_radius=1e11, outer_radius=2e11 + ) + + testfile = profile.export( + 20, example_model_file_dir / "arepo_parser_test.csvy" + ) + + with open(testfile, "r") as file: + data = file.readlines() + + print(testfile) + os.remove(testfile) + + return data + + +@pytest.fixture +def get_full_csvy_model(arepo_snapshot_fname, example_model_file_dir): + with open(arepo_snapshot_fname, "r") as json_file: + data = json.loads(json.load(json_file)) + + pos, vel, rho, mass, nucs, time = ( + data["pos"], + data["vel"], + data["rho"], + data["mass"], + data["xnuc"], + data["time"], + ) + pos = np.array(pos) + vel = np.array(vel) + rho = np.array(rho) + mass = np.array(mass) + + # The nuclear data should be in a dict where each element has its own entry (with the key being the element name) + xnuc = { + "ni56": np.array(nucs[0]), + "si28": np.array(nucs[1]), + } + + profile = arepo.FullProfile(pos, vel, rho, mass, xnuc, time) + + profile.create_profile(inner_radius=1e11, outer_radius=2e11) + + testfile = profile.export( + 20, example_model_file_dir / "arepo_parser_test.csvy" + ) + + with open(testfile, "r") as file: + data = file.readlines() + + os.remove(testfile) + + return data + + +@pytest.fixture +def get_cone_reference_data(example_model_file_dir): + with open( + example_model_file_dir / "arepo_cone_reference_model.csvy", "r" + ) as file: + data = file.readlines() + + return data + + +@pytest.fixture +def get_full_reference_data(example_model_file_dir): + with open( + example_model_file_dir / "arepo_full_reference_model.csvy", "r" + ) as file: + data = file.readlines() + + return data + + +@pytest.mark.ignore_generate +def test_cone_profile(get_cone_csvy_model, get_cone_reference_data): + assert get_cone_csvy_model == get_cone_reference_data + + +@pytest.mark.ignore_generate +def test_full_profile(get_full_csvy_model, get_full_reference_data): + assert get_full_csvy_model == get_full_reference_data diff --git a/tardis/io/model/readers/tests/test_ascii_readers.py b/tardis/io/model/readers/tests/test_ascii_readers.py new file mode 100644 index 00000000000..751a84fb824 --- /dev/null +++ b/tardis/io/model/readers/tests/test_ascii_readers.py @@ -0,0 +1,47 @@ +import os +from astropy import units as u +from tardis import io +from tardis.io.model.readers.generic_readers import ConfigurationError + +import numpy.testing as npt + +import pytest + +import numpy as np + +from pathlib import Path +from tardis.io.model.readers.base import read_density_file + +from tardis.io.model.readers.generic_readers import ( + read_simple_ascii_abundances, + read_simple_ascii_density, +) + +test_data_directory = os.path.dirname(__file__) + + +def test_simple_ascii_density_reader_time(example_model_file_dir): + (time_model, velocity, density,) = read_simple_ascii_density( + example_model_file_dir / "tardis_simple_ascii_density_test.dat" + ) + + assert time_model.unit.physical_type == "time" + npt.assert_almost_equal(time_model.to(u.day).value, 1.0) + npt.assert_allclose(velocity[3].value, 1.3e4 * 1e5) + assert velocity.unit == u.Unit("cm/s") + + +def test_simple_ascii_abundance_reader(example_model_file_dir): + (index, abundances,) = read_simple_ascii_abundances( + example_model_file_dir / "artis_abundances.dat" + ) + + npt.assert_almost_equal(abundances.loc[1, 0], 1.542953e-08) + npt.assert_almost_equal(abundances.loc[14, 54], 0.21864420000000001) + + +def test_ascii_reader_invalid_volumes(example_model_file_dir): + with pytest.raises(ConfigurationError): + read_density_file( + example_model_file_dir / "invalid_artis_model.dat", "artis" + ) diff --git a/tardis/io/model/readers/tests/test_cmfgen_reader.py b/tardis/io/model/readers/tests/test_cmfgen_reader.py new file mode 100644 index 00000000000..6a31952ca42 --- /dev/null +++ b/tardis/io/model/readers/tests/test_cmfgen_reader.py @@ -0,0 +1,39 @@ +import numpy as np + +from pathlib import Path + +from pytest import fixture +from astropy import units as u +from tardis.io.model.cmfgen import read_cmfgen_model + +MODEL_DATA_PATH = Path(__file__).parent / "data" + + +@fixture +def cmfgen_model_example_file(): + return read_cmfgen_model(MODEL_DATA_PATH / "cmfgen_model.csv") + + +def test_read_cmfgen_model_meta(cmfgen_model_example_file): + """ + Test reading a CMFGEN model file + """ + metadata = cmfgen_model_example_file.metadata + assert set(metadata.keys()).issubset( + { + "t0", + "velocity_unit", + "temperature_unit", + "densities_unit", + "electron_densities_unit", + } + ) + np.testing.assert_almost_equal(metadata["t0"].value, 0.976) + + +def test_read_cmfgen_model_data(cmfgen_model_example_file): + """ + Test reading a cmfgen model file + """ + data = cmfgen_model_example_file.data + np.testing.assert_almost_equal(data.iloc[0, 0], 871.66905) diff --git a/tardis/io/tests/test_csvy_reader.py b/tardis/io/model/readers/tests/test_csvy_reader.py similarity index 71% rename from tardis/io/tests/test_csvy_reader.py rename to tardis/io/model/readers/tests/test_csvy_reader.py index 7bb6e8762f3..daf283eca55 100644 --- a/tardis/io/tests/test_csvy_reader.py +++ b/tardis/io/model/readers/tests/test_csvy_reader.py @@ -1,6 +1,7 @@ +from pathlib import Path import tardis -from tardis.io.parsers import csvy -from tardis.io.config_validator import validate_dict +from tardis.io.model.readers import csvy +from tardis.io.configuration.config_validator import validate_dict from jsonschema import exceptions as json_schema_exc import pytest import os @@ -8,22 +9,19 @@ import numpy.testing as npt -DATA_PATH = os.path.join(tardis.__path__[0], "io", "tests", "data") - - @pytest.fixture -def csvy_full_fname(): - return os.path.join(DATA_PATH, "csvy_full.csvy") +def csvy_full_fname(example_model_file_dir: Path): + return example_model_file_dir / "csvy_full.csvy" @pytest.fixture -def csvy_nocsv_fname(): - return os.path.join(DATA_PATH, "csvy_nocsv.csvy") +def csvy_nocsv_fname(example_model_file_dir: Path): + return example_model_file_dir / "csvy_nocsv.csvy" @pytest.fixture -def csvy_missing_fname(): - return os.path.join(DATA_PATH, "csvy_missing.csvy") +def csvy_missing_fname(example_model_file_dir: Path): + return example_model_file_dir / "csvy_missing.csvy" def test_csvy_finds_csv_first_line(csvy_full_fname): diff --git a/tardis/io/model/readers/tests/test_stella_reader.py b/tardis/io/model/readers/tests/test_stella_reader.py new file mode 100644 index 00000000000..ace192118c9 --- /dev/null +++ b/tardis/io/model/readers/tests/test_stella_reader.py @@ -0,0 +1,46 @@ +import numpy as np + +from pathlib import Path + +from pytest import fixture +from astropy import units as u +from tardis.io.model import read_stella_model + +MODEL_DATA_PATH = Path(__file__).parent / "data" + + +@fixture +def stella_model_example_file1(): + return read_stella_model(MODEL_DATA_PATH / "mesa.stella.dat") + + +def test_read_stella_model_meta(stella_model_example_file1): + """ + Test reading a STELLA model file + """ + assert stella_model_example_file1.metadata["zones"] == 400 + np.testing.assert_almost_equal( + stella_model_example_file1.metadata["t_max"].to(u.day).value, 50.0 + ) + np.testing.assert_almost_equal( + stella_model_example_file1.metadata["inner_boundary_mass"] + .to(u.g) + .value, + 5.190242521200000e33, + ) + np.testing.assert_almost_equal( + stella_model_example_file1.metadata["total_mass"].to(u.g).value, + 2.618867335600000e34, + ) + + +def test_read_stella_model_data(stella_model_example_file1): + """ + Test reading a STELLA model file + """ + np.testing.assert_almost_equal( + stella_model_example_file1.data.iloc[0, 0], 6.006769337200000e29 + ) + np.testing.assert_almost_equal( + stella_model_example_file1.data.iloc[-1, -1], 2.123224906916000e04 + ) diff --git a/tardis/io/model/readers/util.py b/tardis/io/model/readers/util.py new file mode 100644 index 00000000000..8597af839bf --- /dev/null +++ b/tardis/io/model/readers/util.py @@ -0,0 +1,76 @@ +import numpy as np +import pandas as pd +from radioactivedecay import Nuclide +from radioactivedecay.utils import Z_DICT, elem_to_Z + + +def read_csv_isotope_abundances( + fname, delimiter=r"\s+", skip_columns=0, skip_rows=[1] +): + """ + A generic parser for a TARDIS composition stored as a CSV file + + The parser can read in both elemental and isotopic abundances. The first + column is always expected to contain a running index, labelling the grid + cells. The parser also allows for additional information to be stored in + the first skip_columns columns. These will be ignored if skip_columns > 0. + Note that the first column, containing the cell index is not taken into + account here. + + Specific header lines can be skipped by the skip_rows keyword argument + + It is expected that the first row of the date block (after skipping the + rows specified in skip_rows) specifies the different elements and isotopes. + Each row after contains the composition in the corresponding grid shell. + The first composition row describes the composition of the photosphere and + is essentially ignored (for the default value of skip_rows). + + Example: + + Index C O Ni56 + 0 1 1 1 + 1 0.4 0.3 0.2 + + Parameters + ---------- + fname : str + filename or path with filename + + Returns + ------- + index : np.ndarray + abundances : pandas.DataFrame + isotope_abundance : pandas.MultiIndex + """ + + df = pd.read_csv( + fname, comment="#", sep=delimiter, skiprows=skip_rows, index_col=0 + ) + df = df.transpose() + + abundance = pd.DataFrame( + columns=np.arange(df.shape[1]), + index=pd.Index([], name="atomic_number"), + dtype=np.float64, + ) + + isotope_index = pd.MultiIndex( + [[]] * 2, [[]] * 2, names=["atomic_number", "mass_number"] + ) + isotope_abundance = pd.DataFrame( + columns=np.arange(df.shape[1]), index=isotope_index, dtype=np.float64 + ) + + for element_symbol_string in df.index[skip_columns:]: + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) + abundance.loc[z, :] = df.loc[element_symbol_string].tolist() + else: + nuc = Nuclide(element_symbol_string) + z = nuc.Z + mass_no = nuc.A + isotope_abundance.loc[(z, mass_no), :] = df.loc[ + element_symbol_string + ].tolist() + + return abundance.index, abundance, isotope_abundance diff --git a/tardis/io/model_reader.py b/tardis/io/model_reader.py index 18225ff0d8f..3e1bc37c3d5 100644 --- a/tardis/io/model_reader.py +++ b/tardis/io/model_reader.py @@ -1,19 +1,27 @@ # reading different model files +import logging import warnings + +import h5py import numpy as np -from numpy import recfromtxt, genfromtxt import pandas as pd from astropy import units as u -from pyne import nucname - -import logging +from numpy import recfromtxt +from radioactivedecay import Nuclide +from radioactivedecay.utils import Z_DICT, elem_to_Z, NuclideStrError + +from tardis.io.configuration.config_reader import ConfigurationNameSpace +from tardis.transport.montecarlo.base import MonteCarloTransportSolver +from tardis.transport.montecarlo.packet_source import ( + BlackBodySimpleSource, + BlackBodySimpleSourceRelativistic, +) +from tardis.util.base import is_valid_nuclide_or_elem, parse_quantity # Adding logging support logger = logging.getLogger(__name__) -from tardis.util.base import parse_quantity - class ConfigurationError(Exception): pass @@ -67,7 +75,7 @@ def read_density_file(filename, filetype): if invalid_volume_mask.sum() > 0: message = "\n".join( [ - f"cell {i:d}: v_inner {v_inner_i:s}, v_outer " f"{v_outer_i:s}" + f"cell {i:d}: v_inner {v_inner_i:s}, v_outer {v_outer_i:s}" for i, v_inner_i, v_outer_i in zip( np.arange(len(v_outer))[invalid_volume_mask], v_inner[invalid_volume_mask], @@ -108,7 +116,6 @@ def read_abundances_file( outer_boundary_index : int index of the outer shell, default None """ - file_parsers = { "simple_ascii": read_simple_ascii_abundances, "artis": read_simple_ascii_abundances, @@ -162,22 +169,26 @@ def read_uniform_abundances(abundances_section, no_of_shells): ) for element_symbol_string in abundances_section: - if element_symbol_string == "type": + if ( + element_symbol_string == "type" + or element_symbol_string == "model_isotope_time_0" + ): continue try: - if element_symbol_string in nucname.name_zz: - z = nucname.name_zz[element_symbol_string] + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) abundance.loc[z] = float( abundances_section[element_symbol_string] ) else: - mass_no = nucname.anum(element_symbol_string) - z = nucname.znum(element_symbol_string) + nuc = Nuclide(element_symbol_string) + mass_no = nuc.A + z = nuc.Z isotope_abundance.loc[(z, mass_no), :] = float( abundances_section[element_symbol_string] ) - except RuntimeError as err: + except NuclideStrError as err: raise RuntimeError( f"Abundances are not defined properly in config file : {err.args}" ) @@ -206,7 +217,6 @@ def read_simple_ascii_density(fname): data : pandas.DataFrame data frame containing index, velocity (in km/s) and density """ - with open(fname) as fh: time_of_model_string = fh.readline().strip() time_of_model = parse_quantity(time_of_model_string) @@ -244,7 +254,6 @@ def read_artis_density(fname): data : pandas.DataFrame data frame containing index, velocity (in km/s) and density """ - with open(fname) as fh: for i, line in enumerate(open(fname)): if i == 0: @@ -380,7 +389,6 @@ def read_cmfgen_composition(fname, delimiter=r"\s+"): fname : str filename of the csv file """ - warnings.warn( "The current CMFGEN model parser is deprecated", DeprecationWarning ) @@ -405,7 +413,6 @@ def read_csv_composition(fname, delimiter=r"\s+"): fname : str filename of the csv file """ - return read_csv_isotope_abundances( fname, delimiter=delimiter, skip_columns=0, skip_rows=[1] ) @@ -449,7 +456,6 @@ def read_csv_isotope_abundances( abundances : pandas.DataFrame isotope_abundance : pandas.MultiIndex """ - df = pd.read_csv( fname, comment="#", sep=delimiter, skiprows=skip_rows, index_col=0 ) @@ -469,12 +475,13 @@ def read_csv_isotope_abundances( ) for element_symbol_string in df.index[skip_columns:]: - if element_symbol_string in nucname.name_zz: - z = nucname.name_zz[element_symbol_string] + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) abundance.loc[z, :] = df.loc[element_symbol_string].tolist() else: - z = nucname.znum(element_symbol_string) - mass_no = nucname.anum(element_symbol_string) + nuc = Nuclide(element_symbol_string) + z = nuc.Z + mass_no = nuc.A isotope_abundance.loc[(z, mass_no), :] = df.loc[ element_symbol_string ].tolist() @@ -496,11 +503,8 @@ def parse_csv_abundances(csvy_data): abundances : pandas.DataFrame isotope_abundance : pandas.MultiIndex """ - abundance_col_names = [ - name - for name in csvy_data.columns - if nucname.iselement(name) or nucname.isnuclide(name) + name for name in csvy_data.columns if is_valid_nuclide_or_elem(name) ] df = csvy_data.loc[:, abundance_col_names] @@ -520,14 +524,323 @@ def parse_csv_abundances(csvy_data): ) for element_symbol_string in df.index[0:]: - if element_symbol_string in nucname.name_zz: - z = nucname.name_zz[element_symbol_string] + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) abundance.loc[z, :] = df.loc[element_symbol_string].tolist() else: - z = nucname.znum(element_symbol_string) - mass_no = nucname.anum(element_symbol_string) + nuc = Nuclide(element_symbol_string) + z = nuc.Z + mass_no = nuc.A isotope_abundance.loc[(z, mass_no), :] = df.loc[ element_symbol_string ].tolist() return abundance.index, abundance, isotope_abundance + + +def transport_to_dict(transport): + """ + Retrieves all the data from a transport object and returns a dictionary. + + Parameters + ---------- + transport : tardis.transport.montecarlo.MontecarloTransport + + Returns + ------- + transport_dict : dict + integrator_settings : dict + virtual_spectrum_spawn_range : dict + """ + transport_dict = { + "Edotlu_estimator": transport.Edotlu_estimator, + "bf_heating_estimator": transport.bf_heating_estimator, + "disable_electron_scattering": transport.disable_electron_scattering, + "enable_full_relativity": transport.enable_full_relativity, + "input_energy": transport.input_energy, + "input_mu": transport.input_mu, + "input_nu": transport.input_nu, + "input_r_cgs": transport.input_r, + "j_blue_estimator": transport.j_blue_estimator, + "j_estimator": transport.j_estimator, + "last_interaction_in_nu": transport.last_interaction_in_nu, + "last_interaction_type": transport.last_interaction_type, + "last_line_interaction_in_id": transport.last_line_interaction_in_id, + "last_line_interaction_out_id": transport.last_line_interaction_out_id, + "last_line_interaction_shell_id": transport.last_line_interaction_shell_id, + "line_interaction_type": transport.line_interaction_type, + "nu_bar_estimator": transport.nu_bar_estimator, + "photo_ion_estimator": transport.photo_ion_estimator, + "photo_ion_estimator_statistics": transport.photo_ion_estimator_statistics, + "r_inner": transport.r_inner_cgs, + "r_outer": transport.r_outer_cgs, + "packet_source_base_seed": transport.packet_source.base_seed, + "spectrum_frequency_cgs": transport.spectrum_frequency, + "spectrum_method": transport.spectrum_method, + "stim_recomb_cooling_estimator": transport.stim_recomb_cooling_estimator, + "stim_recomb_estimator": transport.stim_recomb_estimator, + "time_of_simulation_cgs": transport.time_of_simulation, + "use_gpu": transport.use_gpu, + "v_inner": transport.v_inner_cgs, + "v_outer": transport.v_outer_cgs, + "nthreads": transport.nthreads, + "virt_logging": transport.virt_logging, + "virt_packet_energies": transport.virt_packet_energies, + "virt_packet_initial_mus": transport.virt_packet_initial_mus, + "virt_packet_initial_rs": transport.virt_packet_initial_rs, + "virt_packet_last_interaction_in_nu": transport.virt_packet_last_interaction_in_nu, + "virt_packet_last_interaction_type": transport.virt_packet_last_interaction_type, + "virt_packet_last_line_interaction_in_id": transport.virt_packet_last_line_interaction_in_id, + "virt_packet_last_line_interaction_out_id": transport.virt_packet_last_line_interaction_out_id, + "virt_packet_last_line_interaction_shell_id": transport.virt_packet_last_line_interaction_shell_id, + "virt_packet_nus": transport.virt_packet_nus, + "volume_cgs": transport.volume, + } + + for key, value in transport_dict.items(): + if key.endswith("_cgs"): + transport_dict[key] = [value.cgs.value, value.unit.to_string()] + + integrator_settings = transport.integrator_settings + virtual_spectrum_spawn_range = transport.virtual_spectrum_spawn_range + + return ( + transport_dict, + integrator_settings, + virtual_spectrum_spawn_range, + ) + + +def store_transport_to_hdf(transport, fname): + """ + Stores data from MontecarloTransport object into a hdf file. + + Parameters + ---------- + transport : tardis.transport.montecarlo.MontecarloTransport + filename : str + """ + with h5py.File(fname, "a") as f: + transport_group = f.require_group("transport") + transport_group.clear() + + ( + transport_data, + integrator_settings, + virtual_spectrum_spawn_range, + ) = transport_to_dict(transport) + + for key, value in transport_data.items(): + if key.endswith("_cgs"): + transport_group.create_dataset(key, data=value[0]) + transport_group.create_dataset(key + "_unit", data=value[1]) + else: + if value is not None: + transport_group.create_dataset(key, data=value) + + integrator_settings_group = transport_group.create_group( + "integrator_settings" + ) + for key, value in integrator_settings.items(): + integrator_settings_group.create_dataset(key, data=value) + + virtual_spectrum_spawn_range_group = transport_group.create_group( + "virtual_spectrum_spawn_range" + ) + for key, value in virtual_spectrum_spawn_range.items(): + virtual_spectrum_spawn_range_group.create_dataset(key, data=value) + + +def transport_from_hdf(fname): + """ + Creates a MontecarloTransport object using data stored in a hdf file. + + Parameters + ---------- + fname : str + + Returns + ------- + new_transport : tardis.transport.montecarlo.MontecarloTransport + """ + d = {} + + # Loading data from hdf file + with h5py.File(fname, "r") as f: + transport_group = f["transport"] + for key, value in transport_group.items(): + if not key.endswith("_unit"): + if isinstance(value, h5py.Dataset): + if isinstance(value[()], bytes): + d[key] = value[()].decode("utf-8") + else: + d[key] = value[()] + else: + data_inner = {} + for key_inner, value_inner in value.items(): + if isinstance(value_inner[()], bytes): + data_inner[key] = value_inner[()].decode("utf-8") + else: + data_inner[key] = value_inner[()] + data_inner[key_inner] = value_inner[()] + d[key] = data_inner + + for key, value in transport_group.items(): + if key.endswith("_unit"): + d[key[:-5]] = [d[key[:-5]], value[()]] + + # Converting cgs data to astropy quantities + for key, value in d.items(): + if key.endswith("_cgs"): + d[key] = u.Quantity(value[0], unit=u.Unit(value[1].decode("utf-8"))) + + # Using packet source seed to packet source + if not d["enable_full_relativity"]: + d["packet_source"] = BlackBodySimpleSource(d["packet_source_base_seed"]) + else: + d["packet_source"] = BlackBodySimpleSourceRelativistic( + d["packet_source_base_seed"] + ) + + # Converting virtual spectrum spawn range values to astropy quantities + vssr = d["virtual_spectrum_spawn_range"] + d["virtual_spectrum_spawn_range"] = { + "start": u.Quantity(vssr["start"], unit=u.Unit("Angstrom")), + "end": u.Quantity(vssr["end"], unit=u.Unit("Angstrom")), + } + + # Converting dictionaries to ConfigurationNameSpace + d["integrator_settings"] = ConfigurationNameSpace(d["integrator_settings"]) + d["virtual_spectrum_spawn_range"] = ConfigurationNameSpace( + d["virtual_spectrum_spawn_range"] + ) + + # Creating a transport object and storing data + new_transport = MonteCarloTransportSolver( + spectrum_frequency=d["spectrum_frequency_cgs"], + virtual_spectrum_spawn_range=d["virtual_spectrum_spawn_range"], + disable_electron_scattering=d["disable_electron_scattering"], + enable_full_relativity=d["enable_full_relativity"], + line_interaction_type=d["line_interaction_type"], + integrator_settings=d["integrator_settings"], + spectrum_method=d["spectrum_method"], + packet_source=d["packet_source"], + nthreads=d["nthreads"], + enable_virtual_packet_logging=d["virt_logging"], + use_gpu=d["use_gpu"], + montecarlo_configuration=d["montecarlo_configuration"], + ) + + new_transport.Edotlu_estimator = d["Edotlu_estimator"] + new_transport.bf_heating_estimator = d["bf_heating_estimator"] + new_transport.input_energy = d["input_energy"] + new_transport.input_mu = d["input_mu"] + new_transport.input_nu = d["input_nu"] + new_transport.input_r = d["input_r_cgs"] + new_transport.j_blue_estimator = d["j_blue_estimator"] + new_transport.j_estimator = d["j_estimator"] + new_transport.last_interaction_in_nu = d["last_interaction_in_nu"] + new_transport.last_interaction_type = d["last_interaction_type"] + new_transport.last_line_interaction_in_id = d["last_line_interaction_in_id"] + new_transport.last_line_interaction_out_id = d[ + "last_line_interaction_out_id" + ] + new_transport.last_line_interaction_shell_id = d[ + "last_line_interaction_shell_id" + ] + new_transport.nu_bar_estimator = d["nu_bar_estimator"] + new_transport.photo_ion_estimator = d["photo_ion_estimator"] + new_transport.photo_ion_estimator_statistics = d[ + "photo_ion_estimator_statistics" + ] + new_transport.r_inner_cgs = d["r_inner"] + new_transport.r_outer_cgs = d["r_outer"] + new_transport.stim_recomb_cooling_estimator = d[ + "stim_recomb_cooling_estimator" + ] + new_transport.stim_recomb_estimator = d["stim_recomb_estimator"] + new_transport.time_of_simulation = d["time_of_simulation_cgs"] + new_transport.v_inner_cgs = d["v_inner"] + new_transport.v_outer_cgs = d["v_outer"] + new_transport.virt_packet_energies = d["virt_packet_energies"] + new_transport.virt_packet_initial_mus = d["virt_packet_initial_mus"] + new_transport.virt_packet_initial_rs = d["virt_packet_initial_rs"] + new_transport.virt_packet_last_interaction_in_nu = d[ + "virt_packet_last_interaction_in_nu" + ] + new_transport.virt_packet_last_interaction_type = d[ + "virt_packet_last_interaction_type" + ] + new_transport.virt_packet_last_line_interaction_in_id = d[ + "virt_packet_last_line_interaction_in_id" + ] + new_transport.virt_packet_last_line_interaction_out_id = d[ + "virt_packet_last_line_interaction_out_id" + ] + new_transport.virt_packet_last_line_interaction_shell_id = d[ + "virt_packet_last_line_interaction_shell_id" + ] + new_transport.virt_packet_nus = d["virt_packet_nus"] + new_transport.volume = d["volume_cgs"] + + return new_transport + + +def model_to_dict(model): + """ + Retrieves all the data from a SimulationState object and returns a dictionary. + + Parameters + ---------- + transport : tardis.model.SimulationState + + Returns + ------- + model_dict : dict + isotope_abundance : dict + """ + model_dict = { + "velocity_cgs": model.velocity, + "abundance": model.abundance, + "time_explosion_cgs": model.time_explosion, + "t_inner_cgs": model.t_inner, + "t_radiative_cgs": model.t_radiative, + "dilution_factor": model.dilution_factor, + "v_boundary_inner_cgs": model.v_boundary_inner, + "v_boundary_outer_cgs": model.v_boundary_outer, + "w": model.w, + "t_rad_cgs": model.t_rad, + "r_inner_cgs": model.r_inner, + "density_cgs": model.density, + } + + for key, value in model_dict.items(): + if hasattr(value, "unit"): + model_dict[key] = [value.cgs.value, value.unit.to_string()] + + isotope_abundance = model.raw_isotope_abundance.__dict__ + + return model_dict, isotope_abundance + + +def store_model_to_hdf(model, fname): + """ + Stores data from SimulationState object into a hdf file. + + Parameters + ---------- + model : tardis.model.SimulationState + filename : str + """ + with h5py.File(fname, "a") as f: + model_group = f.require_group("model") + model_group.clear() + + model_dict, isotope_abundance = model_to_dict(model) + + for key, value in model_dict.items(): + if key.endswith("_cgs"): + model_group.create_dataset(key, data=value[0]) + model_group.create_dataset(key + "_unit", data=value[1]) + else: + model_group.create_dataset(key, data=value) diff --git a/tardis/io/parsers/__init__.py b/tardis/io/parsers/__init__.py deleted file mode 100644 index ef3825cde24..00000000000 --- a/tardis/io/parsers/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from tardis.io.parsers.blondin_toymodel import ( - read_blondin_toymodel, - convert_blondin_toymodel, -) diff --git a/tardis/io/parsers/stella.py b/tardis/io/parsers/stella.py deleted file mode 100644 index b102e4c1897..00000000000 --- a/tardis/io/parsers/stella.py +++ /dev/null @@ -1,21 +0,0 @@ -import re -import pandas as pd -from astropy import units as u -import numpy as np - - -def read_stella_data(filename): - with open(filename) as fh: - col = fh.readlines()[5] - col_names = re.split(r"\s{3,}", col.strip()) - col_names = [ - re.sub(r"\s\(.+\)", "", col_name).replace(" ", "_") - for col_name in col_names - ] - data = pd.read_csv( - filename, skiprows=7, delim_whitespace=True, names=col_names - ) - - # drop last row of data - data = data.iloc[0:-1] - return data diff --git a/tardis/io/tests/data/arepo_cone_reference_model.csvy b/tardis/io/tests/data/arepo_cone_reference_model.csvy deleted file mode 100644 index 94300018e3d..00000000000 --- a/tardis/io/tests/data/arepo_cone_reference_model.csvy +++ /dev/null @@ -1,41 +0,0 @@ ---- -name: csvy_full -model_density_time_0: 0.00115628 day -model_isotope_time_0: 0.666016 day -description: Config file for TARDIS from Arepo snapshot. -tardis_model_config_version: v1.0 -datatype: - fields: - - name: velocity - unit: cm/s - desc: velocities of shell outer bounderies. - - name: density - unit: g/cm^3 - desc: density of shell. - - name: Ni56 - desc: fractional Ni56 abundance. - - name: Si28 - desc: fractional Si28 abundance. - ---- -velocity,density,Ni56,Si28 -1.02578e+09,0.150887,0.822682,0.0336797 -1.10713e+09,0.133016,0.551666,0.139149 -1.12296e+09,0.134486,0.536547,0.149411 -1.19955e+09,0.111786,0.187363,0.353107 -1.21382e+09,0.108062,0.161066,0.373762 -1.2876e+09,0.0806537,0.0984963,0.432794 -1.34739e+09,0.0602483,0.0568059,0.455806 -1.36913e+09,0.0552193,0.0417946,0.447125 -1.43019e+09,0.0423093,0.00673486,0.434474 -1.48887e+09,0.0505582,9.4041e-06,0.403988 -1.54686e+09,0.0386499,1.4712e-07,0.350157 -1.57905e+09,0.0282653,1.8919e-08,0.262617 -1.62552e+09,0.0173151,1.26482e-10,0.225123 -1.68912e+09,0.00860024,9.14892e-12,0.178677 -1.73562e+09,0.00478935,3.18801e-12,0.12539 -1.7789e+09,0.00291147,9.23938e-13,0.0878612 -1.83386e+09,0.00142813,4.54184e-13,0.0447214 -1.87803e+09,0.000859721,1.4997e-13,0.0315839 -1.93632e+09,0.0004987,1.03361e-13,0.0276565 -1.98018e+09,0.000343444,1.16766e-13,0.0198007 \ No newline at end of file diff --git a/tardis/io/tests/data/arepo_full_reference_model.csvy b/tardis/io/tests/data/arepo_full_reference_model.csvy deleted file mode 100644 index 911792b3d53..00000000000 --- a/tardis/io/tests/data/arepo_full_reference_model.csvy +++ /dev/null @@ -1,41 +0,0 @@ ---- -name: csvy_full -model_density_time_0: 0.00115628 day -model_isotope_time_0: 0.666016 day -description: Config file for TARDIS from Arepo snapshot. -tardis_model_config_version: v1.0 -datatype: - fields: - - name: velocity - unit: cm/s - desc: velocities of shell outer bounderies. - - name: density - unit: g/cm^3 - desc: density of shell. - - name: Ni56 - desc: fractional Ni56 abundance. - - name: Si28 - desc: fractional Si28 abundance. - ---- -velocity,density,Ni56,Si28 -1.02674e+09,0.134944,0.802387,0.039859 -1.10888e+09,0.114694,0.467788,0.179195 -1.12154e+09,0.1148,0.452686,0.189122 -1.2007e+09,0.0958109,0.178353,0.360045 -1.21456e+09,0.0907571,0.160524,0.373566 -1.28505e+09,0.0721129,0.0989223,0.432523 -1.34824e+09,0.0572256,0.068908,0.457918 -1.36955e+09,0.0530045,0.0576294,0.457682 -1.42952e+09,0.0419773,0.0297433,0.448743 -1.49273e+09,0.0362448,0.0116699,0.448255 -1.54577e+09,0.0318658,0.00352072,0.426684 -1.57839e+09,0.0286726,0.00201344,0.376775 -1.62653e+09,0.0217643,0.000348878,0.35583 -1.68365e+09,0.0161231,2.95896e-05,0.331685 -1.73686e+09,0.0126271,3.42093e-07,0.272973 -1.78223e+09,0.0099846,3.35969e-08,0.236912 -1.82927e+09,0.00734297,2.71566e-09,0.195333 -1.87824e+09,0.00543494,1.37357e-09,0.158942 -1.93278e+09,0.00458367,2.67068e-10,0.164494 -1.97868e+09,0.00233206,9.27189e-11,0.113039 \ No newline at end of file diff --git a/tardis/io/tests/data/arepo_line_reference_model.csvy b/tardis/io/tests/data/arepo_line_reference_model.csvy deleted file mode 100644 index 5ec612c7baf..00000000000 --- a/tardis/io/tests/data/arepo_line_reference_model.csvy +++ /dev/null @@ -1,41 +0,0 @@ ---- -name: csvy_full -model_density_time_0: 0.00115628 day -model_isotope_time_0: 0.666016 day -description: Config file for TARDIS from Arepo snapshot. -tardis_model_config_version: v1.0 -datatype: - fields: - - name: velocity - unit: cm/s - desc: velocities of shell outer bounderies. - - name: density - unit: g/cm^3 - desc: density of shell. - - name: Ni56 - desc: fractional Ni56 abundance. - - name: Si28 - desc: fractional Si28 abundance. - ---- -velocity,density,Ni56,Si28 -1.11396e+09,0.12017,0.38561,0.221 -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -1.42636e+09,0.0396456,0.0164109,0.441123 -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -nan,nan,nan,nan -1.73287e+09,0.0106543,3.53151e-10,0.2323 \ No newline at end of file diff --git a/tardis/io/tests/data/arepo_snapshot.json b/tardis/io/tests/data/arepo_snapshot.json deleted file mode 100644 index a3befe4ef9b..00000000000 --- a/tardis/io/tests/data/arepo_snapshot.json +++ /dev/null @@ -1 +0,0 @@ -"{\"pos\": [[[[-484396536692.5792, -484447238887.25665, -484883158952.442, -484335715593.3214, -483966802720.83417, -484518851394.72906, -484883837119.87964, -483867015065.0876, -483873455930.2735, -484462144482.319, -484239899454.08777, -484333208554.87274, -484057258646.5954, -484450413706.9101, -483962898107.91846, -484567003778.9483, -483846769622.33417, -483835647767.6636, -484088016677.19916, -484737416448.4721, 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a/tardis/io/tests/test_HDFWriter.py +++ b/tardis/io/tests/test_HDFWriter.py @@ -1,11 +1,8 @@ -import os - import numpy as np import pandas as pd -import pandas.util.testing as pdt import pytest from astropy import units as u -from astropy.tests.helper import assert_quantity_allclose + from numpy.testing import assert_almost_equal, assert_array_almost_equal from tardis.io.util import HDFWriterMixin @@ -61,6 +58,7 @@ def test_complex_obj_write(tmpdir, attr): actual = MockHDF(attr) actual.to_hdf(fname, path="test", overwrite=True) expected = pd.read_hdf(fname, key="/test/mock_hdf/property").values + assert_array_almost_equal(actual.property, expected) @@ -73,13 +71,14 @@ def test_complex_obj_write(tmpdir, attr): mock_multiIndex = pd.MultiIndex.from_arrays(arr.transpose()) -def test_MultiIndex_write(tmpdir): +def test_multi_index_write(tmpdir): fname = str(tmpdir.mkdir("data").join("test.hdf")) actual = MockHDF(mock_multiIndex) actual.to_hdf(fname, path="test", overwrite=True) expected = pd.read_hdf(fname, key="/test/mock_hdf/property") expected = pd.MultiIndex.from_tuples(expected.unstack().values) - pdt.assert_almost_equal(actual.property, expected) + # These are multiindex objects, so we need to compare the values + assert np.all(expected.values == actual.property.values) # Test Quantity Objects @@ -156,8 +155,8 @@ def test_snake_case(): assert MockHDF.convert_to_snake_case("BasePlasma") == "base_plasma" assert MockHDF.convert_to_snake_case("LTEPlasma") == "lte_plasma" assert ( - MockHDF.convert_to_snake_case("MonteCarloRunner") - == "monte_carlo_runner" + MockHDF.convert_to_snake_case("MontecarloTransport") + == "montecarlo_transport" ) assert ( MockHDF.convert_to_snake_case("homologous_density") diff --git a/tardis/io/tests/test_arepo_parser.py b/tardis/io/tests/test_arepo_parser.py deleted file mode 100644 index 48a680b6e9a..00000000000 --- a/tardis/io/tests/test_arepo_parser.py +++ /dev/null @@ -1,168 +0,0 @@ -import tardis -from tardis.io.parsers import arepo -import pytest -import numpy as np -import os -import json - - -DATA_PATH = os.path.join(tardis.__path__[0], "io", "tests", "data") - - -@pytest.fixture -def get_line_csvy_model(): - with open(os.path.join(DATA_PATH, "arepo_snapshot.json"), "r") as json_file: - data = json.loads(json.load(json_file)) - - pos, vel, rho, nucs, time = ( - data["pos"], - data["vel"], - data["rho"], - data["xnuc"], - data["time"], - ) - pos = np.array(pos) - vel = np.array(vel) - rho = np.array(rho) - - # The nuclear data should be in a dict where each element has its own entry (with the key being the element name) - xnuc = { - "ni56": np.array(nucs[0]), - "si28": np.array(nucs[1]), - } - - profile = arepo.LineProfile(pos, vel, rho, xnuc, time) - - profile.create_profile(inner_radius=1e11, outer_radius=2e11) - - testfile = profile.export( - 20, os.path.join(DATA_PATH, "arepo_parser_test.csvy") - ) - - with open(testfile, "r") as file: - data = file.readlines() - - os.remove(testfile) - - return data - - -@pytest.fixture -def get_cone_csvy_model(): - with open(os.path.join(DATA_PATH, "arepo_snapshot.json"), "r") as json_file: - data = json.loads(json.load(json_file)) - - pos, vel, rho, nucs, time = ( - data["pos"], - data["vel"], - data["rho"], - data["xnuc"], - data["time"], - ) - pos = np.array(pos) - vel = np.array(vel) - rho = np.array(rho) - - # The nuclear data should be in a dict where each element has its own entry (with the key being the element name) - xnuc = { - "ni56": np.array(nucs[0]), - "si28": np.array(nucs[1]), - } - - profile = arepo.ConeProfile(pos, vel, rho, xnuc, time) - - profile.create_profile( - opening_angle=40, inner_radius=1e11, outer_radius=2e11 - ) - - testfile = profile.export( - 20, os.path.join(DATA_PATH, "arepo_parser_test.csvy") - ) - - with open(testfile, "r") as file: - data = file.readlines() - - print(testfile) - os.remove(testfile) - - return data - - -@pytest.fixture -def get_full_csvy_model(): - with open(os.path.join(DATA_PATH, "arepo_snapshot.json"), "r") as json_file: - data = json.loads(json.load(json_file)) - - pos, vel, rho, nucs, time = ( - data["pos"], - data["vel"], - data["rho"], - data["xnuc"], - data["time"], - ) - pos = np.array(pos) - vel = np.array(vel) - rho = np.array(rho) - - # The nuclear data should be in a dict where each element has its own entry (with the key being the element name) - xnuc = { - "ni56": np.array(nucs[0]), - "si28": np.array(nucs[1]), - } - - profile = arepo.FullProfile(pos, vel, rho, xnuc, time) - - profile.create_profile(inner_radius=1e11, outer_radius=2e11) - - testfile = profile.export( - 20, os.path.join(DATA_PATH, "arepo_parser_test.csvy") - ) - - with open(testfile, "r") as file: - data = file.readlines() - - os.remove(testfile) - - return data - - -@pytest.fixture -def get_line_reference_data(): - with open( - os.path.join(DATA_PATH, "arepo_line_reference_model.csvy"), "r" - ) as file: - data = file.readlines() - - return data - - -@pytest.fixture -def get_cone_reference_data(): - with open( - os.path.join(DATA_PATH, "arepo_cone_reference_model.csvy"), "r" - ) as file: - data = file.readlines() - - return data - - -@pytest.fixture -def get_full_reference_data(): - with open( - os.path.join(DATA_PATH, "arepo_full_reference_model.csvy"), "r" - ) as file: - data = file.readlines() - - return data - - -def test_line_profile(get_line_csvy_model, get_line_reference_data): - assert get_line_csvy_model == get_line_reference_data - - -def test_cone_profile(get_cone_csvy_model, get_cone_reference_data): - assert get_cone_csvy_model == get_cone_reference_data - - -def test_full_profile(get_full_csvy_model, get_full_reference_data): - assert get_full_csvy_model == get_full_reference_data diff --git a/tardis/io/tests/test_ascii_readers.py b/tardis/io/tests/test_ascii_readers.py deleted file mode 100644 index 12f7519e9ca..00000000000 --- a/tardis/io/tests/test_ascii_readers.py +++ /dev/null @@ -1,48 +0,0 @@ -import os -from astropy import units as u -from tardis import io - -import numpy.testing as npt - -import pytest - -import numpy as np - -test_data_directory = os.path.dirname(__file__) - - -def data_path(filename): - data_dir = os.path.dirname(__file__) - return os.path.join(data_dir, "data", filename) - - -def test_simple_ascii_density_reader_time(): - time_model, velocity, density = io.read_simple_ascii_density( - data_path("tardis_simple_ascii_density_test.dat") - ) - - assert time_model.unit.physical_type == "time" - npt.assert_almost_equal(time_model.to(u.day).value, 1.0) - - -def test_simple_ascii_density_reader_data(): - - time_model, velocity, density = io.read_simple_ascii_density( - data_path("tardis_simple_ascii_density_test.dat") - ) - assert velocity.unit == u.Unit("cm/s") - - npt.assert_allclose(velocity[3].value, 1.3e4 * 1e5) - - -def test_simple_ascii_abundance_reader(): - index, abundances = io.read_simple_ascii_abundances( - data_path("artis_abundances.dat") - ) - npt.assert_almost_equal(abundances.loc[1, 0], 1.542953e-08) - npt.assert_almost_equal(abundances.loc[14, 54], 0.21864420000000001) - - -def test_ascii_reader_invalid_volumes(): - with pytest.raises(io.model_reader.ConfigurationError): - io.read_density_file(data_path("invalid_artis_model.dat"), "artis") diff --git a/tardis/io/tests/test_atomic.py b/tardis/io/tests/test_atomic.py index 70de086d9b0..5fdf4c9ba41 100644 --- a/tardis/io/tests/test_atomic.py +++ b/tardis/io/tests/test_atomic.py @@ -49,13 +49,18 @@ def test_atom_data_levels(levels): def test_atom_data_lines(lines): assert_quantity_allclose( - lines.at[(2, 0, 0, 6), "wavelength_cm"] * u.Unit("cm"), + lines.loc[(2, 0, 0, 6), "wavelength_cm"].values[0] * u.Unit("cm"), 584.335 * u.Unit("Angstrom"), ) def test_atomic_reprepare(kurucz_atomic_data): - kurucz_atomic_data.prepare_atom_data([14, 20]) + kurucz_atomic_data.prepare_atom_data( + [14, 20], + line_interaction_type="scatter", + nlte_species=[], + continuum_interaction_species=[], + ) lines = kurucz_atomic_data.lines.reset_index() assert lines["atomic_number"].isin([14, 20]).all() assert len(lines.loc[lines["atomic_number"] == 14]) > 0 diff --git a/tardis/io/tests/test_config_reader.py b/tardis/io/tests/test_config_reader.py deleted file mode 100644 index 36462eb289a..00000000000 --- a/tardis/io/tests/test_config_reader.py +++ /dev/null @@ -1,207 +0,0 @@ -# tests for the config reader module -import os -from attr import validate -import pytest -import pandas as pd -from numpy.testing import assert_almost_equal -from jsonschema.exceptions import ValidationError - -from tardis.io import config_reader -from tardis.io.config_reader import Configuration - - -def data_path(filename): - data_dir = os.path.dirname(__file__) - return os.path.abspath(os.path.join(data_dir, "data", filename)) - - -def test_convergence_section_parser(): - test_convergence_section = { - "type": "damped", - "lock_t_inner_cyles": 1, - "t_inner_update_exponent": -0.5, - "damping_constant": 0.5, - "threshold": 0.05, - "fraction": 0.8, - "hold_iterations": 3, - "t_rad": {"damping_constant": 1.0}, - } - - parsed_convergence_section = config_reader.parse_convergence_section( - test_convergence_section - ) - - assert_almost_equal( - parsed_convergence_section["t_rad"]["damping_constant"], 1.0 - ) - - assert_almost_equal( - parsed_convergence_section["w"]["damping_constant"], 0.5 - ) - - -def test_from_config_dict(tardis_config_verysimple): - conf = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - assert conf.config_dirname == "test" - - assert_almost_equal( - conf.spectrum.start.value, - tardis_config_verysimple["spectrum"]["start"].value, - ) - - assert_almost_equal( - conf.spectrum.stop.value, - tardis_config_verysimple["spectrum"]["stop"].value, - ) - - tardis_config_verysimple["spectrum"]["start"] = "Invalid" - with pytest.raises(ValidationError): - conf = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - - -def test_config_hdf(hdf_file_path, tardis_config_verysimple): - expected = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - expected.to_hdf(hdf_file_path, overwrite=True) - actual = pd.read_hdf(hdf_file_path, key="/simulation/config") - expected = expected.get_properties()["config"] - assert actual[0] == expected[0] - - -def test_model_section_config(tardis_config_verysimple): - """ - Configuration Validation Test for Model Section of the Tardis Config YAML File - - Validates: - Density: branch85_w7 - Velocity (Start < End) - - Parameter - --------- - `tardis_config_verysimple` : YAML File - - Result - ------ - Assertion based on validation for specified values - """ - conf = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - - assert conf.model.structure.density.type == "branch85_w7" - - tardis_config_verysimple["model"]["structure"]["velocity"][ - "start" - ] = "2.0e4 km/s" - tardis_config_verysimple["model"]["structure"]["velocity"][ - "stop" - ] = "1.1e4 km/s" - with pytest.raises(ValueError) as ve: - if ( - conf.model.structure.velocity.start - < conf.model.structure.velocity.stop - ): - raise ValueError("Stop Value must be greater than Start Value") - assert ve.type is ValueError - - -def test_supernova_section_config(tardis_config_verysimple): - """ - Configuration Validation Test for Supernova Section of the Tardis Config YAML File - - Validates: - Time of Explosion (Must always be positive) - Luminosity Wavelength Limits (Start < End) - - Parameter - --------- - `tardis_config_verysimple` : YAML File - - Result - ------ - Assertion based on validation for specified values - """ - conf = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - tardis_config_verysimple["supernova"]["time_explosion"] = "-10 day" - tardis_config_verysimple["supernova"][ - "luminosity_wavelength_start" - ] = "15 angstrom" - tardis_config_verysimple["supernova"][ - "luminosity_wavelength_end" - ] = "0 angstrom" - with pytest.raises(ValueError) as ve: - if conf.supernova.time_explosion.value > 0: - raise ValueError("Time of Explosion cannot be negative") - assert ve.type is ValueError - - with pytest.raises(ValueError) as ve: - if ( - conf.supernova.luminosity_wavelength_start.value - < conf.supernova.luminosity_wavelength_end.value - ): - raise ValueError( - "End Limit must be greater than Start Limit for Luminosity" - ) - assert ve.type is ValueError - - -def test_plasma_section_config(tardis_config_verysimple): - """ - Configuration Validation Test for Plasma Section of the Tardis Config YAML File - - Validates: - Initial temperature inner (must be greater than -1K) - Initial radiative temperature (must be greater than -1K) - - Parameter - --------- - `tardis_config_verysimple` : YAML File - - Result - ------ - Assertion based on validation for specified values - """ - conf = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - tardis_config_verysimple["plasma"]["initial_t_inner"] = "-100 K" - tardis_config_verysimple["plasma"]["initial_t_rad"] = "-100 K" - with pytest.raises(ValueError) as ve: - if (conf.plasma.initial_t_inner.value >= -1) and ( - conf.plasma.initial_t_rad.value >= -1 - ): - raise ValueError("Initial Temperatures are Invalid") - assert ve.type is ValueError - - -def test_spectrum_section_config(tardis_config_verysimple): - """ - Configuration Validation Test for Plasma Section of the Tardis Config YAML File - - Validates: - Spectrum Start & End Limits (Start < End) - - Parameter - --------- - `tardis_config_verysimple` : YAML File - - Result - ------ - Assertion based on validation for specified values - """ - conf = Configuration.from_config_dict( - tardis_config_verysimple, validate=True, config_dirname="test" - ) - tardis_config_verysimple["spectrum"]["start"] = "2500 angstrom" - tardis_config_verysimple["spectrum"]["stop"] = "500 angstrom" - with pytest.raises(ValueError) as ve: - if not conf.spectrum.stop.value < conf.spectrum.start.value: - raise ValueError("Start Value must be less than Stop Value") - assert ve.type is ValueError diff --git a/tardis/io/tests/test_decay.py b/tardis/io/tests/test_decay.py index 42856c47b78..4acccabfb57 100644 --- a/tardis/io/tests/test_decay.py +++ b/tardis/io/tests/test_decay.py @@ -1,7 +1,7 @@ import pytest import pandas as pd -from tardis.io.decay import IsotopeAbundances +from tardis.model.matter.decay import IsotopicMassFraction from numpy.testing import assert_almost_equal @@ -10,17 +10,17 @@ def simple_abundance_model(): index = pd.MultiIndex.from_tuples( [(28, 56)], names=["atomic_number", "mass_number"] ) - return IsotopeAbundances([[1.0, 1.0]], index=index) + return IsotopicMassFraction([[1.0, 1.0]], index=index) def test_simple_decay(simple_abundance_model): decayed_abundance = simple_abundance_model.decay(100) - assert_almost_equal(decayed_abundance.loc[26, 56][0], 0.55752) - assert_almost_equal(decayed_abundance.loc[26, 56][1], 0.55752) - assert_almost_equal(decayed_abundance.loc[27, 56][0], 0.4423791) - assert_almost_equal(decayed_abundance.loc[27, 56][1], 0.4423791) - assert_almost_equal(decayed_abundance.loc[28, 56][0], 1.1086e-05) - assert_almost_equal(decayed_abundance.loc[28, 56][1], 1.1086e-05) + assert_almost_equal(decayed_abundance.loc[26, 56][0], 0.55754786) + assert_almost_equal(decayed_abundance.loc[26, 56][1], 0.55754786) + assert_almost_equal(decayed_abundance.loc[27, 56][0], 0.44235126) + assert_almost_equal(decayed_abundance.loc[27, 56][1], 0.44235126) + assert_almost_equal(decayed_abundance.loc[28, 56][0], 1.10859709e-05) + assert_almost_equal(decayed_abundance.loc[28, 56][1], 1.10859709e-05) @pytest.fixture diff --git a/tardis/io/tests/test_model_reader.py b/tardis/io/tests/test_model_reader.py index 60a110b1a91..97a6ac7fe63 100644 --- a/tardis/io/tests/test_model_reader.py +++ b/tardis/io/tests/test_model_reader.py @@ -1,53 +1,51 @@ -import os - -from astropy import units as u +import h5py import numpy as np import pytest +from astropy import units as u -import tardis -from tardis.io.config_reader import Configuration -from tardis.io.model_reader import ( - read_artis_density, - read_simple_ascii_abundances, +from tardis.io.configuration.config_reader import Configuration +from tardis.io.model.readers.artis import read_artis_density +from tardis.io.model.readers.cmfgen import ( + read_cmfgen_composition, + read_cmfgen_density, +) +from tardis.io.model.readers.generic_readers import ( read_csv_composition, + read_simple_ascii_abundances, read_uniform_abundances, - read_cmfgen_density, - read_cmfgen_composition, ) -data_path = os.path.join(tardis.__path__[0], "io", "tests", "data") - @pytest.fixture -def artis_density_fname(): - return os.path.join(data_path, "artis_model.dat") +def artis_density_fname(example_model_file_dir): + return example_model_file_dir / "artis_model.dat" @pytest.fixture -def artis_abundances_fname(): - return os.path.join(data_path, "artis_abundances.dat") +def artis_abundances_fname(example_model_file_dir): + return example_model_file_dir / "artis_abundances.dat" @pytest.fixture -def cmfgen_fname(): - return os.path.join(data_path, "cmfgen_model.csv") +def cmfgen_fname(example_model_file_dir): + return example_model_file_dir / "cmfgen_model.csv" @pytest.fixture -def csv_composition_fname(): - return os.path.join(data_path, "csv_composition.csv") +def csv_composition_fname(example_model_file_dir): + return example_model_file_dir / "csv_composition.csv" @pytest.fixture -def isotope_uniform_abundance(): - config_path = os.path.join( - data_path, "tardis_configv1_isotope_uniabund.yml" +def isotope_uniform_abundance(example_model_file_dir): + config_path = ( + example_model_file_dir / "tardis_configv1_isotope_uniabund.yml" ) config = Configuration.from_yaml(config_path) return config.model.abundances -def test_simple_read_artis_density(artis_density_fname): +def test_simple_read_artis_density(artis_density_fname: str): time_of_model, velocity, mean_density = read_artis_density( artis_density_fname ) @@ -55,8 +53,8 @@ def test_simple_read_artis_density(artis_density_fname): assert np.isclose(0.00114661 * u.day, time_of_model, atol=1e-7 * u.day) assert np.isclose( mean_density[23], - 0.2250048 * u.g / u.cm ** 3, - atol=1.0e-6 * u.g / u.cm ** 3, + 0.2250048 * u.g / u.cm**3, + atol=1.0e-6 * u.g / u.cm**3, ) assert len(mean_density) == 69 assert len(velocity) == len(mean_density) + 1 @@ -115,11 +113,11 @@ def test_simple_read_cmfgen_density(cmfgen_fname): assert np.isclose(0.976 * u.day, time_of_model, atol=1e-7 * u.day) assert np.isclose( mean_density[4], - 4.2539537e-09 * u.g / u.cm ** 3, - atol=1.0e-6 * u.g / u.cm ** 3, + 4.2539537e-09 * u.g / u.cm**3, + atol=1.0e-6 * u.g / u.cm**3, ) assert np.isclose( - electron_densities[5], 2.6e14 * u.cm ** -3, atol=1.0e-6 * u.cm ** -3 + electron_densities[5], 2.6e14 * u.cm**-3, atol=1.0e-6 * u.cm**-3 ) assert len(mean_density) == 9 assert len(velocity) == len(mean_density) + 1 diff --git a/tardis/io/util.py b/tardis/io/util.py index c3b2c842d0e..06937aaec7f 100644 --- a/tardis/io/util.py +++ b/tardis/io/util.py @@ -1,22 +1,22 @@ # Utility functions for the IO part of TARDIS +import collections.abc as collections_abc +import hashlib +import logging import os import re -import logging - -import pandas as pd -import numpy as np -import collections +import shutil from collections import OrderedDict +from functools import lru_cache -import requests +import numpy as np +import pandas as pd import yaml -from tqdm.auto import tqdm - -from tardis import constants as const from astropy import units as u +from astropy.utils.data import download_file from tardis import __path__ as TARDIS_PATH +from tardis import constants as const logger = logging.getLogger(__name__) @@ -138,10 +138,6 @@ def yaml_load_file(filename, loader=yaml.Loader): return yaml.load(stream, Loader=loader) -def yaml_load_config_file(filename): - return yaml_load_file(filename, YAMLLoader) - - def traverse_configs(base, other, func, *args): """ Recursively traverse a base dict or list along with another one @@ -159,11 +155,11 @@ def traverse_configs(base, other, func, *args): args : Arguments passed into `func` """ - if isinstance(base, collections.Mapping): + if isinstance(base, collections_abc.Mapping): for k in base: traverse_configs(base[k], other[k], func, *args) elif ( - isinstance(base, collections.Iterable) + isinstance(base, collections_abc.Iterable) and not isinstance(base, basestring) and not hasattr(base, "shape") ): @@ -246,7 +242,7 @@ def to_hdf_util( path_or_buf, complevel=complevel, complib=complib ) except TypeError as e: - if e.message == "Expected bytes, got HDFStore": + if str(e) == "Expected bytes, got HDFStore": # when path_or_buf is an HDFStore buffer instead logger.debug( "Expected bytes, got HDFStore. Changing path to HDF buffer" @@ -278,7 +274,7 @@ def to_hdf_util( pd.DataFrame(value).to_hdf(buf, os.path.join(path, key)) else: pd.DataFrame(value).to_hdf(buf, os.path.join(path, key)) - else: # value is a TARDIS object like model, runner or plasma + else: # value is a TARDIS object like model, transport or plasma try: value.to_hdf(buf, path, name=key, overwrite=overwrite) except AttributeError: @@ -391,33 +387,34 @@ def to_hdf( ) -def download_from_url(url, dst): - """ - kindly used from https://gist.github.com/wy193777/0e2a4932e81afc6aa4c8f7a2984f34e2 - @param: url to download file - @param: dst place to put the file +@lru_cache(maxsize=None) +def download_from_url(url, dst, checksum, src=None, retries=3): + """Download files from a given URL + + Parameters + ---------- + url : str + URL to download from + dst : str + Destination folder for the downloaded file + src : tuple + List of URLs to use as mirrors """ - file_size = int(requests.head(url).headers["Content-Length"]) - if os.path.exists(dst): - first_byte = os.path.getsize(dst) + cached_file_path = download_file(url, sources=src, pkgname="tardis") + + with open(cached_file_path, "rb") as f: + new_checksum = hashlib.md5(f.read()).hexdigest() + + if checksum == new_checksum: + shutil.copy(cached_file_path, dst) + + elif checksum != new_checksum and retries > 0: + retries -= 1 + logger.warning( + f"Incorrect checksum, retrying... ({retries+1} attempts remaining)" + ) + download_from_url(url, dst, checksum, src, retries) + else: - first_byte = 0 - if first_byte >= file_size: - return file_size - header = {f"Range": "bytes={first_byte}-{file_size}"} - pbar = tqdm( - total=file_size, - initial=first_byte, - unit="B", - unit_scale=True, - desc=url.split("/")[-1], - ) - req = requests.get(url, headers=header, stream=True) - with open(dst, "ab") as f: - for chunk in req.iter_content(chunk_size=1024): - if chunk: - f.write(chunk) - pbar.update(1024) - pbar.close() - return file_size + logger.error("Maximum number of retries reached. Aborting") diff --git a/tardis/model/__init__.py b/tardis/model/__init__.py index 66f102eba18..4b7881ad71e 100644 --- a/tardis/model/__init__.py +++ b/tardis/model/__init__.py @@ -1 +1,9 @@ -from tardis.model.base import * +""" +Holding information about the TARDIS model. + +This includes information about the shell structure, +density, abundance, temperatures and dilution +factor of the model used in the simulation. +""" + +from tardis.model.base import SimulationState diff --git a/tardis/model/base.py b/tardis/model/base.py index 12f7dd1bf31..adb86b99bd6 100644 --- a/tardis/model/base.py +++ b/tardis/model/base.py @@ -1,91 +1,42 @@ -import os import logging +import os +from pathlib import Path + import numpy as np -import pandas as pd from astropy import units as u -from tardis import constants -from tardis.util.base import quantity_linspace -from tardis.io.parsers.csvy import load_csvy -from tardis.io.model_reader import ( - read_density_file, - read_abundances_file, - read_uniform_abundances, - parse_csv_abundances, +from tardis import constants +from tardis.io.configuration.config_reader import Configuration +from tardis.io.configuration.config_validator import validate_dict +from tardis.io.model.readers.csvy import ( + load_csvy, ) -from tardis.io.config_validator import validate_dict -from tardis.io.config_reader import Configuration from tardis.io.util import HDFWriterMixin -from tardis.io.decay import IsotopeAbundances -from tardis.model.density import HomologousDensity -from pyne import nucname +from tardis.model.matter.composition import Composition +from tardis.model.parse_input import ( + parse_abundance_config, + parse_csvy_composition, + parse_csvy_geometry, + parse_csvy_radiation_field_state, + parse_radiation_field_state, + parse_structure_config, + parse_packet_source, +) +from tardis.transport.montecarlo.packet_source import BlackBodySimpleSource +from tardis.model.radiation_field_state import ( + DiluteBlackBodyRadiationFieldState, +) +from tardis.util.base import is_valid_nuclide_or_elem logger = logging.getLogger(__name__) -class ModelState: - """ - Store Model State Information. +SCHEMA_DIR = ( + Path(__file__).parent / ".." / "io" / "configuration" / "schemas" +).resolve() - Parameters - ---------- - v_inner : astropy.units.quantity.Quantity - v_outer : astropy.units.quantity.Quantity - r_inner : astropy.units.quantity.Quantity - r_outer : astropy.units.quantity.Quantity - density : astropy.units.quantity.Quantity - time_explosion : astropy.units.quantity.Quantity - Attributes - ---------- - geometry : pd.DataFrame - DataFrame storing `v_inner`, `v_outer`, `r_inner` and `r_outer`. - geometry_units : dict - Units of arrays stored in the `geometry` dataframe. - """ - - def __init__( - self, v_inner, v_outer, r_inner, r_outer, time_explosion, density - ): - self.time_explosion = time_explosion - self.density = density - self.geometry = pd.DataFrame( - { - "v_inner": v_inner.value, - "r_inner": r_inner.value, - "v_outer": v_outer.value, - "r_outer": r_outer.value, - } - ) - self.geometry_units = { - "v_inner": v_inner.unit, - "r_inner": r_inner.unit, - "v_outer": v_outer.unit, - "r_outer": r_outer.unit, - } - - @property - def v_inner(self): - """Inner boundary velocity.""" - return self.geometry.v_inner.values * self.geometry_units["v_inner"] - - @property - def r_inner(self): - """Inner radius of model shells.""" - return self.geometry.r_inner.values * self.geometry_units["r_inner"] - - @property - def v_outer(self): - """Outer boundary velocity.""" - return self.geometry.v_outer.values * self.geometry_units["v_outer"] - - @property - def r_outer(self): - """Outer radius of model shells.""" - return self.geometry.r_outer.values * self.geometry_units["r_outer"] - - -class Radial1DModel(HDFWriterMixin): +class SimulationState(HDFWriterMixin): """ An object that hold information about the individual shells. @@ -96,11 +47,11 @@ class Radial1DModel(HDFWriterMixin): boundaries .. note:: To access the entire, "uncut", velocity array, use `raw_velocity` - homologous_density : HomologousDensity abundance : pd.DataFrame time_explosion : astropy.units.Quantity Time since explosion t_inner : astropy.units.Quantity + elemental_mass: pd.Series luminosity_requested : astropy.units.quantity.Quantity t_radiative : astropy.units.Quantity Radiative temperature for the shells @@ -137,153 +88,56 @@ class Radial1DModel(HDFWriterMixin): hdf_properties = [ "t_inner", - "w", + "dilution_factor", "t_radiative", "v_inner", "v_outer", - "homologous_density", + "density", "r_inner", + "time_explosion", ] - hdf_name = "model" + hdf_name = "simulation_state" def __init__( self, - velocity, - homologous_density, - abundance, - isotope_abundance, + geometry, + composition, + radiation_field_state, time_explosion, - t_inner, - luminosity_requested=None, - t_radiative=None, - dilution_factor=None, - v_boundary_inner=None, - v_boundary_outer=None, + packet_source, electron_densities=None, ): - self._v_boundary_inner = None - self._v_boundary_outer = None - self._velocity = None - self.raw_velocity = velocity - self.v_boundary_inner = v_boundary_inner - self.v_boundary_outer = v_boundary_outer - self.homologous_density = homologous_density - self._abundance = abundance + self.geometry = geometry + self.composition = composition + self.radiation_field_state = radiation_field_state self.time_explosion = time_explosion self._electron_densities = electron_densities - v_outer = self.velocity[1:] - v_inner = self.velocity[:-1] - density = ( - self.homologous_density.calculate_density_at_time_of_simulation( - self.time_explosion - )[self.v_boundary_inner_index + 1 : self.v_boundary_outer_index + 1] - ) - self.model_state = ModelState( - v_inner=v_inner, - v_outer=v_outer, - r_inner=self.time_explosion * v_inner, - r_outer=self.time_explosion * v_outer, - time_explosion=self.time_explosion, - density=density, - ) - self.raw_abundance = self._abundance - self.raw_isotope_abundance = isotope_abundance - - if t_inner is None: - if luminosity_requested is not None: - self.t_inner = ( - ( - luminosity_requested - / ( - 4 - * np.pi - * self.r_inner[0] ** 2 - * constants.sigma_sb - ) - ) - ** 0.25 - ).to("K") - else: - raise ValueError( - "Both t_inner and luminosity_requested cannot " "be None." - ) - else: - self.t_inner = t_inner - - if t_radiative is None: - lambda_wien_inner = constants.b_wien / self.t_inner - self._t_radiative = constants.b_wien / ( - lambda_wien_inner - * (1 + (self.v_middle - self.v_boundary_inner) / constants.c) - ) - else: - # self._t_radiative = t_radiative[self.v_boundary_inner_index + 1:self.v_boundary_outer_index] - self._t_radiative = t_radiative - - if dilution_factor is None: - self._dilution_factor = 0.5 * ( - 1 - - np.sqrt( - 1 - (self.r_inner[0] ** 2 / self.r_middle ** 2).to(1).value - ) - ) - else: - # self.dilution_factor = dilution_factor[self.v_boundary_inner_index + 1:self.v_boundary_outer_index] - self._dilution_factor = dilution_factor + self.packet_source = packet_source @property - def w(self): - return self.dilution_factor - - @w.setter - def w(self, value): - self.dilution_factor = value + def blackbody_packet_source(self): + return self.packet_source @property - def t_rad(self): - return self.t_radiative + def t_inner(self): + return self.packet_source.temperature - @t_rad.setter - def t_rad(self, value): - self.t_radiative = value + @t_inner.setter + def t_inner(self, value): + self.packet_source.temperature = value @property def dilution_factor(self): - if len(self._dilution_factor) == self.no_of_shells: - return self._dilution_factor - - # if self.v_boundary_inner in self.raw_velocity: - # v_inner_ind = np.argwhere(self.raw_velocity == self.v_boundary_inner)[0][0] - # else: - # v_inner_ind = np.searchsorted(self.raw_velocity, self.v_boundary_inner) - 1 - # if self.v_boundary_outer in self.raw_velocity: - # v_outer_ind = np.argwhere(self.raw_velocity == self.v_boundary_outer)[0][0] - # else: - # v_outer_ind = np.searchsorted(self.raw_velocity, self.v_boundary_outer) - - return self._dilution_factor[ - self.v_boundary_inner_index + 1 : self.v_boundary_outer_index + 1 + return self.radiation_field_state.dilution_factor[ + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index ] @dilution_factor.setter - def dilution_factor(self, value): - if len(value) == len(self._dilution_factor): - self._dilution_factor = value - elif len(value) == self.no_of_shells: - # if self.v_boundary_inner in self.raw_velocity: - # v_inner_ind = np.argwhere(self.raw_velocity == self.v_boundary_inner)[0][0] - # else: - # v_inner_ind = np.searchsorted(self.raw_velocity, self.v_boundary_inner) - 1 - # if self.v_boundary_outer in self.raw_velocity: - # v_outer_ind = np.argwhere(self.raw_velocity == self.v_boundary_outer)[0][0] - # else: - # v_outer_ind = np.searchsorted(self.raw_velocity, self.v_boundary_outer) - # assert v_outer_ind - v_inner_ind == self.no_of_shells, "trad shape different from number of shells" - self._dilution_factor[ - self.v_boundary_inner_index - + 1 : self.v_boundary_outer_index - + 1 - ] = value + def dilution_factor(self, new_dilution_factor): + if len(new_dilution_factor) == self.no_of_shells: + self.radiation_field_state.dilution_factor[ + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index + ] = new_dilution_factor else: raise ValueError( "Trying to set dilution_factor for unmatching number" @@ -292,57 +146,79 @@ def dilution_factor(self, value): @property def t_radiative(self): - if len(self._t_radiative) == self.no_of_shells: - return self._t_radiative - - # if self.v_boundary_inner in self.raw_velocity: - # v_inner_ind = np.argwhere(self.raw_velocity == self.v_boundary_inner)[0][0] - # else: - # v_inner_ind = np.searchsorted(self.raw_velocity, self.v_boundary_inner) - 1 - # if self.v_boundary_outer in self.raw_velocity: - # v_outer_ind = np.argwhere(self.raw_velocity == self.v_boundary_outer)[0][0] - # else: - # v_outer_ind = np.searchsorted(self.raw_velocity, self.v_boundary_outer) - - return self._t_radiative[ - self.v_boundary_inner_index + 1 : self.v_boundary_outer_index + 1 + return self.radiation_field_state.t_radiative[ + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index ] @t_radiative.setter - def t_radiative(self, value): - if len(value) == len(self._t_radiative): - self._t_radiative = value - elif len(value) == self.no_of_shells: - # if self.v_boundary_inner in self.raw_velocity: - # v_inner_ind = np.argwhere(self.raw_velocity == self.v_boundary_inner)[0][0] - # else: - # v_inner_ind = np.searchsorted(self.raw_velocity, self.v_boundary_inner) - 1 - # if self.v_boundary_outer in self.raw_velocity: - # v_outer_ind = np.argwhere(self.raw_velocity == self.v_boundary_outer)[0][0] - # else: - # v_outer_ind = np.searchsorted(self.raw_velocity, self.v_boundary_outer) - # assert v_outer_ind - v_inner_ind == self.no_of_shells, "trad shape different from number of shells" - self._t_radiative[ - self.v_boundary_inner_index - + 1 : self.v_boundary_outer_index - + 1 - ] = value + def t_radiative(self, new_t_radiative): + if len(new_t_radiative) == self.no_of_shells: + self.radiation_field_state.t_radiative[ + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index + ] = new_t_radiative else: raise ValueError( - "Trying to set t_radiative for unmatching number" "of shells." + "Trying to set t_radiative for different number of shells." ) + @property + def elemental_number_density(self): + elemental_number_density = ( + ( + self.composition.elemental_mass_fraction + * self.composition.density + ) + .divide(self.composition.element_masses, axis=0) + .dropna() + ) + elemental_number_density = elemental_number_density.iloc[ + :, + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index, + ] + elemental_number_density.columns = range( + len(elemental_number_density.columns) + ) + return elemental_number_density + + @property + def isotopic_number_density(self): + isotopic_number_density = ( + self.composition.isotopic_mass_fraction * self.composition.density + ).divide( + self.composition.isotope_masses.loc[ + self.composition.isotopic_mass_fraction.index + ] + * u.u.to(u.g), + axis=0, + ) + isotopic_number_density = isotopic_number_density.iloc[ + :, + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index, + ] + isotopic_number_density.columns = range( + len(isotopic_number_density.columns) + ) + return isotopic_number_density + @property def radius(self): return self.time_explosion * self.velocity + @property + def v_boundary_inner(self): + return self.geometry.v_inner_boundary + + @property + def v_boundary_outer(self): + return self.geometry.v_outer_boundary + @property def r_inner(self): - return self.model_state.r_inner + return self.geometry.r_inner_active @property def r_outer(self): - return self.model_state.r_outer + return self.geometry.r_outer_active @property def r_middle(self): @@ -350,22 +226,16 @@ def r_middle(self): @property def velocity(self): - - if self._velocity is None: - self._velocity = self.raw_velocity[ - self.v_boundary_inner_index : self.v_boundary_outer_index + 1 - ] - self._velocity[0] = self.v_boundary_inner - self._velocity[-1] = self.v_boundary_outer - return self._velocity + velocity = self.geometry.v_outer_active.copy() + return velocity.insert(0, self.geometry.v_inner_active[0]) @property def v_inner(self): - return self.model_state.v_inner + return self.geometry.v_inner_active @property def v_outer(self): - return self.model_state.v_outer + return self.geometry.v_outer_active @property def v_middle(self): @@ -373,261 +243,104 @@ def v_middle(self): @property def density(self): - return self.model_state.density + return self.composition.density[ + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index + ] @property def abundance(self): - if not self.raw_isotope_abundance.empty: - self._abundance = self.raw_isotope_abundance.decay( - self.time_explosion - ).merge(self.raw_abundance) - abundance = self._abundance.loc[ - :, self.v_boundary_inner_index : self.v_boundary_outer_index - 1 + elemental_mass_fraction = ( + self.composition.elemental_mass_fraction.copy() + ) + elemental_mass_fraction = elemental_mass_fraction.iloc[ + :, + self.geometry.v_inner_boundary_index : self.geometry.v_outer_boundary_index, ] - abundance.columns = range(len(abundance.columns)) - return abundance + elemental_mass_fraction.columns = range( + len(elemental_mass_fraction.columns) + ) + return elemental_mass_fraction @property def volume(self): - return ((4.0 / 3) * np.pi * (self.r_outer ** 3 - self.r_inner ** 3)).cgs + return ((4.0 / 3) * np.pi * (self.r_outer**3 - self.r_inner**3)).cgs @property def no_of_shells(self): - return len(self.velocity) - 1 + return self.geometry.no_of_shells_active @property def no_of_raw_shells(self): - return len(self.raw_velocity) - 1 - - @property - def v_boundary_inner(self): - if self._v_boundary_inner is None: - return self.raw_velocity[0] - if self._v_boundary_inner < 0 * u.km / u.s: - return self.raw_velocity[0] - return self._v_boundary_inner - - @v_boundary_inner.setter - def v_boundary_inner(self, value): - if value is not None: - if value > 0 * u.km / u.s: - value = u.Quantity(value, self.v_boundary_inner.unit) - if value > self.v_boundary_outer: - raise ValueError( - "v_boundary_inner must not be higher than " - "v_boundary_outer." - ) - if value > self.raw_velocity[-1]: - raise ValueError( - "v_boundary_inner is outside of " "the model range." - ) - if value < self.raw_velocity[0]: - raise ValueError( - "v_boundary_inner is lower than the lowest shell in the model." - ) - self._v_boundary_inner = value - # Invalidate the cached cut-down velocity array - self._velocity = None - - @property - def v_boundary_outer(self): - if self._v_boundary_outer is None: - return self.raw_velocity[-1] - if self._v_boundary_outer < 0 * u.km / u.s: - return self.raw_velocity[-1] - return self._v_boundary_outer - - @v_boundary_outer.setter - def v_boundary_outer(self, value): - if value is not None: - if value > 0 * u.km / u.s: - value = u.Quantity(value, self.v_boundary_outer.unit) - if value < self.v_boundary_inner: - raise ValueError( - "v_boundary_outer must not be smaller than " - "v_boundary_inner." - ) - if value < self.raw_velocity[0]: - raise ValueError( - "v_boundary_outer is outside of " "the model range." - ) - if value > self.raw_velocity[-1]: - raise ValueError( - "v_boundary_outer is larger than the largest shell in the model." - ) - self._v_boundary_outer = value - # Invalidate the cached cut-down velocity array - self._velocity = None - - @property - def v_boundary_inner_index(self): - if self.v_boundary_inner in self.raw_velocity: - v_inner_ind = np.argwhere( - self.raw_velocity == self.v_boundary_inner - )[0][0] - else: - v_inner_ind = ( - np.searchsorted(self.raw_velocity, self.v_boundary_inner) - 1 - ) - return v_inner_ind - - @property - def v_boundary_outer_index(self): - if self.v_boundary_outer in self.raw_velocity: - v_outer_ind = np.argwhere( - self.raw_velocity == self.v_boundary_outer - )[0][0] - else: - v_outer_ind = np.searchsorted( - self.raw_velocity, self.v_boundary_outer - ) - return v_outer_ind - - # @property - # def v_boundary_inner_index(self): - # if self.v_boundary_inner <= self.raw_velocity[0]: - # return 0 - # else: - # idx = max(0, - # self.raw_velocity.searchsorted(self.v_boundary_inner) - 1) - # # check for zero volume of designated first cell - # if np.isclose(self.v_boundary_inner, self.raw_velocity[idx + 1], - # atol=1e-8 * u.km / u.s) and (self.v_boundary_inner <= - # self.raw_velocity[idx + 1]): - # idx += 1 - # return idx - # - # @property - # def v_boundary_outer_index(self): - # if self.v_boundary_outer >= self.raw_velocity[-1]: - # return None - # return self.raw_velocity.searchsorted(self.v_boundary_outer) + 1 + return self.geometry.no_of_shells @classmethod - def from_config(cls, config): + def from_config(cls, config, atom_data, legacy_mode_enabled=False): """ - Create a new Radial1DModel instance from a Configuration object. + Create a new SimulationState instance from a Configuration object. Parameters ---------- config : tardis.io.config_reader.Configuration + atom_data : tardis.io.AtomData Returns ------- - Radial1DModel + SimulationState """ time_explosion = config.supernova.time_explosion.cgs - structure = config.model.structure - electron_densities = None - temperature = None - if structure.type == "specific": - velocity = quantity_linspace( - structure.velocity.start, - structure.velocity.stop, - structure.velocity.num + 1, - ).cgs - homologous_density = HomologousDensity.from_config(config) - elif structure.type == "file": - if os.path.isabs(structure.filename): - structure_fname = structure.filename - else: - structure_fname = os.path.join( - config.config_dirname, structure.filename - ) - - ( - time_0, - velocity, - density_0, - electron_densities, - temperature, - ) = read_density_file(structure_fname, structure.filetype) - density_0 = density_0.insert(0, 0) - homologous_density = HomologousDensity(density_0, time_0) - else: - raise NotImplementedError - # Note: This is the number of shells *without* taking in mind the - # v boundaries. - no_of_shells = len(velocity) - 1 - - if temperature: - t_radiative = temperature - elif config.plasma.initial_t_rad > 0 * u.K: - t_radiative = ( - np.ones(no_of_shells + 1) * config.plasma.initial_t_rad - ) - else: - t_radiative = None - - if config.plasma.initial_t_inner < 0.0 * u.K: - luminosity_requested = config.supernova.luminosity_requested - t_inner = None - else: - luminosity_requested = None - t_inner = config.plasma.initial_t_inner - - abundances_section = config.model.abundances - isotope_abundance = pd.DataFrame() - - if abundances_section.type == "uniform": - abundance, isotope_abundance = read_uniform_abundances( - abundances_section, no_of_shells - ) - - elif abundances_section.type == "file": - if os.path.isabs(abundances_section.filename): - abundances_fname = abundances_section.filename - else: - abundances_fname = os.path.join( - config.config_dirname, abundances_section.filename - ) + ( + electron_densities, + t_radiative, + geometry, + density, + ) = parse_structure_config(config, time_explosion) - index, abundance, isotope_abundance = read_abundances_file( - abundances_fname, abundances_section.filetype - ) - - abundance = abundance.replace(np.nan, 0.0) - abundance = abundance[abundance.sum(axis=1) > 0] - - norm_factor = abundance.sum(axis=0) + isotope_abundance.sum(axis=0) + nuclide_mass_fraction, raw_isotope_abundance = parse_abundance_config( + config, geometry, time_explosion + ) - if np.any(np.abs(norm_factor - 1) > 1e-12): - logger.warning( - "Abundances have not been normalized to 1." " - normalizing" - ) - abundance /= norm_factor - isotope_abundance /= norm_factor + # using atom_data.mass.copy() to ensure that the original atom_data is not modified + composition = Composition( + density, + nuclide_mass_fraction, + raw_isotope_abundance, + atom_data.atom_data.mass.copy(), + ) - isotope_abundance = IsotopeAbundances(isotope_abundance) + packet_source = parse_packet_source( + config, geometry, legacy_mode_enabled + ) + radiation_field_state = parse_radiation_field_state( + config, + t_radiative, + geometry, + dilution_factor=None, + packet_source=packet_source, + ) return cls( - velocity=velocity, - homologous_density=homologous_density, - abundance=abundance, - isotope_abundance=isotope_abundance, + geometry=geometry, + composition=composition, + radiation_field_state=radiation_field_state, time_explosion=time_explosion, - t_radiative=t_radiative, - t_inner=t_inner, - luminosity_requested=luminosity_requested, - dilution_factor=None, - v_boundary_inner=structure.get("v_inner_boundary", None), - v_boundary_outer=structure.get("v_outer_boundary", None), + packet_source=packet_source, electron_densities=electron_densities, ) @classmethod - def from_csvy(cls, config): + def from_csvy(cls, config, atom_data=None, legacy_mode_enabled=False): """ - Create a new Radial1DModel instance from a Configuration object. + Create a new SimulationState instance from a Configuration object. Parameters ---------- config : tardis.io.config_reader.Configuration + atom_data : tardis.io.AtomData Returns ------- - Radial1DModel + SimulationState """ CSVY_SUPPORTED_COLUMNS = { "velocity", @@ -643,11 +356,9 @@ def from_csvy(cls, config): config.config_dirname, config.csvy_model ) csvy_model_config, csvy_model_data = load_csvy(csvy_model_fname) - base_dir = os.path.abspath(os.path.dirname(__file__)) - schema_dir = os.path.join(base_dir, "..", "io", "schemas") - csvy_schema_file = os.path.join(schema_dir, "csvy_model.yml") + csvy_schema_fname = SCHEMA_DIR / "csvy_model.yml" csvy_model_config = Configuration( - validate_dict(csvy_model_config, schemapath=csvy_schema_file) + validate_dict(csvy_model_config, schemapath=csvy_schema_fname) ) if hasattr(csvy_model_data, "columns"): @@ -655,7 +366,7 @@ def from_csvy(cls, config): [ name for name in csvy_model_data.columns - if nucname.iselement(name) or nucname.isnuclide(name) + if is_valid_nuclide_or_elem(name) ] ) unsupported_columns = ( @@ -675,156 +386,40 @@ def from_csvy(cls, config): ), "CSVY field descriptions exist without corresponding csv data" if unsupported_columns != set(): logger.warning( - "The following columns are " - "specified in the csvy model file," - f" but are IGNORED by TARDIS: {str(unsupported_columns)}" - ) + "The following columns are " + "specified in the csvy model file," + f" but are IGNORED by TARDIS: {str(unsupported_columns)}" + ) time_explosion = config.supernova.time_explosion.cgs electron_densities = None - temperature = None - - # if hasattr(csvy_model_config, 'v_inner_boundary'): - # v_boundary_inner = csvy_model_config.v_inner_boundary - # else: - # v_boundary_inner = None - - # if hasattr(csvy_model_config, 'v_outer_boundary'): - # v_boundary_outer = csvy_model_config.v_outer_boundary - # else: - # v_boundary_outer = None - - if hasattr(config, "model"): - if hasattr(config.model, "v_inner_boundary"): - v_boundary_inner = config.model.v_inner_boundary - else: - v_boundary_inner = None - - if hasattr(config.model, "v_outer_boundary"): - v_boundary_outer = config.model.v_outer_boundary - else: - v_boundary_outer = None - else: - v_boundary_inner = None - v_boundary_outer = None - - if hasattr(csvy_model_config, "velocity"): - velocity = quantity_linspace( - csvy_model_config.velocity.start, - csvy_model_config.velocity.stop, - csvy_model_config.velocity.num + 1, - ).cgs - else: - velocity_field_index = [ - field["name"] for field in csvy_model_config.datatype.fields - ].index("velocity") - velocity_unit = u.Unit( - csvy_model_config.datatype.fields[velocity_field_index]["unit"] - ) - velocity = csvy_model_data["velocity"].values * velocity_unit - velocity = velocity.to("cm/s") - if hasattr(csvy_model_config, "density"): - homologous_density = HomologousDensity.from_csvy( - config, csvy_model_config - ) - else: - time_0 = csvy_model_config.model_density_time_0 - density_field_index = [ - field["name"] for field in csvy_model_config.datatype.fields - ].index("density") - density_unit = u.Unit( - csvy_model_config.datatype.fields[density_field_index]["unit"] - ) - density_0 = csvy_model_data["density"].values * density_unit - density_0 = density_0.to("g/cm^3")[1:] - density_0 = density_0.insert(0, 0) - homologous_density = HomologousDensity(density_0, time_0) - - no_of_shells = len(velocity) - 1 - - # TODO -- implement t_radiative - # t_radiative = None - if temperature: - t_radiative = temperature - elif hasattr(csvy_model_data, "columns"): - if "t_rad" in csvy_model_data.columns: - t_rad_field_index = [ - field["name"] for field in csvy_model_config.datatype.fields - ].index("t_rad") - t_rad_unit = u.Unit( - csvy_model_config.datatype.fields[t_rad_field_index]["unit"] - ) - t_radiative = ( - csvy_model_data["t_rad"].iloc[0:].values * t_rad_unit - ) - else: - t_radiative = None - - dilution_factor = None - if hasattr(csvy_model_data, "columns"): - if "dilution_factor" in csvy_model_data.columns: - dilution_factor = ( - csvy_model_data["dilution_factor"].iloc[0:].to_numpy() - ) - - elif config.plasma.initial_t_rad > 0 * u.K: - t_radiative = np.ones(no_of_shells) * config.plasma.initial_t_rad - else: - t_radiative = None + geometry = parse_csvy_geometry( + config, csvy_model_config, csvy_model_data, time_explosion + ) - if config.plasma.initial_t_inner < 0.0 * u.K: - luminosity_requested = config.supernova.luminosity_requested - t_inner = None - else: - luminosity_requested = None - t_inner = config.plasma.initial_t_inner + composition = parse_csvy_composition( + atom_data, + csvy_model_config, + csvy_model_data, + time_explosion, + geometry, + ) - if hasattr(csvy_model_config, "abundance"): - abundances_section = csvy_model_config.abundance - abundance, isotope_abundance = read_uniform_abundances( - abundances_section, no_of_shells - ) - else: - index, abundance, isotope_abundance = parse_csv_abundances( - csvy_model_data - ) - abundance = abundance.loc[:, 1:] - abundance.columns = np.arange(abundance.shape[1]) - isotope_abundance = isotope_abundance.loc[:, 1:] - isotope_abundance.columns = np.arange(isotope_abundance.shape[1]) - - abundance = abundance.replace(np.nan, 0.0) - abundance = abundance[abundance.sum(axis=1) > 0] - isotope_abundance = isotope_abundance.replace(np.nan, 0.0) - isotope_abundance = isotope_abundance[isotope_abundance.sum(axis=1) > 0] - norm_factor = abundance.sum(axis=0) + isotope_abundance.sum(axis=0) - - if np.any(np.abs(norm_factor - 1) > 1e-12): - logger.warning( - "Abundances have not been normalized to 1." " - normalizing" - ) - abundance /= norm_factor - isotope_abundance /= norm_factor + packet_source = parse_packet_source( + config, geometry, legacy_mode_enabled + ) - # isotope_abundance = IsotopeAbundances(isotope_abundance) - isotope_abundance = IsotopeAbundances( - isotope_abundance, time_0=csvy_model_config.model_isotope_time_0 + radiation_field_state = parse_csvy_radiation_field_state( + config, csvy_model_config, csvy_model_data, geometry, packet_source ) - # isotope_abundance.time_0 = csvy_model_config.model_isotope_time_0 return cls( - velocity=velocity, - homologous_density=homologous_density, - abundance=abundance, - isotope_abundance=isotope_abundance, + geometry=geometry, + composition=composition, time_explosion=time_explosion, - t_radiative=t_radiative, - t_inner=t_inner, - luminosity_requested=luminosity_requested, - dilution_factor=dilution_factor, - v_boundary_inner=v_boundary_inner, - v_boundary_outer=v_boundary_outer, + radiation_field_state=radiation_field_state, + packet_source=packet_source, electron_densities=electron_densities, ) diff --git a/tardis/model/conftest.py b/tardis/model/conftest.py new file mode 100644 index 00000000000..2e7ce7de5eb --- /dev/null +++ b/tardis/model/conftest.py @@ -0,0 +1,8 @@ +from pathlib import Path + +import pytest + + +@pytest.fixture(scope="session") +def example_csvy_file_dir(): + return Path(__file__).resolve().parent / "tests/data" diff --git a/tardis/model/density.py b/tardis/model/density.py deleted file mode 100644 index 152b16cb477..00000000000 --- a/tardis/model/density.py +++ /dev/null @@ -1,220 +0,0 @@ -import numpy as np -from astropy import units as u - -from tardis.util.base import quantity_linspace -from tardis.io.util import HDFWriterMixin - - -class HomologousDensity(HDFWriterMixin): - """A class that holds an initial density and time - - Parameters - ---------- - density_0 : astropy.units.Quantity - time_0 : astropy.units.Quantity - - """ - - hdf_properties = ["density_0", "time_0"] - - def __init__(self, density_0, time_0): - self.density_0 = density_0 - self.time_0 = time_0 - - def calculate_density_at_time_of_simulation(self, time_explosion): - """ - Scale `density_0` from an `time_0` to the `time_explosion` by ^-3 - - Parameters - ---------- - time_explosion : astropy.units.Quantity - - Returns - ------- - astropy.units.Quantity - """ - return calculate_density_after_time( - self.density_0, self.time_0, time_explosion - ).cgs - - @classmethod - def from_csvy(cls, config, csvy_model_config): - """ - Create a new HomologousDensity instance from a base - Configuration object and a csvy model Configuration object. - - Parameters - ---------- - config : tardis.io.config_reader.Configuration - csvy_model_config : tardis.io.config_reader.Configuration - - Returns - ------- - HomologousDensity - - """ - if hasattr(csvy_model_config, "velocity"): - velocity = quantity_linspace( - csvy_model_config.velocity.start, - csvy_model_config.velocity.stop, - csvy_model_config.velocity.num + 1, - ).cgs - else: - velocity_field_index = [ - field.name for field in csvy_model_config.datatype.fields - ].index("velocity") - velocity_unit = u.Unit( - csvy_model_config.datatype.fields[velocity_field_index].unit - ) - velocity = csvy_model_config.velocity.values * velocity_unit - - adjusted_velocity = velocity.insert(0, 0) - v_middle = adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5 - no_of_shells = len(adjusted_velocity) - 1 - time_explosion = config.supernova.time_explosion.cgs - - if hasattr(csvy_model_config, "density"): - d_conf = csvy_model_config.density - density_type = d_conf.type - if density_type == "branch85_w7": - density_0 = calculate_power_law_density( - v_middle, d_conf.w7_v_0, d_conf.w7_rho_0, -7 - ) - time_0 = d_conf.w7_time_0 - elif density_type == "uniform": - density_0 = d_conf.value.to("g cm^-3") * np.ones(no_of_shells) - time_0 = d_conf.get("time_0", time_explosion) - elif density_type == "power_law": - density_0 = calculate_power_law_density( - v_middle, d_conf.v_0, d_conf.rho_0, d_conf.exponent - ) - time_0 = d_conf.get("time_0", time_explosion) - elif density_type == "exponential": - density_0 = calculate_exponential_density( - v_middle, d_conf.v_0, d_conf.rho_0 - ) - time_0 = d_conf.get("time_0", time_explosion) - else: - raise ValueError( - f"Unrecognized density type " f"'{d_conf.type}'" - ) - return cls(density_0, time_0) - - @classmethod - def from_config(cls, config): - """ - Create a new HomologousDensity instance from a Configuration object. - - Parameters - ---------- - config : tardis.io.config_reader.Configuration - - Returns - ------- - HomologousDensity - - """ - d_conf = config.model.structure.density - velocity = quantity_linspace( - config.model.structure.velocity.start, - config.model.structure.velocity.stop, - config.model.structure.velocity.num + 1, - ).cgs - - adjusted_velocity = velocity.insert(0, 0) - v_middle = adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5 - no_of_shells = len(adjusted_velocity) - 1 - time_explosion = config.supernova.time_explosion.cgs - - if d_conf.type == "branch85_w7": - density_0 = calculate_power_law_density( - v_middle, d_conf.w7_v_0, d_conf.w7_rho_0, -7 - ) - time_0 = d_conf.w7_time_0 - elif d_conf.type == "uniform": - density_0 = d_conf.value.to("g cm^-3") * np.ones(no_of_shells) - time_0 = d_conf.get("time_0", time_explosion) - elif d_conf.type == "power_law": - density_0 = calculate_power_law_density( - v_middle, d_conf.v_0, d_conf.rho_0, d_conf.exponent - ) - time_0 = d_conf.get("time_0", time_explosion) - elif d_conf.type == "exponential": - density_0 = calculate_exponential_density( - v_middle, d_conf.v_0, d_conf.rho_0 - ) - time_0 = d_conf.get("time_0", time_explosion) - else: - raise ValueError(f"Unrecognized density type " f"'{d_conf.type}'") - return cls(density_0, time_0) - - -def calculate_power_law_density(velocities, velocity_0, rho_0, exponent): - """ - - This function computes a descret exponential density profile. - :math:`\\rho = \\rho_0 \\times \\left( \\frac{v}{v_0} \\right)^n` - - Parameters - ---------- - velocities : astropy.Quantity - Array like velocity profile - velocity_0 : astropy.Quantity - reference velocity - rho_0 : astropy.Quantity - reference density - exponent : float - exponent used in the powerlaw - - Returns - ------- - densities : astropy.Quantity - - """ - densities = rho_0 * np.power((velocities / velocity_0), exponent) - return densities - - -def calculate_exponential_density(velocities, velocity_0, rho_0): - """ - This function computes the exponential density profile. - :math:`\\rho = \\rho_0 \\times \\exp \\left( -\\frac{v}{v_0} \\right)` - - Parameters - ---------- - velocities : astropy.Quantity - Array like velocity profile - velocity_0 : astropy.Quantity - reference velocity - rho_0 : astropy.Quantity - reference density - - Returns - ------- - densities : astropy.Quantity - - """ - densities = rho_0 * np.exp(-(velocities / velocity_0)) - return densities - - -def calculate_density_after_time(densities, time_0, time_explosion): - """ - scale the density from an initial time of the model to the - time of the explosion by ^-3 - - Parameters - ----------- - densities : astropy.units.Quantity - densities - time_0 : astropy.units.Quantity - time of the model - time_explosion : astropy.units.Quantity - time to be scaled to - - Returns - -------- - scaled_density - """ - - return densities * (time_explosion / time_0) ** -3 diff --git a/tardis/model/geometry/__init__.py b/tardis/model/geometry/__init__.py new file mode 100644 index 00000000000..44b4461913d --- /dev/null +++ b/tardis/model/geometry/__init__.py @@ -0,0 +1,10 @@ +""" +Holding information about model geometry for radial 1D models. + +The information stored about the model are the following attributes: +r_inner : The radius of the inner shell boundaries +r_outer : The radius of the outer shell boundaries +v_inner : The velocity of the inner boundaries of each shell +v_outer : The velocity of the outer boundaries of each shell +volume : Volume of each shell computed from r_outer and r_inner +""" diff --git a/tardis/model/geometry/radial1d.py b/tardis/model/geometry/radial1d.py new file mode 100644 index 00000000000..a6bf3382cbc --- /dev/null +++ b/tardis/model/geometry/radial1d.py @@ -0,0 +1,213 @@ +from numba import float64 +from numba.experimental import jitclass +import numpy as np +from astropy import units as u +import warnings + + +class HomologousRadial1DGeometry: + """ + Holds information about model geometry for radial 1D models. + + Parameters + ---------- + v_inner : astropy.units.quantity.Quantity + v_outer : astropy.units.quantity.Quantity + v_inner_boundary : astropy.units.quantity.Quantity + v_outer_boundary : astropy.units.quantity.Quantity + + Attributes + ---------- + volume : astropy.units.quantity.Quantity + Volume in each shell + """ + + def __init__( + self, + v_inner, + v_outer, + v_inner_boundary, + v_outer_boundary, + time_explosion, + ): + self.time_explosion = time_explosion + + # ensuring that the cells are continuous + assert np.allclose(v_inner[1:], v_outer[:-1]) + + assert "velocity" in v_inner.unit.physical_type + assert "velocity" in v_outer.unit.physical_type + + self.v_inner = v_inner + self.v_outer = v_outer + + # ensuring that the boundaries are within the simulation area + + if v_inner_boundary is None: + self.v_inner_boundary = self.v_inner[0] + elif v_inner_boundary < 0: + warnings.warn( + "v_inner_boundary < 0, assuming default value", + DeprecationWarning, + ) + self.v_inner_boundary = self.v_inner[0] + else: + self.v_inner_boundary = v_inner_boundary + + if v_outer_boundary is None: + self.v_outer_boundary = self.v_outer[-1] + elif v_outer_boundary < 0: + warnings.warn( + "v_outer_boundary < 0, assuming default value", + DeprecationWarning, + ) + self.v_outer_boundary = self.v_outer[-1] + else: + self.v_outer_boundary = v_outer_boundary + + assert self.v_inner_boundary < self.v_outer_boundary + if self.v_inner_boundary < self.v_inner[0]: + warnings.warn( + "Requesting inner boundary below inner shell. Extrapolating the inner cell" + ) + + if self.v_outer_boundary > self.v_outer[-1]: + warnings.warn( + "Requesting inner boundary below inner shell. Extrapolating the inner cell" + ) + + @property + def v_middle(self): + return (self.v_inner + self.v_outer) / 2.0 + + @property + def v_middle_active(self): + return self.v_middle[ + self.v_inner_boundary_index : self.v_outer_boundary_index + ] + + @property + def v_inner_boundary_index(self): + return np.clip( + np.searchsorted(self.v_inner, self.v_inner_boundary, side="right") + - 1, + 0, + None, + ) + + @property + def v_outer_boundary_index(self): + return np.clip( + np.searchsorted(self.v_outer, self.v_outer_boundary, side="left") + + 1, + None, + len(self.v_outer), + ) + + @property + def v_inner_active(self): + v_inner_active = self.v_inner[ + self.v_inner_boundary_index : self.v_outer_boundary_index + ].copy() + v_inner_active[0] = self.v_inner_boundary + return v_inner_active + + @property + def v_outer_active(self): + v_outer_active = self.v_outer[ + self.v_inner_boundary_index : self.v_outer_boundary_index + ].copy() + v_outer_active[-1] = self.v_outer_boundary + return v_outer_active + + @property + def r_inner(self): + return (self.v_inner * self.time_explosion).cgs + + @property + def r_inner_active(self): + return (self.v_inner_active * self.time_explosion).cgs + + @property + def r_outer(self): + return (self.v_outer * self.time_explosion).cgs + + @property + def r_outer_active(self): + return (self.v_outer_active * self.time_explosion).cgs + + @property + def r_middle(self): + return (self.v_middle * self.time_explosion).cgs + + @property + def r_middle_active(self): + return (self.v_middle_active * self.time_explosion).cgs + + @property + def volume(self): + """Volume in shell computed from r_outer and r_inner""" + return (4.0 / 3) * np.pi * (self.r_outer**3 - self.r_inner**3) + + @property + def volume_active(self): + """Volume in shell computed from r_outer and r_inner""" + return ( + (4.0 / 3) + * np.pi + * (self.r_outer_active**3 - self.r_inner_active**3) + ) + + @property + def no_of_shells(self): + return len(self.r_inner) + + @property + def no_of_shells_active(self): + return len(self.r_inner_active) + + def to_numba(self): + """ + Returns a new NumbaRadial1DGeometry object + + Returns + ------- + NumbaRadial1DGeometry + Numba version of Radial1DGeometry with properties in cgs units + """ + return NumbaRadial1DGeometry( + self.r_inner_active.to(u.cm).value, + self.r_outer_active.to(u.cm).value, + self.v_inner_active.to(u.cm / u.s).value, + self.v_outer_active.to(u.cm / u.s).value, + ) + + +numba_geometry_spec = [ + ("r_inner", float64[:]), + ("r_outer", float64[:]), + ("v_inner", float64[:]), + ("v_outer", float64[:]), + ("volume", float64[:]), +] + + +@jitclass(numba_geometry_spec) +class NumbaRadial1DGeometry(object): + def __init__(self, r_inner, r_outer, v_inner, v_outer): + """ + Radial 1D Geometry for the Numba mode + + Parameters + ---------- + r_inner : numpy.ndarray + r_outer : numpy.ndarray + v_inner : numpy.ndarray + v_outer : numpy.ndarray + volume : numpy.ndarray + """ + self.r_inner = r_inner + self.r_outer = r_outer + self.v_inner = v_inner + self.v_outer = v_outer + self.volume = (4 / 3) * np.pi * (self.r_outer**3 - self.r_inner**3) diff --git a/tardis/model/geometry/tests/test_radial1d.py b/tardis/model/geometry/tests/test_radial1d.py new file mode 100644 index 00000000000..e6c887180d0 --- /dev/null +++ b/tardis/model/geometry/tests/test_radial1d.py @@ -0,0 +1,117 @@ +from astropy import units as u +import numpy as np +import numpy.testing as npt + +from tardis.model.geometry.radial1d import HomologousRadial1DGeometry + +import pytest + + +@pytest.fixture(scope="function") +def homologous_radial1d_geometry(): + velocity = np.arange(8000, 21000, 1000) * u.km / u.s + v_inner = velocity[:-1] + v_outer = velocity[1:] + time_explosion = 5 * u.day + geometry = HomologousRadial1DGeometry( + v_inner, v_outer, v_inner[0], v_outer[-1], time_explosion + ) + return geometry + + +def test_vb_indices(homologous_radial1d_geometry): + # Testing if the indices returned are correct when inner and outer + # boundary are on the innermost and outermost shell + + homologous_radial1d_geometry.v_inner_boundary = ( + homologous_radial1d_geometry.v_inner[0] + ) + homologous_radial1d_geometry.v_outer_boundary = ( + homologous_radial1d_geometry.v_outer[-1] + ) + assert homologous_radial1d_geometry.v_inner_boundary_index == 0 + assert homologous_radial1d_geometry.v_outer_boundary_index == len( + homologous_radial1d_geometry.v_inner + ) + vib_index = homologous_radial1d_geometry.v_inner_boundary_index + vob_index = homologous_radial1d_geometry.v_outer_boundary_index + assert np.all( + homologous_radial1d_geometry.v_inner[vib_index:vob_index] + == homologous_radial1d_geometry.v_inner + ) + EPSILON_VELOCITY_SHIFT = 1 * u.km / u.s + # pivoting around the inner boundary of the simulation + + homologous_radial1d_geometry.v_inner_boundary = ( + homologous_radial1d_geometry.v_inner[0] + EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_inner_boundary_index == 0 + homologous_radial1d_geometry.v_inner_boundary = ( + homologous_radial1d_geometry.v_inner[0] - EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_inner_boundary_index == 0 + + # pivoting around the first shell boundary of the simulation + homologous_radial1d_geometry.v_inner_boundary = ( + homologous_radial1d_geometry.v_inner[1] - EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_inner_boundary_index == 0 + homologous_radial1d_geometry.v_inner_boundary = ( + homologous_radial1d_geometry.v_inner[1] + EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_inner_boundary_index == 1 + + # pivoting around the outer boundary of the simulation + homologous_radial1d_geometry.v_outer_boundary = ( + homologous_radial1d_geometry.v_outer[-1] + EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_outer_boundary_index == 12 + homologous_radial1d_geometry.v_outer_boundary = ( + homologous_radial1d_geometry.v_outer[-1] - EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_outer_boundary_index == 12 + + # pivoting around the second to outer boundary of the simulation + homologous_radial1d_geometry.v_outer_boundary = ( + homologous_radial1d_geometry.v_outer[-2] + EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_outer_boundary_index == 12 + homologous_radial1d_geometry.v_outer_boundary = ( + homologous_radial1d_geometry.v_outer[-2] - EPSILON_VELOCITY_SHIFT + ) + assert homologous_radial1d_geometry.v_outer_boundary_index == 11 + + +def test_velocity_boundary(homologous_radial1d_geometry): + # testing the active cell boundaries when setting the boundaries + + homologous_radial1d_geometry.v_inner_boundary = 7999 * u.km / u.s + npt.assert_almost_equal( + homologous_radial1d_geometry.v_inner_active[0].value, 7999 + ) + assert len(homologous_radial1d_geometry.v_inner_active) == len( + homologous_radial1d_geometry.v_inner + ) + + homologous_radial1d_geometry.v_inner_boundary = 8001 * u.km / u.s + npt.assert_almost_equal( + homologous_radial1d_geometry.v_inner_active[0].value, 8001 + ) + assert len(homologous_radial1d_geometry.v_inner_active) == len( + homologous_radial1d_geometry.v_inner + ) + + homologous_radial1d_geometry.v_inner_boundary = 9001 * u.km / u.s + npt.assert_almost_equal( + homologous_radial1d_geometry.v_inner_active[0].value, 9001 + ) + assert len(homologous_radial1d_geometry.v_inner_active) == ( + len(homologous_radial1d_geometry.v_inner) - 1 + ) + homologous_radial1d_geometry.v_inner_boundary = 9000 * u.km / u.s + npt.assert_almost_equal( + homologous_radial1d_geometry.v_inner_active[0].value, 9000 + ) + assert len(homologous_radial1d_geometry.v_inner_active) == ( + len(homologous_radial1d_geometry.v_inner) - 1 + ) diff --git a/tardis/model/matter/__init__.py b/tardis/model/matter/__init__.py new file mode 100644 index 00000000000..b32268f05a6 --- /dev/null +++ b/tardis/model/matter/__init__.py @@ -0,0 +1 @@ +from tardis.model.matter.composition import Composition diff --git a/tardis/model/matter/composition.py b/tardis/model/matter/composition.py new file mode 100644 index 00000000000..67b0a0ec8ce --- /dev/null +++ b/tardis/model/matter/composition.py @@ -0,0 +1,249 @@ +import numpy as np +import pandas as pd +import radioactivedecay as rd +from astropy import units as u +from radioactivedecay.decaydata import DEFAULTDATA as RD_DEFAULT_DATA + +from tardis.model.matter.decay import IsotopicMassFraction + + +def compile_rd_isotope_masses(): + """ + Compiles the masses of isotopes from the default data in RD_DEFAULT_DATA. + + Parameters + ---------- + None + + Returns + ------- + pandas.Series + A series containing the masses of isotopes, indexed by atomic number and mass number. + """ + atomic_numbers = [] + mass_numbers = [] + nuclide_masses = [] + for nuclide_name in RD_DEFAULT_DATA.nuclides: + current_nuclide = rd.Nuclide(nuclide_name) + atomic_numbers.append(current_nuclide.Z) + mass_numbers.append(current_nuclide.A) + nuclide_masses.append(current_nuclide.atomic_mass) + + isotope_mass_index = pd.MultiIndex.from_arrays( + (atomic_numbers, mass_numbers), names=["atomic_number", "mass_number"] + ) + isotope_masses = pd.Series( + index=isotope_mass_index, data=nuclide_masses + ).sort_index() + # there are duplicates that are likely due to excited states + # dropping them for now + + return isotope_masses.drop_duplicates() + + +ISOTOPE_MASSES = compile_rd_isotope_masses() + + +class Composition: + """ + Holds information about model composition + + Parameters + ---------- + density : astropy.units.quantity.Quantity + An array of densities for each shell. + isotopic_mass_fraction : pd.DataFrame + raw_isotope_abundance : pd.DataFrame + atomic_mass : pd.DataFrame + atomic_mass_unit: astropy.units.Unit + + Attributes + ---------- + atomic_mass : pd.DataFrame + Atomic mass of elements calculated for each shell. + elemental_number_density : pd.DataFrame + Number density of each element in each shell. + """ + + def __init__( + self, + density, + nuclide_mass_fraction, + raw_isotope_abundance, + element_masses, + element_masses_unit=u.g, + ): + self.density = density + assert np.all( + nuclide_mass_fraction.values >= 0 + ), "Negative mass fraction detected" + self.nuclide_mass_fraction = nuclide_mass_fraction + + self.nuclide_masses_unit = element_masses_unit + + self.nuclide_masses = element_masses + self.nuclide_masses.index = self.convert_element2nuclide_index( + element_masses.index + ) + + isotope_masses = self.assemble_isotope_masses() + + self.nuclide_masses = pd.concat([self.nuclide_masses, isotope_masses]) + self.raw_isotope_abundance = raw_isotope_abundance + + def assemble_isotope_masses(self): + isotope_mass_df = pd.Series( + index=self.isotopic_mass_fraction.index, data=-1 + ) + for isotope_tuple in self.isotopic_mass_fraction.index: + isotope_symbol = int("{:03d}{:03d}0000".format(*isotope_tuple)) + isotope_mass = rd.Nuclide(isotope_symbol).atomic_mass * u.u.to(u.g) + isotope_mass_df[isotope_tuple] = isotope_mass + + return isotope_mass_df + + @staticmethod + def convert_element2nuclide_index(element_index): + new_nuclide_index = pd.MultiIndex.from_product([element_index, [-1]]) + new_nuclide_index.names = ["atomic_number", "mass_number"] + return new_nuclide_index + + @property + def isotopic_mass_fraction(self): + filtered_nuclide_mass_fraction = self.nuclide_mass_fraction[ + self.nuclide_mass_fraction.index.get_level_values(1) != -1 + ] + return IsotopicMassFraction(filtered_nuclide_mass_fraction) + + @property + def elemental_mass_fraction(self): + return self.nuclide_mass_fraction.groupby(level=0).sum() + + @property + def element_masses(self): + """Atomic mass of elements in each shell""" + element_masses = self.nuclide_masses[ + self.nuclide_masses.index.get_level_values(1) == -1 + ] + element_masses.index = element_masses.index.droplevel(1) + return element_masses + + @property + def effective_element_masses(self): + # This is functionality that we will likely want to remove + effective_element_masses = self.nuclide_mass_fraction[ + self.nuclide_mass_fraction.index.get_level_values(1) == -1 + ].copy() + effective_element_masses.index = ( + effective_element_masses.index.droplevel(1) + ) + for col in effective_element_masses.columns: + effective_element_masses[col] = self.element_masses.loc[ + effective_element_masses.index + ] + + current_isotope_masses = ISOTOPE_MASSES.loc[ + self.isotopic_mass_fraction.index + ] + contributing_isotope_masses = ( + self.isotopic_mass_fraction.multiply(current_isotope_masses, axis=0) + .groupby(level=0) + .sum() + ) + effective_isotopes_masses = ( + contributing_isotope_masses + / self.isotopic_mass_fraction.groupby(level=0).sum() + ) * u.u.to(u.g) + + effective_element_masses = pd.concat( + [effective_element_masses, effective_isotopes_masses] + ) + return effective_element_masses + + @property + def elemental_number_density(self): + """Elemental Number Density computed using the formula: (elemental_mass_fraction * density) / atomic mass""" + return ( + self.elemental_mass_fraction + * self.density.to(u.g / u.cm**3).value + ).divide( + self.effective_element_masses.reindex( + self.elemental_mass_fraction.index + ), + axis=0, + ) + + @property + def isotopic_number_density(self): + """Isotopic Number Density computed using the formula: (isotopic_mass_fraction * density) / atomic mass""" + return ( + self.isotopic_mass_fraction * self.density.to(u.g / u.cm**3).value + ).divide( + ISOTOPE_MASSES.loc[self.isotopic_mass_fraction.index] * u.u.to(u.g), + axis=0, + ) + + def calculate_mass_fraction_at_time(self, time_explosion): + """ + Calculate the mass fraction at a given time using the radioactive decay from + the IsotopicMassFraction. + + Parameters + ---------- + time_explosion : astropy.units.quantity.Quantity + The time of the explosion. + + Returns + ------- + None + + Examples + -------- + >>> composition.calculate_mass_fraction_at_time(10 * u.s) + """ + if self.isotopic_mass_fraction.empty: + return self.elemental_mass_fraction + else: + self.isotopic_mass_fraction.decay(time_explosion) + + def calculate_elemental_cell_masses(self, volume): + """ + Calculate the elemental cell masses. + + Parameters + ---------- + volume : astropy.units.quantity.Quantity + The volume of the cell. + + Returns + ------- + numpy.ndarray + An array of elemental cell masses. + + Examples + -------- + >>> composition.calculate_cell_masses(10 * u.cm**3) + """ + return ( + self.elemental_mass_fraction * (self.density * volume).to(u.g).value + ) + + def calculate_cell_masses(self, volume): + """ + Calculate the cell masses. + + Parameters + ---------- + volume : astropy.units.quantity.Quantity + The volume of the cell. + + Returns + ------- + astropy.units.quantity.Quantity + An array of cell masses. + + Examples + -------- + >>> composition.calculate_cell_masses(10 * u.cm**3) + """ + return (self.density * volume).to(u.g) diff --git a/tardis/io/decay.py b/tardis/model/matter/decay.py similarity index 52% rename from tardis/io/decay.py rename to tardis/model/matter/decay.py index cd71458e138..5d5e00279dc 100644 --- a/tardis/io/decay.py +++ b/tardis/model/matter/decay.py @@ -1,10 +1,14 @@ +import logging + import pandas as pd -from pyne import nucname, material from astropy import units as u +from radioactivedecay import Inventory, Nuclide +from radioactivedecay.utils import Z_to_elem +logger = logging.getLogger(__name__) -class IsotopeAbundances(pd.DataFrame): +class IsotopicMassFraction(pd.DataFrame): _metadata = ["time_0"] def __init__(self, *args, **kwargs): @@ -13,26 +17,26 @@ def __init__(self, *args, **kwargs): kwargs.pop("time_0") else: time_0 = 0 * u.d - super(IsotopeAbundances, self).__init__(*args, **kwargs) + super(IsotopicMassFraction, self).__init__(*args, **kwargs) self.time_0 = time_0 @property def _constructor(self): - return IsotopeAbundances + return IsotopicMassFraction - def _update_material(self): + def _update_inventory(self): self.comp_dicts = [dict() for i in range(len(self.columns))] - for (atomic_number, mass_number), abundances in self.iterrows(): - nuclear_symbol = f"{nucname.name(atomic_number)}{mass_number}" + for (atomic_number, mass_number), mass_fractions in self.iterrows(): + nuclear_symbol = f"{Z_to_elem(atomic_number)}{mass_number}" for i in range(len(self.columns)): - self.comp_dicts[i][nuclear_symbol] = abundances[i] + self.comp_dicts[i][nuclear_symbol] = mass_fractions[i] @classmethod - def from_materials(cls, materials): + def from_inventories(cls, inventories): multi_index_tuples = set([]) - for material in materials: + for inventory in inventories: multi_index_tuples.update( - [cls.id_to_tuple(key) for key in material.keys()] + [cls.id_to_tuple(key) for key in inventory.contents.keys()] ) index = pd.MultiIndex.from_tuples( @@ -40,36 +44,41 @@ def from_materials(cls, materials): ) abundances = pd.DataFrame( - data=0.0, index=index, columns=range(len(materials)) + data=0.0, index=index, columns=range(len(inventories)) ) - for i, material in enumerate(materials): - for key, value in material.items(): - abundances.loc[cls.id_to_tuple(key), i] = value + for i, inventory in enumerate(inventories): + for nuclide, abundance in inventory.masses("g").items(): + abundances.loc[cls.id_to_tuple(nuclide), i] = abundance return cls(abundances) @staticmethod def id_to_tuple(atomic_id): - return nucname.znum(atomic_id), nucname.anum(atomic_id) + nuclide = Nuclide(atomic_id) + return nuclide.Z, nuclide.A - def to_materials(self): + def to_inventories(self, shell_masses=None): """ - Convert DataFrame to a list of materials interpreting the MultiIndex as + Convert DataFrame to a list of inventories interpreting the MultiIndex as atomic_number and mass_number Returns ------- list - list of pyne Materials + list of radioactivedecay Inventories """ - comp_dicts = [dict() for i in range(len(self.columns))] for (atomic_number, mass_number), abundances in self.iterrows(): - nuclear_symbol = f"{nucname.name(atomic_number):s}{mass_number:d}" + nuclear_symbol = f"{Z_to_elem(atomic_number)}{mass_number}" for i in range(len(self.columns)): - comp_dicts[i][nuclear_symbol] = abundances[i] - return [material.Material(comp_dict) for comp_dict in comp_dicts] + if shell_masses is None: + comp_dicts[i][nuclear_symbol] = abundances[i] + else: + comp_dicts[i][nuclear_symbol] = ( + abundances[i] * shell_masses[i].to(u.g).value + ) + return [Inventory(comp_dict, "g") for comp_dict in comp_dicts] def decay(self, t): """ @@ -85,16 +94,22 @@ def decay(self, t): pandas.DataFrame Decayed abundances """ - - materials = self.to_materials() + inventories = self.to_inventories() t_second = ( u.Quantity(t, u.day).to(u.s).value - self.time_0.to(u.s).value ) - decayed_materials = [item.decay(t_second) for item in materials] - for i in range(len(materials)): - materials[i].update(decayed_materials[i]) - df = IsotopeAbundances.from_materials(materials) + logger.info(f"Decaying abundances for {t_second} seconds") + if t_second < 0: + logger.warning( + f"Decay time {t_second} is negative. This could indicate a miss-specified input model." + f" A negative decay time can potentially lead to negative abundances." + ) + decayed_inventories = [item.decay(t_second) for item in inventories] + df = IsotopicMassFraction.from_inventories(decayed_inventories) df.sort_index(inplace=True) + assert ( + df.ge(0.0).all().all() + ), "Negative abundances detected. Please make sure your input abundances are correct." return df def as_atoms(self): @@ -106,7 +121,6 @@ def as_atoms(self): pandas.DataFrame Merged isotope abundances """ - return self.groupby("atomic_number").sum() def merge(self, other, normalize=True): diff --git a/tardis/model/parse_input.py b/tardis/model/parse_input.py new file mode 100644 index 00000000000..d1b5ba3766f --- /dev/null +++ b/tardis/model/parse_input.py @@ -0,0 +1,722 @@ +import logging +import os + +import numpy as np +import pandas as pd +from astropy import units as u + +from tardis import constants as const +from tardis.io.model.parse_density_configuration import ( + calculate_density_after_time, + parse_config_v1_density, + parse_csvy_density, +) +from tardis.io.model.readers.base import read_abundances_file, read_density_file +from tardis.io.model.readers.csvy import parse_csv_abundances +from tardis.io.model.readers.generic_readers import read_uniform_abundances +from tardis.model.geometry.radial1d import HomologousRadial1DGeometry +from tardis.model.matter.composition import Composition +from tardis.model.matter.decay import IsotopicMassFraction +from tardis.model.radiation_field_state import ( + DiluteBlackBodyRadiationFieldState, +) +from tardis.transport.montecarlo.packet_source import ( + BlackBodySimpleSource, + BlackBodySimpleSourceRelativistic, +) +from tardis.util.base import quantity_linspace + +logger = logging.getLogger(__name__) + + +def parse_structure_config(config, time_explosion, enable_homology=True): + """ + Parse the structure configuration data. + + Parameters + ---------- + config : object + The configuration data. + time_explosion : float + The time of the explosion. + enable_homology : bool, optional + Whether to enable homology (default is True). + + Returns + ------- + electron_densities : object + The parsed electron densities. + temperature : object + The parsed temperature. + geometry : object + The parsed geometry. + density : object + The parsed density. + + Raises + ------ + NotImplementedError + If the structure configuration type is not supported. + + Notes + ----- + This function parses the structure configuration data and returns the parsed electron + densities, temperature, geometry, and density. The structure configuration can be of + type 'specific' or 'file'. If it is of type 'specific', the velocity and density are + parsed from the configuration. If it is of type 'file', the velocity and density are + read from a file. The parsed data is used to create a homologous radial 1D geometry object. + """ + electron_densities = None + temperature = None + structure_config = config.model.structure + if structure_config.type == "specific": + velocity = quantity_linspace( + structure_config.velocity.start, + structure_config.velocity.stop, + structure_config.velocity.num + 1, + ).cgs + density = parse_config_v1_density(config) + + elif structure_config.type == "file": + if os.path.isabs(structure_config.filename): + structure_config_fname = structure_config.filename + else: + structure_config_fname = os.path.join( + config.config_dirname, structure_config.filename + ) + + ( + time_0, + velocity, + density_0, + electron_densities, + temperature, + ) = read_density_file(structure_config_fname, structure_config.filetype) + density_0 = density_0.insert(0, 0) + + density = calculate_density_after_time( + density_0, time_0, time_explosion + ) + + else: + raise NotImplementedError + + # Note: This is the number of shells *without* taking in mind the + # v boundaries. + if len(density) == len(velocity): + logger.warning( + "Number of density points larger than number of shells. Assuming inner point irrelevant" + ) + density = density[1:] + geometry = HomologousRadial1DGeometry( + velocity[:-1], # v_inner + velocity[1:], # v_outer + v_inner_boundary=structure_config.get("v_inner_boundary", None), + v_outer_boundary=structure_config.get("v_outer_boundary", None), + time_explosion=time_explosion, + ) + return electron_densities, temperature, geometry, density + + +def parse_csvy_geometry( + config, csvy_model_config, csvy_model_data, time_explosion +): + """ + Parse the geometry data from a CSVY model. + + Parameters + ---------- + config : object + The configuration data. + csvy_model_config : object + The configuration data of the CSVY model. + csvy_model_data : object + The data of the CSVY model. + time_explosion : float + The time of the explosion. + + Returns + ------- + geometry : object + The parsed geometry. + + Raises + ------ + None. + + Notes + ----- + This function parses the geometry data from a CSVY model. It extracts the velocity + information from the CSVY model configuration or data. The parsed velocity data is + used to create a homologous radial 1D geometry object, which is returned. + """ + if hasattr(config, "model"): + if hasattr(config.model, "v_inner_boundary"): + v_boundary_inner = config.model.v_inner_boundary + else: + v_boundary_inner = None + + if hasattr(config.model, "v_outer_boundary"): + v_boundary_outer = config.model.v_outer_boundary + else: + v_boundary_outer = None + else: + v_boundary_inner = None + v_boundary_outer = None + + if hasattr(csvy_model_config, "velocity"): + velocity = quantity_linspace( + csvy_model_config.velocity.start, + csvy_model_config.velocity.stop, + csvy_model_config.velocity.num + 1, + ).cgs + else: + velocity_field_index = [ + field["name"] for field in csvy_model_config.datatype.fields + ].index("velocity") + velocity_unit = u.Unit( + csvy_model_config.datatype.fields[velocity_field_index]["unit"] + ) + velocity = csvy_model_data["velocity"].values * velocity_unit + velocity = velocity.to("cm/s") + + geometry = HomologousRadial1DGeometry( + velocity[:-1], # v_inner + velocity[1:], # v_outer + v_inner_boundary=v_boundary_inner, + v_outer_boundary=v_boundary_outer, + time_explosion=time_explosion, + ) + return geometry + + +def parse_abundance_config(config, geometry, time_explosion): + """ + Parse the abundance configuration data. + + Parameters + ---------- + config : object + The configuration data. + geometry : object + The geometry of the model. + time_explosion : float + The time of the explosion. + + Returns + ------- + nuclide_mass_fraction : object + The parsed nuclide mass fraction. + + raw_isotope_abundance : object + The parsed raw isotope abundance. This is the isotope abundance data before decay. + + Raises + ------ + None. + + Notes + ----- + This function parses the abundance configuration data and returns the parsed nuclide + mass fraction. The abundance configuration can be of type 'uniform' or 'file'. If it + is of type 'uniform', the abundance and isotope abundance are read using the + 'read_uniform_abundances' function. If it is of type 'file', the abundance and + isotope abundance are read from a file using the 'read_abundances_file' function. + The parsed data is then processed to replace NaN values with 0.0, remove rows with + zero sum, and normalize the data if necessary. The resulting nuclide mass fraction + is returned. + """ + abundances_section = config.model.abundances + isotope_abundance = pd.DataFrame() + + if abundances_section.type == "uniform": + abundance, isotope_abundance = read_uniform_abundances( + abundances_section, geometry.no_of_shells + ) + + elif abundances_section.type == "file": + if os.path.isabs(abundances_section.filename): + abundances_fname = abundances_section.filename + else: + abundances_fname = os.path.join( + config.config_dirname, abundances_section.filename + ) + + index, abundance, isotope_abundance = read_abundances_file( + abundances_fname, abundances_section.filetype + ) + + abundance = abundance.replace(np.nan, 0.0) + abundance = abundance[abundance.sum(axis=1) > 0] + + norm_factor = abundance.sum(axis=0) + isotope_abundance.sum(axis=0) + + if np.any(np.abs(norm_factor - 1) > 1e-12): + logger.warning( + "Abundances have not been normalized to 1. - normalizing" + ) + abundance /= norm_factor + isotope_abundance /= norm_factor + # The next line is if the abundances are given via dict + # and not gone through the schema validator + raw_isotope_abundance = isotope_abundance + model_isotope_time_0 = config.model.abundances.get( + "model_isotope_time_0", 0.0 * u.day + ) + isotope_abundance = IsotopicMassFraction( + isotope_abundance, time_0=model_isotope_time_0 + ).decay(time_explosion) + + nuclide_mass_fraction = convert_to_nuclide_mass_fraction( + isotope_abundance, abundance + ) + return nuclide_mass_fraction, raw_isotope_abundance + + +def convert_to_nuclide_mass_fraction(isotopic_mass_fraction, mass_fraction): + """ + Convert the abundance and isotope abundance data to nuclide mass fraction. + + Parameters + ---------- + isotope_abundance : pandas.DataFrame + The isotope abundance data. + abundance : pandas.DataFrame + The abundance data. + + Returns + ------- + nuclide_mass_fraction : pandas.DataFrame + The converted nuclide mass fraction. + + Raises + ------ + None. + + Notes + ----- + This function converts the abundance and isotope abundance data to nuclide mass fraction. + If the abundance data is not None, it is converted to nuclide mass fraction by mapping + the abundance index to nuclide indices using the 'convert_element2nuclide_index' function. + The resulting abundance data is then concatenated with the isotope abundance data to + obtain the final nuclide mass fraction. + """ + nuclide_mass_fraction = pd.DataFrame() + if mass_fraction is not None: + mass_fraction.index = Composition.convert_element2nuclide_index( + mass_fraction.index + ) + nuclide_mass_fraction = mass_fraction + else: + nuclide_mass_fraction = pd.DataFrame() + + if isotopic_mass_fraction is not None: + nuclide_mass_fraction = pd.concat( + [nuclide_mass_fraction, isotopic_mass_fraction] + ) + return nuclide_mass_fraction + + +def parse_csvy_composition( + atom_data, csvy_model_config, csvy_model_data, time_explosion, geometry +): + """ + Parse the composition data from a CSVY model. + + Parameters + ---------- + atom_data : object + The atom data used for parsing. + csvy_model_config : object + The configuration data of the CSVY model. + csvy_model_data : object + The data of the CSVY model. + time_explosion : float + The time of the explosion. + geometry : object + The geometry of the model. + + Returns + ------- + density : object + The parsed density data. + abundance : object + The parsed abundance data. + isotope_abundance : object + The parsed isotope abundance data. + elemental_mass : object + The elemental mass data. + + Raises + ------ + None. + + Notes + ----- + This function parses the composition data from a CSVY model. It calls the 'parse_density_csvy' + function to parse the density data, and the 'parse_abundance_csvy' function to parse the abundance + and isotope abundance data. The parsed data is returned as density, abundance, isotope_abundance, + and elemental_mass. + """ + density = parse_density_csvy( + csvy_model_config, csvy_model_data, time_explosion + ) + + nuclide_mass_fraction, raw_isotope_mass_fraction = parse_abundance_csvy( + csvy_model_config, csvy_model_data, geometry, time_explosion + ) + return Composition( + density, + nuclide_mass_fraction, + raw_isotope_mass_fraction, + atom_data.atom_data.mass.copy(), + ) + + +def parse_abundance_csvy( + csvy_model_config, csvy_model_data, geometry, time_explosion +): + """ + Parse the abundance data from a CSVY model. + + Parameters + ---------- + csvy_model_config : object + The configuration data of the CSVY model. + csvy_model_data : object + The data of the CSVY model. + geometry : object + The geometry of the model. + + Returns + ------- + abundance : pd.DataFrame + The parsed abundance data. + isotope_abundance : pandas.DataFrame + The parsed isotope abundance data. + + Raises + ------ + None. + + Notes + ----- + This function parses the abundance data from a CSVY model. If the CSVY model + configuration contains an 'abundance' attribute, it uses the 'read_uniform_abundances' + function to parse the abundance and isotope abundance data. Otherwise, it uses the + 'parse_csv_abundances' function to parse the data. The parsed data is then processed + to replace NaN values with 0.0, remove rows with zero sum, and normalize the data + if necessary. The resulting abundance and isotope abundance arrays are returned. + """ + if hasattr(csvy_model_config, "abundance"): + abundances_section = csvy_model_config.abundance + mass_fraction, isotope_mass_fraction = read_uniform_abundances( + abundances_section, geometry.no_of_shells + ) + else: + _, mass_fraction, isotope_mass_fraction = parse_csv_abundances( + csvy_model_data + ) + mass_fraction = mass_fraction.loc[:, 1:] + mass_fraction.columns = np.arange(mass_fraction.shape[1]) + isotope_mass_fraction = isotope_mass_fraction.loc[:, 1:] + isotope_mass_fraction.columns = np.arange( + isotope_mass_fraction.shape[1] + ) + + mass_fraction = mass_fraction.replace(np.nan, 0.0) + mass_fraction = mass_fraction[mass_fraction.sum(axis=1) > 0] + isotope_mass_fraction = isotope_mass_fraction.replace(np.nan, 0.0) + isotope_mass_fraction = isotope_mass_fraction[ + isotope_mass_fraction.sum(axis=1) > 0 + ] + norm_factor = mass_fraction.sum(axis=0) + isotope_mass_fraction.sum(axis=0) + + if np.any(np.abs(norm_factor - 1) > 1e-12): + logger.warning( + "Abundances have not been normalized to 1. - normalizing" + ) + mass_fraction /= norm_factor + isotope_mass_fraction /= norm_factor + + raw_isotope_mass_fraction = isotope_mass_fraction + isotope_mass_fraction = IsotopicMassFraction( + isotope_mass_fraction, time_0=csvy_model_config.model_isotope_time_0 + ).decay(time_explosion) + return ( + convert_to_nuclide_mass_fraction(isotope_mass_fraction, mass_fraction), + raw_isotope_mass_fraction, + ) + + +def parse_density_csvy(csvy_model_config, csvy_model_data, time_explosion): + """ + Parse the density data from a CSVY model. + + Parameters + ---------- + csvy_model_config : object + The configuration data of the CSVY model. + csvy_model_data : object + The data of the CSVY model. + time_explosion : float + The time of the explosion. + + Returns + ------- + density : object + The parsed density data. + + Raises + ------ + None. + + Notes + ----- + This function parses the density data from a CSVY model. If the CSVY model configuration + contains a 'density' attribute, it uses the 'parse_csvy_density' function to parse the + density data. Otherwise, it calculates the density data using the 'calculate_density_after_time' + function. The parsed density data is returned. + """ + if hasattr(csvy_model_config, "density"): + density = parse_csvy_density(csvy_model_config, time_explosion) + else: + time_0 = csvy_model_config.model_density_time_0 + density_field_index = [ + field["name"] for field in csvy_model_config.datatype.fields + ].index("density") + density_unit = u.Unit( + csvy_model_config.datatype.fields[density_field_index]["unit"] + ) + density_0 = csvy_model_data["density"].values * density_unit + # Removing as thee new architecture removes the 0th shell already + # density_0 = density_0.to("g/cm^3")[1:] + # density_0 = density_0.insert(0, 0) + density = calculate_density_after_time( + density_0, time_0, time_explosion + ) + + return density + + +def parse_radiation_field_state( + config, t_radiative, geometry, dilution_factor=None, packet_source=None +): + """ + Parses the radiation field state based on the provided configuration, radiative temperature, geometry, dilution factor, and packet source. + + Parameters + ---------- + config : Config + The configuration object. + t_radiative : {None, Quantity}, optional + The radiative temperature. If None, it is calculated based on the initial_t_rad value in the plasma configuration. + geometry : Geometry + The geometry object. + dilution_factor : {None, ndarray}, optional + The dilution factor. If None, it is calculated based on the geometry. + packet_source : {None, PacketSource}, optional + The packet source object. + + Returns + ------- + DiluteThermalRadiationFieldState + The parsed radiation field state. + + Raises + ------ + AssertionError + If the length of t_radiative or dilution_factor is not compatible with the geometry. + """ + if t_radiative is None: + if config.plasma.initial_t_rad > 0 * u.K: + t_radiative = ( + np.ones(geometry.no_of_shells) * config.plasma.initial_t_rad + ) + else: + t_radiative = calculate_t_radiative_from_t_inner( + geometry, packet_source + ) + + assert len(t_radiative) == geometry.no_of_shells + + if dilution_factor is None: + dilution_factor = calculate_geometric_dilution_factor(geometry) + + assert len(dilution_factor) == geometry.no_of_shells + + return DiluteBlackBodyRadiationFieldState( + t_radiative, dilution_factor, geometry + ) + + +def initialize_packet_source( + config, geometry, packet_source, legacy_mode_enabled +): + """ + Initialize the packet source based on config and geometry + + Parameters + ---------- + config : Config + The configuration object containing the supernova and plasma settings. + geometry : Geometry + The geometry object containing the inner radius information. + packet_source : BasePacketSource + The packet source object based on the configuration and geometry. + + Returns + ------- + packet_source : BasePacketSource + The packet source object based on the configuration and geometry. + + Raises + ------ + ValueError + If both t_inner and luminosity_requested are None. + """ + if config.montecarlo.enable_full_relativity: + packet_source = BlackBodySimpleSourceRelativistic( + base_seed=config.montecarlo.seed, + time_explosion=config.supernova.time_explosion, + legacy_mode_enabled=legacy_mode_enabled, + ) + else: + packet_source = BlackBodySimpleSource( + base_seed=config.montecarlo.seed, + legacy_mode_enabled=legacy_mode_enabled, + ) + + luminosity_requested = config.supernova.luminosity_requested + if config.plasma.initial_t_inner > 0.0 * u.K: + packet_source.radius = geometry.r_inner_active[0] + packet_source.temperature = config.plasma.initial_t_inner + + elif (config.plasma.initial_t_inner < 0.0 * u.K) and ( + luminosity_requested is not None + ): + packet_source.radius = geometry.r_inner_active[0] + packet_source.set_temperature_from_luminosity(luminosity_requested) + else: + raise ValueError( + "Both t_inner and luminosity_requested cannot be None." + ) + + return packet_source + + +def parse_packet_source(config, geometry, legacy_mode_enabled): + """ + Parse the packet source based on the given configuration and geometry. + + Parameters + ---------- + config : Config + The configuration object containing the supernova and plasma settings. + geometry : Geometry + The geometry object containing the inner radius information. + + Returns + ------- + packet_source : BlackBodySimpleSource + The packet source object based on the configuration and geometry. + """ + if config.montecarlo.enable_full_relativity: + packet_source = BlackBodySimpleSourceRelativistic( + base_seed=config.montecarlo.seed, + time_explosion=config.supernova.time_explosion, + legacy_mode_enabled=legacy_mode_enabled, + ) + else: + packet_source = BlackBodySimpleSource( + base_seed=config.montecarlo.seed, + legacy_mode_enabled=legacy_mode_enabled, + ) + + return initialize_packet_source( + config, geometry, packet_source, legacy_mode_enabled + ) + + +def parse_csvy_radiation_field_state( + config, csvy_model_config, csvy_model_data, geometry, packet_source +): + t_radiative = None + dilution_factor = None + + if hasattr(csvy_model_data, "columns") and ( + "t_rad" in csvy_model_data.columns + ): + t_rad_field_index = [ + field["name"] for field in csvy_model_config.datatype.fields + ].index("t_rad") + t_rad_unit = u.Unit( + csvy_model_config.datatype.fields[t_rad_field_index]["unit"] + ) + t_radiative = csvy_model_data["t_rad"].iloc[1:].values * t_rad_unit + + elif config.plasma.initial_t_rad > 0 * u.K: + t_radiative = ( + np.ones(geometry.no_of_shells) * config.plasma.initial_t_rad + ) + else: + t_radiative = calculate_t_radiative_from_t_inner( + geometry, packet_source + ) + + if np.any(t_radiative < 1000 * u.K): + logging.critical( + "Radiative temperature is too low in some of the shells, temperatures below 1000K " + f"(e.g., T_rad = {t_radiative[np.argmin(t_radiative)]} in shell {np.argmin(t_radiative)} in your model) " + "are not accurately handled by TARDIS.", + ) + + if hasattr(csvy_model_data, "columns") and ( + "dilution_factor" in csvy_model_data.columns + ): + dilution_factor = csvy_model_data["dilution_factor"].iloc[1:].values + else: + dilution_factor = calculate_geometric_dilution_factor(geometry) + + return DiluteBlackBodyRadiationFieldState( + t_radiative, dilution_factor, geometry + ) + + +def calculate_t_radiative_from_t_inner(geometry, packet_source): + """ + Calculates the radiative temperature based on the inner temperature and the geometry of the system. + + Parameters + ---------- + geometry : Geometry + The geometry object. + packet_source : PacketSource + The packet source object. + + Returns + ------- + Quantity + The calculated radiative temperature. + """ + lambda_wien_inner = const.b_wien / packet_source.temperature + t_radiative = const.b_wien / ( + lambda_wien_inner + * (1 + (geometry.v_middle - geometry.v_inner_boundary) / const.c) + ) + return t_radiative + + +def calculate_geometric_dilution_factor(geometry): + return 0.5 * ( + 1 + - np.sqrt( + 1 + - ( + geometry.r_inner[geometry.v_inner_boundary_index] ** 2 + / geometry.r_middle**2 + ) + .to(1) + .value + ) + ) diff --git a/tardis/model/radiation_field_state.py b/tardis/model/radiation_field_state.py new file mode 100644 index 00000000000..dff0bd65bbc --- /dev/null +++ b/tardis/model/radiation_field_state.py @@ -0,0 +1,70 @@ +import numpy as np +from astropy import units as u + +from tardis.util.base import intensity_black_body + +from typing import Union + + +class DiluteBlackBodyRadiationFieldState: + """ + Represents the state of a dilute thermal radiation field. + + + Parameters + ---------- + t_radiative : u.Quantity + Radiative temperature in each shell + dilution_factor : numpy.ndarray + Dilution Factors in each shell + geometry: tardis.model.Radial1DModel + The geometry of the model that uses to constrains the active shells + """ + + def __init__( + self, + t_radiative: u.Quantity, + dilution_factor: np.ndarray, + geometry=None, + ): + # ensuring that the radiation_field has both + # dilution_factor and t_radiative equal length + assert len(t_radiative) == len(dilution_factor) + if ( + geometry is not None + ): # check the active shells only (this is used when setting up the radiation_field_state) + assert np.all( + t_radiative[ + geometry.v_inner_boundary_index : geometry.v_outer_boundary_index + ] + > 0 * u.K + ) + assert np.all( + dilution_factor[ + geometry.v_inner_boundary_index : geometry.v_outer_boundary_index + ] + > 0 + ) + else: + assert np.all(t_radiative > 0 * u.K) + assert np.all(dilution_factor > 0) + self.t_radiative = t_radiative + self.dilution_factor = dilution_factor + + def calculate_mean_intensity(self, nu: Union[u.Quantity, np.ndarray]): + """ + Calculate the intensity of the radiation field at a given frequency. + + Parameters + ---------- + nu : u.Quantity + Frequency at which the intensity is to be calculated + + Returns + ------- + intensity : u.Quantity + Intensity of the radiation field at the given frequency + """ + return self.dilution_factor * intensity_black_body( + nu[np.newaxis].T, self.t_radiative + ) diff --git a/tardis/model/tests/test_base.py b/tardis/model/tests/test_base.py index 01e4c825b53..3aedf574420 100644 --- a/tardis/model/tests/test_base.py +++ b/tardis/model/tests/test_base.py @@ -1,210 +1,258 @@ import os +from pathlib import Path import pytest import pandas as pd from astropy import units as u from numpy.testing import assert_almost_equal, assert_array_almost_equal -from tardis.io.config_reader import Configuration -from tardis.model import Radial1DModel -from tardis.io.decay import IsotopeAbundances - - -def data_path(filename): - return os.path.abspath(os.path.join("tardis/io/tests/data/", filename)) +from tardis.io.configuration.config_reader import Configuration +from tardis.model import SimulationState +from tardis.model.matter.decay import IsotopicMassFraction class TestModelFromPaper1Config: - def setup(self): - filename = "paper1_tardis_configv1.yml" - self.config = Configuration.from_yaml(data_path(filename)) - self.model = Radial1DModel.from_config(self.config) + @pytest.fixture(autouse=True) + def setup(self, example_configuration_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_configuration_dir / "paper1_tardis_configv1.yml" + ) + + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_abundances(self): oxygen_abundance = self.config.model.abundances.O assert_array_almost_equal( - oxygen_abundance, self.model.abundance.loc[8].values + oxygen_abundance, self.simulation_state.abundance.loc[8].values ) def test_velocities(self): velocity = self.config.model.structure.velocity assert_almost_equal( - velocity.start.cgs.value, self.model.v_inner[0].cgs.value + velocity.start.cgs.value, self.simulation_state.v_inner[0].cgs.value ) assert_almost_equal( - velocity.stop.cgs.value, self.model.v_outer[-1].cgs.value + velocity.stop.cgs.value, self.simulation_state.v_outer[-1].cgs.value ) - assert len(self.model.v_outer) == velocity.num + assert len(self.simulation_state.v_outer) == velocity.num def test_densities(self): assert_almost_equal( - self.model.density[0].cgs.value, + self.simulation_state.density[0].cgs.value, (7.542803599143591e-14 * u.Unit("g/cm^3")).value, ) assert_almost_equal( - self.model.density[-1].cgs.value, + self.simulation_state.density[-1].cgs.value, (1.432259798833509e-15 * u.Unit("g/cm^3")).value, ) def test_time_explosion(self): - assert_almost_equal(self.model.time_explosion.to(u.day).value, 13.0) + assert_almost_equal( + self.simulation_state.time_explosion.to(u.day).value, 13.0 + ) class TestModelFromASCIIDensity: - def setup(self): - filename = "tardis_configv1_ascii_density.yml" - self.config = Configuration.from_yaml(data_path(filename)) - self.model = Radial1DModel.from_config(self.config) + @pytest.fixture(autouse=True) + def setup(self, example_model_file_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_ascii_density.yml" + ) + self.simulation_state = SimulationState.from_config( + self.config, atomic_dataset + ) def test_velocities(self): - assert self.model.v_inner.unit == u.Unit("cm/s") - assert_almost_equal(self.model.v_inner[0].value, 1e4 * 1e5) + assert_almost_equal( + self.simulation_state.v_inner.to(u.cm / u.s).value[0], 1e4 * 1e5 + ) def test_abundances(self): oxygen_abundance = self.config.model.abundances.O assert_array_almost_equal( - oxygen_abundance, self.model.abundance.loc[8].values + oxygen_abundance, self.simulation_state.abundance.loc[8].values ) class TestModelFromArtisDensity: - def setup(self): - filename = "tardis_configv1_artis_density.yml" - self.config = Configuration.from_yaml(data_path(filename)) - self.model = Radial1DModel.from_config(self.config) + @pytest.fixture(autouse=True) + def setup(self, example_model_file_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_artis_density.yml" + ) + + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_velocities(self): - assert self.model.v_inner.unit == u.Unit("cm/s") - assert_almost_equal(self.model.v_inner[0].value, 1.259375e03 * 1e5) + assert_almost_equal( + self.simulation_state.v_inner[0].to(u.cm / u.s).value, + 1.259375e03 * 1e5, + ) def test_abundances(self): oxygen_abundance = self.config.model.abundances.O assert_array_almost_equal( - oxygen_abundance, self.model.abundance.loc[8].values + oxygen_abundance, self.simulation_state.abundance.loc[8].values ) class TestModelFromArtisDensityAbundances: - def setup(self): - filename = "tardis_configv1_artis_density.yml" - self.config = Configuration.from_yaml(data_path(filename)) + @pytest.fixture(autouse=True) + def setup(self, example_model_file_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_artis_density.yml" + ) self.config.model.abundances.type = "file" self.config.model.abundances.filename = "artis_abundances.dat" self.config.model.abundances.filetype = "artis" - self.model = Radial1DModel.from_config(self.config) + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_velocities(self): - assert self.model.v_inner.unit == u.Unit("cm/s") - assert_almost_equal(self.model.v_inner[0].value, 1.259375e03 * 1e5) + assert_almost_equal( + self.simulation_state.v_inner[0].to(u.cm / u.s).value, + 1.259375e03 * 1e5, + ) def test_abundances(self): assert_almost_equal( - self.model.abundance.loc[14, 54], 0.21864420000000001 + self.simulation_state.abundance.loc[14, 54], 0.21864420000000001 ) class TestModelFromArtisDensityAbundancesVSlice: - def setup(self): - filename = "tardis_configv1_artis_density_v_slice.yml" - self.config = Configuration.from_yaml(data_path(filename)) + @pytest.fixture(autouse=True) + def setup(self, example_model_file_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_artis_density_v_slice.yml" + ) self.config.model.abundances.type = "file" self.config.model.abundances.filename = "artis_abundances.dat" self.config.model.abundances.filetype = "artis" - self.model = Radial1DModel.from_config(self.config) + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_velocities(self): - assert self.model.v_inner.unit == u.Unit("cm/s") - assert_almost_equal(self.model.v_inner[0].to(u.km / u.s).value, 9000) + assert_almost_equal( + self.simulation_state.v_inner[0].to(u.km / u.s).value, 9000 + ) def test_abundances(self): - assert_almost_equal(self.model.abundance.loc[14, 31], 2.156751e-01) + assert_almost_equal( + self.simulation_state.abundance.loc[14, 31], 2.156751e-01 + ) class TestModelFromUniformDensity: - def setup(self): - filename = "tardis_configv1_uniform_density.yml" - self.config = Configuration.from_yaml(data_path(filename)) - self.model = Radial1DModel.from_config(self.config) + @pytest.fixture(autouse=True) + def setup(self, example_configuration_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_uniform_density.yml" + ) + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_density(self): assert_array_almost_equal( - self.model.density.to(u.Unit("g / cm3")).value, 1.0e-14 + self.simulation_state.density.to(u.Unit("g / cm3")).value, 1.0e-14 ) class TestModelFromInitialTinner: - def setup(self): - filename = "tardis_configv1_uniform_density.yml" - self.config = Configuration.from_yaml(data_path(filename)) + @pytest.fixture(autouse=True) + def setup(self, example_configuration_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_uniform_density.yml" + ) self.config.plasma.initial_t_inner = 2508 * u.K - self.model = Radial1DModel.from_config(self.config) + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_initial_temperature(self): - assert_almost_equal(self.model.t_inner.value, 2508) + assert_almost_equal( + self.simulation_state.packet_source.temperature.value, 2508 + ) class TestModelFromArtisDensityAbundancesAllAscii: - def setup(self): - filename = "tardis_configv1_ascii_density_abund.yml" - self.config = Configuration.from_yaml(data_path(filename)) + @pytest.fixture(autouse=True) + def setup(self, example_model_file_dir, atomic_dataset): + self.config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_ascii_density_abund.yml" + ) self.config.model.structure.filename = "density.dat" self.config.model.abundances.filename = "abund.dat" - self.model = Radial1DModel.from_config(self.config) + self.simulation_state = SimulationState.from_config( + self.config, atom_data=atomic_dataset + ) def test_velocities(self): - assert self.model.v_inner.unit == u.Unit("cm/s") - assert_almost_equal(self.model.v_inner[0].to(u.km / u.s).value, 11000) + # unclear why we are testing this + # assert self.simulation_state.v_inner.unit == u.Unit("cm/s") + assert hasattr(self.simulation_state.v_inner, "unit") + assert_almost_equal( + self.simulation_state.v_inner[0].to(u.km / u.s).value, 11000 + ) def test_abundances(self): - assert_almost_equal(self.model.abundance.loc[14, 0], 0.1) - assert_almost_equal(self.model.abundance.loc[14, 1], 0.2) - assert_almost_equal(self.model.abundance.loc[14, 2], 0.2) - assert_almost_equal(self.model.abundance.loc[14, 3], 0.2) - assert_almost_equal(self.model.abundance.loc[14, 4], 0.2) - assert_almost_equal(self.model.abundance.loc[14, 5], 0.2) - assert_almost_equal(self.model.abundance.loc[14, 6], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 0], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 1], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 2], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 3], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 4], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 5], 0.0) - assert_almost_equal(self.model.abundance.loc[6, 6], 0.5) + assert_almost_equal(self.simulation_state.abundance.loc[14, 0], 0.1) + assert_almost_equal(self.simulation_state.abundance.loc[14, 1], 0.2) + assert_almost_equal(self.simulation_state.abundance.loc[14, 2], 0.2) + assert_almost_equal(self.simulation_state.abundance.loc[14, 3], 0.2) + assert_almost_equal(self.simulation_state.abundance.loc[14, 4], 0.2) + assert_almost_equal(self.simulation_state.abundance.loc[14, 5], 0.2) + assert_almost_equal(self.simulation_state.abundance.loc[14, 6], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 0], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 1], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 2], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 3], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 4], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 5], 0.0) + assert_almost_equal(self.simulation_state.abundance.loc[6, 6], 0.5) def test_densities(self): assert_almost_equal( - self.model.density[0].to(u.Unit("g/cm3")).value, - 9.7656229e-11 / 13.0 ** 3, + self.simulation_state.density[0].to(u.Unit("g/cm3")).value, + 9.7656229e-11 / 13.0**3, ) assert_almost_equal( - self.model.density[1].to(u.Unit("g/cm3")).value, - 4.8170911e-11 / 13.0 ** 3, + self.simulation_state.density[1].to(u.Unit("g/cm3")).value, + 4.8170911e-11 / 13.0**3, ) assert_almost_equal( - self.model.density[2].to(u.Unit("g/cm3")).value, - 2.5600000e-11 / 13.0 ** 3, + self.simulation_state.density[2].to(u.Unit("g/cm3")).value, + 2.5600000e-11 / 13.0**3, ) assert_almost_equal( - self.model.density[3].to(u.Unit("g/cm3")).value, - 1.4450533e-11 / 13.0 ** 3, + self.simulation_state.density[3].to(u.Unit("g/cm3")).value, + 1.4450533e-11 / 13.0**3, ) assert_almost_equal( - self.model.density[4].to(u.Unit("g/cm3")).value, - 8.5733893e-11 / 13.0 ** 3, + self.simulation_state.density[4].to(u.Unit("g/cm3")).value, + 8.5733893e-11 / 13.0**3, ) assert_almost_equal( - self.model.density[5].to(u.Unit("g/cm3")).value, - 5.3037103e-11 / 13.0 ** 3, + self.simulation_state.density[5].to(u.Unit("g/cm3")).value, + 5.3037103e-11 / 13.0**3, ) assert_almost_equal( - self.model.density[6].to(u.Unit("g/cm3")).value, - 3.3999447e-11 / 13.0 ** 3, + self.simulation_state.density[6].to(u.Unit("g/cm3")).value, + 3.3999447e-11 / 13.0**3, ) -def test_ascii_reader_power_law(): - filename = "tardis_configv1_density_power_law_test.yml" - config = Configuration.from_yaml(data_path(filename)) - model = Radial1DModel.from_config(config) +def test_ascii_reader_power_law(example_configuration_dir, atomic_dataset): + config = Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_density_power_law_test.yml" + ) + simulation_state = SimulationState.from_config(config, atomic_dataset) expected_densites = [ 3.29072513e-14, @@ -229,17 +277,21 @@ def test_ascii_reader_power_law(): 1.93928168e-15, ] - assert model.no_of_shells == 20 + assert simulation_state.no_of_shells == 20 for i, mdens in enumerate(expected_densites): assert_almost_equal( - model.density[i].to(u.Unit("g / (cm3)")).value, mdens + simulation_state.density[i].to(u.Unit("g / (cm3)")).value, mdens ) -def test_ascii_reader_exponential_law(): - filename = "tardis_configv1_density_exponential_test.yml" - config = Configuration.from_yaml(data_path(filename)) - model = Radial1DModel.from_config(config) +def test_ascii_reader_exponential_law( + example_configuration_dir, atomic_dataset +): + config = Configuration.from_yaml( + example_configuration_dir + / "tardis_configv1_density_exponential_test.yml" + ) + simulation_state = SimulationState.from_config(config, atomic_dataset) expected_densites = [ 5.18114795e-14, @@ -265,10 +317,10 @@ def test_ascii_reader_exponential_law(): ] expected_unit = "g / (cm3)" - assert model.no_of_shells == 20 + assert simulation_state.no_of_shells == 20 for i, mdens in enumerate(expected_densites): - assert_almost_equal(model.density[i].value, mdens) - assert model.density[i].unit == u.Unit(expected_unit) + assert_almost_equal(simulation_state.density[i].value, mdens) + assert simulation_state.density[i].unit == u.Unit(expected_unit) @pytest.fixture @@ -277,105 +329,131 @@ def simple_isotope_abundance(): [(6, 14), (12, 28)], names=["atomic_number", "mass_number"] ) abundance = [[0.2] * 20] * 2 - return IsotopeAbundances(abundance, index=index) + return IsotopicMassFraction(abundance, index=index) -def test_model_decay(simple_isotope_abundance): - filename = "tardis_configv1_verysimple.yml" - config = Configuration.from_yaml(data_path(filename)) - model = Radial1DModel.from_config(config) - - model.raw_isotope_abundance = simple_isotope_abundance - decayed = simple_isotope_abundance.decay(model.time_explosion).as_atoms() - norm_factor = 1.4 +@pytest.mark.parametrize( + ("index", "expected"), + [ + (0, 1.00977478e45), + (10, 1.98154804e45), + (19, 3.13361319e45), + ], +) +def test_radial_1D_geometry_volume(simulation_verysimple, index, expected): + geometry = simulation_verysimple.simulation_state.geometry + volume = geometry.volume assert_almost_equal( - model.abundance.loc[8][0], - model.raw_abundance.loc[8][0] / norm_factor, - decimal=4, + volume[index].to(u.cm**3).value, expected, decimal=-40 ) + + +@pytest.mark.parametrize( + ("index", "expected"), + [ + ((8, 0), 539428198), + ((8, 1), 409675383), + ((8, 2), 314387928), + ((12, 0), 56066111), + ((12, 1), 42580098), + ((12, 2), 32676283), + ((14, 0), 841032262), + ((14, 1), 638732300), + ((14, 2), 490167906), + ((16, 0), 269136275), + ((16, 1), 204398856), + ((16, 2), 156857199), + ((18, 0), 45482957), + ((18, 1), 34542591), + ((18, 2), 26508241), + ((20, 0), 34001569), + ((20, 1), 25822910), + ((20, 2), 19816693), + ], +) +def test_composition_elemental_number_density( + simulation_verysimple, index, expected +): + comp = simulation_verysimple.simulation_state.composition + assert_almost_equal( - model.abundance.loc[14][0], - (model.raw_abundance.loc[14][0] + decayed.loc[14][0]) / norm_factor, - decimal=4, + comp.elemental_number_density.loc[index], expected, decimal=-2 ) - assert_almost_equal( - model._abundance.loc[12][5], - (model.raw_abundance.loc[12][5] + decayed.loc[12][5]) / norm_factor, - decimal=4, + + +@pytest.mark.parametrize( + ("index", "expected"), + [ + ((8, 0), 1.4471412e31), + ((16, 10), 2.6820129e30), + ((20, 19), 1.3464444e29), + ], +) +def test_simulation_state_mass(simulation_verysimple, index, expected): + simulation_state = simulation_verysimple.simulation_state + volume = simulation_state.geometry.volume + elemental_cell_masses = ( + simulation_state.composition.calculate_elemental_cell_masses(volume) ) - assert_almost_equal( - model.abundance.loc[6][12], - (decayed.loc[6][12]) / norm_factor, - decimal=4, + + assert_almost_equal(elemental_cell_masses.loc[index], expected, decimal=-27) + + +@pytest.fixture +def non_uniform_simulation_state(atomic_dataset, example_model_file_dir): + config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_isotope_iabund.yml" + ) + + return SimulationState.from_config(config, atom_data=atomic_dataset) + + +@pytest.mark.parametrize( + ("index", "expected"), + [ + ((1, 0), 1.67378172e-24), + ((28, 0), 9.51707707e-23), + ((28, 1), 9.54725917e-23), + ], +) +def test_radial_1d_model_atomic_mass( + non_uniform_simulation_state, index, expected +): + atomic_mass = ( + non_uniform_simulation_state.composition.effective_element_masses ) + assert_almost_equal( + atomic_mass.loc[index], + expected, + decimal=30, + ) -class TestModelState: - """Test the ModelState class.""" - def setup(self): - """Initialize config and model.""" - filename = "tardis_configv1_verysimple.yml" - self.config = Configuration.from_yaml(data_path(filename)) - self.model = Radial1DModel.from_config(self.config) - def test_geometry_velocities(self): - """Test if model velocities and the velocities stored in the geometry dict are the same.""" - assert_almost_equal( - self.model.model_state.geometry.v_inner.values, - self.model.v_inner.value, - ) - assert_almost_equal( - self.model.model_state.geometry.v_outer.values, - self.model.v_outer.value, +class TestModelStateFromNonUniformAbundances: + @pytest.fixture + def simulation_state(self, example_model_file_dir, atomic_dataset): + config = Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_isotope_iabund.yml" ) + return SimulationState.from_config(config, atom_data=atomic_dataset) - def test_geometry_radius(self): - """Test if model radii and the radii stored in the geometry dict are the same.""" + def test_atomic_mass(self, simulation_state): + atomic_mass = simulation_state.composition.effective_element_masses + assert_almost_equal(atomic_mass.loc[(1, 0)], 1.67378172e-24, decimal=30) assert_almost_equal( - self.model.model_state.geometry.r_inner.values, - self.model.r_inner.value, + atomic_mass.loc[(28, 0)], 9.51707707e-23, decimal=30 ) assert_almost_equal( - self.model.model_state.geometry.r_outer.values, - self.model.r_outer.value, + atomic_mass.loc[(28, 1)], 9.54725917e-23, decimal=30 ) - def test_geometry_units(self): - """Test the units stored in the geometry_units dict.""" - assert ( - self.model.model_state.geometry_units["v_inner"] - == self.model.v_inner.unit - ) - assert ( - self.model.model_state.geometry_units["v_outer"] - == self.model.v_outer.unit - ) - assert ( - self.model.model_state.geometry_units["r_inner"] - == self.model.r_inner.unit - ) - assert ( - self.model.model_state.geometry_units["r_outer"] - == self.model.r_outer.unit - ) - - def test_time_explosion(self): - """Test if time_explosion stored in ModelState is the same as that stored in Model.""" - assert ( - self.model.model_state.time_explosion.unit - == self.model.time_explosion.unit - ) - assert ( - self.model.model_state.time_explosion == self.model.time_explosion - ) - - def test_density(self): - """Test if density stored in ModelState is the same as that stored in Model.""" - assert self.model.model_state.density.unit == self.model.density.unit - assert_almost_equal( - self.model.model_state.density.value, self.model.density.value - ) + def test_elemental_number_density(self, simulation_state): + number = simulation_state.composition.elemental_number_density + assert_almost_equal(number.loc[(1, 0)], 0) + assert_almost_equal(number.loc[(28, 0)], 10825403.434893506, decimal=2) + assert_almost_equal(number.loc[(28, 1)], 1640835.7822178686, decimal=2) ### @@ -385,30 +463,34 @@ def test_density(self): @pytest.fixture(scope="module", autouse=True) def to_hdf_buffer(hdf_file_path, simulation_verysimple): - simulation_verysimple.model.to_hdf(hdf_file_path, overwrite=True) + simulation_verysimple.simulation_state.to_hdf(hdf_file_path, overwrite=True) -model_scalar_attrs = ["t_inner"] +simulation_state_scalar_attrs = ["t_inner"] -@pytest.mark.parametrize("attr", model_scalar_attrs) -def test_hdf_model_scalars(hdf_file_path, simulation_verysimple, attr): - path = os.path.join("model", "scalars") +@pytest.mark.parametrize("attr", simulation_state_scalar_attrs) +def test_hdf_simulation_state_scalars( + hdf_file_path, simulation_verysimple, attr +): + path = "simulation_state/scalars" expected = pd.read_hdf(hdf_file_path, path)[attr] - actual = getattr(simulation_verysimple.model, attr) + actual = getattr(simulation_verysimple.simulation_state, attr) if hasattr(actual, "cgs"): actual = actual.cgs.value assert_almost_equal(actual, expected) -model_nparray_attrs = ["w", "v_inner", "v_outer"] +simulation_state_nparray_attrs = ["dilution_factor", "v_inner", "v_outer"] -@pytest.mark.parametrize("attr", model_nparray_attrs) -def test_hdf_model_nparray(hdf_file_path, simulation_verysimple, attr): - path = os.path.join("model", attr) +@pytest.mark.parametrize("attr", simulation_state_nparray_attrs) +def test_hdf_simulation_state_nparray( + hdf_file_path, simulation_verysimple, attr +): + path = f"simulation_state/{attr}" expected = pd.read_hdf(hdf_file_path, path) - actual = getattr(simulation_verysimple.model, attr) + actual = getattr(simulation_verysimple.simulation_state, attr) if hasattr(actual, "cgs"): actual = actual.cgs.value assert_almost_equal(actual, expected.values) diff --git a/tardis/model/tests/test_csvy_model.py b/tardis/model/tests/test_csvy_model.py index 8d562f92c85..c82c23b8e26 100644 --- a/tardis/model/tests/test_csvy_model.py +++ b/tardis/model/tests/test_csvy_model.py @@ -1,15 +1,14 @@ +from pathlib import Path import numpy as np import pandas as pd import numpy.testing as npt -import tardis -import os + from astropy import units as u -from tardis.io.config_reader import Configuration -from tardis.model import Radial1DModel +from tardis.io.configuration.config_reader import Configuration +from tardis.io.atom_data.base import AtomData +from tardis.model import SimulationState import pytest -DATA_PATH = os.path.join(tardis.__path__[0], "model", "tests", "data") - @pytest.fixture( scope="module", @@ -22,29 +21,32 @@ "radiative", ], ) -def model_config_fnames(request): +def model_config_fnames(request, example_csvy_file_dir): """Function to retrieve filenames of target data for tests""" - filename = request.param - csvy_config_file = os.path.join(DATA_PATH, filename + "_csvy.yml") - old_config_file = os.path.join(DATA_PATH, filename + "_old_config.yml") + csvy_config_file = example_csvy_file_dir / f"{request.param}_csvy.yml" + old_config_file = example_csvy_file_dir / f"{request.param}_old_config.yml" return csvy_config_file, old_config_file -def test_compare_models(model_config_fnames): +def test_compare_models(model_config_fnames, atomic_dataset): """Compare identical models produced by .from_config and .from_csvy to check that velocities, densities and abundances (pre and post decay) are the same""" csvy_config_file, old_config_file = model_config_fnames tardis_config = Configuration.from_yaml(csvy_config_file) tardis_config_old = Configuration.from_yaml(old_config_file) - csvy_model = Radial1DModel.from_csvy(tardis_config) - config_model = Radial1DModel.from_config(tardis_config_old) - csvy_model_props = csvy_model.get_properties().keys() - config_model_props = config_model.get_properties().keys() + csvy_simulation_state = SimulationState.from_csvy( + tardis_config, atom_data=atomic_dataset + ) + config_simulation_state = SimulationState.from_config( + tardis_config_old, atom_data=atomic_dataset + ) + csvy_model_props = csvy_simulation_state.get_properties().keys() + config_model_props = config_simulation_state.get_properties().keys() npt.assert_array_equal(csvy_model_props, config_model_props) for prop in config_model_props: - csvy_model_val = csvy_model.get_properties()[prop] - config_model_val = config_model.get_properties()[prop] + csvy_model_val = csvy_simulation_state.get_properties()[prop] + config_model_val = config_simulation_state.get_properties()[prop] if prop == "homologous_density": npt.assert_array_almost_equal( csvy_model_val.density_0.value, config_model_val.density_0.value @@ -58,31 +60,66 @@ def test_compare_models(model_config_fnames): csvy_model_val = csvy_model_val.value npt.assert_array_almost_equal(csvy_model_val, config_model_val) - assert csvy_model.raw_abundance.shape == config_model.raw_abundance.shape assert ( - csvy_model.raw_isotope_abundance.shape - == config_model.raw_isotope_abundance.shape + csvy_simulation_state.abundance.shape + == config_simulation_state.abundance.shape + ) + assert ( + csvy_simulation_state.composition.nuclide_mass_fraction.shape + == config_simulation_state.composition.nuclide_mass_fraction.shape + ) + assert ( + csvy_simulation_state.abundance.shape + == config_simulation_state.abundance.shape ) - assert csvy_model.abundance.shape == config_model.abundance.shape npt.assert_array_almost_equal( - csvy_model.raw_abundance.to_numpy(), - config_model.raw_abundance.to_numpy(), + csvy_simulation_state.abundance.to_numpy(), + config_simulation_state.abundance.to_numpy(), ) npt.assert_array_almost_equal( - csvy_model.raw_isotope_abundance.to_numpy(), - config_model.raw_isotope_abundance.to_numpy(), + csvy_simulation_state.composition.nuclide_mass_fraction.to_numpy(), + config_simulation_state.composition.nuclide_mass_fraction.to_numpy(), ) npt.assert_array_almost_equal( - csvy_model.abundance.to_numpy(), config_model.abundance.to_numpy() + csvy_simulation_state.abundance.to_numpy(), + config_simulation_state.abundance.to_numpy(), + ) + + +def test_dimensionality_after_update_v_inner_boundary( + example_csvy_file_dir, atomic_dataset +): + """Test that the dimensionality of SimulationState parameters after updating v_inner_boundary + in the context of csvy models specifically""" + csvy_config_file = example_csvy_file_dir / "radiative_csvy.yml" + config = Configuration.from_yaml(csvy_config_file) + csvy_model = SimulationState.from_csvy(config, atom_data=atomic_dataset) + + new_config = config + new_config.model.v_inner_boundary = csvy_model.velocity[1] + new_csvy_model = SimulationState.from_csvy( + new_config, atom_data=atomic_dataset + ) + + assert new_csvy_model.no_of_raw_shells == csvy_model.no_of_raw_shells + assert new_csvy_model.no_of_shells == csvy_model.no_of_shells - 1 + assert new_csvy_model.velocity.shape[0] == csvy_model.velocity.shape[0] - 1 + assert new_csvy_model.density.shape[0] == csvy_model.density.shape[0] - 1 + assert new_csvy_model.volume.shape[0] == csvy_model.volume.shape[0] - 1 + assert ( + new_csvy_model.t_radiative.shape[0] + == csvy_model.t_radiative.shape[0] - 1 ) @pytest.fixture(scope="module") -def csvy_model_test_abundances(): - """Returns Radial1DModel to use to test abundances dataframes""" - csvypath = os.path.join(DATA_PATH, "csvy_model_to_test_abundances.yml") +def csvy_model_test_abundances(example_csvy_file_dir, atomic_dataset): + """Returns SimulationState to use to test abundances dataframes""" + csvypath = example_csvy_file_dir / "csvy_model_to_test_abundances.yml" config = Configuration.from_yaml(csvypath) - csvy_model_test_abundances = Radial1DModel.from_csvy(config) + csvy_model_test_abundances = SimulationState.from_csvy( + config, atom_data=atomic_dataset + ) return csvy_model_test_abundances @@ -122,22 +159,30 @@ def test_read_csvy_abundances( reference_input_isotopes, ) = reference_input_dataframes - model_abundance_shape = csvy_model_test_abundances.raw_abundance.shape + composition = csvy_model_test_abundances.composition + nuclide_mass_fraction = composition.nuclide_mass_fraction + model_abundances = nuclide_mass_fraction[ + nuclide_mass_fraction.index.get_level_values(1) == -1 + ] + reference_input_shape = reference_input_abundance.shape - assert model_abundance_shape == reference_input_shape + assert model_abundances.shape == reference_input_shape npt.assert_array_almost_equal( reference_input_abundance.to_numpy(), - csvy_model_test_abundances.raw_abundance.to_numpy(), + model_abundances.to_numpy(), ) - model_isotopes_shape = ( - csvy_model_test_abundances.raw_isotope_abundance.shape - ) - reference_input_isotopes_shape = reference_input_isotopes.shape - assert model_isotopes_shape == reference_input_isotopes_shape + model_isotopes = composition.isotopic_mass_fraction + # reference_input_isotopes_shape = reference_input_isotopes.shape + # We can't assert the shape anymore because the isotope abundances used + # to be decayed after being loaded into SimulationState. + # Now the abundances are decayed before + # assert model_isotopes.shape == reference_input_isotopes_shape + # Same applies to the comparison - we are summing up the mass_fraction to compare pre/post decay npt.assert_array_almost_equal( - reference_input_isotopes.to_numpy(), - csvy_model_test_abundances.raw_isotope_abundance.to_numpy(), + reference_input_isotopes.to_numpy()[0], + model_isotopes.sum(axis=0).to_numpy(), + decimal=1, ) diff --git a/tardis/model/tests/test_density.py b/tardis/model/tests/test_density.py index 8aeda87666d..907e2ef3e24 100644 --- a/tardis/model/tests/test_density.py +++ b/tardis/model/tests/test_density.py @@ -10,24 +10,22 @@ @pytest.fixture(scope="module", autouse=True) def to_hdf_buffer(hdf_file_path, simulation_verysimple): - simulation_verysimple.model.homologous_density.to_hdf( - hdf_file_path, overwrite=True - ) + simulation_verysimple.simulation_state.to_hdf(hdf_file_path, overwrite=True) def test_hdf_density_0(hdf_file_path, simulation_verysimple): - actual = simulation_verysimple.model.homologous_density.density_0 + actual = simulation_verysimple.simulation_state.density if hasattr(actual, "cgs"): actual = actual.cgs.value - path = os.path.join("homologous_density", "density_0") + path = "simulation_state/density" expected = pd.read_hdf(hdf_file_path, path) assert_almost_equal(actual, expected.values) def test_hdf_time_0(hdf_file_path, simulation_verysimple): - actual = simulation_verysimple.model.homologous_density.time_0 + actual = simulation_verysimple.simulation_state.time_explosion if hasattr(actual, "cgs"): actual = actual.cgs.value - path = os.path.join("homologous_density", "scalars") - expected = pd.read_hdf(hdf_file_path, path)["time_0"] + path = "simulation_state/scalars" + expected = pd.read_hdf(hdf_file_path, path)["time_explosion"] assert_almost_equal(actual, expected) diff --git a/tardis/montecarlo/__init__.py b/tardis/montecarlo/__init__.py deleted file mode 100644 index 222ee95b0b8..00000000000 --- a/tardis/montecarlo/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from tardis.montecarlo.base import * diff --git a/tardis/montecarlo/base.py b/tardis/montecarlo/base.py deleted file mode 100644 index ed0bc3b7a5f..00000000000 --- a/tardis/montecarlo/base.py +++ /dev/null @@ -1,636 +0,0 @@ -import os -import logging -import warnings - -from astropy import units as u -from tardis import constants as const -from numba import set_num_threads - -from scipy.special import zeta -from tardis.montecarlo.spectrum import TARDISSpectrum - -from tardis.util.base import quantity_linspace -from tardis.io.util import HDFWriterMixin -from tardis.montecarlo import packet_source as source -from tardis.montecarlo.montecarlo_numba.formal_integral import FormalIntegrator -from tardis.montecarlo import montecarlo_configuration as mc_config_module - - -from tardis.montecarlo.montecarlo_numba import montecarlo_radial1d -from tardis.montecarlo.montecarlo_numba.numba_interface import ( - configuration_initialize, -) -from tardis.montecarlo.montecarlo_numba import numba_config -from tardis.io.logger import montecarlo_tracking as mc_tracker - -import numpy as np - -logger = logging.getLogger(__name__) - - -MAX_SEED_VAL = 2 ** 32 - 1 - -# MAX_SEED_VAL must be multiple orders of magnitude larger than no_of_packets; -# otherwise, each packet would not have its own seed. Here, we set the max -# seed val to the maximum allowed by numpy. -# TODO: refactor this into more parts -class MontecarloRunner(HDFWriterMixin): - """ - This class is designed as an interface between the Python part and the - montecarlo C-part - """ - - hdf_properties = [ - "output_nu", - "output_energy", - "nu_bar_estimator", - "j_estimator", - "montecarlo_virtual_luminosity", - "last_interaction_in_nu", - "last_interaction_type", - "last_line_interaction_in_id", - "last_line_interaction_out_id", - "last_line_interaction_shell_id", - "packet_luminosity", - "spectrum", - "spectrum_virtual", - "spectrum_reabsorbed", - "time_of_simulation", - "emitted_packet_mask", - ] - - vpacket_hdf_properties = [ - "virt_packet_nus", - "virt_packet_energies", - "virt_packet_initial_rs", - "virt_packet_initial_mus", - "virt_packet_last_interaction_in_nu", - "virt_packet_last_interaction_type", - "virt_packet_last_line_interaction_in_id", - "virt_packet_last_line_interaction_out_id", - ] - - hdf_name = "runner" - w_estimator_constant = ( - (const.c ** 2 / (2 * const.h)) - * (15 / np.pi ** 4) - * (const.h / const.k_B) ** 4 - / (4 * np.pi) - ).cgs.value - - t_rad_estimator_constant = ( - (np.pi ** 4 / (15 * 24 * zeta(5, 1))) * (const.h / const.k_B) - ).cgs.value - - def __init__( - self, - seed, - spectrum_frequency, - virtual_spectrum_spawn_range, - disable_electron_scattering, - enable_reflective_inner_boundary, - enable_full_relativity, - inner_boundary_albedo, - line_interaction_type, - integrator_settings, - v_packet_settings, - spectrum_method, - virtual_packet_logging, - packet_source=None, - debug_packets=False, - logger_buffer=1, - single_packet_seed=None, - tracking_rpacket=False, - ): - - self.seed = seed - if packet_source is None: - self.packet_source = source.BlackBodySimpleSource(seed) - else: - self.packet_source = packet_source - # inject different packets - self.disable_electron_scattering = disable_electron_scattering - self.spectrum_frequency = spectrum_frequency - self.virtual_spectrum_spawn_range = virtual_spectrum_spawn_range - self.enable_reflective_inner_boundary = enable_reflective_inner_boundary - self.inner_boundary_albedo = inner_boundary_albedo - self.enable_full_relativity = enable_full_relativity - numba_config.ENABLE_FULL_RELATIVITY = enable_full_relativity - self.line_interaction_type = line_interaction_type - self.single_packet_seed = single_packet_seed - self.integrator_settings = integrator_settings - self.v_packet_settings = v_packet_settings - self.spectrum_method = spectrum_method - self.seed = seed - self._integrator = None - self._spectrum_integrated = None - - self.virt_logging = virtual_packet_logging - self.virt_packet_last_interaction_type = np.ones(2) * -1 - self.virt_packet_last_interaction_in_nu = np.ones(2) * -1.0 - self.virt_packet_last_line_interaction_in_id = np.ones(2) * -1 - self.virt_packet_last_line_interaction_out_id = np.ones(2) * -1 - self.virt_packet_nus = np.ones(2) * -1.0 - self.virt_packet_energies = np.ones(2) * -1.0 - self.virt_packet_initial_rs = np.ones(2) * -1.0 - self.virt_packet_initial_mus = np.ones(2) * -1.0 - - # Setting up the Tracking array for storing all the RPacketTracker instances - self.rpacket_tracker = None - - # set up logger based on config - mc_tracker.DEBUG_MODE = debug_packets - mc_tracker.BUFFER = logger_buffer - - mc_config_module.RPACKET_TRACKING = tracking_rpacket - - if self.spectrum_method == "integrated": - self.optional_hdf_properties.append("spectrum_integrated") - - def _initialize_estimator_arrays(self, tau_sobolev_shape): - """ - Initialize the output arrays of the montecarlo simulation. - - Parameters - ---------- - tau_sobolev_shape : tuple - tuple for the tau_sobolev_shape - """ - - # Estimators - self.j_estimator = np.zeros(tau_sobolev_shape[1], dtype=np.float64) - self.nu_bar_estimator = np.zeros(tau_sobolev_shape[1], dtype=np.float64) - self.j_blue_estimator = np.zeros(tau_sobolev_shape) - self.Edotlu_estimator = np.zeros(tau_sobolev_shape) - # TODO: this is the wrong attribute naming style. - - def _initialize_geometry_arrays(self, model): - """ - Generate the cgs like geometry arrays for the montecarlo part - - Parameters - ---------- - model : model.Radial1DModel - """ - self.r_inner_cgs = model.r_inner.to("cm").value - self.r_outer_cgs = model.r_outer.to("cm").value - self.v_inner_cgs = model.v_inner.to("cm/s").value - - def _initialize_packets(self, T, no_of_packets, iteration, radius): - # the iteration is added each time to preserve randomness - # across different simulations with the same temperature, - # for example. We seed the random module instead of the numpy module - # because we call random.sample, which references a different internal - # state than in the numpy.random module. - seed = self.seed + iteration - rng = np.random.default_rng(seed=seed) - seeds = rng.choice(MAX_SEED_VAL, no_of_packets, replace=True) - radii, nus, mus, energies = self.packet_source.create_packets( - T, no_of_packets, rng, radius - ) - mc_config_module.packet_seeds = seeds - self.input_r = radii - self.input_nu = nus - self.input_mu = mus - self.input_energy = energies - - self._output_nu = np.ones(no_of_packets, dtype=np.float64) * -99.0 - self._output_energy = np.ones(no_of_packets, dtype=np.float64) * -99.0 - - self.last_line_interaction_in_id = -1 * np.ones( - no_of_packets, dtype=np.int64 - ) - self.last_line_interaction_out_id = -1 * np.ones( - no_of_packets, dtype=np.int64 - ) - self.last_line_interaction_shell_id = -1 * np.ones( - no_of_packets, dtype=np.int64 - ) - self.last_interaction_type = -1 * np.ones(no_of_packets, dtype=np.int64) - self.last_interaction_in_nu = np.zeros(no_of_packets, dtype=np.float64) - - self._montecarlo_virtual_luminosity = u.Quantity( - np.zeros_like(self.spectrum_frequency.value), "erg / s" - ) - - @property - def spectrum(self): - return TARDISSpectrum( - self.spectrum_frequency, self.montecarlo_emitted_luminosity - ) - - @property - def spectrum_reabsorbed(self): - return TARDISSpectrum( - self.spectrum_frequency, self.montecarlo_reabsorbed_luminosity - ) - - @property - def spectrum_virtual(self): - if np.all(self.montecarlo_virtual_luminosity == 0): - warnings.warn( - "MontecarloRunner.spectrum_virtual" - "is zero. Please run the montecarlo simulation with" - "no_of_virtual_packets > 0", - UserWarning, - ) - - return TARDISSpectrum( - self.spectrum_frequency, self.montecarlo_virtual_luminosity - ) - - @property - def spectrum_integrated(self): - if self._spectrum_integrated is None: - self._spectrum_integrated = self.integrator.calculate_spectrum( - self.spectrum_frequency[:-1], **self.integrator_settings - ) - return self._spectrum_integrated - - @property - def integrator(self): - if self._integrator is None: - warnings.warn( - "MontecarloRunner.integrator: " - "The FormalIntegrator is not yet available." - "Please run the montecarlo simulation at least once.", - UserWarning, - ) - if self.enable_full_relativity: - raise NotImplementedError( - "The FormalIntegrator is not yet implemented for the full " - "relativity mode. " - "Please run with config option enable_full_relativity: " - "False." - ) - return self._integrator - - def run( - self, - model, - plasma, - no_of_packets, - no_of_virtual_packets=0, - nthreads=1, - last_run=False, - iteration=0, - total_iterations=0, - show_progress_bars=True, - ): - """ - Run the montecarlo calculation - - Parameters - ---------- - model : tardis.model.Radial1DModel - plasma : tardis.plasma.BasePlasma - no_of_packets : int - no_of_virtual_packets : int - nthreads : int - last_run : bool - total_iterations : int - The total number of iterations in the simulation. - - Returns - ------- - None - """ - - set_num_threads(nthreads) - - self.time_of_simulation = self.calculate_time_of_simulation(model) - self.volume = model.volume - - # Initializing estimator array - self._initialize_estimator_arrays(plasma.tau_sobolevs.shape) - - self._initialize_geometry_arrays(model) - - self._initialize_packets( - model.t_inner.value, no_of_packets, iteration, model.r_inner[0] - ) - - configuration_initialize(self, no_of_virtual_packets) - montecarlo_radial1d( - model, - plasma, - iteration, - no_of_packets, - total_iterations, - show_progress_bars, - self, - ) - self._integrator = FormalIntegrator(model, plasma, self) - # montecarlo.montecarlo_radial1d( - # model, plasma, self, - # virtual_packet_flag=no_of_virtual_packets, - # nthreads=nthreads, - # last_run=last_run) - - def legacy_return(self): - return ( - self.output_nu, - self.output_energy, - self.j_estimator, - self.nu_bar_estimator, - self.last_line_interaction_in_id, - self.last_line_interaction_out_id, - self.last_interaction_type, - self.last_line_interaction_shell_id, - ) - - def get_line_interaction_id(self, line_interaction_type): - return ["scatter", "downbranch", "macroatom"].index( - line_interaction_type - ) - - @property - def output_nu(self): - return u.Quantity(self._output_nu, u.Hz) - - @property - def output_energy(self): - return u.Quantity(self._output_energy, u.erg) - - @property - def virtual_packet_nu(self): - try: - return u.Quantity(self.virt_packet_nus, u.Hz) - except AttributeError: - warnings.warn( - "MontecarloRunner.virtual_packet_nu:" - "Set 'virtual_packet_logging: True' in the configuration file" - "to access this property" - "It should be added under 'virtual' property of 'spectrum' property", - UserWarning, - ) - return None - - @property - def virtual_packet_energy(self): - try: - return u.Quantity(self.virt_packet_energies, u.erg) - except AttributeError: - warnings.warn( - "MontecarloRunner.virtual_packet_energy:" - "Set 'virtual_packet_logging: True' in the configuration file" - "to access this property" - "It should be added under 'virtual' property of 'spectrum' property", - UserWarning, - ) - return None - - @property - def virtual_packet_luminosity(self): - try: - return self.virtual_packet_energy / self.time_of_simulation - except TypeError: - warnings.warn( - "MontecarloRunner.virtual_packet_luminosity:" - "Set 'virtual_packet_logging: True' in the configuration file" - "to access this property" - "It should be added under 'virtual' property of 'spectrum' property", - UserWarning, - ) - return None - - @property - def packet_luminosity(self): - return self.output_energy / self.time_of_simulation - - @property - def emitted_packet_mask(self): - return self.output_energy >= 0 - - @property - def emitted_packet_nu(self): - return self.output_nu[self.emitted_packet_mask] - - @property - def reabsorbed_packet_nu(self): - return self.output_nu[~self.emitted_packet_mask] - - @property - def emitted_packet_luminosity(self): - return self.packet_luminosity[self.emitted_packet_mask] - - @property - def reabsorbed_packet_luminosity(self): - return -self.packet_luminosity[~self.emitted_packet_mask] - - @property - def montecarlo_reabsorbed_luminosity(self): - return u.Quantity( - np.histogram( - self.reabsorbed_packet_nu, - weights=self.reabsorbed_packet_luminosity, - bins=self.spectrum_frequency.value, - )[0], - "erg / s", - ) - - @property - def montecarlo_emitted_luminosity(self): - return u.Quantity( - np.histogram( - self.emitted_packet_nu, - weights=self.emitted_packet_luminosity, - bins=self.spectrum_frequency.value, - )[0], - "erg / s", - ) - - @property - def montecarlo_virtual_luminosity(self): - return ( - self._montecarlo_virtual_luminosity[:-1] - / self.time_of_simulation.value - ) - - def calculate_emitted_luminosity( - self, luminosity_nu_start, luminosity_nu_end - ): - """ - Calculate emitted luminosity. - - Parameters - ---------- - luminosity_nu_start : astropy.units.Quantity - luminosity_nu_end : astropy.units.Quantity - - Returns - ------- - astropy.units.Quantity - """ - luminosity_wavelength_filter = ( - self.emitted_packet_nu > luminosity_nu_start - ) & (self.emitted_packet_nu < luminosity_nu_end) - - emitted_luminosity = self.emitted_packet_luminosity[ - luminosity_wavelength_filter - ].sum() - - return emitted_luminosity - - def calculate_reabsorbed_luminosity( - self, luminosity_nu_start, luminosity_nu_end - ): - """ - Calculate reabsorbed luminosity. - - Parameters - ---------- - luminosity_nu_start : astropy.units.Quantity - luminosity_nu_end : astropy.units.Quantity - - Returns - ------- - astropy.units.Quantity - """ - luminosity_wavelength_filter = ( - self.reabsorbed_packet_nu > luminosity_nu_start - ) & (self.reabsorbed_packet_nu < luminosity_nu_end) - - reabsorbed_luminosity = self.reabsorbed_packet_luminosity[ - luminosity_wavelength_filter - ].sum() - - return reabsorbed_luminosity - - def calculate_radiationfield_properties(self): - """ - Calculate an updated radiation field from the :math: - `\\bar{nu}_\\textrm{estimator}` and :math:`\\J_\\textrm{estimator}` - calculated in the montecarlo simulation. - The details of the calculation can be found in the documentation. - - Parameters - ---------- - nubar_estimator : np.ndarray (float) - j_estimator : np.ndarray (float) - - Returns - ------- - t_rad : astropy.units.Quantity (float) - w : numpy.ndarray (float) - """ - - t_rad = ( - self.t_rad_estimator_constant - * self.nu_bar_estimator - / self.j_estimator - ) - w = self.j_estimator / ( - 4 - * const.sigma_sb.cgs.value - * t_rad ** 4 - * self.time_of_simulation.value - * self.volume.value - ) - - return t_rad * u.K, w - - def calculate_luminosity_inner(self, model): - """ - Calculate inner luminosity. - - Parameters - ---------- - model : model.Radial1DModel - - Returns - ------- - astropy.units.Quantity - """ - return ( - 4 - * np.pi - * const.sigma_sb.cgs - * model.r_inner[0] ** 2 - * model.t_inner ** 4 - ).to("erg/s") - - def calculate_time_of_simulation(self, model): - """ - Calculate time of montecarlo simulation. - - Parameters - ---------- - model : model.Radial1DModel - - Returns - ------- - float - """ - return 1.0 * u.erg / self.calculate_luminosity_inner(model) - - def calculate_f_nu(self, frequency): - pass - - def calculate_f_lambda(self, wavelength): - pass - - @classmethod - def from_config( - cls, config, packet_source=None, virtual_packet_logging=False - ): - """ - Create a new MontecarloRunner instance from a Configuration object. - - Parameters - ---------- - config : tardis.io.config_reader.Configuration - virtual_packet_logging : bool - - Returns - ------- - MontecarloRunner - """ - if config.plasma.disable_electron_scattering: - logger.warn( - "Disabling electron scattering - this is not physical." - "Likely bug in formal integral - " - "will not give same results." - ) - numba_config.SIGMA_THOMSON = 1e-200 - # mc_config_module.disable_electron_scattering = True - else: - logger.debug("Electron scattering switched on") - numba_config.SIGMA_THOMSON = const.sigma_T.to("cm^2").value - # mc_config_module.disable_electron_scattering = False - - spectrum_frequency = quantity_linspace( - config.spectrum.stop.to("Hz", u.spectral()), - config.spectrum.start.to("Hz", u.spectral()), - num=config.spectrum.num + 1, - ) - mc_config_module.disable_line_scattering = ( - config.plasma.disable_line_scattering - ) - - mc_config_module.INITIAL_TRACKING_ARRAY_LENGTH = ( - config.montecarlo.tracking.initial_array_length - ) - - return cls( - seed=config.montecarlo.seed, - spectrum_frequency=spectrum_frequency, - virtual_spectrum_spawn_range=config.montecarlo.virtual_spectrum_spawn_range, - enable_reflective_inner_boundary=config.montecarlo.enable_reflective_inner_boundary, - inner_boundary_albedo=config.montecarlo.inner_boundary_albedo, - enable_full_relativity=config.montecarlo.enable_full_relativity, - line_interaction_type=config.plasma.line_interaction_type, - integrator_settings=config.spectrum.integrated, - v_packet_settings=config.spectrum.virtual, - spectrum_method=config.spectrum.method, - disable_electron_scattering=config.plasma.disable_electron_scattering, - packet_source=packet_source, - debug_packets=config.montecarlo.debug_packets, - logger_buffer=config.montecarlo.logger_buffer, - single_packet_seed=config.montecarlo.single_packet_seed, - virtual_packet_logging=( - config.spectrum.virtual.virtual_packet_logging - | virtual_packet_logging - ), - tracking_rpacket=config.montecarlo.tracking.track_rpacket, - ) diff --git a/tardis/montecarlo/montecarlo_configuration.py b/tardis/montecarlo/montecarlo_configuration.py deleted file mode 100644 index 2547ba121a0..00000000000 --- a/tardis/montecarlo/montecarlo_configuration.py +++ /dev/null @@ -1,18 +0,0 @@ -from tardis import constants as const - -full_relativity = True -single_packet_seed = -1 -temporary_v_packet_bins = 0 -number_of_vpackets = 0 -montecarlo_seed = 0 -line_interaction_type = None -packet_seeds = [] -disable_electron_scattering = False -disable_line_scattering = False -survival_probability = 0.0 -tau_russian = 10.0 - -INITIAL_TRACKING_ARRAY_LENGTH = None -LEGACY_MODE_ENABLED = False -VPACKET_LOGGING = False -RPACKET_TRACKING = False diff --git a/tardis/montecarlo/montecarlo_numba/__init__.py b/tardis/montecarlo/montecarlo_numba/__init__.py deleted file mode 100644 index d73c539a7a9..00000000000 --- a/tardis/montecarlo/montecarlo_numba/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -from llvmlite import binding - -binding.set_option("tmp", "-non-global-value-max-name-size=2048") -njit_dict = {"fastmath": True, "error_model": "numpy", "parallel": True} -njit_dict_no_parallel = { - "fastmath": True, - "error_model": "numpy", - "parallel": False, -} - -from tardis.montecarlo.montecarlo_numba.r_packet import RPacket -from tardis.montecarlo.montecarlo_numba.base import montecarlo_radial1d -from tardis.montecarlo.montecarlo_numba.numba_interface import PacketCollection diff --git a/tardis/montecarlo/montecarlo_numba/base.py b/tardis/montecarlo/montecarlo_numba/base.py deleted file mode 100644 index f07d6fc057f..00000000000 --- a/tardis/montecarlo/montecarlo_numba/base.py +++ /dev/null @@ -1,355 +0,0 @@ -from numba import prange, njit, jit, objmode -import logging -import numpy as np - -from tardis.montecarlo.montecarlo_numba.r_packet import ( - RPacket, - PacketStatus, -) -from tardis.montecarlo.montecarlo_numba.utils import MonteCarloException - -from tardis.montecarlo.montecarlo_numba.numba_interface import ( - PacketCollection, - VPacketCollection, - RPacketTracker, - NumbaModel, - numba_plasma_initialize, - Estimators, - configuration_initialize, -) - -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, -) - -from tardis.montecarlo.montecarlo_numba.single_packet_loop import ( - single_packet_loop, -) -from tardis.montecarlo.montecarlo_numba import njit_dict -from numba.typed import List -from tardis.util.base import update_iterations_pbar, update_packet_pbar - - -def montecarlo_radial1d( - model, - plasma, - iteration, - no_of_packets, - total_iterations, - show_progress_bars, - runner, -): - packet_collection = PacketCollection( - runner.input_r, - runner.input_nu, - runner.input_mu, - runner.input_energy, - runner._output_nu, - runner._output_energy, - ) - - numba_model = NumbaModel( - runner.r_inner_cgs, - runner.r_outer_cgs, - model.time_explosion.to("s").value, - ) - numba_plasma = numba_plasma_initialize(plasma, runner.line_interaction_type) - estimators = Estimators( - runner.j_estimator, - runner.nu_bar_estimator, - runner.j_blue_estimator, - runner.Edotlu_estimator, - ) - packet_seeds = montecarlo_configuration.packet_seeds - - number_of_vpackets = montecarlo_configuration.number_of_vpackets - - ( - v_packets_energy_hist, - last_interaction_type, - last_interaction_in_nu, - last_line_interaction_in_id, - last_line_interaction_out_id, - virt_packet_nus, - virt_packet_energies, - virt_packet_initial_mus, - virt_packet_initial_rs, - virt_packet_last_interaction_in_nu, - virt_packet_last_interaction_type, - virt_packet_last_line_interaction_in_id, - virt_packet_last_line_interaction_out_id, - rpacket_trackers, - ) = montecarlo_main_loop( - packet_collection, - numba_model, - numba_plasma, - estimators, - runner.spectrum_frequency.value, - number_of_vpackets, - packet_seeds, - montecarlo_configuration.VPACKET_LOGGING, - iteration=iteration, - show_progress_bars=show_progress_bars, - no_of_packets=no_of_packets, - total_iterations=total_iterations, - ) - - runner._montecarlo_virtual_luminosity.value[:] = v_packets_energy_hist - runner.last_interaction_type = last_interaction_type - runner.last_interaction_in_nu = last_interaction_in_nu - runner.last_line_interaction_in_id = last_line_interaction_in_id - runner.last_line_interaction_out_id = last_line_interaction_out_id - - if montecarlo_configuration.VPACKET_LOGGING and number_of_vpackets > 0: - runner.virt_packet_nus = np.concatenate( - np.array(virt_packet_nus) - ).ravel() - runner.virt_packet_energies = np.concatenate( - np.array(virt_packet_energies) - ).ravel() - runner.virt_packet_initial_mus = np.concatenate( - np.array(virt_packet_initial_mus) - ).ravel() - runner.virt_packet_initial_rs = np.concatenate( - np.array(virt_packet_initial_rs) - ).ravel() - runner.virt_packet_last_interaction_in_nu = np.concatenate( - np.array(virt_packet_last_interaction_in_nu) - ).ravel() - runner.virt_packet_last_interaction_type = np.concatenate( - np.array(virt_packet_last_interaction_type) - ).ravel() - runner.virt_packet_last_line_interaction_in_id = np.concatenate( - np.array(virt_packet_last_line_interaction_in_id) - ).ravel() - runner.virt_packet_last_line_interaction_out_id = np.concatenate( - np.array(virt_packet_last_line_interaction_out_id) - ).ravel() - update_iterations_pbar(1) - - # Condition for Checking if RPacket Tracking is enabled - if montecarlo_configuration.RPACKET_TRACKING: - runner.rpacket_tracker = rpacket_trackers - - -@njit(**njit_dict) -def montecarlo_main_loop( - packet_collection, - numba_model, - numba_plasma, - estimators, - spectrum_frequency, - number_of_vpackets, - packet_seeds, - virtual_packet_logging, - iteration, - show_progress_bars, - no_of_packets, - total_iterations, -): - """ - This is the main loop of the MonteCarlo routine that generates packets - and sends them through the ejecta. - - Parameters - ---------- - packet_collection : PacketCollection - numba_model : NumbaModel - estimators : NumbaEstimators - spectrum_frequency : astropy.units.Quantity - frequency bins - number_of_vpackets : int - VPackets released per interaction - packet_seeds : numpy.array - virtual_packet_logging : bool - Option to enable virtual packet logging. - """ - output_nus = np.empty_like(packet_collection.packets_output_nu) - last_interaction_types = ( - np.ones_like(packet_collection.packets_output_nu, dtype=np.int64) * -1 - ) - output_energies = np.empty_like(packet_collection.packets_output_nu) - - last_interaction_in_nus = np.empty_like(packet_collection.packets_output_nu) - last_line_interaction_in_ids = ( - np.ones_like(packet_collection.packets_output_nu, dtype=np.int64) * -1 - ) - last_line_interaction_out_ids = ( - np.ones_like(packet_collection.packets_output_nu, dtype=np.int64) * -1 - ) - - v_packets_energy_hist = np.zeros_like(spectrum_frequency) - delta_nu = spectrum_frequency[1] - spectrum_frequency[0] - - # Pre-allocate a list of vpacket collections for later storage - vpacket_collections = List() - for i in range(len(output_nus)): - vpacket_collections.append( - VPacketCollection( - i, - spectrum_frequency, - montecarlo_configuration.v_packet_spawn_start_frequency, - montecarlo_configuration.v_packet_spawn_end_frequency, - number_of_vpackets, - montecarlo_configuration.temporary_v_packet_bins, - ) - ) - - # Configuring the Tracking for R_Packets - rpacket_trackers = List() - for i in range(len(output_nus)): - rpacket_trackers.append(RPacketTracker()) - - # Arrays for vpacket logging - virt_packet_nus = [] - virt_packet_energies = [] - virt_packet_initial_mus = [] - virt_packet_initial_rs = [] - virt_packet_last_interaction_in_nu = [] - virt_packet_last_interaction_type = [] - virt_packet_last_line_interaction_in_id = [] - virt_packet_last_line_interaction_out_id = [] - - for i in prange(len(output_nus)): - if show_progress_bars: - with objmode: - update_amount = 1 - update_packet_pbar( - update_amount, - current_iteration=iteration, - no_of_packets=no_of_packets, - total_iterations=total_iterations, - ) - - if montecarlo_configuration.single_packet_seed != -1: - seed = packet_seeds[montecarlo_configuration.single_packet_seed] - np.random.seed(seed) - else: - seed = packet_seeds[i] - np.random.seed(seed) - r_packet = RPacket( - numba_model.r_inner[0], - packet_collection.packets_input_mu[i], - packet_collection.packets_input_nu[i], - packet_collection.packets_input_energy[i], - seed, - i, - ) - vpacket_collection = vpacket_collections[i] - tracked_rpacket = rpacket_trackers[i] - - single_packet_loop( - r_packet, - numba_model, - numba_plasma, - estimators, - vpacket_collection, - tracked_rpacket, - ) - - output_nus[i] = r_packet.nu - last_interaction_in_nus[i] = r_packet.last_interaction_in_nu - last_line_interaction_in_ids[i] = r_packet.last_line_interaction_in_id - last_line_interaction_out_ids[i] = r_packet.last_line_interaction_out_id - - if r_packet.status == PacketStatus.REABSORBED: - output_energies[i] = -r_packet.energy - last_interaction_types[i] = r_packet.last_interaction_type - elif r_packet.status == PacketStatus.EMITTED: - output_energies[i] = r_packet.energy - last_interaction_types[i] = r_packet.last_interaction_type - - vpackets_nu = vpacket_collection.nus[: vpacket_collection.idx] - vpackets_energy = vpacket_collection.energies[: vpacket_collection.idx] - vpackets_initial_mu = vpacket_collection.initial_mus[ - : vpacket_collection.idx - ] - vpackets_initial_r = vpacket_collection.initial_rs[ - : vpacket_collection.idx - ] - - v_packets_idx = np.floor( - (vpackets_nu - spectrum_frequency[0]) / delta_nu - ).astype(np.int64) - # if we're only in a single-packet mode - # if montecarlo_configuration.single_packet_seed == -1: - # break - for j, idx in enumerate(v_packets_idx): - if (vpackets_nu[j] < spectrum_frequency[0]) or ( - vpackets_nu[j] > spectrum_frequency[-1] - ): - continue - v_packets_energy_hist[idx] += vpackets_energy[j] - - if virtual_packet_logging: - for vpacket_collection in vpacket_collections: - vpackets_nu = vpacket_collection.nus[: vpacket_collection.idx] - vpackets_energy = vpacket_collection.energies[ - : vpacket_collection.idx - ] - vpackets_initial_mu = vpacket_collection.initial_mus[ - : vpacket_collection.idx - ] - vpackets_initial_r = vpacket_collection.initial_rs[ - : vpacket_collection.idx - ] - virt_packet_nus.append(np.ascontiguousarray(vpackets_nu)) - virt_packet_energies.append(np.ascontiguousarray(vpackets_energy)) - virt_packet_initial_mus.append( - np.ascontiguousarray(vpackets_initial_mu) - ) - virt_packet_initial_rs.append( - np.ascontiguousarray(vpackets_initial_r) - ) - virt_packet_last_interaction_in_nu.append( - np.ascontiguousarray( - vpacket_collection.last_interaction_in_nu[ - : vpacket_collection.idx - ] - ) - ) - virt_packet_last_interaction_type.append( - np.ascontiguousarray( - vpacket_collection.last_interaction_type[ - : vpacket_collection.idx - ] - ) - ) - virt_packet_last_line_interaction_in_id.append( - np.ascontiguousarray( - vpacket_collection.last_interaction_in_id[ - : vpacket_collection.idx - ] - ) - ) - virt_packet_last_line_interaction_out_id.append( - np.ascontiguousarray( - vpacket_collection.last_interaction_out_id[ - : vpacket_collection.idx - ] - ) - ) - - if montecarlo_configuration.RPACKET_TRACKING: - for rpacket_tracker in rpacket_trackers: - rpacket_tracker.finalize_array() - - packet_collection.packets_output_energy[:] = output_energies[:] - packet_collection.packets_output_nu[:] = output_nus[:] - - return ( - v_packets_energy_hist, - last_interaction_types, - last_interaction_in_nus, - last_line_interaction_in_ids, - last_line_interaction_out_ids, - virt_packet_nus, - virt_packet_energies, - virt_packet_initial_mus, - virt_packet_initial_rs, - virt_packet_last_interaction_in_nu, - virt_packet_last_interaction_type, - virt_packet_last_line_interaction_in_id, - virt_packet_last_line_interaction_out_id, - rpacket_trackers, - ) diff --git a/tardis/montecarlo/montecarlo_numba/estimators.py b/tardis/montecarlo/montecarlo_numba/estimators.py deleted file mode 100644 index 1e7782350e3..00000000000 --- a/tardis/montecarlo/montecarlo_numba/estimators.py +++ /dev/null @@ -1,76 +0,0 @@ -from numba import njit - -from tardis.montecarlo.montecarlo_numba import ( - njit_dict_no_parallel, -) - -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( - calc_packet_energy, - calc_packet_energy_full_relativity, -) - -from tardis.montecarlo.montecarlo_numba.numba_config import ( - ENABLE_FULL_RELATIVITY, -) - - -@njit(**njit_dict_no_parallel) -def set_estimators(r_packet, distance, numba_estimator, comov_nu, comov_energy): - """ - Updating the estimators - """ - numba_estimator.j_estimator[r_packet.current_shell_id] += ( - comov_energy * distance - ) - numba_estimator.nu_bar_estimator[r_packet.current_shell_id] += ( - comov_energy * distance * comov_nu - ) - - -@njit(**njit_dict_no_parallel) -def set_estimators_full_relativity( - r_packet, distance, numba_estimator, comov_nu, comov_energy, doppler_factor -): - numba_estimator.j_estimator[r_packet.current_shell_id] += ( - comov_energy * distance * doppler_factor - ) - numba_estimator.nu_bar_estimator[r_packet.current_shell_id] += ( - comov_energy * distance * comov_nu * doppler_factor - ) - - -@njit(**njit_dict_no_parallel) -def update_line_estimators( - estimators, r_packet, cur_line_id, distance_trace, time_explosion -): - """ - Function to update the line estimators - - Parameters - ---------- - estimators : tardis.montecarlo.montecarlo_numba.numba_interface.Estimators - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - cur_line_id : int - distance_trace : float - time_explosion : float - """ - - """ Actual calculation - simplified below - r_interaction = math.sqrt(r_packet.r**2 + distance_trace**2 + - 2 * r_packet.r * distance_trace * r_packet.mu) - mu_interaction = (r_packet.mu * r_packet.r + distance_trace) / r_interaction - doppler_factor = 1.0 - mu_interaction * r_interaction / - ( time_explosion * C) - """ - - if not ENABLE_FULL_RELATIVITY: - energy = calc_packet_energy(r_packet, distance_trace, time_explosion) - else: - energy = calc_packet_energy_full_relativity(r_packet) - - estimators.j_blue_estimator[cur_line_id, r_packet.current_shell_id] += ( - energy / r_packet.nu - ) - estimators.Edotlu_estimator[ - cur_line_id, r_packet.current_shell_id - ] += energy diff --git a/tardis/montecarlo/montecarlo_numba/interaction.py b/tardis/montecarlo/montecarlo_numba/interaction.py deleted file mode 100644 index 5841aa3d930..00000000000 --- a/tardis/montecarlo/montecarlo_numba/interaction.py +++ /dev/null @@ -1,117 +0,0 @@ -from numba import njit -from tardis.montecarlo.montecarlo_numba import njit_dict, njit_dict_no_parallel -from tardis.montecarlo.montecarlo_numba.numba_interface import ( - LineInteractionType, -) - -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, -) -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( - get_doppler_factor, - get_inverse_doppler_factor, - angle_aberration_CMF_to_LF, -) -from tardis.montecarlo.montecarlo_numba.r_packet import ( - InteractionType, -) -from tardis.montecarlo.montecarlo_numba.utils import get_random_mu -from tardis.montecarlo.montecarlo_numba.macro_atom import macro_atom - - -@njit(**njit_dict_no_parallel) -def thomson_scatter(r_packet, time_explosion): - """ - Thomson scattering — no longer line scattering - \n1) get the doppler factor at that position with the old angle - \n2) convert the current energy and nu into the comoving frame with the old mu - \n3) Scatter and draw new mu - update mu - \n4) Transform the comoving energy and nu back using the new mu - - Parameters - ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - time_explosion : float - time since explosion in seconds - """ - old_doppler_factor = get_doppler_factor( - r_packet.r, r_packet.mu, time_explosion - ) - comov_nu = r_packet.nu * old_doppler_factor - comov_energy = r_packet.energy * old_doppler_factor - r_packet.mu = get_random_mu() - inverse_new_doppler_factor = get_inverse_doppler_factor( - r_packet.r, r_packet.mu, time_explosion - ) - - r_packet.nu = comov_nu * inverse_new_doppler_factor - r_packet.energy = comov_energy * inverse_new_doppler_factor - if montecarlo_configuration.full_relativity: - r_packet.mu = angle_aberration_CMF_to_LF( - r_packet, time_explosion, r_packet.mu - ) - - -@njit(**njit_dict_no_parallel) -def line_scatter(r_packet, time_explosion, line_interaction_type, numba_plasma): - """ - Line scatter function that handles the scattering itself, including new angle drawn, and calculating nu out using macro atom - - Parameters - ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - time_explosion : float - line_interaction_type : enum - numba_plasma : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaPlasma - """ - - old_doppler_factor = get_doppler_factor( - r_packet.r, r_packet.mu, time_explosion - ) - r_packet.mu = get_random_mu() - - inverse_new_doppler_factor = get_inverse_doppler_factor( - r_packet.r, r_packet.mu, time_explosion - ) - - comov_energy = r_packet.energy * old_doppler_factor - r_packet.energy = comov_energy * inverse_new_doppler_factor - - if line_interaction_type == LineInteractionType.SCATTER: - line_emission( - r_packet, r_packet.next_line_id, time_explosion, numba_plasma - ) - else: # includes both macro atom and downbranch - encoded in the transition probabilities - emission_line_id = macro_atom(r_packet, numba_plasma) - line_emission(r_packet, emission_line_id, time_explosion, numba_plasma) - - -@njit(**njit_dict_no_parallel) -def line_emission(r_packet, emission_line_id, time_explosion, numba_plasma): - """ - Sets the frequency of the RPacket properly given the emission channel - - Parameters - ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - emission_line_id : int - time_explosion : float - numba_plasma : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaPlasma - """ - r_packet.last_line_interaction_out_id = emission_line_id - - if emission_line_id != r_packet.next_line_id: - pass - inverse_doppler_factor = get_inverse_doppler_factor( - r_packet.r, r_packet.mu, time_explosion - ) - r_packet.nu = ( - numba_plasma.line_list_nu[emission_line_id] * inverse_doppler_factor - ) - r_packet.next_line_id = emission_line_id + 1 - nu_line = numba_plasma.line_list_nu[emission_line_id] - - if montecarlo_configuration.full_relativity: - r_packet.mu = angle_aberration_CMF_to_LF( - r_packet, time_explosion, r_packet.mu - ) diff --git a/tardis/montecarlo/montecarlo_numba/numba_interface.py b/tardis/montecarlo/montecarlo_numba/numba_interface.py deleted file mode 100644 index 14d3737d38d..00000000000 --- a/tardis/montecarlo/montecarlo_numba/numba_interface.py +++ /dev/null @@ -1,467 +0,0 @@ -from enum import IntEnum - -from numba import float64, int64, boolean -from numba.experimental import jitclass -import numpy as np - -from astropy import units as u -from tardis import constants as const - -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, -) - - -C_SPEED_OF_LIGHT = const.c.to("cm/s").value - -numba_model_spec = [ - ("r_inner", float64[:]), - ("r_outer", float64[:]), - ("time_explosion", float64), -] - - -@jitclass(numba_model_spec) -class NumbaModel(object): - def __init__(self, r_inner, r_outer, time_explosion): - """ - Model for the Numba mode - - Parameters - ---------- - r_inner : numpy.ndarray - r_outer : numpy.ndarray - time_explosion : float - """ - self.r_inner = r_inner - self.r_outer = r_outer - self.time_explosion = time_explosion - - -numba_plasma_spec = [ - ("electron_density", float64[:]), - ("line_list_nu", float64[:]), - ("tau_sobolev", float64[:, :]), - ("transition_probabilities", float64[:, :]), - ("line2macro_level_upper", int64[:]), - ("macro_block_references", int64[:]), - ("transition_type", int64[:]), - ("destination_level_id", int64[:]), - ("transition_line_id", int64[:]), -] - - -@jitclass(numba_plasma_spec) -class NumbaPlasma(object): - def __init__( - self, - electron_density, - line_list_nu, - tau_sobolev, - transition_probabilities, - line2macro_level_upper, - macro_block_references, - transition_type, - destination_level_id, - transition_line_id, - ): - """ - Plasma for the Numba code - - Parameters - ---------- - electron_density : numpy.ndarray - line_list_nu : numpy.ndarray - tau_sobolev : numpy.ndarray - transition_probabilities : numpy.ndarray - line2macro_level_upper : numpy.ndarray - macro_block_references : numpy.ndarray - transition_type : numpy.ndarray - destination_level_id : numpy.ndarray - transition_line_id : numpy.ndarray - """ - - self.electron_density = electron_density - self.line_list_nu = line_list_nu - self.tau_sobolev = tau_sobolev - - #### Macro Atom transition probabilities - self.transition_probabilities = transition_probabilities - self.line2macro_level_upper = line2macro_level_upper - - self.macro_block_references = macro_block_references - self.transition_type = transition_type - - # Destination level is not needed and/or generated for downbranch - self.destination_level_id = destination_level_id - self.transition_line_id = transition_line_id - - -def numba_plasma_initialize(plasma, line_interaction_type): - """ - Initialize the NumbaPlasma object and copy over the data over from TARDIS Plasma - - Parameters - ---------- - plasma : tardis.plasma.BasePlasma - line_interaction_type : enum - """ - electron_densities = plasma.electron_densities.values - line_list_nu = plasma.atomic_data.lines.nu.values - tau_sobolev = np.ascontiguousarray( - plasma.tau_sobolevs.values.copy(), dtype=np.float64 - ) - if montecarlo_configuration.disable_line_scattering: - tau_sobolev *= 0 - - if line_interaction_type == "scatter": - # to adhere to data types, we must have an array of minimum size 1 - array_size = 1 - transition_probabilities = np.zeros( - (array_size, array_size), dtype=np.float64 - ) # to adhere to data types - line2macro_level_upper = np.zeros(array_size, dtype=np.int64) - macro_block_references = np.zeros(array_size, dtype=np.int64) - transition_type = np.zeros(array_size, dtype=np.int64) - destination_level_id = np.zeros(array_size, dtype=np.int64) - transition_line_id = np.zeros(array_size, dtype=np.int64) - else: - transition_probabilities = np.ascontiguousarray( - plasma.transition_probabilities.values.copy(), dtype=np.float64 - ) - line2macro_level_upper = ( - plasma.atomic_data.lines_upper2macro_reference_idx - ) - macro_block_references = plasma.atomic_data.macro_atom_references[ - "block_references" - ].values - transition_type = plasma.atomic_data.macro_atom_data[ - "transition_type" - ].values - - # Destination level is not needed and/or generated for downbranch - destination_level_id = plasma.atomic_data.macro_atom_data[ - "destination_level_idx" - ].values - transition_line_id = plasma.atomic_data.macro_atom_data[ - "lines_idx" - ].values - - return NumbaPlasma( - electron_densities, - line_list_nu, - tau_sobolev, - transition_probabilities, - line2macro_level_upper, - macro_block_references, - transition_type, - destination_level_id, - transition_line_id, - ) - - -packet_collection_spec = [ - ("packets_input_radius", float64[:]), - ("packets_input_nu", float64[:]), - ("packets_input_mu", float64[:]), - ("packets_input_energy", float64[:]), - ("packets_output_nu", float64[:]), - ("packets_output_energy", float64[:]), -] - - -@jitclass(packet_collection_spec) -class PacketCollection(object): - def __init__( - self, - packets_input_radius, - packets_input_nu, - packets_input_mu, - packets_input_energy, - packets_output_nu, - packets_output_energy, - ): - self.packets_input_radius = packets_input_radius - self.packets_input_nu = packets_input_nu - self.packets_input_mu = packets_input_mu - self.packets_input_energy = packets_input_energy - self.packets_output_nu = packets_output_nu - self.packets_output_energy = packets_output_energy - - -vpacket_collection_spec = [ - ("rpacket_index", int64), - ("spectrum_frequency", float64[:]), - ("v_packet_spawn_start_frequency", float64), - ("v_packet_spawn_end_frequency", float64), - ("nus", float64[:]), - ("energies", float64[:]), - ("initial_mus", float64[:]), - ("initial_rs", float64[:]), - ("idx", int64), - ("number_of_vpackets", int64), - ("length", int64), - ("last_interaction_in_nu", float64[:]), - ("last_interaction_type", int64[:]), - ("last_interaction_in_id", int64[:]), - ("last_interaction_out_id", int64[:]), -] - - -@jitclass(vpacket_collection_spec) -class VPacketCollection(object): - def __init__( - self, - rpacket_index, - spectrum_frequency, - v_packet_spawn_start_frequency, - v_packet_spawn_end_frequency, - number_of_vpackets, - temporary_v_packet_bins, - ): - self.spectrum_frequency = spectrum_frequency - self.v_packet_spawn_start_frequency = v_packet_spawn_start_frequency - self.v_packet_spawn_end_frequency = v_packet_spawn_end_frequency - self.nus = np.empty(temporary_v_packet_bins, dtype=np.float64) - self.energies = np.empty(temporary_v_packet_bins, dtype=np.float64) - self.initial_mus = np.empty(temporary_v_packet_bins, dtype=np.float64) - self.initial_rs = np.empty(temporary_v_packet_bins, dtype=np.float64) - self.number_of_vpackets = number_of_vpackets - self.last_interaction_in_nu = np.zeros( - temporary_v_packet_bins, dtype=np.float64 - ) - self.last_interaction_type = -1 * np.ones( - temporary_v_packet_bins, dtype=np.int64 - ) - self.last_interaction_in_id = -1 * np.ones( - temporary_v_packet_bins, dtype=np.int64 - ) - self.last_interaction_out_id = -1 * np.ones( - temporary_v_packet_bins, dtype=np.int64 - ) - self.idx = 0 - self.rpacket_index = rpacket_index - self.length = temporary_v_packet_bins - - def set_properties( - self, - nu, - energy, - initial_mu, - initial_r, - last_interaction_in_nu, - last_interaction_type, - last_interaction_in_id, - last_interaction_out_id, - ): - if self.idx >= self.length: - temp_length = self.length * 2 + self.number_of_vpackets - temp_nus = np.empty(temp_length, dtype=np.float64) - temp_energies = np.empty(temp_length, dtype=np.float64) - temp_initial_mus = np.empty(temp_length, dtype=np.float64) - temp_initial_rs = np.empty(temp_length, dtype=np.float64) - temp_last_interaction_in_nu = np.empty( - temp_length, dtype=np.float64 - ) - temp_last_interaction_type = np.empty(temp_length, dtype=np.int64) - temp_last_interaction_in_id = np.empty(temp_length, dtype=np.int64) - temp_last_interaction_out_id = np.empty(temp_length, dtype=np.int64) - - temp_nus[: self.length] = self.nus - temp_energies[: self.length] = self.energies - temp_initial_mus[: self.length] = self.initial_mus - temp_initial_rs[: self.length] = self.initial_rs - temp_last_interaction_in_nu[ - : self.length - ] = self.last_interaction_in_nu - temp_last_interaction_type[ - : self.length - ] = self.last_interaction_type - temp_last_interaction_in_id[ - : self.length - ] = self.last_interaction_in_id - temp_last_interaction_out_id[ - : self.length - ] = self.last_interaction_out_id - - self.nus = temp_nus - self.energies = temp_energies - self.initial_mus = temp_initial_mus - self.initial_rs = temp_initial_rs - self.last_interaction_in_nu = temp_last_interaction_in_nu - self.last_interaction_type = temp_last_interaction_type - self.last_interaction_in_id = temp_last_interaction_in_id - self.last_interaction_out_id = temp_last_interaction_out_id - self.length = temp_length - - self.nus[self.idx] = nu - self.energies[self.idx] = energy - self.initial_mus[self.idx] = initial_mu - self.initial_rs[self.idx] = initial_r - self.last_interaction_in_nu[self.idx] = last_interaction_in_nu - self.last_interaction_type[self.idx] = last_interaction_type - self.last_interaction_in_id[self.idx] = last_interaction_in_id - self.last_interaction_out_id[self.idx] = last_interaction_out_id - self.idx += 1 - - -rpacket_collection_spec = [ - ("length", int64), - ("seed", int64), - ("index", int64), - ("status", int64[:]), - ("r", float64[:]), - ("nu", float64[:]), - ("mu", float64[:]), - ("energy", float64[:]), - ("shell_id", int64[:]), - ("interact_id", int64), -] - - -@jitclass(rpacket_collection_spec) -class RPacketTracker(object): - """ - Numba JITCLASS for storing the information for each interaction a RPacket instance undergoes. - - Parameters - ---------- - length : int - Length of the initial array that is instantiated - seed : int - Seed for each RPacket - index : int - Index position of each RPacket - status : int - Current status of the RPacket as per interactions - r : float - Radius of the shell where the RPacket is present - nu : float - Luminosity of the RPacket - mu : float - Cosine of the angle made by the direction of movement of the RPacket from its original direction - energy : float - Energy possessed by the RPacket at a particular shell - shell_id : int - Current Shell No in which the RPacket is present - interact_id : int - Internal counter for the interactions that a particular RPacket undergoes - """ - - def __init__(self): - self.length = montecarlo_configuration.INITIAL_TRACKING_ARRAY_LENGTH - self.seed = np.int64(0) - self.index = np.int64(0) - self.status = np.empty(self.length, dtype=np.int64) - self.r = np.empty(self.length, dtype=np.float64) - self.nu = np.empty(self.length, dtype=np.float64) - self.mu = np.empty(self.length, dtype=np.float64) - self.energy = np.empty(self.length, dtype=np.float64) - self.shell_id = np.empty(self.length, dtype=np.int64) - self.interact_id = 0 - - def track(self, r_packet): - if self.interact_id >= self.length: - temp_length = self.length * 2 - temp_status = np.empty(temp_length, dtype=np.int64) - temp_r = np.empty(temp_length, dtype=np.float64) - temp_nu = np.empty(temp_length, dtype=np.float64) - temp_mu = np.empty(temp_length, dtype=np.float64) - temp_energy = np.empty(temp_length, dtype=np.float64) - temp_shell_id = np.empty(temp_length, dtype=np.int64) - - temp_status[: self.length] = self.status - temp_r[: self.length] = self.r - temp_nu[: self.length] = self.nu - temp_mu[: self.length] = self.mu - temp_energy[: self.length] = self.energy - temp_shell_id[: self.length] = self.shell_id - - self.status = temp_status - self.r = temp_r - self.nu = temp_nu - self.mu = temp_mu - self.energy = temp_energy - self.shell_id = temp_shell_id - self.length = temp_length - - self.index = r_packet.index - self.seed = r_packet.seed - self.status[self.interact_id] = r_packet.status - self.r[self.interact_id] = r_packet.r - self.nu[self.interact_id] = r_packet.nu - self.mu[self.interact_id] = r_packet.mu - self.energy[self.interact_id] = r_packet.energy - self.shell_id[self.interact_id] = r_packet.current_shell_id - self.interact_id += 1 - - def finalize_array(self): - self.status = self.status[: self.interact_id] - self.r = self.r[: self.interact_id] - self.nu = self.nu[: self.interact_id] - self.mu = self.mu[: self.interact_id] - self.energy = self.energy[: self.interact_id] - self.shell_id = self.shell_id[: self.interact_id] - - -estimators_spec = [ - ("j_estimator", float64[:]), - ("nu_bar_estimator", float64[:]), - ("j_blue_estimator", float64[:, :]), - ("Edotlu_estimator", float64[:, :]), -] - - -@jitclass(estimators_spec) -class Estimators(object): - def __init__( - self, j_estimator, nu_bar_estimator, j_blue_estimator, Edotlu_estimator - ): - self.j_estimator = j_estimator - self.nu_bar_estimator = nu_bar_estimator - self.j_blue_estimator = j_blue_estimator - self.Edotlu_estimator = Edotlu_estimator - - -def configuration_initialize(runner, number_of_vpackets): - if runner.line_interaction_type == "macroatom": - montecarlo_configuration.line_interaction_type = ( - LineInteractionType.MACROATOM - ) - elif runner.line_interaction_type == "downbranch": - montecarlo_configuration.line_interaction_type = ( - LineInteractionType.DOWNBRANCH - ) - elif runner.line_interaction_type == "scatter": - montecarlo_configuration.line_interaction_type = ( - LineInteractionType.SCATTER - ) - else: - raise ValueError( - f'Line interaction type must be one of "macroatom",' - f'"downbranch", or "scatter" but is ' - f"{runner.line_interaction_type}" - ) - montecarlo_configuration.number_of_vpackets = number_of_vpackets - montecarlo_configuration.temporary_v_packet_bins = number_of_vpackets - montecarlo_configuration.full_relativity = runner.enable_full_relativity - montecarlo_configuration.montecarlo_seed = runner.seed - montecarlo_configuration.single_packet_seed = runner.single_packet_seed - montecarlo_configuration.v_packet_spawn_start_frequency = ( - runner.virtual_spectrum_spawn_range.end.to( - u.Hz, equivalencies=u.spectral() - ).value - ) - montecarlo_configuration.v_packet_spawn_end_frequency = ( - runner.virtual_spectrum_spawn_range.start.to( - u.Hz, equivalencies=u.spectral() - ).value - ) - montecarlo_configuration.VPACKET_LOGGING = runner.virt_logging - - -# class TrackRPacket(object): -class LineInteractionType(IntEnum): - SCATTER = 0 - DOWNBRANCH = 1 - MACROATOM = 2 diff --git a/tardis/montecarlo/montecarlo_numba/opacities.py b/tardis/montecarlo/montecarlo_numba/opacities.py deleted file mode 100644 index 10812ae2784..00000000000 --- a/tardis/montecarlo/montecarlo_numba/opacities.py +++ /dev/null @@ -1,22 +0,0 @@ -from numba import njit - -from tardis.montecarlo.montecarlo_numba import ( - njit_dict_no_parallel, -) - -from tardis.montecarlo.montecarlo_numba.numba_config import ( - SIGMA_THOMSON, -) - - -@njit(**njit_dict_no_parallel) -def calculate_tau_electron(electron_density, distance): - """ - Calculate tau for Thomson scattering - - Parameters - ---------- - electron_density : float - distance : float - """ - return electron_density * SIGMA_THOMSON * distance diff --git a/tardis/montecarlo/montecarlo_numba/r_packet_transport.py b/tardis/montecarlo/montecarlo_numba/r_packet_transport.py deleted file mode 100644 index 33dd109c8be..00000000000 --- a/tardis/montecarlo/montecarlo_numba/r_packet_transport.py +++ /dev/null @@ -1,242 +0,0 @@ -import numpy as np -from numba import njit - -from tardis.montecarlo import montecarlo_configuration -from tardis.montecarlo.montecarlo_numba import njit_dict_no_parallel -from tardis.montecarlo.montecarlo_numba.calculate_distances import \ - calculate_distance_boundary, calculate_distance_electron, \ - calculate_distance_line -from tardis.montecarlo.montecarlo_numba.estimators import \ - update_line_estimators, set_estimators, set_estimators_full_relativity -from tardis.montecarlo.montecarlo_numba.frame_transformations import \ - get_doppler_factor -from tardis.montecarlo.montecarlo_numba.numba_config import \ - ENABLE_FULL_RELATIVITY -from tardis.montecarlo.montecarlo_numba.opacities import calculate_tau_electron -from tardis.montecarlo.montecarlo_numba.r_packet import InteractionType, \ - PacketStatus - - -@njit(**njit_dict_no_parallel) -def trace_packet(r_packet, numba_model, numba_plasma, estimators): - """ - Traces the RPacket through the ejecta and stops when an interaction happens (heart of the calculation) - - Parameters - ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - numba_model : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaModel - numba_plasma : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaPlasma - estimators : tardis.montecarlo.montecarlo_numba.numba_interface.Estimators - - Returns - ------- - """ - - r_inner = numba_model.r_inner[r_packet.current_shell_id] - r_outer = numba_model.r_outer[r_packet.current_shell_id] - - ( - distance_boundary, - delta_shell, - ) = calculate_distance_boundary(r_packet.r, r_packet.mu, r_inner, r_outer) - - # defining start for line interaction - start_line_id = r_packet.next_line_id - - # defining taus - tau_event = -np.log(np.random.random()) - tau_trace_line_combined = 0.0 - - # e scattering initialization - - cur_electron_density = numba_plasma.electron_density[ - r_packet.current_shell_id - ] - distance_electron = calculate_distance_electron( - cur_electron_density, tau_event - ) - - # Calculating doppler factor - doppler_factor = get_doppler_factor( - r_packet.r, r_packet.mu, numba_model.time_explosion - ) - comov_nu = r_packet.nu * doppler_factor - - cur_line_id = start_line_id # initializing varibale for Numba - # - do not remove - last_line_id = len(numba_plasma.line_list_nu) - 1 - for cur_line_id in range(start_line_id, len(numba_plasma.line_list_nu)): - - # Going through the lines - nu_line = numba_plasma.line_list_nu[cur_line_id] - nu_line_last_interaction = numba_plasma.line_list_nu[cur_line_id - 1] - - # Getting the tau for the next line - tau_trace_line = numba_plasma.tau_sobolev[ - cur_line_id, r_packet.current_shell_id - ] - - # Adding it to the tau_trace_line_combined - tau_trace_line_combined += tau_trace_line - - # Calculating the distance until the current photons co-moving nu - # redshifts to the line frequency - is_last_line = cur_line_id == last_line_id - - distance_trace = calculate_distance_line( - r_packet, - comov_nu, - is_last_line, - nu_line, - numba_model.time_explosion, - ) - - # calculating the tau electron of how far the trace has progressed - tau_trace_electron = calculate_tau_electron( - cur_electron_density, distance_trace - ) - - # calculating the trace - tau_trace_combined = tau_trace_line_combined + tau_trace_electron - - if ( - (distance_boundary <= distance_trace) - and (distance_boundary <= distance_electron) - ) and distance_trace != 0.0: - interaction_type = InteractionType.BOUNDARY # BOUNDARY - r_packet.next_line_id = cur_line_id - distance = distance_boundary - break - - if ( - (distance_electron < distance_trace) - and (distance_electron < distance_boundary) - ) and distance_trace != 0.0: - interaction_type = InteractionType.ESCATTERING - # print('scattering') - distance = distance_electron - r_packet.next_line_id = cur_line_id - break - - # Updating the J_b_lu and E_dot_lu - # This means we are still looking for line interaction and have not - # been kicked out of the path by boundary or electron interaction - - update_line_estimators( - estimators, - r_packet, - cur_line_id, - distance_trace, - numba_model.time_explosion, - ) - - if ( - tau_trace_combined > tau_event - and not montecarlo_configuration.disable_line_scattering - ): - interaction_type = InteractionType.LINE # Line - r_packet.last_interaction_in_nu = r_packet.nu - r_packet.last_line_interaction_in_id = cur_line_id - r_packet.next_line_id = cur_line_id - distance = distance_trace - break - - # Recalculating distance_electron using tau_event - - # tau_trace_line_combined - distance_electron = calculate_distance_electron( - cur_electron_density, tau_event - tau_trace_line_combined - ) - - else: # Executed when no break occurs in the for loop - # We are beyond the line list now and the only next thing is to see - # if we are interacting with the boundary or electron scattering - if cur_line_id == (len(numba_plasma.line_list_nu) - 1): - # Treatment for last line - cur_line_id += 1 - if distance_electron < distance_boundary: - distance = distance_electron - interaction_type = InteractionType.ESCATTERING - # print('scattering') - else: - distance = distance_boundary - interaction_type = InteractionType.BOUNDARY - - # r_packet.next_line_id = cur_line_id - - return distance, interaction_type, delta_shell - - -@njit(**njit_dict_no_parallel) -def move_r_packet(r_packet, distance, time_explosion, numba_estimator): - """ - Move packet a distance and recalculate the new angle mu - - Parameters - ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - r_packet objects - time_explosion : float - time since explosion in s - numba_estimator : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaEstimator - Estimators object - distance : float - distance in cm - """ - - doppler_factor = get_doppler_factor(r_packet.r, r_packet.mu, time_explosion) - - r = r_packet.r - if distance > 0.0: - new_r = np.sqrt( - r * r + distance * distance + 2.0 * r * distance * r_packet.mu - ) - r_packet.mu = (r_packet.mu * r + distance) / new_r - r_packet.r = new_r - - comov_nu = r_packet.nu * doppler_factor - comov_energy = r_packet.energy * doppler_factor - - if not ENABLE_FULL_RELATIVITY: - set_estimators( - r_packet, distance, numba_estimator, comov_nu, comov_energy - ) - - else: - distance = distance * doppler_factor - set_estimators_full_relativity( - r_packet, - distance, - numba_estimator, - comov_nu, - comov_energy, - doppler_factor, - ) - - -@njit(**njit_dict_no_parallel) -def move_packet_across_shell_boundary(packet, delta_shell, no_of_shells): - """ - Move packet across shell boundary - realizing if we are still in the simulation or have - moved out through the inner boundary or outer boundary and updating packet - status. - - Parameters - ---------- - distance : float - distance to move to shell boundary - - delta_shell : int - is +1 if moving outward or -1 if moving inward - - no_of_shells : int - number of shells in TARDIS simulation - """ - next_shell_id = packet.current_shell_id + delta_shell - - if next_shell_id >= no_of_shells: - packet.status = PacketStatus.EMITTED - elif next_shell_id < 0: - packet.status = PacketStatus.REABSORBED - else: - packet.current_shell_id = next_shell_id \ No newline at end of file diff --git a/tardis/montecarlo/montecarlo_numba/single_packet_loop.py b/tardis/montecarlo/montecarlo_numba/single_packet_loop.py deleted file mode 100644 index a1fe4a3aa8a..00000000000 --- a/tardis/montecarlo/montecarlo_numba/single_packet_loop.py +++ /dev/null @@ -1,145 +0,0 @@ -from numba import njit -import numpy as np - -from tardis.montecarlo.montecarlo_numba.r_packet import ( - PacketStatus, -) -from tardis.montecarlo.montecarlo_numba.r_packet_transport import trace_packet, \ - move_r_packet, move_packet_across_shell_boundary - -from tardis.montecarlo.montecarlo_numba.utils import MonteCarloException - -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( - get_inverse_doppler_factor, -) -from tardis.montecarlo.montecarlo_numba.interaction import ( - InteractionType, - thomson_scatter, - line_scatter, -) -from tardis.montecarlo.montecarlo_numba.numba_interface import ( - LineInteractionType, -) -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, -) - -from tardis.montecarlo.montecarlo_numba.vpacket import trace_vpacket_volley - -from tardis import constants as const - -C_SPEED_OF_LIGHT = const.c.to("cm/s").value - - -@njit -def single_packet_loop( - r_packet, - numba_model, - numba_plasma, - estimators, - vpacket_collection, - rpacket_collection, -): - """ - Parameters - ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - numba_model : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaModel - numba_plasma : tardis.montecarlo.montecarlo_numba.numba_interface.NumbaPlasma - estimators : tardis.montecarlo.montecarlo_numba.numba_interface.Estimators - vpacket_collection : tardis.montecarlo.montecarlo_numba.numba_interface.VPacketCollection - rpacket_collection : tardis.montecarlo.montecarlo_numba.numba_interface.RPacketCollection - - Returns - ------- - None - This function does not return anything but changes the r_packet object - and if virtual packets are requested - also updates the vpacket_collection - """ - - line_interaction_type = montecarlo_configuration.line_interaction_type - - if montecarlo_configuration.full_relativity: - set_packet_props_full_relativity(r_packet, numba_model) - else: - set_packet_props_partial_relativity(r_packet, numba_model) - r_packet.initialize_line_id(numba_plasma, numba_model) - - trace_vpacket_volley( - r_packet, vpacket_collection, numba_model, numba_plasma - ) - - if montecarlo_configuration.RPACKET_TRACKING: - rpacket_collection.track(r_packet) - - while r_packet.status == PacketStatus.IN_PROCESS: - distance, interaction_type, delta_shell = trace_packet( - r_packet, numba_model, numba_plasma, estimators - ) - - if interaction_type == InteractionType.BOUNDARY: - move_r_packet( - r_packet, distance, numba_model.time_explosion, estimators - ) - move_packet_across_shell_boundary( - r_packet, delta_shell, len(numba_model.r_inner) - ) - - elif interaction_type == InteractionType.LINE: - r_packet.last_interaction_type = 2 - - move_r_packet( - r_packet, distance, numba_model.time_explosion, estimators - ) - line_scatter( - r_packet, - numba_model.time_explosion, - line_interaction_type, - numba_plasma, - ) - trace_vpacket_volley( - r_packet, vpacket_collection, numba_model, numba_plasma - ) - - elif interaction_type == InteractionType.ESCATTERING: - r_packet.last_interaction_type = 1 - - move_r_packet( - r_packet, distance, numba_model.time_explosion, estimators - ) - thomson_scatter(r_packet, numba_model.time_explosion) - - trace_vpacket_volley( - r_packet, vpacket_collection, numba_model, numba_plasma - ) - - if montecarlo_configuration.RPACKET_TRACKING: - rpacket_collection.track(r_packet) - - # check where else initialize line ID happens! - - -@njit -def set_packet_props_partial_relativity(r_packet, numba_model): - inverse_doppler_factor = get_inverse_doppler_factor( - r_packet.r, - r_packet.mu, - numba_model.time_explosion, - ) - r_packet.nu *= inverse_doppler_factor - r_packet.energy *= inverse_doppler_factor - - -@njit -def set_packet_props_full_relativity(r_packet, numba_model): - beta = (r_packet.r / numba_model.time_explosion) / C_SPEED_OF_LIGHT - - inverse_doppler_factor = get_inverse_doppler_factor( - r_packet.r, - r_packet.mu, - numba_model.time_explosion, - ) - - r_packet.nu *= inverse_doppler_factor - r_packet.energy *= inverse_doppler_factor - r_packet.mu = (r_packet.mu + beta) / (1 + beta * r_packet.mu) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_base.py b/tardis/montecarlo/montecarlo_numba/tests/test_base.py deleted file mode 100644 index 37f097407a9..00000000000 --- a/tardis/montecarlo/montecarlo_numba/tests/test_base.py +++ /dev/null @@ -1,71 +0,0 @@ -import pytest -import pandas as pd -import os -import numpy.testing as npt -from copy import deepcopy - -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, -) -from tardis.simulation import Simulation - - -@pytest.mark.xfail(reason="To be implemented") -def test_montecarlo_radial1d(): - assert False - -def test_montecarlo_main_loop( - config_verysimple, - atomic_dataset, - tardis_ref_path, - tmpdir, - set_seed_fixture, - random_call_fixture, - request -): - - montecarlo_configuration.LEGACY_MODE_ENABLED = True - # Setup model config from verysimple - atomic_data = deepcopy(atomic_dataset) - config_verysimple.montecarlo.last_no_of_packets = 1e5 - config_verysimple.montecarlo.no_of_virtual_packets = 0 - config_verysimple.montecarlo.iterations = 1 - config_verysimple.montecarlo.single_packet_seed = 0 - config_verysimple.plasma.line_interaction_type = 'macroatom' - del config_verysimple["config_dirname"] - - sim = Simulation.from_config(config_verysimple, atom_data=atomic_data) - sim.run() - - - compare_fname = os.path.join(tardis_ref_path, "montecarlo_1e5_compare_data.h5") - if request.config.getoption("--generate-reference"): - sim.to_hdf(compare_fname, overwrite=True) - - # Load compare data from refdata - expected_nu = pd.read_hdf( - compare_fname, key="/simulation/runner/output_nu" - ).values - expected_energy = pd.read_hdf( - compare_fname, key="/simulation/runner/output_energy" - ).values - expected_nu_bar_estimator = pd.read_hdf( - compare_fname, key="/simulation/runner/nu_bar_estimator" - ).values - expected_j_estimator = pd.read_hdf( - compare_fname, key="/simulation/runner/j_estimator" - ).values - - - actual_energy = sim.runner.output_energy - actual_nu = sim.runner.output_nu - actual_nu_bar_estimator = sim.runner.nu_bar_estimator - actual_j_estimator = sim.runner.j_estimator - - # Compare - npt.assert_allclose( - actual_nu_bar_estimator, expected_nu_bar_estimator, rtol=1e-13 - ) - npt.assert_allclose(actual_j_estimator, expected_j_estimator, rtol=1e-13) - npt.assert_allclose(actual_energy.value, expected_energy, rtol=1e-13) - npt.assert_allclose(actual_nu.value, expected_nu, rtol=1e-13) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_macro_atom.py b/tardis/montecarlo/montecarlo_numba/tests/test_macro_atom.py deleted file mode 100644 index d8442be6153..00000000000 --- a/tardis/montecarlo/montecarlo_numba/tests/test_macro_atom.py +++ /dev/null @@ -1,23 +0,0 @@ -import pytest -import tardis.montecarlo.montecarlo_numba.macro_atom as macro_atom -import numpy as np - - -@pytest.mark.parametrize( - ["seed", "expected"], - [(1963, 10015), (1, 9993), (2111963, 17296), (10000, 9993)], -) -def test_macro_atom( - static_packet, - verysimple_numba_plasma, - verysimple_numba_model, - set_seed_fixture, - seed, - expected, -): - set_seed_fixture(seed) - static_packet.initialize_line_id( - verysimple_numba_plasma, verysimple_numba_model - ) - result = macro_atom.macro_atom(static_packet, verysimple_numba_plasma) - assert result == expected diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_vpacket.py b/tardis/montecarlo/montecarlo_numba/tests/test_vpacket.py deleted file mode 100644 index 5ce91a086e8..00000000000 --- a/tardis/montecarlo/montecarlo_numba/tests/test_vpacket.py +++ /dev/null @@ -1,132 +0,0 @@ -import os -import pytest -import numpy as np -import pandas as pd -import tardis.montecarlo.montecarlo_numba.r_packet as r_packet -import tardis.montecarlo.montecarlo_numba.vpacket as vpacket -import tardis.montecarlo.montecarlo_configuration as mc -import tardis.montecarlo.montecarlo_numba.numba_interface as numba_interface -from tardis import constants as const -from tardis.montecarlo.montecarlo_numba.numba_interface import Estimators -from tardis.montecarlo.montecarlo_numba import macro_atom - -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( - get_doppler_factor, -) - -C_SPEED_OF_LIGHT = const.c.to("cm/s").value - -import numpy.testing as npt - - -@pytest.fixture(scope="function") -def v_packet(): - return vpacket.VPacket( - r=7.5e14, - nu=4e15, - mu=0.3, - energy=0.9, - current_shell_id=0, - next_line_id=0, - index=0, - ) - - -def v_packet_initialize_line_id(v_packet, numba_plasma, numba_model): - inverse_line_list_nu = numba_plasma.line_list_nu[::-1] - doppler_factor = get_doppler_factor( - v_packet.r, v_packet.mu, numba_model.time_explosion - ) - comov_nu = v_packet.nu * doppler_factor - next_line_id = len(numba_plasma.line_list_nu) - np.searchsorted( - inverse_line_list_nu, comov_nu - ) - v_packet.next_line_id = next_line_id - - -def test_trace_vpacket_within_shell( - v_packet, verysimple_numba_model, verysimple_numba_plasma -): - # Give the vpacket a reasonable line ID - v_packet_initialize_line_id( - v_packet, verysimple_numba_plasma, verysimple_numba_model - ) - - ( - tau_trace_combined, - distance_boundary, - delta_shell, - ) = vpacket.trace_vpacket_within_shell( - v_packet, verysimple_numba_model, verysimple_numba_plasma - ) - - npt.assert_almost_equal(tau_trace_combined, 8164850.891288479) - npt.assert_almost_equal(distance_boundary, 843684056256104.1) - assert delta_shell == 1 - - -def test_trace_vpacket( - v_packet, verysimple_numba_model, verysimple_numba_plasma -): - # Set seed because of RNG in trace_vpacket - np.random.seed(1) - - # Give the vpacket a reasonable line ID - v_packet_initialize_line_id( - v_packet, verysimple_numba_plasma, verysimple_numba_model - ) - - tau_trace_combined = vpacket.trace_vpacket( - v_packet, verysimple_numba_model, verysimple_numba_plasma - ) - - npt.assert_almost_equal(tau_trace_combined, 8164850.891288479) - npt.assert_almost_equal(v_packet.r, 1286064000000000.0) - npt.assert_almost_equal(v_packet.nu, 4.0e15) - npt.assert_almost_equal(v_packet.energy, 0.0) - npt.assert_almost_equal(v_packet.mu, 0.8309726858508629) - assert v_packet.next_line_id == 2773 - assert v_packet.current_shell_id == 1 - - -# NEEDS TO TEST VPACKET COLLECTION OVERFLOW -@pytest.mark.xfail(reason="Needs to be implemented") -def test_trace_vpacket_volley( - packet, - verysimple_packet_collection, - verysimple_3vpacket_collection, - verysimple_numba_model, - verysimple_numba_plasma, -): - # Set seed because of RNG in trace_vpacket - np.random.seed(1) - - packet.initialize_line_id(verysimple_numba_plasma, verysimple_numba_model) - - vpacket.trace_vpacket_volley( - packet, - verysimple_3vpacket_collection, - verysimple_numba_model, - verysimple_numba_plasma, - ) - - -@pytest.fixture(scope="function") -def broken_packet(): - return vpacket.VPacket( - r=1286064000000000.0, - nu=1660428912896553.2, - mu=0.4916053094346575, - energy=2.474533071386993e-07, - index=3, - current_shell_id=0, - next_line_id=5495, - ) - - -def test_trace_bad_vpacket( - broken_packet, verysimple_numba_model, verysimple_numba_plasma -): - vpacket.trace_vpacket( - broken_packet, verysimple_numba_model, verysimple_numba_plasma - ) diff --git a/tardis/montecarlo/packet_source.py b/tardis/montecarlo/packet_source.py deleted file mode 100644 index d801f3e39bb..00000000000 --- a/tardis/montecarlo/packet_source.py +++ /dev/null @@ -1,141 +0,0 @@ -import abc - -import numpy as np -import numexpr as ne -from tardis import constants as const -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, -) - - -class BasePacketSource(abc.ABC): - def __init__(self, seed): - self.seed = seed - np.random.seed(seed) - - @abc.abstractmethod - def create_packets(self, seed=None, **kwargs): - pass - - @staticmethod - def create_zero_limb_darkening_packet_mus(no_of_packets, rng): - """ - Create zero-limb-darkening packet :math:`\mu` distributed - according to :math:`\\mu=\\sqrt{z}, z \isin [0, 1]` - - Parameters - ---------- - no_of_packets : int - number of packets to be created - """ - - # For testing purposes - if montecarlo_configuration.LEGACY_MODE_ENABLED: - return np.sqrt(np.random.random(no_of_packets)) - else: - return np.sqrt(rng.random(no_of_packets)) - - @staticmethod - def create_uniform_packet_energies(no_of_packets, rng): - """ - Uniformly distribute energy in arbitrary units where the ensemble of - packets has energy of 1. - - Parameters - ---------- - no_of_packets : int - number of packets - - Returns - ------- - energies for packets : numpy.ndarray - """ - return np.ones(no_of_packets) / no_of_packets - - @staticmethod - def create_blackbody_packet_nus(T, no_of_packets, rng, l_samples=1000): - """ - Create packet :math:`\\nu` distributed using the algorithm described in - Bjorkman & Wood 2001 (page 4) which references - Carter & Cashwell 1975: - First, generate a uniform random number, :math:`\\xi_0 \\in [0, 1]` and - determine the minimum value of - :math:`l, l_{\\rm min}`, that satisfies the condition - - .. math:: - \\sum_{i=1}^{l} i^{-4} \\ge {{\\pi^4}\\over{90}} m_0 \\;. - - Next obtain four additional uniform random numbers (in the range 0 - to 1) :math:`\\xi_1, \\xi_2, \\xi_3, {\\rm and } \\xi_4`. - Finally, the packet frequency is given by - - .. math:: - x = -\\ln{(\\xi_1\\xi_2\\xi_3\\xi_4)}/l_{\\rm min}\\;. - - where :math:`x=h\\nu/kT` - - Parameters - ---------- - T : float - temperature - no_of_packets : int - l_samples : int - number of l_samples needed in the algorithm - - Returns - ------- - array of frequencies: numpy.ndarray - """ - l_samples = l_samples - l_array = np.cumsum(np.arange(1, l_samples, dtype=np.float64) ** -4) - l_coef = np.pi ** 4 / 90.0 - - # For testing purposes - if montecarlo_configuration.LEGACY_MODE_ENABLED: - xis = np.random.random((5, no_of_packets)) - else: - xis = rng.random((5, no_of_packets)) - - l = l_array.searchsorted(xis[0] * l_coef) + 1.0 - xis_prod = np.prod(xis[1:], 0) - x = ne.evaluate("-log(xis_prod)/l") - - return x * (const.k_B.cgs.value * T) / const.h.cgs.value - - -class BlackBodySimpleSource(BasePacketSource): - """ - Simple packet source that generates Blackbody packets for the Montecarlo - part. - """ - - def create_packets(self, T, no_of_packets, rng, radius): - """Generate black-body packet properties as arrays - - Parameters - ---------- - T : float64 - Temperature - no_of_packets : int - Number of packets - rng : numpy random number generator - radius : float64 - Initial packet radius - - Returns - ------- - array - Packet radii - array - Packet frequencies - array - Packet directions - array - Packet energies - """ - radii = np.ones(no_of_packets) * radius - nus = self.create_blackbody_packet_nus(T, no_of_packets, rng) - mus = self.create_zero_limb_darkening_packet_mus(no_of_packets, rng) - energies = self.create_uniform_packet_energies(no_of_packets, rng) - - return radii, nus, mus, energies diff --git a/tardis/montecarlo/tests/conftest.py b/tardis/montecarlo/tests/conftest.py deleted file mode 100644 index bad1613fd68..00000000000 --- a/tardis/montecarlo/tests/conftest.py +++ /dev/null @@ -1,13 +0,0 @@ -import os -import pytest -from tardis.io import config_reader -from tardis.montecarlo.base import MontecarloRunner - - -@pytest.fixture(scope="function") -def runner(): - config_fname = "tardis/io/tests/data/tardis_configv1_verysimply.yml" - config = config_reader.Configuration.from_yaml(config_fname) - runner = MontecarloRunner.from_config(config) - return runner - diff --git a/tardis/montecarlo/tests/test_base.py b/tardis/montecarlo/tests/test_base.py deleted file mode 100644 index 7dda40ef237..00000000000 --- a/tardis/montecarlo/tests/test_base.py +++ /dev/null @@ -1,42 +0,0 @@ -import os -import pandas as pd -import numpy as np -import pytest -from astropy import units as u -from numpy.testing import assert_almost_equal - -### -# Save and Load -### - - -@pytest.fixture(scope="module", autouse=True) -def to_hdf_buffer(hdf_file_path, simulation_verysimple): - simulation_verysimple.runner.to_hdf( - hdf_file_path, name="runner", overwrite=True - ) - - -runner_properties = [ - "output_nu", - "output_energy", - "nu_bar_estimator", - "j_estimator", - "montecarlo_virtual_luminosity", - "last_interaction_in_nu", - "last_interaction_type", - "last_line_interaction_in_id", - "last_line_interaction_out_id", - "last_line_interaction_shell_id", - "packet_luminosity", -] - - -@pytest.mark.parametrize("attr", runner_properties) -def test_hdf_runner(hdf_file_path, simulation_verysimple, attr): - actual = getattr(simulation_verysimple.runner, attr) - if hasattr(actual, "cgs"): - actual = actual.cgs.value - path = os.path.join("runner", attr) - expected = pd.read_hdf(hdf_file_path, path) - assert_almost_equal(actual, expected.values) diff --git a/tardis/montecarlo/tests/test_packet_source.py b/tardis/montecarlo/tests/test_packet_source.py deleted file mode 100644 index 6c560fdc1a2..00000000000 --- a/tardis/montecarlo/tests/test_packet_source.py +++ /dev/null @@ -1,38 +0,0 @@ -import os - -import numpy as np -import pandas as pd -import pytest - -import tardis -from tardis.montecarlo.packet_source import BlackBodySimpleSource - - -@pytest.fixture -def data_path(): - return os.path.join(tardis.__path__[0], "montecarlo", "tests", "data") - - -@pytest.fixture -def packet_unit_test_fpath(tardis_ref_path): - return os.path.abspath(os.path.join(tardis_ref_path, "packet_unittest.h5")) - - -def test_bb_packet_sampling(request, tardis_ref_data, packet_unit_test_fpath): - bb = BlackBodySimpleSource(2508) - rng = np.random.default_rng(seed=1963) - # ref_df = pd.read_hdf('test_bb_sampling.h5') - if request.config.getoption("--generate-reference"): - ref_bb = pd.read_hdf(packet_unit_test_fpath, key="/blackbody") - ref_bb.to_hdf( - tardis_ref_data, key="/packet_unittest/blackbody", mode="a" - ) - pytest.skip("Reference data was generated during this run.") - - ref_df = tardis_ref_data["/packet_unittest/blackbody"] - nus = bb.create_blackbody_packet_nus(10000, 100, rng) - mus = bb.create_zero_limb_darkening_packet_mus(100, rng) - unif_energies = bb.create_uniform_packet_energies(100, rng) - assert np.all(np.isclose(nus, ref_df["nus"])) - assert np.all(np.isclose(mus, ref_df["mus"])) - assert np.all(np.isclose(unif_energies, ref_df["energies"])) diff --git a/tardis/opacities/__init__.py b/tardis/opacities/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/opacities/macro_atom/__init__.py b/tardis/opacities/macro_atom/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/opacities/macro_atom/base.py b/tardis/opacities/macro_atom/base.py new file mode 100644 index 00000000000..d23e5473198 --- /dev/null +++ b/tardis/opacities/macro_atom/base.py @@ -0,0 +1,141 @@ +import logging + +import numpy as np +import pandas as pd + +from tardis.opacities.macro_atom import util +from tardis.plasma.properties.base import ProcessingPlasmaProperty + +logger = logging.getLogger(__name__) + + +class TransitionProbabilities(ProcessingPlasmaProperty): + """ + Attributes + ---------- + transition_probabilities : Pandas DataFrame, dtype float + """ + + outputs = ("transition_probabilities",) + + def __init__(self, plasma_parent): + super(TransitionProbabilities, self).__init__(plasma_parent) + self.initialize = True + self.normalize = True + + def calculate( + self, + atomic_data, + beta_sobolev, + j_blues, + stimulated_emission_factor, + tau_sobolevs, + ): + # I wonder why? + # Not sure who wrote this but the answer is that when the plasma is + # first initialised (before the first iteration, without temperature + # values etc.) there are no j_blues values so this just prevents + # an error. Aoife. + if len(j_blues) == 0: + return None + macro_atom_data = self._get_macro_atom_data(atomic_data) + if self.initialize: + self.initialize_macro_atom_transition_type_filters( + atomic_data, macro_atom_data + ) + self.transition_probability_coef = ( + self._get_transition_probability_coefs(macro_atom_data) + ) + self.initialize = False + transition_probabilities = self._calculate_transition_probability( + macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor + ) + transition_probabilities = pd.DataFrame( + transition_probabilities, + index=macro_atom_data.transition_line_id, + columns=tau_sobolevs.columns, + ) + return transition_probabilities + + def _calculate_transition_probability( + self, macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor + ): + transition_probabilities = np.empty( + (self.transition_probability_coef.shape[0], beta_sobolev.shape[1]) + ) + # trans_old = self.calculate_transition_probabilities(macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor) + transition_type = macro_atom_data.transition_type.values + lines_idx = macro_atom_data.lines_idx.values + tpos = macro_atom_data.transition_probability.values + util.fast_calculate_transition_probabilities( + tpos, + beta_sobolev.values, + j_blues.values, + stimulated_emission_factor, + transition_type, + lines_idx, + self.block_references, + transition_probabilities, + self.normalize, + ) + return transition_probabilities + + def calculate_transition_probabilities( + self, macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor + ): + transition_probabilities = self.prepare_transition_probabilities( + macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor + ) + return transition_probabilities + + def initialize_macro_atom_transition_type_filters( + self, atomic_data, macro_atom_data + ): + self.transition_up_filter = macro_atom_data.transition_type.values == 1 + self.transition_up_line_filter = macro_atom_data.lines_idx.values[ + self.transition_up_filter + ] + self.block_references = np.hstack( + ( + atomic_data.macro_atom_references.block_references, + len(macro_atom_data), + ) + ) + + @staticmethod + def _get_transition_probability_coefs(macro_atom_data): + return macro_atom_data.transition_probability.values[np.newaxis].T + + def prepare_transition_probabilities( + self, macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor + ): + current_beta_sobolev = beta_sobolev.values.take( + macro_atom_data.lines_idx.values, axis=0, mode="raise" + ) + transition_probabilities = ( + self.transition_probability_coef * current_beta_sobolev + ) + j_blues = j_blues.take( + self.transition_up_line_filter, axis=0, mode="raise" + ) + macro_stimulated_emission = stimulated_emission_factor.take( + self.transition_up_line_filter, axis=0, mode="raise" + ) + transition_probabilities[self.transition_up_filter] *= ( + j_blues * macro_stimulated_emission + ) + return transition_probabilities + + @staticmethod + def _get_macro_atom_data(atomic_data): + try: + return atomic_data.macro_atom_data + except: + logger.debug( + "Macro Atom Data was not found. Instead returning All Macro Atom Data" + ) + return atomic_data.macro_atom_data_all + + +class NonMarkovChainTransitionProbabilities(TransitionProbabilities): + outputs = ("non_markov_transition_probabilities",) diff --git a/tardis/opacities/macro_atom/transition_probabilities.py b/tardis/opacities/macro_atom/transition_probabilities.py new file mode 100644 index 00000000000..6facd5ee70a --- /dev/null +++ b/tardis/opacities/macro_atom/transition_probabilities.py @@ -0,0 +1,424 @@ +import logging + +import numpy as np +import pandas as pd +from scipy import sparse as sp + +from tardis.plasma.properties.base import ProcessingPlasmaProperty +from tardis.plasma.properties.continuum_processes import ( + get_ground_state_multi_index, +) +from tardis.transport.montecarlo.macro_atom import ( + MacroAtomTransitionType, +) + +__all__ = [ + "MarkovChainTransProbs", + "MarkovChainIndex", + "MarkovChainTransProbsCollector", + "NonContinuumTransProbsMask", + "MonteCarloTransProbs", +] + +logger = logging.getLogger(__name__) + + +def normalize_trans_probs(p): + """ + Normalize a set of transition probabilities. + + Parameters + ---------- + p : pandas.DataFrame, dtype float + Unnormalized transition probabilities. Indexed by + source_level_idx, destination_level_idx. + + Returns + ------- + pandas.DataFrame, dtype float + Normalized transition probabilities: the sum of + all probabilites with the same source_level_idx sum to one. + Indexed by source_level_idx, destination_level_idx. + """ + p = p.astype(np.float64) + p_summed = p.groupby(level=0).sum() + p_summed[p_summed == 0] = 1 + index = p.index.get_level_values("source_level_idx") + p_norm = p / p_summed.loc[index].values + assert np.all(np.isfinite(p_norm)) + return p_norm + + +class SpMatrixSeriesConverterMixin: + @staticmethod + def series2matrix(series, idx2reduced_idx): + """ + Convert a Pandas Series to a sparse matrix and re-index it. + + Parameters + ---------- + series : pandas.Series, dtype float + Rates or transition probabilities. Indexed by + source_level_idx, destination_level_idx. + idx2reduced_idx : pandas.Series + Values of (compact) matrix index. Indexed by references_idx. + Maps the references_idx of a level to the index + used in the sparse matrix. + + Returns + ------- + scipy.sparse.coo.coo_matrix + Sparse matrix of rates or transition probabilites. + """ + q_indices = ( + series.index.get_level_values(0), + series.index.get_level_values(1), + ) + q_indices = ( + idx2reduced_idx.loc[q_indices[0]].values, + idx2reduced_idx.loc[q_indices[1]].values, + ) + max_idx = idx2reduced_idx.max() + 1 + matrix = sp.coo_matrix( + (series.astype(np.float64), q_indices), shape=(max_idx, max_idx) + ) + return matrix + + @staticmethod + def matrix2series(matrix, idx2reduced_idx, names=None): + """ + Convert a sparse matrix to a Pandas Series and index it. + + Parameters + ---------- + matrix : scipy.sparse.coo.coo_matrix + Sparse matrix of rates or transition probabilites. + idx2reduced_idx : pandas.Series + Values of (compact) matrix index. Indexed by references_idx. + Maps the references_idx of a level to the index + used in the sparse matrix. + names : array-like, optional + Names of levels in MultiIndex of returned Series. + + Returns + ------- + pandas.Series + Rates or transition probabilities. Indexed by + source_level_idx, destination_level_idx. + """ + reduced_idx2idx = pd.Series( + idx2reduced_idx.index, index=idx2reduced_idx + ) + matrix = matrix.tocoo() + index = pd.MultiIndex.from_arrays( + [reduced_idx2idx.loc[matrix.row], reduced_idx2idx.loc[matrix.col]] + ) + series = pd.Series(matrix.data, index=index) + if names: + series.index.names = names + return series + + +class MarkovChainIndex(ProcessingPlasmaProperty): + """ + Attributes + ---------- + idx2mkv_idx : pandas.Series, dtype int + k_packet_idx : int + Macro atom level idx corresponding to a k-packet. + idx2deactivation_idx : pandas.Series, dtype int + """ + + outputs = ("idx2mkv_idx", "k_packet_idx", "idx2deactivation_idx") + + def calculate(self, atomic_data, continuum_interaction_species): + ma_ref = atomic_data.macro_atom_references + mask = ma_ref.index.droplevel("source_level_number").isin( + continuum_interaction_species + ) + mask2 = ma_ref.index.isin( + get_ground_state_multi_index(continuum_interaction_species) + ) + mask = np.logical_or(mask, mask2) + idx = ma_ref[mask].references_idx.values + idx2mkv_idx = pd.Series(np.arange(len(idx)), index=idx) + idx2mkv_idx.loc["k"] = idx2mkv_idx.max() + 1 + + k_packet_idx = ma_ref.references_idx.max() + 1 + + idx2deactivation_idx = idx2mkv_idx + k_packet_idx + 1 + return idx2mkv_idx, k_packet_idx, idx2deactivation_idx + + +class NonContinuumTransProbsMask(ProcessingPlasmaProperty): + """ + Attributes + ---------- + non_continuum_trans_probs_mask : numpy.ndarray, dtype bool + """ + + outputs = ("non_continuum_trans_probs_mask",) + + def calculate(self, atomic_data, continuum_interaction_species): + # I don't have to remove the ground states of + # the next higher ionization states of the continuum species + # since they only contain zero probabilities. + continuum_trans_probs_mask = atomic_data.macro_atom_data.set_index( + ["atomic_number", "ion_number"] + ).index.isin(continuum_interaction_species) + non_continuum_trans_probs_mask = np.logical_not( + continuum_trans_probs_mask + ) + return non_continuum_trans_probs_mask + + +class MarkovChainTransProbsCollector(ProcessingPlasmaProperty): + """ + Attributes + ---------- + p_combined : pandas.DataFrame, dtype float + Combined and normalized transition probabilities. + Indexed by source_level_idx, destination_level_idx. + """ + + outputs = ("p_combined",) + + def __init__(self, plasma_parent, inputs): + super().__init__(plasma_parent) + self.inputs = inputs + + def calculate(self, *args): + p = pd.concat(args) + p = p.groupby(level=[0, 1, 2]).sum() + p = normalize_trans_probs(p) + return p + + +class MarkovChainTransProbs( + ProcessingPlasmaProperty, SpMatrixSeriesConverterMixin +): + outputs = ("N", "R", "B", "p_deactivation") + latex_name = ("N", "R", "B", r"p_\textrm{deactivation}") + """ + Attributes + ---------- + N : pandas.DataFrame, dtype float + Fundamental matrix of the Markov-chain macro atom. + Indexed by source_level_idx, destination_level_idx. + Expected number of visits to destination_level_idx starting + from souce_level_idx (before being absorbed). + R : pandas.DataFrame, dtype float + Deactivation probabilities of the Markov-chain macro atom. + Indexed by source_level_idx. + Probability of deactivation/absorption in source_level_idx. + B : pandas.DataFrame, dtype float + Absorbing probabilities of the Markov-chain macro atom. + Indexed by source_level_idx, destination_level_idx. + Probability of being absorbed in destination_level_idx when + starting from source_level_idx. + p_deactivation : pandas.DataFrame, dtype float + Redistribution probabilities after deactivation of the Markov-chain + macro atom. Indexed by source_level_idx, destination_level_idx. + Probability of an r-packet being emitted in the transition + (source_level_idx --> destination_level_idx) after deactivation + in source_level_idx. + """ + + def calculate(self, p_combined, idx2mkv_idx): + p = p_combined + p_internal = p.xs(0, level="transition_type") + p_deactivation = normalize_trans_probs( + p.xs(-1, level="transition_type") + ) + + N = pd.DataFrame(columns=p_internal.columns) + B = pd.DataFrame(columns=p_internal.columns) + R = pd.DataFrame(columns=p_internal.columns, index=idx2mkv_idx.index) + R.index.name = "source_level_idx" + for column in p_internal: + Q = self.series2matrix(p_internal[column], idx2mkv_idx) + inv_N = sp.identity(Q.shape[0]) - Q + N1 = sp.linalg.inv(inv_N.tocsc()) + R1 = (1 - np.asarray(Q.sum(axis=1))).flatten() + B1 = N1.multiply(R1) + N1 = self.matrix2series( + N1, idx2mkv_idx, names=p_internal.index.names + ) + B1 = self.matrix2series( + B1, idx2mkv_idx, names=p_internal.index.names + ) + N[column] = N1 + B[column] = B1 + R[column] = R1 + N = N.sort_index() + B = B.sort_index() + return N, R, B, p_deactivation + + +class MonteCarloTransProbs(ProcessingPlasmaProperty): + outputs = ( + "non_continuum_trans_probs", + "level_absorption_probs", + "deactivation_channel_probs", + "transition_probabilities", + "macro_block_references", + "macro_atom_data", + ) + """ + Attributes + ---------- + non_continuum_trans_probs + level_absorption_probs + deactivation_channel_probs + transition_probabilities + macro_block_references + macro_atom_data + """ + + def calculate( + self, + non_markov_transition_probabilities, + atomic_data, + non_continuum_trans_probs_mask, + k_packet_idx, + idx2deactivation_idx, + level_idxs2transition_idx, + p_deactivation, + cool_rate_fb, + cool_rate_fb_tot, + level2continuum_idx, + B, + ): + # Prepare the transition probabilities for the non continuum species + macro_atom_data = atomic_data.macro_atom_data + transition_info = macro_atom_data[ + ["lines_idx", "transition_type"] + ].set_index(non_markov_transition_probabilities.index) + non_continuum_trans_probs = pd.concat( + [transition_info, non_markov_transition_probabilities], axis=1 + ) + index = macro_atom_data.set_index( + ["source_level_idx", "destination_level_idx"] + ).index + non_continuum_trans_probs = non_continuum_trans_probs.set_index(index) + non_continuum_trans_probs = non_continuum_trans_probs[ + non_continuum_trans_probs_mask + ] + + # Prepare the level absorption probabilities for the continuum species + level_absorption_probs = B.copy() + level_absorption_probs.insert(0, "lines_idx", -1) + level_absorption_probs.insert(0, "transition_type", 3) + destination_level_idx = level_absorption_probs.index.get_level_values( + "destination_level_idx" + ) + source_level_idx = level_absorption_probs.rename( + index={"k": k_packet_idx} + ).index.get_level_values("source_level_idx") + destination_level_idx = idx2deactivation_idx.loc[destination_level_idx] + absorption_index = pd.MultiIndex.from_arrays( + [source_level_idx, destination_level_idx], names=B.index.names + ) + level_absorption_probs.index = absorption_index + + # Prepare the free-bound cooling probabilities + fb_cooling_probs = ( + cool_rate_fb + / cool_rate_fb_tot.values + * p_deactivation.loc[("k"), ("bf")] + ) + continuum_idx = level2continuum_idx.loc[fb_cooling_probs.index].values + fb_cooling_probs.index = pd.MultiIndex.from_product( + [["k"], np.ones(len(fb_cooling_probs), dtype=int) * -1], + names=p_deactivation.index.names, + ) + fb_cooling_probs.insert(0, "lines_idx", continuum_idx) + fb_cooling_probs.insert( + 0, + "transition_type", + level_idxs2transition_idx.at[("k", "bf"), "transition_type"], + ) + + # Check if there are two-photon decays + if "two-photon" in p_deactivation.index.get_level_values(1): + two_photon_index = p_deactivation[ + p_deactivation.index.get_level_values(1) == "two-photon" + ].index + level_idxs2transition_idx_two_photon = pd.DataFrame( + [[-1, MacroAtomTransitionType.TWO_PHOTON.value]], + index=two_photon_index, + columns=level_idxs2transition_idx.columns, + ) + level_idxs2transition_idx = pd.concat( + [ + level_idxs2transition_idx_two_photon, + level_idxs2transition_idx, + ] + ) + + # Prepare the deactivation channel probabilities for the continuum species + deactivation_channel_probs = p_deactivation.copy() + deactivation_channel_probs = pd.concat( + [ + level_idxs2transition_idx.reindex( + deactivation_channel_probs.index + ), + deactivation_channel_probs, + ], + axis=1, + ).reindex(deactivation_channel_probs.index) + + deactivation_channel_probs = deactivation_channel_probs.drop( + ("k", "bf") + ) + deactivation_channel_probs = pd.concat( + [deactivation_channel_probs, fb_cooling_probs], sort=False + ) + + source_level_idx = deactivation_channel_probs.index.get_level_values( + "source_level_idx" + ) + + source_level_idx = idx2deactivation_idx.loc[source_level_idx] + destination_level_idx = np.ones_like(source_level_idx) * -1 + deactivation_index = pd.MultiIndex.from_arrays( + [source_level_idx, destination_level_idx], names=B.index.names + ) + + deactivation_channel_probs.index = deactivation_index + + # Combine everything + combined_trans_probs = pd.concat( + [ + level_absorption_probs, + deactivation_channel_probs, + non_continuum_trans_probs, + ] + ) + combined_trans_probs = combined_trans_probs.sort_index() + + block_references = ( + combined_trans_probs[0].groupby("source_level_idx").count().cumsum() + ) + continous_index = np.arange(block_references.index.max() + 1) + block_references = ( + block_references.reindex(continous_index).ffill().astype(int) + ) # This is needed because some macro atom levels have no transitions + block_references = np.pad(block_references, (1, 0), constant_values=0.0) + + macro_atom_info = combined_trans_probs[ + ["transition_type", "lines_idx"] + ].reset_index() + + combined_trans_probs = combined_trans_probs.drop( + ["lines_idx", "transition_type"], axis="columns" + ) + + return ( + non_continuum_trans_probs, + level_absorption_probs, + deactivation_channel_probs, + combined_trans_probs, + block_references, + macro_atom_info, + ) diff --git a/tardis/plasma/properties/util/macro_atom.py b/tardis/opacities/macro_atom/util.py similarity index 88% rename from tardis/plasma/properties/util/macro_atom.py rename to tardis/opacities/macro_atom/util.py index 68b141fa51a..97eb98f1a64 100644 --- a/tardis/plasma/properties/util/macro_atom.py +++ b/tardis/opacities/macro_atom/util.py @@ -1,16 +1,12 @@ -from numba import njit -from tardis.montecarlo.montecarlo_numba import njit_dict import numpy as np -from tardis import constants as const +from numba import njit -h_cgs = const.h.cgs.value -c = const.c.to("cm/s").value -kb = const.k_B.cgs.value -inv_c2 = 1 / (c ** 2) +from tardis import constants as const +from tardis.transport.montecarlo import njit_dict @njit(**njit_dict) -def calculate_transition_probabilities( +def fast_calculate_transition_probabilities( transition_probability_coef, beta_sobolev, j_blues, @@ -28,7 +24,6 @@ def calculate_transition_probabilities( transition_type, lines_idx, and block_references must be int-type arrays beta_sobolev, j_blues,stimulated_emission_factor, and transition_probabilities must be 2D array """ - norm_factor = np.zeros(transition_probabilities.shape[1]) for i in range(transition_probabilities.shape[0]): @@ -57,5 +52,5 @@ def calculate_transition_probabilities( else: norm_factor[k] = 1.0 for j in range(block_references[i], block_references[i + 1]): - for k in range(0, transition_probabilities.shape[1]): + for k in range(transition_probabilities.shape[1]): transition_probabilities[j, k] *= norm_factor[k] diff --git a/tardis/opacities/opacities.py b/tardis/opacities/opacities.py new file mode 100644 index 00000000000..c917f59294f --- /dev/null +++ b/tardis/opacities/opacities.py @@ -0,0 +1,480 @@ +import numpy as np +import radioactivedecay as rd +from numba import njit + +from tardis import constants as const +from tardis.transport.montecarlo import ( + njit_dict_no_parallel, +) +from tardis.transport.montecarlo.numba_config import ( + SIGMA_THOMSON, +) + +H = const.h.cgs.value +M_E = const.m_e.cgs.value +K_B = const.k_B.cgs.value +E = const.e.esu.value +C = const.c.cgs.value +M_P = const.m_p.cgs.value +MASS_SI = rd.Nuclide("Si-28").atomic_mass * M_P +MASS_FE = rd.Nuclide("Fe-56").atomic_mass * M_P +SIGMA_T = const.sigma_T.cgs.value +FINE_STRUCTURE = const.alpha.value +ELECTRON_MASS_ENERGY_KEV = (const.m_e * const.c**2.0).to("keV").value + +FF_OPAC_CONST = ( + (2 * np.pi / (3 * M_E * K_B)) ** 0.5 * 4 * E**6 / (3 * M_E * H * C) +) # See Eq. 6.1.8 in http://personal.psu.edu/rbc3/A534/lec6.pdf + + +@njit(**njit_dict_no_parallel) +def kappa_calculation(energy): + """ + Calculates kappa for various other calculations + i.e. energy normalized to electron rest energy + 511.0 KeV + + Parameters + ---------- + energy : float + + Returns + ------- + kappa : float + + """ + return energy / ELECTRON_MASS_ENERGY_KEV + + +@njit(**njit_dict_no_parallel) +def chi_electron_calculator(opacity_state, nu, shell): + """ + Calculate chi for Thomson scattering + + Parameters + ---------- + opacity_state : OpacityState + nu : float + Comoving frequency of the r-packet. + shell : int + Shell of current r_packet + + Returns + ------- + numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + """ + return opacity_state.electron_density[shell] * SIGMA_THOMSON + + +@njit(**njit_dict_no_parallel) +def calculate_tau_electron(electron_density, distance): + """ + Calculate tau for Thomson scattering + + Parameters + ---------- + electron_density : float + distance : float + + Returns + ------- + tau_electron : float + tau for thomson scattering + """ + return electron_density * SIGMA_THOMSON * distance + + +@njit(**njit_dict_no_parallel) +def get_current_bound_free_continua(opacity_state, nu): + """ + Determine bound-free continua for which absorption is possible. + + Parameters + ---------- + opacity_state : OpacityState + nu : float + Comoving frequency of the r-packet. + + Returns + ------- + numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + """ + nu_mins = opacity_state.photo_ion_nu_threshold_mins + nu_maxs = opacity_state.photo_ion_nu_threshold_maxs + current_continua = np.where(np.logical_and(nu >= nu_mins, nu <= nu_maxs))[0] + return current_continua + + +@njit(**njit_dict_no_parallel) +def chi_bf_interpolator(opacity_state, nu, shell): + """ + Interpolate the bound-free opacity. + + This function interpolates the tabulated bound-free opacities + and cross-sections to new frequency values `nu`. + + Parameters + ---------- + opacity_state : OpacityState + nu : float, dtype float + Comoving frequency of the r-packet. + shell : int, dtype float + Current computational shell. + + Returns + ------- + chi_bf_tot : float + Total bound-free opacity at frequency `nu`. + chi_bf_contributions : numpy.ndarray, dtype float + Cumulative distribution function of the contributions of the + individual bound free continua to the total bound-free opacity. + current_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + x_sect_bfs : numpy.ndarray, dtype float + Photoionization cross-sections of all bound-free continua for + which absorption is possible for frequency `nu`. + """ + current_continua = get_current_bound_free_continua(opacity_state, nu) + chi_bfs = np.zeros(len(current_continua)) + x_sect_bfs = np.zeros(len(current_continua)) + for i, continuum_id in enumerate(current_continua): + start = opacity_state.photo_ion_block_references[continuum_id] + end = opacity_state.photo_ion_block_references[continuum_id + 1] + phot_nus_continuum = opacity_state.phot_nus[start:end] + nu_idx = np.searchsorted(phot_nus_continuum, nu) + interval = phot_nus_continuum[nu_idx] - phot_nus_continuum[nu_idx - 1] + high_weight = nu - phot_nus_continuum[nu_idx - 1] + low_weight = phot_nus_continuum[nu_idx] - nu + chi_bfs_continuum = opacity_state.chi_bf[start:end, shell] + chi_bfs[i] = ( + chi_bfs_continuum[nu_idx] * high_weight + + chi_bfs_continuum[nu_idx - 1] * low_weight + ) / interval + x_sect_bfs_continuum = opacity_state.x_sect[start:end] + x_sect_bfs[i] = ( + x_sect_bfs_continuum[nu_idx] * high_weight + + x_sect_bfs_continuum[nu_idx - 1] * low_weight + ) / interval + + chi_bf_contributions = chi_bfs.cumsum() + + # If we are outside the range of frequencies + # for which we have photo-ionization cross sections + # we will have no local continuua and therefore + # no bound-free interactions can occur + # so we set the bound free opacity to zero + if len(current_continua) == 0: + chi_bf_tot = 0.0 + else: + chi_bf_tot = chi_bf_contributions[-1] + chi_bf_contributions /= chi_bf_tot + + return ( + chi_bf_tot, + chi_bf_contributions, + current_continua, + x_sect_bfs, + ) + + +@njit(**njit_dict_no_parallel) +def chi_ff_calculator(opacity_state, nu, shell): + """ + Attributes + ---------- + opacity_state : OpacityState + nu : float64 + Comoving frequency of the r_packet + shell : int64 + Current shell id of the r_packet + + Returns + ------- + chi_ff : float64 + Free Free opacity + """ + chi_ff = ( + FF_OPAC_CONST + * opacity_state.ff_opacity_factor[shell] + / nu**3 + * (1 - np.exp(-H * nu / (K_B * opacity_state.t_electrons[shell]))) + ) + return chi_ff + + +@njit(**njit_dict_no_parallel) +def chi_continuum_calculator(opacity_state, nu, shell): + """ + Attributes + ---------- + opacity_state : OpacityState + nu : float64 + Comoving frequency of the r_packet + shell : int64 + Current shell id of the r_packet + + Returns + ------- + chi_bf_tot : float + Total bound-free opacity at frequency `nu`. + chi_bf_contributions : numpy.ndarray, dtype float + Cumulative distribution function of the contributions of the + individual bound free continua to the total bound-free opacity. + current_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + x_sect_bfs : numpy.ndarray, dtype float + Photoionization cross-sections of all bound-free continua for + which absorption is possible for frequency `nu`. + chi_ff : float64 + Free Free opacity at frequency `nu` + """ + ( + chi_bf_tot, + chi_bf_contributions, + current_continua, + x_sect_bfs, + ) = chi_bf_interpolator(opacity_state, nu, shell) + chi_ff = chi_ff_calculator(opacity_state, nu, shell) + return ( + chi_bf_tot, + chi_bf_contributions, + current_continua, + x_sect_bfs, + chi_ff, + ) + + +@njit(**njit_dict_no_parallel) +def compton_opacity_partial(energy, fraction): + """Partial Compton scattering opacity, from artis file + gamma.cc + + Parameters + ---------- + energy : float + packet energy in terms of electron rest energy + fraction : float + 1 + 2 * packet energy + + Returns + ------- + np.float64 + Compton scattering opacity + """ + term_1 = ( + ((energy**2.0) - (2.0 * energy) - 2.0) + * np.log(fraction) + / energy + / energy + ) + term_2 = (((fraction**2.0) - 1.0) / (fraction**2.0)) / 2.0 + term_3 = ((fraction - 1.0) / energy) * ( + (1 / energy) + (2.0 / fraction) + (1.0 / (energy * fraction)) + ) + return 3.0 * SIGMA_T * (term_1 + term_2 + term_3) / (8 * energy) + + +@njit(**njit_dict_no_parallel) +def compton_opacity_calculation(energy, electron_density): + """Calculate the Compton scattering opacity for a given energy + (Rybicki & Lightman, 1979) + + $ + \\rho / 2 p_m \\times 3/4 \\sigma_T ((1 + \\kappa) / \\kappa^3 + ((2\\kappa(1 + \\kappa)) / (1 + 2\\kappa) - \\ln(1 + 2\\kappa) + 1/(2\\kappa) \\ln(1 + 2\\kappa) + - (1 + 3\\kappa) / (1 + 2\\kappa)^2) + $ + + Parameters + ---------- + energy : float + The energy of the photon + ejecta_density : float + The density of the ejecta + + Returns + ------- + float + The Compton scattering opacity + """ + kappa = kappa_calculation(energy) + + a = 1.0 + 2.0 * kappa + + sigma_KN = ( + 3.0 + / 4.0 + * SIGMA_T + * ( + (1.0 + kappa) + / kappa**3.0 + * ((2.0 * kappa * (1.0 + kappa)) / a - np.log(a)) + + 1.0 / (2.0 * kappa) * np.log(a) + - (1.0 + 3 * kappa) / a**2.0 + ) + ) + + return electron_density * sigma_KN + + +@njit(**njit_dict_no_parallel) +def photoabsorption_opacity_calculation( + energy, ejecta_density, iron_group_fraction +): + """Calculates photoabsorption opacity for a given energy + Approximate treatment from Ambwani & Sutherland (1988) + Magic numbers are from the approximate treatment + + Parameters + ---------- + energy : float + Photon energy + ejecta_density : float + The density of the ejecta + iron_group_fraction : float + Fraction of iron group elements in the shell + + Returns + ------- + float + Photoabsorption opacity + """ + si_opacity = ( + 1.16e-24 + * (energy / 100.0) ** -3.13 + * ejecta_density + / MASS_SI + * (1.0 - iron_group_fraction) + ) + + fe_opacity = ( + 25.7e-24 + * (energy / 100.0) ** -3.0 + * ejecta_density + / MASS_FE + * iron_group_fraction + ) + + return si_opacity + fe_opacity + + +@njit(**njit_dict_no_parallel) +def photoabsorption_opacity_calculation_kasen( + energy, number_density, proton_count +): + """Calculates photoabsorption opacity for a given energy + Approximate treatment from Kasen et al. (2006) + + Parameters + ---------- + energy : float + Photon energy + number_density : float + The number density of the ejecta for each atom + proton_count : float + Number of protons for each atom in the ejecta + + Returns + ------- + float + Photoabsorption opacity + """ + kappa = kappa_calculation(energy) + + opacity = (FINE_STRUCTURE**4.0) * 8.0 * np.sqrt(2) * (kappa**-3.5) + # Note- this should actually be atom_number_density * (atom_proton_number ** 5) + return ( + SIGMA_T + * opacity + * np.sum((number_density / proton_count) * proton_count**5) + ) + + +@njit(**njit_dict_no_parallel) +def pair_creation_opacity_calculation( + energy, ejecta_density, iron_group_fraction +): + """Calculates pair creation opacity for a given energy + Approximate treatment from Ambwani & Sutherland (1988) + + Parameters + ---------- + energy : float + Photon energy + ejecta_density : float + The density of the ejecta + iron_group_fraction : float + Fraction of iron group elements in the shell + + Returns + ------- + float + Pair creation opacity + """ + z_si = 14 + z_fe = 26 + + si_proton_ratio = z_si**2.0 / MASS_SI + fe_proton_ratio = z_fe**2.0 / MASS_FE + + multiplier = ejecta_density * ( + si_proton_ratio * (1.0 - iron_group_fraction) + + fe_proton_ratio * iron_group_fraction + ) + + # Conditions prevent divide by zero + # Ambwani & Sutherland (1988) + if energy > 1022 and energy < 1500: + opacity = multiplier * 1.0063 * (energy / 1000 - 1.022) * 1.0e-27 + elif energy >= 1500: + opacity = ( + multiplier * (0.0481 + 0.301 * (energy / 1000 - 1.5)) * 1.0e-27 + ) + else: + opacity = 0 + + return opacity + + +@njit(**njit_dict_no_parallel) +def pair_creation_opacity_artis(energy, ejecta_density, iron_group_fraction): + """Calculates pair creation opacity for a given energy + Approximate treatment from Ambwani & Sutherland (1988) + as implemented in ARTIS + + Parameters + ---------- + energy : float + Photon energy + ejecta_density : float + The density of the ejecta + iron_group_fraction : float + Fraction of iron group elements in the shell + + Returns + ------- + float + Pair creation opacity + """ + # Conditions prevent divide by zero + # Ambwani & Sutherland (1988) + if energy > 1022: + if energy > 1500: + opacity_si = (0.0481 + (0.301 * (energy - 1500))) * 196.0e-27 + opacity_fe = (0.0481 + (0.301 * (energy - 1500))) * 784.0e-27 + else: + opacity_si = 1.0063 * (energy - 1022) * 196.0e-27 + opacity_fe = 1.0063 * (energy - 1022) * 784.0e-27 + + opacity_si *= ejecta_density / M_P / 28 + opacity_fe *= ejecta_density / M_P / 56 + + opacity = (opacity_fe * iron_group_fraction) + ( + opacity_si * (1.0 - iron_group_fraction) + ) + else: + opacity = 0 + + return opacity diff --git a/tardis/opacities/opacity_state.py b/tardis/opacities/opacity_state.py new file mode 100644 index 00000000000..6bfa5e308c0 --- /dev/null +++ b/tardis/opacities/opacity_state.py @@ -0,0 +1,249 @@ +import numpy as np +from numba import float64, int64 +from numba.experimental import jitclass + +from tardis.opacities.tau_sobolev import calculate_sobolev_line_opacity + +opacity_state_spec = [ + ("electron_density", float64[:]), + ("t_electrons", float64[:]), + ("line_list_nu", float64[:]), + ("tau_sobolev", float64[:, :]), + ("transition_probabilities", float64[:, :]), + ("line2macro_level_upper", int64[:]), + ("macro_block_references", int64[:]), + ("transition_type", int64[:]), + ("destination_level_id", int64[:]), + ("transition_line_id", int64[:]), + ("bf_threshold_list_nu", float64[:]), + ("p_fb_deactivation", float64[:, :]), + ("photo_ion_nu_threshold_mins", float64[:]), + ("photo_ion_nu_threshold_maxs", float64[:]), + ("photo_ion_block_references", int64[:]), + ("chi_bf", float64[:, :]), + ("x_sect", float64[:]), + ("phot_nus", float64[:]), + ("ff_opacity_factor", float64[:]), + ("emissivities", float64[:, :]), + ("photo_ion_activation_idx", int64[:]), + ("k_packet_idx", int64), +] + + +@jitclass(opacity_state_spec) +class OpacityState: + def __init__( + self, + electron_density, + t_electrons, + line_list_nu, + tau_sobolev, + transition_probabilities, + line2macro_level_upper, + macro_block_references, + transition_type, + destination_level_id, + transition_line_id, + bf_threshold_list_nu, + p_fb_deactivation, + photo_ion_nu_threshold_mins, + photo_ion_nu_threshold_maxs, + photo_ion_block_references, + chi_bf, + x_sect, + phot_nus, + ff_opacity_factor, + emissivities, + photo_ion_activation_idx, + k_packet_idx, + ): + """ + Plasma for the Numba code + + Parameters + ---------- + electron_density : numpy.ndarray + t_electrons : numpy.ndarray + line_list_nu : numpy.ndarray + tau_sobolev : numpy.ndarray + transition_probabilities : numpy.ndarray + line2macro_level_upper : numpy.ndarray + macro_block_references : numpy.ndarray + transition_type : numpy.ndarray + destination_level_id : numpy.ndarray + transition_line_id : numpy.ndarray + bf_threshold_list_nu : numpy.ndarray + """ + self.electron_density = electron_density + self.t_electrons = t_electrons + self.line_list_nu = line_list_nu + self.tau_sobolev = tau_sobolev + self.bf_threshold_list_nu = bf_threshold_list_nu + + #### Macro Atom transition probabilities + self.transition_probabilities = transition_probabilities + self.line2macro_level_upper = line2macro_level_upper + + self.macro_block_references = macro_block_references + self.transition_type = transition_type + + # Destination level is not needed and/or generated for downbranch + self.destination_level_id = destination_level_id + self.transition_line_id = transition_line_id + self.p_fb_deactivation = p_fb_deactivation + + # Continuum Opacity Data + self.photo_ion_nu_threshold_mins = photo_ion_nu_threshold_mins + self.photo_ion_nu_threshold_maxs = photo_ion_nu_threshold_maxs + + self.photo_ion_block_references = photo_ion_block_references + self.chi_bf = chi_bf + self.x_sect = x_sect + self.phot_nus = phot_nus + self.ff_opacity_factor = ff_opacity_factor + self.emissivities = emissivities + self.photo_ion_activation_idx = photo_ion_activation_idx + self.k_packet_idx = k_packet_idx + + +def opacity_state_initialize( + plasma, + line_interaction_type, + disable_line_scattering, + continuum_processes_enabled, +): + """ + Initialize the OpacityState object and copy over the data over from TARDIS Plasma + + Parameters + ---------- + plasma : tardis.plasma.BasePlasma + line_interaction_type : enum + """ + electron_densities = plasma.electron_densities.values + t_electrons = plasma.t_electrons + line_list_nu = plasma.atomic_data.lines.nu.values + + tau_sobolev_df = calculate_sobolev_line_opacity( + plasma.atomic_data.lines, + plasma.level_number_density, + plasma.time_explosion, + plasma.stimulated_emission_factor, + ) + + tau_sobolev = np.ascontiguousarray(tau_sobolev_df, dtype=np.float64) + + if disable_line_scattering: + tau_sobolev *= 0 + + if line_interaction_type == "scatter": + # to adhere to data types, we must have an array of minimum size 1 + array_size = 1 + transition_probabilities = np.zeros( + (array_size, array_size), dtype=np.float64 + ) # to adhere to data types + line2macro_level_upper = np.zeros(array_size, dtype=np.int64) + macro_block_references = np.zeros(array_size, dtype=np.int64) + transition_type = np.zeros(array_size, dtype=np.int64) + destination_level_id = np.zeros(array_size, dtype=np.int64) + transition_line_id = np.zeros(array_size, dtype=np.int64) + else: + transition_probabilities = np.ascontiguousarray( + plasma.transition_probabilities.values.copy(), dtype=np.float64 + ) + line2macro_level_upper = ( + plasma.atomic_data.lines_upper2macro_reference_idx + ) + # TODO: Fix setting of block references for non-continuum mode + + if continuum_processes_enabled: + macro_block_references = plasma.macro_block_references + else: + macro_block_references = plasma.atomic_data.macro_atom_references[ + "block_references" + ].values + transition_type = plasma.macro_atom_data["transition_type"].values + + # Destination level is not needed and/or generated for downbranch + destination_level_id = plasma.macro_atom_data[ + "destination_level_idx" + ].values + transition_line_id = plasma.macro_atom_data["lines_idx"].values + if continuum_processes_enabled: + bf_threshold_list_nu = plasma.nu_i.loc[ + plasma.level2continuum_idx.index + ].values + p_fb_deactivation = np.ascontiguousarray( + plasma.p_fb_deactivation.values.copy(), dtype=np.float64 + ) + + phot_nus = plasma.photo_ion_cross_sections.nu.loc[ + plasma.level2continuum_idx.index + ] + photo_ion_block_references = np.pad( + phot_nus.groupby(level=[0, 1, 2], sort=False) + .count() + .values.cumsum(), + [1, 0], + ) + photo_ion_nu_threshold_mins = ( + phot_nus.groupby(level=[0, 1, 2], sort=False).first().values + ) + photo_ion_nu_threshold_maxs = ( + phot_nus.groupby(level=[0, 1, 2], sort=False).last().values + ) + + chi_bf = plasma.chi_bf.loc[plasma.level2continuum_idx.index].values + x_sect = plasma.photo_ion_cross_sections.x_sect.loc[ + plasma.level2continuum_idx.index + ].values + + phot_nus = phot_nus.values + ff_opacity_factor = ( + plasma.ff_cooling_factor / np.sqrt(t_electrons) + ).astype(np.float64) + emissivities = plasma.fb_emission_cdf.loc[ + plasma.level2continuum_idx.index + ].values + photo_ion_activation_idx = plasma.photo_ion_idx.loc[ + plasma.level2continuum_idx.index, "destination_level_idx" + ].values + k_packet_idx = np.int64(plasma.k_packet_idx) + else: + bf_threshold_list_nu = np.zeros(0, dtype=np.float64) + p_fb_deactivation = np.zeros((0, 0), dtype=np.float64) + photo_ion_nu_threshold_mins = np.zeros(0, dtype=np.float64) + photo_ion_nu_threshold_maxs = np.zeros(0, dtype=np.float64) + photo_ion_block_references = np.zeros(0, dtype=np.int64) + chi_bf = np.zeros((0, 0), dtype=np.float64) + x_sect = np.zeros(0, dtype=np.float64) + phot_nus = np.zeros(0, dtype=np.float64) + ff_opacity_factor = np.zeros(0, dtype=np.float64) + emissivities = np.zeros((0, 0), dtype=np.float64) + photo_ion_activation_idx = np.zeros(0, dtype=np.int64) + k_packet_idx = np.int64(-1) + + return OpacityState( + electron_densities, + t_electrons, + line_list_nu, + tau_sobolev, + transition_probabilities, + line2macro_level_upper, + macro_block_references, + transition_type, + destination_level_id, + transition_line_id, + bf_threshold_list_nu, + p_fb_deactivation, + photo_ion_nu_threshold_mins, + photo_ion_nu_threshold_maxs, + photo_ion_block_references, + chi_bf, + x_sect, + phot_nus, + ff_opacity_factor, + emissivities, + photo_ion_activation_idx, + k_packet_idx, + ) diff --git a/tardis/opacities/tau_sobolev.py b/tardis/opacities/tau_sobolev.py new file mode 100644 index 00000000000..cf667f9f0ff --- /dev/null +++ b/tardis/opacities/tau_sobolev.py @@ -0,0 +1,170 @@ +import numpy as np +import pandas as pd +from astropy import units as u + +from tardis import constants as const +from tardis.plasma.properties.base import ProcessingPlasmaProperty + +SOBOLEV_COEFFICIENT = ( + ( + ((np.pi * const.e.gauss**2) / (const.m_e.cgs * const.c.cgs)) + * u.cm + * u.s + / u.cm**3 + ) + .to(1) + .value +) + + +def calculate_sobolev_line_opacity( + lines, + level_number_density, + time_explosion, + stimulated_emission_factor, +): + """ + Calculates the Sobolev line opacity based on the provided parameters. + + Parameters + ---------- + lines : pandas.DataFrame + DataFrame containing information about spectral lines. + level_number_density : pandas.DataFrame + DataFrame with level number densities. + time_explosion : astropy.units.Quantity + Time since explosion. + stimulated_emission_factor : float + Factor for stimulated emission. + + Returns + ------- + pandas.DataFrame + Calculated Sobolev line opacity values. + + Raises + ------ + ValueError + If any calculated tau_sobolevs are nan or inf. + + Examples + -------- + >>> calculate_sobolev_line_opacity(lines_data, level_density_data, time_exp, stim_factor) + """ + tau_sobolevs = ( + (lines.wavelength_cm * lines.f_lu).values[np.newaxis].T + * SOBOLEV_COEFFICIENT + * time_explosion.to(u.s).value + * stimulated_emission_factor + * level_number_density.reindex(lines.droplevel(-1).index).values + ) + + if np.any(np.isnan(tau_sobolevs)) or np.any(np.isinf(np.abs(tau_sobolevs))): + raise ValueError( + "Some tau_sobolevs are nan, inf, -inf in tau_sobolevs." + " Something went wrong!" + ) + + return pd.DataFrame( + tau_sobolevs, + index=lines.index, + columns=np.array(level_number_density.columns), + ) + + +class TauSobolev(ProcessingPlasmaProperty): + """ + Attributes + ---------- + tau_sobolev : Pandas DataFrame, dtype float + Sobolev optical depth for each line. Indexed by line. + Columns as zones. + """ + + outputs = ("tau_sobolevs",) + latex_name = (r"\tau_{\textrm{sobolev}}",) + latex_formula = ( + r"\dfrac{\pi e^{2}}{m_{e} c}f_{lu}\lambda t_{exp}\ + n_{lower} \Big(1-\dfrac{g_{lower}n_{upper}}{g_{upper}n_{lower}}\Big)", + ) + + def __init__(self, plasma_parent): + super(TauSobolev, self).__init__(plasma_parent) + self.sobolev_coefficient = ( + ( + ((np.pi * const.e.gauss**2) / (const.m_e.cgs * const.c.cgs)) + * u.cm + * u.s + / u.cm**3 + ) + .to(1) + .value + ) + + def calculate( + self, + lines, + level_number_density, + lines_lower_level_index, + time_explosion, + stimulated_emission_factor, + f_lu, + wavelength_cm, + ): + """ + Calculate Sobolev line opacity. + + Calculates the Sobolev line opacity based on the provided parameters. + + Parameters + ---------- + lines : pandas.DataFrame + DataFrame containing information about spectral lines. + level_number_density : pandas.DataFrame + DataFrame with level number densities. + time_explosion : astropy.units.Quantity + Time since explosion. + stimulated_emission_factor : float + Factor for stimulated emission. + + Returns + ------- + pandas.DataFrame + Calculated Sobolev line opacity values. + + Raises + ------ + ValueError + If any calculated tau_sobolevs are nan or inf. + + Examples + -------- + >>> calculate_sobolev_line_opacity(lines_data, level_density_data, time_exp, stim_factor) + """ + f_lu = f_lu.values[np.newaxis].T + wavelength = wavelength_cm.values[np.newaxis].T + n_lower = level_number_density.values.take( + lines_lower_level_index, axis=0, mode="raise" + ) + tau_sobolevs = ( + self.sobolev_coefficient + * f_lu + * wavelength + * time_explosion + * n_lower + * stimulated_emission_factor + ) + + if np.any(np.isnan(tau_sobolevs)) or np.any( + np.isinf(np.abs(tau_sobolevs)) + ): + raise ValueError( + "Some tau_sobolevs are nan, inf, -inf in tau_sobolevs." + " Something went wrong!" + ) + + return pd.DataFrame( + tau_sobolevs, + index=lines.index, + columns=np.array(level_number_density.columns), + ) diff --git a/tardis/plasma/__init__.py b/tardis/plasma/__init__.py index 67591ed64b5..ec0d4cd7358 100644 --- a/tardis/plasma/__init__.py +++ b/tardis/plasma/__init__.py @@ -1 +1,5 @@ +""" +Dealing with plasma properties and calculations related to it. +""" + from tardis.plasma.base import BasePlasma diff --git a/tardis/plasma/base.py b/tardis/plasma/base.py index ab9632a9336..ef785486673 100644 --- a/tardis/plasma/base.py +++ b/tardis/plasma/base.py @@ -5,7 +5,6 @@ import fileinput import networkx as nx -import pandas as pd from tardis.plasma.exceptions import PlasmaMissingModule, NotInitializedModule from tardis.plasma.properties.base import * @@ -26,7 +25,6 @@ def __init__(self, plasma_properties, property_kwargs=None, **kwargs): plasma_properties, property_kwargs, **kwargs ) self._build_graph() - # self.write_to_tex('Plasma_Graph') self.update(**kwargs) def __getattr__(self, item): @@ -67,7 +65,7 @@ def _build_graph(self): """ self.graph = nx.DiGraph() - ## Adding all nodes + # Adding all nodes self.graph.add_nodes_from( [ (plasma_property.name, {}) @@ -122,8 +120,8 @@ def _init_properties( of arguments that will be passed to the __init__ method of the respective plasma module. kwargs : dictionary - input values for input properties. For example, t_rad=[5000, 6000,], - j_blues=[..] + input values for input properties. For example, + t_rad=[5000, 6000,], j_blues=[..] """ if property_kwargs is None: property_kwargs = {} @@ -264,13 +262,28 @@ def _resolve_update_list(self, changed_properties): descendants_ob.sort(key=lambda val: sort_order.index(val)) logger.debug( - f'Updating modules in the following order: {"->".join(descendants_ob)}' + f"Updating modules in the following order:" + f'{"->".join(descendants_ob)}' ) return descendants_ob - def write_to_dot(self, fname, latex_label=True): - # self._update_module_type_str() + def write_to_dot(self, fname, args=None, latex_label=True): + """ + This method takes the NetworkX Graph generated from the _build_graph + method, converts it into a DOT code, and saves it to a file + + Parameters + ---------- + fname: str + the name of the file the graph will be saved to + args: list + a list of optional settings for displaying the + graph written in DOT format + latex_label: boolean + enables/disables writing LaTeX equations and + edge labels into the file. + """ try: import pygraphviz @@ -281,20 +294,83 @@ def write_to_dot(self, fname, latex_label=True): return print_graph = self.graph.copy() print_graph = self.remove_hidden_properties(print_graph) + for node in print_graph: - print_graph.node[str(node)]["label"] = node - if hasattr(self.plasma_properties_dict[node], "latex_formula"): - formulae = self.plasma_properties_dict[node].latex_formula - for output in range(0, len(formulae)): - formula = formulae[output] - label = formula.replace("\\", "\\\\") - print_graph.node[str(node)]["label"] += "\\n$" - print_graph.node[str(node)]["label"] += label - print_graph.node[str(node)]["label"] += "$" + if latex_label == True: + if hasattr(self.plasma_properties_dict[node], "latex_formula"): + print_graph.nodes[str(node)][ + "label" + ] = f"\\\\textrm{{{node}: }}" + node_list = self.plasma_properties_dict[node] + formulae = node_list.latex_formula + for output in range(0, len(formulae)): + formula = formulae[output] + label = formula.replace("\\", "\\\\") + print_graph.nodes[str(node)]["label"] += label + else: + print_graph.nodes[str(node)][ + "label" + ] = f"\\\\textrm{{{node}}}" + else: + print_graph.nodes[str(node)]["label"] = node + + for edge in print_graph.edges: + label = print_graph.edges[edge]["label"] + print_graph.edges[edge]["label"] = " " + if latex_label == True: + print_graph.edges[edge]["texlbl"] = label nx.drawing.nx_agraph.write_dot(print_graph, fname) - def write_to_tex(self, fname_graph): + for line in fileinput.FileInput(fname, inplace=1): + if latex_label == True: + print( + line.replace( + r'node [label="\N"]', + r'node [texmode="math"]', + ), + end="", + ) + else: + print( + line.replace( + r'node [label="\N"];', + "", + ), + end="", + ) + + if args is not None: + with open(fname, "r") as file: + lines = file.readlines() + + for newline in args: + lines.insert(1, f"\t{newline};\n") + + with open(fname, "w") as f: + lines = "".join(lines) + f.write(lines) + + def write_to_tex(self, fname_graph, scale=0.5, args=None, latex_label=True): + """ + This method takes the NetworkX Graph generated from the _build_graph + method, converts it into a LaTeX friendly format, + and saves it to a file + + Parameters + ---------- + fname_graph: str + the name of the file the graph will be saved to + args: list + a list of optional settings for displaying the + graph written in DOT format + scale: float + a scaling factor to expand/contract the generated + graph + latex_label: boolean + enables/disables writing LaTeX equations and + edge labels into the file. + """ try: import dot2tex except: @@ -305,11 +381,17 @@ def write_to_tex(self, fname_graph): temp_fname = tempfile.NamedTemporaryFile().name - self.write_to_dot(temp_fname) + self.write_to_dot(temp_fname, args=args, latex_label=latex_label) + + with open(temp_fname, "r") as file: + dot_string = file.read().replace("\\\\", "\\") - dot_string = open(temp_fname).read() + texcode = dot2tex.dot2tex( + dot_string, format="tikz", crop=True, valignmode="dot" + ) - open(fname_graph, "w").write(dot2tex.dot2tex(dot_string, texmode="raw")) + with open(fname_graph, "w") as file: + file.write(texcode) for line in fileinput.input(fname_graph, inplace=1): print( @@ -323,6 +405,17 @@ def write_to_tex(self, fname_graph): for line in fileinput.input(fname_graph, inplace=1): print(line.replace(r"\enlargethispage{100cm}", ""), end="") + for line in fileinput.input(fname_graph, inplace=1): + print( + line.replace( + r"\begin{tikzpicture}[>=latex',line join=bevel,]", + r"\begin{tikzpicture}" + r"[>=latex',line join=bevel," + rf"scale={scale}]", + ), + end="", + ) + def remove_hidden_properties(self, print_graph): for item in self.plasma_properties_dict.values(): module = self.plasma_properties_dict[item.name].__class__ diff --git a/tardis/plasma/properties/__init__.py b/tardis/plasma/properties/__init__.py index dc9de8f556b..63d473f01f9 100644 --- a/tardis/plasma/properties/__init__.py +++ b/tardis/plasma/properties/__init__.py @@ -1,11 +1,21 @@ +""" +Store and calculate the properties of the plasma. + +Each plasma object has an array of properties which are then used to calculate plasma parameter values. +Every property has a calculate function that returns the values of its outputs. +""" + +from tardis.opacities.macro_atom.transition_probabilities import * from tardis.plasma.properties.atomic import * +from tardis.plasma.properties.continuum_processes import * from tardis.plasma.properties.general import * +from tardis.plasma.properties.helium_nlte import * from tardis.plasma.properties.ion_population import * +from tardis.plasma.properties.j_blues import * from tardis.plasma.properties.level_population import * +from tardis.plasma.properties.nlte import * +from tardis.plasma.properties.nlte_rate_equation_solver import * from tardis.plasma.properties.partition_function import * from tardis.plasma.properties.plasma_input import * from tardis.plasma.properties.radiative_properties import * -from tardis.plasma.properties.nlte import * -from tardis.plasma.properties.j_blues import * -from tardis.plasma.properties.continuum_processes import * -from tardis.plasma.properties.transition_probabilities import * +from tardis.plasma.properties.rate_matrix_index import * diff --git a/tardis/plasma/properties/atomic.py b/tardis/plasma/properties/atomic.py index 5c2033ebdf5..72fd4b6b472 100644 --- a/tardis/plasma/properties/atomic.py +++ b/tardis/plasma/properties/atomic.py @@ -1,26 +1,27 @@ import logging +from collections import Counter as counter import numpy as np import pandas as pd -from scipy.special import expn +import radioactivedecay as rd +from numba import njit from scipy.interpolate import PchipInterpolator -from collections import Counter as counter -from tardis import constants as const +from scipy.special import exp1 +from tardis import constants as const +from tardis.plasma.exceptions import IncompleteAtomicData from tardis.plasma.properties.base import ( - ProcessingPlasmaProperty, - HiddenPlasmaProperty, BaseAtomicDataProperty, + HiddenPlasmaProperty, + ProcessingPlasmaProperty, ) -from tardis.plasma.exceptions import IncompleteAtomicData from tardis.plasma.properties.continuum_processes import ( - get_ground_state_multi_index, - K_B, - BETA_COLL, - H, A0, + BETA_COLL, + K_B, M_E, - C, + H, + get_ground_state_multi_index, ) logger = logging.getLogger(__name__) @@ -30,15 +31,17 @@ "Lines", "LinesLowerLevelIndex", "LinesUpperLevelIndex", - "AtomicMass", "IonizationData", "ZetaData", "NLTEData", + "MacroAtomData", "PhotoIonizationData", "YgData", "YgInterpolator", "LevelIdxs2LineIdx", + "LevelIdxs2TransitionIdx", "TwoPhotonData", + "ContinuumInteractionHandler", ] @@ -68,12 +71,9 @@ class Levels(BaseAtomicDataProperty): ) def _filter_atomic_property(self, levels, selected_atoms): - return levels - # return levels[levels.atomic_number.isin(selected_atoms)] + return levels[levels.index.isin(selected_atoms, level="atomic_number")] def _set_index(self, levels): - # levels = levels.set_index(['atomic_number', 'ion_number', - # 'level_number']) return ( levels.index, levels["energy"], @@ -101,6 +101,13 @@ class Lines(BaseAtomicDataProperty): # Would like for lines to just be the line_id values outputs = ("lines", "nu", "f_lu", "wavelength_cm") + latex_name = ( + r"\textrm{lines}", + r"\nu", + r"f_lu", + r"\lambda_{cm}", + ) + def _filter_atomic_property(self, lines, selected_atoms): # return lines[lines.atomic_number.isin(selected_atoms)] return lines @@ -110,6 +117,16 @@ def _set_index(self, lines): return lines, lines["nu"], lines["f_lu"], lines["wavelength_cm"] +class MacroAtomData(BaseAtomicDataProperty): + outputs = ("macro_atom_data",) + + def _filter_atomic_property(self, macro_atom_data, selected_atoms): + return macro_atom_data + + def _set_index(self, macro_atom_data): + return macro_atom_data + + class PhotoIonizationData(ProcessingPlasmaProperty): """ Attributes @@ -132,6 +149,8 @@ class PhotoIonizationData(ProcessingPlasmaProperty): Maps a level MultiIndex (atomic_number, ion_number, level_number) to the continuum_idx of the corresponding bound-free continuum (which are sorted by decreasing frequency). + level_idxs2continuum_idx : pandas.DataFrame, dtype int + Maps a source_level_idx destination_level_idx pair to a continuum_idx. """ outputs = ( @@ -142,6 +161,7 @@ class PhotoIonizationData(ProcessingPlasmaProperty): "energy_i", "photo_ion_idx", "level2continuum_idx", + "level_idxs2continuum_idx", ) latex_name = ( r"\xi_{\textrm{i}}(\nu)", @@ -150,12 +170,14 @@ class PhotoIonizationData(ProcessingPlasmaProperty): r"\nu_i", r"\epsilon_i", "", + "", ) def calculate(self, atomic_data, continuum_interaction_species): - photoionization_data = atomic_data.photoionization_data.set_index( - ["atomic_number", "ion_number", "level_number"] - ) + # photoionization_data = atomic_data.photoionization_data.set_index( + # ["atomic_number", "ion_number", "level_number"] + # ) + photoionization_data = atomic_data.photoionization_data mask_selected_species = photoionization_data.index.droplevel( "level_number" ).isin(continuum_interaction_species) @@ -187,6 +209,12 @@ def calculate(self, atomic_data, continuum_interaction_species): nu_i.sort_values(ascending=False).index, name="continuum_idx", ) + + level_idxs2continuum_idx = photo_ion_idx.copy() + level_idxs2continuum_idx["continuum_idx"] = level2continuum_edge_idx + level_idxs2continuum_idx = level_idxs2continuum_idx.set_index( + ["source_level_idx", "destination_level_idx"] + ) return ( photoionization_data, block_references, @@ -195,6 +223,134 @@ def calculate(self, atomic_data, continuum_interaction_species): energy_i, photo_ion_idx, level2continuum_edge_idx, + level_idxs2continuum_idx, + ) + + +class ContinuumInteractionHandler(ProcessingPlasmaProperty): + outputs = ( + "get_current_bound_free_continua", + "determine_bf_macro_activation_idx", + "determine_continuum_macro_activation_idx", + ) + + def calculate( + self, + photo_ion_cross_sections, + level2continuum_idx, + photo_ion_idx, + k_packet_idx, + ): + nus = photo_ion_cross_sections.nu.loc[ + level2continuum_idx.index + ] # Sort by descending frequency + nu_mins = nus.groupby(level=[0, 1, 2], sort=False).first().values + nu_maxs = nus.groupby(level=[0, 1, 2], sort=False).last().values + + @njit(error_model="numpy", fastmath=True) + def get_current_bound_free_continua(nu): + """ + Determine bound-free continua for which absorption is possible. + + Parameters + ---------- + nu : float + Comoving frequency of the r-packet. + + Returns + ------- + numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + """ + # searchsorted would be faster but would need stricter format for photoionization data + current_continua = np.where( + np.logical_and(nu >= nu_mins, nu <= nu_maxs) + )[0] + return current_continua + + destination_level_idxs = photo_ion_idx.loc[ + level2continuum_idx.index, "destination_level_idx" + ].values + + @njit(error_model="numpy", fastmath=True) + def determine_bf_macro_activation_idx( + nu, chi_bf_contributions, active_continua + ): + """ + Determine the macro atom activation level after bound-free absorption. + + Parameters + ---------- + nu : float + Comoving frequency of the r-packet. + chi_bf_contributions : numpy.ndarray, dtype float + Cumulative distribution of bound-free opacities at frequency + `nu`. + active_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + + Returns + ------- + float + Macro atom activation idx. + """ + # Perform a MC experiment to determine the continuum for absorption + index = np.searchsorted(chi_bf_contributions, np.random.random()) + continuum_id = active_continua[index] + + # Perform a MC experiment to determine whether thermal or + # ionization energy is created + nu_threshold = nu_mins[continuum_id] + fraction_ionization = nu_threshold / nu + if ( + np.random.random() < fraction_ionization + ): # Create ionization energy (i-packet) + destination_level_idx = destination_level_idxs[continuum_id] + else: # Create thermal energy (k-packet) + destination_level_idx = k_packet_idx + return destination_level_idx + + @njit(error_model="numpy", fastmath=True) + def determine_continuum_macro_activation_idx( + nu, chi_bf, chi_ff, chi_bf_contributions, active_continua + ): + """ + Determine the macro atom activation level after a continuum absorption. + + Parameters + ---------- + nu : float + Comoving frequency of the r-packet. + chi_bf : numpy.ndarray, dtype float + Bound-free opacity. + chi_bf : numpy.ndarray, dtype float + Free-free opacity. + chi_bf_contributions : numpy.ndarray, dtype float + Cumulative distribution of bound-free opacities at frequency + `nu`. + active_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + + Returns + ------- + float + Macro atom activation idx. + """ + fraction_bf = chi_bf / (chi_bf + chi_ff) + # TODO: In principle, we can also decide here whether a Thomson + # scattering event happens and need one less RNG call. + if np.random.random() < fraction_bf: # Bound-free absorption + destination_level_idx = determine_bf_macro_activation_idx( + nu, chi_bf_contributions, active_continua + ) + else: # Free-free absorption (i.e. k-packet creation) + destination_level_idx = k_packet_idx + return destination_level_idx + + return ( + get_current_bound_free_continua, + determine_bf_macro_activation_idx, + determine_continuum_macro_activation_idx, ) @@ -241,6 +397,11 @@ def calculate(self, atomic_data, continuum_interaction_species): }, index=two_photon_data.index, ) + if len(two_photon_data) != 1: + raise NotImplementedError( + "Currently only one two-photon decay is supported but there " + f"are {len(two_photon_data)} in the atomic data." + ) return two_photon_data, two_photon_idx @@ -293,32 +454,87 @@ class LevelIdxs2LineIdx(HiddenPlasmaProperty): def calculate(self, atomic_data): index = pd.MultiIndex.from_arrays( [ - atomic_data.lines_upper2level_idx, - atomic_data.lines_lower2level_idx, + atomic_data.lines_upper2macro_reference_idx, + atomic_data.lines_lower2macro_reference_idx, ], names=["source_level_idx", "destination_level_idx"], ) level_idxs2line_idx = pd.Series( np.arange(len(index)), index=index, name="lines_idx" ) + + # Check for duplicate indices + if level_idxs2line_idx.index.duplicated().any(): + logger.warning( + "Duplicate indices in level_idxs2line_idx. " + "Dropping duplicates. " + "This is an issue with the atomic data & carsus. " + "Once fixed upstream, this warning will be removed. " + "This will raise an error in the future instead. " + "See https://github.com/tardis-sn/carsus/issues/384" + ) + # This is necessary since pd.DataFrame.drop_duplicates() + # does not remove duplicates if the data is different + # and only the index is duplicated. See the example given + # in the pandas documentation: + # https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.drop_duplicates.html + level_idxs2line_idx = level_idxs2line_idx[ + ~level_idxs2line_idx.index.duplicated() + ] + return level_idxs2line_idx -class AtomicMass(ProcessingPlasmaProperty): +class LevelIdxs2TransitionIdx(HiddenPlasmaProperty): """ Attributes ---------- - atomic_mass : pandas.Series - Atomic masses of the elements used. Indexed by atomic number. + level_idxs2transition_idx : pandas.DataFrame, dtype int + Maps a source_level_idx destination_level_idx pair to a transition_idx + and transition type. """ - outputs = ("atomic_mass",) + outputs = ("level_idxs2transition_idx",) - def calculate(self, atomic_data, selected_atoms): - if getattr(self, self.outputs[0]) is not None: - return (getattr(self, self.outputs[0]),) - else: - return atomic_data.atom_data.loc[selected_atoms].mass + def calculate(self, level_idxs2line_idx, level_idxs2continuum_idx): + level_idxs2line_idx = level_idxs2line_idx.to_frame() + level_idxs2line_idx.insert(1, "transition_type", -1) + + level_idxs2continuum_idx = level_idxs2continuum_idx.copy() + level_idxs2continuum_idx.insert(1, "transition_type", -2) + level_idxs2continuum_idx = level_idxs2continuum_idx.rename( + columns=({"continuum_idx": "lines_idx"}) + ) + + names = level_idxs2continuum_idx.index.names + level_idxs2continuum_idx = level_idxs2continuum_idx.swaplevel() + level_idxs2continuum_idx.index.names = names + + # TODO: This should probably be defined somewhere else. + # One possibility would be to attach it to the cooling properties as + # a class attribute. + index_cooling = pd.MultiIndex.from_product( + [["k"], ["ff", "adiabatic", "bf"]], names=names + ) + num_cool = len(index_cooling) + level_idxs2cooling_idx = pd.DataFrame( + { + "lines_idx": np.ones(num_cool, dtype=int) * -1, + "transition_type": np.arange(-3, -3 - num_cool, -1), + }, + index=index_cooling, + ) + level_idxs2transition_idx = pd.concat( + [ + level_idxs2continuum_idx, + level_idxs2line_idx, + level_idxs2cooling_idx, + ] + ) + + # TODO: Add two-photon processes + + return level_idxs2transition_idx class IonizationData(BaseAtomicDataProperty): @@ -337,7 +553,7 @@ def _filter_atomic_property(self, ionization_data, selected_atoms): ionization_data = ionization_data[mask] counts = ionization_data.groupby(level="atomic_number").count() - if np.alltrue(counts.index == counts): + if np.all(counts.index == counts): return ionization_data else: raise IncompleteAtomicData( @@ -368,7 +584,7 @@ def _filter_atomic_property(self, zeta_data, selected_atoms): zeta_data_check = counter(zeta_data.atomic_number.values) keys = np.array(list(zeta_data_check.keys())) values = np.array(zeta_data_check.values()) - if np.alltrue(keys + 1 == values): + if np.all(keys + 1 == values) and keys: return zeta_data else: # raise IncompleteAtomicData('zeta data') @@ -382,7 +598,7 @@ def _filter_atomic_property(self, zeta_data, selected_atoms): if (atom, ion) not in zeta_data.index: missing_ions.append((atom, ion)) updated_index.append([atom, ion]) - logger.warn( + logger.warning( f"Zeta_data missing - replaced with 1s. Missing ions: {missing_ions}" ) updated_index = np.array(updated_index) @@ -458,13 +674,17 @@ class YgData(ProcessingPlasmaProperty): def calculate(self, atomic_data, continuum_interaction_species): yg_data = atomic_data.yg_data + if yg_data is None: + raise ValueError( + "Tardis does not support continuum interactions for atomic data sources that do not contain yg_data" + ) mask_selected_species = yg_data.index.droplevel( ["level_number_lower", "level_number_upper"] ).isin(continuum_interaction_species) yg_data = yg_data[mask_selected_species] - t_yg = yg_data.columns.values.astype(float) + t_yg = atomic_data.collision_data_temperatures yg_data.columns = t_yg approximate_yg_data = self.calculate_yg_van_regemorter( atomic_data, t_yg, continuum_interaction_species @@ -494,9 +714,9 @@ def calculate(self, atomic_data, continuum_interaction_species): ) return yg_data, t_yg, index, delta_E, yg_idx - @staticmethod + @classmethod def calculate_yg_van_regemorter( - atomic_data, t_electrons, continuum_interaction_species + cls, atomic_data, t_electrons, continuum_interaction_species ): """ Calculate collision strengths in the van Regemorter approximation. @@ -538,17 +758,41 @@ def calculate_yg_van_regemorter( nu_lines = lines_filtered.nu.values yg = f_lu * (I_H / (H * nu_lines)) ** 2 - coll_const = A0 ** 2 * np.pi * np.sqrt(8 * K_B / (np.pi * M_E)) + coll_const = A0**2 * np.pi * np.sqrt(8 * K_B / (np.pi * M_E)) yg = 14.5 * coll_const * t_electrons * yg[:, np.newaxis] u0 = nu_lines[np.newaxis].T / t_electrons * (H / K_B) - gamma = 0.276 * np.exp(u0) * expn(1, u0) + gamma = 0.276 * cls.exp1_times_exp(u0) gamma[gamma < 0.2] = 0.2 yg *= u0 * gamma / BETA_COLL yg = pd.DataFrame(yg, index=lines_filtered.index, columns=t_electrons) return yg + @staticmethod + def exp1_times_exp(x): + """ + Product of the Exponential integral E1 and an exponential. + + This function calculates the product of the Exponential integral E1 + and an exponential in a way that also works for large values. + + Parameters + ---------- + x : array_like + Input values. + + Returns + ------- + array_like + Output array. + """ + f = exp1(x) * np.exp(x) + # Use Laurent series for large values to avoid infinite exponential + mask = x > 500 + f[mask] = (x**-1 - x**-2 + 2 * x**-3 - 6 * x**-4)[mask] + return f + class YgInterpolator(ProcessingPlasmaProperty): """ diff --git a/tardis/plasma/properties/continuum_processes.py b/tardis/plasma/properties/continuum_processes.py index abb780a3bc6..06121cc4e20 100644 --- a/tardis/plasma/properties/continuum_processes.py +++ b/tardis/plasma/properties/continuum_processes.py @@ -2,14 +2,18 @@ import numpy as np import pandas as pd +from numba import njit, prange -from numba import prange, njit from tardis import constants as const - +from tardis.transport.montecarlo.estimators.util import ( + bound_free_estimator_array2frame, + integrate_array_by_blocks, +) +from tardis.transport.montecarlo import njit_dict from tardis.plasma.exceptions import PlasmaException from tardis.plasma.properties.base import ( - ProcessingPlasmaProperty, Input, + ProcessingPlasmaProperty, TransitionProbabilitiesProperty, ) from tardis.plasma.properties.j_blues import JBluesDiluteBlackBody @@ -23,6 +27,7 @@ "StimRecombRateCoeffEstimator", "CorrPhotoIonRateCoeff", "BfHeatingRateCoeffEstimator", + "StimRecombCoolingRateCoeffEstimator", "SpontRecombCoolingRateCoeff", "RawRecombTransProbs", "RawPhotoIonTransProbs", @@ -38,55 +43,32 @@ "FreeBoundEmissionCDF", "RawTwoPhotonTransProbs", "TwoPhotonEmissionCDF", + "TwoPhotonFrequencySampler", "CollIonRateCoeffSeaton", "CollRecombRateCoeff", "RawCollIonTransProbs", ] - +N_A = const.N_A.cgs.value K_B = const.k_B.cgs.value C = const.c.cgs.value H = const.h.cgs.value A0 = const.a0.cgs.value M_E = const.m_e.cgs.value -BETA_COLL = (H ** 4 / (8 * K_B * M_E ** 3 * np.pi ** 3)) ** 0.5 - +E = const.e.esu.value +BETA_COLL = (H**4 / (8 * K_B * M_E**3 * np.pi**3)) ** 0.5 +F_K = ( + 16 + / (3.0 * np.sqrt(3)) + * np.sqrt((2 * np.pi) ** 3 * K_B / (H**2 * M_E**3)) + * (E**2 / C) ** 3 +) # See Eq. 19 in Sutherland, R. S. 1998, MNRAS, 300, 321 +FF_OPAC_CONST = ( + (2 * np.pi / (3 * M_E * K_B)) ** 0.5 * 4 * E**6 / (3 * M_E * H * C) +) # See Eq. 6.1.8 in http://personal.psu.edu/rbc3/A534/lec6.pdf logger = logging.getLogger(__name__) -njit_dict = {"fastmath": False, "parallel": False} - - -@njit(**njit_dict) -def integrate_array_by_blocks(f, x, block_references): - """ - Integrate a function over blocks. - - This function integrates a function `f` defined at locations `x` - over blocks given in `block_references`. - - Parameters - ---------- - f : numpy.ndarray, dtype float - 2D input array to integrate. - x : numpy.ndarray, dtype float - 1D array with the sample points corresponding to the `f` values. - block_references : numpy.ndarray, dtype int - 1D array with the start indices of the blocks to be integrated. - - Returns - ------- - numpy.ndarray, dtype float - 2D array with integrated values. - """ - integrated = np.zeros((len(block_references) - 1, f.shape[1])) - for i in prange(f.shape[1]): # columns - for j in prange(len(integrated)): # rows - start = block_references[j] - stop = block_references[j + 1] - integrated[j, i] = np.trapz(f[start:stop, i], x[start:stop]) - return integrated - # It is currently not possible to use scipy.integrate.cumulative_trapezoid in # numba. So here is my own implementation. @@ -229,7 +211,7 @@ def cooling_rate_series2dataframe(cooling_rate_series, destination_level_idx): return cooling_rate_frame -class IndexSetterMixin(object): +class IndexSetterMixin: @staticmethod def set_index(p, photo_ion_idx, transition_type=0, reverse=True): idx = photo_ion_idx.loc[p.index] @@ -271,7 +253,7 @@ def calculate( x_sect = photo_ion_cross_sections["x_sect"].values nu = photo_ion_cross_sections["nu"].values - alpha_sp = 8 * np.pi * x_sect * nu ** 2 / C ** 2 + alpha_sp = 8 * np.pi * x_sect * nu**2 / C**2 alpha_sp = alpha_sp[:, np.newaxis] alpha_sp = alpha_sp * boltzmann_factor_photo_ion alpha_sp = integrate_array_by_blocks( @@ -306,7 +288,7 @@ def calculate( x_sect = photo_ion_cross_sections["x_sect"].values nu = photo_ion_cross_sections["nu"].values factor = (1 - nu_i / photo_ion_cross_sections["nu"]).values - alpha_sp = (8 * np.pi * x_sect * factor * nu ** 3 / C ** 2) * H + alpha_sp = (8 * np.pi * x_sect * factor * nu**3 / C**2) * H alpha_sp = alpha_sp[:, np.newaxis] alpha_sp = alpha_sp * boltzmann_factor_photo_ion alpha_sp = integrate_array_by_blocks( @@ -344,7 +326,7 @@ def calculate( nu = photo_ion_cross_sections["nu"].values # alpha_sp_E will be missing a lot of prefactors since we are only # interested in relative values here - alpha_sp_E = nu ** 3 * x_sect + alpha_sp_E = nu**3 * x_sect alpha_sp_E = alpha_sp_E[:, np.newaxis] alpha_sp_E = alpha_sp_E * boltzmann_factor_photo_ion alpha_sp_E = cumulative_integrate_array_by_blocks( @@ -376,6 +358,7 @@ def calculate( photo_ion_index, t_rad, w, + level2continuum_idx, ): # Used for initialization if gamma_estimator is None: @@ -387,7 +370,11 @@ def calculate( w, ) else: - gamma = gamma_estimator * photo_ion_norm_factor + gamma_estimator = bound_free_estimator_array2frame( + gamma_estimator, level2continuum_idx + ) + gamma = gamma_estimator * photo_ion_norm_factor.value + return gamma @staticmethod @@ -434,6 +421,7 @@ def calculate( phi_ik, t_electrons, boltzmann_factor_photo_ion, + level2continuum_idx, ): # Used for initialization if alpha_stim_estimator is None: @@ -446,9 +434,12 @@ def calculate( t_electrons, boltzmann_factor_photo_ion, ) - alpha_stim *= phi_ik.loc[alpha_stim.index] else: + alpha_stim_estimator = bound_free_estimator_array2frame( + alpha_stim_estimator, level2continuum_idx + ) alpha_stim = alpha_stim_estimator * photo_ion_norm_factor + alpha_stim *= phi_ik.loc[alpha_stim.index] return alpha_stim @staticmethod @@ -544,10 +535,14 @@ def calculate( n_k_index = get_ion_multi_index(alpha_stim.index) n_k = ion_number_density.loc[n_k_index].values n_i = level_number_density.loc[alpha_stim.index].values - gamma_corr = gamma - alpha_stim * n_k * electron_densities / n_i + gamma_corr = gamma - (alpha_stim * n_k / n_i).multiply( + electron_densities + ) num_neg_elements = (gamma_corr < 0).sum().sum() if num_neg_elements: - raise PlasmaException("Negative values in CorrPhotoIonRateCoeff.") + raise PlasmaException( + "Negative values in CorrPhotoIonRateCoeff. Try raising the number of montecarlo packets." + ) return gamma_corr @@ -586,6 +581,18 @@ class StimRecombRateCoeffEstimator(Input): latex_name = (r"\alpha^{\textrm{stim}}_\textrm{estim}",) +class StimRecombCoolingRateCoeffEstimator(Input): + """ + Attributes + ---------- + stim_recomb_cooling_coeff_estimator : pandas.DataFrame, dtype float + Unnormalized MC estimator for the stimulated recombination cooling rate + coefficient. + """ + + outputs = ("stim_recomb_cooling_coeff_estimator",) + + class BfHeatingRateCoeffEstimator(Input): """ Attributes @@ -843,9 +850,17 @@ class FreeFreeCoolingRate(TransitionProbabilitiesProperty): ---------- cool_rate_ff : pandas.DataFrame, dtype float The free-free cooling rate of the electron gas. + ff_cooling_factor : pandas.Series, dtype float + Pre-factor needed in the calculation of the free-free cooling rate and + the free-free opacity. + + Notes + ----- + This implementation uses a free-free Gaunt factor of one for all species + and ionization stages, which is an approximation. """ - outputs = ("cool_rate_ff",) + outputs = ("cool_rate_ff", "ff_cooling_factor") transition_probabilities_outputs = ("cool_rate_ff",) latex_name = (r"C^{\textrm{ff}}",) @@ -853,22 +868,48 @@ def calculate(self, ion_number_density, electron_densities, t_electrons): ff_cooling_factor = self._calculate_ff_cooling_factor( ion_number_density, electron_densities ) - cool_rate_ff = 1.426e-27 * np.sqrt(t_electrons) * ff_cooling_factor + cool_rate_ff = F_K * np.sqrt(t_electrons) * ff_cooling_factor cool_rate_ff = cooling_rate_series2dataframe( cool_rate_ff, destination_level_idx="ff" ) - return cool_rate_ff + return cool_rate_ff, ff_cooling_factor.values @staticmethod def _calculate_ff_cooling_factor(ion_number_density, electron_densities): ion_charge = ion_number_density.index.get_level_values(1).values factor = ( electron_densities - * ion_number_density.multiply(ion_charge ** 2, axis=0).sum() + * ion_number_density.multiply(ion_charge**2, axis=0).sum() ) return factor +class TwoPhotonFrequencySampler(ProcessingPlasmaProperty): + """ + Attributes + ---------- + nu_two_photon_sampler : float + Frequency of the two-photon emission process + """ + + outputs = ("nu_two_photon_sampler",) + + def calculate(self, two_photon_emission_cdf): + nus = two_photon_emission_cdf["nu"].values + em = two_photon_emission_cdf["cdf"].values + + @njit(error_model="numpy", fastmath=True) + def nu_two_photon(): + zrand = np.random.random() + idx = np.searchsorted(em, zrand, side="right") + + return nus[idx] - (em[idx] - zrand) / (em[idx] - em[idx - 1]) * ( + nus[idx] - nus[idx - 1] + ) + + return nu_two_photon + + class FreeBoundCoolingRate(TransitionProbabilitiesProperty): """ Attributes @@ -976,7 +1017,8 @@ class PhotoIonBoltzmannFactor(ProcessingPlasmaProperty): outputs = ("boltzmann_factor_photo_ion",) - def calculate(self, photo_ion_cross_sections, t_electrons): + @staticmethod + def calculate(photo_ion_cross_sections, t_electrons): nu = photo_ion_cross_sections["nu"].values boltzmann_factor = np.exp(-nu[np.newaxis].T / t_electrons * (H / K_B)) diff --git a/tardis/plasma/properties/general.py b/tardis/plasma/properties/general.py index 8560529883d..cfc56fba66c 100644 --- a/tardis/plasma/properties/general.py +++ b/tardis/plasma/properties/general.py @@ -1,10 +1,9 @@ import logging import numpy as np -import pandas as pd from astropy import units as u -from tardis import constants as const +from tardis import constants as const from tardis.plasma.properties.base import ProcessingPlasmaProperty logger = logging.getLogger(__name__) @@ -12,7 +11,6 @@ __all__ = [ "BetaRadiation", "GElectron", - "NumberDensity", "SelectedAtoms", "ElectronTemperature", "BetaElectron", @@ -57,7 +55,7 @@ class GElectron(ProcessingPlasmaProperty): def calculate(self, beta_rad): return ( (2 * np.pi * const.m_e.cgs.value / beta_rad) - / (const.h.cgs.value ** 2) + / (const.h.cgs.value**2) ) ** 1.5 @@ -78,23 +76,6 @@ def calculate(self, beta_electron): return super(ThermalGElectron, self).calculate(beta_electron) -class NumberDensity(ProcessingPlasmaProperty): - """ - Attributes - ---------- - number_density : Pandas DataFrame, dtype float - Indexed by atomic number, columns corresponding to zones - """ - - outputs = ("number_density",) - latex_name = ("N_{i}",) - - @staticmethod - def calculate(atomic_mass, abundance, density): - number_densities = abundance * density - return number_densities.div(atomic_mass.loc[abundance.index], axis=0) - - class SelectedAtoms(ProcessingPlasmaProperty): """ Attributes @@ -149,7 +130,7 @@ class LuminosityInner(ProcessingPlasmaProperty): @staticmethod def calculate(r_inner, t_inner): return ( - 4 * np.pi * const.sigma_sb.cgs * r_inner[0] ** 2 * t_inner ** 4 + 4 * np.pi * const.sigma_sb.cgs * r_inner[0] ** 2 * t_inner**4 ).to("erg/s") diff --git a/tardis/plasma/properties/helium_nlte.py b/tardis/plasma/properties/helium_nlte.py new file mode 100644 index 00000000000..cd05ce73327 --- /dev/null +++ b/tardis/plasma/properties/helium_nlte.py @@ -0,0 +1,278 @@ +import logging +import os + +import numpy as np +import pandas as pd + +from tardis.plasma.properties.base import ( + ProcessingPlasmaProperty, +) +from tardis.plasma.properties.ion_population import PhiSahaNebular + +__all__ = [ + "HeliumNLTE", + "HeliumNumericalNLTE", +] + +logger = logging.getLogger(__name__) + + +class HeliumNLTE(ProcessingPlasmaProperty): + outputs = ("helium_population",) + + @staticmethod + def calculate( + level_boltzmann_factor, + ionization_data, + beta_rad, + g, + g_electron, + w, + t_rad, + t_electrons, + delta, + zeta_data, + number_density, + partition_function, + ): + """ + Updates all of the helium level populations according to the helium NLTE recomb approximation. + """ + helium_population = level_boltzmann_factor.loc[2].copy() + # He I excited states + he_one_population = HeliumNLTE.calculate_helium_one( + g_electron, beta_rad, ionization_data, level_boltzmann_factor, g, w + ) + helium_population.loc[0].update(he_one_population) + # He I ground state + helium_population.loc[0, 0] = 0.0 + # He II excited states + he_two_population = level_boltzmann_factor.loc[2, 1].mul( + (float(g.loc[2, 1, 0]) ** (-1.0)) + ) + helium_population.loc[1].update(he_two_population) + # He II ground state + helium_population.loc[1, 0] = 1.0 + # He III states + helium_population.loc[2, 0] = HeliumNLTE.calculate_helium_three( + t_rad, + w, + zeta_data, + t_electrons, + delta, + g_electron, + beta_rad, + ionization_data, + g, + ) + # unnormalised = helium_population.sum() + # normalised = helium_population.mul(number_density.ix[2] / unnormalised) + # helium_population.update(normalised) + return helium_population + + @staticmethod + def calculate_helium_one( + g_electron, beta_rad, ionization_data, level_boltzmann_factor, g, w + ): + """ + Calculates the He I level population values, in equilibrium with the He II ground state. + """ + return ( + level_boltzmann_factor.loc[2, 0] + * (1.0 / (2 * float(g.loc[2, 1, 0]))) + * (1 / g_electron) + * (1 / (w**2.0)) + * np.exp(ionization_data.loc[2, 1] * beta_rad) + ) + + @staticmethod + def calculate_helium_three( + t_rad, + w, + zeta_data, + t_electrons, + delta, + g_electron, + beta_rad, + ionization_data, + g, + ): + """ + Calculates the He III level population values. + """ + zeta = PhiSahaNebular.get_zeta_values(zeta_data, 2, t_rad)[1] + he_three_population = ( + 2 + * (float(g.loc[2, 2, 0]) / float(g.loc[2, 1, 0])) + * g_electron + * np.exp(-ionization_data.loc[2, 2] * beta_rad) + * w + * (delta.loc[2, 2] * zeta + w * (1.0 - zeta)) + * (t_electrons / t_rad) ** 0.5 + ) + return he_three_population + + +class HeliumNumericalNLTE(ProcessingPlasmaProperty): + """ + IMPORTANT: This particular property requires a specific numerical NLTE + solver and a specific atomic dataset (neither of which are distributed + with Tardis) to work. + """ + + outputs = ("helium_population",) + + def __init__(self, plasma_parent, heating_rate_data_file): + super(HeliumNumericalNLTE, self).__init__(plasma_parent) + self._g_upper = None + self._g_lower = None + self.heating_rate_data = np.loadtxt(heating_rate_data_file, unpack=True) + + def calculate( + self, + ion_number_density, + electron_densities, + t_electrons, + w, + lines, + j_blues, + levels, + level_boltzmann_factor, + t_rad, + zeta_data, + g_electron, + delta, + partition_function, + ionization_data, + beta_rad, + g, + time_explosion, + ): + logger.info("Performing numerical NLTE He calculations.") + if len(j_blues) == 0: + return None + # Outputting data required by SH module + for zone, _ in enumerate(electron_densities): + with open( + f"He_NLTE_Files/shellconditions_{zone}.txt", "w" + ) as output_file: + output_file.write(ion_number_density.loc[2].sum()[zone]) + output_file.write(electron_densities[zone]) + output_file.write(t_electrons[zone]) + output_file.write(self.heating_rate_data[zone]) + output_file.write(w[zone]) + output_file.write(time_explosion) + output_file.write(t_rad[zone]) + output_file.write(self.plasma_parent.v_inner[zone]) + output_file.write(self.plasma_parent.v_outer[zone]) + + for zone, _ in enumerate(electron_densities): + with open( + f"He_NLTE_Files/abundances_{zone}.txt", "w" + ) as output_file: + for element in range(1, 31): + try: + number_density = ( + ion_number_density[zone].loc[element].sum() + ) + except: + number_density = 0.0 + logger.debug( + f"Number Density could not be calculated. Setting Number Density to {number_density}" + ) + output_file.write(number_density) + + helium_lines = lines[lines["atomic_number"] == 2] + helium_lines = helium_lines[helium_lines["ion_number"] == 0] + for zone, _ in enumerate(electron_densities): + with open( + f"He_NLTE_Files/discradfield_{zone}.txt", "w" + ) as output_file: + j_blues = pd.DataFrame(j_blues, index=lines.index) + helium_j_blues = j_blues[zone].loc[helium_lines.index] + for value in helium_lines.index: + if helium_lines.level_number_lower.loc[value] < 35: + output_file.write( + int(helium_lines.level_number_lower.loc[value] + 1), + int(helium_lines.level_number_upper.loc[value] + 1), + j_blues[zone].loc[value], + ) + # Running numerical simulations + for zone, _ in enumerate(electron_densities): + os.rename( + f"He_NLTE_Files/abundances{zone}.txt", + "He_NLTE_Files/abundances_current.txt", + ) + os.rename( + f"He_NLTE_Files/shellconditions{zone}.txt", + "He_NLTE_Files/shellconditions_current.txt", + ) + os.rename( + f"He_NLTE_Files/discradfield{zone}.txt", + "He_NLTE_Files/discradfield_current.txt", + ) + os.system("nlte-solver-module/bin/nlte_solvertest >/dev/null") + os.rename( + "He_NLTE_Files/abundances_current.txt", + f"He_NLTE_Files/abundances{zone}.txt", + ) + os.rename( + "He_NLTE_Files/shellconditions_current.txt", + f"He_NLTE_Files/shellconditions{zone}.txt", + ) + os.rename( + "He_NLTE_Files/discradfield_current.txt", + f"He_NLTE_Files/discradfield{zone}.txt", + ) + os.rename("debug_occs.dat", f"He_NLTE_Files/occs{zone}.txt") + # Reading in populations from files + helium_population = level_boltzmann_factor.loc[2].copy() + for zone, _ in enumerate(electron_densities): + with open( + f"He_NLTE_Files/discradfield{zone}.txt", "r" + ) as read_file: + for level in range(0, 35): + level_population = read_file.readline() + level_population = float(level_population) + helium_population[zone].loc[0, level] = level_population + helium_population[zone].loc[1, 0] = float(read_file.readline()) + # Performing He LTE level populations (upper two energy levels, + # He II excited states, He III) + he_one_population = HeliumNLTE.calculate_helium_one( + g_electron, + beta_rad, + partition_function, + ionization_data, + level_boltzmann_factor, + electron_densities, + g, + w, + t_rad, + t_electrons, + ) + helium_population.loc[0, 35].update(he_one_population.loc[35]) + helium_population.loc[0, 36].update(he_one_population.loc[36]) + + he_two_population = level_boltzmann_factor.loc[2, 1, 1:].mul( + (float(g.loc[2, 1, 0]) ** (-1)) * helium_population.loc[s1, 0] + ) + helium_population.loc[1, 1:].update(he_two_population) + + helium_population.loc[2, 0] = HeliumNLTE.calculate_helium_three( + t_rad, + w, + zeta_data, + t_electrons, + delta, + g_electron, + beta_rad, + partition_function, + ionization_data, + electron_densities, + ) + unnormalised = helium_population.sum() + normalised = helium_population.mul( + ion_number_density.loc[2].sum() / unnormalised + ) + helium_population.update(normalised) + return helium_population diff --git a/tardis/plasma/properties/ion_population.py b/tardis/plasma/properties/ion_population.py index 3c65b65ae68..794ecde510d 100644 --- a/tardis/plasma/properties/ion_population.py +++ b/tardis/plasma/properties/ion_population.py @@ -1,19 +1,19 @@ import logging +import sys import warnings -import sys import numpy as np import pandas as pd - from scipy import interpolate +from tardis.plasma.exceptions import PlasmaIonizationError from tardis.plasma.properties.base import ProcessingPlasmaProperty from tardis.plasma.properties.continuum_processes import get_ion_multi_index -from tardis.plasma.exceptions import PlasmaIonizationError - logger = logging.getLogger(__name__) +ION_ZERO_THRESHOLD = 1e-20 + __all__ = [ "PhiSahaNebular", "PhiSahaLTE", @@ -44,16 +44,15 @@ class PhiSahaLTE(ProcessingPlasmaProperty): outputs = ("phi",) latex_name = (r"\Phi",) latex_formula = ( - r"\dfrac{2Z_{i,j+1}}{Z_{i,j}}\Big(\ - dfrac{2\pi m_{e}/\beta_{\textrm{rad}}}{h^2}\ - Big)^{3/2}e^{\dfrac{-\chi_{i,j}}{kT_{\textrm{rad}}}}", + r"\dfrac{2Z_{i,j+1}}{Z_{i,j}}\big( \ + \dfrac{2\pi m_{e}/\beta_{\textrm{rad}}}{h^2} \ + \big)^{3/2}e^{\dfrac{-\chi_{i,j}}{kT_{\textrm{rad}}}}", ) broadcast_ionization_energy = None @staticmethod def calculate(g_electron, beta_rad, partition_function, ionization_data): - phis = np.empty( ( partition_function.shape[0] @@ -70,9 +69,9 @@ def calculate(g_electron, beta_rad, partition_function, ionization_data): current_phis = current_block[1:] / current_block[:-1] phis[start_id - i : end_id - i - 1] = current_phis - broadcast_ionization_energy = ionization_data[ + broadcast_ionization_energy = ionization_data.reindex( partition_function.index - ].dropna() + ).dropna() phi_index = broadcast_ionization_energy.index broadcast_ionization_energy = broadcast_ionization_energy.values @@ -101,9 +100,9 @@ class ThermalPhiSahaLTE(PhiSahaLTE): outputs = ("thermal_phi_lte",) latex_name = (r"\Phi^{*}(T_\mathrm{e})",) latex_formula = ( - r"\dfrac{2Z_{i,j+1}}{Z_{i,j}}\Big(\ - dfrac{2\pi m_{e}/\beta_{\textrm{electron}}}{h^2}\ - Big)^{3/2}e^{\dfrac{-\chi_{i,j}}{kT_{\textrm{electron}}}}", + r"\dfrac{2Z_{i,j+1}}{Z_{i,j}}\big( \ + \dfrac{2\pi m_{e}/\beta_{\textrm{electron}}}{h^2} \ + \big)^{3/2}e^{\dfrac{-\chi_{i,j}}{kT_{\textrm{electron}}}}", ) @staticmethod @@ -133,8 +132,8 @@ class PhiSahaNebular(ProcessingPlasmaProperty): outputs = ("phi",) latex_name = (r"\Phi",) latex_formula = ( - r"W(\delta\zeta_{i,j}+W(1-\zeta_{i,j}))\left(\ - dfrac{T_{\textrm{electron}}}{T_{\textrm{rad}}}\right)^{1/2}", + r"W(\delta\zeta_{i,j}+W(1-\zeta_{i,j}))\left( \ + \dfrac{T_{\textrm{electron}}}{T_{\textrm{rad}}}\right)^{1/2}", ) @staticmethod @@ -280,7 +279,10 @@ class IonNumberDensity(ProcessingPlasmaProperty): ) def __init__( - self, plasma_parent, ion_zero_threshold=1e-20, electron_densities=None + self, + plasma_parent, + ion_zero_threshold=ION_ZERO_THRESHOLD, + electron_densities=None, ): super(IonNumberDensity, self).__init__(plasma_parent) self.ion_zero_threshold = ion_zero_threshold @@ -360,7 +362,7 @@ def calculate(self, phi, partition_function, number_density): ) n_electron_iterations += 1 if n_electron_iterations > 100: - logger.warn( + logger.warning( f"n_electron iterations above 100 ({n_electron_iterations}) -" f" something is probably wrong" ) @@ -481,7 +483,7 @@ def calculate( ) n_electron_iterations += 1 if n_electron_iterations > 100: - logger.warn( + logger.warning( f"n_electron iterations above 100 ({n_electron_iterations}) -" f" something is probably wrong" ) diff --git a/tardis/plasma/properties/j_blues.py b/tardis/plasma/properties/j_blues.py index 9ffbe3c1b5c..1f34f0a276b 100644 --- a/tardis/plasma/properties/j_blues.py +++ b/tardis/plasma/properties/j_blues.py @@ -1,10 +1,10 @@ import numpy as np import pandas as pd -from tardis import constants as const +from tardis import constants as const from tardis.plasma.properties.base import ( - ProcessingPlasmaProperty, DataFrameInput, + ProcessingPlasmaProperty, ) from tardis.util.base import intensity_black_body diff --git a/tardis/plasma/properties/nlte.py b/tardis/plasma/properties/nlte.py index 47b2a7e82c9..f5a9a424046 100644 --- a/tardis/plasma/properties/nlte.py +++ b/tardis/plasma/properties/nlte.py @@ -6,15 +6,12 @@ from tardis.plasma.properties.base import ( PreviousIterationProperty, - ProcessingPlasmaProperty, ) from tardis.plasma.properties.ion_population import PhiSahaNebular __all__ = [ "PreviousElectronDensities", "PreviousBetaSobolev", - "HeliumNLTE", - "HeliumNumericalNLTE", ] logger = logging.getLogger(__name__) @@ -53,264 +50,3 @@ def set_initial_value(self, kwargs): columns=kwargs["abundance"].columns, ) self._set_initial_value(initial_value) - - -class HeliumNLTE(ProcessingPlasmaProperty): - outputs = ("helium_population",) - - @staticmethod - def calculate( - level_boltzmann_factor, - ionization_data, - beta_rad, - g, - g_electron, - w, - t_rad, - t_electrons, - delta, - zeta_data, - number_density, - partition_function, - ): - """ - Updates all of the helium level populations according to the helium NLTE recomb approximation. - """ - helium_population = level_boltzmann_factor.loc[2].copy() - # He I excited states - he_one_population = HeliumNLTE.calculate_helium_one( - g_electron, beta_rad, ionization_data, level_boltzmann_factor, g, w - ) - helium_population.loc[0].update(he_one_population) - # He I ground state - helium_population.loc[0, 0] = 0.0 - # He II excited states - he_two_population = level_boltzmann_factor.loc[2, 1].mul( - (g.loc[2, 1, 0] ** (-1.0)) - ) - helium_population.loc[1].update(he_two_population) - # He II ground state - helium_population.loc[1, 0] = 1.0 - # He III states - helium_population.loc[2, 0] = HeliumNLTE.calculate_helium_three( - t_rad, - w, - zeta_data, - t_electrons, - delta, - g_electron, - beta_rad, - ionization_data, - g, - ) - # unnormalised = helium_population.sum() - # normalised = helium_population.mul(number_density.ix[2] / unnormalised) - # helium_population.update(normalised) - return helium_population - - @staticmethod - def calculate_helium_one( - g_electron, beta_rad, ionization_data, level_boltzmann_factor, g, w - ): - """ - Calculates the He I level population values, in equilibrium with the He II ground state. - """ - return ( - level_boltzmann_factor.loc[2, 0] - * (1.0 / (2 * g.loc[2, 1, 0])) - * (1 / g_electron) - * (1 / (w ** 2.0)) - * np.exp(ionization_data.loc[2, 1] * beta_rad) - ) - - @staticmethod - def calculate_helium_three( - t_rad, - w, - zeta_data, - t_electrons, - delta, - g_electron, - beta_rad, - ionization_data, - g, - ): - """ - Calculates the He III level population values. - """ - zeta = PhiSahaNebular.get_zeta_values(zeta_data, 2, t_rad)[1] - he_three_population = ( - 2 - * (float(g.loc[2, 2, 0]) / g.loc[2, 1, 0]) - * g_electron - * np.exp(-ionization_data.loc[2, 2] * beta_rad) - * w - * (delta.loc[2, 2] * zeta + w * (1.0 - zeta)) - * (t_electrons / t_rad) ** 0.5 - ) - return he_three_population - - -class HeliumNumericalNLTE(ProcessingPlasmaProperty): - """ - IMPORTANT: This particular property requires a specific numerical NLTE - solver and a specific atomic dataset (neither of which are distributed - with Tardis) to work. - """ - - outputs = ("helium_population",) - - def __init__(self, plasma_parent, heating_rate_data_file): - super(HeliumNumericalNLTE, self).__init__(plasma_parent) - self._g_upper = None - self._g_lower = None - self.heating_rate_data = np.loadtxt(heating_rate_data_file, unpack=True) - - def calculate( - self, - ion_number_density, - electron_densities, - t_electrons, - w, - lines, - j_blues, - levels, - level_boltzmann_factor, - t_rad, - zeta_data, - g_electron, - delta, - partition_function, - ionization_data, - beta_rad, - g, - time_explosion, - ): - logger.info("Performing numerical NLTE He calculations.") - if len(j_blues) == 0: - return None - # Outputting data required by SH module - for zone, _ in enumerate(electron_densities): - with open( - f"He_NLTE_Files/shellconditions_{zone}.txt", "w" - ) as output_file: - output_file.write(ion_number_density.loc[2].sum()[zone]) - output_file.write(electron_densities[zone]) - output_file.write(t_electrons[zone]) - output_file.write(self.heating_rate_data[zone]) - output_file.write(w[zone]) - output_file.write(time_explosion) - output_file.write(t_rad[zone]) - output_file.write(self.plasma_parent.v_inner[zone]) - output_file.write(self.plasma_parent.v_outer[zone]) - - for zone, _ in enumerate(electron_densities): - with open( - f"He_NLTE_Files/abundances_{zone}.txt", "w" - ) as output_file: - for element in range(1, 31): - try: - number_density = ( - ion_number_density[zone].loc[element].sum() - ) - except: - number_density = 0.0 - logger.debug( - f"Number Density could not be calculated. Setting Number Density to {number_density}" - ) - output_file.write(number_density) - - helium_lines = lines[lines["atomic_number"] == 2] - helium_lines = helium_lines[helium_lines["ion_number"] == 0] - for zone, _ in enumerate(electron_densities): - with open( - f"He_NLTE_Files/discradfield_{zone}.txt", "w" - ) as output_file: - j_blues = pd.DataFrame(j_blues, index=lines.index) - helium_j_blues = j_blues[zone].loc[helium_lines.index] - for value in helium_lines.index: - if helium_lines.level_number_lower.loc[value] < 35: - output_file.write( - int(helium_lines.level_number_lower.loc[value] + 1), - int(helium_lines.level_number_upper.loc[value] + 1), - j_blues[zone].loc[value], - ) - # Running numerical simulations - for zone, _ in enumerate(electron_densities): - os.rename( - f"He_NLTE_Files/abundances{zone}.txt", - "He_NLTE_Files/abundances_current.txt", - ) - os.rename( - f"He_NLTE_Files/shellconditions{zone}.txt", - "He_NLTE_Files/shellconditions_current.txt", - ) - os.rename( - f"He_NLTE_Files/discradfield{zone}.txt", - "He_NLTE_Files/discradfield_current.txt", - ) - os.system("nlte-solver-module/bin/nlte_solvertest >/dev/null") - os.rename( - "He_NLTE_Files/abundances_current.txt", - f"He_NLTE_Files/abundances{zone}.txt", - ) - os.rename( - "He_NLTE_Files/shellconditions_current.txt", - f"He_NLTE_Files/shellconditions{zone}.txt", - ) - os.rename( - "He_NLTE_Files/discradfield_current.txt", - f"He_NLTE_Files/discradfield{zone}.txt", - ) - os.rename("debug_occs.dat", f"He_NLTE_Files/occs{zone}.txt") - # Reading in populations from files - helium_population = level_boltzmann_factor.loc[2].copy() - for zone, _ in enumerate(electron_densities): - with open( - f"He_NLTE_Files/discradfield{zone}.txt", "r" - ) as read_file: - for level in range(0, 35): - level_population = read_file.readline() - level_population = float(level_population) - helium_population[zone].loc[0, level] = level_population - helium_population[zone].loc[1, 0] = float(read_file.readline()) - # Performing He LTE level populations (upper two energy levels, - # He II excited states, He III) - he_one_population = HeliumNLTE.calculate_helium_one( - g_electron, - beta_rad, - partition_function, - ionization_data, - level_boltzmann_factor, - electron_densities, - g, - w, - t_rad, - t_electrons, - ) - helium_population.loc[0, 35].update(he_one_population.loc[35]) - helium_population.loc[0, 36].update(he_one_population.loc[36]) - - he_two_population = level_boltzmann_factor.loc[2, 1, 1:].mul( - (g.loc[2, 1, 0] ** (-1)) * helium_population.loc[s1, 0] - ) - helium_population.loc[1, 1:].update(he_two_population) - - helium_population.loc[2, 0] = HeliumNLTE.calculate_helium_three( - t_rad, - w, - zeta_data, - t_electrons, - delta, - g_electron, - beta_rad, - partition_function, - ionization_data, - electron_densities, - ) - unnormalised = helium_population.sum() - normalised = helium_population.mul( - ion_number_density.loc[2].sum() / unnormalised - ) - helium_population.update(normalised) - return helium_population diff --git a/tardis/plasma/properties/nlte_excitation_data.py b/tardis/plasma/properties/nlte_excitation_data.py new file mode 100644 index 00000000000..6ea6bf06a76 --- /dev/null +++ b/tardis/plasma/properties/nlte_excitation_data.py @@ -0,0 +1,53 @@ +import logging + +import numpy as np + +logger = logging.getLogger(__name__) + + +class NLTEExcitationData(object): + """Data needed for NLTE excitation treatment.""" + + def __init__(self, atom_data_lines, nlte_excitation_species): + """Initializes the NLTEExcitationData object. + + Parameters + ---------- + atom_data_lines : pandas.DataFrame + Information on lines in the atomic data. + nlte_excitation_species : list + List of species treated in NLTE excitation. + """ + self.atom_data_lines = atom_data_lines + self.lines = atom_data_lines.reset_index() + self.nlte_excitation_species = nlte_excitation_species + + if nlte_excitation_species: + logger.info("Preparing the NLTE data") + self._init_indices() + + def _init_indices(self): + """Initializes A_ul and B_ul, B_lu coefficients.""" + self.lines_idx = {} + self.lines_level_number_lower = {} + self.lines_level_number_upper = {} + self.A_uls = {} + self.B_uls = {} + self.B_lus = {} + nlte_excitation_species = self.nlte_excitation_species + for species in nlte_excitation_species: + lines_idx = np.where( + (self.lines.atomic_number == species[0]) + & (self.lines.ion_number == species[1]) + ) + self.lines_idx[species] = lines_idx + self.lines_level_number_lower[ + species + ] = self.lines.level_number_lower.values[lines_idx].astype(int) + self.lines_level_number_upper[ + species + ] = self.lines.level_number_upper.values[lines_idx].astype(int) + + self.A_uls[species] = self.atom_data_lines.A_ul.values[lines_idx] + self.B_uls[species] = self.atom_data_lines.B_ul.values[lines_idx] + self.B_lus[species] = self.atom_data_lines.B_lu.values[lines_idx] diff --git a/tardis/plasma/properties/nlte_rate_equation_solver.py b/tardis/plasma/properties/nlte_rate_equation_solver.py new file mode 100644 index 00000000000..c15a46bf196 --- /dev/null +++ b/tardis/plasma/properties/nlte_rate_equation_solver.py @@ -0,0 +1,1173 @@ +import logging + +import numpy as np +import pandas as pd +from scipy.optimize import root + +from tardis.plasma.properties.base import ProcessingPlasmaProperty + +__all__ = [ + "NLTEPopulationSolverRoot", + "NLTEPopulationSolverLU", +] + +logger = logging.getLogger(__name__) + +NLTE_POPULATION_SOLVER_MAX_ITERATIONS = 100 +NLTE_POPULATION_SOLVER_TOLERANCE = 1e-3 +NLTE_POPULATION_NEGATIVE_RELATIVE_POPULATION_TOLERANCE = ( + -1e-10 +) # Minimum relative negative population allowed before solver fails +NLTE_POPULATION_SOLVER_CHARGE_CONSERVATION_TOLERANCE = 1e-6 # Arbitrary tolerance for charge conservation, should be changed to a more reasonable value + + +class NLTEPopulationSolverRoot(ProcessingPlasmaProperty): + outputs = ("ion_number_density", "electron_densities") + + def calculate( + self, + gamma, + alpha_sp, + alpha_stim, + coll_ion_coeff, + coll_recomb_coeff, + partition_function, + levels, + level_boltzmann_factor, + phi, + rate_matrix_index, + number_density, + nlte_excitation_species, + ): + """Calculates ion number densities and electron densities using NLTE ionization. + + Parameters + ---------- + gamma : pandas.DataFrame + The rate coefficient for radiative ionization. + alpha_sp : pandas.DataFrame + The rate coefficient for spontaneous recombination. + alpha_stim : pandas.DataFrame + The rate coefficient for stimulated recombination. + coll_ion_coeff : pandas.DataFrame + The rate coefficient for collisional ionization in the Seaton + approximation. + coll_recomb_coeff : pandas.DataFrame + The rate coefficient for collisional recombination. + partition_function : pandas.DataFrame + General partition function. Indexed by atomic number, ion number. + levels : MultiIndex + (atomic_number, ion_number, level_number) + Index of filtered atomic data. + level_boltzmann_factor : pandas.DataFrame + General Boltzmann factor. + phi : pandas.DataFrame + Saha Factors. + rate_matrix_index : MultiIndex + (atomic_number, ion_number, treatment type) + If ion is treated in LTE or nebular ionization, 3rd index is "lte_ion", + if treated in NLTE ionization, 3rd index is "nlte_ion". + number_density : pandas.DataFrame + Number density in each shell for each species. + nlte_excitation_species : list + List of species treated in NLTE excitation. + + Returns + ------- + ion_number_densities : pandas.DataFrame + Number density with NLTE ionization treatment. + electron_densities : Series + Electron density with NLTE ionization treatment. + """ + # nlte_data = NLTEExcitationData(atomic_data.lines, nlte_excitation_species) - will be used in a future PR + ( + total_photo_ion_coefficients, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + ) = prepare_ion_recomb_coefficients_nlte_ion( + gamma, + alpha_sp, + alpha_stim, + coll_ion_coeff, + coll_recomb_coeff, + partition_function, + levels, + level_boltzmann_factor, + ) + # TODO: call prepare_bound_bound_rate_matrix if there are NLTE excitation species + initial_electron_densities = number_density.sum(axis=0) + atomic_numbers = ( + rate_matrix_index.get_level_values("atomic_number") + .unique() + .drop("n_e") + ) # dropping the n_e index, as rate_matrix_index's first index is (atomic_numbers, "n_e") + + index = rate_matrix_index.droplevel("level_number").drop("n_e") + ion_number_density = pd.DataFrame(0.0, index=index, columns=phi.columns) + electron_densities = pd.Series(0.0, index=phi.columns) + ion_numbers = index.get_level_values("ion_number") + + for shell in phi.columns: + solution_vector = calculate_balance_vector( + number_density[shell], + rate_matrix_index, + ) + first_guess = calculate_first_guess( + rate_matrix_index, + atomic_numbers, + number_density[shell], + initial_electron_densities[shell], + ) + # All first guess values have to be positive + assert ( + np.greater_equal(first_guess, 0.0).all() + ).all(), "First guess for NLTE solver has negative values, something went wrong." + solution = root( + population_objective_function, + first_guess, + args=( + atomic_numbers, + phi[shell], + solution_vector, + rate_matrix_index, + total_photo_ion_coefficients[shell], + total_rad_recomb_coefficients[shell], + total_coll_ion_coefficients[shell], + total_coll_recomb_coefficients[shell], + ), + jac=True, + ) + assert ( + solution.success + ), "No solution for NLTE population equation found or solver takes too long to converge" + ( + ion_number_density[shell], + electron_densities[shell], + ) = check_negative_population( + pd.Series(solution.x[:-1], index=index), + solution.x[-1], + number_density[shell], + ion_numbers, + ) + # Check that the electron density is still in line with charge conservation + # after removing negative populations + assert ( + np.abs( + np.sum(ion_numbers * ion_number_density[shell]) + - electron_densities[shell] + ) + / electron_densities[shell] + < NLTE_POPULATION_SOLVER_CHARGE_CONSERVATION_TOLERANCE + ), "Charge conservation not fulfilled after correcting for negative populations, solver failed." + + # TODO: change the jacobian and rate matrix to use shell id and get coefficients from the attribute of the class. + + return ion_number_density, electron_densities + + +class NLTEPopulationSolverLU(ProcessingPlasmaProperty): + outputs = ("ion_number_density", "electron_densities") + + def calculate( + self, + gamma, + alpha_sp, + alpha_stim, + coll_ion_coeff, + coll_recomb_coeff, + partition_function, + levels, + level_boltzmann_factor, + phi, + rate_matrix_index, + number_density, + nlte_excitation_species, + ): + """Calculates ion number densities and electron densities using NLTE ionization using an iterative LU decomposition approach. + + Parameters + ---------- + gamma : pandas.DataFrame + The rate coefficient for radiative ionization. + alpha_sp : pandas.DataFrame + The rate coefficient for spontaneous recombination. + alpha_stim : pandas.DataFrame + The rate coefficient for stimulated recombination. + coll_ion_coeff : pandas.DataFrame + The rate coefficient for collisional ionization in the Seaton + approximation. + coll_recomb_coeff : pandas.DataFrame + The rate coefficient for collisional recombination. + partition_function : pandas.DataFrame + General partition function. Indexed by atomic number, ion number. + levels : MultiIndex + (atomic_number, ion_number, level_number) + Index of filtered atomic data. + level_boltzmann_factor : pandas.DataFrame + General Boltzmann factor. + phi : pandas.DataFrame + Saha Factors. + rate_matrix_index : MultiIndex + (atomic_number, ion_number, treatment type) + If ion is treated in LTE or nebular ionization, 3rd index is "lte_ion", + if treated in NLTE ionization, 3rd index is "nlte_ion". + number_density : pandas.DataFrame + Number density in each shell for each species. + nlte_excitation_species : list + List of species treated in NLTE excitation. + + Returns + ------- + ion_number_densities : pandas.DataFrame + Number density with NLTE ionization treatment. + electron_densities : Series + Electron density with NLTE ionization treatment. + """ + ( + total_photo_ion_coefficients, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + ) = prepare_ion_recomb_coefficients_nlte_ion( + gamma, + alpha_sp, + alpha_stim, + coll_ion_coeff, + coll_recomb_coeff, + partition_function, + levels, + level_boltzmann_factor, + ) + + # TODO: Don't create the rate_matrix_index with n_e in the first place + rate_matrix_index = rate_matrix_index.drop("n_e") + + initial_electron_densities = number_density.sum(axis=0) + atomic_numbers = rate_matrix_index.get_level_values( + "atomic_number" + ).unique() + + index = rate_matrix_index.droplevel("level_number") + electron_densities = initial_electron_densities.copy() + ion_number_density = pd.DataFrame(0.0, index=index, columns=phi.columns) + ion_numbers = index.get_level_values("ion_number") + + # Ordering of loops is important to allow for + # easier parallelization in the future + logger.info("Starting NLTE ionization solver") + for shell in phi.columns: + iteration = 0 + balance_vector = calculate_balance_vector( + number_density[shell], + rate_matrix_index, + include_electron_density=False, + ) + while iteration < NLTE_POPULATION_SOLVER_MAX_ITERATIONS: + rate_matrix = calculate_rate_matrix( + atomic_numbers, + phi[shell], + electron_densities[shell], + rate_matrix_index, + total_photo_ion_coefficients[shell], + total_rad_recomb_coefficients[shell], + total_coll_ion_coefficients[shell], + total_coll_recomb_coefficients[shell], + set_charge_conservation=False, + ) + # TODO: Solve for each element individually + # and handle errors in the solver + ion_solution = np.linalg.solve(rate_matrix, balance_vector) + + ion_solution, electron_solution = check_negative_population( + pd.Series(ion_solution, index=index), + None, # Electron density will be recalculated from ion number densities + number_density[shell], + ion_numbers, + ) + delta_ion, delta_electron = self.calculate_lu_solver_delta( + ion_solution, + electron_solution, + ion_number_density[shell], + electron_densities[shell], + ) + ion_number_density[shell] = ion_solution + electron_densities[shell] = electron_solution + if ( + np.all(np.abs(delta_ion) < NLTE_POPULATION_SOLVER_TOLERANCE) + and np.abs(delta_electron) + < NLTE_POPULATION_SOLVER_TOLERANCE + ): + logger.debug( + "NLTE ionization solver converged after {} iterations for shell {}".format( + iteration, shell + ) + ) + break + + iteration += 1 + if iteration == NLTE_POPULATION_SOLVER_MAX_ITERATIONS: + logger.warning( + f"NLTE ionization solver did not converge for shell {shell} " + ) + break + + logger.info("NLTE ionization solver finished") + + return ion_number_density, electron_densities + + @staticmethod + def calculate_lu_solver_delta( + ion_solution, electron_solution, ion_number_density, electron_densities + ): + """Calculates relative change between new solution and old value. + + Parameters + ---------- + ion_solution : numpy.array + Solution vector for the NLTE ionization solver. + electron_solution : float + Solution for the electron density. + + Returns + ------- + numpy.array + Change in ion number densities. + float + Change in electron density. + """ + assert np.all( + ion_solution >= 0.0 + ), "Negative ion number density found, this should not happen." + assert ( + electron_solution >= 0.0 + ), "Negative electron density found, this should not happen." + delta_ion = (ion_number_density - ion_solution) / ion_solution + delta_electron = ( + electron_densities - electron_solution + ) / electron_solution + return delta_ion, delta_electron + + +def check_negative_population( + ion_number_density, electron_densities, number_density, ion_numbers +): + """ + Checks if negative populations are present in the solution. If the relative + negative population is smaller than the tolerance, the negative population + is set to zero. If the relative negative population is larger than the + tolerance, the solver failed. + + Parameters + ---------- + ion_number_density : pandas.Series + Number density with NLTE ionization treatment. + electron_densities : float + Electron density with NLTE ionization treatment. + number_density : pandas.Series + Number density of all present species. + ion_numbers : numpy.array + Ion numbers of all present species. + + Returns + ------- + ion_number_density : pandas.Series + Number density with NLTE ionization treatment. + electron_densities : float + Electron density with NLTE ionization treatment. + """ + # This can probably be done in a more concise way, but since the number + # densities can be zero, we need to check that we don't divide by zero. + for atom_number in number_density.index: + if number_density.loc[atom_number] == 0.0: + # Not sure what to do here, but if the number density is zero, the + # ion number density should also be zero. + # There could be an edge case where the number density is zero, but + # e.g. two ion number densities are -1e-30 and 1e-30, which would + # result in a zero number density. The above value would be acceptable + # within numerical tolerances, but I don't know how to distinguish + # between this case and the case where the ion number density is + # to large to be numerical. + continue + else: + for ion_number in ion_number_density.loc[atom_number].index: + if (ion_number_density.loc[atom_number, ion_number] < 0.0) and ( + ion_number_density.loc[atom_number, ion_number] + / number_density.loc[atom_number] + > NLTE_POPULATION_NEGATIVE_RELATIVE_POPULATION_TOLERANCE + ): + ion_number_density.loc[atom_number, ion_number] = 0.0 + + assert np.greater_equal( + ion_number_density, 0.0 + ).all(), "Negative ion number density found, solver failed." + + if electron_densities is None: + # For the root solver, we don't want to recalculate the electron density + electron_densities = np.sum(ion_numbers * ion_number_density) + assert ( + electron_densities >= 0.0 + ), "Negative electron density found, solver failed." + return ion_number_density, electron_densities + + +def prepare_ion_recomb_coefficients_nlte_ion( + gamma, + alpha_sp, + alpha_stim, + coll_ion_coeff, + coll_recomb_coeff, + partition_function, + levels, + level_boltzmann_factor, +): + """ + Prepares the ionization and recombination coefficients by grouping them for + ion numbers. + + Parameters + ---------- + gamma : pandas.DataFrame + The rate coefficient for radiative ionization. + alpha_sp : pandas.DataFrame + The rate coefficient for spontaneous recombination. + alpha_stim : pandas.DataFrame + The rate coefficient for stimulated recombination. + coll_ion_coeff : pandas.DataFrame + The rate coefficient for collisional ionization in the Seaton + approximation. + coll_recomb_coeff : pandas.DataFrame + The rate coefficient for collisional recombination. + partition_function : pandas.DataFrame + General partition function. Indexed by atomic number, ion number. + levels : MultiIndex + (atomic_number, ion_number, level_number) + Index of filtered atomic data. + level_boltzmann_factor : pandas.DataFrame + General Boltzmann factor. + + Returns + ------- + total_photo_ion_coefficients + Photoionization coefficients grouped by atomic number and ion number. + total_rad_recomb_coefficients + Radiative recombination coefficients grouped by atomic number and ion number. + total_coll_ion_coefficients + Collisional ionization coefficients grouped by atomic number and ion number. + total_coll_recomb_coefficients + Collisional recombination coefficients grouped by atomic number and ion number. + """ + indexer = pd.Series( + np.arange(partition_function.shape[0]), + index=partition_function.index, + ) + _ion2level_idx = indexer.loc[levels.droplevel("level_number")].values + partition_function_broadcast = partition_function.values[_ion2level_idx] + level_population_fraction = pd.DataFrame( + level_boltzmann_factor.values / partition_function_broadcast, + index=levels, + ) + total_photo_ion_coefficients = ( + (level_population_fraction.loc[gamma.index] * gamma) + .groupby(level=("atomic_number", "ion_number")) + .sum() + ) + + total_rad_recomb_coefficients = ( + (alpha_sp + alpha_stim) + .groupby(level=["atomic_number", "ion_number"]) + .sum() + ) + total_coll_ion_coefficients = ( + (level_population_fraction.loc[coll_ion_coeff.index] * coll_ion_coeff) + .groupby(level=("atomic_number", "ion_number")) + .sum() + ) + total_coll_recomb_coefficients = ( + (coll_recomb_coeff).groupby(level=("atomic_number", "ion_number")).sum() + ) + return ( + total_photo_ion_coefficients, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + ) + + +def calculate_balance_vector( + number_density, + rate_matrix_index, + include_electron_density=True, +): + """Constructs the balance vector for the NLTE ionization solver set of equations by combining + all solution verctor blocks. + + Parameters + ---------- + number_density : pandas.DataFrame + Number densities of all present species. + rate_matrix_index : pandas.MultiIndex + (atomic_number, ion_number, treatment type) + + Returns + ------- + numpy.array + Solution vector for the NLTE ionization solver. + """ + atomic_numbers = number_density.index + balance_array = [] + for atomic_number in atomic_numbers: + needed_number_of_elements = ( + rate_matrix_index.get_level_values("atomic_number") == atomic_number + ).sum() + balance_vector_block = np.zeros(needed_number_of_elements) + balance_vector_block[-1] = number_density.loc[atomic_number] + balance_array.append(balance_vector_block) + if include_electron_density: + balance_array.append(np.array([0.0])) + return np.hstack(balance_array) + + +def calculate_first_guess( + rate_matrix_index, + atomic_numbers, + number_density, + electron_density, +): + """Constructs a first guess for ion number densities and electron density, where all species are singly ionized. + + Parameters + ---------- + rate_matrix_index : pandas.MultiIndex + (atomic_number, ion_number, treatment type) + atomic_numbers : numpy.array + All atomic numbers present in the plasma. + number_density : pandas.DataFrame + Number density of present species. + electron_density : float + Current value of electron density. + + Returns + ------- + numpy.array + Guess for ion number densities and electron density. + """ + first_guess = pd.Series(0.0, index=rate_matrix_index) + for atomic_number in atomic_numbers: + first_guess.loc[(atomic_number, 1)].iloc[0] = number_density.loc[ + atomic_number + ] + # TODO: After the first iteration, the new guess can be the old solution. + first_guess = first_guess.values + first_guess[-1] = electron_density + return first_guess + + +def population_objective_function( + populations, + atomic_numbers, + phi, + solution_vector, + rate_matrix_index, + total_photo_ion_coefficients, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + set_charge_conservation=True, +): + """Main set of equations for the NLTE ionization solver. + + To solve the statistical equilibrium equations, we need to find the root + of the objective function A*x - B, where x are the populations, + A is the matrix of rates, and B is the solution vector. + + Parameters + ---------- + populations : numpy.array + Current values of ion number densities and electron density. + atomic_numbers : numpy.array + All atomic numbers present in the plasma. + phi : pandas.DataFrame + Saha Factors of the current shell. + solution_vector : numpy.array + Solution vector for the set of equations. + rate_matrix_index : pandas.MultiIndex + (atomic_number, ion_number, treatment type) + If ion is treated in LTE or nebular ionization, 3rd index is "lte_ion", + if treated in NLTE ionization, 3rd index is "nlte_ion". + total_photo_ion_coefficients : pandas.DataFrame + Photo ion. coefficients for current atomic number + total_rad_recomb_coefficients : pandas.DataFrame + Radiative recombination coefficients for current atomic number + total_coll_ion_coefficients : pandas.DataFrame + Collisional ionization coefficients for current atomic number + total_coll_recomb_coefficients : pandas.DataFrame + Coll. recomb. coefficients for current atomic number + set_charge_conservation : bool + If True, sets the last row of the rate matrix to the charge conservation equation. + + Returns + ------- + (numpy.array, numpy.array) + Returns the objective function and jacobian of the rate matrix in a tuple. + """ + electron_density = populations[-1] + rate_matrix = calculate_rate_matrix( + atomic_numbers, + phi, + electron_density, + rate_matrix_index, + total_photo_ion_coefficients, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + set_charge_conservation=set_charge_conservation, + ) + jacobian_matrix = calculate_jacobian_matrix( + atomic_numbers, + populations, + rate_matrix, + rate_matrix_index, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + ) + return ( + np.dot(rate_matrix.values, populations) - solution_vector, + jacobian_matrix, + ) + + +def calculate_rate_matrix( + atomic_numbers, + phi_shell, + electron_density, + rate_matrix_index, + total_photo_ion_coefficients, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + set_charge_conservation=True, +): + """ + + Parameters + ---------- + phi_shell : pandas.DataFrame + Saha Factors in the current shell + electron_density : float + Guess for electron density in the current shell + rate_matrix_index : pandas.MultiIndex + Index used for constructing the rate matrix + total_photo_ion_coefficients : pandas.DataFrame + Photo ionization coefficients + total_rad_recomb_coefficients : pandas.DataFrame + Radiative recombination coefficients (should get multiplied by electron density) + total_coll_ion_coefficients : pandas.DataFrame + Collisional ionization coefficients (should get multiplied by electron density) + total_coll_recomb_coefficients : pandas.DataFrame + Collisional recombination coefficients (should get multiplied by electron density^2) + set_charge_conservation : bool + If True, sets the last row of the rate matrix to the charge conservation equation. + + Returns + ------- + pandas.DataFrame + Rate matrix used for NLTE solver. + """ + rate_matrix = pd.DataFrame( + 0.0, columns=rate_matrix_index, index=rate_matrix_index + ) + total_rad_recomb_coefficients = ( + total_rad_recomb_coefficients * electron_density + ) + total_coll_ion_coefficients = total_coll_ion_coefficients * electron_density + total_coll_recomb_coefficients = ( + total_coll_recomb_coefficients * electron_density**2 + ) + for atomic_number in atomic_numbers: + ion_numbers = rate_matrix.loc[atomic_number].index.get_level_values( + "ion_number" + ) + phi_block = phi_shell.loc[atomic_number] + rate_matrix_block = lte_rate_matrix_block(phi_block, electron_density) + + nlte_ion_numbers = ion_numbers[ + rate_matrix.loc[atomic_number].index.get_level_values( + "level_number" + ) + == "nlte_ion" + ] + # >>> lte_ion_numbers is for future use in NLTE excitation treatment + if False: + lte_ion_numbers = ion_numbers[ + rate_matrix.loc[atomic_number].index.get_level_values( + "level_number" + ) + == "lte_ion" + ] + # <<< + for ion_number in nlte_ion_numbers: + rate_matrix_block = set_nlte_ion_rate( + rate_matrix_block, + atomic_number, + ion_number, + total_rad_recomb_coefficients.loc[(atomic_number,)], + total_photo_ion_coefficients.loc[(atomic_number,)], + total_coll_ion_coefficients.loc[(atomic_number,)], + total_coll_recomb_coefficients.loc[(atomic_number,)], + ) + rate_matrix.loc[ + (atomic_number, slice(None)), (atomic_number) + ] = rate_matrix_block + + charge_conservation_row = calculate_charge_conservation_row(atomic_numbers) + if set_charge_conservation: + rate_matrix.loc[("n_e", slice(None))] = charge_conservation_row + return rate_matrix + + +def calculate_jacobian_matrix( + atomic_numbers, + populations, + rate_matrix, + rate_matrix_index, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, +): + """Creates the jacobian matrix used for NLTE ionization solver + + Parameters + ---------- + populations : numpy.array + Ion populations, electron density + rate_matrix : pandas.DataFrame + Rate matrix used for NLTE solver. + rate_matrix_index : MultiIndex + (atomic_number, ion_number, treatment type) + If ion is treated in LTE or nebular ionization, 3rd index is "lte_ion", + if treated in NLTE ionization, 3rd index is "nlte_ion". + total_rad_recomb_coefficients : pandas.DataFrame + Radiative recombination coefficients grouped by atomic number and ion number. + total_coll_ion_coefficients : pandas.DataFrame + Collisional ionization coefficients(should get multiplied by electron density). + total_coll_recomb_coefficients : pandas.DataFrame + Collisional recombination coefficients(should get multiplied by electron density). + + Returns + ------- + numpy.array + Jacobian matrix used for NLTE ionization solver + """ + # TODO: for future use, can be vectorized. + index = 0 + jacobian_matrix = rate_matrix.copy().values + jacobian_matrix[:-1, -1] = populations[1:] + for atomic_number in atomic_numbers: + for i in range(index, index + atomic_number): + if rate_matrix_index[i][2] == "nlte_ion": + jacobian_matrix[i, -1] = deriv_matrix_block( + atomic_number, + total_rad_recomb_coefficients.loc[(atomic_number,)], + total_coll_ion_coefficients.loc[(atomic_number,)], + total_coll_recomb_coefficients.loc[(atomic_number,)], + populations[index : index + atomic_number + 1], + populations[-1], + )[i - index] + index += atomic_number + 1 + jacobian_matrix[index - 1, -1] = 0 # number conservation row + return jacobian_matrix + + +def lte_rate_matrix_block(phi_block, electron_density): + """Creates the generic LTE block for rate matrix. + + Parameters + ---------- + phi_block : pandas.DataFrame + Saha Factors for current atomic number + electron_density : float + Current guess for electron density + + Returns + ------- + numpy.array + LTE block for rate matrix + """ + lte_rate_vector_block = -1.0 * np.hstack([*phi_block.values, -1.0]) + lte_rate_matrix_block = np.diag(lte_rate_vector_block) + n_e_initial = np.ones(len(phi_block)) * electron_density + n_e_matrix = np.diag(n_e_initial, 1) + lte_rate_matrix_block += n_e_matrix + lte_rate_matrix_block[-1, :] = 1.0 + return lte_rate_matrix_block + + +def set_nlte_ion_rate( + rate_matrix_block, + atomic_number, + ion_number, + total_rad_recomb_coefficients, + total_photo_ion_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, +): + """Calculates the row for the species treated in NLTE ionization + + Parameters + ---------- + rate_matrix_block : numpy.array + The diagonal block corresponding to current atomic number. + atomic_number : int + Current atomic number + ion_number : int + Current ion number + total_rad_recomb_coefficients : pandas.DataFrame + Rad. recomb. coefficients for current atomic number + total_photo_ion_coefficients : pandas.DataFrame + Photo ionization coefficients for current atomic number + total_coll_ion_coefficients : pandas.DataFrame + Collisional ionization coefficients for current atomic number + total_coll_recomb_coefficients : pandas.DataFrame + Collisional recombination coefficients for current atomic number + + Returns + ------- + numpy.array + Rate matrix block with a changed row for NLTE ionization treatment + """ + ion_coefficients = ( + total_photo_ion_coefficients + total_coll_ion_coefficients + ) + recomb_coefficients = ( + total_rad_recomb_coefficients + total_coll_recomb_coefficients + ) + if atomic_number != ion_number: + ion_coeff_matrix_ion_row = ion_matrix( + ion_coefficients, atomic_number, ion_number + ) + recomb_coeff_matrix_ion_row = recomb_matrix( + recomb_coefficients, atomic_number, ion_number + ) + rate_matrix_block[ion_number, :] = ( + ion_coeff_matrix_ion_row + recomb_coeff_matrix_ion_row + ) + return rate_matrix_block + + +def calculate_charge_conservation_row(atomic_numbers): + """calculate the last row of the rate_matrix. This row corresponds to the charge + density equation. + """ + charge_conservation_row = [] + for atomic_number in atomic_numbers: + charge_conservation_row.append(np.arange(0, atomic_number + 1)) + charge_conservation_row = np.hstack([*charge_conservation_row, -1]) + # TODO needs to be modified for use in nlte_excitation + return charge_conservation_row + + +def deriv_matrix_block( + atomic_number, + total_rad_recomb_coefficients, + total_coll_ion_coefficients, + total_coll_recomb_coefficients, + current_ion_number_densities, + current_electron_density, +): + """Calculates the dot product of the derivative of rate matrix and ion number densities+electron density column. + + Parameters + ---------- + atomic_number : int64 + Current atomic number + total_rad_recomb_coefficients : pandas.DataFrame + Radiative recombination coefficients grouped by atomic number and ion number. + total_coll_ion_coefficients : pandas.DataFrame + Collisional ionization coefficients. + total_coll_recomb_coefficients : pandas.DataFrame + Collisional recombination coefficients. + current_ion_number_densities : numpy.array + Current ion number densities for the current atomic number. + current_electron_density : float64 + Current electron density + + Returns + ------- + numpy.array + Returns the part of the last column of the jacobian matrix, corresponding to atomic number. + """ + ion_numbers = np.arange(0, atomic_number) + radiative_rate_coeff_matrix = recomb_matrix( + total_rad_recomb_coefficients, atomic_number, ion_numbers + ) + coll_recomb_matrix = ( + recomb_matrix( + total_coll_recomb_coefficients, atomic_number, ion_numbers + ) + * current_electron_density + * 2 + ) + coll_ion_coeff_matrix = ion_matrix( + total_coll_ion_coefficients, atomic_number, ion_numbers + ) + deriv_matrix = ( + radiative_rate_coeff_matrix + coll_ion_coeff_matrix + coll_recomb_matrix + ) + return np.dot(deriv_matrix, current_ion_number_densities) + + +def ion_matrix(ion_coefficients, atomic_number, ion_number): + """Constructs an ionization rate matrix from the ionization rates. + + Parameters + ---------- + ion_coefficients : pandas.DataFrame + Recombination coefficients. + atomic_number : int64 + Current atomic number. Used for the dimension of a square matrix. + ion_number : int64 + Current ion number. Used for returning the correct row. + + Returns + ------- + numpy.ndarray + """ + offdiag = np.zeros(atomic_number) + index = ion_coefficients.index + for i in index: + offdiag[i] = ion_coefficients.loc[i] + diag = np.hstack([-offdiag, np.zeros(1)]) + return (np.diag(diag) + np.diag(offdiag, k=-1))[ion_number, :] + + +def recomb_matrix(recomb_coefficients, atomic_number, ion_number): + """Constructs a recombination rate matrix from the recombination rates. + + Parameters + ---------- + recomb_coefficients : pandas.DataFrame + Recombination coefficients. + atomic_number : int64 + Current atomic number. Used for the dimension of a square matrix. + ion_number : int64 + Current ion number. Used for returning the correct row. + + Returns + ------- + numpy.ndarray + """ + offdiag = np.zeros(atomic_number) + index = recomb_coefficients.index + for i in index: + offdiag[i] = recomb_coefficients.loc[i] + diag = np.hstack([np.zeros(1), -offdiag]) + return (np.diag(diag) + np.diag(offdiag, k=1))[ion_number, :] + + +#################### +# Unused functions # +# vvvvvvvvvvvvvvvv # +#################### +def prepare_phi(phi): + """ + Makes sure that phi does not have any 0 entries. + """ + phi[phi == 0.0] = 1.0e-10 * phi[phi > 0.0].min().min() + return phi + + +def prepare_bound_bound_rate_matrix( + number_of_levels, + lines_index, + r_ul_index, + r_ul_matrix, + r_lu_index, + r_lu_matrix, + beta_sobolev, +): + """Calculates a matrix with bound-bound rates for NLTE excitation treatment. + + Parameters + ---------- + number_of_levels : int + Number of levels for the specified species. + lines_index : numpy.array + Index of lines in nlte_data. + r_ul_index : numpy.array + Index used for r_ul matrix + r_ul_matrix : numpy.array + Matrix with the rates(upper to lower transition) of bound-bound interaction(DOES NOT INCLUDE THE BETA SOBOLEVS) + (number_of_levels, number_of_levels, number_of_shells) + r_lu_index : numpy.array + Index used for r_lu matrix + r_lu_matrix : numpy.array + r_lu_matrix : numpy.array + Matrix with the rates(lower to upper transition) of bound-bound interaction(DOES NOT INCLUDE THE BETA SOBOLEVS) + (number_of_levels, number_of_levels, number_of_shells) + beta_sobolev : pandas.DataFrame + Beta Sobolev factors. + + Returns + ------- + numpy.array (number of levels, number of levels) + Matrix with excitation-deexcitation rates(should be added to NLTE rate matrix for excitation treatment). + NOTE: only works with ONE ion number treated in NLTE excitation AT ONCE. + """ + number_of_shells = beta_sobolev.shape[1] + try: + beta_sobolev_filtered = beta_sobolev.iloc[lines_index] + except AttributeError: + beta_sobolev_filtered = beta_sobolev + r_ul_matrix_reshaped = r_ul_matrix.reshape( + (number_of_levels**2, number_of_shells) + ) + r_lu_matrix_reshaped = r_lu_matrix.reshape( + (number_of_levels**2, number_of_shells) + ) + r_ul_matrix_reshaped[r_ul_index] *= beta_sobolev_filtered + r_lu_matrix_reshaped[r_lu_index] *= beta_sobolev_filtered + rates_matrix_bound_bound = r_ul_matrix + r_lu_matrix + for i in range(number_of_levels): + rates_matrix_bound_bound[i, i] = -rates_matrix_bound_bound[:, i].sum( + axis=0 + ) + return rates_matrix_bound_bound + + +def prepare_r_uls_r_lus( + number_of_levels, + number_of_shells, + j_blues, + excitation_species, + nlte_data, +): + """Calculates part of rate matrices for bound bound interactions. + + Parameters + ---------- + number_of_levels : int + Number of levels for the NLTE excitation species. + number_of_shells : int + Number of shells. + j_blues : pandas.DataFrame, dtype float + Mean intensities in the blue wings of the line transitions. + excitation_species : tuple + Species treated in NLTE excitation. + nlte_data : NLTEExcitationData + Data relevant to NLTE excitation species. + + Returns + ------- + lines_index : numpy.array + Index of lines in nlte_data. + number_of_levels : int + Number of levels for the specified species. + r_ul_index : numpy.array + Index used for r_ul matrix + r_ul_matrix_reshaped : numpy.array + Matrix with the rates(upper to lower transition) of bound-bound interaction(DOES NOT INCLUDE THE BETA SOBOLEVS) + r_lu_index : numpy.array + Index used for r_lu matrix + r_lu_matrix_reshaped : numpy.array + Matrix with the rates(lower to upper transition) of bound-bound interaction(DOES NOT INCLUDE THE BETA SOBOLEVS) + """ + # number_of_levels = atomic_data_levels.energy.loc[ + # excitation_species + # ].count() do this in the solver + lnl = nlte_data.lines_level_number_lower[excitation_species] + lnu = nlte_data.lines_level_number_upper[excitation_species] + (lines_index,) = nlte_data.lines_idx[excitation_species] + + try: + j_blues_filtered = j_blues.iloc[lines_index] + except AttributeError: + j_blues_filtered = j_blues + A_uls = nlte_data.A_uls[excitation_species] + B_uls = nlte_data.B_uls[excitation_species] + B_lus = nlte_data.B_lus[excitation_species] + r_lu_index = lnu * number_of_levels + lnl + r_ul_index = lnl * number_of_levels + lnu + r_ul_matrix = np.zeros( + (number_of_levels, number_of_levels, number_of_shells), + dtype=np.float64, + ) + r_ul_matrix_reshaped = r_ul_matrix.reshape( + (number_of_levels**2, number_of_shells) + ) + r_ul_matrix_reshaped[r_ul_index] = ( + A_uls[np.newaxis].T + B_uls[np.newaxis].T * j_blues_filtered + ) + r_lu_matrix = np.zeros_like(r_ul_matrix) + r_lu_matrix_reshaped = r_lu_matrix.reshape( + (number_of_levels**2, number_of_shells) + ) + r_lu_matrix_reshaped[r_lu_index] = B_lus[np.newaxis].T * j_blues_filtered + return ( + lines_index, + r_ul_index, + r_ul_matrix, + r_lu_index, + r_lu_matrix, + ) + + +def create_coll_exc_deexc_matrix( + coll_exc_coefficient, + coll_deexc_coefficient, + number_of_levels, +): + """Generates a coefficient matrix from collisional excitation/deexcitation coefficients. + + Needs to be multiplied by electron density when added to the overall rate_matrix. + + Parameters + ---------- + coll_exc_coefficient : pandas.Series + Series of collisional excitation coefficients for current (atomic number, ion_number) + in the current shell. + coll_deexc_coefficient : pandas.Series + Series of collisional deexcitation coefficients for (atomic number, ion_number) + in the current shell. + number_of_levels : int + Number of levels for the current atomic number, ion number. + + Returns + ------- + coeff_matrix : np.array (number of levels, number of levels) + Square matrix constructed by collisional exc./deexc. coefficients. + """ + diagonal_exc = np.zeros(number_of_levels) + diagonal_deexc = np.zeros(number_of_levels) + col_exc_coefficient_sum_lower = coll_exc_coefficient.groupby( + "level_number_lower" + ).sum() + col_deexc_coefficient_sum_upper = coll_deexc_coefficient.groupby( + "level_number_upper" + ).sum() + + diagonal_exc[col_exc_coefficient_sum_lower.index] = ( + -1 * col_exc_coefficient_sum_lower.values + ) + diagonal_deexc[col_deexc_coefficient_sum_upper.index] = ( + -1 * col_deexc_coefficient_sum_upper.values + ) + exc_matrix = np.zeros((number_of_levels, number_of_levels)) + deexc_matrix = np.zeros((number_of_levels, number_of_levels)) + exc_matrix[ + ( + coll_exc_coefficient.index.get_level_values("level_number_upper"), + coll_exc_coefficient.index.get_level_values("level_number_lower"), + ) + ] = coll_exc_coefficient.values + deexc_matrix[ + ( + coll_exc_coefficient.index.get_level_values("level_number_lower"), + coll_exc_coefficient.index.get_level_values("level_number_upper"), + ) + ] = coll_deexc_coefficient.values + np.fill_diagonal(exc_matrix, diagonal_exc) + np.fill_diagonal(deexc_matrix, diagonal_deexc) + coeff_matrix = exc_matrix + deexc_matrix + return coeff_matrix diff --git a/tardis/plasma/properties/partition_function.py b/tardis/plasma/properties/partition_function.py index 4e00332d7cd..0fafaeee976 100644 --- a/tardis/plasma/properties/partition_function.py +++ b/tardis/plasma/properties/partition_function.py @@ -208,7 +208,7 @@ def _main_nlte_calculation( dtype=np.float64, ) r_ul_matrix_reshaped = r_ul_matrix.reshape( - (number_of_levels ** 2, len(t_electrons)) + (number_of_levels**2, len(t_electrons)) ) r_ul_matrix_reshaped[r_ul_index] = ( A_uls[np.newaxis].T + B_uls[np.newaxis].T * j_blues_filtered @@ -216,7 +216,7 @@ def _main_nlte_calculation( r_ul_matrix_reshaped[r_ul_index] *= beta_sobolevs_filtered r_lu_matrix = np.zeros_like(r_ul_matrix) r_lu_matrix_reshaped = r_lu_matrix.reshape( - (number_of_levels ** 2, len(t_electrons)) + (number_of_levels**2, len(t_electrons)) ) r_lu_matrix_reshaped[r_lu_index] = ( B_lus[np.newaxis].T * j_blues_filtered * beta_sobolevs_filtered diff --git a/tardis/plasma/properties/plasma_input.py b/tardis/plasma/properties/plasma_input.py index 5d931960a48..ae8b6ab4adc 100644 --- a/tardis/plasma/properties/plasma_input.py +++ b/tardis/plasma/properties/plasma_input.py @@ -1,11 +1,15 @@ -from tardis.plasma.properties.base import Input, ArrayInput, DataFrameInput +from tardis.plasma.properties.base import ( + ArrayInput, + Input, +) __all__ = [ "TRadiative", "DilutionFactor", "AtomicData", "Abundance", - "Density", + "NumberDensity", + "IsotopeAbundance", "TimeExplosion", "JBlueEstimator", "LinkTRadTElectron", @@ -14,6 +18,8 @@ "TInner", "Volume", "ContinuumInteractionSpecies", + "NLTEIonizationSpecies", + "NLTEExcitationSpecies", ] @@ -62,16 +68,15 @@ class Abundance(Input): outputs = ("abundance",) -class Density(ArrayInput): +class IsotopeAbundance(Input): """ Attributes ---------- - density : Numpy array, dtype float - Total density values + isotope_abundance : Numpy array, dtype float + Fractional abundance of isotopes """ - outputs = ("density",) - latex_name = (r"\rho",) + outputs = ("isotope_abundance",) class TimeExplosion(Input): @@ -136,3 +141,25 @@ class ContinuumInteractionSpecies(Input): """ outputs = ("continuum_interaction_species",) + + +class NLTEIonizationSpecies(Input): + + outputs = ("nlte_ionization_species",) + + +class NLTEExcitationSpecies(Input): + + outputs = ("nlte_excitation_species",) + + +class NumberDensity(Input): + """ + Attributes + ---------- + number_density : Pandas DataFrame, dtype float + Indexed by atomic number, columns corresponding to zones + """ + + outputs = ("number_density",) + latex_name = ("N_{i}",) diff --git a/tardis/plasma/properties/property_collections.py b/tardis/plasma/properties/property_collections.py index 3abd04b3008..3b1e8ebc5cd 100644 --- a/tardis/plasma/properties/property_collections.py +++ b/tardis/plasma/properties/property_collections.py @@ -1,4 +1,9 @@ +from tardis.opacities.macro_atom.base import ( + NonMarkovChainTransitionProbabilities, + TransitionProbabilities, +) from tardis.plasma.properties import * +from tardis.opacities.tau_sobolev import TauSobolev class PlasmaPropertyCollection(list): @@ -9,13 +14,15 @@ class PlasmaPropertyCollection(list): [ TRadiative, Abundance, - Density, + NumberDensity, TimeExplosion, AtomicData, DilutionFactor, LinkTRadTElectron, HeliumTreatment, ContinuumInteractionSpecies, + NLTEIonizationSpecies, + NLTEExcitationSpecies, ] ) basic_properties = PlasmaPropertyCollection( @@ -23,11 +30,9 @@ class PlasmaPropertyCollection(list): BetaRadiation, Levels, Lines, - AtomicMass, PartitionFunction, GElectron, IonizationData, - NumberDensity, LinesLowerLevelIndex, LinesUpperLevelIndex, TauSobolev, @@ -39,7 +44,7 @@ class PlasmaPropertyCollection(list): lte_ionization_properties = PlasmaPropertyCollection([PhiSahaLTE]) lte_excitation_properties = PlasmaPropertyCollection([LevelBoltzmannFactorLTE]) macro_atom_properties = PlasmaPropertyCollection( - [BetaSobolev, TransitionProbabilities] + [BetaSobolev, TransitionProbabilities, MacroAtomData] ) nebular_ionization_properties = PlasmaPropertyCollection( [PhiSahaNebular, ZetaData, BetaElectron, RadiationFieldCorrection] @@ -57,6 +62,12 @@ class PlasmaPropertyCollection(list): BetaSobolev, ] ) +nlte_root_solver_properties = PlasmaPropertyCollection( + [NLTEIndexHelper, NLTEPopulationSolverRoot] +) +nlte_lu_solver_properties = PlasmaPropertyCollection( + [NLTEIndexHelper, NLTEPopulationSolverLU] +) helium_nlte_properties = PlasmaPropertyCollection( [ HeliumNLTE, @@ -87,6 +98,7 @@ class PlasmaPropertyCollection(list): TInner, Volume, BfHeatingRateCoeffEstimator, + StimRecombCoolingRateCoeffEstimator, YgData, ] ) @@ -111,12 +123,15 @@ class PlasmaPropertyCollection(list): RawPhotoIonTransProbs, RawRadBoundBoundTransProbs, MarkovChainTransProbs, + NonContinuumTransProbsMask, YgInterpolator, CollExcRateCoeff, CollDeexcRateCoeff, RawCollisionTransProbs, MarkovChainIndex, MarkovChainTransProbsCollector, + NonMarkovChainTransitionProbabilities, + MonteCarloTransProbs, FreeFreeCoolingRate, FreeBoundCoolingRate, BoundFreeOpacity, @@ -124,12 +139,20 @@ class PlasmaPropertyCollection(list): PhotoIonBoltzmannFactor, FreeBoundEmissionCDF, LevelIdxs2LineIdx, + LevelIdxs2TransitionIdx, CollIonRateCoeffSeaton, CollRecombRateCoeff, RawCollIonTransProbs, + ContinuumInteractionHandler, + BetaSobolev, ] ) adiabatic_cooling_properties = PlasmaPropertyCollection([AdiabaticCoolingRate]) two_photon_properties = PlasmaPropertyCollection( - [RawTwoPhotonTransProbs, TwoPhotonData, TwoPhotonEmissionCDF] + [ + RawTwoPhotonTransProbs, + TwoPhotonData, + TwoPhotonEmissionCDF, + TwoPhotonFrequencySampler, + ] ) diff --git a/tardis/plasma/properties/radiative_properties.py b/tardis/plasma/properties/radiative_properties.py index d3a50f801d6..37170b5c9e6 100644 --- a/tardis/plasma/properties/radiative_properties.py +++ b/tardis/plasma/properties/radiative_properties.py @@ -3,22 +3,20 @@ import numpy as np import pandas as pd from astropy import units as u -from tardis import constants as const from numba import jit, prange +from tardis import constants as const +from tardis.opacities.macro_atom.base import TransitionProbabilities from tardis.plasma.properties.base import ( ProcessingPlasmaProperty, TransitionProbabilitiesProperty, ) -from tardis.plasma.properties.util import macro_atom logger = logging.getLogger(__name__) __all__ = [ "StimulatedEmissionFactor", - "TauSobolev", "BetaSobolev", - "TransitionProbabilities", "RawRadBoundBoundTransProbs", ] @@ -114,75 +112,6 @@ def calculate( return stimulated_emission_factor -class TauSobolev(ProcessingPlasmaProperty): - """ - Attributes - ---------- - tau_sobolev : Pandas DataFrame, dtype float - Sobolev optical depth for each line. Indexed by line. - Columns as zones. - """ - - outputs = ("tau_sobolevs",) - latex_name = (r"\tau_{\textrm{sobolev}}",) - latex_formula = ( - r"\dfrac{\pi e^{2}}{m_{e} c}f_{lu}\lambda t_{exp}\ - n_{lower} \Big(1-\dfrac{g_{lower}n_{upper}}{g_{upper}n_{lower}}\Big)", - ) - - def __init__(self, plasma_parent): - super(TauSobolev, self).__init__(plasma_parent) - self.sobolev_coefficient = ( - ( - ((np.pi * const.e.gauss ** 2) / (const.m_e.cgs * const.c.cgs)) - * u.cm - * u.s - / u.cm ** 3 - ) - .to(1) - .value - ) - - def calculate( - self, - lines, - level_number_density, - lines_lower_level_index, - time_explosion, - stimulated_emission_factor, - j_blues, - f_lu, - wavelength_cm, - ): - f_lu = f_lu.values[np.newaxis].T - wavelength = wavelength_cm.values[np.newaxis].T - n_lower = level_number_density.values.take( - lines_lower_level_index, axis=0, mode="raise" - ) - tau_sobolevs = ( - self.sobolev_coefficient - * f_lu - * wavelength - * time_explosion - * n_lower - * stimulated_emission_factor - ) - - if np.any(np.isnan(tau_sobolevs)) or np.any( - np.isinf(np.abs(tau_sobolevs)) - ): - raise ValueError( - "Some tau_sobolevs are nan, inf, -inf in tau_sobolevs." - " Something went wrong!" - ) - - return pd.DataFrame( - tau_sobolevs, - index=lines.index, - columns=np.array(level_number_density.columns), - ) - - class BetaSobolev(ProcessingPlasmaProperty): """ Attributes @@ -223,139 +152,6 @@ def calculate_beta_sobolev(tau_sobolevs, beta_sobolevs): return beta_sobolevs -class TransitionProbabilities(ProcessingPlasmaProperty): - """ - Attributes - ---------- - transition_probabilities : Pandas DataFrame, dtype float - """ - - outputs = ("transition_probabilities",) - - def __init__(self, plasma_parent): - super(TransitionProbabilities, self).__init__(plasma_parent) - self.initialize = True - self.normalize = True - - def calculate( - self, - atomic_data, - beta_sobolev, - j_blues, - stimulated_emission_factor, - tau_sobolevs, - ): - # I wonder why? - # Not sure who wrote this but the answer is that when the plasma is - # first initialised (before the first iteration, without temperature - # values etc.) there are no j_blues values so this just prevents - # an error. Aoife. - if len(j_blues) == 0: - return None - macro_atom_data = self._get_macro_atom_data(atomic_data) - if self.initialize: - self.initialize_macro_atom_transition_type_filters( - atomic_data, macro_atom_data - ) - self.transition_probability_coef = ( - self._get_transition_probability_coefs(macro_atom_data) - ) - self.initialize = False - transition_probabilities = self._calculate_transition_probability( - macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor - ) - transition_probabilities = pd.DataFrame( - transition_probabilities, - index=macro_atom_data.transition_line_id, - columns=tau_sobolevs.columns, - ) - return transition_probabilities - - def _calculate_transition_probability( - self, macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor - ): - transition_probabilities = np.empty( - (self.transition_probability_coef.shape[0], beta_sobolev.shape[1]) - ) - # trans_old = self.calculate_transition_probabilities(macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor) - transition_type = macro_atom_data.transition_type.values - lines_idx = macro_atom_data.lines_idx.values - tpos = macro_atom_data.transition_probability.values - macro_atom.calculate_transition_probabilities( - tpos, - beta_sobolev.values, - j_blues.values, - stimulated_emission_factor, - transition_type, - lines_idx, - self.block_references, - transition_probabilities, - self.normalize, - ) - return transition_probabilities - - def calculate_transition_probabilities( - self, macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor - ): - transition_probabilities = self.prepare_transition_probabilities( - macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor - ) - return transition_probabilities - - def initialize_macro_atom_transition_type_filters( - self, atomic_data, macro_atom_data - ): - self.transition_up_filter = macro_atom_data.transition_type.values == 1 - self.transition_up_line_filter = macro_atom_data.lines_idx.values[ - self.transition_up_filter - ] - self.block_references = np.hstack( - ( - atomic_data.macro_atom_references.block_references, - len(macro_atom_data), - ) - ) - - @staticmethod - def _get_transition_probability_coefs(macro_atom_data): - return macro_atom_data.transition_probability.values[np.newaxis].T - - def prepare_transition_probabilities( - self, macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor - ): - current_beta_sobolev = beta_sobolev.values.take( - macro_atom_data.lines_idx.values, axis=0, mode="raise" - ) - transition_probabilities = ( - self.transition_probability_coef * current_beta_sobolev - ) - j_blues = j_blues.take( - self.transition_up_line_filter, axis=0, mode="raise" - ) - macro_stimulated_emission = stimulated_emission_factor.take( - self.transition_up_line_filter, axis=0, mode="raise" - ) - transition_probabilities[self.transition_up_filter] *= ( - j_blues * macro_stimulated_emission - ) - return transition_probabilities - - def _normalize_transition_probabilities(self, transition_probabilities): - macro_atom.normalize_transition_probabilities( - transition_probabilities, self.block_references - ) - - @staticmethod - def _get_macro_atom_data(atomic_data): - try: - return atomic_data.macro_atom_data - except: - logger.debug( - "Macro Atom Data was not found. Instead returning All Macro Atom Data" - ) - return atomic_data.macro_atom_data_all - - class RawRadBoundBoundTransProbs( TransitionProbabilities, TransitionProbabilitiesProperty ): diff --git a/tardis/plasma/properties/rate_matrix_index.py b/tardis/plasma/properties/rate_matrix_index.py new file mode 100644 index 00000000000..ab16121b57f --- /dev/null +++ b/tardis/plasma/properties/rate_matrix_index.py @@ -0,0 +1,65 @@ +import pandas as pd +from tardis.plasma.properties.base import ProcessingPlasmaProperty + +__all__ = [ + "NLTEIndexHelper", +] + + +class NLTEIndexHelper(ProcessingPlasmaProperty): + outputs = ("rate_matrix_index",) + + def __init__( + self, + plasma_parent, + nlte_ionization_species=0, + nlte_excitation_species=0, + ): + super().__init__(plasma_parent) + self.nlte_ionization_species = nlte_ionization_species + self.nlte_excitation_species = nlte_excitation_species + + def calculate( + self, levels, nlte_ionization_species, nlte_excitation_species + ): + """Generates rate_matrix_index using levels and changing the last index(level) to + "lte_ion" if that ion_number is treated in LTE or nebular, "nlte_ion" for NLTE ionization and + keeps the levels for the rest. + + Parameters + ---------- + levels : MultiIndex + (Atomic number, Ion number, Level) + nlte_ionization_species : list + List of tuples for (atomic number, ion number) which are treated in NLTE ionization. + + Returns + ------- + MultiIndex + """ + nlte_excitation_species = [] # not yet implemented + rate_matrix_index = pd.MultiIndex.from_tuples( + list( + self.calculate_rate_matrix_index( + levels, + nlte_ionization_species, + nlte_excitation_species, + ) + ), + names=levels.names, + ).drop_duplicates() + return rate_matrix_index + + def calculate_rate_matrix_index( + self, levels, nlte_ionization_species, nlte_excitation_species=[] + ): + for level in levels: + if level[:2] in nlte_ionization_species: + yield (*level[:2], "nlte_ion") + elif (level[:2] not in nlte_ionization_species) and ( + level[:2] not in nlte_excitation_species + ): + yield (*level[:2], "lte_ion") + else: + yield level + yield ("n_e", "n_e", "n_e") diff --git a/tardis/plasma/properties/transition_probabilities.py b/tardis/plasma/properties/transition_probabilities.py deleted file mode 100644 index 66102e5958b..00000000000 --- a/tardis/plasma/properties/transition_probabilities.py +++ /dev/null @@ -1,218 +0,0 @@ -import logging - -import numpy as np -import pandas as pd - -from scipy import sparse as sp - -from tardis.plasma.properties.base import ProcessingPlasmaProperty -from tardis.plasma.properties.continuum_processes import ( - get_ground_state_multi_index, -) - -__all__ = [ - "MarkovChainTransProbs", - "MarkovChainIndex", - "MarkovChainTransProbsCollector", -] - -logger = logging.getLogger(__name__) - - -def normalize_trans_probs(p): - """ - Normalize a set of transition probabilities. - - Parameters - ---------- - p : pandas.DataFrame, dtype float - Unnormalized transition probabilities. Indexed by - source_level_idx, destination_level_idx. - - Returns - ------- - pandas.DataFrame, dtype float - Normalized transition probabilities: the sum of - all probabilites with the same source_level_idx sum to one. - Indexed by source_level_idx, destination_level_idx. - """ - p_summed = p.groupby(level=0).sum() - index = p.index.get_level_values("source_level_idx") - p_norm = p / p_summed.loc[index].values - p_norm = p_norm.fillna(0.0) - return p_norm - - -class SpMatrixSeriesConverterMixin(object): - @staticmethod - def series2matrix(series, idx2reduced_idx): - """ - Convert a Pandas Series to a sparse matrix and re-index it. - - Parameters - ---------- - series : pandas.Series, dtype float - Rates or transition probabilities. Indexed by - source_level_idx, destination_level_idx. - idx2reduced_idx : pandas.Series - Values of (compact) matrix index. Indexed by references_idx. - Maps the references_idx of a level to the index - used in the sparse matrix. - - Returns - ------- - scipy.sparse.coo.coo_matrix - Sparse matrix of rates or transition probabilites. - """ - q_indices = ( - series.index.get_level_values(0), - series.index.get_level_values(1), - ) - q_indices = ( - idx2reduced_idx.loc[q_indices[0]].values, - idx2reduced_idx.loc[q_indices[1]].values, - ) - max_idx = idx2reduced_idx.max() + 1 - matrix = sp.coo_matrix((series, q_indices), shape=(max_idx, max_idx)) - return matrix - - @staticmethod - def matrix2series(matrix, idx2reduced_idx, names=None): - """ - Convert a sparse matrix to a Pandas Series and index it. - - Parameters - ---------- - matrix : scipy.sparse.coo.coo_matrix - Sparse matrix of rates or transition probabilites. - idx2reduced_idx : pandas.Series - Values of (compact) matrix index. Indexed by references_idx. - Maps the references_idx of a level to the index - used in the sparse matrix. - names : array-like, optional - Names of levels in MultiIndex of returned Series. - - Returns - ------- - pandas.Series - Rates or transition probabilities. Indexed by - source_level_idx, destination_level_idx. - """ - reduced_idx2idx = pd.Series( - idx2reduced_idx.index, index=idx2reduced_idx - ) - matrix = matrix.tocoo() - index = pd.MultiIndex.from_arrays( - [reduced_idx2idx.loc[matrix.row], reduced_idx2idx.loc[matrix.col]] - ) - series = pd.Series(matrix.data, index=index) - if names: - series.index.names = names - return series - - -class MarkovChainIndex(ProcessingPlasmaProperty): - """ - Attributes - ---------- - idx2mkv_idx : pandas.Series, dtype int - """ - - outputs = ("idx2mkv_idx",) - - def calculate(self, atomic_data, continuum_interaction_species): - ma_ref = atomic_data.macro_atom_references - mask = ma_ref.index.droplevel("source_level_number").isin( - continuum_interaction_species - ) - mask2 = ma_ref.index.isin( - get_ground_state_multi_index(continuum_interaction_species) - ) - mask = np.logical_or(mask, mask2) - idx = ma_ref[mask].references_idx.values - idx2mkv_idx = pd.Series(np.arange(len(idx)), index=idx) - idx2mkv_idx.loc["k"] = idx2mkv_idx.max() + 1 - return idx2mkv_idx - - -class MarkovChainTransProbsCollector(ProcessingPlasmaProperty): - """ - Attributes - ---------- - p_combined : pandas.DataFrame, dtype float - Combined and normalized transition probabilities. - Indexed by source_level_idx, destination_level_idx. - """ - - outputs = ("p_combined",) - - def __init__(self, plasma_parent, inputs): - super().__init__(plasma_parent) - self.inputs = inputs - - def calculate(self, *args): - p = pd.concat(args) - p = p.groupby(level=[0, 1, 2]).sum() - p = normalize_trans_probs(p) - return p - - -class MarkovChainTransProbs( - ProcessingPlasmaProperty, SpMatrixSeriesConverterMixin -): - outputs = ("N", "R", "B", "p_deactivation") - latex_name = ("N", "R", "B", r"p_\textrm{deactivation}") - """ - Attributes - ---------- - N : pandas.DataFrame, dtype float - Fundamental matrix of the Markov-chain macro atom. - Indexed by source_level_idx, destination_level_idx. - Expected number of visits to destination_level_idx starting - from souce_level_idx (before being absorbed). - R : pandas.DataFrame, dtype float - Deactivation probabilities of the Markov-chain macro atom. - Indexed by source_level_idx. - Probability of deactivation/absorption in source_level_idx. - B : pandas.DataFrame, dtype float - Absorbing probabilities of the Markov-chain macro atom. - Indexed by source_level_idx, destination_level_idx. - Probability of being absorbed in destination_level_idx when - starting from source_level_idx. - p_deactivation : pandas.DataFrame, dtype float - Redistribution probabilities after deactivation of the Markov-chain - macro atom. Indexed by source_level_idx, destination_level_idx. - Probability of an r-packet being emitted in the transition - (source_level_idx --> destination_level_idx) after deactivation - in source_level_idx. - """ - - def calculate(self, p_combined, idx2mkv_idx): - p = p_combined - p_internal = p.xs(0, level="transition_type") - p_deactivation = normalize_trans_probs( - p.xs(-1, level="transition_type") - ) - - N = pd.DataFrame(columns=p_internal.columns) - B = pd.DataFrame(columns=p_internal.columns) - R = pd.DataFrame(columns=p_internal.columns, index=idx2mkv_idx.index) - R.index.name = "source_level_idx" - for column in p_internal: - Q = self.series2matrix(p_internal[column], idx2mkv_idx) - inv_N = sp.identity(Q.shape[0]) - Q - N1 = sp.linalg.inv(inv_N.tocsc()) - R1 = (1 - np.asarray(Q.sum(axis=1))).flatten() - B1 = N1.multiply(R1) - N1 = self.matrix2series( - N1, idx2mkv_idx, names=p_internal.index.names - ) - B1 = self.matrix2series( - B1, idx2mkv_idx, names=p_internal.index.names - ) - N[column] = N1 - B[column] = B1 - R[column] = R1 - N = N.sort_index() - B = B.sort_index() - return N, R, B, p_deactivation diff --git a/tardis/plasma/properties/util/__init__.py b/tardis/plasma/properties/util/__init__.py index 8b137891791..9aec5b1c60a 100644 --- a/tardis/plasma/properties/util/__init__.py +++ b/tardis/plasma/properties/util/__init__.py @@ -1 +1,3 @@ - +""" +Calculating transition probabilities for macro_atom interactions. +""" diff --git a/tardis/plasma/properties/util/integrate_array_by_blocks.py b/tardis/plasma/properties/util/integrate_array_by_blocks.py new file mode 100644 index 00000000000..3573b0f6447 --- /dev/null +++ b/tardis/plasma/properties/util/integrate_array_by_blocks.py @@ -0,0 +1,35 @@ +import numpy as np +from numba import njit, prange + +from tardis.transport.montecarlo import njit_dict + + +@njit(**njit_dict) +def integrate_array_by_blocks(f, x, block_references): + """ + Integrate a function over blocks. + + This function integrates a function `f` defined at locations `x` + over blocks given in `block_references`. + + Parameters + ---------- + f : numpy.ndarray, dtype float + 2D input array to integrate. + x : numpy.ndarray, dtype float + 1D array with the sample points corresponding to the `f` values. + block_references : numpy.ndarray, dtype int + 1D array with the start indices of the blocks to be integrated. + + Returns + ------- + numpy.ndarray, dtype float + 2D array with integrated values. + """ + integrated = np.zeros((len(block_references) - 1, f.shape[1])) + for i in prange(f.shape[1]): # columns + for j in prange(len(integrated)): # rows + start = block_references[j] + stop = block_references[j + 1] + integrated[j, i] = np.trapz(f[start:stop, i], x[start:stop]) + return integrated diff --git a/tardis/plasma/standard_plasmas.py b/tardis/plasma/standard_plasmas.py index 5e2fe4a8f9a..2a72c5eb6fa 100644 --- a/tardis/plasma/standard_plasmas.py +++ b/tardis/plasma/standard_plasmas.py @@ -1,60 +1,66 @@ -import os import logging import numpy as np import pandas as pd +from astropy import units as u -from tardis.io.atom_data import AtomData -from tardis.util.base import species_string_to_tuple from tardis.plasma import BasePlasma +from tardis.plasma.exceptions import PlasmaConfigError +from tardis.plasma.properties import ( + HeliumNumericalNLTE, + IonNumberDensity, + IonNumberDensityHeNLTE, + JBluesBlackBody, + JBluesDetailed, + JBluesDiluteBlackBody, + LevelBoltzmannFactorNLTE, + MarkovChainTransProbsCollector, + RadiationFieldCorrection, + StimulatedEmissionFactor, +) from tardis.plasma.properties.base import TransitionProbabilitiesProperty +from tardis.plasma.properties.level_population import LevelNumberDensity +from tardis.plasma.properties.nlte_rate_equation_solver import ( + NLTEPopulationSolverLU, + NLTEPopulationSolverRoot, +) from tardis.plasma.properties.property_collections import ( + adiabatic_cooling_properties, basic_inputs, basic_properties, + continuum_interaction_inputs, + continuum_interaction_properties, + detailed_j_blues_inputs, + detailed_j_blues_properties, + dilute_lte_excitation_properties, + helium_lte_properties, + helium_nlte_properties, + helium_numerical_nlte_properties, lte_excitation_properties, lte_ionization_properties, macro_atom_properties, - dilute_lte_excitation_properties, nebular_ionization_properties, - non_nlte_properties, + nlte_lu_solver_properties, nlte_properties, - helium_nlte_properties, - helium_numerical_nlte_properties, - helium_lte_properties, - detailed_j_blues_properties, - detailed_j_blues_inputs, - continuum_interaction_properties, - continuum_interaction_inputs, - adiabatic_cooling_properties, + nlte_root_solver_properties, + non_nlte_properties, two_photon_properties, ) -from tardis.plasma.exceptions import PlasmaConfigError - -from tardis.plasma.properties import ( - LevelBoltzmannFactorNLTE, - JBluesBlackBody, - JBluesDiluteBlackBody, - JBluesDetailed, - RadiationFieldCorrection, - StimulatedEmissionFactor, - HeliumNumericalNLTE, - IonNumberDensity, - IonNumberDensityHeNLTE, - MarkovChainTransProbsCollector, -) +from tardis.plasma.properties.rate_matrix_index import NLTEIndexHelper +from tardis.util.base import species_string_to_tuple logger = logging.getLogger(__name__) -def assemble_plasma(config, model, atom_data=None): +def assemble_plasma(config, simulation_state, atom_data=None): """ Create a BasePlasma instance from a Configuration object - and a Radial1DModel. + and a SimulationState. Parameters ---------- config : io.config_reader.Configuration - model : model.Radial1DModel + simulation_state : model.SimulationState atom_data : atomic.AtomData If None, an attempt will be made to read the atomic data from config. @@ -78,33 +84,10 @@ def assemble_plasma(config, model, atom_data=None): continuum_interaction_species, names=["atomic_number", "ion_number"] ) - if atom_data is None: - if "atom_data" in config: - if os.path.isabs(config.atom_data): - atom_data_fname = config.atom_data - else: - atom_data_fname = os.path.join( - config.config_dirname, config.atom_data - ) - else: - raise ValueError("No atom_data option found in the configuration.") - - logger.info(f"Reading Atomic Data from {atom_data_fname}") - - try: - atom_data = AtomData.from_hdf(atom_data_fname) - except TypeError as e: - print( - e, - "Error might be from the use of an old-format of the atomic database, \n" - "please see https://github.com/tardis-sn/tardis-refdata/tree/master/atom_data" - " for the most recent version.", - ) - raise - atom_data.prepare_atom_data( - model.abundance.index, + simulation_state.abundance.index, line_interaction_type=config.plasma.line_interaction_type, + continuum_interaction_species=continuum_interaction_species, nlte_species=nlte_species, ) @@ -122,25 +105,36 @@ def assemble_plasma(config, model, atom_data=None): "in the configuration." ) + nlte_ionization_species = [ + species_string_to_tuple(s) + for s in config.plasma.nlte_ionization_species + ] + nlte_excitation_species = [ + species_string_to_tuple(s) + for s in config.plasma.nlte_excitation_species + ] + kwargs = dict( - t_rad=model.t_radiative, - abundance=model.abundance, - density=model.density, + t_rad=simulation_state.t_radiative, + abundance=simulation_state.abundance, + number_density=simulation_state.elemental_number_density, atomic_data=atom_data, - time_explosion=model.time_explosion, - w=model.dilution_factor, - link_t_rad_t_electron=0.9, + time_explosion=simulation_state.time_explosion, + w=simulation_state.dilution_factor, + link_t_rad_t_electron=config.plasma.link_t_rad_t_electron, continuum_interaction_species=continuum_interaction_species, + nlte_ionization_species=nlte_ionization_species, + nlte_excitation_species=nlte_excitation_species, ) plasma_modules = basic_inputs + basic_properties property_kwargs = {} - if config.plasma.continuum_interaction.species: + if len(config.plasma.continuum_interaction.species) > 0: line_interaction_type = config.plasma.line_interaction_type if line_interaction_type != "macroatom": raise PlasmaConfigError( "Continuum interactions require line_interaction_type " - "macroatom (instead of {}).".format(line_interaction_type) + f"macroatom (instead of {line_interaction_type})." ) plasma_modules += continuum_interaction_properties @@ -166,14 +160,54 @@ def assemble_plasma(config, model, atom_data=None): property_kwargs[MarkovChainTransProbsCollector] = { "inputs": transition_probabilities_outputs } + if ( + config.plasma.nlte_ionization_species + or config.plasma.nlte_excitation_species + ): + if config.plasma.nlte_ionization_species: + nlte_ionization_species = config.plasma.nlte_ionization_species + for species in nlte_ionization_species: + if ( + species + not in config.plasma.continuum_interaction.species + ): + raise PlasmaConfigError( + f"NLTE ionization species {species} not in continuum species." + ) + if config.plasma.nlte_excitation_species: + nlte_excitation_species = config.plasma.nlte_excitation_species + for species in nlte_excitation_species: + if ( + species + not in config.plasma.continuum_interaction.species + ): + raise PlasmaConfigError( + f"NLTE excitation species {species} not in continuum species." + ) + property_kwargs[NLTEIndexHelper] = { + "nlte_ionization_species": config.plasma.nlte_ionization_species, + "nlte_excitation_species": config.plasma.nlte_excitation_species, + } + if config.plasma.nlte_solver == "lu": + plasma_modules += nlte_lu_solver_properties + logger.warning( + "LU solver will be inaccurate for NLTE excitation, proceed with caution." + ) + elif config.plasma.nlte_solver == "root": + plasma_modules += nlte_root_solver_properties + else: + raise PlasmaConfigError( + f"NLTE solver type unknown - {config.plasma.nlte_solver}" + ) kwargs.update( gamma_estimator=None, bf_heating_coeff_estimator=None, + stim_recomb_cooling_coeff_estimator=None, alpha_stim_estimator=None, - volume=model.volume, - r_inner=model.r_inner, - t_inner=model.t_inner, + volume=simulation_state.volume, + r_inner=simulation_state.r_inner.to(u.cm), + t_inner=simulation_state.t_inner, ) if config.plasma.radiative_rates_type == "blackbody": plasma_modules.append(JBluesBlackBody) @@ -182,9 +216,9 @@ def assemble_plasma(config, model, atom_data=None): elif config.plasma.radiative_rates_type == "detailed": plasma_modules += detailed_j_blues_properties + detailed_j_blues_inputs kwargs.update( - r_inner=model.r_inner, - t_inner=model.t_inner, - volume=model.volume, + r_inner=simulation_state.r_inner.to(u.cm), + t_inner=simulation_state.t_inner, + volume=simulation_state.volume, j_blue_estimator=None, ) property_kwargs[JBluesDetailed] = {"w_epsilon": config.plasma.w_epsilon} @@ -214,13 +248,34 @@ def assemble_plasma(config, model, atom_data=None): plasma_modules += non_nlte_properties if config.plasma.line_interaction_type in ("downbranch", "macroatom"): - plasma_modules += macro_atom_properties + if not config.plasma.continuum_interaction.species: + plasma_modules += macro_atom_properties if "delta_treatment" in config.plasma: property_kwargs[RadiationFieldCorrection] = dict( delta_treatment=config.plasma.delta_treatment ) + if ( + config.plasma.helium_treatment == "recomb-nlte" + or config.plasma.helium_treatment == "numerical-nlte" + ) and ( + config.plasma.nlte_ionization_species + or config.plasma.nlte_excitation_species + ): + # Prevent the user from using helium NLTE treatment with + # NLTE ionization and excitation treatment. This is because + # the helium_nlte_properties could overwrite the NLTE ionization + # and excitation ion number and electron densities. + # helium_numerical_nlte_properties is also included here because + # it is currently in the same if else block, and thus may block + # the addition of the components from the else block. + raise PlasmaConfigError( + "Helium NLTE treatment is incompatible with the NLTE eonization and excitation treatment." + ) + + # TODO: Disentangle these if else block such that compatible components + # can be added independently. if config.plasma.helium_treatment == "recomb-nlte": plasma_modules += helium_nlte_properties elif config.plasma.helium_treatment == "numerical-nlte": @@ -233,14 +288,39 @@ def assemble_plasma(config, model, atom_data=None): heating_rate_data_file=config.plasma.heating_rate_data_file ) else: - plasma_modules += helium_lte_properties + # If nlte ionization species are present, we don't want to add the + # IonNumberDensity from helium_lte_properties, since we want + # to use the IonNumberDensity provided by the NLTE solver. + if ( + config.plasma.nlte_ionization_species + or config.plasma.nlte_excitation_species + ): + plasma_modules += [LevelNumberDensity] + else: + plasma_modules += helium_lte_properties - if model._electron_densities: - electron_densities = pd.Series(model._electron_densities.cgs.value) + if simulation_state._electron_densities is not None: + electron_densities = pd.Series( + simulation_state._electron_densities.cgs.value + ) if config.plasma.helium_treatment == "numerical-nlte": property_kwargs[IonNumberDensityHeNLTE] = dict( electron_densities=electron_densities ) + elif ( + config.plasma.nlte_ionization_species + or config.plasma.nlte_excitation_species + ) and config.plasma.nlte_solver == "root": + property_kwargs[NLTEPopulationSolverRoot] = dict( + electron_densities=electron_densities + ) + elif ( + config.plasma.nlte_ionization_species + or config.plasma.nlte_excitation_species + ) and config.plasma.nlte_solver == "lu": + property_kwargs[NLTEPopulationSolverLU] = dict( + electron_densities=electron_densities + ) else: property_kwargs[IonNumberDensity] = dict( electron_densities=electron_densities diff --git a/tardis/plasma/tests/data/config_init_trad.yml b/tardis/plasma/tests/data/config_init_trad.yml index 9d36e8a4102..a7ecefcd289 100755 --- a/tardis/plasma/tests/data/config_init_trad.yml +++ b/tardis/plasma/tests/data/config_init_trad.yml @@ -59,7 +59,7 @@ montecarlo: # threads is used or the number specified in the OMP_NUM_THREADS environment # variable # -------- - nthreads: 16 + nthreads: 1 last_no_of_packets: 1.e+5 no_of_virtual_packets: 10 diff --git a/tardis/plasma/tests/data/plasma_base_test_config.yml b/tardis/plasma/tests/data/plasma_base_test_config.yml index f17612618da..b8e06f580e8 100644 --- a/tardis/plasma/tests/data/plasma_base_test_config.yml +++ b/tardis/plasma/tests/data/plasma_base_test_config.yml @@ -7,18 +7,14 @@ supernova: atom_data: kurucz_atom_pure_simple.h5 model: - structure: type: specific - velocity: start: 1.1e4 km/s stop: 2.0e4 km/s num: 20 - density: type: branch85_w7 - abundances: type: uniform He: 1 diff --git a/tardis/plasma/tests/test_complete_plasmas.py b/tardis/plasma/tests/test_complete_plasmas.py index b5e7e645806..a28aeba63e8 100644 --- a/tardis/plasma/tests/test_complete_plasmas.py +++ b/tardis/plasma/tests/test_complete_plasmas.py @@ -1,12 +1,19 @@ -import os import warnings +from pathlib import Path import pandas as pd import pytest -from pandas.util import testing as pdt -from numpy.testing import assert_almost_equal -from tardis.io.config_reader import Configuration +from numpy import testing as npt +from pandas import testing as pdt + +from tardis.io.configuration.config_reader import Configuration from tardis.simulation import Simulation +from tardis.tests.fixtures.regression_data import RegressionData + +PLASMA_CONFIG_FPATH = ( + Path("tardis") / "plasma" / "tests" / "data" / "plasma_base_test_config.yml" +) + ionization = [ {"ionization": "nebular"}, @@ -48,7 +55,7 @@ {"helium_treatment": "recomb-nlte", "delta_treatment": 0.5}, ] -config_list = ( +CONFIG_LIST = ( ionization + excitation + radiative_rates_type @@ -66,10 +73,11 @@ def idfn(fixture_value): This function creates a string from a dictionary. We use it to obtain a readable name for the config fixture. """ - return str("-".join([f"{k}:{v}" for k, v in fixture_value.items()])) + return "-".join([f"{k}:{v}" for k, v in fixture_value.items()]) -class TestPlasma(object): +class TestPlasma: + regression_data = None general_properties = [ "beta_rad", @@ -129,16 +137,11 @@ class TestPlasma(object): @pytest.fixture(scope="class") def chianti_he_db_fpath(self, tardis_ref_path): - return os.path.abspath( - os.path.join(tardis_ref_path, "atom_data", "chianti_He.h5") - ) + return (tardis_ref_path / "atom_data" / "chianti_He.h5").absolute() - @pytest.fixture(scope="class", params=config_list, ids=idfn) + @pytest.fixture(scope="class", params=CONFIG_LIST, ids=idfn) def config(self, request): - config_path = os.path.join( - "tardis", "plasma", "tests", "data", "plasma_base_test_config.yml" - ) - config = Configuration.from_yaml(config_path) + config = Configuration.from_yaml(PLASMA_CONFIG_FPATH) hash_string = "" for prop, value in request.param.items(): hash_string = "_".join((hash_string, prop)) @@ -150,59 +153,70 @@ def config(self, request): else: config.plasma[prop] = value hash_string = "_".join((hash_string, str(value))) - hash_string = os.path.join("plasma_unittest", hash_string) - setattr(config.plasma, "save_path", hash_string) + hash_string = f"plasma_unittest{hash_string}" + config.plasma.save_path = hash_string + request.cls.regression_data = RegressionData(request) + request.cls.regression_data.fname = f"{hash_string}.h5" return config @pytest.fixture(scope="class") - def plasma(self, request, chianti_he_db_fpath, config, tardis_ref_data): - config["atom_data"] = chianti_he_db_fpath + def plasma( + self, + chianti_he_db_fpath, + config, + ): + config["atom_data"] = str(chianti_he_db_fpath) sim = Simulation.from_config(config) - if request.config.getoption("--generate-reference"): - sim.plasma.to_hdf( - tardis_ref_data, path=config.plasma.save_path, overwrite=True - ) - pytest.skip(f"Reference data saved at {tardis_ref_data}") + self.regression_data.sync_hdf_store(sim.plasma, update_fname=False) return sim.plasma @pytest.mark.parametrize("attr", combined_properties) - def test_plasma_properties(self, plasma, tardis_ref_data, config, attr): + def test_plasma_properties(self, plasma, attr): + key = f"plasma/{attr}" + try: + expected = pd.read_hdf(self.regression_data.fpath, key) + except KeyError: + pytest.skip(f"Key {key} not found in regression data") + if hasattr(plasma, attr): actual = getattr(plasma, attr) - if actual.ndim == 1: + if attr == "selected_atoms": + npt.assert_allclose(actual.values, expected.values) + elif actual.ndim == 1: actual = pd.Series(actual) + pdt.assert_series_equal(actual, expected) else: actual = pd.DataFrame(actual) - key = os.path.join(config.plasma.save_path, "plasma", attr) - expected = tardis_ref_data[key] - pdt.assert_almost_equal(actual, expected) + pdt.assert_frame_equal(actual, expected) else: warnings.warn(f'Property "{attr}" not found') - def test_levels(self, plasma, tardis_ref_data, config): + def test_levels(self, plasma): actual = pd.DataFrame(plasma.levels) - key = os.path.join(config.plasma.save_path, "plasma", "levels") - expected = tardis_ref_data[key] - pdt.assert_almost_equal(actual, expected) + key = "plasma/levels" + expected = pd.read_hdf(self.regression_data.fpath, key) + pdt.assert_frame_equal(actual, expected) @pytest.mark.parametrize("attr", scalars_properties) - def test_scalars_properties(self, plasma, tardis_ref_data, config, attr): + def test_scalars_properties(self, plasma, attr): actual = getattr(plasma, attr) if hasattr(actual, "cgs"): actual = actual.cgs.value - key = os.path.join(config.plasma.save_path, "plasma", "scalars") - expected = tardis_ref_data[key][attr] - pdt.assert_almost_equal(actual, expected) + key = "plasma/scalars" + expected = pd.read_hdf(self.regression_data.fpath, key)[attr] + npt.assert_equal(actual, expected) - def test_helium_treatment(self, plasma, tardis_ref_data, config): + def test_helium_treatment(self, plasma): actual = plasma.helium_treatment - key = os.path.join(config.plasma.save_path, "plasma", "scalars") - expected = tardis_ref_data[key]["helium_treatment"] + key = "plasma/scalars" + expected = pd.read_hdf(self.regression_data.fpath, key)[ + "helium_treatment" + ] assert actual == expected - def test_zeta_data(self, plasma, tardis_ref_data, config): + def test_zeta_data(self, plasma): if hasattr(plasma, "zeta_data"): actual = plasma.zeta_data - key = os.path.join(config.plasma.save_path, "plasma", "zeta_data") - expected = tardis_ref_data[key] - assert_almost_equal(actual, expected.values) + key = "plasma/zeta_data" + expected = pd.read_hdf(self.regression_data.fpath, key) + npt.assert_allclose(actual, expected.values) diff --git a/tardis/plasma/tests/test_hdf_plasma.py b/tardis/plasma/tests/test_hdf_plasma.py index 028ab4f40d1..13169bdfa4e 100644 --- a/tardis/plasma/tests/test_hdf_plasma.py +++ b/tardis/plasma/tests/test_hdf_plasma.py @@ -1,20 +1,13 @@ -import os -import pandas as pd +import numpy as np +import numpy.testing as npt +import pandas.testing as pdt import pytest -import pandas.util.testing as pdt -from numpy.testing import assert_almost_equal -from tardis.plasma.properties import property_collections ### # saving and loading of plasma properties in the HDF file ### -@pytest.fixture(scope="module", autouse=True) -def to_hdf_buffer(hdf_file_path, simulation_verysimple): - simulation_verysimple.plasma.to_hdf(hdf_file_path, overwrite=True) - - plasma_properties_list = [ "number_density", "beta_rad", @@ -52,70 +45,54 @@ def to_hdf_buffer(hdf_file_path, simulation_verysimple): @pytest.mark.parametrize("attr", plasma_properties_list) -def test_hdf_plasma(hdf_file_path, simulation_verysimple, attr): +def test_hdf_plasma(simulation_verysimple, attr, regression_data): if hasattr(simulation_verysimple.plasma, attr): actual = getattr(simulation_verysimple.plasma, attr) + expected = regression_data.sync_ndarray(actual) if hasattr(actual, "cgs"): actual = actual.cgs.value - path = os.path.join("plasma", attr) - expected = pd.read_hdf(hdf_file_path, path) - assert_almost_equal(actual, expected.values) + npt.assert_allclose(actual, expected) -def test_hdf_levels(hdf_file_path, simulation_verysimple): - actual = getattr(simulation_verysimple.plasma, "levels") +def test_hdf_levels(simulation_verysimple, regression_data): + actual = simulation_verysimple.plasma.levels.to_frame() + expected = regression_data.sync_dataframe(actual) if hasattr(actual, "cgs"): - actual = actual.cgs.value - path = os.path.join("plasma", "levels") - expected = pd.read_hdf(hdf_file_path, path) - pdt.assert_almost_equal(pd.DataFrame(actual), expected) + raise ValueError("should not ever happen") + pdt.assert_frame_equal(actual, expected) -scalars_list = ["time_explosion", "link_t_rad_t_electron"] +SCALARS_LIST = ["time_explosion", "link_t_rad_t_electron"] -@pytest.mark.parametrize("attr", scalars_list) -def test_hdf_scalars(hdf_file_path, simulation_verysimple, attr): +@pytest.mark.parametrize("attr", SCALARS_LIST) +def test_hdf_scalars(simulation_verysimple, attr, regression_data): actual = getattr(simulation_verysimple.plasma, attr) if hasattr(actual, "cgs"): actual = actual.cgs.value - path = os.path.join("plasma", "scalars") - expected = pd.read_hdf(hdf_file_path, path)[attr] - assert_almost_equal(actual, expected) + expected = regression_data.sync_ndarray(actual) + npt.assert_allclose(actual, expected) -def test_hdf_helium_treatment(hdf_file_path, simulation_verysimple): - actual = getattr(simulation_verysimple.plasma, "helium_treatment") - path = os.path.join("plasma", "scalars") - expected = pd.read_hdf(hdf_file_path, path)["helium_treatment"] +def test_hdf_helium_treatment(simulation_verysimple, regression_data): + actual = simulation_verysimple.plasma.helium_treatment + expected = regression_data.sync_str(actual) assert actual == expected -def test_atomic_data_uuid(hdf_file_path, simulation_verysimple): - actual = getattr(simulation_verysimple.plasma.atomic_data, "uuid1") - path = os.path.join("plasma", "scalars") - expected = pd.read_hdf(hdf_file_path, path)["atom_data_uuid"] +def test_atomic_data_uuid(simulation_verysimple, regression_data): + actual = simulation_verysimple.plasma.atomic_data.uuid1 + expected = regression_data.sync_str(actual) assert actual == expected -@pytest.fixture(scope="module", autouse=True) -def to_hdf_collection_buffer(hdf_file_path, simulation_verysimple): - simulation_verysimple.plasma.to_hdf( - hdf_file_path, - name="collection", - collection=property_collections.basic_inputs, - overwrite=True, - ) - - -collection_properties = ["t_rad", "w", "density"] +COLLECTION_PROPERTIES = ["t_rad", "w"] -@pytest.mark.parametrize("attr", collection_properties) -def test_collection(hdf_file_path, simulation_verysimple, attr): +@pytest.mark.parametrize("attr", COLLECTION_PROPERTIES) +def test_collection(simulation_verysimple, attr, regression_data): actual = getattr(simulation_verysimple.plasma, attr) + expected = regression_data.sync_ndarray(actual) if hasattr(actual, "cgs"): actual = actual.cgs.value - path = os.path.join("collection", attr) - expected = pd.read_hdf(hdf_file_path, path) - assert_almost_equal(actual, expected.values) + npt.assert_allclose(actual, expected) diff --git a/tardis/plasma/tests/test_nlte_excitation.py b/tardis/plasma/tests/test_nlte_excitation.py new file mode 100644 index 00000000000..fcefce08c73 --- /dev/null +++ b/tardis/plasma/tests/test_nlte_excitation.py @@ -0,0 +1,124 @@ +import numpy as np +import numpy.testing as npt +import pandas as pd +import pytest +from numpy.testing import assert_allclose + +from tardis.plasma.properties.nlte_excitation_data import NLTEExcitationData +from tardis.plasma.properties.nlte_rate_equation_solver import ( + prepare_r_uls_r_lus, + prepare_bound_bound_rate_matrix, + create_coll_exc_deexc_matrix, +) + + +def test_prepare_bound_bound_rate_matrix(nlte_atomic_dataset, regression_data): + """ + Using a simple case of nlte_exc for HI, checks if prepare_bound_bound_rate_matrix generates the correct data. + """ + simple_excitation_species = [(1, 0)] + copy_atomic_dataset = nlte_atomic_dataset + copy_atomic_dataset.levels = nlte_atomic_dataset.levels[ + nlte_atomic_dataset.levels.index.get_level_values("level_number") < 5 + ] + lines_filtered = nlte_atomic_dataset.lines[ + nlte_atomic_dataset.lines.index.get_level_values("level_number_lower") + < 5 + ] + copy_atomic_dataset.lines = lines_filtered[ + lines_filtered.index.get_level_values("level_number_upper") < 5 + ] + simple_nlte_data = NLTEExcitationData( + copy_atomic_dataset.lines, simple_excitation_species + ) + simple_number_of_shells = 1 + simple_j_blues_matrix = np.linspace( + 0.1, 1.0, copy_atomic_dataset.lines.index.size + ) + simple_j_blues = pd.DataFrame( + simple_j_blues_matrix, + index=copy_atomic_dataset.lines.index, + columns=["0"], + ) + simple_number_of_levels = copy_atomic_dataset.levels.energy.loc[ + simple_excitation_species[0] + ].count() + ( + lines_index, + r_ul_index, + r_ul_matrix, + r_lu_index, + r_lu_matrix, + ) = prepare_r_uls_r_lus( + simple_number_of_levels, + simple_number_of_shells, + simple_j_blues, + simple_excitation_species[0], + simple_nlte_data, + ) + simple_beta_sobolev_matrix = np.linspace( + 2.5, 4.7, copy_atomic_dataset.lines.index.size + ) + simple_beta_sobolev = pd.DataFrame( + simple_beta_sobolev_matrix, + index=copy_atomic_dataset.lines.index, + columns=["0"], + ) + actual_rate_matrix = prepare_bound_bound_rate_matrix( + simple_number_of_levels, + lines_index, + r_ul_index, + r_ul_matrix, + r_lu_index, + r_lu_matrix, + simple_beta_sobolev, + ) + # if this test fails the first thing to check is if the reshape in the + # methods made a view or a copy. If it's a copy rewrite the function. + # TODO: allow rtol=1e-6 + expected_rate_matrix = regression_data.sync_ndarray(actual_rate_matrix) + npt.assert_allclose(actual_rate_matrix, expected_rate_matrix, rtol=1e-6) + + +@pytest.mark.parametrize( + [ + "coll_exc_coeff_values", + "coll_deexc_coeff_values", + "number_of_levels", + ], + [ + ( + [1, -2, 3], + [4, 9, 10], + 3, + ), + ( + [0.21, 0.045, 0.1234], + [0.7865, 0.987, 0.00123], + 3, + ), + ], +) +def test_coll_exc_deexc_matrix( + coll_exc_coeff_values, + coll_deexc_coeff_values, + number_of_levels, + regression_data, +): + """ + Checks the NLTERateEquationSolver.create_coll_exc_deexc_matrix for simple values of species with 3 levels. + NOTE: Values used for testing are not physical. + """ + index = pd.MultiIndex.from_tuples( + [(0, 1), (0, 2), (1, 2)], + names=["level_number_lower", "level_number_upper"], + ) + exc_coeff = pd.Series(coll_exc_coeff_values, index=index) + deexc_coeff = pd.Series(coll_deexc_coeff_values, index=index) + obtained_coeff_matrix = create_coll_exc_deexc_matrix( + exc_coeff, deexc_coeff, number_of_levels + ) + expected_obtained_coeff_matrix = regression_data.sync_ndarray( + obtained_coeff_matrix + ) + npt.assert_allclose(expected_obtained_coeff_matrix, obtained_coeff_matrix) diff --git a/tardis/plasma/tests/test_nlte_solver.py b/tardis/plasma/tests/test_nlte_solver.py new file mode 100644 index 00000000000..48045d3cf09 --- /dev/null +++ b/tardis/plasma/tests/test_nlte_solver.py @@ -0,0 +1,413 @@ +import numpy as np +import numpy.testing as npt +import pandas as pd +import pytest +import numpy.testing as npt + + +from tardis.plasma.properties import ( + NLTEPopulationSolverLU, + NLTEPopulationSolverRoot, +) +from tardis.plasma.properties.ion_population import IonNumberDensity +from tardis.plasma.properties.nlte_rate_equation_solver import ( + calculate_jacobian_matrix, + calculate_rate_matrix, +) +from tardis.plasma.standard_plasmas import assemble_plasma + + +@pytest.fixture +def simple_index_nlte_ion(): + """Simple fixture for nlte_ion treatment for H I and He II. + + Returns + ------- + MultiIndex + MultiIndex for HI and HeII. + """ + return pd.MultiIndex.from_tuples( + [(1, 0), (2, 1)], names=("atomic_number", "ion_number") + ) + + +@pytest.fixture +def simple_index_lte_ion(): + """Simple fixture for lte_ion treatment for H II and He I and He III. + + Returns + ------- + MultiIndex + MultiIndex for H II and He I and He III. + """ + return pd.MultiIndex.from_tuples( + [(1, 1), (2, 1), (2, 2)], names=("atomic_number", "ion_number") + ) + + +@pytest.fixture +def simple_rate_matrix_index(): + """Simple rate_matrix_index for NTLE ionization treatment of H I and He II. + + Returns + ------- + MultiIndex + (atomic_number, ion_number, treatment) + """ + return pd.MultiIndex.from_tuples( + [ + (1, 0, "nlte_ion"), + (1, 1, "lte_ion"), + (2, 0, "lte_ion"), + (2, 1, "nlte_ion"), + (2, 2, "lte_ion"), + ("n_e", "n_e", "n_e"), + ], + names=("atomic_number", "ion_number", "level_number"), + ) + + +@pytest.fixture +def simple_total_photo_ion_coefficients(simple_index_nlte_ion): + """Simple coefficients for photoionization of H I and He II. + + Returns + ------- + DataFrame + Photoionization coefficients for H I and He II. + """ + simple_photo_ion_coefficients = [0.03464792, 0.68099508] + return pd.DataFrame( + simple_photo_ion_coefficients, index=simple_index_nlte_ion + ) + + +@pytest.fixture +def simple_total_rad_recomb_coefficients(simple_index_nlte_ion): + """Simple coefficients for radiative recombination of H I and He II. + + Returns + ------- + DataFrame + Radiative recombination coefficients for H I and He II. + """ + simple_rad_recomb_coefficients = [0.43303813, 0.66140309] + return pd.DataFrame( + simple_rad_recomb_coefficients, index=simple_index_nlte_ion + ) + + +@pytest.fixture +def simple_total_col_ion_coefficients(simple_index_nlte_ion): + """Simple coefficients for collisional ionization of H I and He II. + + Returns + ------- + DataFrame + Collisional ionization coefficients for H I and He II. + """ + simple_col_ion_coefficients = [0.19351674, 0.69214007] + return pd.DataFrame( + simple_col_ion_coefficients, index=simple_index_nlte_ion + ) + + +@pytest.fixture +def simple_total_col_recomb_coefficients(simple_index_nlte_ion): + """Simple coefficients for collisional recombination of H I and He II. + + Returns + ------- + DataFrame + Collisional recombination coefficients for H I and He II. + """ + simple_col_recomb_coefficients = [0.06402515, 0.29785023] + return pd.DataFrame( + simple_col_recomb_coefficients, index=simple_index_nlte_ion + ) + + +@pytest.fixture +def simple_phi(simple_index_lte_ion): + """Simple Saha factors for H II, He I and He III.""" + simple_phi = [0.18936306, 0.15726292, 0.79851244] + return pd.DataFrame(simple_phi, index=simple_index_lte_ion) + + +@pytest.fixture +def simple_electron_density(): + """Simple electron density.""" + return 0.2219604493076 + + +def test_rate_matrix( + simple_phi, + simple_electron_density, + simple_rate_matrix_index, + simple_total_photo_ion_coefficients, + simple_total_rad_recomb_coefficients, + simple_total_col_ion_coefficients, + simple_total_col_recomb_coefficients, + regression_data, +): + """ + Using a simple case of nlte_ion for HI and HeII, checks if the calculate_rate_matrix generates the correct data. + """ + atomic_numbers = [1, 2] + actual_rate_matrix = calculate_rate_matrix( + atomic_numbers, + simple_phi, + simple_electron_density, + simple_rate_matrix_index, + simple_total_photo_ion_coefficients, + simple_total_rad_recomb_coefficients, + simple_total_col_ion_coefficients, + simple_total_col_recomb_coefficients, + ) + # TODO: decimal=6 + # allow for assert_almost_equal + expected_rate_matrix = regression_data.sync_ndarray(actual_rate_matrix) + npt.assert_allclose(actual_rate_matrix, expected_rate_matrix, rtol=1e-6) + + +def test_jacobian_matrix( + simple_phi, + simple_electron_density, + simple_rate_matrix_index, + simple_total_photo_ion_coefficients, + simple_total_rad_recomb_coefficients, + simple_total_col_ion_coefficients, + simple_total_col_recomb_coefficients, + regression_data, +): + """ + Using a simple case of nlte_ion for HI and HeII, + checks if the jacobian_matrix generates the correct data. + """ + atomic_numbers = [1, 2] + + initial_guess = [ + 0.7192433675307516, + 0.8101666197902874, + 0.7171853313284426, + 0.040220760173800496, + 0.2878574499274399, + simple_electron_density, + ] + simple_rate_matrix = calculate_rate_matrix( + atomic_numbers, + simple_phi, + simple_electron_density, + simple_rate_matrix_index, + simple_total_photo_ion_coefficients, + simple_total_rad_recomb_coefficients, + simple_total_col_ion_coefficients, + simple_total_col_recomb_coefficients, + ) + + actual_jacobian_matrix = calculate_jacobian_matrix( + atomic_numbers, + initial_guess, + simple_rate_matrix, + simple_rate_matrix_index, + simple_total_rad_recomb_coefficients, + simple_total_col_ion_coefficients, + simple_total_col_recomb_coefficients, + ) + + # TODO: allow for assert_almost_equal + expected_jacobian_matrix = regression_data.sync_ndarray( + actual_jacobian_matrix + ) + npt.assert_allclose(actual_jacobian_matrix, expected_jacobian_matrix) + + +@pytest.fixture +def nlte_raw_plasma_dilution_factor_1_root( + tardis_model_config_nlte_root, nlte_raw_model_root, nlte_atom_data +): + """ + Plasma assembled with dilution factors set to 1.0. + """ + new_dilution_factor = np.ones_like(nlte_raw_model_root.dilution_factor) + nlte_raw_model_root.dilution_factor = new_dilution_factor + plasma = assemble_plasma( + tardis_model_config_nlte_root, nlte_raw_model_root, nlte_atom_data + ) + return plasma + + +@pytest.fixture +def nlte_raw_plasma_dilution_factor_1_lu( + tardis_model_config_nlte_lu, nlte_raw_model_lu, nlte_atom_data +): + """ + Plasma assembled with dilution factors set to 1.0. + """ + new_dilution_factor = np.ones_like(nlte_raw_model_lu.dilution_factor) + nlte_raw_model_lu.dilution_factor = new_dilution_factor + plasma = assemble_plasma( + tardis_model_config_nlte_lu, nlte_raw_model_lu, nlte_atom_data + ) + return plasma + + +@pytest.fixture +def nlte_raw_plasma_dilution_factor_0_root( + tardis_model_config_nlte_root, nlte_raw_model_root, nlte_atom_data +): + """ + Plasma assembled with dilution factors set to 0.0. + """ + new_dilution_factor = np.zeros_like(nlte_raw_model_root.dilution_factor) + nlte_raw_model_root.dilution_factor = new_dilution_factor + plasma = assemble_plasma( + tardis_model_config_nlte_root, nlte_raw_model_root, nlte_atom_data + ) + return plasma + + +@pytest.fixture +def nlte_raw_plasma_dilution_factor_0_lu( + tardis_model_config_nlte_lu, nlte_raw_model_lu, nlte_atom_data +): + """ + Plasma assembled with dilution factors set to 0.0. + """ + new_dilution_factor = np.zeros_like(nlte_raw_model_lu.dilution_factor) + nlte_raw_model_lu.dilution_factor = new_dilution_factor + plasma = assemble_plasma( + tardis_model_config_nlte_lu, nlte_raw_model_lu, nlte_atom_data + ) + return plasma + + +def test_critical_case_dilution_factor_1_root( + nlte_raw_plasma_dilution_factor_1_root, +): + """Check that the LTE and NLTE solution agree for dilution_factor=1.0.""" + ion_number_density_nlte = ( + nlte_raw_plasma_dilution_factor_1_root.ion_number_density.values + ) + # ion_number_density_nlte[np.abs(ion_number_density_nlte) < 1e-10] = 0.0 + + ind = IonNumberDensity(nlte_raw_plasma_dilution_factor_1_root) + ion_number_density_lte = ind.calculate( + nlte_raw_plasma_dilution_factor_1_root.thermal_phi_lte, + nlte_raw_plasma_dilution_factor_1_root.partition_function, + nlte_raw_plasma_dilution_factor_1_root.number_density, + )[0] + + npt.assert_allclose( + ion_number_density_lte, + ion_number_density_nlte, + atol=1e-10, # seems fair for the test + rtol=1e-2, + ) + + +def test_critical_case_dilution_factor_1_lu( + nlte_raw_plasma_dilution_factor_1_lu, +): + """Check that the LTE and NLTE solution agree for dilution_factor=1.0.""" + ion_number_density_nlte = ( + nlte_raw_plasma_dilution_factor_1_lu.ion_number_density.values + ) + # ion_number_density_nlte[np.abs(ion_number_density_nlte) < 1e-10] = 0.0 + + ind = IonNumberDensity(nlte_raw_plasma_dilution_factor_1_lu) + ion_number_density_lte = ind.calculate( + nlte_raw_plasma_dilution_factor_1_lu.thermal_phi_lte, + nlte_raw_plasma_dilution_factor_1_lu.partition_function, + nlte_raw_plasma_dilution_factor_1_lu.number_density, + )[0] + + ion_number_density_lte = ion_number_density_lte.values + ion_number_density_lte[ + ion_number_density_lte < 1e-10 + ] = 0.0 # getting rid of small numbers. + npt.assert_allclose( + ion_number_density_lte, + ion_number_density_nlte, + atol=1e-10, # seems fair for the test + rtol=1e-2, + ) + + +def test_critical_case_dilution_factor_0_root( + nlte_raw_plasma_dilution_factor_0_root, +): + """Check that the LTE and NLTE solution agree for dilution_factor=0.0.""" + nlte_solver = NLTEPopulationSolverRoot( + nlte_raw_plasma_dilution_factor_0_root + ) + ion_number_density_nlte = nlte_solver.calculate( + nlte_raw_plasma_dilution_factor_0_root.gamma, + 0.0, # to test collisions only, we set the radiative recombination rate to 0 + nlte_raw_plasma_dilution_factor_0_root.alpha_stim, + nlte_raw_plasma_dilution_factor_0_root.coll_ion_coeff, + nlte_raw_plasma_dilution_factor_0_root.coll_recomb_coeff, + nlte_raw_plasma_dilution_factor_0_root.partition_function, + nlte_raw_plasma_dilution_factor_0_root.levels, + nlte_raw_plasma_dilution_factor_0_root.level_boltzmann_factor, + nlte_raw_plasma_dilution_factor_0_root.phi, + nlte_raw_plasma_dilution_factor_0_root.rate_matrix_index, + nlte_raw_plasma_dilution_factor_0_root.number_density, + nlte_raw_plasma_dilution_factor_0_root.nlte_excitation_species, + )[0] + ion_number_density_nlte = ion_number_density_nlte.values + # ion_number_density_nlte[np.abs(ion_number_density_nlte) < 1e-10] = 0.0 + + ind = IonNumberDensity(nlte_raw_plasma_dilution_factor_0_root) + ion_number_density_lte = ind.calculate( + nlte_raw_plasma_dilution_factor_0_root.thermal_phi_lte, + nlte_raw_plasma_dilution_factor_0_root.partition_function, + nlte_raw_plasma_dilution_factor_0_root.number_density, + )[0] + + ion_number_density_lte = ion_number_density_lte.values + npt.assert_allclose( + ion_number_density_lte, ion_number_density_nlte, rtol=1e-2, atol=1e-10 + ) + + +@pytest.mark.xfail +def test_critical_case_dilution_factor_0_lu( + nlte_raw_plasma_dilution_factor_0_lu, +): + """Check that the LTE and NLTE solution agree for dilution_factor=0.0.""" + nlte_solver = NLTEPopulationSolverLU(nlte_raw_plasma_dilution_factor_0_lu) + ion_number_density_nlte = nlte_solver.calculate( + nlte_raw_plasma_dilution_factor_0_lu.gamma, + 0.0, # to test collisions only, we set the radiative recombination rate to 0 + nlte_raw_plasma_dilution_factor_0_lu.alpha_stim, + nlte_raw_plasma_dilution_factor_0_lu.coll_ion_coeff, + nlte_raw_plasma_dilution_factor_0_lu.coll_recomb_coeff, + nlte_raw_plasma_dilution_factor_0_lu.partition_function, + nlte_raw_plasma_dilution_factor_0_lu.levels, + nlte_raw_plasma_dilution_factor_0_lu.level_boltzmann_factor, + nlte_raw_plasma_dilution_factor_0_lu.phi, + nlte_raw_plasma_dilution_factor_0_lu.rate_matrix_index, + nlte_raw_plasma_dilution_factor_0_lu.number_density, + nlte_raw_plasma_dilution_factor_0_lu.nlte_excitation_species, + )[0] + ion_number_density_nlte = ion_number_density_nlte.values + # ion_number_density_nlte[np.abs(ion_number_density_nlte) < 1e-10] = 0.0 + + ind = IonNumberDensity(nlte_raw_plasma_dilution_factor_0_lu) + ion_number_density_lte = ind.calculate( + nlte_raw_plasma_dilution_factor_0_lu.thermal_phi_lte, + nlte_raw_plasma_dilution_factor_0_lu.partition_function, + nlte_raw_plasma_dilution_factor_0_lu.number_density, + )[0] + + ion_number_density_lte = ion_number_density_lte.values + ion_number_density_lte[ + ion_number_density_lte < 1e-10 + ] = 0.0 # getting rid of small numbers. + npt.assert_allclose( + ion_number_density_lte, + ion_number_density_nlte, + rtol=1e-2, + atol=1e-10, + ) diff --git a/tardis/plasma/tests/test_plasma_continuum.py b/tardis/plasma/tests/test_plasma_continuum.py new file mode 100644 index 00000000000..f0eaa28e170 --- /dev/null +++ b/tardis/plasma/tests/test_plasma_continuum.py @@ -0,0 +1,11 @@ +import numpy as np + +import numpy.testing as npt +from tardis.plasma.properties import YgData + + +def test_exp1_times_exp(regression_data): + x = np.array([499.0, 501.0, 710.0]) + actual = YgData.exp1_times_exp(x) + expected = regression_data.sync_ndarray(actual) + npt.assert_allclose(actual, expected) diff --git a/tardis/plasma/tests/test_plasma_vboundary.py b/tardis/plasma/tests/test_plasma_vboundary.py index 57228a60693..af48ac49355 100644 --- a/tardis/plasma/tests/test_plasma_vboundary.py +++ b/tardis/plasma/tests/test_plasma_vboundary.py @@ -1,10 +1,10 @@ -import tardis -import pytest import os + import astropy.units as u +import pytest -from tardis.io.config_reader import Configuration -from tardis.io.atom_data.base import AtomData +import tardis +from tardis.io.configuration.config_reader import Configuration from tardis.simulation import Simulation DATA_PATH = os.path.join(tardis.__path__[0], "plasma", "tests", "data") diff --git a/tardis/plasma/tests/test_tardis_model_density_config.py b/tardis/plasma/tests/test_tardis_model_density_config.py index 6ac84e1db7b..20c9ec46cda 100644 --- a/tardis/plasma/tests/test_tardis_model_density_config.py +++ b/tardis/plasma/tests/test_tardis_model_density_config.py @@ -1,36 +1,50 @@ +import numpy.testing as npt +import pandas.testing as pdt import pytest -import os -from tardis.io.config_reader import Configuration -from tardis.model import Radial1DModel -from tardis.plasma.standard_plasmas import assemble_plasma -from numpy.testing import assert_almost_equal -data_path = os.path.join("tardis", "io", "tests", "data") +from tardis.io.configuration.config_reader import Configuration +from tardis.model import SimulationState +from tardis.plasma.standard_plasmas import assemble_plasma @pytest.fixture -def tardis_model_density_config(): - filename = "tardis_configv1_tardis_model_format.yml" - return Configuration.from_yaml(os.path.join(data_path, filename)) +def tardis_model_density_config(example_model_file_dir): + return Configuration.from_yaml( + example_model_file_dir / "tardis_configv1_tardis_model_format.yml" + ) @pytest.fixture() -def raw_model(tardis_model_density_config): - return Radial1DModel.from_config(tardis_model_density_config) +def raw_simulation_state(tardis_model_density_config, kurucz_atomic_data): + return SimulationState.from_config( + tardis_model_density_config, atom_data=kurucz_atomic_data + ) @pytest.fixture() -def raw_plasma(tardis_model_density_config, raw_model, kurucz_atomic_data): +def raw_plasma( + tardis_model_density_config, raw_simulation_state, kurucz_atomic_data +): return assemble_plasma( - tardis_model_density_config, raw_model, kurucz_atomic_data + tardis_model_density_config, raw_simulation_state, kurucz_atomic_data ) -def test_electron_densities(raw_plasma): - assert_almost_equal(raw_plasma.electron_densities[8], 2.72e14) - assert_almost_equal(raw_plasma.electron_densities[3], 2.6e14) +def test_electron_densities(raw_plasma, regression_data): + actual = raw_plasma.electron_densities + expected = regression_data.sync_ndarray(actual) + npt.assert_allclose(actual, expected) + + +def test_isotope_number_densities( + request, raw_simulation_state, regression_data +): + actual = raw_simulation_state.composition.isotopic_number_density + expected = regression_data.sync_dataframe(actual) + pdt.assert_frame_equal(actual, expected) -def test_t_rad(raw_plasma): - assert_almost_equal(raw_plasma.t_rad[5], 76459.592) - assert_almost_equal(raw_plasma.t_rad[3], 76399.042) +def test_t_rad(raw_plasma, regression_data): + actual = raw_plasma.t_rad + expected = regression_data.sync_ndarray(actual) + npt.assert_array_equal(actual, expected) diff --git a/tardis/radiation_field/__init__.py b/tardis/radiation_field/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/radiation_field/base.py b/tardis/radiation_field/base.py new file mode 100644 index 00000000000..4fe0658c20c --- /dev/null +++ b/tardis/radiation_field/base.py @@ -0,0 +1,34 @@ +import numpy as np +from astropy import units as u + +from tardis.transport.montecarlo.packet_source import BasePacketSource +from tardis.opacities.opacity_state import OpacityState + + +class MonteCarloRadiationFieldState: + """_summary_ + + Parameters + ---------- + t_radiative : u.Quantity + Radiative temperature in each shell + dilution_factor : numpy.ndarray + Dilution Factors in each shell + opacities : OpacityState + Opacity container object + packet_source : SourceFunction + Source function for radiative transfer, for example a packet_source + """ + + def __init__( + self, + t_radiative: u.Quantity, + dilution_factor: np.ndarray, + opacities: OpacityState, + packet_source: BasePacketSource, + ): + self.t_radiative = t_radiative + self.dilution_factor = dilution_factor + self.t_rad = self.t_radiative + self.opacities = opacities + self.packet_source = packet_source diff --git a/tardis/radiation_field/opacities/__init__.py b/tardis/radiation_field/opacities/__init__.py new file mode 100644 index 00000000000..47f2c79e60d --- /dev/null +++ b/tardis/radiation_field/opacities/__init__.py @@ -0,0 +1 @@ +from tardis.radiation_field.opacities.base import * diff --git a/tardis/scripts/__init__.py b/tardis/scripts/__init__.py index e69de29bb2d..63fb31fbbbd 100644 --- a/tardis/scripts/__init__.py +++ b/tardis/scripts/__init__.py @@ -0,0 +1,3 @@ +""" +Translate cmfgen format to a format TARDIS can use. +""" diff --git a/tardis/scripts/cmfgen2tardis.py b/tardis/scripts/cmfgen2tardis.py index 9c4c2c77bf5..7f01fba3940 100644 --- a/tardis/scripts/cmfgen2tardis.py +++ b/tardis/scripts/cmfgen2tardis.py @@ -79,7 +79,7 @@ def convert_format(file_path): abundances_df.loc[element_symbol] = abundances density_df = pd.DataFrame.from_records( - [velocity, temperature * 10 ** 4, density, electron_density] + [velocity, temperature * 10**4, density, electron_density] ).transpose() density_df.columns = [ "velocity", diff --git a/tardis/scripts/debug/run_numba_single.py b/tardis/scripts/debug/run_numba_single.py index 1ab234b282c..09d28199fab 100644 --- a/tardis/scripts/debug/run_numba_single.py +++ b/tardis/scripts/debug/run_numba_single.py @@ -1,22 +1,5 @@ from tardis import run_tardis -import numpy as np -from tardis.montecarlo.montecarlo_numba.base import montecarlo_main_loop -import os -import numba -import sys -import yaml - -SEED = eval(sys.argv[1].split("=")[1])[0] - -yaml_file, params = "tardis_example_single.yml", None - -with open(yaml_file) as f: - params = yaml.safe_load(f) - -params["montecarlo"]["single_packet_seed"] = SEED - -with open(yaml_file, "w") as f: - yaml.safe_dump(params, f) +yaml_file = "tardis_example_single.yml" mdl = run_tardis(yaml_file) diff --git a/tardis/scripts/debug/tardis_example_single.yml b/tardis/scripts/debug/tardis_example_single.yml index 35c17071b18..9365ebe65f0 100644 --- a/tardis/scripts/debug/tardis_example_single.yml +++ b/tardis/scripts/debug/tardis_example_single.yml @@ -28,7 +28,6 @@ montecarlo: no_of_virtual_packets: 0 nthreads: 6 seed: 23111963 - single_packet_seed: 46 plasma: disable_electron_scattering: false excitation: lte diff --git a/tardis/scripts/tardis b/tardis/scripts/tardis index 8abf78ad82b..9d99a9b3776 100755 --- a/tardis/scripts/tardis +++ b/tardis/scripts/tardis @@ -11,14 +11,14 @@ from tardis.simulation import Simulation def get_virtual_spectrum(): # Catch warning when acessing invalid spectrum_virtual with warnings.catch_warnings(record=True) as w: - spectrum = simulation.runner.spectrum_virtual + spectrum = simulation.transport.spectrum_virtual if len(w) > 0 and w[-1]._category_name == "UserWarning": warnings.warn( "Virtual spectrum is not available, using the " "real packet spectrum instead." ) - spectrum = simulation.runner.spectrum + spectrum = simulation.transport.spectrum return spectrum @@ -99,9 +99,9 @@ print("Saving the {} spectrum.".format(tardis_config.spectrum.method)) # the warning properly get_spectrum = { - "real": lambda: simulation.runner.spectrum, + "real": lambda: simulation.transport.spectrum, "virtual": get_virtual_spectrum, - "integrated": lambda: simulation.runner.spectrum_integrated, + "integrated": lambda: simulation.transport.spectrum_integrated, }[tardis_config.spectrum.method] if args.gdb: @@ -114,10 +114,14 @@ if args.profile: import cProfile cProfile.runctx( - "simulation.run()", locals(), globals(), filename=args.profiler_log_file + "simulation.run_convergence()\nsimulation.run_final()", + locals(), + globals(), + filename=args.profiler_log_file, ) else: - simulation.run() + simulation.run_convergence() + simulation.run_final() get_spectrum().to_ascii(args.spectrum_fname) diff --git a/tardis/simulation/__init__.py b/tardis/simulation/__init__.py index 8c88a5ab087..101ac28d6f7 100644 --- a/tardis/simulation/__init__.py +++ b/tardis/simulation/__init__.py @@ -1 +1,5 @@ +""" +Handling simulation runs. +""" + from tardis.simulation.base import Simulation diff --git a/tardis/simulation/base.py b/tardis/simulation/base.py index 60e00578a84..219e20f363f 100644 --- a/tardis/simulation/base.py +++ b/tardis/simulation/base.py @@ -1,27 +1,31 @@ -import time import logging +import time +from collections import OrderedDict +from pathlib import Path + import numpy as np import pandas as pd from astropy import units as u -from tardis import constants as const -from collections import OrderedDict -from tardis import model +from IPython.display import display -from tardis.montecarlo import MontecarloRunner -from tardis.model import Radial1DModel -from tardis.plasma.standard_plasmas import assemble_plasma +import tardis +from tardis import constants as const +from tardis.io.atom_data.base import AtomData +from tardis.io.configuration.config_reader import ConfigurationError from tardis.io.util import HDFWriterMixin -from tardis.io.config_reader import ConfigurationError +from tardis.model import SimulationState +from tardis.model.parse_input import initialize_packet_source +from tardis.transport.montecarlo.base import MonteCarloTransportSolver +from tardis.plasma.standard_plasmas import assemble_plasma +from tardis.simulation.convergence import ConvergenceSolver from tardis.util.base import is_notebook -from tardis.montecarlo import montecarlo_configuration as mc_config_module from tardis.visualization import ConvergencePlots -from IPython.display import display # Adding logging support logger = logging.getLogger(__name__) -class PlasmaStateStorerMixin(object): +class PlasmaStateStorerMixin: """Mixin class to provide the capability to the simulation object of storing plasma information and the inner boundary temperature during each MC iteration. @@ -32,7 +36,6 @@ class PlasmaStateStorerMixin(object): """ def __init__(self, iterations, no_of_shells): - self.iterations_w = np.zeros((iterations, no_of_shells)) self.iterations_t_rad = np.zeros((iterations, no_of_shells)) * u.K self.iterations_electron_densities = np.zeros( @@ -91,9 +94,9 @@ class Simulation(PlasmaStateStorerMixin, HDFWriterMixin): ---------- converged : bool iterations : int - model : tardis.model.Radial1DModel + model : tardis.model.SimulationState plasma : tardis.plasma.BasePlasma - runner : tardis.montecarlo.MontecarloRunner + transport : tardis.transport.montecarlo.MontecarloTransport no_of_packets : int last_no_of_packets : int no_of_virtual_packets : int @@ -101,17 +104,12 @@ class Simulation(PlasmaStateStorerMixin, HDFWriterMixin): luminosity_nu_end : astropy.units.Quantity luminosity_requested : astropy.units.Quantity convergence_plots_kwargs: dict - nthreads : int - The number of threads to run montecarlo with - - .. note:: TARDIS must be built with OpenMP support in order for ``nthreads`` to have effect. - """ hdf_properties = [ - "model", + "simulation_state", "plasma", - "runner", + "transport", "iterations_w", "iterations_t_rad", "iterations_electron_densities", @@ -122,9 +120,9 @@ class Simulation(PlasmaStateStorerMixin, HDFWriterMixin): def __init__( self, iterations, - model, + simulation_state, plasma, - runner, + transport, no_of_packets, no_of_virtual_packets, luminosity_nu_start, @@ -132,121 +130,111 @@ def __init__( last_no_of_packets, luminosity_requested, convergence_strategy, - nthreads, show_convergence_plots, convergence_plots_kwargs, show_progress_bars, ): - - super(Simulation, self).__init__(iterations, model.no_of_shells) + super(Simulation, self).__init__( + iterations, simulation_state.no_of_shells + ) self.converged = False self.iterations = iterations self.iterations_executed = 0 - self.model = model + self.simulation_state = simulation_state self.plasma = plasma - self.runner = runner + self.transport = transport self.no_of_packets = no_of_packets self.last_no_of_packets = last_no_of_packets self.no_of_virtual_packets = no_of_virtual_packets self.luminosity_nu_start = luminosity_nu_start self.luminosity_nu_end = luminosity_nu_end self.luminosity_requested = luminosity_requested - self.nthreads = nthreads self.show_progress_bars = show_progress_bars + self.version = tardis.__version__ - if convergence_strategy.type in ("damped"): - self.convergence_strategy = convergence_strategy - self.converged = False - self.consecutive_converges_count = 0 - elif convergence_strategy.type in ("custom"): - raise NotImplementedError( - "Convergence strategy type is custom; " - "you need to implement your specific treatment!" - ) - else: - raise ValueError( - f"Convergence strategy type is " - f"not damped or custom " - f"- input is {convergence_strategy.type}" - ) + # Convergence + self.convergence_strategy = convergence_strategy + self.converged = False + self.consecutive_converges_count = 0 - if show_convergence_plots: - self.convergence_plots = ConvergencePlots( - iterations=self.iterations, **convergence_plots_kwargs - ) + # Convergence solvers + self.t_rad_convergence_solver = ConvergenceSolver( + self.convergence_strategy.t_rad + ) + self.w_convergence_solver = ConvergenceSolver( + self.convergence_strategy.w + ) + self.t_inner_convergence_solver = ConvergenceSolver( + self.convergence_strategy.t_inner + ) - if "export_convergence_plots" in convergence_plots_kwargs: - if not isinstance( - convergence_plots_kwargs["export_convergence_plots"], bool - ): - raise TypeError( - "Expected bool in export_convergence_plots argument" - ) - self.export_convergence_plots = convergence_plots_kwargs[ - "export_convergence_plots" - ] + if show_convergence_plots: + if not is_notebook(): + raise RuntimeError( + "Convergence Plots cannot be displayed in command-line. Set show_convergence_plots " + "to False." + ) else: - self.export_convergence_plots = False + self.convergence_plots = ConvergencePlots( + iterations=self.iterations, **convergence_plots_kwargs + ) + + if "export_convergence_plots" in convergence_plots_kwargs: + if not isinstance( + convergence_plots_kwargs["export_convergence_plots"], + bool, + ): + raise TypeError( + "Expected bool in export_convergence_plots argument" + ) + self.export_convergence_plots = convergence_plots_kwargs[ + "export_convergence_plots" + ] + else: + self.export_convergence_plots = False self._callbacks = OrderedDict() self._cb_next_id = 0 + self.transport.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED = ( + not self.plasma.continuum_interaction_species.empty + ) + def estimate_t_inner( self, input_t_inner, luminosity_requested, t_inner_update_exponent=-0.5 ): - emitted_luminosity = self.runner.calculate_emitted_luminosity( - self.luminosity_nu_start, self.luminosity_nu_end + emitted_luminosity = ( + self.transport.transport_state.calculate_emitted_luminosity( + self.luminosity_nu_start, self.luminosity_nu_end + ) ) luminosity_ratios = ( (emitted_luminosity / luminosity_requested).to(1).value ) - return input_t_inner * luminosity_ratios ** t_inner_update_exponent - - @staticmethod - def damped_converge(value, estimated_value, damping_factor): - # FIXME: Should convergence strategy have its own class containing this - # as a method - return value + damping_factor * (estimated_value - value) + return input_t_inner * luminosity_ratios**t_inner_update_exponent def _get_convergence_status( self, t_rad, w, t_inner, estimated_t_rad, estimated_w, estimated_t_inner ): - # FIXME: Move the convergence checking in its own class. - no_of_shells = self.model.no_of_shells - - convergence_t_rad = ( - abs(t_rad - estimated_t_rad) / estimated_t_rad - ).value - convergence_w = abs(w - estimated_w) / estimated_w - convergence_t_inner = ( - abs(t_inner - estimated_t_inner) / estimated_t_inner - ).value - - fraction_t_rad_converged = ( - np.count_nonzero( - convergence_t_rad < self.convergence_strategy.t_rad.threshold - ) - / no_of_shells + t_rad_converged = self.t_rad_convergence_solver.get_convergence_status( + t_rad.value, + estimated_t_rad.value, + self.simulation_state.no_of_shells, ) - t_rad_converged = ( - fraction_t_rad_converged > self.convergence_strategy.fraction + w_converged = self.w_convergence_solver.get_convergence_status( + w, estimated_w, self.simulation_state.no_of_shells ) - fraction_w_converged = ( - np.count_nonzero( - convergence_w < self.convergence_strategy.w.threshold - ) - / no_of_shells - ) - - w_converged = fraction_w_converged > self.convergence_strategy.fraction - t_inner_converged = ( - convergence_t_inner < self.convergence_strategy.t_inner.threshold + self.t_inner_convergence_solver.get_convergence_status( + t_inner.value, + estimated_t_inner.value, + 1, + ) ) if np.all([t_rad_converged, w_converged, t_inner_converged]): @@ -276,73 +264,75 @@ def advance_state(self): """ ( estimated_t_rad, - estimated_w, - ) = self.runner.calculate_radiationfield_properties() + estimated_dilution_factor, + ) = self.transport.transport_state.calculate_radiationfield_properties() estimated_t_inner = self.estimate_t_inner( - self.model.t_inner, + self.simulation_state.t_inner, self.luminosity_requested, t_inner_update_exponent=self.convergence_strategy.t_inner_update_exponent, ) converged = self._get_convergence_status( - self.model.t_rad, - self.model.w, - self.model.t_inner, + self.simulation_state.t_radiative, + self.simulation_state.dilution_factor, + self.simulation_state.t_inner, estimated_t_rad, - estimated_w, + estimated_dilution_factor, estimated_t_inner, ) # calculate_next_plasma_state equivalent - # FIXME: Should convergence strategy have its own class? - next_t_rad = self.damped_converge( - self.model.t_rad, + next_t_radiative = self.t_rad_convergence_solver.converge( + self.simulation_state.t_radiative, estimated_t_rad, - self.convergence_strategy.t_rad.damping_constant, ) - next_w = self.damped_converge( - self.model.w, - estimated_w, - self.convergence_strategy.w.damping_constant, + next_dilution_factor = self.w_convergence_solver.converge( + self.simulation_state.dilution_factor, + estimated_dilution_factor, ) if ( self.iterations_executed + 1 ) % self.convergence_strategy.lock_t_inner_cycles == 0: - next_t_inner = self.damped_converge( - self.model.t_inner, + next_t_inner = self.t_inner_convergence_solver.converge( + self.simulation_state.t_inner, estimated_t_inner, - self.convergence_strategy.t_inner.damping_constant, ) else: - next_t_inner = self.model.t_inner + next_t_inner = self.simulation_state.t_inner if hasattr(self, "convergence_plots"): self.convergence_plots.fetch_data( name="t_inner", - value=self.model.t_inner.value, + value=self.simulation_state.t_inner.value, item_type="value", ) self.convergence_plots.fetch_data( - name="t_rad", value=self.model.t_rad, item_type="iterable" + name="t_rad", + value=self.simulation_state.t_radiative, + item_type="iterable", ) self.convergence_plots.fetch_data( - name="w", value=self.model.w, item_type="iterable" + name="w", + value=self.simulation_state.dilution_factor, + item_type="iterable", ) self.convergence_plots.fetch_data( - name="velocity", value=self.model.velocity, item_type="iterable" + name="velocity", + value=self.simulation_state.velocity, + item_type="iterable", ) self.log_plasma_state( - self.model.t_rad, - self.model.w, - self.model.t_inner, - next_t_rad, - next_w, + self.simulation_state.t_radiative, + self.simulation_state.dilution_factor, + self.simulation_state.t_inner, + next_t_radiative, + next_dilution_factor, next_t_inner, ) - self.model.t_rad = next_t_rad - self.model.w = next_w - self.model.t_inner = next_t_inner + self.simulation_state.t_radiative = next_t_radiative + self.simulation_state.dilution_factor = next_dilution_factor + self.simulation_state.blackbody_packet_source.temperature = next_t_inner # model.calculate_j_blues() equivalent # model.update_plasmas() equivalent @@ -350,43 +340,67 @@ def advance_state(self): if "nlte_data" in self.plasma.outputs_dict: self.plasma.store_previous_properties() - update_properties = dict(t_rad=self.model.t_rad, w=self.model.w) + update_properties = dict( + t_rad=self.simulation_state.t_radiative, + w=self.simulation_state.dilution_factor, + ) # A check to see if the plasma is set with JBluesDetailed, in which # case it needs some extra kwargs. + + estimators = self.transport.transport_state.radfield_mc_estimators if "j_blue_estimator" in self.plasma.outputs_dict: update_properties.update( t_inner=next_t_inner, - j_blue_estimator=self.runner.j_blue_estimator, + j_blue_estimator=estimators.j_blue_estimator, + ) + if "gamma_estimator" in self.plasma.outputs_dict: + update_properties.update( + gamma_estimator=estimators.photo_ion_estimator, + alpha_stim_estimator=estimators.stim_recomb_estimator, + bf_heating_coeff_estimator=estimators.bf_heating_estimator, + stim_recomb_cooling_coeff_estimator=estimators.stim_recomb_cooling_estimator, ) self.plasma.update(**update_properties) return converged - def iterate(self, no_of_packets, no_of_virtual_packets=0, last_run=False): + def iterate(self, no_of_packets, no_of_virtual_packets=0): logger.info( - f"Starting iteration {(self.iterations_executed + 1):d} of {self.iterations:d}" + f"\n\tStarting iteration {(self.iterations_executed + 1):d} of {self.iterations:d}" ) - self.runner.run( - self.model, + + transport_state = self.transport.initialize_transport_state( + self.simulation_state, self.plasma, no_of_packets, no_of_virtual_packets=no_of_virtual_packets, - nthreads=self.nthreads, - last_run=last_run, + iteration=self.iterations_executed, + ) + + self.transport.run( + transport_state, + time_explosion=self.simulation_state.time_explosion, iteration=self.iterations_executed, total_iterations=self.iterations, show_progress_bars=self.show_progress_bars, ) - output_energy = self.runner.output_energy + + output_energy = ( + self.transport.transport_state.packet_collection.output_energies + ) if np.sum(output_energy < 0) == len(output_energy): logger.critical("No r-packet escaped through the outer boundary.") - emitted_luminosity = self.runner.calculate_emitted_luminosity( - self.luminosity_nu_start, self.luminosity_nu_end + emitted_luminosity = ( + self.transport.transport_state.calculate_emitted_luminosity( + self.luminosity_nu_start, self.luminosity_nu_end + ) ) - reabsorbed_luminosity = self.runner.calculate_reabsorbed_luminosity( - self.luminosity_nu_start, self.luminosity_nu_end + reabsorbed_luminosity = ( + self.transport.transport_state.calculate_reabsorbed_luminosity( + self.luminosity_nu_start, self.luminosity_nu_end + ) ) if hasattr(self, "convergence_plots"): self.convergence_plots.fetch_data( @@ -408,19 +422,18 @@ def iterate(self, no_of_packets, no_of_virtual_packets=0, last_run=False): self.log_run_results(emitted_luminosity, reabsorbed_luminosity) self.iterations_executed += 1 - def run(self): + def run_convergence(self): """ run the simulation """ - start_time = time.time() while self.iterations_executed < self.iterations - 1: self.store_plasma_state( self.iterations_executed, - self.model.w, - self.model.t_rad, + self.simulation_state.dilution_factor, + self.simulation_state.t_radiative, self.plasma.electron_densities, - self.model.t_inner, + self.simulation_state.t_inner, ) self.iterate(self.no_of_packets) self.converged = self.advance_state() @@ -430,23 +443,30 @@ def run(self): if self.converged: if self.convergence_strategy.stop_if_converged: break - # Last iteration + + logger.info( + f"\n\tSimulation finished in {self.iterations_executed:d} iterations " + f"\n\tSimulation took {(time.time() - start_time):.2f} s\n" + ) + + def run_final(self): + """ + run the last iteration of the simulation + """ self.store_plasma_state( self.iterations_executed, - self.model.w, - self.model.t_rad, + self.simulation_state.dilution_factor, + self.simulation_state.t_radiative, self.plasma.electron_densities, - self.model.t_inner, - ) - self.iterate( - self.last_no_of_packets, self.no_of_virtual_packets, last_run=True + self.simulation_state.t_inner, ) + self.iterate(self.last_no_of_packets, self.no_of_virtual_packets) self.reshape_plasma_state_store(self.iterations_executed) if hasattr(self, "convergence_plots"): self.convergence_plots.fetch_data( name="t_inner", - value=self.model.t_inner.value, + value=self.simulation_state.t_inner.value, item_type="value", ) self.convergence_plots.update( @@ -454,19 +474,15 @@ def run(self): last=True, ) - logger.info( - f"Simulation finished in {self.iterations_executed:d} iterations " - f"Simulation took {(time.time() - start_time):.2f} s\n" - ) self._call_back() def log_plasma_state( self, t_rad, - w, + dilution_factor, t_inner, next_t_rad, - next_w, + next_dilution_factor, next_t_inner, log_sampling=5, ): @@ -489,19 +505,18 @@ def log_plasma_state( Returns ------- """ - plasma_state_log = pd.DataFrame( index=np.arange(len(t_rad)), columns=["t_rad", "next_t_rad", "w", "next_w"], ) plasma_state_log["t_rad"] = t_rad plasma_state_log["next_t_rad"] = next_t_rad - plasma_state_log["w"] = w - plasma_state_log["next_w"] = next_w + plasma_state_log["w"] = dilution_factor + plasma_state_log["next_w"] = next_dilution_factor plasma_state_log.columns.name = "Shell No." if is_notebook(): - logger.info("Plasma stratification:") + logger.info("\n\tPlasma stratification:") # Displaying the DataFrame only when the logging level is NOTSET, DEBUG or INFO if logger.level <= logging.INFO: @@ -520,21 +535,21 @@ def log_plasma_state( else: output_df = "" plasma_output = plasma_state_log.iloc[::log_sampling].to_string( - float_format=lambda x: "{:.3g}".format(x), + float_format=lambda x: f"{x:.3g}", justify="center", ) for value in plasma_output.split("\n"): - output_df = output_df + "\t{}\n".format(value) - logger.info("Plasma stratification:") + output_df = output_df + f"\t{value}\n" + logger.info("\n\tPlasma stratification:") logger.info(f"\n{output_df}") logger.info( - f"Current t_inner = {t_inner:.3f}\n\tExpected t_inner for next iteration = {next_t_inner:.3f}\n" + f"\n\tCurrent t_inner = {t_inner:.3f}\n\tExpected t_inner for next iteration = {next_t_inner:.3f}\n" ) def log_run_results(self, emitted_luminosity, absorbed_luminosity): logger.info( - f"Luminosity emitted = {emitted_luminosity:.3e}\n" + f"\n\tLuminosity emitted = {emitted_luminosity:.3e}\n" f"\tLuminosity absorbed = {absorbed_luminosity:.3e}\n" f"\tLuminosity requested = {self.luminosity_requested:.3e}\n" ) @@ -596,8 +611,9 @@ def from_config( config, packet_source=None, virtual_packet_logging=False, - show_convergence_plots=True, + show_convergence_plots=False, show_progress_bars=True, + legacy_mode_enabled=False, **kwargs, ): """ @@ -609,7 +625,7 @@ def from_config( **kwargs Allow overriding some structures, such as model, plasma, atomic data - and the runner, instead of creating them from the configuration + and the transport, instead of creating them from the configuration object. Returns @@ -618,30 +634,75 @@ def from_config( """ # Allow overriding some config structures. This is useful in some # unit tests, and could be extended in all the from_config classmethods. + + atom_data = kwargs.get("atom_data", None) + if atom_data is None: + if "atom_data" in config: + if Path(config.atom_data).is_absolute(): + atom_data_fname = Path(config.atom_data) + else: + atom_data_fname = ( + Path(config.config_dirname) / config.atom_data + ) + + else: + raise ValueError( + "No atom_data option found in the configuration." + ) + + logger.info(f"\n\tReading Atomic Data from {atom_data_fname}") + + try: + atom_data = AtomData.from_hdf(atom_data_fname) + except TypeError as e: + print( + e, + "Error might be from the use of an old-format of the atomic database, \n" + "please see https://github.com/tardis-sn/tardis-refdata/tree/master/atom_data" + " for the most recent version.", + ) + raise if "model" in kwargs: - model = kwargs["model"] + simulation_state = kwargs["model"] else: if hasattr(config, "csvy_model"): - model = Radial1DModel.from_csvy(config) + simulation_state = SimulationState.from_csvy( + config, + atom_data=atom_data, + legacy_mode_enabled=legacy_mode_enabled, + ) else: - model = Radial1DModel.from_config(config) + simulation_state = SimulationState.from_config( + config, + atom_data=atom_data, + legacy_mode_enabled=legacy_mode_enabled, + ) + if packet_source is not None: + simulation_state.packet_source = initialize_packet_source( + config, + simulation_state.geometry, + packet_source, + legacy_mode_enabled, + ) if "plasma" in kwargs: plasma = kwargs["plasma"] else: plasma = assemble_plasma( - config, model, atom_data=kwargs.get("atom_data", None) + config, + simulation_state, + atom_data=atom_data, ) - if "runner" in kwargs: + if "transport" in kwargs: if packet_source is not None: raise ConfigurationError( - "Cannot specify packet_source and runner at the same time." + "Cannot specify packet_source and transport at the same time." ) - runner = kwargs["runner"] + transport = kwargs["transport"] else: - runner = MontecarloRunner.from_config( + transport = MonteCarloTransportSolver.from_config( config, - packet_source=packet_source, - virtual_packet_logging=virtual_packet_logging, + packet_source=simulation_state.packet_source, + enable_virtual_packet_logging=virtual_packet_logging, ) convergence_plots_config_options = [ @@ -677,9 +738,9 @@ def from_config( return cls( iterations=config.montecarlo.iterations, - model=model, + simulation_state=simulation_state, plasma=plasma, - runner=runner, + transport=transport, show_convergence_plots=show_convergence_plots, no_of_packets=int(config.montecarlo.no_of_packets), no_of_virtual_packets=int(config.montecarlo.no_of_virtual_packets), @@ -688,7 +749,6 @@ def from_config( last_no_of_packets=last_no_of_packets, luminosity_requested=config.supernova.luminosity_requested.cgs, convergence_strategy=config.montecarlo.convergence_strategy, - nthreads=config.montecarlo.nthreads, convergence_plots_kwargs=convergence_plots_kwargs, show_progress_bars=show_progress_bars, ) diff --git a/tardis/simulation/convergence.py b/tardis/simulation/convergence.py new file mode 100644 index 00000000000..3891b50374e --- /dev/null +++ b/tardis/simulation/convergence.py @@ -0,0 +1,78 @@ +import numpy as np + + +class ConvergenceSolver: + def __init__(self, strategy): + """Convergence solver. Sets convergence strategy and assigns a method + to the converge property. + + Parameters + ---------- + strategy : string + Convergence strategy for the physical property + + Raises + ------ + NotImplementedError + Custom convergence type specified + ValueError + Unknown convergence type specified + """ + self.convergence_strategy = strategy + self.damping_factor = self.convergence_strategy.damping_constant + self.threshold = self.convergence_strategy.threshold + + if self.convergence_strategy.type in ("damped"): + self.converge = self.damped_converge + elif self.convergence_strategy.type in ("custom"): + raise NotImplementedError( + "Convergence strategy type is custom; " + "you need to implement your specific treatment!" + ) + else: + raise ValueError( + f"Convergence strategy type is " + f"not damped or custom " + f"- input is {self.convergence_strategy.type}" + ) + + def damped_converge(self, value, estimated_value): + """Damped convergence solver + + Parameters + ---------- + value : np.float64 + The current value of the physical property + estimated_value : np.float64 + The estimated value of the physical property + + Returns + ------- + np.float64 + The converged value + """ + return value + self.damping_factor * (estimated_value - value) + + def get_convergence_status(self, value, estimated_value, no_of_cells): + """Get the status of convergence for the physical property + + Parameters + ---------- + value : np.float64, Quantity + The current value of the physical property + estimated_value : np.float64, Quantity + The estimated value of the physical property + no_of_cells : np.int64 + The number of cells to measure convergence over + + Returns + ------- + bool + True if convergence is reached + """ + convergence = abs(value - estimated_value) / estimated_value + + fraction_converged = ( + np.count_nonzero(convergence < self.threshold) / no_of_cells + ) + return fraction_converged > self.threshold diff --git a/tardis/simulation/tests/test_convergence.py b/tardis/simulation/tests/test_convergence.py new file mode 100644 index 00000000000..b53b9251f19 --- /dev/null +++ b/tardis/simulation/tests/test_convergence.py @@ -0,0 +1,65 @@ +from pathlib import Path + +import numpy as np +import numpy.testing as npt +import pytest + +from tardis.io.configuration.config_reader import Configuration +from tardis.simulation.convergence import ConvergenceSolver + + +@pytest.fixture(scope="function") +def config(example_configuration_dir: Path): + return Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_verysimple.yml" + ) + + +@pytest.fixture(scope="function") +def strategy(config): + return config.montecarlo.convergence_strategy.t_rad + + +def test_convergence_solver_init_damped(strategy): + solver = ConvergenceSolver(strategy) + assert solver.damping_factor == 0.5 + assert solver.threshold == 0.05 + assert solver.converge == solver.damped_converge + + +def test_convergence_solver_init_custom(strategy): + strategy.type = "custom" + with pytest.raises(NotImplementedError): + ConvergenceSolver(strategy) + + +def test_convergence_solver_init_invalid(strategy): + strategy.type = "invalid" + with pytest.raises(ValueError): + ConvergenceSolver(strategy) + + +def test_damped_converge(strategy): + solver = ConvergenceSolver(strategy) + value = np.float64(10.0) + estimated_value = np.float64(20.0) + converged_value = solver.damped_converge(value, estimated_value) + npt.assert_almost_equal(converged_value, 15.0) + + +def test_get_convergence_status(strategy): + solver = ConvergenceSolver(strategy) + value = np.array([1.0, 2.0, 3.0], dtype=np.float64) + estimated_value = np.array([1.01, 2.02, 3.03], dtype=np.float64) + no_of_cells = np.int64(3) + is_converged = solver.get_convergence_status( + value, estimated_value, no_of_cells + ) + assert is_converged + + value = np.array([1.0, 2.0, 3.0], dtype=np.float64) + estimated_value = np.array([2.0, 3.0, 4.0], dtype=np.float64) + is_converged = solver.get_convergence_status( + value, estimated_value, no_of_cells + ) + assert not is_converged diff --git a/tardis/simulation/tests/test_simulation.py b/tardis/simulation/tests/test_simulation.py index 88f3daff827..5e6188bd746 100644 --- a/tardis/simulation/tests/test_simulation.py +++ b/tardis/simulation/tests/test_simulation.py @@ -1,30 +1,34 @@ import os +from pathlib import Path + import pytest import logging -from tardis.io.config_reader import Configuration +from tardis.io.configuration.config_reader import Configuration from tardis.simulation import Simulation from tardis import run_tardis +import pandas.testing as pdt import numpy as np import pandas as pd -import pandas.util.testing as pdt + import astropy.units as u +import tardis @pytest.fixture(scope="module") def refdata(tardis_ref_data): def get_ref_data(key): - return tardis_ref_data[os.path.join("test_simulation", key)] + return tardis_ref_data[f"test_simulation/{key}"] return get_ref_data @pytest.fixture(scope="module") -def config(): +def config(example_configuration_dir: Path): return Configuration.from_yaml( - "tardis/io/tests/data/tardis_configv1_verysimple.yml" + example_configuration_dir / "tardis_configv1_verysimple.yml" ) @@ -38,7 +42,8 @@ def simulation_one_loop( config.montecarlo.last_no_of_packets = int(4e4) simulation = Simulation.from_config(config) - simulation.run() + simulation.run_convergence() + simulation.run_final() if not generate_reference: return simulation @@ -49,20 +54,18 @@ def simulation_one_loop( "iterations_electron_densities", "iterations_t_inner", ] - simulation.model.hdf_properties = ["t_radiative", "dilution_factor"] - simulation.runner.hdf_properties = [ - "j_estimator", - "nu_bar_estimator", - "output_nu", - "output_energy", + simulation.simulation_state.hdf_properties = [ + "t_radiative", + "dilution_factor", ] + simulation.transport.hdf_properties = ["transport_state"] simulation.to_hdf( tardis_ref_data, "", "test_simulation", overwrite=True ) - simulation.model.to_hdf( + simulation.simulation_state.to_hdf( tardis_ref_data, "", "test_simulation", overwrite=True ) - simulation.runner.to_hdf( + simulation.transport.to_hdf( tardis_ref_data, "", "test_simulation", overwrite=True ) pytest.skip("Reference data was generated during this run.") @@ -80,14 +83,36 @@ def simulation_one_loop( ], ) def test_plasma_estimates(simulation_one_loop, refdata, name): - try: - actual = getattr(simulation_one_loop.runner, name) - except AttributeError: - actual = getattr(simulation_one_loop.model, name) - + if name in ["nu_bar_estimator", "j_estimator"]: + actual = getattr( + simulation_one_loop.transport.transport_state.radfield_mc_estimators, + name, + ) + elif name in ["t_radiative", "dilution_factor"]: + actual = getattr(simulation_one_loop.simulation_state, name) + elif name in ["output_nu", "output_energy"]: + OLD_TO_NEW_DICT = { + "output_nu": "output_nus", + "output_energy": "output_energies", + } + actual = getattr( + simulation_one_loop.transport.transport_state.packet_collection, + OLD_TO_NEW_DICT[name], + ) + else: + try: + actual = getattr(simulation_one_loop.transport, name) + except AttributeError: + actual = getattr(simulation_one_loop.simulation_state, name) + if name in ["t_radiative"]: + # removing the quantitiness of the data + actual = actual.value actual = pd.Series(actual) - - pdt.assert_almost_equal(actual, refdata(name)) + try: + refdata_keyname = refdata(name) + except KeyError: + refdata_keyname = refdata(f"transport_state/{name}") + pdt.assert_series_equal(actual, refdata_keyname, rtol=1e-5, atol=1e-8) @pytest.mark.parametrize( @@ -102,17 +127,25 @@ def test_plasma_estimates(simulation_one_loop, refdata, name): def test_plasma_state_iterations(simulation_one_loop, refdata, name): actual = getattr(simulation_one_loop, name) + # removing the quantitiness of the data as it will screw up the comparison via pandas + if hasattr(actual, "value"): + actual = actual.value + try: actual = pd.Series(actual) except Exception: actual = pd.DataFrame(actual) - pdt.assert_almost_equal(actual, refdata(name)) + if type(actual) == pd.DataFrame: + pdt.assert_frame_equal(actual, refdata(name), rtol=1e-5, atol=1e-8) + elif type(actual) == pd.Series: + pdt.assert_series_equal(actual, refdata(name)) + else: + raise ValueError(f"Unknown type of actual {type(actual)}") @pytest.fixture(scope="module") def simulation_without_loop(atomic_data_fname, config): - config.atom_data = atomic_data_fname config.montecarlo.iterations = 2 return Simulation.from_config(config) @@ -121,7 +154,6 @@ def simulation_without_loop(atomic_data_fname, config): def test_plasma_state_storer_store( atomic_data_fname, config, simulation_without_loop ): - simulation = simulation_without_loop w_test = np.linspace(0, 1, 20) @@ -144,7 +176,6 @@ def test_plasma_state_storer_store( def test_plasma_state_storer_reshape( atomic_data_fname, config, simulation_without_loop ): - simulation = simulation_without_loop simulation.reshape_plasma_state_store(0) @@ -156,3 +187,8 @@ def test_plasma_state_storer_reshape( # assert_quantity_allclose( # t_rad, simulation_compare_data['test1/t_rad'] * u.Unit('K'), atol=0.0 * u.Unit('K')) + + +def test_version_tag(simulation_without_loop): + simulation = simulation_without_loop + assert simulation.version == tardis.__version__ diff --git a/tardis/montecarlo/spectrum.py b/tardis/spectrum.py similarity index 92% rename from tardis/montecarlo/spectrum.py rename to tardis/spectrum.py index 57639a81112..2479206bfe3 100644 --- a/tardis/montecarlo/spectrum.py +++ b/tardis/spectrum.py @@ -37,8 +37,10 @@ def __init__(self, _frequency, luminosity): self._frequency = _frequency.to("Hz", u.spectral()) self.luminosity = luminosity.to("erg / s") - l_nu_unit = u.def_unit('erg\ s^{-1}\ Hz^{-1}', u.Unit('erg/(s Hz)')) - l_lambda_unit = u.def_unit('erg\ s^{-1}\ \\AA^{-1}', u.Unit('erg/(s AA)')) + l_nu_unit = u.def_unit("erg\ s^{-1}\ Hz^{-1}", u.Unit("erg/(s Hz)")) + l_lambda_unit = u.def_unit( + "erg\ s^{-1}\ \\AA^{-1}", u.Unit("erg/(s AA)") + ) self.frequency = self._frequency[:-1] self.delta_frequency = self._frequency[1] - self._frequency[0] @@ -119,13 +121,17 @@ def plot(self, ax=None, mode="wavelength", **kwargs): `matplotlib documentation <https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D>`_ for a list of all possible arguments. - """ + """ if ax is None: from matplotlib.pyplot import gca ax = gca() if mode == "wavelength": - ax.plot(self.wavelength.value, self.luminosity_density_lambda.value, **kwargs) + ax.plot( + self.wavelength.value, + self.luminosity_density_lambda.value, + **kwargs, + ) ax.set_xlabel( f"Wavelength [{self.wavelength.unit.to_string('latex_inline')}]" ) @@ -133,7 +139,9 @@ def plot(self, ax=None, mode="wavelength", **kwargs): f"$L_\\lambda$ [{self.luminosity_density_lambda.unit.to_string('latex_inline')}]" ) elif mode == "frequency": - ax.plot(self.frequency.value, self.luminosity_density_nu.value, **kwargs) + ax.plot( + self.frequency.value, self.luminosity_density_nu.value, **kwargs + ) ax.set_xlabel( f"Frequency [{self.frequency.unit.to_string('latex_inline')}]" ) diff --git a/tardis/stats/__init__.py b/tardis/stats/__init__.py index 8b137891791..b174821c479 100644 --- a/tardis/stats/__init__.py +++ b/tardis/stats/__init__.py @@ -1 +1,3 @@ - +""" +Providing Poisson statistics that govern the MonteCarlo processes. +""" diff --git a/tardis/tests/fixtures/atom_data.py b/tardis/tests/fixtures/atom_data.py index 520ede4b980..d2b4c7b084a 100644 --- a/tardis/tests/fixtures/atom_data.py +++ b/tardis/tests/fixtures/atom_data.py @@ -1,24 +1,25 @@ -import os from copy import deepcopy - +from pathlib import Path import pytest from tardis.io.atom_data.base import AtomData +from tardis.io.configuration.config_reader import Configuration +from tardis.model.base import SimulationState DEFAULT_ATOM_DATA_UUID = "864f1753714343c41f99cb065710cace" @pytest.fixture(scope="session") def atomic_data_fname(tardis_ref_path): - atomic_data_fname = os.path.join( - tardis_ref_path, "atom_data", "kurucz_cd23_chianti_H_He.h5" + atomic_data_fname = ( + tardis_ref_path / "atom_data" / "kurucz_cd23_chianti_H_He.h5" ) atom_data_missing_str = ( f"{atomic_data_fname} atomic datafiles " f"does not seem to exist" ) - if not os.path.exists(atomic_data_fname): + if not atomic_data_fname.exists(): pytest.exit(atom_data_missing_str) return atomic_data_fname @@ -40,3 +41,67 @@ def atomic_dataset(atomic_data_fname): def kurucz_atomic_data(atomic_dataset): atomic_data = deepcopy(atomic_dataset) return atomic_data + + +@pytest.fixture # (scope="session") +def nlte_atomic_data_fname(tardis_ref_path): + """ + File name for the atomic data file used in NTLE ionization solver tests. + """ + atomic_data_fname = tardis_ref_path / "nlte_atom_data" / "TestNLTE_He_Ti.h5" + + atom_data_missing_str = ( + f"{atomic_data_fname} atomic datafiles " f"does not seem to exist" + ) + + if not atomic_data_fname.exists(): + pytest.exit(atom_data_missing_str) + + return atomic_data_fname + + +@pytest.fixture # (scope="session") +def nlte_atomic_dataset(nlte_atomic_data_fname): + """ + Atomic dataset used for NLTE ionization solver tests. + """ + nlte_atomic_data = AtomData.from_hdf(nlte_atomic_data_fname) + return nlte_atomic_data + + +@pytest.fixture # (scope="session") +def nlte_atom_data(nlte_atomic_dataset): + atomic_data = deepcopy(nlte_atomic_dataset) + return atomic_data + + +@pytest.fixture # (scope="session") +def tardis_model_config_nlte_root(example_configuration_dir): + config = Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_nlte.yml" + ) + config.plasma.nlte_solver = "root" + return config + + +@pytest.fixture # (scope="session") +def tardis_model_config_nlte_lu(example_configuration_dir): + config = Configuration.from_yaml( + example_configuration_dir / "tardis_configv1_nlte.yml" + ) + config.plasma.nlte_solver = "lu" + return config + + +@pytest.fixture # (scope="session") +def nlte_raw_model_root(tardis_model_config_nlte_root, nlte_atom_data): + return SimulationState.from_config( + tardis_model_config_nlte_root, nlte_atom_data + ) + + +@pytest.fixture # (scope="session") +def nlte_raw_model_lu(tardis_model_config_nlte_lu, nlte_atom_data): + return SimulationState.from_config( + tardis_model_config_nlte_lu, nlte_atom_data + ) diff --git a/tardis/tests/fixtures/regression_data.py b/tardis/tests/fixtures/regression_data.py new file mode 100644 index 00000000000..2c295e376e9 --- /dev/null +++ b/tardis/tests/fixtures/regression_data.py @@ -0,0 +1,169 @@ +import os +import re +from pathlib import Path + +import numpy as np +import pandas as pd +import pytest + +from tardis.io.util import HDFWriterMixin + + +class RegressionData: + def __init__(self, request) -> None: + self.request = request + regression_data_path = Path( + request.config.getoption("--tardis-regression-data") + ) + if regression_data_path is None: + pytest.skip("--tardis-regression-data was not specified") + self.regression_data_path = Path( + os.path.expandvars(regression_data_path.expanduser()) + ) + self.enable_generate_reference = request.config.getoption( + "--generate-reference" + ) + self.fname = f"{self.fname_prefix}.UNKNOWN_FORMAT" + + @property + def module_name(self): + return self.request.node.module.__name__ + + @property + def test_name(self): + return self.request.node.name + + @property + def fname_prefix(self): + double_under = re.compile(r"[:\[\]{}]") + no_space = re.compile(r'[,"\']') # quotes and commas + + name = double_under.sub("__", self.test_name) + name = no_space.sub("", name) + return name + + @property + def relative_regression_data_dir(self): + relative_data_dir = Path(self.module_name.replace(".", "/")) + if self.request.cls is not None: + relative_data_dir /= HDFWriterMixin.convert_to_snake_case( + self.request.cls.__name__ + ) + return relative_data_dir + + @property + def absolute_regression_data_dir(self): + return self.regression_data_path / self.relative_regression_data_dir + + @property + def fpath(self): + return self.absolute_regression_data_dir / self.fname + + def sync_dataframe(self, data, key="data"): + """ + Synchronizes the dataframe with the regression data. + + Parameters + ---------- + data : DataFrame + The dataframe to be synchronized. + key : str, optional + The key to use for storing the dataframe in the regression data file. Defaults to "data". + + Returns + ------- + DataFrame or None + The synchronized dataframe if `enable_generate_reference` is `False`, otherwise `None`. + """ + self.fname = f"{self.fname_prefix}.h5" + if self.enable_generate_reference: + self.fpath.parent.mkdir(parents=True, exist_ok=True) + data.to_hdf( + self.fpath, + key=key, + ) + pytest.skip("Skipping test to generate reference data") + else: + return pd.read_hdf(self.fpath, key=key) + + def sync_ndarray(self, data): + """ + Synchronizes the ndarray with the regression data. + + Parameters + ---------- + data : ndarray + The ndarray to be synchronized. + + Returns + ------- + ndarray or None + The synchronized ndarray if `enable_generate_reference` is `False`, otherwise `None`. + """ + self.fname = f"{self.fname_prefix}.npy" + if self.enable_generate_reference: + self.fpath.parent.mkdir(parents=True, exist_ok=True) + self.fpath.parent.mkdir(parents=True, exist_ok=True) + np.save(self.fpath, data) + pytest.skip("Skipping test to generate reference data") + else: + return np.load(self.fpath) + + def sync_str(self, data): + """ + Synchronizes the string with the regression data. + + Parameters + ---------- + data : str + The string to be synchronized. + + Returns + ------- + str or None + The synchronized string if `enable_generate_reference` is `False`, otherwise `None`. + """ + self.fname = f"{self.fname_prefix}.txt" + if self.enable_generate_reference: + self.fpath.parent.mkdir(parents=True, exist_ok=True) + with self.fpath.open("w") as fh: + fh.write(data) + pytest.skip( + f"Skipping test to generate regression_data {self.fpath} data" + ) + else: + with self.fpath.open("r") as fh: + return fh.read() + + def sync_hdf_store(self, tardis_module, update_fname=True): + """ + Synchronizes the HDF store with the regression data. + + Parameters + ---------- + tardis_module : object + The module to be synchronized. + update_fname : bool, optional + Whether to update the file name. Defaults to True. + + Returns + ------- + HDFStore or None + The synchronized HDF store if `enable_generate_reference` is `False`, otherwise `None`. + """ + if update_fname: + self.fname = f"{self.fname_prefix}.h5" + if self.enable_generate_reference: + self.fpath.parent.mkdir(parents=True, exist_ok=True) + with pd.HDFStore(self.fpath, mode="w") as store: + tardis_module.to_hdf(store, overwrite=True) + pytest.skip( + f"Skipping test to generate regression data: {self.fpath}" + ) + else: + return pd.HDFStore(self.fpath, mode="r") + + +@pytest.fixture(scope="function") +def regression_data(request): + return RegressionData(request) diff --git a/tardis/tests/integration_tests/conftest.py b/tardis/tests/integration_tests/conftest.py index 89cfc3cd6bb..2392fbe8446 100644 --- a/tardis/tests/integration_tests/conftest.py +++ b/tardis/tests/integration_tests/conftest.py @@ -8,11 +8,6 @@ # on `version.py`. Find another way to fix it! # from tardis import __githash__ as tardis_githash -from tardis.tests.integration_tests.report import DokuReport -from tardis.tests.integration_tests.plot_helpers import ( - LocalPlotSaver, - RemotePlotSaver, -) def pytest_configure(config): @@ -25,61 +20,6 @@ def pytest_configure(config): open(integration_tests_configpath), Loader=yaml.CLoader ) - if not config.getoption("--generate-reference"): - # Used by DokuReport class to show build environment details in report. - config._environment = [] - # prevent opening dokupath on slave nodes (xdist) - if not hasattr(config, "slaveinput"): - config.dokureport = DokuReport( - config.integration_tests_config["report"] - ) - config.pluginmanager.register(config.dokureport) - - -def pytest_unconfigure(config): - # Unregister only if it was registered in pytest_configure - if config.getvalue("integration-tests") and not config.getoption( - "--generate-reference" - ): - config.pluginmanager.unregister(config.dokureport) - - -def pytest_terminal_summary(terminalreporter): - if terminalreporter.config.getoption( - "--generate-reference" - ) and terminalreporter.config.getvalue("integration-tests"): - # TODO: Add a check whether generation was successful or not. - terminalreporter.write_sep( - "-", - f"Generated reference data: {os.path.join(terminalreporter.config.integration_tests_config['reference'], tardis_githash[:7],)}", - ) - - -@pytest.mark.hookwrapper -def pytest_runtest_makereport(item, call): - # execute all other hooks to obtain the report object - outcome = yield - report = outcome.get_result() - if report.when == "call": - if "plot_object" in item.fixturenames: - plot_obj = item.funcargs["plot_object"] - plot_obj.upload(report) - report.extra = plot_obj.get_extras() - - -@pytest.fixture(scope="function") -def plot_object(request): - integration_tests_config = request.config.integration_tests_config - report_save_mode = integration_tests_config["report"]["save_mode"] - - if report_save_mode == "remote": - return RemotePlotSaver(request, request.config.dokureport.dokuwiki_url) - else: - return LocalPlotSaver( - request, - os.path.join(request.config.dokureport.report_dirpath, "assets"), - ) - @pytest.fixture( scope="class", diff --git a/tardis/tests/integration_tests/plot_helpers.py b/tardis/tests/integration_tests/plot_helpers.py deleted file mode 100644 index a3fd41a2415..00000000000 --- a/tardis/tests/integration_tests/plot_helpers.py +++ /dev/null @@ -1,159 +0,0 @@ -import os -import tempfile - -from pytest_html import extras - -# NOTE: the __githash__ variable is not available anymore -# on `version.py`. Find another way to fix it! - -# from tardis import __githash__ as tardis_githash - - -class BasePlotSaver(object): - def __init__(self, request, dokuwiki_url=None, assets_dirpath=None): - """Base Class for RemotePlotSaver and LocalPlotSaver classes. - These help in uploading plots to DokuWiki instance or saving them - locally in a directory. - - Parameters - ---------- - request : _pytest.python.RequestObject - dokuwiki_url : str - assets_dirpath : str - """ - self.request = request - self._plots = list() - self.plot_html = list() - self.dokuwiki_url = dokuwiki_url - self.assets_dirpath = assets_dirpath - - def add(self, plot, name): - """Accept a plot figure and add it to ``self._plots``. - - Parameters - ---------- - plot : matplotlib.pyplot.figure - name : str - """ - self._plots.append((plot, name)) - - def save(self, plot, filepath, report): - """Mark pass / fail and save a plot with ``name`` to ``filepath``. - - Parameters - ---------- - plot : matplotlib.pyplot.figure - filepath : str - report : _pytest.runner.TestReport - """ - axes = plot.axes[0] - - if report.passed: - axes.text( - 0.8, - 0.8, - "passed", - transform=axes.transAxes, - bbox={"facecolor": "green", "alpha": 0.5, "pad": 10}, - ) - else: - axes.text( - 0.8, - 0.8, - "failed", - transform=axes.transAxes, - bbox={"facecolor": "red", "alpha": 0.5, "pad": 10}, - ) - - plot.savefig(filepath) - - def get_extras(self): - """Return ``self.plot_html`` which is further added into html report. - - Returns - ------- - list - List of strings containing raw html snippet to embed images. - """ - return self.plot_html - - -thumbnail_html_remote = """ -<div class="image" style="float: left"> - <a href="#"> - <img src= "{dokuwiki_url}/lib/exe/fetch.php?media=reports:{githash}:{name}.png" /> - </a> -</div> -""" - - -class RemotePlotSaver(BasePlotSaver): - def __init__(self, request, dokuwiki_url): - super(RemotePlotSaver, self).__init__( - request, dokuwiki_url=dokuwiki_url - ) - - def upload(self, report): - """Upload content of ``self._plots`` to ``self.dokuwiki_url``. - - Parameters - ---------- - report : _pytest.runner.TestReport - - """ - - for plot, name in self._plots: - plot_file = tempfile.NamedTemporaryFile(suffix=".png") - self.save(plot, plot_file.name, report) - - self.request.config.dokureport.doku_conn.medias.add( - f"reports:{tardis_githash[:7]}:{name}.png", - plot_file.name, - ) - - self.plot_html.append( - extras.html( - thumbnail_html_remote.format( - dokuwiki_url=self.dokuwiki_url, - githash=tardis_githash[:7], - name=name, - ) - ) - ) - plot_file.close() - - -thumbnail_html_local = """ -<div class="image" style="float: left"> - <a href="#"> - <img src= "assets/{name}.png" /> - </a> -</div> -""" - - -class LocalPlotSaver(BasePlotSaver): - def __init__(self, request, assets_dirpath): - super(LocalPlotSaver, self).__init__( - request, assets_dirpath=assets_dirpath - ) - - def upload(self, report): - """Save content of ``self._plots`` to ``self.assets_dirpath``. - - Parameters - ---------- - report : _pytest.runner.TestReport - - """ - - for plot, name in self._plots: - self.save( - plot, - os.path.join(self.assets_dirpath, f"{name}.png"), - report, - ) - - self.plot_html.append( - extras.html(thumbnail_html_local.format(name=name)) - ) diff --git a/tardis/tests/integration_tests/report.py b/tardis/tests/integration_tests/report.py deleted file mode 100644 index ff571ff8f72..00000000000 --- a/tardis/tests/integration_tests/report.py +++ /dev/null @@ -1,231 +0,0 @@ -""" -A helper class which works as a plugin to generate the test report and upload it -to the group server's dokuwiki. It inheirts from the class `HTMLReport` of -the `pytest-html` plugin. The test report contains the following details: - -* The git commit hash on which test run was executed. -* The time of generation of test report. -* Number of passes, fails, errors, skips etc. -* Tabular representation of each method - name, result, duration. -* Embedded image of plot(s) and error log below a particular method (if any). - -As a subclass, this class serves as a plugin and hence, `pytest-html` has to be -unregistered during the test run for tis plugin to function. - -When the integration tests are selected for a particular test run, this class -is registered as a plugin in `pytest_configure` and subsequently unregistered in -`pytest_unconfigure`. As a plugin, it implements several "hook" functions -specified in pytest's official documentation. - - -References -========== -1. "Writing Plugins" ( https://pytest.org/latest/writing_plugins.html ) -2. "Hookspec Source" ( https://pytest.org/latest/_modules/_pytest/hookspec.html ) -3. "pytest-html" ( https://www.github.com/davehunt/pytest-html ) -""" -import datetime -import json -import os -import shutil -import time - -# For specifying error while exception handling -from socket import gaierror - -# from tardis import __githash__ as tardis_githash - -try: - from pytest_html import __name__ as pytest_html_path - from pytest_html.plugin import HTMLReport - import requests -except ImportError: - pytest_html = None - dokuwiki = None - requests = None - - -class DokuReport(HTMLReport): - def __init__(self, report_config): - """ - Initialization of a DokuReport object and registration as a plugin - occurs in `pytest_configure`, where a dict containing url, username and - password of dokuwiki is passed through `dokuwiki_details`. - """ - # This will be either "remote" or "local". - self.save_mode = report_config["save_mode"] - - if self.save_mode == "remote": - import dokuwiki - - # Base class accepts a file path to save the report, but we pass an - # empty string as it is redundant for this use case. - super(DokuReport, self).__init__( - logfile=" ", self_contained=True, has_rerun=False - ) - - # Upload the report on a dokuwiki instance. - dokuwiki_details = report_config["dokuwiki"] - try: - self.doku_conn = dokuwiki.DokuWiki( - url=dokuwiki_details["url"], - user=dokuwiki_details["username"], - password=dokuwiki_details["password"], - ) - except (TypeError, gaierror, dokuwiki.DokuWikiError) as e: - raise e - self.doku_conn = None - self.dokuwiki_url = "" - else: - self.dokuwiki_url = dokuwiki_details["url"] - else: - # Save the html report file locally. - self.report_dirpath = os.path.join( - os.path.expandvars( - os.path.expanduser(report_config["reportpath"]) - ), - tardis_githash[:7], - ) - - if os.path.exists(self.report_dirpath): - shutil.rmtree(self.report_dirpath) - os.makedirs(self.report_dirpath) - os.makedirs(os.path.join(self.report_dirpath, "assets")) - - super(DokuReport, self).__init__( - logfile=os.path.join(self.report_dirpath, "report.html"), - self_contained=False, - has_rerun=False, - ) - - self.suite_start_time = time.time() - - def _generate_report(self, session): - """Writes HTML report to a temporary logfile.""" - # Little hack to include suite_time_delta in wiki overview page. - suite_stop_time = time.time() - self.suite_time_delta = suite_stop_time - self.suite_start_time - - report_content = super(DokuReport, self)._generate_report(session) - - # A string which holds the complete report. - report_content = ( - "Test executed on commit " - f"[[https://www.github.com/tardis-sn/tardis/commit/{tardis_githash}|{tardis_githash}]]\n\n" - ) + report_content - - # Quick hack for preventing log to be placed in narrow left out space - report_content = report_content.replace( - 'class="log"', 'class="log" style="clear: both"' - ) - # It was displayed raw on wiki pages, but not needed. - report_content = report_content.replace("<!DOCTYPE html>", "") - return report_content - - def _save_report(self, report_content): - """ - Uploads the report and closes the temporary file. Temporary file is - made using `tempfile` built-in module, it gets deleted upon closing. - """ - if self.save_mode == "remote": - # Upload the report content to wiki - try: - self.doku_conn.pages.set( - f"reports:{tardis_githash[:7]}", report_content - ) - except (gaierror, TypeError): - pass - else: - # Save the file locally at "self.logfile" path - with open(self.logfile, "w") as f: - f.write(report_content) - - with open( - os.path.join(self.report_dirpath, "assets", "style.css"), "w" - ) as f: - f.write(self.style_css) - - def _wiki_overview_entry(self): - """Makes an entry of current test run on overview page of dokuwiki.""" - if self.errors == 0: - if self.failed + self.xpassed == 0: - status = "Passed" - else: - status = "Failed" - else: - status = "Errored" - - suite_start_datetime = datetime.datetime.utcfromtimestamp( - self.suite_start_time - ) - - # Fetch commit message from github. - gh_request = requests.get( - f"https://api.github.com/repos/tardis-sn/tardis/git/commits/{tardis_githash}" - ) - gh_commit_data = json.loads(gh_request.content) - # Pick only first line of commit message - gh_commit_message = gh_commit_data["message"].split("\n")[0] - - # Truncate long commit messages - if len(gh_commit_message) > 60: - gh_commit_message = f"{gh_commit_message[:57]}..." - row = "| " - # Append hash - row += f"[[reports:{tardis_githash[:7]}|{tardis_githash[:7]}]] | " - # Append commit message - row += f"[[https://www.github.com/tardis-sn/tardis/commit/{tardis_githash}|{gh_commit_message}]] | " - # Append start time - row += f'{suite_start_datetime.strftime("%d %b %H:%M:%S")} | ' - # Append time elapsed - row += f"{self.suite_time_delta:.2f} sec | " - # Append status - row += f"{status} |\n" - try: - self.doku_conn.pages.append("/", row) - except (gaierror, TypeError): - pass - - def pytest_sessionfinish(self, session): - """ - This hook function is called by pytest when whole test run is completed. - It calls the two helper methods `_generate_report` and `_save_report`. - """ - report_content = self._generate_report(session) - self._save_report(report_content) - - # This method need not be called if saving locally - if self.save_mode == "remote": - self._wiki_overview_entry() - - def pytest_terminal_summary(self, terminalreporter): - """ - This hook is called by pytest after session ends, and it adds an extra - summary at the end. Here, the success / failure of upload of report - to dokuwiki is logged. - """ - if self.save_mode == "remote": - try: - uploaded_report = self.doku_conn.pages.get( - f"reports:{tardis_githash[:7]}" - ) - except (gaierror, TypeError): - uploaded_report = "" - - if len(uploaded_report) > 0: - terminalreporter.write_sep( - "-", "Successfully uploaded report to Dokuwiki" - ) - terminalreporter.write_sep( - "-", - f"URL: {self.dokuwiki_url}doku.php?id=reports:{tardis_githash[:7]}", - ) - else: - terminalreporter.write_sep( - "-", "Connection not established, upload failed." - ) - else: - if os.path.exists(self.logfile): - super(DokuReport, self).pytest_terminal_summary( - terminalreporter - ) diff --git a/tardis/tests/integration_tests/runner.py b/tardis/tests/integration_tests/runner.py index 88e461311f2..ccd11b136a8 100644 --- a/tardis/tests/integration_tests/runner.py +++ b/tardis/tests/integration_tests/runner.py @@ -1,14 +1,6 @@ import argparse -import datetime -import json import logging import subprocess -import time -import yaml - -import dokuwiki -import requests - logger = logging.getLogger(__name__) @@ -33,15 +25,6 @@ def run_tests(): args = parser.parse_args() - - integration_tests_config = yaml.load( - open(args.yaml_filepath), Loader=yaml.CLoader - ) - doku_conn = dokuwiki.DokuWiki( - url=integration_tests_config["dokuwiki"]["url"], - user=integration_tests_config["dokuwiki"]["username"], - password=integration_tests_config["dokuwiki"]["password"], - ) less_packets = "--less-packets" if args.less_packets else "" test_command = [ "python", @@ -53,34 +36,3 @@ def run_tests(): f"{less_packets}", ] subprocess.call(test_command) - - while True: - # Request Github API and get githash of master on Github. - gh_request = requests.get( - "https://api.github.com/repos/tardis-sn/tardis/branches/master" - ) - gh_master_head_data = json.loads(gh_request.content) - gh_tardis_githash = gh_master_head_data["commit"]["sha"][:7] - - # Check whether a report of this githash is uploaded on dokuwiki. - # If not, then this is a new commit and tests should be executed. - dokuwiki_report = doku_conn.pages.get(f"reports:{gh_tardis_githash}") - - # If dokuwiki returns empty string, then it means that report has not - # been created yet. - if len(dokuwiki_report) == 0: - subprocess.call( - [ - "git", - "pull", - "https://www.github.com/tardis-sn/tardis", - "master", - ] - ) - subprocess.call(test_command) - else: - checked = datetime.datetime.now() - logger.info( - f'Up-to-date. Checked on {checked.strftime("%d-%b-%Y")} {checked.strftime("%H:%M:%S")}' - ) - time.sleep(600) diff --git a/tardis/tests/integration_tests/test_integration.py b/tardis/tests/integration_tests/test_integration.py index 8dc9edc2863..a380763e12a 100644 --- a/tardis/tests/integration_tests/test_integration.py +++ b/tardis/tests/integration_tests/test_integration.py @@ -10,34 +10,34 @@ from tardis.io.atom_data.base import AtomData from tardis.simulation import Simulation -from tardis.io.config_reader import Configuration +from tardis.io.configuration.config_reader import Configuration pytestmarker = [pytest.mark.no_cover, pytest.mark.integration] quantity_comparison = [ ( - "/simulation/runner/last_line_interaction_in_id", - "runner.last_line_interaction_in_id", + "/simulation/transport/last_line_interaction_in_id", + "transport.last_line_interaction_in_id", ), ( - "/simulation/runner/last_line_interaction_out_id", - "runner.last_line_interaction_out_id", + "/simulation/transport/last_line_interaction_out_id", + "transport.last_line_interaction_out_id", ), ( - "/simulation/runner/last_line_interaction_shell_id", - "runner.last_line_interaction_shell_id", + "/simulation/transport/last_line_interaction_shell_id", + "transport.last_line_interaction_shell_id", ), ("/simulation/plasma/j_blues", "plasma.j_blues"), ("/simulation/plasma/j_blue_estimator", "plasma.j_blue_estimator"), ( - "/simulation/runner/packet_luminosity", - "runner.packet_luminosity.cgs.value", + "/simulation/transport/packet_luminosity", + "transport.packet_luminosity.cgs.value", ), ( - "/simulation/runner/montecarlo_virtual_luminosity", - "runner.montecarlo_virtual_luminosity.cgs.value", + "/simulation/transport/montecarlo_virtual_luminosity", + "transport.montecarlo_virtual_luminosity.cgs.value", ), - ("/simulation/runner/output_nu", "runner.output_nu.cgs.value"), + ("/simulation/transport/output_nu", "transport.output_nu.cgs.value"), ("/simulation/plasma/ion_number_density", "plasma.ion_number_density"), ("/simulation/plasma/level_number_density", "plasma.level_number_density"), ("/simulation/plasma/electron_densities", "plasma.electron_densities"), @@ -48,8 +48,8 @@ ), ("/simulation/model/t_radiative", "model.t_radiative.cgs.value"), ("/simulation/model/w", "model.w"), - ("/simulation/runner/j_estimator", "runner.j_estimator"), - ("/simulation/runner/nu_bar_estimator", "runner.nu_bar_estimator"), + ("/simulation/transport/j_estimator", "transport.j_estimator"), + ("/simulation/transport/nu_bar_estimator", "transport.nu_bar_estimator"), ( "/simulation/plasma/j_blues_norm_factor", "plasma.j_blues_norm_factor.cgs.value", @@ -139,7 +139,8 @@ def setup(self, request, reference, data_path): # output model to HDF file, save it at specified path. Skip all tests. # Else simply perform the run and move further for performing # assertions. - self.result.run() + self.result.run_convergence() + self.result.run_final() if request.config.getoption("--generate-reference"): ref_data_path = os.path.join( data_path["reference_path"], f"{self.name}.h5" @@ -175,7 +176,7 @@ def plot_t_rad(self): ax.set_ylabel("t_rad") result_line = ax.plot( - self.result.model.t_rad.cgs, + self.result.simulation_state.t_rad.cgs, color="blue", marker=".", label="Result", @@ -191,7 +192,7 @@ def plot_t_rad(self): error_line = error_ax.plot( ( 1 - - self.result.model.t_rad.cgs.value + - self.result.simulation_state.t_rad.cgs.value / self.reference["/simulation/model/t_rad"] ), color="red", @@ -210,24 +211,25 @@ def test_spectrum(self, plot_object): plot_object.add(self.plot_spectrum(), f"{self.name}_spectrum") assert_allclose( - self.reference["/simulation/runner/spectrum/luminosity_density_nu"], - self.result.runner.spectrum.luminosity_density_nu.cgs.value, + self.reference[ + "/simulation/transport/spectrum/luminosity_density_nu" + ], + self.result.transport.spectrum.luminosity_density_nu.cgs.value, ) assert_allclose( - self.reference["/simulation/runner/spectrum/wavelength"], - self.result.runner.spectrum.wavelength.cgs.value, + self.reference["/simulation/transport/spectrum/wavelength"], + self.result.transport.spectrum.wavelength.cgs.value, ) assert_allclose( self.reference[ - "/simulation/runner/spectrum/luminosity_density_lambda" + "/simulation/transport/spectrum/luminosity_density_lambda" ], - self.result.runner.spectrum.luminosity_density_lambda.cgs.value, + self.result.transport.spectrum.luminosity_density_lambda.cgs.value, ) def plot_spectrum(self): - # `ldl_` prefixed variables associated with `luminosity_density_lambda`. # Axes of subplot are extracted, if we wish to make multiple plots # for different spectrum quantities all in one figure. @@ -237,29 +239,29 @@ def plot_spectrum(self): spectrum_ax.set_ylabel("Flux [cgs]") deviation = 1 - ( - self.result.runner.spectrum.luminosity_density_lambda.cgs.value + self.result.transport.spectrum.luminosity_density_lambda.cgs.value / self.reference[ - "/simulation/runner/spectrum/luminosity_density_lambda" + "/simulation/transport/spectrum/luminosity_density_lambda" ] ) spectrum_ax.plot( - self.reference["/simulation/runner/spectrum/wavelength"], + self.reference["/simulation/transport/spectrum/wavelength"], self.reference[ - "/simulation/runner/spectrum/luminosity_density_lambda" + "/simulation/transport/spectrum/luminosity_density_lambda" ], color="black", ) spectrum_ax.plot( - self.reference["/simulation/runner/spectrum/wavelength"], - self.result.runner.spectrum.luminosity_density_lambda.cgs.value, + self.reference["/simulation/transport/spectrum/wavelength"], + self.result.transport.spectrum.luminosity_density_lambda.cgs.value, color="red", ) spectrum_ax.set_xticks([]) deviation_ax = plt.subplot(gs[1]) deviation_ax.plot( - self.reference["/simulation/runner/spectrum/wavelength"], + self.reference["/simulation/transport/spectrum/wavelength"], deviation, color="black", ) diff --git a/tardis/montecarlo/tests/test_spectrum.py b/tardis/tests/test_spectrum.py similarity index 95% rename from tardis/montecarlo/tests/test_spectrum.py rename to tardis/tests/test_spectrum.py index 2d94ff6de4a..c0862b2ebb8 100644 --- a/tardis/montecarlo/tests/test_spectrum.py +++ b/tardis/tests/test_spectrum.py @@ -6,7 +6,7 @@ from tardis import constants as c import astropy.tests.helper as test_helper from numpy.testing import assert_almost_equal -from tardis.montecarlo.spectrum import ( +from tardis.spectrum import ( TARDISSpectrum, ) @@ -38,7 +38,7 @@ def spectrum(request): request.param["lum"], ) distance = request.param["distance"] - if distance: + if distance is not None: data.distance = distance return data @@ -67,7 +67,7 @@ def test_luminosity_density_lambda(spectrum): def test_flux_nu(spectrum): - if getattr(spectrum, "distance", None): + if getattr(spectrum, "distance", None) is not None: with pytest.warns(DeprecationWarning): test_helper.assert_quantity_allclose( @@ -82,7 +82,7 @@ def test_flux_nu(spectrum): def test_flux_lambda(spectrum): - if getattr(spectrum, "distance", None): + if getattr(spectrum, "distance", None) is not None: with pytest.warns(DeprecationWarning): test_helper.assert_quantity_allclose( @@ -113,7 +113,7 @@ def test_luminosity_to_flux(): def test_f_nu_to_f_lambda(spectrum): expected = ( spectrum.luminosity_density_nu - * spectrum.frequency ** 2 + * spectrum.frequency**2 / c.c.to("angstrom/s") ).to("erg / (s angstrom)") print(expected) @@ -122,7 +122,7 @@ def test_f_nu_to_f_lambda(spectrum): ) expected = ( spectrum.luminosity_density_nu - * spectrum.frequency ** 2 + * spectrum.frequency**2 / c.c.to("angstrom/s") ).to("erg / (s angstrom)") np.testing.assert_allclose( diff --git a/tardis/tests/test_tardis_full.py b/tardis/tests/test_tardis_full.py index 2f341d2169a..1c6b12ed936 100644 --- a/tardis/tests/test_tardis_full.py +++ b/tardis/tests/test_tardis_full.py @@ -1,23 +1,26 @@ -import os -import pytest -import numpy as np +from pathlib import Path + import numpy.testing as npt +import pandas as pd +import pytest from astropy import units as u from astropy.tests.helper import assert_quantity_allclose -from tardis.simulation.base import Simulation -from tardis.io.config_reader import Configuration - from tardis import run_tardis +from tardis.io.configuration.config_reader import Configuration +from tardis.simulation.base import Simulation +from tardis.tests.fixtures.regression_data import RegressionData -def test_run_tardis_from_config_obj(atomic_data_fname): +def test_run_tardis_from_config_obj( + atomic_data_fname, example_configuration_dir: Path +): """ Tests whether the run_tardis function can take in the Configuration object as arguments """ config = Configuration.from_yaml( - "tardis/io/tests/data/tardis_configv1_verysimple.yml" + example_configuration_dir / "tardis_configv1_verysimple.yml" ) config["atom_data"] = atomic_data_fname @@ -27,87 +30,64 @@ def test_run_tardis_from_config_obj(atomic_data_fname): pytest.fail(str(e.args[0])) -class TestRunnerSimple: +class TestTransportSimple: """ Very simple run """ - name = "test_runner_simple" + regression_data: RegressionData = None @pytest.fixture(scope="class") - def runner(self, atomic_data_fname, tardis_ref_data, generate_reference): + def transport_state( + self, + request, + atomic_data_fname, + generate_reference, + example_configuration_dir: Path, + ): config = Configuration.from_yaml( - "tardis/io/tests/data/tardis_configv1_verysimple.yml" + str(example_configuration_dir / "tardis_configv1_verysimple.yml") ) config["atom_data"] = atomic_data_fname simulation = Simulation.from_config(config) - simulation.run() - - if not generate_reference: - return simulation.runner - else: - simulation.runner.hdf_properties = [ - "j_blue_estimator", - "spectrum", - "spectrum_virtual", - ] - simulation.runner.to_hdf( - tardis_ref_data, "", self.name, overwrite=True - ) - pytest.skip("Reference data was generated during this run.") + simulation.run_convergence() + simulation.run_final() - @pytest.fixture(scope="class") - def refdata(self, tardis_ref_data): - def get_ref_data(key): - return tardis_ref_data[os.path.join(self.name, key)] + transport_state = simulation.transport.transport_state + request.cls.regression_data = RegressionData(request) + request.cls.regression_data.sync_hdf_store(transport_state) - return get_ref_data + return transport_state - def test_j_blue_estimators(self, runner, refdata): - j_blue_estimator = refdata("j_blue_estimator").values + def get_expected_data(self, key: str): + return pd.read_hdf(self.regression_data.fpath, key) - npt.assert_allclose(runner.j_blue_estimator, j_blue_estimator) + def test_j_blue_estimators(self, transport_state): + key = "transport_state/j_blue_estimator" + expected = self.get_expected_data(key) - def test_spectrum(self, runner, refdata): - luminosity = u.Quantity(refdata("spectrum/luminosity"), "erg /s") - - assert_quantity_allclose(runner.spectrum.luminosity, luminosity) - - def test_virtual_spectrum(self, runner, refdata): - luminosity = u.Quantity( - refdata("spectrum_virtual/luminosity"), "erg /s" + npt.assert_allclose( + transport_state.radfield_mc_estimators.j_blue_estimator, + expected.values, ) - assert_quantity_allclose(runner.spectrum_virtual.luminosity, luminosity) - - def test_runner_properties(self, runner): - """ - Tests whether a number of runner attributes exist and also verifies - their types + def test_spectrum(self, transport_state): + key = "transport_state/spectrum/luminosity" + expected = self.get_expected_data(key) - Currently, runner attributes needed to call the model routine to_hdf5 - are checked. - """ + luminosity = u.Quantity(expected, "erg /s") - virt_type = np.ndarray - - props_required_by_modeltohdf5 = dict( - [ - ("virt_packet_last_interaction_type", virt_type), - ("virt_packet_last_line_interaction_in_id", virt_type), - ("virt_packet_last_line_interaction_out_id", virt_type), - ("virt_packet_last_interaction_in_nu", virt_type), - ("virt_packet_nus", virt_type), - ("virt_packet_energies", virt_type), - ] + assert_quantity_allclose( + transport_state.spectrum.luminosity, luminosity ) - required_props = props_required_by_modeltohdf5.copy() + def test_virtual_spectrum(self, transport_state): + key = "transport_state/spectrum_virtual/luminosity" + expected = self.get_expected_data(key) + + luminosity = u.Quantity(expected, "erg /s") - for prop, prop_type in required_props.items(): - actual = getattr(runner, prop) - assert type(actual) == prop_type, ( - f"wrong type of attribute '{prop}':" - f"expected {prop_type}, found {type(actual)}" - ) + assert_quantity_allclose( + transport_state.spectrum_virtual.luminosity, luminosity + ) diff --git a/tardis/tests/test_tardis_full_formal_integral.py b/tardis/tests/test_tardis_full_formal_integral.py index d83a7987a08..d3a0eeaecc5 100644 --- a/tardis/tests/test_tardis_full_formal_integral.py +++ b/tardis/tests/test_tardis_full_formal_integral.py @@ -1,20 +1,21 @@ -import os -import pytest +from pathlib import Path + import numpy.testing as npt +import pytest from astropy import units as u from astropy.tests.helper import assert_quantity_allclose +from tardis.io.configuration.config_reader import Configuration from tardis.simulation.base import Simulation -from tardis.io.config_reader import Configuration config_line_modes = ["downbranch", "macroatom"] interpolate_shells = [-1, 30] @pytest.fixture(scope="module", params=config_line_modes) -def base_config(request): +def base_config(request, example_configuration_dir: Path): config = Configuration.from_yaml( - "tardis/io/tests/data/tardis_configv1_verysimple.yml" + example_configuration_dir / "tardis_configv1_verysimple.yml" ) config["plasma"]["line_interaction_type"] = request.param @@ -34,15 +35,15 @@ def config(base_config, request): return base_config -class TestRunnerSimpleFormalInegral: +class TestTransportSimpleFormalIntegral: """ Very simple run with the formal integral spectral synthesis method """ - _name = "test_runner_simple_integral" + _name = "test_transport_simple_integral" @pytest.fixture(scope="class") - def runner( + def transport( self, config, atomic_data_fname, tardis_ref_data, generate_reference ): config.atom_data = atomic_data_fname @@ -52,17 +53,14 @@ def runner( self.name += "_interp" simulation = Simulation.from_config(config) - simulation.run() + simulation.run_convergence() + simulation.run_final() if not generate_reference: - return simulation.runner + return simulation.transport else: - simulation.runner.hdf_properties = [ - "j_blue_estimator", - "spectrum", - "spectrum_integrated", - ] - simulation.runner.to_hdf( + simulation.transport.hdf_properties = ["transport_state"] + simulation.transport.to_hdf( tardis_ref_data, "", self.name, overwrite=True ) pytest.skip("Reference data was generated during this run.") @@ -70,30 +68,32 @@ def runner( @pytest.fixture(scope="class") def refdata(self, tardis_ref_data): def get_ref_data(key): - return tardis_ref_data[os.path.join(self.name, key)] + return tardis_ref_data[f"{self.name}/{key}"] return get_ref_data - def test_j_blue_estimators(self, runner, refdata): - j_blue_estimator = refdata("j_blue_estimator").values + def test_j_blue_estimators(self, transport, refdata): + j_blue_estimator = refdata("transport_state/j_blue_estimator").values - npt.assert_allclose(runner.j_blue_estimator, j_blue_estimator) + npt.assert_allclose( + transport.transport_state.radfield_mc_estimators.j_blue_estimator, + j_blue_estimator, + ) - def test_spectrum(self, runner, refdata): - luminosity = u.Quantity(refdata("spectrum/luminosity"), "erg /s") + def test_spectrum(self, transport, refdata): + luminosity = u.Quantity( + refdata("transport_state/spectrum/luminosity"), "erg /s" + ) - assert_quantity_allclose(runner.spectrum.luminosity, luminosity) + assert_quantity_allclose( + transport.transport_state.spectrum.luminosity, luminosity + ) - def test_spectrum_integrated(self, runner, refdata): + def test_spectrum_integrated(self, transport, refdata): luminosity = u.Quantity( - refdata("spectrum_integrated/luminosity"), "erg /s" + refdata("transport_state/spectrum_integrated/luminosity"), "erg /s" ) - print( - "actual, desired: ", - luminosity, - runner.spectrum_integrated.luminosity, - ) assert_quantity_allclose( - runner.spectrum_integrated.luminosity, luminosity + transport.transport_state.spectrum_integrated.luminosity, luminosity ) diff --git a/tardis/tests/test_util.py b/tardis/tests/test_util.py index 9fa47d19c40..335f9442d14 100644 --- a/tardis/tests/test_util.py +++ b/tardis/tests/test_util.py @@ -1,7 +1,7 @@ import pytest import numpy as np import numpy.testing as npt -import os + from astropy import units as u from io import StringIO @@ -24,12 +24,19 @@ convert_abundances_format, ) -data_path = os.path.join("tardis", "io", "tests", "data") - @pytest.fixture -def artis_abundances_fname(): - return os.path.join(data_path, "artis_abundances.dat") +def artis_abundances_fname(example_model_file_dir): + return example_model_file_dir / "artis_abundances.dat" + + +@pytest.fixture(scope="session") +def monkeysession(): + """ + Creates a session-scoped fixture to be used to mock functions dependent on the user. + """ + with pytest.MonkeyPatch.context() as mp: + yield mp def test_malformed_species_error(): @@ -119,10 +126,10 @@ def test_calculate_luminosity(string_io, distance, result): @pytest.mark.parametrize( ["nu", "t", "i"], [ - (10 ** 6, 1000, 3.072357852080765e-22), - (10 ** 6, 300, 9.21707305730458e-23), - (10 ** 8, 1000, 6.1562660718558254e-24), - (10 ** 8, 300, 1.846869480674048e-24), + (10**6, 1000, 3.072357852080765e-22), + (10**6, 300, 9.21707305730458e-23), + (10**8, 1000, 6.1562660718558254e-24), + (10**8, 300, 1.846869480674048e-24), ], ) def test_intensity_black_body(nu, t, i): diff --git a/tardis/transport/__init__.py b/tardis/transport/__init__.py new file mode 100644 index 00000000000..41612a06e1d --- /dev/null +++ b/tardis/transport/__init__.py @@ -0,0 +1,3 @@ +""" +Handling the packet propagation. +""" diff --git a/tardis/montecarlo/montecarlo_numba/frame_transformations.py b/tardis/transport/frame_transformations.py similarity index 85% rename from tardis/montecarlo/montecarlo_numba/frame_transformations.py rename to tardis/transport/frame_transformations.py index 5bdcab59d70..a9768fc6f1a 100644 --- a/tardis/montecarlo/montecarlo_numba/frame_transformations.py +++ b/tardis/transport/frame_transformations.py @@ -2,22 +2,19 @@ from numba import njit -from tardis.montecarlo.montecarlo_numba import ( +from tardis.transport.montecarlo import ( njit_dict_no_parallel, ) -from tardis.montecarlo.montecarlo_numba.numba_config import ( - C_SPEED_OF_LIGHT, - ENABLE_FULL_RELATIVITY, -) +from tardis.transport.montecarlo.numba_config import C_SPEED_OF_LIGHT @njit(**njit_dict_no_parallel) -def get_doppler_factor(r, mu, time_explosion): +def get_doppler_factor(r, mu, time_explosion, enable_full_relativity): inv_c = 1 / C_SPEED_OF_LIGHT inv_t = 1 / time_explosion beta = r * inv_t * inv_c - if not ENABLE_FULL_RELATIVITY: + if not enable_full_relativity: return get_doppler_factor_partial_relativity(mu, beta) else: return get_doppler_factor_full_relativity(mu, beta) @@ -34,7 +31,7 @@ def get_doppler_factor_full_relativity(mu, beta): @njit(**njit_dict_no_parallel) -def get_inverse_doppler_factor(r, mu, time_explosion): +def get_inverse_doppler_factor(r, mu, time_explosion, enable_full_relativity): """ Calculate doppler factor for frame transformation @@ -47,7 +44,7 @@ def get_inverse_doppler_factor(r, mu, time_explosion): inv_c = 1 / C_SPEED_OF_LIGHT inv_t = 1 / time_explosion beta = r * inv_t * inv_c - if not ENABLE_FULL_RELATIVITY: + if not enable_full_relativity: return get_inverse_doppler_factor_partial_relativity(mu, beta) else: return get_inverse_doppler_factor_full_relativity(mu, beta) @@ -87,7 +84,7 @@ def angle_aberration_CMF_to_LF(r_packet, time_explosion, mu): """ ct = C_SPEED_OF_LIGHT * time_explosion beta = r_packet.r / (ct) - return (r_packet.mu + beta) / (1.0 + beta * mu) + return (mu + beta) / (1.0 + beta * mu) @njit(**njit_dict_no_parallel) diff --git a/tardis/transport/geometry/__init__.py b/tardis/transport/geometry/__init__.py new file mode 100644 index 00000000000..d585337f711 --- /dev/null +++ b/tardis/transport/geometry/__init__.py @@ -0,0 +1,3 @@ +""" +Calculating distances. +""" diff --git a/tardis/montecarlo/montecarlo_numba/calculate_distances.py b/tardis/transport/geometry/calculate_distances.py similarity index 80% rename from tardis/montecarlo/montecarlo_numba/calculate_distances.py rename to tardis/transport/geometry/calculate_distances.py index 3e114efa592..3649f6c811f 100644 --- a/tardis/montecarlo/montecarlo_numba/calculate_distances.py +++ b/tardis/transport/geometry/calculate_distances.py @@ -2,20 +2,22 @@ from numba import njit -from tardis.montecarlo.montecarlo_numba import ( +from tardis.transport.montecarlo import ( njit_dict_no_parallel, ) -from tardis.montecarlo.montecarlo_numba.numba_config import ( +from tardis.transport.montecarlo.numba_config import ( C_SPEED_OF_LIGHT, MISS_DISTANCE, SIGMA_THOMSON, - ENABLE_FULL_RELATIVITY, CLOSE_LINE_THRESHOLD, ) -from tardis.montecarlo.montecarlo_numba.utils import MonteCarloException -from tardis.montecarlo.montecarlo_numba.r_packet import print_r_packet_properties +from tardis.transport.montecarlo.utils import MonteCarloException +from tardis.transport.montecarlo.r_packet import ( + print_r_packet_properties, +) + @njit(**njit_dict_no_parallel) def calculate_distance_boundary(r, mu, r_inner, r_outer): @@ -59,18 +61,21 @@ def calculate_distance_boundary(r, mu, r_inner, r_outer): return distance, delta_shell -# @log_decorator -#'float64(RPacket, float64, int64, float64, float64)' @njit(**njit_dict_no_parallel) def calculate_distance_line( - r_packet, comov_nu, is_last_line, nu_line, time_explosion + r_packet, + comov_nu, + is_last_line, + nu_line, + time_explosion, + enable_full_relativity, ): """ Calculate distance until RPacket is in resonance with the next line Parameters ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket + r_packet : tardis.transport.montecarlo.r_packet.RPacket comov_nu : float comoving frequency at the CURRENT position of the RPacket is_last_line : bool @@ -98,14 +103,9 @@ def calculate_distance_line( if nu_diff >= 0: distance = (nu_diff / nu) * C_SPEED_OF_LIGHT * time_explosion else: - print("WARNING: nu difference is less than 0.0; see packet information below") - print_r_packet_properties(r_packet) - raise MonteCarloException( - "nu difference is less than 0.0; for more" - " information, see print statement beforehand" - ) + raise MonteCarloException("nu difference is less than 0.0") - if ENABLE_FULL_RELATIVITY: + if enable_full_relativity: return calculate_distance_line_full_relativity( nu_line, nu, time_explosion, r_packet ) diff --git a/tardis/transport/montecarlo/__init__.py b/tardis/transport/montecarlo/__init__.py new file mode 100644 index 00000000000..6cc925c5879 --- /dev/null +++ b/tardis/transport/montecarlo/__init__.py @@ -0,0 +1,30 @@ +""" +Faciliating the MonteCarlo iterations. + +During a simulation run, a number of MonteCarlo iterations specified +in the configuration are run using the numba compiler. +Most of the iterations are used to calculate the steady-state plasma +properties and with the last iteration, the spectrum is determined. +""" + +""" +Implements the main loop of the MonteCarlo routine. +""" + +from llvmlite import binding + +binding.set_option("tmp", "-non-global-value-max-name-size=2048") +njit_dict = {"fastmath": True, "error_model": "numpy", "parallel": True} +njit_dict_no_parallel = { + "fastmath": True, + "error_model": "numpy", + "parallel": False, +} + +from tardis.transport.montecarlo.r_packet import RPacket +from tardis.transport.montecarlo.montecarlo_main_loop import ( + montecarlo_main_loop, +) +from tardis.transport.montecarlo.packet_collections import ( + PacketCollection, +) diff --git a/tardis/transport/montecarlo/base.py b/tardis/transport/montecarlo/base.py new file mode 100644 index 00000000000..ce62695eb4d --- /dev/null +++ b/tardis/transport/montecarlo/base.py @@ -0,0 +1,310 @@ +import logging + +from astropy import units as u +from numba import cuda, set_num_threads + +from tardis import constants as const +from tardis.io.logger import montecarlo_tracking as mc_tracker +from tardis.io.util import HDFWriterMixin +from tardis.transport.montecarlo import ( + montecarlo_main_loop, + numba_config, +) +from tardis.transport.montecarlo.estimators.radfield_mc_estimators import ( + initialize_estimator_statistics, +) +from tardis.transport.montecarlo.formal_integral import FormalIntegrator +from tardis.transport.montecarlo.montecarlo_configuration import ( + MonteCarloConfiguration, + configuration_initialize, +) +from tardis.transport.montecarlo.montecarlo_transport_state import ( + MonteCarloTransportState, +) +from tardis.transport.montecarlo.numba_interface import ( + opacity_state_initialize, +) +from tardis.transport.montecarlo.packet_trackers import ( + rpacket_trackers_to_dataframe, +) +from tardis.util.base import ( + quantity_linspace, + refresh_packet_pbar, + update_iterations_pbar, +) + +logger = logging.getLogger(__name__) + + +# TODO: refactor this into more parts +class MonteCarloTransportSolver(HDFWriterMixin): + """ + This class modifies the MonteCarloTransportState to solve the radiative + transfer problem. + """ + + hdf_properties = ["transport_state"] + + hdf_name = "transport" + + def __init__( + self, + spectrum_frequency, + virtual_spectrum_spawn_range, + enable_full_relativity, + line_interaction_type, + integrator_settings, + spectrum_method, + packet_source, + enable_virtual_packet_logging=False, + enable_rpacket_tracking=False, + nthreads=1, + debug_packets=False, + logger_buffer=1, + use_gpu=False, + montecarlo_configuration=None, + ): + # inject different packets + self.spectrum_frequency = spectrum_frequency + self.virtual_spectrum_spawn_range = virtual_spectrum_spawn_range + self.enable_full_relativity = enable_full_relativity + self.line_interaction_type = line_interaction_type + self.integrator_settings = integrator_settings + self.spectrum_method = spectrum_method + self._integrator = None + + self.use_gpu = use_gpu + + self.enable_vpacket_tracking = enable_virtual_packet_logging + self.enable_rpacket_tracking = enable_rpacket_tracking + self.montecarlo_configuration = montecarlo_configuration + + self.packet_source = packet_source + + # Setting up the Tracking array for storing all the RPacketTracker instances + self.rpacket_tracker = None + + # Set number of threads + self.nthreads = nthreads + + # set up logger based on config + mc_tracker.DEBUG_MODE = debug_packets + mc_tracker.BUFFER = logger_buffer + + def initialize_transport_state( + self, + simulation_state, + plasma, + no_of_packets, + no_of_virtual_packets=0, + iteration=0, + ): + if not plasma.continuum_interaction_species.empty: + gamma_shape = plasma.gamma.shape + else: + gamma_shape = (0, 0) + + packet_collection = self.packet_source.create_packets( + no_of_packets, seed_offset=iteration + ) + estimators = initialize_estimator_statistics( + plasma.tau_sobolevs.shape, gamma_shape + ) + + geometry_state = simulation_state.geometry.to_numba() + opacity_state = opacity_state_initialize( + plasma, + self.line_interaction_type, + self.montecarlo_configuration.DISABLE_LINE_SCATTERING, + self.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + ) + transport_state = MonteCarloTransportState( + packet_collection, + estimators, + spectrum_frequency=self.spectrum_frequency, + geometry_state=geometry_state, + opacity_state=opacity_state, + ) + + transport_state.enable_full_relativity = ( + self.montecarlo_configuration.ENABLE_FULL_RELATIVITY + ) + transport_state.integrator_settings = self.integrator_settings + transport_state._integrator = FormalIntegrator( + simulation_state, plasma, self + ) + configuration_initialize( + self.montecarlo_configuration, self, no_of_virtual_packets + ) + + return transport_state + + def run( + self, + transport_state, + time_explosion, + iteration=0, + total_iterations=0, + show_progress_bars=True, + ): + """ + Run the montecarlo calculation + + Parameters + ---------- + model : tardis.model.SimulationState + plasma : tardis.plasma.BasePlasma + no_of_packets : int + no_of_virtual_packets : int + total_iterations : int + The total number of iterations in the simulation. + + Returns + ------- + None + """ + set_num_threads(self.nthreads) + self.transport_state = transport_state + + number_of_vpackets = self.montecarlo_configuration.NUMBER_OF_VPACKETS + + ( + v_packets_energy_hist, + last_interaction_tracker, + vpacket_tracker, + rpacket_trackers, + ) = montecarlo_main_loop( + transport_state.packet_collection, + transport_state.geometry_state, + time_explosion.cgs.value, + transport_state.opacity_state, + self.montecarlo_configuration, + transport_state.radfield_mc_estimators, + transport_state.spectrum_frequency.value, + number_of_vpackets, + iteration=iteration, + show_progress_bars=show_progress_bars, + total_iterations=total_iterations, + ) + + transport_state._montecarlo_virtual_luminosity.value[ + : + ] = v_packets_energy_hist + transport_state.last_interaction_type = last_interaction_tracker.types + transport_state.last_interaction_in_nu = last_interaction_tracker.in_nus + transport_state.last_line_interaction_in_id = ( + last_interaction_tracker.in_ids + ) + transport_state.last_line_interaction_out_id = ( + last_interaction_tracker.out_ids + ) + transport_state.last_line_interaction_shell_id = ( + last_interaction_tracker.shell_ids + ) + + if self.montecarlo_configuration.ENABLE_VPACKET_TRACKING and ( + number_of_vpackets > 0 + ): + transport_state.vpacket_tracker = vpacket_tracker + + update_iterations_pbar(1) + refresh_packet_pbar() + # Condition for Checking if RPacket Tracking is enabled + if self.montecarlo_configuration.ENABLE_RPACKET_TRACKING: + transport_state.rpacket_tracker = rpacket_trackers + + if self.transport_state.rpacket_tracker is not None: + self.transport_state.rpacket_tracker_df = ( + rpacket_trackers_to_dataframe( + self.transport_state.rpacket_tracker + ) + ) + transport_state.virt_logging = ( + self.montecarlo_configuration.ENABLE_VPACKET_TRACKING + ) + + @classmethod + def from_config( + cls, config, packet_source, enable_virtual_packet_logging=False + ): + """ + Create a new MontecarloTransport instance from a Configuration object. + + Parameters + ---------- + config : tardis.io.config_reader.Configuration + virtual_packet_logging : bool + + Returns + ------- + MontecarloTransport + """ + if config.plasma.disable_electron_scattering: + logger.warning( + "Disabling electron scattering - this is not physical." + "Likely bug in formal integral - " + "will not give same results." + ) + numba_config.SIGMA_THOMSON = 1e-200 + else: + logger.debug("Electron scattering switched on") + numba_config.SIGMA_THOMSON = const.sigma_T.to("cm^2").value + + spectrum_frequency = quantity_linspace( + config.spectrum.stop.to("Hz", u.spectral()), + config.spectrum.start.to("Hz", u.spectral()), + num=config.spectrum.num + 1, + ) + running_mode = config.spectrum.integrated.compute.upper() + + if running_mode == "GPU": + if cuda.is_available(): + use_gpu = True + else: + raise ValueError( + """The GPU option was selected for the formal_integral, + but no CUDA GPU is available.""" + ) + elif running_mode == "AUTOMATIC": + use_gpu = bool(cuda.is_available()) + elif running_mode == "CPU": + use_gpu = False + else: + raise ValueError( + """An invalid option for compute was passed. The three + valid values are 'GPU', 'CPU', and 'Automatic'.""" + ) + + montecarlo_configuration = MonteCarloConfiguration() + + montecarlo_configuration.DISABLE_LINE_SCATTERING = ( + config.plasma.disable_line_scattering + ) + + montecarlo_configuration.DISABLE_ELECTRON_SCATTERING = ( + config.plasma.disable_electron_scattering + ) + + montecarlo_configuration.INITIAL_TRACKING_ARRAY_LENGTH = ( + config.montecarlo.tracking.initial_array_length + ) + + return cls( + spectrum_frequency=spectrum_frequency, + virtual_spectrum_spawn_range=config.montecarlo.virtual_spectrum_spawn_range, + enable_full_relativity=config.montecarlo.enable_full_relativity, + line_interaction_type=config.plasma.line_interaction_type, + integrator_settings=config.spectrum.integrated, + spectrum_method=config.spectrum.method, + packet_source=packet_source, + debug_packets=config.montecarlo.debug_packets, + logger_buffer=config.montecarlo.logger_buffer, + enable_virtual_packet_logging=( + config.spectrum.virtual.virtual_packet_logging + | enable_virtual_packet_logging + ), + enable_rpacket_tracking=config.montecarlo.tracking.track_rpacket, + nthreads=config.montecarlo.nthreads, + use_gpu=use_gpu, + montecarlo_configuration=montecarlo_configuration, + ) diff --git a/tardis/transport/montecarlo/conftest.py b/tardis/transport/montecarlo/conftest.py new file mode 100644 index 00000000000..8be326055f5 --- /dev/null +++ b/tardis/transport/montecarlo/conftest.py @@ -0,0 +1,16 @@ +import pytest + +from tardis.io.configuration.config_reader import Configuration + + +@pytest.fixture(scope="function") +def continuum_config( + tardis_config_verysimple_nlte, +): + continuum_config = Configuration.from_config_dict( + tardis_config_verysimple_nlte + ) + continuum_config.plasma.continuum_interaction.species = ["H I", "Ti II"] + continuum_config.plasma.nlte_ionization_species = [] + + return continuum_config diff --git a/tardis/transport/montecarlo/estimators/__init__.py b/tardis/transport/montecarlo/estimators/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/transport/montecarlo/estimators/continuum_radfield_properties.py b/tardis/transport/montecarlo/estimators/continuum_radfield_properties.py new file mode 100644 index 00000000000..dcd3b9e1560 --- /dev/null +++ b/tardis/transport/montecarlo/estimators/continuum_radfield_properties.py @@ -0,0 +1,225 @@ +from dataclasses import dataclass + +import numpy as np +import pandas as pd +from astropy import units as u + +import tardis.constants as const +from tardis.io.atom_data import AtomData +from tardis.model.radiation_field_state import ( + DiluteBlackBodyRadiationFieldState, +) +from tardis.transport.montecarlo.estimators.radfield_mc_estimators import ( + RadiationFieldMCEstimators, +) +from tardis.transport.montecarlo.estimators.util import ( + bound_free_estimator_array2frame, + integrate_array_by_blocks, +) +from tardis.plasma.properties.continuum_processes import PhotoIonBoltzmannFactor + +H = const.h.cgs.value + + +class MCContinuumPropertiesSolver: + def __init__( + self, + atom_data: AtomData, + ): + self.atom_data = atom_data + + def solve( + self, + radfield_mc_estimators: RadiationFieldMCEstimators, + time_simulation, + volume, + ): + """ + Solve for the continuum properties. + + Parameters + ---------- + radfield_mc_estimators : RadiationFieldMCEstimators + The Monte Carlo estimators for the radiation field. + time_simulation : float + The simulation time. + volume : float + The volume of the cells. + + Returns + ------- + ContinuumProperties + The calculated continuum properties. + """ + photo_ion_norm_factor = (time_simulation * volume * H) ** -1 + + photo_ionization_rate_coefficient = bound_free_estimator_array2frame( + radfield_mc_estimators.photo_ion_estimator, + self.atom_data.level2continuum_edge_idx, + ) + photo_ionization_rate_coefficient *= photo_ion_norm_factor + + stimulated_recomb_rate_factor = bound_free_estimator_array2frame( + radfield_mc_estimators.stim_recomb_estimator, + self.atom_data.level2continuum_edge_idx, + ) + stimulated_recomb_rate_factor *= photo_ion_norm_factor + + return ContinuumProperties( + stimulated_recomb_rate_factor, photo_ionization_rate_coefficient + ) + + +class DiluteBlackBodyContinuumPropertiesSolver: + def __init__(self, atom_data: AtomData) -> None: + self.atom_data = atom_data + + def solve( + self, + dilute_blackbody_radiationfield_state: DiluteBlackBodyRadiationFieldState, + t_electrons: u.Quantity, + ): + """ + Solve for the continuum properties. + + Parameters + ---------- + dilute_blackbody_radiationfield_state : DiluteBlackBodyRadiationFieldState + The state of the dilute blackbody radiation field. + t_electrons : u.Quantity + The temperature of the electrons. + + Returns + ------- + ContinuumProperties + The calculated continuum properties. + + """ + photo_ion_boltzmann_factor = PhotoIonBoltzmannFactor.calculate( + self.atom_data.photoionization_data, t_electrons + ) + mean_intensity_photo_ion_df = ( + self.calculate_mean_intensity_photo_ion_table( + dilute_blackbody_radiationfield_state + ) + ) + + photo_ion_rate_coeff = self.calculate_photo_ionization_rate_coefficient( + mean_intensity_photo_ion_df + ) + stimulated_recomb_rate_coeff = ( + self.calculate_stimulated_recomb_rate_factor( + mean_intensity_photo_ion_df, + photo_ion_boltzmann_factor, + ) + ) + + return ContinuumProperties( + stimulated_recomb_rate_coeff, photo_ion_rate_coeff + ) + + def calculate_photo_ionization_rate_coefficient( + self, + mean_intensity_photo_ion_df: pd.DataFrame, + ): + """ + Calculate the photoionization rate coefficient. + + Parameters + ---------- + mean_intensity_photo_ion_df : pd.DataFrame + The mean intensity of the radiation field at the frequencies of the photoionization table. + + Returns + ------- + pd.DataFrame + The calculated photoionization rate coefficient. + + Notes + ----- + Equation 16 in Lucy 2003. + """ + gamma = mean_intensity_photo_ion_df.multiply( + 4.0 + * np.pi + * self.atom_data.photoionization_data.x_sect + / (self.atom_data.photoionization_data.nu * H), + axis=0, + ) + gamma = integrate_array_by_blocks( + gamma.values, + self.atom_data.photoionization_data.nu.values, + self.atom_data.photo_ion_block_references, + ) + gamma = pd.DataFrame(gamma, index=self.atom_data.photo_ion_unique_index) + return gamma + + def calculate_stimulated_recomb_rate_factor( + self, + mean_intensity_photo_ion_df: pd.DataFrame, + photo_ion_boltzmann_factor: np.ndarray, + ): + """ + Calculate the stimulated recombination rate factor (the phi_ik are multiplied in the plasma). + + Parameters + ---------- + mean_intensity_photo_ion_df : pd.DataFrame + The mean intensity of the radiation field at the frequencies of the photoionization table. + photo_ion_boltzmann_factor: np.ndarray + The Boltzmann factor for the photoionization table. + + Returns + ------- + pd.DataFrame + The calculated stimulated recombination rate factor. + + Notes + ----- + Equation 15 in Lucy 2003. + """ + alpha_stim_factor = ( + mean_intensity_photo_ion_df * photo_ion_boltzmann_factor + ) + alpha_stim_factor = alpha_stim_factor.multiply( + 4.0 + * np.pi + * self.atom_data.photoionization_data.x_sect + / (self.atom_data.photoionization_data.nu * H), + axis=0, + ) + alpha_stim_factor = integrate_array_by_blocks( + alpha_stim_factor.values, + self.atom_data.photoionization_data.nu.values, + self.atom_data.photo_ion_block_references, + ) + + alpha_stim_factor = pd.DataFrame( + alpha_stim_factor, index=self.atom_data.photo_ion_unique_index + ) + + return alpha_stim_factor + + def calculate_mean_intensity_photo_ion_table( + self, + dilute_blackbody_radiationfield_state: DiluteBlackBodyRadiationFieldState, + ): + mean_intensity = ( + dilute_blackbody_radiationfield_state.calculate_mean_intensity( + self.atom_data.photoionization_data.nu.values + ) + ) + mean_intensity_df = pd.DataFrame( + mean_intensity, + index=self.atom_data.photoionization_data.index, + columns=np.arange( + len(dilute_blackbody_radiationfield_state.t_radiative) + ), + ) + return mean_intensity_df + + +@dataclass +class ContinuumProperties: + stimulated_recomb_rate_factor: pd.DataFrame + photo_ionization_rate_coefficient: pd.DataFrame diff --git a/tardis/transport/montecarlo/estimators/dilute_blackbody_properties.py b/tardis/transport/montecarlo/estimators/dilute_blackbody_properties.py new file mode 100644 index 00000000000..8e7c98c7ed7 --- /dev/null +++ b/tardis/transport/montecarlo/estimators/dilute_blackbody_properties.py @@ -0,0 +1,57 @@ +import numpy as np +from astropy import units as u +from scipy.special import zeta + +from tardis import constants as const +from tardis.model.radiation_field_state import ( + DiluteBlackBodyRadiationFieldState, +) + +DILUTION_FACTOR_ESTIMATOR_CONSTANT = ( + (const.c**2 / (2 * const.h)) + * (15 / np.pi**4) + * (const.h / const.k_B) ** 4 + / (4 * np.pi) +).cgs.value +T_RADIATIVE_ESTIMATOR_CONSTANT = ( + (np.pi**4 / (15 * 24 * zeta(5, 1))) * (const.h / const.k_B) +).cgs.value + + +class MCDiluteBlackBodyRadFieldSolver: + def __init__(self) -> None: + pass + + def solve(self, radfield_mc_estimators, time_of_simulation, volume): + """ + Calculate an updated radiation field from the :math: + `\\bar{nu}_\\textrm{estimator}` and :math:`\\J_\\textrm{estimator}` + calculated in the montecarlo simulation. + The details of the calculation can be found in the documentation. + + Parameters + ---------- + nubar_estimator : np.ndarray (float) + j_estimator : np.ndarray (float) + + Returns + ------- + t_radiative : astropy.units.Quantity (float) + dilution_factor : numpy.ndarray (float) + """ + temperature_radiative = ( + T_RADIATIVE_ESTIMATOR_CONSTANT + * radfield_mc_estimators.nu_bar_estimator + / radfield_mc_estimators.j_estimator + ) * u.K + dilution_factor = radfield_mc_estimators.j_estimator / ( + 4 + * const.sigma_sb.cgs.value + * temperature_radiative.value**4 + * time_of_simulation.value + * volume + ) + + return DiluteBlackBodyRadiationFieldState( + temperature_radiative, dilution_factor + ) diff --git a/tardis/transport/montecarlo/estimators/radfield_estimator_calcs.py b/tardis/transport/montecarlo/estimators/radfield_estimator_calcs.py new file mode 100644 index 00000000000..dd574abcedd --- /dev/null +++ b/tardis/transport/montecarlo/estimators/radfield_estimator_calcs.py @@ -0,0 +1,120 @@ +from math import exp + +from numba import njit + +from tardis.transport.montecarlo import ( + njit_dict_no_parallel, +) +from tardis.transport.montecarlo.numba_config import KB, H +from tardis.transport.frame_transformations import ( + calc_packet_energy, + calc_packet_energy_full_relativity, +) + + +@njit(**njit_dict_no_parallel) +def update_base_estimators( + r_packet, distance, estimator_state, comov_nu, comov_energy +): + """ + Updating the estimators + """ + estimator_state.j_estimator[r_packet.current_shell_id] += ( + comov_energy * distance + ) + estimator_state.nu_bar_estimator[r_packet.current_shell_id] += ( + comov_energy * distance * comov_nu + ) + + +@njit(**njit_dict_no_parallel) +def update_bound_free_estimators( + comov_nu, + comov_energy, + shell_id, + distance, + estimator_state, + t_electron, + x_sect_bfs, + current_continua, + bf_threshold_list_nu, +): + """ + Update the estimators for bound-free processes. + + Parameters + ---------- + comov_nu : float + comov_energy : float + shell_id : int + distance : float + numba_estimator : tardis.transport.montecarlo.numba_interface.Estimators + t_electron : float + Electron temperature in the current cell. + x_sect_bfs : numpy.ndarray, dtype float + Photoionization cross-sections of all bound-free continua for + which absorption is possible for frequency `comov_nu`. + current_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `comov_nu`. + bf_threshold_list_nu : numpy.ndarray, dtype float + Threshold frequencies for photoionization sorted by decreasing frequency. + """ + # TODO: Add full relativity mode + boltzmann_factor = exp(-(H * comov_nu) / (KB * t_electron)) + for i, current_continuum in enumerate(current_continua): + photo_ion_rate_estimator_increment = ( + comov_energy * distance * x_sect_bfs[i] / comov_nu + ) + estimator_state.photo_ion_estimator[ + current_continuum, shell_id + ] += photo_ion_rate_estimator_increment + estimator_state.stim_recomb_estimator[current_continuum, shell_id] += ( + photo_ion_rate_estimator_increment * boltzmann_factor + ) + estimator_state.photo_ion_estimator_statistics[ + current_continuum, shell_id + ] += 1 + + nu_th = bf_threshold_list_nu[current_continuum] + bf_heating_estimator_increment = ( + comov_energy * distance * x_sect_bfs[i] * (1 - nu_th / comov_nu) + ) + estimator_state.bf_heating_estimator[ + current_continuum, shell_id + ] += bf_heating_estimator_increment + estimator_state.stim_recomb_cooling_estimator[ + current_continuum, shell_id + ] += (bf_heating_estimator_increment * boltzmann_factor) + + +@njit(**njit_dict_no_parallel) +def update_line_estimators( + radfield_mc_estimators, + r_packet, + cur_line_id, + distance_trace, + time_explosion, + enable_full_relativity, +): + """ + Function to update the line estimators + + Parameters + ---------- + estimators : tardis.transport.montecarlo.numba_interface.Estimators + r_packet : tardis.transport.montecarlo.r_packet.RPacket + cur_line_id : int + distance_trace : float + time_explosion : float + """ + if not enable_full_relativity: + energy = calc_packet_energy(r_packet, distance_trace, time_explosion) + else: + energy = calc_packet_energy_full_relativity(r_packet) + + radfield_mc_estimators.j_blue_estimator[ + cur_line_id, r_packet.current_shell_id + ] += (energy / r_packet.nu) + radfield_mc_estimators.Edotlu_estimator[ + cur_line_id, r_packet.current_shell_id + ] += energy diff --git a/tardis/transport/montecarlo/estimators/radfield_mc_estimators.py b/tardis/transport/montecarlo/estimators/radfield_mc_estimators.py new file mode 100644 index 00000000000..de91643e5a5 --- /dev/null +++ b/tardis/transport/montecarlo/estimators/radfield_mc_estimators.py @@ -0,0 +1,140 @@ +import numpy as np +from numba import float64, int64 +from numba.experimental import jitclass +from numba.typed import List + + +def initialize_estimator_statistics(tau_sobolev_shape, gamma_shape): + """ + Initializes the estimators used in the Monte Carlo simulation. + + Parameters + ---------- + tau_sobolev_shape : tuple + Shape of the array with the Sobolev optical depth. + gamma_shape : tuple + Shape of the array with the photoionization rate coefficients. + + Returns + ------- + Estimators + The initialized estimators. + + Examples + -------- + >>> tau_sobolev_shape = (10, 20) + >>> gamma_shape = (5, 5) + >>> initialize_estimators(tau_sobolev_shape, gamma_shape) + <Estimators object at 0x...> + """ + j_estimator = np.zeros(tau_sobolev_shape[1], dtype=np.float64) + nu_bar_estimator = np.zeros(tau_sobolev_shape[1], dtype=np.float64) + j_blue_estimator = np.zeros(tau_sobolev_shape) + Edotlu_estimator = np.zeros(tau_sobolev_shape) + + photo_ion_estimator = np.zeros(gamma_shape, dtype=np.float64) + stim_recomb_estimator = np.zeros(gamma_shape, dtype=np.float64) + stim_recomb_cooling_estimator = np.zeros(gamma_shape, dtype=np.float64) + bf_heating_estimator = np.zeros(gamma_shape, dtype=np.float64) + + stim_recomb_cooling_estimator = np.zeros(gamma_shape, dtype=np.float64) + + photo_ion_estimator_statistics = np.zeros(gamma_shape, dtype=np.int64) + return RadiationFieldMCEstimators( + j_estimator, + nu_bar_estimator, + j_blue_estimator, + Edotlu_estimator, + photo_ion_estimator, + stim_recomb_estimator, + bf_heating_estimator, + stim_recomb_cooling_estimator, + photo_ion_estimator_statistics, + ) + + +base_estimators_spec = [ + ("j_estimator", float64[:]), + ("nu_bar_estimator", float64[:]), + ("j_blue_estimator", float64[:, :]), + ("Edotlu_estimator", float64[:, :]), +] + +continuum_estimators_spec = [ + ("photo_ion_estimator", float64[:, :]), + ("stim_recomb_estimator", float64[:, :]), + ("bf_heating_estimator", float64[:, :]), + ("stim_recomb_cooling_estimator", float64[:, :]), + ("photo_ion_estimator_statistics", int64[:, :]), +] + + +@jitclass(base_estimators_spec + continuum_estimators_spec) +class RadiationFieldMCEstimators: + def __init__( + self, + j_estimator, + nu_bar_estimator, + j_blue_estimator, + Edotlu_estimator, + photo_ion_estimator, + stim_recomb_estimator, + bf_heating_estimator, + stim_recomb_cooling_estimator, + photo_ion_estimator_statistics, + ): + self.j_estimator = j_estimator + self.nu_bar_estimator = nu_bar_estimator + self.j_blue_estimator = j_blue_estimator + self.Edotlu_estimator = Edotlu_estimator + self.photo_ion_estimator = photo_ion_estimator + self.stim_recomb_estimator = stim_recomb_estimator + self.bf_heating_estimator = bf_heating_estimator + self.stim_recomb_cooling_estimator = stim_recomb_cooling_estimator + self.photo_ion_estimator_statistics = photo_ion_estimator_statistics + + def increment(self, other): + """ + Increments each estimator with the corresponding estimator from another instance of the class. + + Parameters + ---------- + other : RadiationFieldMCEstimators + Another instance of the RadiationFieldMCEstimators class. + + Returns + ------- + None + """ + self.j_estimator += other.j_estimator + self.nu_bar_estimator += other.nu_bar_estimator + self.j_blue_estimator += other.j_blue_estimator + self.Edotlu_estimator += other.Edotlu_estimator + self.photo_ion_estimator += other.photo_ion_estimator + self.stim_recomb_estimator += other.stim_recomb_estimator + self.bf_heating_estimator += other.bf_heating_estimator + self.stim_recomb_cooling_estimator += ( + other.stim_recomb_cooling_estimator + ) + self.photo_ion_estimator_statistics += ( + other.photo_ion_estimator_statistics + ) + + def create_estimator_list(self, number): + estimator_list = List() + + for i in range(number): + estimator_list.append( + RadiationFieldMCEstimators( + np.copy(self.j_estimator), + np.copy(self.nu_bar_estimator), + np.copy(self.j_blue_estimator), + np.copy(self.Edotlu_estimator), + np.copy(self.photo_ion_estimator), + np.copy(self.stim_recomb_estimator), + np.copy(self.bf_heating_estimator), + np.copy(self.stim_recomb_cooling_estimator), + np.copy(self.photo_ion_estimator_statistics), + ) + ) + return estimator_list diff --git a/tardis/transport/montecarlo/estimators/tests/conftest.py b/tardis/transport/montecarlo/estimators/tests/conftest.py new file mode 100644 index 00000000000..8be326055f5 --- /dev/null +++ b/tardis/transport/montecarlo/estimators/tests/conftest.py @@ -0,0 +1,16 @@ +import pytest + +from tardis.io.configuration.config_reader import Configuration + + +@pytest.fixture(scope="function") +def continuum_config( + tardis_config_verysimple_nlte, +): + continuum_config = Configuration.from_config_dict( + tardis_config_verysimple_nlte + ) + continuum_config.plasma.continuum_interaction.species = ["H I", "Ti II"] + continuum_config.plasma.nlte_ionization_species = [] + + return continuum_config diff --git a/tardis/transport/montecarlo/estimators/tests/test_continuum_property_solver.py b/tardis/transport/montecarlo/estimators/tests/test_continuum_property_solver.py new file mode 100644 index 00000000000..744683a49e9 --- /dev/null +++ b/tardis/transport/montecarlo/estimators/tests/test_continuum_property_solver.py @@ -0,0 +1,85 @@ +from copy import deepcopy + +import numpy.testing as npt +import pandas.testing as pdt +import pytest + +from tardis.transport.montecarlo.estimators.continuum_radfield_properties import ( + DiluteBlackBodyContinuumPropertiesSolver, + MCContinuumPropertiesSolver, +) +from tardis.simulation import Simulation + + +def test_continuum_estimators( + continuum_config, + nlte_atomic_dataset, +): + nlte_atomic_dataset = deepcopy(nlte_atomic_dataset) + continuum_simulation = Simulation.from_config( + continuum_config, + atom_data=nlte_atomic_dataset, + virtual_packet_logging=False, + ) + # continuum_simulation.run_convergence() + continuum_properties_solver_dilute_bb = ( + DiluteBlackBodyContinuumPropertiesSolver( + continuum_simulation.plasma.atomic_data + ) + ) + + continuum_properties_dilute_bb = ( + continuum_properties_solver_dilute_bb.solve( + continuum_simulation.simulation_state.radiation_field_state, + continuum_simulation.plasma.t_electrons, + ) + ) + + continuum_plasma = continuum_simulation.plasma + + pdt.assert_frame_equal( + continuum_properties_dilute_bb.photo_ionization_rate_coefficient, + continuum_simulation.plasma.gamma, + ) + stimulated_recomb_rate_coeff = ( + continuum_properties_dilute_bb.stimulated_recomb_rate_factor + * continuum_plasma.phi_ik.loc[ + continuum_properties_dilute_bb.stimulated_recomb_rate_factor.index + ] + ) + pdt.assert_frame_equal( + stimulated_recomb_rate_coeff, continuum_plasma.alpha_stim + ) + + continuum_simulation.run_final() + + continuum_properties_solver_mc = MCContinuumPropertiesSolver( + continuum_simulation.plasma.atomic_data + ) + transport_state = continuum_simulation.transport.transport_state + continuum_properties_mc = continuum_properties_solver_mc.solve( + transport_state.radfield_mc_estimators, + transport_state.time_of_simulation, + transport_state.geometry_state.volume, + ) + + continuum_plasma.update( + gamma_estimator=transport_state.radfield_mc_estimators.photo_ion_estimator, + alpha_stim_estimator=transport_state.radfield_mc_estimators.stim_recomb_estimator, + bf_heating_coeff_estimator=transport_state.radfield_mc_estimators.bf_heating_estimator, + stim_recomb_cooling_coeff_estimator=transport_state.radfield_mc_estimators.stim_recomb_cooling_estimator, + ) + + pdt.assert_frame_equal( + continuum_properties_mc.photo_ionization_rate_coefficient, + continuum_simulation.plasma.gamma, + ) + stimulated_recomb_rate_coeff = ( + continuum_properties_mc.stimulated_recomb_rate_factor + * continuum_plasma.phi_ik.loc[ + continuum_properties_dilute_bb.stimulated_recomb_rate_factor.index + ] + ) + pdt.assert_frame_equal( + stimulated_recomb_rate_coeff, continuum_plasma.alpha_stim + ) diff --git a/tardis/transport/montecarlo/estimators/util.py b/tardis/transport/montecarlo/estimators/util.py new file mode 100644 index 00000000000..86a91ef7915 --- /dev/null +++ b/tardis/transport/montecarlo/estimators/util.py @@ -0,0 +1,67 @@ +import numpy as np +import pandas as pd +from numba import njit, prange + +from tardis.transport.montecarlo import njit_dict + + +def bound_free_estimator_array2frame( + bound_free_estimator_array, level2continuum_idx +): + """ + Transform a bound-free estimator array to a DataFrame. + + This function transforms a bound-free estimator array with entries + sorted by frequency to a multi-indexed DataFrame sorted by level. + + Parameters + ---------- + bf_estimator_array : numpy.ndarray, dtype float + Array of bound-free estimators (e.g., for the stimulated recombination rate) + with entries sorted by the threshold frequency of the bound-free continuum. + level2continuum_idx : pandas.Series, dtype int + Maps a level MultiIndex (atomic_number, ion_number, level_number) to + the continuum_idx of the corresponding bound-free continuum (which are + sorted by decreasing frequency). + + Returns + ------- + pandas.DataFrame, dtype float + Bound-free estimators indexed by (atomic_number, ion_number, level_number). + """ + bf_estimator_frame = pd.DataFrame( + bound_free_estimator_array, index=level2continuum_idx.index + ).sort_index() + bf_estimator_frame.columns.name = "Shell No." + return bf_estimator_frame + + +@njit(**njit_dict) +def integrate_array_by_blocks(f, x, block_references): + """ + Integrate a function over blocks. + + This function integrates a function `f` defined at locations `x` + over blocks given in `block_references`. + + Parameters + ---------- + f : numpy.ndarray, dtype float + 2D input array to integrate. + x : numpy.ndarray, dtype float + 1D array with the sample points corresponding to the `f` values. + block_references : numpy.ndarray, dtype int + 1D array with the start indices of the blocks to be integrated. + + Returns + ------- + numpy.ndarray, dtype float + 2D array with integrated values. + """ + integrated = np.zeros((len(block_references) - 1, f.shape[1])) + for i in prange(f.shape[1]): # columns + for j in prange(len(integrated)): # rows + start = block_references[j] + stop = block_references[j + 1] + integrated[j, i] = np.trapz(f[start:stop, i], x[start:stop]) + return integrated diff --git a/tardis/montecarlo/montecarlo_numba/formal_integral.py b/tardis/transport/montecarlo/formal_integral.py similarity index 69% rename from tardis/montecarlo/montecarlo_numba/formal_integral.py rename to tardis/transport/montecarlo/formal_integral.py index 041ac18313b..c699490fcc5 100644 --- a/tardis/montecarlo/montecarlo_numba/formal_integral.py +++ b/tardis/transport/montecarlo/formal_integral.py @@ -1,4 +1,3 @@ -import sys import warnings import numpy as np import pandas as pd @@ -9,17 +8,23 @@ from tardis import constants as const from numba import njit, char, float64, int64, typeof, byte, prange from numba.experimental import jitclass -import pdb - -from tardis.montecarlo.montecarlo_numba.numba_config import SIGMA_THOMSON -from tardis.montecarlo.montecarlo_numba import njit_dict, njit_dict_no_parallel -from tardis.montecarlo.montecarlo_numba.numba_interface import ( - numba_plasma_initialize, - NumbaModel, - NumbaPlasma, + + +from tardis.opacities.opacity_state import ( + OpacityState, + opacity_state_initialize, +) +from tardis.transport.montecarlo.numba_config import SIGMA_THOMSON +from tardis.transport.montecarlo import njit_dict, njit_dict_no_parallel +from tardis.transport.montecarlo.numba_interface import ( + opacity_state_initialize, + OpacityState, +) +from tardis.transport.montecarlo.formal_integral_cuda import ( + CudaFormalIntegrator, ) -from tardis.montecarlo.spectrum import TARDISSpectrum +from tardis.spectrum import TARDISSpectrum C_INV = 3.33564e-11 M_PI = np.arccos(-1) @@ -33,7 +38,8 @@ class IntegrationError(Exception): @njit(**njit_dict) def numba_formal_integral( - model, + geometry, + time_explosion, plasma, iT, inu, @@ -46,16 +52,23 @@ def numba_formal_integral( N, ): """ - model, plasma, and estimator are the numba variants + Returns + ------- + L : float64 array + integrated luminosities + I_nu_p : float64 2D array + intensities at each p-ray multiplied by p + frequency x p-ray grid """ + # todo: add all the original todos # Initialize the output which is shared among threads L = np.zeros(inu_size, dtype=np.float64) # global read-only values size_line, size_shell = tau_sobolev.shape size_tau = size_line * size_shell - R_ph = model.r_inner[0] # make sure these are cgs - R_max = model.r_outer[size_shell - 1] + R_ph = geometry.r_inner[0] # make sure these are cgs + R_max = geometry.r_outer[size_shell - 1] pp = np.zeros(N, dtype=np.float64) # check exp_tau = np.zeros(size_tau, dtype=np.float64) exp_tau = np.exp(-tau_sobolev.T.ravel()) # maybe make this 2D? @@ -63,8 +76,9 @@ def numba_formal_integral( line_list_nu = plasma.line_list_nu # done with instantiation # now loop over wavelength in spectrum + I_nu_p = np.zeros((inu_size, N), dtype=np.float64) for nu_idx in prange(inu_size): - I_nu = np.zeros(N, dtype=np.float64) + I_nu = I_nu_p[nu_idx] z = np.zeros(2 * size_shell, dtype=np.float64) shell_id = np.zeros(2 * size_shell, dtype=np.int64) offset = 0 @@ -95,7 +109,9 @@ def numba_formal_integral( p = pp[p_idx] # initialize z intersections for p values - size_z = populate_z(model, p, z, shell_id) # check returns + size_z = populate_z( + geometry, time_explosion, p, z, shell_id + ) # check returns # initialize I_nu if p <= R_ph: I_nu[p_idx] = intensity_black_body(nu * z[0], iT) @@ -108,7 +124,7 @@ def numba_formal_integral( idx_nu_start = line_search(plasma.line_list_nu, nu_start, size_line) offset = shell_id[0] * size_line # start tracking accumulated e-scattering optical depth - zstart = model.time_explosion / C_INV * (1.0 - z[0]) + zstart = time_explosion / C_INV * (1.0 - z[0]) # Initialize "pointers" pline = int(idx_nu_start) pexp_tau = int(offset + idx_nu_start) @@ -128,10 +144,9 @@ def numba_formal_integral( nu_end = nu_ends[i] nu_end_idx = nu_ends_idxs[i] for _ in range(max(nu_end_idx - pline, 0)): - # calculate e-scattering optical depth to next resonance point zend = ( - model.time_explosion + time_explosion / C_INV * (1.0 - line_list_nu[pline] / nu) ) # check @@ -173,9 +188,7 @@ def numba_formal_integral( # calculate e-scattering optical depth to grid cell boundary Jkkp = 0.5 * (Jred_lu[pJred_lu] + Jblue_lu[pJblue_lu]) - zend = ( - model.time_explosion / C_INV * (1.0 - nu_end / nu) - ) # check + zend = time_explosion / C_INV * (1.0 - nu_end / nu) # check escat_contrib += ( (zend - zstart) * escat_op * (Jkkp - I_nu[p_idx]) ) @@ -190,26 +203,26 @@ def numba_formal_integral( I_nu[p_idx] *= p L[nu_idx] = 8 * M_PI * M_PI * trapezoid_integration(I_nu, R_max / N) - return L + return L, I_nu_p -integrator_spec = [ - ("model", NumbaModel.class_type.instance_type), - ("plasma", NumbaPlasma.class_type.instance_type), - ("points", int64), -] +# integrator_spec = [ +# ("model", NumbaModel.class_type.instance_type), +# ("plasma", OpacityState.class_type.instance_type), +# ("points", int64), +# ] -@jitclass(integrator_spec) +# @jitclass(integrator_spec) class NumbaFormalIntegrator(object): """ Helper class for performing the formal integral with numba. """ - def __init__(self, model, plasma, points=1000): - - self.model = model + def __init__(self, geometry, time_explosion, plasma, points=1000): + self.geometry = geometry + self.time_explosion = time_explosion self.plasma = plasma self.points = points @@ -225,9 +238,12 @@ def formal_integral( electron_density, N, ): - """simple wrapper for the numba implementation of the formal integral""" + """ + Simple wrapper for the numba implementation of the formal integral + """ return numba_formal_integral( - self.model, + self.geometry, + self.time_explosion, self.plasma, iT, inu, @@ -243,36 +259,75 @@ def formal_integral( class FormalIntegrator(object): """ - Class containing the formal integrator + Class containing the formal integrator. + + If there is a NVIDIA CUDA GPU available, + the formal integral will automatically run + on it. If multiple GPUs are available, it will + choose the first one that it sees. You can + read more about selecting different GPUs on + Numba's CUDA documentation. + + Parameters + ---------- + model : tardis.model.SimulationState + plasma : tardis.plasma.BasePlasma + transport : tardis.transport.montecarlo.MontecarloTransport + points : int64 """ - def __init__(self, model, plasma, runner, points=1000): - - self.model = model - self.runner = runner + def __init__(self, simulation_state, plasma, transport, points=1000): + self.simulation_state = simulation_state + self.transport = transport self.points = points + if transport: + self.montecarlo_configuration = ( + self.transport.montecarlo_configuration + ) if plasma: - self.plasma = numba_plasma_initialize( - plasma, runner.line_interaction_type + self.plasma = opacity_state_initialize( + plasma, + transport.line_interaction_type, + self.montecarlo_configuration.DISABLE_LINE_SCATTERING, + self.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, ) self.atomic_data = plasma.atomic_data self.original_plasma = plasma + self.levels_index = plasma.levels def generate_numba_objects(self): """instantiate the numba interface objects needed for computing the formal integral""" - self.numba_model = NumbaModel( - self.runner.r_inner_i, - self.runner.r_outer_i, - self.model.time_explosion.to("s").value, - ) - self.numba_plasma = numba_plasma_initialize( - self.original_plasma, self.runner.line_interaction_type + from tardis.model.geometry.radial1d import NumbaRadial1DGeometry + + self.numba_radial_1d_geometry = NumbaRadial1DGeometry( + self.transport.r_inner_i, + self.transport.r_outer_i, + self.transport.r_inner_i + / self.simulation_state.time_explosion.to("s").value, + self.transport.r_outer_i + / self.simulation_state.time_explosion.to("s").value, ) - - self.numba_integrator = NumbaFormalIntegrator( - self.numba_model, self.numba_plasma, self.points + self.opacity_state = opacity_state_initialize( + self.original_plasma, + self.transport.line_interaction_type, + self.montecarlo_configuration.DISABLE_LINE_SCATTERING, + self.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, ) + if self.transport.use_gpu: + self.integrator = CudaFormalIntegrator( + self.numba_radial_1d_geometry, + self.simulation_state.time_explosion.cgs.value, + self.opacity_state, + self.points, + ) + else: + self.integrator = NumbaFormalIntegrator( + self.numba_radial_1d_geometry, + self.simulation_state.time_explosion.cgs.value, + self.opacity_state, + self.points, + ) def check(self, raises=True): """ @@ -291,21 +346,30 @@ def raise_or_return(message): warnings.warn(message) return False - for obj in (self.model, self.plasma, self.runner): + for obj in (self.simulation_state, self.plasma, self.transport): if obj is None: return raise_or_return( "The integrator is missing either model, plasma or " - "runner. Please make sure these are provided to the " + "transport. Please make sure these are provided to the " "FormalIntegrator." ) - if not self.runner.line_interaction_type in ["downbranch", "macroatom"]: + if not self.transport.line_interaction_type in [ + "downbranch", + "macroatom", + ]: return raise_or_return( "The FormalIntegrator currently only works for " 'line_interaction_type == "downbranch"' 'and line_interaction_type == "macroatom"' ) + if self.montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED: + return raise_or_return( + "The FormalIntegrator currently does not work for " + "continuum interactions." + ) + return True def calculate_spectrum( @@ -317,7 +381,7 @@ def calculate_spectrum( self.check(raises) N = points or self.points if interpolate_shells == 0: # Default Value - interpolate_shells = max(2 * self.model.no_of_shells, 80) + interpolate_shells = max(2 * self.simulation_state.no_of_shells, 80) warnings.warn( "The number of interpolate_shells was not " f"specified. The value was set to {interpolate_shells}." @@ -351,23 +415,25 @@ def make_source_function(self): Parameters ---------- - model : tardis.model.Radial1DModel + model : tardis.model.SimulationState Returns ------- Numpy array containing ( 1 - exp(-tau_ul) ) S_ul ordered by wavelength of the transition u -> l """ + simulation_state = self.simulation_state + transport = self.transport + montecarlo_transport_state = transport.transport_state - model = self.model - runner = self.runner - + # macro_ref = self.atomic_data.macro_atom_references macro_ref = self.atomic_data.macro_atom_references - macro_data = self.atomic_data.macro_atom_data + # macro_data = self.atomic_data.macro_atom_data + macro_data = self.original_plasma.macro_atom_data - no_lvls = len(self.atomic_data.levels) - no_shells = len(model.w) + no_lvls = len(self.levels_index) + no_shells = len(simulation_state.dilution_factor) - if runner.line_interaction_type == "macroatom": + if transport.line_interaction_type == "macroatom": internal_jump_mask = (macro_data.transition_type >= 0).values ma_int_data = macro_data[internal_jump_mask] internal = self.original_plasma.transition_probabilities[ @@ -377,33 +443,48 @@ def make_source_function(self): source_level_idx = ma_int_data.source_level_idx.values destination_level_idx = ma_int_data.destination_level_idx.values - Edotlu_norm_factor = 1 / (runner.time_of_simulation * model.volume) + Edotlu_norm_factor = 1 / ( + montecarlo_transport_state.packet_collection.time_of_simulation + * simulation_state.volume + ) exptau = 1 - np.exp(-self.original_plasma.tau_sobolevs) - Edotlu = Edotlu_norm_factor * exptau * runner.Edotlu_estimator + Edotlu = ( + Edotlu_norm_factor + * exptau + * montecarlo_transport_state.radfield_mc_estimators.Edotlu_estimator + ) # The following may be achieved by calling the appropriate plasma # functions Jbluelu_norm_factor = ( ( const.c.cgs - * model.time_explosion - / (4 * np.pi * runner.time_of_simulation * model.volume) + * simulation_state.time_explosion + / ( + 4 + * np.pi + * montecarlo_transport_state.time_of_simulation + * simulation_state.volume + ) ) .to("1/(cm^2 s)") .value ) # Jbluelu should already by in the correct order, i.e. by wavelength of # the transition l->u - Jbluelu = runner.j_blue_estimator * Jbluelu_norm_factor + Jbluelu = ( + transport.transport_state.radfield_mc_estimators.j_blue_estimator + * Jbluelu_norm_factor + ) upper_level_index = self.atomic_data.lines.index.droplevel( "level_number_lower" ) - e_dot_lu = pd.DataFrame(Edotlu, index=upper_level_index) + e_dot_lu = pd.DataFrame(Edotlu.values, index=upper_level_index) e_dot_u = e_dot_lu.groupby(level=[0, 1, 2]).sum() e_dot_u_src_idx = macro_ref.loc[e_dot_u.index].references_idx.values - if runner.line_interaction_type == "macroatom": + if transport.line_interaction_type == "macroatom": C_frame = pd.DataFrame( columns=np.arange(no_shells), index=macro_ref.index ) @@ -433,12 +514,13 @@ def make_source_function(self): (self.atomic_data.macro_atom_data.transition_type == -1).values ] q_ul = tmp.set_index(transitions_index) - t = model.time_explosion.value + t = simulation_state.time_explosion.value + t = simulation_state.time_explosion.value lines = self.atomic_data.lines.set_index("line_id") wave = lines.wavelength_cm.loc[ transitions.transition_line_id ].values.reshape(-1, 1) - if runner.line_interaction_type == "macroatom": + if transport.line_interaction_type == "macroatom": e_dot_u = C_frame.loc[e_dot_u.index] att_S_ul = wave * (q_ul * e_dot_u) * t / (4 * np.pi) @@ -460,10 +542,16 @@ def make_source_function(self): att_S_ul, Jredlu, Jbluelu, e_dot_u ) else: - runner.r_inner_i = runner.r_inner_cgs - runner.r_outer_i = runner.r_outer_cgs - runner.tau_sobolevs_integ = self.original_plasma.tau_sobolevs.values - runner.electron_densities_integ = ( + transport.r_inner_i = ( + montecarlo_transport_state.geometry_state.r_inner + ) + transport.r_outer_i = ( + montecarlo_transport_state.geometry_state.r_outer + ) + transport.tau_sobolevs_integ = ( + self.original_plasma.tau_sobolevs.values + ) + transport.electron_densities_integ = ( self.original_plasma.electron_densities.values ) @@ -472,20 +560,25 @@ def make_source_function(self): def interpolate_integrator_quantities( self, att_S_ul, Jredlu, Jbluelu, e_dot_u ): - runner = self.runner + transport = self.transport + mct_state = transport.transport_state plasma = self.original_plasma nshells = self.interpolate_shells - r_middle = (runner.r_inner_cgs + runner.r_outer_cgs) / 2.0 + r_middle = ( + mct_state.geometry_state.r_inner + mct_state.geometry_state.r_outer + ) / 2.0 r_integ = np.linspace( - runner.r_inner_cgs[0], runner.r_outer_cgs[-1], nshells + mct_state.geometry_state.r_inner[0], + mct_state.geometry_state.r_outer[-1], + nshells, ) - runner.r_inner_i = r_integ[:-1] - runner.r_outer_i = r_integ[1:] + transport.r_inner_i = r_integ[:-1] + transport.r_outer_i = r_integ[1:] r_middle_integ = (r_integ[:-1] + r_integ[1:]) / 2.0 - runner.electron_densities_integ = interp1d( + transport.electron_densities_integ = interp1d( r_middle, plasma.electron_densities, fill_value="extrapolate", @@ -493,7 +586,7 @@ def interpolate_integrator_quantities( )(r_middle_integ) # Assume tau_sobolevs to be constant within a shell # (as in the MC simulation) - runner.tau_sobolevs_integ = interp1d( + transport.tau_sobolevs_integ = interp1d( r_middle, plasma.tau_sobolevs, fill_value="extrapolate", @@ -531,22 +624,40 @@ def formal_integral(self, nu, N): Jblue_lu = res[2].flatten(order="F") self.generate_numba_objects() - L = self.numba_integrator.formal_integral( - self.model.t_inner, + L, I_nu_p = self.integrator.formal_integral( + self.simulation_state.t_inner, nu, nu.shape[0], att_S_ul, Jred_lu, Jblue_lu, - self.runner.tau_sobolevs_integ, - self.runner.electron_densities_integ, + self.transport.tau_sobolevs_integ, + self.transport.electron_densities_integ, N, ) + R_max = self.transport.r_outer_i[-1] + ps = calculate_p_values(R_max, N)[None, :] + I_nu_p[:, 1:] /= ps[:, 1:] + self.transport.I_nu_p = I_nu_p + self.transport.p_rays = ps + + I_nu = self.transport.I_nu_p * ps + L_test = np.array( + [ + 8 * M_PI * M_PI * trapezoid_integration((I_nu)[i, :], R_max / N) + for i in range(nu.shape[0]) + ] + ) + error = np.max(np.abs((L_test - L) / L)) + assert ( + error < 1e-7 + ), f"Incorrect I_nu_p values, max relative difference:{error}" + return np.array(L, np.float64) @njit(**njit_dict_no_parallel) -def populate_z(model, p, oz, oshell_id): +def populate_z(geometry, time_explosion, p, oz, oshell_id): """Calculate p line intersections This function calculates the intersection points of the p-line with @@ -559,14 +670,13 @@ def populate_z(model, p, oz, oshell_id): :oshell_id: (int64) will be set with the corresponding shell_ids """ # abbreviations - r = model.r_outer - N = len(model.r_inner) # check - # print(N) - inv_t = 1 / model.time_explosion + r = geometry.r_outer + N = len(geometry.r_inner) # check + inv_t = 1 / time_explosion z = 0 offset = N - if p <= model.r_inner[0]: + if p <= geometry.r_inner[0]: # intersect the photosphere for i in range(N): oz[i] = 1 - calculate_z(r[i], p, inv_t) @@ -612,7 +722,7 @@ def calculate_z(r, p, inv_t): return 0 -class BoundsError(ValueError): +class BoundsError(IndexError): pass @@ -674,12 +784,24 @@ def trapezoid_integration(array, h): @njit(**njit_dict_no_parallel) -def intensity_black_body(nu, T): - """Get the black body intensity at frequency nu - and temperature T""" +def intensity_black_body(nu, temperature): + """ + Calculate the blackbody intensity. + + Parameters + ---------- + nu : float64 + frequency + temperature : float64 + Temperature + + Returns + ------- + float64 + """ if nu == 0: return np.nan # to avoid ZeroDivisionError - beta_rad = 1 / (KB_CGS * T) + beta_rad = 1 / (KB_CGS * temperature) coefficient = 2 * H_CGS * C_INV * C_INV return coefficient * nu * nu * nu / (np.exp(H_CGS * nu * beta_rad) - 1) diff --git a/tardis/transport/montecarlo/formal_integral_cuda.py b/tardis/transport/montecarlo/formal_integral_cuda.py new file mode 100644 index 00000000000..75455f19c5f --- /dev/null +++ b/tardis/transport/montecarlo/formal_integral_cuda.py @@ -0,0 +1,514 @@ +import sys +import numpy as np +from astropy import units as u +from numba import float64, int64, cuda +import math + +from tardis.transport.montecarlo.numba_config import SIGMA_THOMSON + +C_INV = 3.33564e-11 +M_PI = np.arccos(-1) +KB_CGS = 1.3806488e-16 +H_CGS = 6.62606957e-27 + + +@cuda.jit +def cuda_formal_integral( + r_inner, + r_outer, + time_explosion, + line_list_nu, + iT, + inu, + inu_size, + att_S_ul, + Jred_lu, + Jblue_lu, + tau_sobolev, + electron_density, + N, + L, + pp, + exp_tau, + I_nu, + z, + shell_id, +): + """ + The CUDA version of numba_formal_integral that can run + on a NVIDIA GPU. + + Parameters + ---------- + r_inner : array(float64, 1d, C) + self.geometry.r_inner + r_outer : array(float64, 1d, C) + self.geometry.r_outer + time_explosion: float64 + self.geometry.time_explosion + line_list_nu : array(float64, 1d, A) + self.plasma.line_list_nu + iT : np.float64 + inu : np.float64 + inu_size : int64 + att_S_ul : array(float64, 1d, C) + Jred_lu : array(float64, 1d, C) + Jblue_lu : array(float64, 1d, C) + tau_sobolev : array(float64, 2d, C) + electron_density : array(float64, 1d, C) + N : int64 + L : array(float64, 1d, C) + This is where the results will be stored + pp : array(float64, 1d, C) + exp_tau : array(float64, 1d, C) + I_nu array(floatt64, 2d, C) + z : array(float64, 2d, C) + shell_id : array(int64, 2d, C) + """ + + # todo: add all the original todos + + # global read-only values + size_line, size_shell = tau_sobolev.shape + size_tau = size_line * size_shell + R_ph = r_inner[0] # make sure these are cgs + R_max = r_outer[size_shell - 1] + + nu_idx = cuda.grid(1) + # Check to see if CUDA is out of bounds + if nu_idx >= inu_size: + return + + # These all have their own version for each thread to avoid race conditions + I_nu_thread = I_nu[nu_idx] + z_thread = z[nu_idx] + shell_id_thread = shell_id[nu_idx] + + offset = 0 + size_z = 0 + idx_nu_start = 0 + direction = 0 + first = 0 + i = 0 + p = 0.0 + nu_start = 0.0 + nu_end = 0.0 + nu = 0.0 + zstart = 0.0 + zend = 0.0 + escat_contrib = 0.0 + escat_op = 0.0 + Jkkp = 0.0 + pexp_tau = 0 + patt_S_ul = 0 + pJred_lu = 0 + pJblue_lu = 0 + pline = 0 + + nu = inu[nu_idx] + + # now loop over discrete values along line + for p_idx in range(1, N): + escat_contrib = 0.0 + p = pp[p_idx] + + # initialize z intersections for p values + size_z = populate_z_cuda( + r_inner, r_outer, time_explosion, p, z_thread, shell_id_thread + ) + if p <= R_ph: + I_nu_thread[p_idx] = intensity_black_body_cuda(nu * z_thread[0], iT) + else: + I_nu_thread[p_idx] = 0 + nu_start = nu * z_thread[0] + nu_end = nu * z_thread[1] + + idx_nu_start = line_search_cuda(line_list_nu, nu_start, size_line) + offset = shell_id_thread[0] * size_line + # start tracking accumulated e-scattering optical depth + zstart = time_explosion / C_INV * (1.0 - z_thread[0]) + # Initialize "pointers" + pline = int(idx_nu_start) + pexp_tau = int(offset + idx_nu_start) + patt_S_ul = int(offset + idx_nu_start) + pJred_lu = int(offset + idx_nu_start) + pJblue_lu = int(offset + idx_nu_start) + + # flag for first contribution to integration on current p-ray + first = 1 + + # loop over all interactions + for i in range(size_z - 1): + escat_op = electron_density[int(shell_id_thread[i])] * SIGMA_THOMSON + nu_end = ( + nu * z_thread[i + 1] + ) # +1 is the offset as the original is from z[1:] + + nu_end_idx = line_search_cuda( + line_list_nu, nu_end, len(line_list_nu) + ) + + for _ in range(max(nu_end_idx - pline, 0)): + + # calculate e-scattering optical depth to next resonance point + zend = time_explosion / C_INV * (1.0 - line_list_nu[pline] / nu) + if first == 1: + # first contribution to integration + # NOTE: this treatment of I_nu_b (given + # by boundary conditions) is not in Lucy 1999; + # should be re-examined carefully + escat_contrib += ( + (zend - zstart) + * escat_op + * (Jblue_lu[pJblue_lu] - I_nu_thread[p_idx]) + ) + first = 0 + else: + # Account for e-scattering, c.f. Eqs 27, 28 in Lucy 1999 + Jkkp = 0.5 * (Jred_lu[pJred_lu] + Jblue_lu[pJblue_lu]) + escat_contrib += ( + (zend - zstart) * escat_op * (Jkkp - I_nu_thread[p_idx]) + ) + # this introduces the necessary offset of one element between + # pJblue_lu and pJred_lu + pJred_lu += 1 + I_nu_thread[p_idx] += escat_contrib + # // Lucy 1999, Eq 26 + I_nu_thread[p_idx] *= exp_tau[pexp_tau] + I_nu_thread[p_idx] += att_S_ul[patt_S_ul] + + # // reset e-scattering opacity + escat_contrib = 0.0 + zstart = zend + + pline += 1 + pexp_tau += 1 + patt_S_ul += 1 + pJblue_lu += 1 + + # calculate e-scattering optical depth to grid cell boundary + + Jkkp = 0.5 * (Jred_lu[pJred_lu] + Jblue_lu[pJblue_lu]) + zend = time_explosion / C_INV * (1.0 - nu_end / nu) + escat_contrib += ( + (zend - zstart) * escat_op * (Jkkp - I_nu_thread[p_idx]) + ) + zstart = zend + + # advance pointers + direction = int( + (shell_id_thread[i + 1] - shell_id_thread[i]) * size_line + ) + pexp_tau += direction + patt_S_ul += direction + pJred_lu += direction + pJblue_lu += direction + + I_nu_thread[p_idx] *= p + L[nu_idx] = ( + 8 * M_PI * M_PI * trapezoid_integration_cuda(I_nu_thread, R_max / N) + ) + + +class CudaFormalIntegrator(object): + """ + Helper class for performing the formal integral + with CUDA. + """ + + def __init__(self, geometry, time_explosion, plasma, points=1000): + self.geometry = geometry + self.time_explosion = time_explosion + self.plasma = plasma + self.points = points + + def formal_integral( + self, + iT, + inu, + inu_size, + att_S_ul, + Jred_lu, + Jblue_lu, + tau_sobolev, + electron_density, + N, + ): + """ + Simple wrapper for the CUDA implementation of the formal integral + """ + L = np.zeros(inu_size, dtype=np.float64) # array(float64, 1d, C) + # global read-only values + size_line, size_shell = tau_sobolev.shape # int64, int64 + size_tau = size_line * size_shell # int64 + + pp = np.zeros(N, dtype=np.float64) # array(float64, 1d, C) + exp_tau = np.zeros(size_tau, dtype=np.float64) # array(float64, 1d, C) + exp_tau = np.exp(-tau_sobolev.T.ravel()) # array(float64, 1d, C) + pp[::] = calculate_p_values( + self.geometry.r_outer[size_shell - 1], N + ) # array(float64, 1d, C) + + I_nu = np.zeros( + (inu_size, N), dtype=np.float64 + ) # array(float64, 1d, C) + z = np.zeros( + (inu_size, 2 * size_shell), dtype=np.float64 + ) # array(float64, 1d, C) + shell_id = np.zeros( + (inu_size, 2 * size_shell), dtype=np.int64 + ) # array(int64, 1d, C) + THREADS_PER_BLOCK = 32 + blocks_per_grid = (inu_size // THREADS_PER_BLOCK) + 1 + + cuda_formal_integral[blocks_per_grid, THREADS_PER_BLOCK]( + self.geometry.r_inner, + self.geometry.r_outer, + self.time_explosion, + self.plasma.line_list_nu, + iT.value, + inu.value, + inu_size, + att_S_ul, + Jred_lu, + Jblue_lu, + tau_sobolev, + electron_density, + N, + L, + pp, + exp_tau, + I_nu, + z, + shell_id, + ) + + return L, I_nu + + +@cuda.jit(device=True) +def populate_z_cuda(r_inner, r_outer, time_explosion, p, oz, oshell_id): + """ + Calculate p line intersections + + This function calculates the intersection points of the p-line with + each shell + + Parameters + ---------- + r_inner : array(float64, 1d, C) + r_outer : array(float64, 1d, C) + p : float64 + distance of the integration line to the center + oz : array(float64, 1d, C) + will be set with z values. the array is truncated + by the value `1`. + oshell_id : array(int64, 1d, C) + will be set with the corresponding shell_ids + + Returns + ------- + int64 + """ + N = len(r_inner) + inv_t = 1 / time_explosion + z = 0 + offset = N + + if p <= r_inner[0]: + # intersect the photosphere + for i in range(N): + oz[i] = 1 - calculate_z_cuda(r_outer[i], p, inv_t) + oshell_id[i] = i + return N + else: + # no intersection with photosphere + # that means we intersect each shell twice + for i in range(N): + z = calculate_z_cuda(r_outer[i], p, inv_t) + if z == 0: + continue + if offset == N: + offset = i + # calculate the index in the resulting array + i_low = N - i - 1 # the far intersection with the shell + i_up = N + i - 2 * offset # the nearer intersection with the shell + + # setting the arrays + oz[i_low] = 1 + z + oshell_id[i_low] = i + oz[i_up] = 1 - z + oshell_id[i_up] = i + return 2 * (N - offset) + + +@cuda.jit(device=True) +def calculate_z_cuda(r, p, inv_t): + """ + Calculate distance to p line + + Calculate half of the length of the p-line inside a shell + of radius r in terms of unit length (c * t_exp). + If shell and p-line do not intersect, return 0. + + Parameters + ---------- + r : float64 + radius of the shell + p : float64 + distance of the p-line to the center of the supernova + inv_t : float64 + inverse time_explosio is needed to norm to unit-length + + Returns + ------- + float64 + """ + if r > p: + return math.sqrt(r * r - p * p) * C_INV * inv_t + else: + return 0.0 + + +class BoundsError(IndexError): + """ + Used to check bounds in reverse + binary search + """ + + pass + + +@cuda.jit(device=True) +def line_search_cuda(nu, nu_insert, number_of_lines): + """ + Insert a value in to an array of line frequencies + + Parameters + ---------- + nu : (array) line frequencies + nu_insert : (int) value of nu key + number_of_lines : (int) number of lines in the line list + + Returns + ------- + int + index of the next line to the red. + If the key value is redder than + the reddest line returns number_of_lines. + """ + imin = 0 + imax = number_of_lines - 1 + if nu_insert > nu[imin]: + result = imin + elif nu_insert < nu[imax]: + result = imax + 1 + else: + result = reverse_binary_search_cuda(nu, nu_insert, imin, imax) + result = result + 1 + return result + + +# Credit for this computation is https://github.com/numba/numba/blob/3fd158f79a12ac5276bc5a72c2404464487c91f0/numba/np/arraymath.py#L3542 +@cuda.jit(device=True) +def reverse_binary_search_cuda(x, x_insert, imin, imax): + """ + Find indicies where elements should be inserted + to maintain order in an inversely sorted float + array. + + Find the indices into a sorted array a such that, + if the corresponding elements in v were inserted + before the indices on the right, the order of a + would be preserved. + + Parameters + ---------- + x : np.ndarray(np.float64, 1d, C) + x_insert : float64 + imin : int + Lower bound + imax : int + Upper bound + + Returns + ------- + np.int64 + Location of insertion + """ + if (x_insert > x[imin]) or (x_insert < x[imax]): + raise BoundsError # check + arr = x[::-1] + n = len(arr) + lo = 0 + hi = n + while hi > lo: + mid = (lo + hi) >> 1 + if arr[mid] <= x_insert: + # mid is too low of an index, go higher + lo = mid + 1 + else: + # mid is too high of an index, go down some + hi = mid + + return len(x) - 1 - lo + + +@cuda.jit(device=True) +def trapezoid_integration_cuda(arr, dx): + """ + Computes the approximation of the + trapezoidal integration of the array. + + Parameters + ---------- + arr : (array(float64, 1d, C) + dx : np.float64 + """ + + result = arr[0] + arr[-1] + + for x in range(1, len(arr) - 1): + result += arr[x] * 2.0 + + return result * (dx / 2.0) + + +@cuda.jit(device=True) +def intensity_black_body_cuda(nu, temperature): + """ + Calculate the blackbody intensity. + + Parameters + ---------- + nu : float64 + frequency + temperature : float64 + Temperature + + Returns + ------- + float64 + """ + if nu == 0: + return np.nan # to avoid ZeroDivisionError + beta_rad = 1 / (KB_CGS * temperature) + coefficient = 2 * H_CGS * C_INV * C_INV + return coefficient * nu * nu * nu / (math.exp(H_CGS * nu * beta_rad) - 1) + + +def calculate_p_values(R_max, N): + """ + Calculates the p values of N + + Parameters + ---------- + R_max : float64 + N : int64 + + Returns + ------- + float64 + """ + + return np.arange(N).astype(np.float64) * R_max / (N - 1) diff --git a/tardis/transport/montecarlo/interaction.py b/tardis/transport/montecarlo/interaction.py new file mode 100644 index 00000000000..044fbcd11a8 --- /dev/null +++ b/tardis/transport/montecarlo/interaction.py @@ -0,0 +1,514 @@ +import numpy as np +from numba import njit + +from tardis import constants as const +from tardis.transport.montecarlo import njit_dict_no_parallel +from tardis.transport.montecarlo.macro_atom import ( + MacroAtomTransitionType, + macro_atom, +) +from tardis.transport.montecarlo.numba_interface import ( + LineInteractionType, +) +from tardis.transport.montecarlo.r_packet import ( + PacketStatus, +) +from tardis.transport.montecarlo.utils import get_random_mu +from tardis.transport.frame_transformations import ( + angle_aberration_CMF_to_LF, + get_doppler_factor, + get_inverse_doppler_factor, +) + +K_B = const.k_B.cgs.value +H = const.h.cgs.value + + +@njit(**njit_dict_no_parallel) +def determine_bf_macro_activation_idx( + opacity_state, nu, chi_bf_contributions, active_continua +): + """ + Determine the macro atom activation level after bound-free absorption. + + Parameters + ---------- + nu : float + Comoving frequency of the r-packet. + chi_bf_contributions : numpy.ndarray, dtype float + Cumulative distribution of bound-free opacities at frequency + `nu`. + active_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + + Returns + ------- + float + Macro atom activation idx. + """ + # Perform a MC experiment to determine the continuum for absorption + index = np.searchsorted(chi_bf_contributions, np.random.random()) + continuum_id = active_continua[index] + + # Perform a MC experiment to determine whether thermal or + # ionization energy is created + nu_threshold = opacity_state.photo_ion_nu_threshold_mins[continuum_id] + fraction_ionization = nu_threshold / nu + if ( + np.random.random() < fraction_ionization + ): # Create ionization energy (i-packet) + destination_level_idx = opacity_state.photo_ion_activation_idx[ + continuum_id + ] + else: # Create thermal energy (k-packet) + destination_level_idx = opacity_state.k_packet_idx + return destination_level_idx + + +@njit(**njit_dict_no_parallel) +def determine_continuum_macro_activation_idx( + opacity_state, nu, chi_bf, chi_ff, chi_bf_contributions, active_continua +): + """ + Determine the macro atom activation level after a continuum absorption. + + Parameters + ---------- + nu : float + Comoving frequency of the r-packet. + chi_bf : numpy.ndarray, dtype float + Bound-free opacity. + chi_bf : numpy.ndarray, dtype float + Free-free opacity. + chi_bf_contributions : numpy.ndarray, dtype float + Cumulative distribution of bound-free opacities at frequency + `nu`. + active_continua : numpy.ndarray, dtype int + Continuum ids for which absorption is possible for frequency `nu`. + + Returns + ------- + float + Macro atom activation idx. + """ + fraction_bf = chi_bf / (chi_bf + chi_ff) + # TODO: In principle, we can also decide here whether a Thomson + # scattering event happens and need one less RNG call. + if np.random.random() < fraction_bf: # Bound-free absorption + destination_level_idx = determine_bf_macro_activation_idx( + opacity_state, nu, chi_bf_contributions, active_continua + ) + else: # Free-free absorption (i.e. k-packet creation) + destination_level_idx = opacity_state.k_packet_idx + return destination_level_idx + + +@njit(**njit_dict_no_parallel) +def sample_nu_free_free(opacity_state, shell): + """ + Attributes + ---------- + nu_ff_sampler : float + Frequency of the free-free emission process + + """ + temperature = opacity_state.t_electrons[shell] + zrand = np.random.random() + return -K_B * temperature / H * np.log(zrand) + + +@njit(**njit_dict_no_parallel) +def sample_nu_free_bound(opacity_state, shell, continuum_id): + """ + Attributes + ---------- + nu_fb_sampler : float + Frequency of the free-bounds emission process + """ + start = opacity_state.photo_ion_block_references[continuum_id] + end = opacity_state.photo_ion_block_references[continuum_id + 1] + phot_nus_block = opacity_state.phot_nus[start:end] + em = opacity_state.emissivities[start:end, shell] + + zrand = np.random.random() + idx = np.searchsorted(em, zrand, side="right") + + return phot_nus_block[idx] - (em[idx] - zrand) / (em[idx] - em[idx - 1]) * ( + phot_nus_block[idx] - phot_nus_block[idx - 1] + ) + + +@njit(**njit_dict_no_parallel) +def continuum_event( + r_packet, + time_explosion, + opacity_state, + chi_bf_tot, + chi_ff, + chi_bf_contributions, + current_continua, + continuum_processes_enabled, + enable_full_relativity, +): + """ + continuum event handler - activate the macroatom and run the handler + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + continuum : tardis.transport.montecarlo.numba_interface.Continuum + """ + old_doppler_factor = get_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + + r_packet.mu = get_random_mu() + inverse_doppler_factor = get_inverse_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + comov_energy = r_packet.energy * old_doppler_factor + comov_nu = ( + r_packet.nu * old_doppler_factor + ) # make sure frequency should be updated + r_packet.energy = comov_energy * inverse_doppler_factor + r_packet.nu = comov_nu * inverse_doppler_factor + + destination_level_idx = determine_continuum_macro_activation_idx( + opacity_state, + comov_nu, + chi_bf_tot, + chi_ff, + chi_bf_contributions, + current_continua, + ) + + macro_atom_event( + destination_level_idx, + r_packet, + time_explosion, + opacity_state, + continuum_processes_enabled, + enable_full_relativity, + ) + + +@njit(**njit_dict_no_parallel) +def macro_atom_event( + destination_level_idx, + r_packet, + time_explosion, + opacity_state, + continuum_processes_enabled, + enable_full_relativity, +): + """ + Macroatom event handler - run the macroatom and handle the result + + Parameters + ---------- + destination_level_idx : int + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + """ + transition_id, transition_type = macro_atom( + destination_level_idx, r_packet.current_shell_id, opacity_state + ) + + if ( + continuum_processes_enabled + and transition_type == MacroAtomTransitionType.FF_EMISSION + ): + free_free_emission( + r_packet, time_explosion, opacity_state, enable_full_relativity + ) + + elif ( + continuum_processes_enabled + and transition_type == MacroAtomTransitionType.BF_EMISSION + ): + bound_free_emission( + r_packet, + time_explosion, + opacity_state, + transition_id, + enable_full_relativity, + ) + elif ( + continuum_processes_enabled + and transition_type == MacroAtomTransitionType.BF_COOLING + ): + bf_cooling( + r_packet, time_explosion, opacity_state, enable_full_relativity + ) + + elif ( + continuum_processes_enabled + and transition_type == MacroAtomTransitionType.ADIABATIC_COOLING + ): + adiabatic_cooling(r_packet) + + elif transition_type == MacroAtomTransitionType.BB_EMISSION: + line_emission( + r_packet, + transition_id, + time_explosion, + opacity_state, + enable_full_relativity, + ) + else: + raise Exception("No Interaction Found!") + + +@njit(**njit_dict_no_parallel) +def bf_cooling(r_packet, time_explosion, opacity_state, enable_full_relativity): + """ + Bound-Free Cooling - Determine and run bf emission from cooling + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + """ + fb_cooling_prob = opacity_state.p_fb_deactivation[ + :, r_packet.current_shell_id + ] + p = fb_cooling_prob[0] + i = 0 + zrand = np.random.random() + while p <= zrand: # Can't search-sorted this because it's not cumulative + i += 1 + p += fb_cooling_prob[i] + continuum_idx = i + bound_free_emission( + r_packet, + time_explosion, + opacity_state, + continuum_idx, + enable_full_relativity, + ) + + +@njit(**njit_dict_no_parallel) +def adiabatic_cooling(r_packet): + """ + Adiabatic cooling - equivalent to destruction of the packet + + Parameters + ---------- + r_packet: tardis.transport.montecarlo.r_packet.RPacket + """ + r_packet.status = PacketStatus.ADIABATIC_COOLING + + +@njit(**njit_dict_no_parallel) +def get_current_line_id(nu, line_list): + """ + Get the line id corresponding to a frequency nu in a line list + + Parameters + ---------- + nu : float + line_list : np.ndarray + """ + # Note: Since this reverses the array, + # it may be faster to just write our own reverse-binary-search + + reverse_line_list = line_list[::-1] + number_of_lines = len(line_list) + line_id = number_of_lines - np.searchsorted(reverse_line_list, nu) + return line_id + + +@njit(**njit_dict_no_parallel) +def free_free_emission( + r_packet, time_explosion, opacity_state, enable_full_relativity +): + """ + Free-Free emission - set the frequency from electron-ion interaction + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + """ + inverse_doppler_factor = get_inverse_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + comov_nu = sample_nu_free_free(opacity_state, r_packet.current_shell_id) + r_packet.nu = comov_nu * inverse_doppler_factor + current_line_id = get_current_line_id(comov_nu, opacity_state.line_list_nu) + r_packet.next_line_id = current_line_id + + if enable_full_relativity: + r_packet.mu = angle_aberration_CMF_to_LF( + r_packet, time_explosion, r_packet.mu + ) + + +@njit(**njit_dict_no_parallel) +def bound_free_emission( + r_packet, + time_explosion, + opacity_state, + continuum_id, + enable_full_relativity, +): + """ + Bound-Free emission - set the frequency from photo-ionization + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + continuum_id : int + """ + inverse_doppler_factor = get_inverse_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + + comov_nu = sample_nu_free_bound( + opacity_state, r_packet.current_shell_id, continuum_id + ) + r_packet.nu = comov_nu * inverse_doppler_factor + current_line_id = get_current_line_id(comov_nu, opacity_state.line_list_nu) + r_packet.next_line_id = current_line_id + + if enable_full_relativity: + r_packet.mu = angle_aberration_CMF_to_LF( + r_packet, time_explosion, r_packet.mu + ) + + +@njit(**njit_dict_no_parallel) +def thomson_scatter(r_packet, time_explosion, enable_full_relativity): + """ + Thomson scattering — no longer line scattering + \n1) get the doppler factor at that position with the old angle + \n2) convert the current energy and nu into the comoving frame with the old mu + \n3) Scatter and draw new mu - update mu + \n4) Transform the comoving energy and nu back using the new mu + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + time since explosion in seconds + """ + old_doppler_factor = get_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + comov_nu = r_packet.nu * old_doppler_factor + comov_energy = r_packet.energy * old_doppler_factor + r_packet.mu = get_random_mu() + inverse_new_doppler_factor = get_inverse_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + + r_packet.nu = comov_nu * inverse_new_doppler_factor + r_packet.energy = comov_energy * inverse_new_doppler_factor + if enable_full_relativity: + r_packet.mu = angle_aberration_CMF_to_LF( + r_packet, time_explosion, r_packet.mu + ) + temp_doppler_factor = get_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + + +@njit(**njit_dict_no_parallel) +def line_scatter( + r_packet, + time_explosion, + line_interaction_type, + opacity_state, + continuum_processes_enabled, + enable_full_relativity, +): + """ + Line scatter function that handles the scattering itself, including new angle drawn, and calculating nu out using macro atom + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + line_interaction_type : enum + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + """ + old_doppler_factor = get_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + r_packet.mu = get_random_mu() + + inverse_new_doppler_factor = get_inverse_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + + comov_energy = r_packet.energy * old_doppler_factor + r_packet.energy = comov_energy * inverse_new_doppler_factor + + if line_interaction_type == LineInteractionType.SCATTER: + line_emission( + r_packet, + r_packet.next_line_id, + time_explosion, + opacity_state, + enable_full_relativity, + ) + else: # includes both macro atom and downbranch - encoded in the transition probabilities + comov_nu = r_packet.nu * old_doppler_factor # Is this necessary? + r_packet.nu = comov_nu * inverse_new_doppler_factor + activation_level_id = opacity_state.line2macro_level_upper[ + r_packet.next_line_id + ] + macro_atom_event( + activation_level_id, + r_packet, + time_explosion, + opacity_state, + continuum_processes_enabled, + enable_full_relativity, + ) + + +@njit(**njit_dict_no_parallel) +def line_emission( + r_packet, + emission_line_id, + time_explosion, + opacity_state, + enable_full_relativity, +): + """ + Sets the frequency of the RPacket properly given the emission channel + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + emission_line_id : int + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + """ + r_packet.last_line_interaction_out_id = emission_line_id + r_packet.last_line_interaction_shell_id = r_packet.current_shell_id + + if emission_line_id != r_packet.next_line_id: + pass + inverse_doppler_factor = get_inverse_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + r_packet.nu = ( + opacity_state.line_list_nu[emission_line_id] * inverse_doppler_factor + ) + r_packet.next_line_id = emission_line_id + 1 + nu_line = opacity_state.line_list_nu[emission_line_id] + + if enable_full_relativity: + r_packet.mu = angle_aberration_CMF_to_LF( + r_packet, time_explosion, r_packet.mu + ) diff --git a/tardis/montecarlo/montecarlo_numba/macro_atom.py b/tardis/transport/montecarlo/macro_atom.py similarity index 52% rename from tardis/montecarlo/montecarlo_numba/macro_atom.py rename to tardis/transport/montecarlo/macro_atom.py index 2caf91af6aa..c1864486bd8 100644 --- a/tardis/montecarlo/montecarlo_numba/macro_atom.py +++ b/tardis/transport/montecarlo/macro_atom.py @@ -2,7 +2,7 @@ from enum import IntEnum from numba import njit -from tardis.montecarlo.montecarlo_numba import njit_dict, njit_dict_no_parallel +from tardis.transport.montecarlo import njit_dict, njit_dict_no_parallel class MacroAtomError(ValueError): @@ -16,45 +16,47 @@ class MacroAtomTransitionType(IntEnum): BF_EMISSION = -2 FF_EMISSION = -3 ADIABATIC_COOLING = -4 + BF_COOLING = -5 # TODO: Maybe merge this with BF_EMISSION + TWO_PHOTON = -6 @njit(**njit_dict_no_parallel) -def macro_atom(r_packet, numba_plasma): +def macro_atom(activation_level_id, current_shell_id, opacity_state): """ Parameters ---------- - r_packet : tardis.montecarlo.montecarlo_numba.r_packet.RPacket - numba_plasma : tardis.montecarlo.numba_interface.numba_plasma.NumbaPlasma + activation_level_id : int + Activation level idx of the macro atom. + current_shell_id : int + opacity_state : tardis.transport.montecarlo.numba_interface.opacity_state.OpacityState Returns ------- """ - activation_level_id = numba_plasma.line2macro_level_upper[ - r_packet.next_line_id - ] current_transition_type = 0 - while current_transition_type >= 0: probability = 0.0 probability_event = np.random.random() - block_start = numba_plasma.macro_block_references[activation_level_id] - block_end = numba_plasma.macro_block_references[activation_level_id + 1] + block_start = opacity_state.macro_block_references[activation_level_id] + block_end = opacity_state.macro_block_references[ + activation_level_id + 1 + ] # looping through the transition probabilities for transition_id in range(block_start, block_end): - transition_probability = numba_plasma.transition_probabilities[ - transition_id, r_packet.current_shell_id + transition_probability = opacity_state.transition_probabilities[ + transition_id, current_shell_id ] probability += transition_probability if probability > probability_event: - activation_level_id = numba_plasma.destination_level_id[ + activation_level_id = opacity_state.destination_level_id[ transition_id ] - current_transition_type = numba_plasma.transition_type[ + current_transition_type = opacity_state.transition_type[ transition_id ] break @@ -66,7 +68,8 @@ def macro_atom(r_packet, numba_plasma): "the probability_event should be less than 1" ) - if current_transition_type == MacroAtomTransitionType.BB_EMISSION: - return numba_plasma.transition_line_id[transition_id] - else: - raise MacroAtomError("MacroAtom currently only allows BB transitions") + # current_transition_type = MacroAtomTransitionType(current_transition_type) + return ( + opacity_state.transition_line_id[transition_id], + current_transition_type, + ) diff --git a/tardis/transport/montecarlo/montecarlo_configuration.py b/tardis/transport/montecarlo/montecarlo_configuration.py new file mode 100644 index 00000000000..27ad015fd8b --- /dev/null +++ b/tardis/transport/montecarlo/montecarlo_configuration.py @@ -0,0 +1,84 @@ +from astropy import units as u +from numba import float64, int64, boolean +from numba.experimental import jitclass +import numpy as np + +from tardis.transport.montecarlo.numba_interface import ( + LineInteractionType, +) + +numba_config_spec = [ + ("ENABLE_FULL_RELATIVITY", boolean), + ("TEMPORARY_V_PACKET_BINS", int64), + ("NUMBER_OF_VPACKETS", int64), + ("MONTECARLO_SEED", int64), + ("LINE_INTERACTION_TYPE", int64), + ("PACKET_SEEDS", int64[:]), + ("DISABLE_ELECTRON_SCATTERING", boolean), + ("DISABLE_LINE_SCATTERING", boolean), + ("SURVIVAL_PROBABILITY", float64), + ("VPACKET_TAU_RUSSIAN", float64), + ("INITIAL_TRACKING_ARRAY_LENGTH", int64), + ("LEGACY_MODE_ENABLED", boolean), + ("ENABLE_RPACKET_TRACKING", boolean), + ("CONTINUUM_PROCESSES_ENABLED", boolean), + ("VPACKET_SPAWN_START_FREQUENCY", float64), + ("VPACKET_SPAWN_END_FREQUENCY", float64), + ("ENABLE_VPACKET_TRACKING", boolean), +] + + +@jitclass(numba_config_spec) +class MonteCarloConfiguration(object): + def __init__(self): + self.ENABLE_FULL_RELATIVITY = False + self.TEMPORARY_V_PACKET_BINS = 0 + self.NUMBER_OF_VPACKETS = 0 + self.MONTECARLO_SEED = 0 + self.LINE_INTERACTION_TYPE = 0 + self.PACKET_SEEDS = np.empty(1, dtype=np.int64) + self.DISABLE_ELECTRON_SCATTERING = False + self.DISABLE_LINE_SCATTERING = False + self.SURVIVAL_PROBABILITY = 0.0 + self.VPACKET_TAU_RUSSIAN = 10.0 + + self.INITIAL_TRACKING_ARRAY_LENGTH = 0 + self.LEGACY_MODE_ENABLED = False + + self.ENABLE_RPACKET_TRACKING = False + self.CONTINUUM_PROCESSES_ENABLED = False + + self.VPACKET_SPAWN_START_FREQUENCY = 0 + self.VPACKET_SPAWN_END_FREQUENCY = 1e200 + self.ENABLE_VPACKET_TRACKING = False + + +def configuration_initialize(config, transport, number_of_vpackets): + if transport.line_interaction_type == "macroatom": + config.LINE_INTERACTION_TYPE = LineInteractionType.MACROATOM + elif transport.line_interaction_type == "downbranch": + config.LINE_INTERACTION_TYPE = LineInteractionType.DOWNBRANCH + elif transport.line_interaction_type == "scatter": + config.LINE_INTERACTION_TYPE = LineInteractionType.SCATTER + else: + raise ValueError( + f'Line interaction type must be one of "macroatom",' + f'"downbranch", or "scatter" but is ' + f"{transport.line_interaction_type}" + ) + config.NUMBER_OF_VPACKETS = number_of_vpackets + config.TEMPORARY_V_PACKET_BINS = number_of_vpackets + config.ENABLE_FULL_RELATIVITY = transport.enable_full_relativity + config.MONTECARLO_SEED = transport.packet_source.base_seed + config.VPACKET_SPAWN_START_FREQUENCY = ( + transport.virtual_spectrum_spawn_range.end.to( + u.Hz, equivalencies=u.spectral() + ).value + ) + config.VPACKET_SPAWN_END_FREQUENCY = ( + transport.virtual_spectrum_spawn_range.start.to( + u.Hz, equivalencies=u.spectral() + ).value + ) + config.ENABLE_VPACKET_TRACKING = transport.enable_vpacket_tracking + config.ENABLE_RPACKET_TRACKING = transport.enable_rpacket_tracking diff --git a/tardis/transport/montecarlo/montecarlo_main_loop.py b/tardis/transport/montecarlo/montecarlo_main_loop.py new file mode 100644 index 00000000000..d20c21eacef --- /dev/null +++ b/tardis/transport/montecarlo/montecarlo_main_loop.py @@ -0,0 +1,197 @@ +import numpy as np +from numba import njit, objmode, prange +from numba.np.ufunc.parallel import get_num_threads, get_thread_id +from numba.typed import List + +from tardis.transport.montecarlo import njit_dict +from tardis.transport.montecarlo.packet_trackers import RPacketTracker +from tardis.transport.montecarlo.packet_collections import ( + VPacketCollection, + consolidate_vpacket_tracker, + initialize_last_interaction_tracker, +) +from tardis.transport.montecarlo.r_packet import ( + PacketStatus, + RPacket, +) +from tardis.transport.montecarlo.single_packet_loop import ( + single_packet_loop, +) +from tardis.util.base import update_packet_pbar + + +@njit(**njit_dict) +def montecarlo_main_loop( + packet_collection, + geometry_state, + time_explosion, + opacity_state, + montecarlo_configuration, + estimators, + spectrum_frequency, + number_of_vpackets, + iteration, + show_progress_bars, + total_iterations, +): + """This is the main loop of the MonteCarlo routine that generates packets + and sends them through the ejecta. + + + Parameters + ---------- + packet_collection : PacketCollection + Real packet collection + geometry_state : GeometryState + Simulation geometry + time_explosion : float + Time in seconds + opacity_state : OpacityState + estimators : Estimators + spectrum_frequency : astropy.units.Quantity + Frequency bins + number_of_vpackets : int + VPackets released per interaction + iteration : int + Current iteration number + show_progress_bars : bool + Display progress bars + total_iterations : int + Maximum number of iterations + """ + no_of_packets = len(packet_collection.initial_nus) + + last_interaction_tracker = initialize_last_interaction_tracker( + no_of_packets + ) + + v_packets_energy_hist = np.zeros_like(spectrum_frequency) + delta_nu = spectrum_frequency[1] - spectrum_frequency[0] + + # Pre-allocate a list of vpacket collections for later storage + vpacket_collections = List() + # Configuring the Tracking for R_Packets + rpacket_trackers = List() + for i in range(no_of_packets): + vpacket_collections.append( + VPacketCollection( + i, + spectrum_frequency, + montecarlo_configuration.VPACKET_SPAWN_START_FREQUENCY, + montecarlo_configuration.VPACKET_SPAWN_END_FREQUENCY, + number_of_vpackets, + montecarlo_configuration.TEMPORARY_V_PACKET_BINS, + ) + ) + rpacket_trackers.append( + RPacketTracker( + montecarlo_configuration.INITIAL_TRACKING_ARRAY_LENGTH + ) + ) + + # Get the ID of the main thread and the number of threads + main_thread_id = get_thread_id() + n_threads = get_num_threads() + + # betting get thread_id goes from 0 to num threads + # Note that get_thread_id() returns values from 0 to n_threads-1, + # so we iterate from 0 to n_threads-1 to create the estimator_list + estimator_list = estimators.create_estimator_list(n_threads) + + for i in prange(no_of_packets): + thread_id = get_thread_id() + if show_progress_bars: + if thread_id == main_thread_id: + with objmode: + update_amount = 1 * n_threads + update_packet_pbar( + update_amount, + current_iteration=iteration, + no_of_packets=no_of_packets, + total_iterations=total_iterations, + ) + + r_packet = RPacket( + packet_collection.initial_radii[i], + packet_collection.initial_mus[i], + packet_collection.initial_nus[i], + packet_collection.initial_energies[i], + packet_collection.packet_seeds[i], + i, + ) + # Seed the random number generator + np.random.seed(r_packet.seed) + + # Get the local estimators for this thread + local_estimators = estimator_list[thread_id] + + # Get the local v_packet_collection for this thread + vpacket_collection = vpacket_collections[i] + + # RPacket Tracker for this thread + rpacket_tracker = rpacket_trackers[i] + + loop = single_packet_loop( + r_packet, + geometry_state, + time_explosion, + opacity_state, + local_estimators, + vpacket_collection, + rpacket_tracker, + montecarlo_configuration, + ) + packet_collection.output_nus[i] = r_packet.nu + + last_interaction_tracker.update_last_interaction(r_packet, i) + + if r_packet.status == PacketStatus.REABSORBED: + packet_collection.output_energies[i] = -r_packet.energy + last_interaction_tracker.types[i] = r_packet.last_interaction_type + elif r_packet.status == PacketStatus.EMITTED: + packet_collection.output_energies[i] = r_packet.energy + last_interaction_tracker.types[i] = r_packet.last_interaction_type + + vpacket_collection.finalize_arrays() + + v_packets_idx = np.floor( + (vpacket_collection.nus - spectrum_frequency[0]) / delta_nu + ).astype(np.int64) + + for j, idx in enumerate(v_packets_idx): + if (vpacket_collection.nus[j] < spectrum_frequency[0]) or ( + vpacket_collection.nus[j] > spectrum_frequency[-1] + ): + continue + v_packets_energy_hist[idx] += vpacket_collection.energies[j] + + for sub_estimator in estimator_list: + estimators.increment(sub_estimator) + + if montecarlo_configuration.ENABLE_VPACKET_TRACKING: + vpacket_tracker = consolidate_vpacket_tracker( + vpacket_collections, + spectrum_frequency, + montecarlo_configuration.VPACKET_SPAWN_START_FREQUENCY, + montecarlo_configuration.VPACKET_SPAWN_END_FREQUENCY, + ) + else: + vpacket_tracker = VPacketCollection( + -1, + spectrum_frequency, + montecarlo_configuration.VPACKET_SPAWN_START_FREQUENCY, + montecarlo_configuration.VPACKET_SPAWN_END_FREQUENCY, + -1, + 1, + ) + + if montecarlo_configuration.ENABLE_RPACKET_TRACKING: + for rpacket_tracker in rpacket_trackers: + rpacket_tracker.finalize_array() + + return ( + v_packets_energy_hist, + last_interaction_tracker, + vpacket_tracker, + rpacket_trackers, + ) diff --git a/tardis/transport/montecarlo/montecarlo_transport_state.py b/tardis/transport/montecarlo/montecarlo_transport_state.py new file mode 100644 index 00000000000..98fc5bf976c --- /dev/null +++ b/tardis/transport/montecarlo/montecarlo_transport_state.py @@ -0,0 +1,456 @@ +import warnings + +import numpy as np +from astropy import units as u + +from tardis.io.util import HDFWriterMixin +from tardis.transport.montecarlo.estimators.dilute_blackbody_properties import ( + MCDiluteBlackBodyRadFieldSolver, +) +from tardis.transport.montecarlo.formal_integral import IntegrationError +from tardis.spectrum import TARDISSpectrum + + +class MonteCarloTransportState(HDFWriterMixin): + hdf_properties = [ + "output_nu", + "output_energy", + "nu_bar_estimator", + "j_estimator", + "j_blue_estimator", + "montecarlo_virtual_luminosity", + "packet_luminosity", + "spectrum", + "spectrum_virtual", + "spectrum_reabsorbed", + "spectrum_integrated", + "time_of_simulation", + "emitted_packet_mask", + "last_interaction_type", + "last_interaction_in_nu", + "last_line_interaction_out_id", + "last_line_interaction_in_id", + "last_line_interaction_shell_id", + ] + + vpacket_hdf_properties = [ + "virt_packet_nus", + "virt_packet_energies", + "virt_packet_initial_rs", + "virt_packet_initial_mus", + "virt_packet_last_interaction_in_nu", + "virt_packet_last_interaction_type", + "virt_packet_last_line_interaction_in_id", + "virt_packet_last_line_interaction_out_id", + "virt_packet_last_line_interaction_shell_id", + ] + + hdf_name = "transport_state" + + last_interaction_type = None + last_interaction_in_nu = None + last_line_interaction_out_id = None + last_line_interaction_in_id = None + last_line_interaction_shell_id = None + + virt_logging = False + + def __init__( + self, + packet_collection, + radfield_mc_estimators, + spectrum_frequency, + geometry_state, + opacity_state, + rpacket_tracker=None, + vpacket_tracker=None, + ): + self.packet_collection = packet_collection + self.radfield_mc_estimators = radfield_mc_estimators + self.spectrum_frequency = spectrum_frequency + self._montecarlo_virtual_luminosity = u.Quantity( + np.zeros_like(self.spectrum_frequency.value), "erg / s" + ) + self._integrator = None + self.integrator_settings = None + self._spectrum_integrated = None + self.enable_full_relativity = False + self.enable_continuum_processes = False + self.geometry_state = geometry_state + self.opacity_state = opacity_state + self.rpacket_tracker = rpacket_tracker + self.vpacket_tracker = vpacket_tracker + + def calculate_radiationfield_properties(self): + """ + Calculate an updated radiation field from the :math: + `\\bar{nu}_\\textrm{estimator}` and :math:`\\J_\\textrm{estimator}` + calculated in the montecarlo simulation. + The details of the calculation can be found in the documentation. + + Parameters + ---------- + nubar_estimator : np.ndarray (float) + j_estimator : np.ndarray (float) + + Returns + ------- + t_radiative : astropy.units.Quantity (float) + dilution_factor : numpy.ndarray (float) + """ + dilute_bb_solver = MCDiluteBlackBodyRadFieldSolver() + dilute_bb_radfield = dilute_bb_solver.solve( + self.radfield_mc_estimators, + self.time_of_simulation, + self.geometry_state.volume, + ) + + return ( + dilute_bb_radfield.t_radiative, + dilute_bb_radfield.dilution_factor, + ) + + @property + def output_nu(self): + return self.packet_collection.output_nus * u.Hz + + @property + def output_energy(self): + return self.packet_collection.output_energies * u.erg + + @property + def nu_bar_estimator(self): + return self.radfield_mc_estimators.nu_bar_estimator + + @property + def j_estimator(self): + return self.radfield_mc_estimators.j_estimator + + @property + def j_blue_estimator(self): + return self.radfield_mc_estimators.j_blue_estimator + + @property + def time_of_simulation(self): + return self.packet_collection.time_of_simulation * u.s + + @property + def packet_luminosity(self): + return ( + self.packet_collection.output_energies + * u.erg + / (self.packet_collection.time_of_simulation * u.s) + ) + + @property + def emitted_packet_mask(self): + return self.packet_collection.output_energies >= 0 + + @property + def emitted_packet_nu(self): + return ( + self.packet_collection.output_nus[self.emitted_packet_mask] * u.Hz + ) + + @property + def reabsorbed_packet_nu(self): + return ( + self.packet_collection.output_nus[~self.emitted_packet_mask] * u.Hz + ) + + @property + def emitted_packet_luminosity(self): + return self.packet_luminosity[self.emitted_packet_mask] + + @property + def reabsorbed_packet_luminosity(self): + return -self.packet_luminosity[~self.emitted_packet_mask] + + @property + def montecarlo_reabsorbed_luminosity(self): + return u.Quantity( + np.histogram( + self.reabsorbed_packet_nu, + weights=self.reabsorbed_packet_luminosity, + bins=self.spectrum_frequency, + )[0], + "erg / s", + ) + + @property + def montecarlo_emitted_luminosity(self): + return u.Quantity( + np.histogram( + self.emitted_packet_nu, + weights=self.emitted_packet_luminosity, + bins=self.spectrum_frequency, + )[0], + "erg / s", + ) + + @property + def montecarlo_virtual_luminosity(self): + return ( + self._montecarlo_virtual_luminosity[:-1] + / self.packet_collection.time_of_simulation + ) + + @property + def spectrum(self): + return TARDISSpectrum( + self.spectrum_frequency, self.montecarlo_emitted_luminosity + ) + + @property + def spectrum_reabsorbed(self): + return TARDISSpectrum( + self.spectrum_frequency, self.montecarlo_reabsorbed_luminosity + ) + + @property + def spectrum_virtual(self): + if np.all(self.montecarlo_virtual_luminosity == 0): + warnings.warn( + "MontecarloTransport.spectrum_virtual" + "is zero. Please run the montecarlo simulation with" + "no_of_virtual_packets > 0", + UserWarning, + ) + + return TARDISSpectrum( + self.spectrum_frequency, self.montecarlo_virtual_luminosity + ) + + @property + def spectrum_integrated(self): + if self._spectrum_integrated is None: + # This was changed from unpacking to specific attributes as compute + # is not used in calculate_spectrum + try: + self._spectrum_integrated = self.integrator.calculate_spectrum( + self.spectrum_frequency[:-1], + points=self.integrator_settings.points, + interpolate_shells=self.integrator_settings.interpolate_shells, + ) + except IntegrationError: + # if integration is impossible or fails, return an empty spectrum + warnings.warn( + "The FormalIntegrator is not yet implemented for the full " + "relativity mode or continuum processes. " + "Please run with config option enable_full_relativity: " + "False and continuum_processes_enabled: False " + "This RETURNS AN EMPTY SPECTRUM!", + UserWarning, + ) + return TARDISSpectrum( + np.array([np.nan, np.nan]) * u.Hz, + np.array([np.nan]) * u.erg / u.s, + ) + return self._spectrum_integrated + + @property + def integrator(self): + if self._integrator is None: + warnings.warn( + "MontecarloTransport.integrator: " + "The FormalIntegrator is not yet available." + "Please run the montecarlo simulation at least once.", + UserWarning, + ) + if self.enable_full_relativity: + raise NotImplementedError( + "The FormalIntegrator is not yet implemented for the full " + "relativity mode. " + "Please run with config option enable_full_relativity: " + "False." + ) + return self._integrator + + def calculate_emitted_luminosity( + self, luminosity_nu_start, luminosity_nu_end + ): + """ + Calculate emitted luminosity. + + Parameters + ---------- + luminosity_nu_start : astropy.units.Quantity + luminosity_nu_end : astropy.units.Quantity + + Returns + ------- + astropy.units.Quantity + """ + luminosity_wavelength_filter = ( + self.emitted_packet_nu > luminosity_nu_start + ) & (self.emitted_packet_nu < luminosity_nu_end) + + return self.emitted_packet_luminosity[ + luminosity_wavelength_filter + ].sum() + + def calculate_reabsorbed_luminosity( + self, luminosity_nu_start, luminosity_nu_end + ): + """ + Calculate reabsorbed luminosity. + + Parameters + ---------- + luminosity_nu_start : astropy.units.Quantity + luminosity_nu_end : astropy.units.Quantity + + Returns + ------- + astropy.units.Quantity + """ + luminosity_wavelength_filter = ( + self.reabsorbed_packet_nu > luminosity_nu_start + ) & (self.reabsorbed_packet_nu < luminosity_nu_end) + + return self.reabsorbed_packet_luminosity[ + luminosity_wavelength_filter + ].sum() + + @property + def virt_packet_nus(self): + try: + return u.Quantity(self.vpacket_tracker.nus, u.Hz) + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_nus:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_energies(self): + try: + return u.Quantity(self.vpacket_tracker.energies, u.erg) + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_energies:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virtual_packet_luminosity(self): + try: + return ( + self.virt_packet_energies + / self.packet_collection.time_of_simulation + ) + except TypeError: + warnings.warn( + "MontecarloTransport.virtual_packet_luminosity:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_initial_rs(self): + try: + return u.Quantity(self.vpacket_tracker.initial_rs, u.erg) + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_initial_rs:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_initial_mus(self): + try: + return u.Quantity(self.vpacket_tracker.initial_mus, u.erg) + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_initial_mus:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_last_interaction_in_nu(self): + try: + return u.Quantity(self.vpacket_tracker.last_interaction_in_nu, u.Hz) + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_last_interaction_in_nu:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_last_interaction_type(self): + try: + return self.vpacket_tracker.last_interaction_type + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_last_interaction_type:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_last_line_interaction_in_id(self): + try: + return self.vpacket_tracker.last_interaction_in_id + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_last_line_interaction_in_id:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_last_line_interaction_out_id(self): + try: + return self.vpacket_tracker.last_interaction_out_id + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_last_line_interaction_out_id:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None + + @property + def virt_packet_last_line_interaction_shell_id(self): + try: + return self.vpacket_tracker.last_interaction_shell_id + except AttributeError: + warnings.warn( + "MontecarloTransport.virt_packet_last_line_interaction_shell_id:" + "Set 'virtual_packet_logging: True' in the configuration file" + "to access this property" + "It should be added under 'virtual' property of 'spectrum' property", + UserWarning, + ) + return None diff --git a/tardis/transport/montecarlo/nonhomologous_grid.py b/tardis/transport/montecarlo/nonhomologous_grid.py new file mode 100644 index 00000000000..05b681a91f7 --- /dev/null +++ b/tardis/transport/montecarlo/nonhomologous_grid.py @@ -0,0 +1,76 @@ +import numpy as np +from numba import njit + +from tardis.transport.montecarlo import ( + njit_dict_no_parallel, +) + + +@njit(**njit_dict_no_parallel) +def velocity_dvdr(r_packet, geometry): + """ + Velocity at radius r and dv/dr of current shell + + Parameters + ---------- + r_packet: RPacket + geometry: Geometry + + Returns + ----------- + v: float, current velocity + frac: float, dv/dr for current shell + """ + shell_id = r_packet.current_shell_id + v_inner = geometry.v_inner[shell_id] + v_outer = geometry.v_outer[shell_id] + r_inner = geometry.r_inner[shell_id] + r_outer = geometry.r_outer[shell_id] + r = r_packet.r + frac = (v_outer - v_inner) / (r_outer - r_inner) + return v_inner + frac * (r - r_inner), frac + + +@njit(**njit_dict_no_parallel) +def tau_sobolev_factor(r_packet, geometry): + """ + The angle and velocity dependent Tau Sobolev factor component. Is called when ENABLE_NONHOMOLOGOUS_EXPANSION is set to True. + + Note: to get Tau Sobolev, this needs to be multiplied by tau_sobolevs found from plasma + Parameters + ---------- + r_packet: RPacket + geometry: Geometry + + Returns + ----------- + factor = 1.0 / ((1 - mu * mu) * v / r + mu * mu * dvdr) + """ + + v, dvdr = velocity_dvdr(r_packet, geometry) + r = r_packet.r + mu = r_packet.mu + factor = 1.0 / ((1 - mu * mu) * v / r + mu * mu * dvdr) + return factor + + +# @njit(**njit_dict_no_parallel) +def quartic_roots(a, b, c, d, e, threshold): + """ + Solves ax^4 + bx^3 + cx^2 + dx + e = 0, for the real roots greater than the threshold returns (x - threshold). + Uses: https://en.wikipedia.org/wiki/Quartic_function#General_formula_for_roots + + Parameters + ----------- + a, b, c, d, e: coefficients of the equations ax^4 + bx^3 + cx^2 + dx + e = 0, float + threshold: lower needed limit on roots, float + Returns + ----------- + roots: real positive roots of ax^4 + bx^3 + cx^2 + dx + e = 0 + + """ + roots = np.roots((a, b, c, d, e)) + roots = [root for root in roots if isinstance(root, float)] + roots = [root for root in roots if root > threshold] + + return roots diff --git a/tardis/montecarlo/montecarlo_numba/numba_config.py b/tardis/transport/montecarlo/numba_config.py similarity index 79% rename from tardis/montecarlo/montecarlo_numba/numba_config.py rename to tardis/transport/montecarlo/numba_config.py index d0c90fe7fed..fb21f5421ae 100644 --- a/tardis/montecarlo/montecarlo_numba/numba_config.py +++ b/tardis/transport/montecarlo/numba_config.py @@ -4,5 +4,5 @@ CLOSE_LINE_THRESHOLD = 1e-14 C_SPEED_OF_LIGHT = const.c.to("cm/s").value MISS_DISTANCE = 1e99 - -ENABLE_FULL_RELATIVITY = False +KB = const.k_B.cgs.value +H = const.h.cgs.value diff --git a/tardis/transport/montecarlo/numba_interface.py b/tardis/transport/montecarlo/numba_interface.py new file mode 100644 index 00000000000..58938bf9044 --- /dev/null +++ b/tardis/transport/montecarlo/numba_interface.py @@ -0,0 +1,256 @@ +from enum import IntEnum + +from numba import float64, int64 +from numba.experimental import jitclass +import numpy as np + +from tardis import constants as const + + +C_SPEED_OF_LIGHT = const.c.to("cm/s").value + + +opacity_state_spec = [ + ("electron_density", float64[:]), + ("t_electrons", float64[:]), + ("line_list_nu", float64[:]), + ("tau_sobolev", float64[:, :]), + ("transition_probabilities", float64[:, :]), + ("line2macro_level_upper", int64[:]), + ("macro_block_references", int64[:]), + ("transition_type", int64[:]), + ("destination_level_id", int64[:]), + ("transition_line_id", int64[:]), + ("bf_threshold_list_nu", float64[:]), + ("p_fb_deactivation", float64[:, :]), + ("photo_ion_nu_threshold_mins", float64[:]), + ("photo_ion_nu_threshold_maxs", float64[:]), + ("photo_ion_block_references", int64[:]), + ("chi_bf", float64[:, :]), + ("x_sect", float64[:]), + ("phot_nus", float64[:]), + ("ff_opacity_factor", float64[:]), + ("emissivities", float64[:, :]), + ("photo_ion_activation_idx", int64[:]), + ("k_packet_idx", int64), +] + + +@jitclass(opacity_state_spec) +class OpacityState(object): + def __init__( + self, + electron_density, + t_electrons, + line_list_nu, + tau_sobolev, + transition_probabilities, + line2macro_level_upper, + macro_block_references, + transition_type, + destination_level_id, + transition_line_id, + bf_threshold_list_nu, + p_fb_deactivation, + photo_ion_nu_threshold_mins, + photo_ion_nu_threshold_maxs, + photo_ion_block_references, + chi_bf, + x_sect, + phot_nus, + ff_opacity_factor, + emissivities, + photo_ion_activation_idx, + k_packet_idx, + ): + """ + Plasma for the Numba code + + Parameters + ---------- + electron_density : numpy.ndarray + t_electrons : numpy.ndarray + line_list_nu : numpy.ndarray + tau_sobolev : numpy.ndarray + transition_probabilities : numpy.ndarray + line2macro_level_upper : numpy.ndarray + macro_block_references : numpy.ndarray + transition_type : numpy.ndarray + destination_level_id : numpy.ndarray + transition_line_id : numpy.ndarray + bf_threshold_list_nu : numpy.ndarray + """ + + self.electron_density = electron_density + self.t_electrons = t_electrons + self.line_list_nu = line_list_nu + self.tau_sobolev = tau_sobolev + self.bf_threshold_list_nu = bf_threshold_list_nu + + #### Macro Atom transition probabilities + self.transition_probabilities = transition_probabilities + self.line2macro_level_upper = line2macro_level_upper + + self.macro_block_references = macro_block_references + self.transition_type = transition_type + + # Destination level is not needed and/or generated for downbranch + self.destination_level_id = destination_level_id + self.transition_line_id = transition_line_id + self.p_fb_deactivation = p_fb_deactivation + + # Continuum Opacity Data + self.photo_ion_nu_threshold_mins = photo_ion_nu_threshold_mins + self.photo_ion_nu_threshold_maxs = photo_ion_nu_threshold_maxs + + self.photo_ion_block_references = photo_ion_block_references + self.chi_bf = chi_bf + self.x_sect = x_sect + self.phot_nus = phot_nus + self.ff_opacity_factor = ff_opacity_factor + self.emissivities = emissivities + self.photo_ion_activation_idx = photo_ion_activation_idx + self.k_packet_idx = k_packet_idx + + +def opacity_state_initialize( + plasma, + line_interaction_type, + disable_line_scattering, + continuum_processes_enabled, +): + """ + Initialize the OpacityState object and copy over the data over from TARDIS Plasma + + Parameters + ---------- + plasma : tardis.plasma.BasePlasma + line_interaction_type : enum + """ + + electron_densities = plasma.electron_densities.values + t_electrons = plasma.t_electrons + line_list_nu = plasma.atomic_data.lines.nu.values + tau_sobolev = np.ascontiguousarray( + plasma.tau_sobolevs.values.copy(), dtype=np.float64 + ) + if disable_line_scattering: + tau_sobolev *= 0 + + if line_interaction_type == "scatter": + # to adhere to data types, we must have an array of minimum size 1 + array_size = 1 + transition_probabilities = np.zeros( + (array_size, array_size), dtype=np.float64 + ) # to adhere to data types + line2macro_level_upper = np.zeros(array_size, dtype=np.int64) + macro_block_references = np.zeros(array_size, dtype=np.int64) + transition_type = np.zeros(array_size, dtype=np.int64) + destination_level_id = np.zeros(array_size, dtype=np.int64) + transition_line_id = np.zeros(array_size, dtype=np.int64) + else: + transition_probabilities = np.ascontiguousarray( + plasma.transition_probabilities.values.copy(), dtype=np.float64 + ) + line2macro_level_upper = ( + plasma.atomic_data.lines_upper2macro_reference_idx + ) + # TODO: Fix setting of block references for non-continuum mode + + if continuum_processes_enabled: + macro_block_references = plasma.macro_block_references + else: + macro_block_references = plasma.atomic_data.macro_atom_references[ + "block_references" + ].values + transition_type = plasma.macro_atom_data["transition_type"].values + + # Destination level is not needed and/or generated for downbranch + destination_level_id = plasma.macro_atom_data[ + "destination_level_idx" + ].values + transition_line_id = plasma.macro_atom_data["lines_idx"].values + if continuum_processes_enabled: + bf_threshold_list_nu = plasma.nu_i.loc[ + plasma.level2continuum_idx.index + ].values + p_fb_deactivation = np.ascontiguousarray( + plasma.p_fb_deactivation.values.copy(), dtype=np.float64 + ) + + phot_nus = plasma.photo_ion_cross_sections.nu.loc[ + plasma.level2continuum_idx.index + ] + photo_ion_block_references = np.pad( + phot_nus.groupby(level=[0, 1, 2], sort=False) + .count() + .values.cumsum(), + [1, 0], + ) + photo_ion_nu_threshold_mins = ( + phot_nus.groupby(level=[0, 1, 2], sort=False).first().values + ) + photo_ion_nu_threshold_maxs = ( + phot_nus.groupby(level=[0, 1, 2], sort=False).last().values + ) + + chi_bf = plasma.chi_bf.loc[plasma.level2continuum_idx.index].values + x_sect = plasma.photo_ion_cross_sections.x_sect.loc[ + plasma.level2continuum_idx.index + ].values + + phot_nus = phot_nus.values + ff_opacity_factor = ( + plasma.ff_cooling_factor / np.sqrt(t_electrons) + ).astype(np.float64) + emissivities = plasma.fb_emission_cdf.loc[ + plasma.level2continuum_idx.index + ].values + photo_ion_activation_idx = plasma.photo_ion_idx.loc[ + plasma.level2continuum_idx.index, "destination_level_idx" + ].values + k_packet_idx = np.int64(plasma.k_packet_idx) + else: + bf_threshold_list_nu = np.zeros(0, dtype=np.float64) + p_fb_deactivation = np.zeros((0, 0), dtype=np.float64) + photo_ion_nu_threshold_mins = np.zeros(0, dtype=np.float64) + photo_ion_nu_threshold_maxs = np.zeros(0, dtype=np.float64) + photo_ion_block_references = np.zeros(0, dtype=np.int64) + chi_bf = np.zeros((0, 0), dtype=np.float64) + x_sect = np.zeros(0, dtype=np.float64) + phot_nus = np.zeros(0, dtype=np.float64) + ff_opacity_factor = np.zeros(0, dtype=np.float64) + emissivities = np.zeros((0, 0), dtype=np.float64) + photo_ion_activation_idx = np.zeros(0, dtype=np.int64) + k_packet_idx = np.int64(-1) + + return OpacityState( + electron_densities, + t_electrons, + line_list_nu, + tau_sobolev, + transition_probabilities, + line2macro_level_upper, + macro_block_references, + transition_type, + destination_level_id, + transition_line_id, + bf_threshold_list_nu, + p_fb_deactivation, + photo_ion_nu_threshold_mins, + photo_ion_nu_threshold_maxs, + photo_ion_block_references, + chi_bf, + x_sect, + phot_nus, + ff_opacity_factor, + emissivities, + photo_ion_activation_idx, + k_packet_idx, + ) + + +class LineInteractionType(IntEnum): + SCATTER = 0 + DOWNBRANCH = 1 + MACROATOM = 2 diff --git a/tardis/transport/montecarlo/packet_collections.py b/tardis/transport/montecarlo/packet_collections.py new file mode 100644 index 00000000000..9745726d7bb --- /dev/null +++ b/tardis/transport/montecarlo/packet_collections.py @@ -0,0 +1,349 @@ +import numpy as np +from numba import float64, int64, njit +from numba.experimental import jitclass + +from tardis.transport.montecarlo import ( + njit_dict_no_parallel, +) + +packet_collection_spec = [ + ("initial_radii", float64[:]), + ("initial_nus", float64[:]), + ("initial_mus", float64[:]), + ("initial_energies", float64[:]), + ("packet_seeds", int64[:]), + ("time_of_simulation", float64), + ("radiation_field_luminosity", float64), # + ("output_nus", float64[:]), + ("output_energies", float64[:]), +] + + +@jitclass(packet_collection_spec) +class PacketCollection: + def __init__( + self, + initial_radii, + initial_nus, + initial_mus, + initial_energies, + packet_seeds, + radiation_field_luminosity, + ): + self.initial_radii = initial_radii + self.initial_nus = initial_nus + self.initial_mus = initial_mus + self.initial_energies = initial_energies + self.packet_seeds = packet_seeds + self.radiation_field_luminosity = radiation_field_luminosity + self.time_of_simulation = ( + 1 / radiation_field_luminosity + ) # 1 erg / luminosity + self.output_nus = np.ones_like(initial_radii, dtype=np.float64) * -99.0 + self.output_energies = ( + np.ones_like(initial_radii, dtype=np.float64) * -99.0 + ) + + +@njit(**njit_dict_no_parallel) +def initialize_last_interaction_tracker(no_of_packets): + last_line_interaction_in_ids = -1 * np.ones(no_of_packets, dtype=np.int64) + last_line_interaction_out_ids = -1 * np.ones(no_of_packets, dtype=np.int64) + last_line_interaction_shell_ids = -1 * np.ones( + no_of_packets, dtype=np.int64 + ) + last_interaction_types = -1 * np.ones(no_of_packets, dtype=np.int64) + last_interaction_in_nus = np.zeros(no_of_packets, dtype=np.float64) + + return LastInteractionTracker( + last_interaction_types, + last_interaction_in_nus, + last_line_interaction_in_ids, + last_line_interaction_out_ids, + last_line_interaction_shell_ids, + ) + + +last_interaction_tracker_spec = [ + ("types", int64[:]), + ("in_nus", float64[:]), + ("in_ids", int64[:]), + ("out_ids", int64[:]), + ("shell_ids", int64[:]), +] + + +@jitclass(last_interaction_tracker_spec) +class LastInteractionTracker: + def __init__( + self, + types, + in_nus, + in_ids, + out_ids, + shell_ids, + ): + self.types = types + self.in_nus = in_nus + self.in_ids = in_ids + self.out_ids = out_ids + self.shell_ids = shell_ids + + def update_last_interaction(self, r_packet, i): + self.types[i] = r_packet.last_interaction_type + self.in_nus[i] = r_packet.last_interaction_in_nu + self.in_ids[i] = r_packet.last_line_interaction_in_id + self.out_ids[i] = r_packet.last_line_interaction_out_id + self.shell_ids[i] = r_packet.last_line_interaction_shell_id + + +vpacket_collection_spec = [ + ("source_rpacket_index", int64), + ("spectrum_frequency", float64[:]), + ("v_packet_spawn_start_frequency", float64), + ("v_packet_spawn_end_frequency", float64), + ("nus", float64[:]), + ("energies", float64[:]), + ("initial_mus", float64[:]), + ("initial_rs", float64[:]), + ("idx", int64), + ("number_of_vpackets", int64), + ("length", int64), + ("last_interaction_in_nu", float64[:]), + ("last_interaction_type", int64[:]), + ("last_interaction_in_id", int64[:]), + ("last_interaction_out_id", int64[:]), + ("last_interaction_shell_id", int64[:]), +] + + +@jitclass(vpacket_collection_spec) +class VPacketCollection: + def __init__( + self, + source_rpacket_index, + spectrum_frequency, + v_packet_spawn_start_frequency, + v_packet_spawn_end_frequency, + number_of_vpackets, + temporary_v_packet_bins, + ): + self.spectrum_frequency = spectrum_frequency + self.v_packet_spawn_start_frequency = v_packet_spawn_start_frequency + self.v_packet_spawn_end_frequency = v_packet_spawn_end_frequency + self.nus = np.empty(temporary_v_packet_bins, dtype=np.float64) + self.energies = np.empty(temporary_v_packet_bins, dtype=np.float64) + self.initial_mus = np.empty(temporary_v_packet_bins, dtype=np.float64) + self.initial_rs = np.empty(temporary_v_packet_bins, dtype=np.float64) + self.number_of_vpackets = number_of_vpackets + self.last_interaction_in_nu = np.zeros( + temporary_v_packet_bins, dtype=np.float64 + ) + self.last_interaction_type = -1 * np.ones( + temporary_v_packet_bins, dtype=np.int64 + ) + self.last_interaction_in_id = -1 * np.ones( + temporary_v_packet_bins, dtype=np.int64 + ) + self.last_interaction_out_id = -1 * np.ones( + temporary_v_packet_bins, dtype=np.int64 + ) + self.last_interaction_shell_id = -1 * np.ones( + temporary_v_packet_bins, dtype=np.int64 + ) + self.idx = 0 + self.source_rpacket_index = source_rpacket_index + self.length = temporary_v_packet_bins + + def add_packet( + self, + nu, + energy, + initial_mu, + initial_r, + last_interaction_in_nu, + last_interaction_type, + last_interaction_in_id, + last_interaction_out_id, + last_interaction_shell_id, + ): + """ + Add a packet to the vpacket collection and potentially resizing the arrays. + + Parameters + ---------- + nu : float + Frequency of the packet. + energy : float + Energy of the packet. + initial_mu : float + Initial mu of the packet. + initial_r : float + Initial r of the packet. + last_interaction_in_nu : float + Frequency of the last interaction of the packet. + last_interaction_type : int + Type of the last interaction of the packet. + last_interaction_in_id : int + ID of the last interaction in the packet. + last_interaction_out_id : int + ID of the last interaction out of the packet. + last_interaction_shell_id : int + ID of the last interaction shell of the packet. + + Returns + ------- + None + + """ + if self.idx >= self.length: + temp_length = self.length * 2 + self.number_of_vpackets + temp_nus = np.empty(temp_length, dtype=np.float64) + temp_energies = np.empty(temp_length, dtype=np.float64) + temp_initial_mus = np.empty(temp_length, dtype=np.float64) + temp_initial_rs = np.empty(temp_length, dtype=np.float64) + temp_last_interaction_in_nu = np.empty( + temp_length, dtype=np.float64 + ) + temp_last_interaction_type = np.empty(temp_length, dtype=np.int64) + temp_last_interaction_in_id = np.empty(temp_length, dtype=np.int64) + temp_last_interaction_out_id = np.empty(temp_length, dtype=np.int64) + temp_last_interaction_shell_id = np.empty( + temp_length, dtype=np.int64 + ) + + temp_nus[: self.length] = self.nus + temp_energies[: self.length] = self.energies + temp_initial_mus[: self.length] = self.initial_mus + temp_initial_rs[: self.length] = self.initial_rs + temp_last_interaction_in_nu[ + : self.length + ] = self.last_interaction_in_nu + temp_last_interaction_type[ + : self.length + ] = self.last_interaction_type + temp_last_interaction_in_id[ + : self.length + ] = self.last_interaction_in_id + temp_last_interaction_out_id[ + : self.length + ] = self.last_interaction_out_id + temp_last_interaction_shell_id[ + : self.length + ] = self.last_interaction_shell_id + + self.nus = temp_nus + self.energies = temp_energies + self.initial_mus = temp_initial_mus + self.initial_rs = temp_initial_rs + self.last_interaction_in_nu = temp_last_interaction_in_nu + self.last_interaction_type = temp_last_interaction_type + self.last_interaction_in_id = temp_last_interaction_in_id + self.last_interaction_out_id = temp_last_interaction_out_id + self.last_interaction_shell_id = temp_last_interaction_shell_id + self.length = temp_length + + self.nus[self.idx] = nu + self.energies[self.idx] = energy + self.initial_mus[self.idx] = initial_mu + self.initial_rs[self.idx] = initial_r + self.last_interaction_in_nu[self.idx] = last_interaction_in_nu + self.last_interaction_type[self.idx] = last_interaction_type + self.last_interaction_in_id[self.idx] = last_interaction_in_id + self.last_interaction_out_id[self.idx] = last_interaction_out_id + self.last_interaction_shell_id[self.idx] = last_interaction_shell_id + self.idx += 1 + + def finalize_arrays(self): + """ + Finalize the arrays by truncating them based on the current index. + + Returns + ------- + None + + """ + self.nus = self.nus[: self.idx] + self.energies = self.energies[: self.idx] + self.initial_mus = self.initial_mus[: self.idx] + self.initial_rs = self.initial_rs[: self.idx] + self.last_interaction_in_nu = self.last_interaction_in_nu[: self.idx] + self.last_interaction_type = self.last_interaction_type[: self.idx] + self.last_interaction_in_id = self.last_interaction_in_id[: self.idx] + self.last_interaction_out_id = self.last_interaction_out_id[: self.idx] + self.last_interaction_shell_id = self.last_interaction_shell_id[ + : self.idx + ] + + +@njit(**njit_dict_no_parallel) +def consolidate_vpacket_tracker( + vpacket_collections, spectrum_frequency, start_frequency, end_frequency +): + """ + Consolidate the vpacket trackers from multiple collections into a single vpacket tracker. + + Parameters + ---------- + vpacket_collections : List[VPacketCollection] + List of vpacket collections to consolidate. + spectrum_frequency : ndarray + Array of spectrum frequencies. + + Returns + ------- + VPacketCollection + Consolidated vpacket tracker. + + """ + vpacket_tracker_length = 0 + for vpacket_collection in vpacket_collections: + vpacket_tracker_length += vpacket_collection.idx + + vpacket_tracker = VPacketCollection( + -1, + spectrum_frequency, + start_frequency, + end_frequency, + -1, + vpacket_tracker_length, + ) + current_start_vpacket_tracker_idx = 0 + for vpacket_collection in vpacket_collections: + current_end_vpacket_tracker_idx = ( + current_start_vpacket_tracker_idx + vpacket_collection.idx + ) + vpacket_tracker.nus[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.nus + vpacket_tracker.energies[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.energies + vpacket_tracker.initial_mus[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.initial_mus + vpacket_tracker.initial_rs[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.initial_rs + vpacket_tracker.last_interaction_in_nu[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.last_interaction_in_nu + + vpacket_tracker.last_interaction_type[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.last_interaction_type + + vpacket_tracker.last_interaction_in_id[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.last_interaction_in_id + + vpacket_tracker.last_interaction_out_id[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.last_interaction_out_id + + vpacket_tracker.last_interaction_shell_id[ + current_start_vpacket_tracker_idx:current_end_vpacket_tracker_idx + ] = vpacket_collection.last_interaction_shell_id + + current_start_vpacket_tracker_idx = current_end_vpacket_tracker_idx + return vpacket_tracker diff --git a/tardis/transport/montecarlo/packet_source.py b/tardis/transport/montecarlo/packet_source.py new file mode 100644 index 00000000000..ae2f73e8df8 --- /dev/null +++ b/tardis/transport/montecarlo/packet_source.py @@ -0,0 +1,387 @@ +import abc + +import numpy as np +import numexpr as ne +from tardis import constants as const +from tardis.transport.montecarlo.packet_collections import ( + PacketCollection, +) +from tardis.io.util import HDFWriterMixin +from astropy import units as u + + +class BasePacketSource(abc.ABC): + """ + Abstract base packet source + + Parameters + ---------- + base_seed : int + Base Seed for random number generator + legacy_secondary_seed : int + Secondary seed for global numpy rng (Deprecated: Legacy reasons only) + """ + + # MAX_SEED_VAL must be multiple orders of magnitude larger than no_of_packets; + # otherwise, each packet would not have its own seed. Here, we set the max + # seed val to the maximum allowed by numpy. + MAX_SEED_VAL = 2**32 - 1 + + def __init__( + self, base_seed=None, legacy_mode_enabled=False, legacy_second_seed=None + ): + self.base_seed = base_seed + self.legacy_mode_enabled = legacy_mode_enabled + if self.legacy_mode_enabled and legacy_second_seed is not None: + np.random.seed(legacy_second_seed) + else: + np.random.seed(self.base_seed) + + def _reseed(self, seed): + self.rng = np.random.default_rng(seed=seed) + + @abc.abstractmethod + def create_packet_radii(self, no_of_packets, *args, **kwargs): + pass + + @abc.abstractmethod + def create_packet_nus(self, no_of_packets, *args, **kwargs): + pass + + @abc.abstractmethod + def create_packet_mus(self, no_of_packets, *args, **kwargs): + pass + + @abc.abstractmethod + def create_packet_energies(self, no_of_packets, *args, **kwargs): + pass + + def create_packets(self, no_of_packets, seed_offset=0, *args, **kwargs): + """Generate packet properties as arrays + + Parameters + ---------- + no_of_packets : int + Number of packets + + Returns + ------- + array + Packet radii + array + Packet frequencies + array + Packet directions + array + Packet energies + """ + # the iteration (passed as seed_offset) is added each time to preserve randomness + # across different simulations with the same temperature, + # for example. We seed the random module instead of the numpy module + # because we call random.sample, which references a different internal + # state than in the numpy.random module. + self._reseed(self.base_seed + seed_offset) + packet_seeds = self.rng.choice( + self.MAX_SEED_VAL, no_of_packets, replace=True + ) + + radii = self.create_packet_radii(no_of_packets, *args, **kwargs).value + nus = self.create_packet_nus(no_of_packets, *args, **kwargs).value + mus = self.create_packet_mus(no_of_packets, *args, **kwargs) + energies = self.create_packet_energies( + no_of_packets, *args, **kwargs + ).value + # Check if all arrays have the same length + assert ( + len(radii) == len(nus) == len(mus) == len(energies) == no_of_packets + ) + radiation_field_luminosity = self.calculate_radfield_luminosity().value + return PacketCollection( + radii, + nus, + mus, + energies, + packet_seeds, + radiation_field_luminosity, + ) + + def calculate_radfield_luminosity(self): + """ + Calculate inner luminosity. + + Parameters + ---------- + model : model.SimulationState + + Returns + ------- + astropy.units.Quantity + """ + return ( + 4 + * np.pi + * const.sigma_sb + * self.radius**2 + * self.temperature**4 + ).to("erg/s") + + +class BlackBodySimpleSource(BasePacketSource, HDFWriterMixin): + """ + Simple packet source that generates Blackbody packets for the Montecarlo + part. + + Parameters + ---------- + radius : astropy.units.Quantity + Initial packet radius + temperature : astropy.units.Quantity + Absolute Temperature. + base_seed : int + Base Seed for random number generator + legacy_secondary_seed : int + Secondary seed for global numpy rng (Deprecated: Legacy reasons only) + """ + + hdf_properties = ["radius", "temperature", "base_seed"] + hdf_name = "black_body_simple_source" + + @classmethod + def from_simulation_state(cls, simulation_state, *args, **kwargs): + return cls( + simulation_state.r_inner[0], + simulation_state.t_inner, + *args, + **kwargs, + ) + + def __init__(self, radius=None, temperature=None, **kwargs): + self.radius = radius + self.temperature = temperature + super().__init__(**kwargs) + + def create_packets(self, no_of_packets, *args, **kwargs): + if self.radius is None or self.temperature is None: + raise ValueError("Black body Radius or Temperature isn't set") + return super().create_packets(no_of_packets, *args, **kwargs) + + def create_packet_radii(self, no_of_packets): + """ + Create packet radii + + Parameters + ---------- + no_of_packets : int + number of packets to be created + + Returns + ------- + Radii for packets + numpy.ndarray + """ + return np.ones(no_of_packets) * self.radius.cgs + + def create_packet_nus(self, no_of_packets, l_samples=1000): + """ + Create packet :math:`\\nu` distributed using the algorithm described in + Bjorkman & Wood 2001 (page 4) which references + Carter & Cashwell 1975: + First, generate a uniform random number, :math:`\\xi_0 \\in [0, 1]` and + determine the minimum value of + :math:`l, l_{\\rm min}`, that satisfies the condition + .. math:: + \\sum_{i=1}^{l} i^{-4} \\ge {{\\pi^4}\\over{90}} m_0 \\;. + Next obtain four additional uniform random numbers (in the range 0 + to 1) :math:`\\xi_1, \\xi_2, \\xi_3, {\\rm and } \\xi_4`. + Finally, the packet frequency is given by + .. math:: + x = -\\ln{(\\xi_1\\xi_2\\xi_3\\xi_4)}/l_{\\rm min}\\;. + where :math:`x=h\\nu/kT` + + Parameters + ---------- + no_of_packets : int + l_samples : int + number of l_samples needed in the algorithm + + Returns + ------- + array of frequencies + numpy.ndarray + """ + l_array = np.cumsum(np.arange(1, l_samples, dtype=np.float64) ** -4) + l_coef = np.pi**4 / 90.0 + + # For testing purposes + if self.legacy_mode_enabled: + xis = np.random.random((5, no_of_packets)) + else: + xis = self.rng.random((5, no_of_packets)) + + l = l_array.searchsorted(xis[0] * l_coef) + 1.0 + xis_prod = np.prod(xis[1:], 0) + x = ne.evaluate("-log(xis_prod)/l") + + return (x * (const.k_B * self.temperature) / const.h).cgs + + def create_packet_mus(self, no_of_packets): + """ + Create zero-limb-darkening packet :math:`\mu` distributed + according to :math:`\\mu=\\sqrt{z}, z \isin [0, 1]` + + Parameters + ---------- + no_of_packets : int + number of packets to be created + + Returns + ------- + Directions for packets + numpy.ndarray + """ + + # For testing purposes + if self.legacy_mode_enabled: + return np.sqrt(np.random.random(no_of_packets)) + else: + return np.sqrt(self.rng.random(no_of_packets)) + + def create_packet_energies(self, no_of_packets): + """ + Uniformly distribute energy in arbitrary units where the ensemble of + packets has energy of 1. + + Parameters + ---------- + no_of_packets : int + number of packets + + Returns + ------- + energies for packets + numpy.ndarray + """ + return np.ones(no_of_packets) / no_of_packets * u.erg + + def set_temperature_from_luminosity(self, luminosity: u.Quantity): + """ + Set blackbody packet source temperature from luminosity + + Parameters + ---------- + + luminosity : u.Quantity + + """ + self.temperature = ( + (luminosity / (4 * np.pi * self.radius**2 * const.sigma_sb)) + ** 0.25 + ).to("K") + + +class BlackBodySimpleSourceRelativistic(BlackBodySimpleSource, HDFWriterMixin): + """ + Simple packet source that generates Blackbody packets for the Montecarlo + part. + + Parameters + ---------- + time_explosion : astropy.units.Quantity + Time elapsed since explosion + radius : astropy.units.Quantity + Initial packet radius + temperature : astropy.units.Quantity + Absolute Temperature. + base_seed : int + Base Seed for random number generator + legacy_secondary_seed : int + Secondary seed for global numpy rng (Deprecated: Legacy reasons only) + """ + + hdf_properties = ["time_explosion", "radius", "temperature", "base_seed"] + + @classmethod + def from_simulation_state(cls, simulation_state, *args, **kwargs): + return cls( + simulation_state.time_explosion, + simulation_state.r_inner[0], + simulation_state.t_inner, + *args, + **kwargs, + ) + + def __init__(self, time_explosion=None, **kwargs): + self.time_explosion = time_explosion + super().__init__(**kwargs) + + def create_packets(self, no_of_packets): + """Generate relativistic black-body packet properties as arrays + + Parameters + ---------- + no_of_packets : int + Number of packets + + Returns + ------- + array + Packet radii + array + Packet frequencies + array + Packet directions + array + Packet energies + """ + if self.radius is None or self.time_explosion is None: + raise ValueError("Black body Radius or Time of Explosion isn't set") + self.beta = (self.radius / self.time_explosion) / const.c + return super().create_packets(no_of_packets) + + def create_packet_mus(self, no_of_packets): + """ + Create zero-limb-darkening packet :math:`\mu^\prime` distributed + according to :math:`\\mu^\\prime=2 \\frac{\\mu^\\prime + \\beta}{2 \\beta + 1}`. + The complicated distribution is due to the fact that the inner boundary + on which the packets are initialized is not comoving with the material. + + Parameters + ---------- + no_of_packets : int + number of packets to be created + + Returns + ------- + Directions for packets + numpy.ndarray + """ + z = self.rng.random(no_of_packets) + beta = self.beta + return -beta + np.sqrt(beta**2 + 2 * beta * z + z) + + def create_packet_energies(self, no_of_packets): + """ + Uniformly distribute energy in arbitrary units where the ensemble of + packets has energy of 1 multiplied by relativistic correction factors. + + Parameters + ---------- + no_of_packets : int + number of packets + + Returns + ------- + energies for packets + numpy.ndarray + """ + beta = self.beta + gamma = 1.0 / np.sqrt(1 - beta**2) + static_inner_boundary2cmf_factor = (2 * beta + 1) / (1 - beta**2) + energies = np.ones(no_of_packets) / no_of_packets + # In principle, the factor gamma should be applied to the time of + # simulation to account for time dilation between the lab and comoving + # frame. However, all relevant quantities (luminosities, estimators, ...) + # are calculated as ratios of packet energies and the time of simulation. + # Thus, we can absorb the factor gamma in the packet energies, which is + # more convenient. + return energies * static_inner_boundary2cmf_factor / gamma * u.erg diff --git a/tardis/transport/montecarlo/packet_trackers.py b/tardis/transport/montecarlo/packet_trackers.py new file mode 100644 index 00000000000..469a4e81c19 --- /dev/null +++ b/tardis/transport/montecarlo/packet_trackers.py @@ -0,0 +1,158 @@ +from numba import float64, int64 +from numba.experimental import jitclass +import numpy as np +import pandas as pd + +rpacket_tracker_spec = [ + ("length", int64), + ("seed", int64), + ("index", int64), + ("status", int64[:]), + ("r", float64[:]), + ("nu", float64[:]), + ("mu", float64[:]), + ("energy", float64[:]), + ("shell_id", int64[:]), + ("interaction_type", int64[:]), + ("num_interactions", int64), +] + + +@jitclass(rpacket_tracker_spec) +class RPacketTracker(object): + """ + Numba JITCLASS for storing the information for each interaction a RPacket instance undergoes. + Parameters + ---------- + length : int + Length of the initial array that is instantiated + seed : int + Seed for each RPacket + index : int + Index position of each RPacket + status : int + Current status of the RPacket as per interactions + r : float + Radius of the shell where the RPacket is present + nu : float + Luminosity of the RPacket + mu : float + Cosine of the angle made by the direction of movement of the RPacket from its original direction + energy : float + Energy possessed by the RPacket at a particular shell + shell_id : int + Current Shell No in which the RPacket is present + interaction_type: int + Type of interaction the rpacket undergoes + num_interactions : int + Internal counter for the interactions that a particular RPacket undergoes + """ + + def __init__(self, length): + self.length = length + self.seed = np.int64(0) + self.index = np.int64(0) + self.status = np.empty(self.length, dtype=np.int64) + self.r = np.empty(self.length, dtype=np.float64) + self.nu = np.empty(self.length, dtype=np.float64) + self.mu = np.empty(self.length, dtype=np.float64) + self.energy = np.empty(self.length, dtype=np.float64) + self.shell_id = np.empty(self.length, dtype=np.int64) + self.interaction_type = np.empty(self.length, dtype=np.int64) + self.num_interactions = 0 + + def track(self, r_packet): + if self.num_interactions >= self.length: + temp_length = self.length * 2 + temp_status = np.empty(temp_length, dtype=np.int64) + temp_r = np.empty(temp_length, dtype=np.float64) + temp_nu = np.empty(temp_length, dtype=np.float64) + temp_mu = np.empty(temp_length, dtype=np.float64) + temp_energy = np.empty(temp_length, dtype=np.float64) + temp_shell_id = np.empty(temp_length, dtype=np.int64) + temp_interaction_type = np.empty(temp_length, dtype=np.int64) + + temp_status[: self.length] = self.status + temp_r[: self.length] = self.r + temp_nu[: self.length] = self.nu + temp_mu[: self.length] = self.mu + temp_energy[: self.length] = self.energy + temp_shell_id[: self.length] = self.shell_id + temp_interaction_type[: self.length] = self.interaction_type + + self.status = temp_status + self.r = temp_r + self.nu = temp_nu + self.mu = temp_mu + self.energy = temp_energy + self.shell_id = temp_shell_id + self.interaction_type = temp_interaction_type + self.length = temp_length + + self.index = r_packet.index + self.seed = r_packet.seed + self.status[self.num_interactions] = r_packet.status + self.r[self.num_interactions] = r_packet.r + self.nu[self.num_interactions] = r_packet.nu + self.mu[self.num_interactions] = r_packet.mu + self.energy[self.num_interactions] = r_packet.energy + self.shell_id[self.num_interactions] = r_packet.current_shell_id + self.interaction_type[ + self.num_interactions + ] = r_packet.last_interaction_type + self.num_interactions += 1 + + def finalize_array(self): + self.status = self.status[: self.num_interactions] + self.r = self.r[: self.num_interactions] + self.nu = self.nu[: self.num_interactions] + self.mu = self.mu[: self.num_interactions] + self.energy = self.energy[: self.num_interactions] + self.shell_id = self.shell_id[: self.num_interactions] + self.interaction_type = self.interaction_type[: self.num_interactions] + + +def rpacket_trackers_to_dataframe(rpacket_trackers): + """Generates a dataframe from the rpacket_trackers list of RPacketCollection Objects. + + Parameters + ---------- + rpacket_trackers : numba.typed.typedlist.List + list of individual RPacketCollection class objects + + Returns + ------- + pandas.core.frame.DataFrame + Dataframe containing properties of RPackets as columns like status, seed, r, nu, mu, energy, shell_id, interaction_type + + """ + len_df = sum([len(tracker.r) for tracker in rpacket_trackers]) + index_array = np.empty([2, len_df], dtype="int") + df_dtypes = np.dtype( + [ + ("status", np.int64), + ("seed", np.int64), + ("r", np.float64), + ("nu", np.float64), + ("mu", np.float64), + ("energy", np.float64), + ("shell_id", np.int64), + ("interaction_type", np.int64), + ] + ) + rpacket_tracker_ndarray = np.empty(len_df, df_dtypes) + cur_index = 0 + for rpacket_tracker in rpacket_trackers: + prev_index = cur_index + cur_index = prev_index + len(rpacket_tracker.r) + for j, column_name in enumerate(df_dtypes.fields.keys()): + rpacket_tracker_ndarray[column_name][ + prev_index:cur_index + ] = getattr(rpacket_tracker, column_name) + index_array[0][prev_index:cur_index] = getattr(rpacket_tracker, "index") + index_array[1][prev_index:cur_index] = range(cur_index - prev_index) + return pd.DataFrame( + rpacket_tracker_ndarray, + index=pd.MultiIndex.from_arrays(index_array, names=["index", "step"]), + columns=df_dtypes.names, + ) diff --git a/tardis/montecarlo/montecarlo_numba/r_packet.py b/tardis/transport/montecarlo/r_packet.py similarity index 63% rename from tardis/montecarlo/montecarlo_numba/r_packet.py rename to tardis/transport/montecarlo/r_packet.py index 271bda7f409..e781ce3572f 100644 --- a/tardis/montecarlo/montecarlo_numba/r_packet.py +++ b/tardis/transport/montecarlo/r_packet.py @@ -1,24 +1,32 @@ from enum import IntEnum import numpy as np +import pandas as pd from numba import int64, float64, njit, objmode from numba.experimental import jitclass -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( +from tardis.transport.montecarlo import ( + njit_dict_no_parallel, +) +from tardis.transport.frame_transformations import ( get_doppler_factor, ) -from tardis.montecarlo.montecarlo_numba import njit_dict_no_parallel +from tardis.transport.montecarlo import numba_config as nc +from tardis.transport.montecarlo import njit_dict_no_parallel + class InteractionType(IntEnum): BOUNDARY = 1 LINE = 2 - ESCATTERING = 3 + ESCATTERING = 4 + CONTINUUM_PROCESS = 8 class PacketStatus(IntEnum): IN_PROCESS = 0 EMITTED = 1 REABSORBED = 2 + ADIABATIC_COOLING = 4 rpacket_spec = [ @@ -35,6 +43,7 @@ class PacketStatus(IntEnum): ("last_interaction_in_nu", float64), ("last_line_interaction_in_id", int64), ("last_line_interaction_out_id", int64), + ("last_line_interaction_shell_id", int64), ] @@ -53,17 +62,20 @@ def __init__(self, r, mu, nu, energy, seed, index=0): self.last_interaction_in_nu = 0.0 self.last_line_interaction_in_id = -1 self.last_line_interaction_out_id = -1 + self.last_line_interaction_shell_id = -1 - def initialize_line_id(self, numba_plasma, numba_model): - inverse_line_list_nu = numba_plasma.line_list_nu[::-1] + def initialize_line_id( + self, opacity_state, time_explosion, enable_full_relativity + ): + inverse_line_list_nu = opacity_state.line_list_nu[::-1] doppler_factor = get_doppler_factor( - self.r, self.mu, numba_model.time_explosion + self.r, self.mu, time_explosion, enable_full_relativity ) comov_nu = self.nu * doppler_factor - next_line_id = len(numba_plasma.line_list_nu) - np.searchsorted( + next_line_id = len(opacity_state.line_list_nu) - np.searchsorted( inverse_line_list_nu, comov_nu ) - if next_line_id == len(numba_plasma.line_list_nu): + if next_line_id == len(opacity_state.line_list_nu): next_line_id -= 1 self.next_line_id = next_line_id @@ -78,9 +90,13 @@ def print_r_packet_properties(r_packet): r_packet : RPacket RPacket object """ - print("-"*80) + print("-" * 80) print("R-Packet information:") with objmode: for r_packet_attribute_name, _ in rpacket_spec: - print(r_packet_attribute_name, "=", str(getattr(r_packet, r_packet_attribute_name))) - print("-"*80) \ No newline at end of file + print( + r_packet_attribute_name, + "=", + str(getattr(r_packet, r_packet_attribute_name)), + ) + print("-" * 80) diff --git a/tardis/transport/montecarlo/r_packet_transport.py b/tardis/transport/montecarlo/r_packet_transport.py new file mode 100644 index 00000000000..24238968b87 --- /dev/null +++ b/tardis/transport/montecarlo/r_packet_transport.py @@ -0,0 +1,248 @@ +import numpy as np +from numba import njit + +from tardis.transport.frame_transformations import ( + get_doppler_factor, +) +from tardis.transport.geometry.calculate_distances import ( + calculate_distance_boundary, + calculate_distance_line, +) +from tardis.transport.montecarlo import njit_dict_no_parallel +from tardis.transport.montecarlo.estimators.radfield_estimator_calcs import ( + update_base_estimators, + update_line_estimators, +) +from tardis.transport.montecarlo.r_packet import ( + InteractionType, + PacketStatus, +) + + +@njit(**njit_dict_no_parallel) +def trace_packet( + r_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + estimators, + chi_continuum, + escat_prob, + continuum_processes_enabled, + enable_full_relativity, + disable_line_scattering, +): + """ + Traces the RPacket through the ejecta and stops when an interaction happens (heart of the calculation) + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + numba_radial_1d_geometry : tardis.transport.montecarlo.numba_interface.NumbaRadial1DGeometry + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + estimators : tardis.transport.montecarlo.numba_interface.Estimators + + Returns + ------- + """ + r_inner = numba_radial_1d_geometry.r_inner[r_packet.current_shell_id] + r_outer = numba_radial_1d_geometry.r_outer[r_packet.current_shell_id] + + ( + distance_boundary, + delta_shell, + ) = calculate_distance_boundary(r_packet.r, r_packet.mu, r_inner, r_outer) + + # defining start for line interaction + start_line_id = r_packet.next_line_id + + # defining taus + tau_event = -np.log(np.random.random()) + tau_trace_line_combined = 0.0 + + # Calculating doppler factor + doppler_factor = get_doppler_factor( + r_packet.r, + r_packet.mu, + time_explosion, + enable_full_relativity, + ) + comov_nu = r_packet.nu * doppler_factor + + distance_continuum = tau_event / chi_continuum + cur_line_id = start_line_id # initializing varibale for Numba + # - do not remove + last_line_id = len(opacity_state.line_list_nu) - 1 + for cur_line_id in range(start_line_id, len(opacity_state.line_list_nu)): + # Going through the lines + nu_line = opacity_state.line_list_nu[cur_line_id] + + # Getting the tau for the next line + tau_trace_line = opacity_state.tau_sobolev[ + cur_line_id, r_packet.current_shell_id + ] + + # Adding it to the tau_trace_line_combined + tau_trace_line_combined += tau_trace_line + + # Calculating the distance until the current photons co-moving nu + # redshifts to the line frequency + is_last_line = cur_line_id == last_line_id + + distance_trace = calculate_distance_line( + r_packet, + comov_nu, + is_last_line, + nu_line, + time_explosion, + enable_full_relativity, + ) + + # calculating the tau continuum of how far the trace has progressed + tau_trace_continuum = chi_continuum * distance_trace + + # calculating the trace + tau_trace_combined = tau_trace_line_combined + tau_trace_continuum + + distance = min(distance_trace, distance_boundary, distance_continuum) + + if distance_trace != 0: + if distance == distance_boundary: + interaction_type = InteractionType.BOUNDARY # BOUNDARY + r_packet.next_line_id = cur_line_id + break + elif distance == distance_continuum: + if not continuum_processes_enabled: + interaction_type = InteractionType.ESCATTERING + else: + zrand = np.random.random() + if zrand < escat_prob: + interaction_type = InteractionType.ESCATTERING + else: + interaction_type = InteractionType.CONTINUUM_PROCESS + r_packet.next_line_id = cur_line_id + break + + # Updating the J_b_lu and E_dot_lu + # This means we are still looking for line interaction and have not + # been kicked out of the path by boundary or electron interaction + + update_line_estimators( + estimators, + r_packet, + cur_line_id, + distance_trace, + time_explosion, + enable_full_relativity, + ) + + if tau_trace_combined > tau_event and not disable_line_scattering: + interaction_type = InteractionType.LINE # Line + r_packet.last_interaction_in_nu = r_packet.nu + r_packet.last_line_interaction_in_id = cur_line_id + r_packet.last_line_interaction_shell_id = r_packet.current_shell_id + r_packet.next_line_id = cur_line_id + distance = distance_trace + break + + # Recalculating distance_continuum using tau_event - + # tau_trace_line_combined + # I don't think this needs to be updated + # since tau_event is already the result of the integral + # from the initial line + distance_continuum = (tau_event - tau_trace_line_combined) / ( + chi_continuum + ) + + else: # Executed when no break occurs in the for loop + # We are beyond the line list now and the only next thing is to see + # if we are interacting with the boundary or electron scattering + if cur_line_id == (len(opacity_state.line_list_nu) - 1): + # Treatment for last line + cur_line_id += 1 + if distance_continuum < distance_boundary: + distance = distance_continuum + if not continuum_processes_enabled: + interaction_type = InteractionType.ESCATTERING + else: + zrand = np.random.random() + if zrand < escat_prob: + interaction_type = InteractionType.ESCATTERING + else: + interaction_type = InteractionType.CONTINUUM_PROCESS + else: + distance = distance_boundary + interaction_type = InteractionType.BOUNDARY + + return distance, interaction_type, delta_shell + + +@njit(**njit_dict_no_parallel) +def move_r_packet( + r_packet, distance, time_explosion, numba_estimator, enable_full_relativity +): + """ + Move packet a distance and recalculate the new angle mu + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + r_packet objects + time_explosion : float + time since explosion in s + numba_estimator : tardis.transport.montecarlo.numba_interface.NumbaEstimator + Estimators object + distance : float + distance in cm + """ + doppler_factor = get_doppler_factor( + r_packet.r, r_packet.mu, time_explosion, enable_full_relativity + ) + + r = r_packet.r + if distance > 0.0: + new_r = np.sqrt( + r * r + distance * distance + 2.0 * r * distance * r_packet.mu + ) + r_packet.mu = (r_packet.mu * r + distance) / new_r + r_packet.r = new_r + + comov_nu = r_packet.nu * doppler_factor + comov_energy = r_packet.energy * doppler_factor + + # Account for length contraction + if enable_full_relativity: + distance *= doppler_factor + + update_base_estimators( + r_packet, distance, numba_estimator, comov_nu, comov_energy + ) + + +@njit(**njit_dict_no_parallel) +def move_packet_across_shell_boundary(packet, delta_shell, no_of_shells): + """ + Move packet across shell boundary - realizing if we are still in the simulation or have + moved out through the inner boundary or outer boundary and updating packet + status. + + Parameters + ---------- + distance : float + distance to move to shell boundary + + delta_shell : int + is +1 if moving outward or -1 if moving inward + + no_of_shells : int + number of shells in TARDIS simulation + """ + next_shell_id = packet.current_shell_id + delta_shell + + if next_shell_id >= no_of_shells: + packet.status = PacketStatus.EMITTED + elif next_shell_id < 0: + packet.status = PacketStatus.REABSORBED + else: + packet.current_shell_id = next_shell_id diff --git a/tardis/transport/montecarlo/single_packet_loop.py b/tardis/transport/montecarlo/single_packet_loop.py new file mode 100644 index 00000000000..e695ae5dbbc --- /dev/null +++ b/tardis/transport/montecarlo/single_packet_loop.py @@ -0,0 +1,314 @@ +from numba import njit + +from tardis import constants as const +from tardis.opacities.opacities import ( + chi_continuum_calculator, + chi_electron_calculator, +) +from tardis.transport.frame_transformations import ( + get_doppler_factor, + get_inverse_doppler_factor, +) +from tardis.transport.montecarlo.estimators.radfield_estimator_calcs import ( + update_bound_free_estimators, +) +from tardis.transport.montecarlo.interaction import ( + continuum_event, + line_scatter, + thomson_scatter, +) +from tardis.transport.montecarlo.r_packet import ( + InteractionType, + PacketStatus, +) +from tardis.transport.montecarlo.vpacket import trace_vpacket_volley +from tardis.transport.frame_transformations import ( + get_doppler_factor, + get_inverse_doppler_factor, +) +from tardis.transport.montecarlo.r_packet_transport import ( + move_packet_across_shell_boundary, + move_r_packet, + trace_packet, +) + +C_SPEED_OF_LIGHT = const.c.to("cm/s").value + + +@njit +def single_packet_loop( + r_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + estimators, + vpacket_collection, + rpacket_tracker, + montecarlo_configuration, +): + """ + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + numba_radial_1d_geometry : tardis.transport.montecarlo.numba_interface.NumbaRadial1DGeometry + time_explosion : float + opacity_state : tardis.transport.montecarlo.numba_interface.OpacityState + estimators : tardis.transport.montecarlo.numba_interface.Estimators + vpacket_collection : tardis.transport.montecarlo.numba_interface.VPacketCollection + rpacket_collection : tardis.transport.montecarlo.numba_interface.RPacketCollection + + Returns + ------- + None + This function does not return anything but changes the r_packet object + and if virtual packets are requested - also updates the vpacket_collection + """ + line_interaction_type = montecarlo_configuration.LINE_INTERACTION_TYPE + + if montecarlo_configuration.ENABLE_FULL_RELATIVITY: + set_packet_props_full_relativity(r_packet, time_explosion) + else: + set_packet_props_partial_relativity(r_packet, time_explosion) + r_packet.initialize_line_id( + opacity_state, + time_explosion, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + + trace_vpacket_volley( + r_packet, + vpacket_collection, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + montecarlo_configuration.VPACKET_TAU_RUSSIAN, + montecarlo_configuration.SURVIVAL_PROBABILITY, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + ) + + if montecarlo_configuration.ENABLE_RPACKET_TRACKING: + rpacket_tracker.track(r_packet) + + # this part of the code is temporary and will be better incorporated + while r_packet.status == PacketStatus.IN_PROCESS: + # Compute continuum quantities + # trace packet (takes opacities) + doppler_factor = get_doppler_factor( + r_packet.r, + r_packet.mu, + time_explosion, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + + comov_nu = r_packet.nu * doppler_factor + chi_e = chi_electron_calculator( + opacity_state, comov_nu, r_packet.current_shell_id + ) + if montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED: + ( + chi_bf_tot, + chi_bf_contributions, + current_continua, + x_sect_bfs, + chi_ff, + ) = chi_continuum_calculator( + opacity_state, comov_nu, r_packet.current_shell_id + ) + chi_continuum = chi_e + chi_bf_tot + chi_ff + + escat_prob = chi_e / chi_continuum # probability of e-scatter + if montecarlo_configuration.ENABLE_FULL_RELATIVITY: + chi_continuum *= doppler_factor + distance, interaction_type, delta_shell = trace_packet( + r_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + estimators, + chi_continuum, + escat_prob, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + montecarlo_configuration.DISABLE_LINE_SCATTERING, + ) + update_bound_free_estimators( + comov_nu, + r_packet.energy * doppler_factor, + r_packet.current_shell_id, + distance, + estimators, + opacity_state.t_electrons[r_packet.current_shell_id], + x_sect_bfs, + current_continua, + opacity_state.bf_threshold_list_nu, + ) + else: + escat_prob = 1.0 + chi_continuum = chi_e + if montecarlo_configuration.ENABLE_FULL_RELATIVITY: + chi_continuum *= doppler_factor + distance, interaction_type, delta_shell = trace_packet( + r_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + estimators, + chi_continuum, + escat_prob, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + montecarlo_configuration.DISABLE_LINE_SCATTERING, + ) + + # If continuum processes: update continuum estimators + + if interaction_type == InteractionType.BOUNDARY: + move_r_packet( + r_packet, + distance, + time_explosion, + estimators, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + move_packet_across_shell_boundary( + r_packet, delta_shell, len(numba_radial_1d_geometry.r_inner) + ) + + elif interaction_type == InteractionType.LINE: + r_packet.last_interaction_type = 2 + move_r_packet( + r_packet, + distance, + time_explosion, + estimators, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + line_scatter( + r_packet, + time_explosion, + line_interaction_type, + opacity_state, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + trace_vpacket_volley( + r_packet, + vpacket_collection, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + montecarlo_configuration.VPACKET_TAU_RUSSIAN, + montecarlo_configuration.SURVIVAL_PROBABILITY, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + ) + + elif interaction_type == InteractionType.ESCATTERING: + r_packet.last_interaction_type = 1 + + move_r_packet( + r_packet, + distance, + time_explosion, + estimators, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + thomson_scatter( + r_packet, + time_explosion, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + + trace_vpacket_volley( + r_packet, + vpacket_collection, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + montecarlo_configuration.VPACKET_TAU_RUSSIAN, + montecarlo_configuration.SURVIVAL_PROBABILITY, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + ) + elif ( + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED + and interaction_type == InteractionType.CONTINUUM_PROCESS + ): + r_packet.last_interaction_type = InteractionType.CONTINUUM_PROCESS + move_r_packet( + r_packet, + distance, + time_explosion, + estimators, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + continuum_event( + r_packet, + time_explosion, + opacity_state, + chi_bf_tot, + chi_ff, + chi_bf_contributions, + current_continua, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + ) + + trace_vpacket_volley( + r_packet, + vpacket_collection, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + montecarlo_configuration.ENABLE_FULL_RELATIVITY, + montecarlo_configuration.VPACKET_TAU_RUSSIAN, + montecarlo_configuration.SURVIVAL_PROBABILITY, + montecarlo_configuration.CONTINUUM_PROCESSES_ENABLED, + ) + else: + pass + if montecarlo_configuration.ENABLE_RPACKET_TRACKING: + rpacket_tracker.track(r_packet) + + +@njit +def set_packet_props_partial_relativity(r_packet, time_explosion): + """Sets properties of the packets given partial relativity + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + """ + inverse_doppler_factor = get_inverse_doppler_factor( + r_packet.r, + r_packet.mu, + time_explosion, + enable_full_relativity=False, + ) + r_packet.nu *= inverse_doppler_factor + r_packet.energy *= inverse_doppler_factor + + +@njit +def set_packet_props_full_relativity(r_packet, time_explosion): + """Sets properties of the packets given full relativity + + Parameters + ---------- + r_packet : tardis.transport.montecarlo.r_packet.RPacket + time_explosion : float + """ + beta = (r_packet.r / time_explosion) / C_SPEED_OF_LIGHT + + inverse_doppler_factor = get_inverse_doppler_factor( + r_packet.r, + r_packet.mu, + time_explosion, + enable_full_relativity=True, + ) + + r_packet.nu *= inverse_doppler_factor + r_packet.energy *= inverse_doppler_factor + r_packet.mu = (r_packet.mu + beta) / (1 + beta * r_packet.mu) diff --git a/tardis/montecarlo/tests/__init__.py b/tardis/transport/montecarlo/tests/__init__.py similarity index 100% rename from tardis/montecarlo/tests/__init__.py rename to tardis/transport/montecarlo/tests/__init__.py diff --git a/tardis/montecarlo/montecarlo_numba/tests/conftest.py b/tardis/transport/montecarlo/tests/conftest.py similarity index 51% rename from tardis/montecarlo/montecarlo_numba/tests/conftest.py rename to tardis/transport/montecarlo/tests/conftest.py index 53cf34788d7..b67fc70b1f4 100644 --- a/tardis/montecarlo/montecarlo_numba/tests/conftest.py +++ b/tardis/transport/montecarlo/tests/conftest.py @@ -3,16 +3,20 @@ import pytest import numpy as np from numba import njit +from tardis.opacities.opacity_state import opacity_state_initialize +from tardis.transport.montecarlo.packet_collections import ( + VPacketCollection, +) from tardis.simulation import Simulation -from tardis.montecarlo.montecarlo_numba import RPacket, PacketCollection +from tardis.transport.montecarlo import RPacket +from tardis.transport.montecarlo.estimators.radfield_mc_estimators import ( + RadiationFieldMCEstimators, +) -from tardis.montecarlo.montecarlo_numba.numba_interface import ( - numba_plasma_initialize, - NumbaModel, - Estimators, - VPacketCollection, +from tardis.transport.montecarlo.numba_interface import ( + opacity_state_initialize, ) @@ -24,55 +28,51 @@ def nb_simulation_verysimple(config_verysimple, atomic_dataset): return sim -@pytest.fixture() -def verysimple_collection(nb_simulation_verysimple): - runner = nb_simulation_verysimple.runner - return PacketCollection( - runner.input_r, - runner.input_nu, - runner.input_mu, - runner.input_energy, - runner._output_nu, - runner._output_energy, +@pytest.fixture(scope="package") +def verysimple_opacity_state(nb_simulation_verysimple): + return opacity_state_initialize( + nb_simulation_verysimple.plasma, + line_interaction_type="macroatom", + disable_line_scattering=False, + continuum_processes_enabled=False, ) @pytest.fixture(scope="package") -def verysimple_numba_plasma(nb_simulation_verysimple): - return numba_plasma_initialize( - nb_simulation_verysimple.plasma, line_interaction_type="macroatom" - ) +def verysimple_numba_radial_1d_geometry(nb_simulation_verysimple): + return nb_simulation_verysimple.simulation_state.geometry.to_numba() @pytest.fixture(scope="package") -def verysimple_numba_model(nb_simulation_verysimple): - runner = nb_simulation_verysimple.runner - model = nb_simulation_verysimple.model - return NumbaModel( - runner.r_inner_cgs, - runner.r_outer_cgs, - model.time_explosion.to("s").value, - ) +def verysimple_time_explosion(nb_simulation_verysimple): + model = nb_simulation_verysimple.simulation_state + return model.time_explosion.cgs.value @pytest.fixture(scope="package") def verysimple_estimators(nb_simulation_verysimple): - runner = nb_simulation_verysimple.runner - return Estimators( - runner.j_estimator, - runner.nu_bar_estimator, - runner.j_blue_estimator, - runner.Edotlu_estimator, + transport = nb_simulation_verysimple.transport + + return RadiationFieldMCEstimators( + transport.j_estimator, + transport.nu_bar_estimator, + transport.j_blue_estimator, + transport.Edotlu_estimator, + transport.photo_ion_estimator, + transport.stim_recomb_estimator, + transport.bf_heating_estimator, + transport.stim_recomb_cooling_estimator, + transport.photo_ion_estimator_statistics, ) @pytest.fixture(scope="package") def verysimple_vpacket_collection(nb_simulation_verysimple): spectrum_frequency = ( - nb_simulation_verysimple.runner.spectrum_frequency.value + nb_simulation_verysimple.transport.spectrum_frequency.value ) return VPacketCollection( - rpacket_index=0, + source_rpacket_index=0, spectrum_frequency=spectrum_frequency, number_of_vpackets=0, v_packet_spawn_start_frequency=0, @@ -84,10 +84,10 @@ def verysimple_vpacket_collection(nb_simulation_verysimple): @pytest.fixture(scope="package") def verysimple_3vpacket_collection(nb_simulation_verysimple): spectrum_frequency = ( - nb_simulation_verysimple.runner.spectrum_frequency.value + nb_simulation_verysimple.transport.spectrum_frequency.value ) return VPacketCollection( - rpacket_index=0, + source_rpacket_index=0, spectrum_frequency=spectrum_frequency, number_of_vpackets=3, v_packet_spawn_start_frequency=0, @@ -98,24 +98,16 @@ def verysimple_3vpacket_collection(nb_simulation_verysimple): @pytest.fixture(scope="package") def verysimple_packet_collection(nb_simulation_verysimple): - runner = nb_simulation_verysimple.runner - return PacketCollection( - runner.input_r, - runner.input_nu, - runner.input_mu, - runner.input_energy, - runner._output_nu, - runner._output_energy, - ) + return nb_simulation_verysimple.transport.transport_state.packet_collection @pytest.fixture(scope="function") def packet(verysimple_packet_collection): return RPacket( r=7.5e14, - nu=verysimple_packet_collection.packets_input_nu[0], - mu=verysimple_packet_collection.packets_input_mu[0], - energy=verysimple_packet_collection.packets_input_energy[0], + nu=verysimple_packet_collection.initial_nus[0], + mu=verysimple_packet_collection.initial_mus[0], + energy=verysimple_packet_collection.initial_energies[0], seed=1963, index=0, ) diff --git a/tardis/montecarlo/tests/data/continuum_compare_data.hdf b/tardis/transport/montecarlo/tests/data/continuum_compare_data.hdf similarity index 100% rename from tardis/montecarlo/tests/data/continuum_compare_data.hdf rename to tardis/transport/montecarlo/tests/data/continuum_compare_data.hdf diff --git a/tardis/transport/montecarlo/tests/test_base.py b/tardis/transport/montecarlo/tests/test_base.py new file mode 100644 index 00000000000..9c7ec3bffbe --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_base.py @@ -0,0 +1,82 @@ +import os +import pandas as pd +import numpy as np +import pytest +from astropy import units as u +from numpy.testing import assert_almost_equal +from pathlib import Path + +### +# Save and Load +### + + +@pytest.fixture(scope="module", autouse=True) +def to_hdf_buffer(hdf_file_path, simulation_verysimple_vpacket_tracking): + simulation_verysimple_vpacket_tracking.transport.to_hdf( + hdf_file_path, name="transport", overwrite=True + ) + simulation_verysimple_vpacket_tracking.transport.transport_state.to_hdf( + hdf_file_path, name="transport_state", overwrite=True + ) + + +transport_properties = [None] + + +@pytest.mark.xfail(reason="No HDF properties being written currently") +@pytest.mark.parametrize("attr", transport_properties) +def test_hdf_transport( + hdf_file_path, simulation_verysimple_vpacket_tracking, attr +): + actual = getattr(simulation_verysimple_vpacket_tracking.transport, attr) + if hasattr(actual, "cgs"): + actual = actual.cgs.value + path = f"transport/{attr}" + expected = pd.read_hdf(hdf_file_path, path) + assert_almost_equal(actual, expected.values) + + +transport_state_properties = [ + "output_nu", + "output_energy", + "nu_bar_estimator", + "j_estimator", + "montecarlo_virtual_luminosity", + "packet_luminosity", + # These are nested properties that should be tested differently + # "spectrum", + # "spectrum_virtual", + # "spectrum_reabsorbed", + # This is a scalar and should be tested differently + # "time_of_simulation", + "emitted_packet_mask", + "last_interaction_type", + "last_interaction_in_nu", + "last_line_interaction_out_id", + "last_line_interaction_in_id", + "last_line_interaction_shell_id", + "virt_packet_nus", + "virt_packet_energies", + "virt_packet_initial_rs", + "virt_packet_initial_mus", + "virt_packet_last_interaction_in_nu", + "virt_packet_last_interaction_type", + "virt_packet_last_line_interaction_in_id", + "virt_packet_last_line_interaction_out_id", + "virt_packet_last_line_interaction_shell_id", +] + + +@pytest.mark.parametrize("attr", transport_state_properties) +def test_hdf_transport_state( + hdf_file_path, simulation_verysimple_vpacket_tracking, attr +): + actual = getattr( + simulation_verysimple_vpacket_tracking.transport.transport_state, attr + ) + if hasattr(actual, "cgs"): + actual = actual.cgs.value + path = f"transport_state/{attr}" + expected = pd.read_hdf(hdf_file_path, path) + assert_almost_equal(actual, expected.values) diff --git a/tardis/transport/montecarlo/tests/test_continuum.py b/tardis/transport/montecarlo/tests/test_continuum.py new file mode 100644 index 00000000000..d11b394b2cf --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_continuum.py @@ -0,0 +1,39 @@ +from copy import deepcopy + +import numpy.testing as npt +import pytest + +from tardis.simulation import Simulation + + +def test_montecarlo_continuum( + continuum_config, + regression_data, + nlte_atomic_dataset, +): + nlte_atomic_dataset = deepcopy(nlte_atomic_dataset) + continuum_simulation = Simulation.from_config( + continuum_config, + atom_data=nlte_atomic_dataset, + virtual_packet_logging=False, + ) + # continuum_simulation.run_convergence() + + continuum_simulation.run_final() + + expected_hdf_store = regression_data.sync_hdf_store(continuum_simulation) + + expected_nu = expected_hdf_store[ + "/simulation/transport/transport_state/output_nu" + ] + expected_energy = expected_hdf_store[ + "/simulation/transport/transport_state/output_energy" + ] + expected_hdf_store.close() + + transport_state = continuum_simulation.transport.transport_state + actual_energy = transport_state.packet_collection.output_energies + actual_nu = transport_state.packet_collection.output_nus + + npt.assert_allclose(actual_energy, expected_energy, rtol=1e-13) + npt.assert_allclose(actual_nu, expected_nu, rtol=1e-13) diff --git a/tardis/transport/montecarlo/tests/test_cuda_formal_integral.py b/tardis/transport/montecarlo/tests/test_cuda_formal_integral.py new file mode 100644 index 00000000000..831d945bbcd --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_cuda_formal_integral.py @@ -0,0 +1,403 @@ +import numpy as np +import numpy.testing as ntest +import pytest +from numba import cuda + +import tardis.transport.montecarlo.formal_integral as formal_integral_numba +import tardis.transport.montecarlo.formal_integral_cuda as formal_integral_cuda +from tardis import constants as c +from tardis.model.geometry.radial1d import NumbaRadial1DGeometry +from tardis.transport.montecarlo.formal_integral import ( + FormalIntegrator, + NumbaFormalIntegrator, +) + +from tardis.transport.montecarlo.base import MonteCarloTransportSolver + + +# Test cases must also take into account use of a GPU to run. If there is no GPU then the test cases will fail. +GPUs_available = cuda.is_available() + + +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize( + ["nu", "temperature"], + [ + (1e14, 1e4), + (0, 1), + (1, 1), + ], +) +def test_intensity_black_body_cuda(nu, temperature): + """ + Initializes the test of the cuda version + against the numba implementation of the + intensity_black_body to 15 decimals. This + is done as both results have 15 digits of precision. + """ + actual = np.zeros(3) + black_body_caller[1, 3](nu, temperature, actual) + + expected = formal_integral_numba.intensity_black_body(nu, temperature) + + ntest.assert_allclose(actual, expected, rtol=1e-14) + + +@cuda.jit +def black_body_caller(nu, temperature, actual): + """ + This calls the CUDA function and fills out + the array + """ + x = cuda.grid(1) + actual[x] = formal_integral_cuda.intensity_black_body_cuda(nu, temperature) + + +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize("N", (1e2, 1e3, 1e4, 1e5)) +def test_trapezoid_integration_cuda(N): + """ + Initializes the test of the cuda version + against the numba implementation of the + trapezoid_integration to 15 decimals. This + is done as both results have 15 digits of precision. + """ + actual = np.zeros(1) + + h = 1.0 + N = int(N) + np.random.seed(12) + data = np.random.random(N) + + expected = formal_integral_numba.trapezoid_integration(data, h) + trapezoid_integration_caller[1, 1](data, h, actual) + + # This is 1e-13, as more points are added to the integration + # there will be more floating point error due to the difference + # in how the trapezoid integration is called. + ntest.assert_allclose(actual[0], expected, rtol=1e-13) + + +@cuda.jit +def trapezoid_integration_caller(data, h, actual): + """ + This calls the CUDA function and fills out + the array + """ + x = cuda.grid(1) + actual[x] = formal_integral_cuda.trapezoid_integration_cuda(data, h) + + +TESTDATA_model = [ + { + "r": np.linspace(1, 2, 3, dtype=np.float64), + }, + { + "r": np.linspace(0, 1, 3), + }, + # {"r": np.linspace(1, 2, 10, dtype=np.float64)}, +] + + +@pytest.fixture(scope="function", params=TESTDATA_model) +def formal_integral_geometry(request): + """ + This gets the Numba model to be used in later tests + """ + r = request.param["r"] + geometry = NumbaRadial1DGeometry( + r[:-1], + r[1:], + r[:-1] * c.c.cgs.value, + r[1:] * c.c.cgs.value, + ) + return geometry + + +@pytest.fixture(scope="function") +def time_explosion(): + """ + This gets the time_explosion to be used in later tests + """ + # previously used model value that passes tests + # time taken for a photon to move 1 cm + return 1 / c.c.cgs.value + + +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize(["p", "p_loc"], [(0.0, 0), (0.5, 1), (1.0, 2)]) +def test_calculate_z_cuda(formal_integral_geometry, time_explosion, p, p_loc): + """ + Initializes the test of the cuda version + against the numba implementation of the + calculate_z to 15 decimals. This is done as + both results have 15 digits of precision. + """ + actual = np.zeros(3) + inv_t = 1.0 / time_explosion + size = len(formal_integral_geometry.r_outer) + r_outer = formal_integral_geometry.r_outer + for r in r_outer: + calculate_z_caller[1, 3](r, p, inv_t, actual) + expected = formal_integral_numba.calculate_z(r, p, inv_t) + + ntest.assert_allclose(actual[p_loc], expected, rtol=1e-14) + + +@cuda.jit +def calculate_z_caller(r, p, inv_t, actual): + """ + This calls the CUDA function and fills out + the array + """ + x = cuda.grid(1) + actual[x] = formal_integral_cuda.calculate_z_cuda(r, p, inv_t) + + +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize( + ["p", "p_loc"], + [(1e-5, 0), (1e-3, 1), (0.1, 2), (0.5, 3), (0.99, 4), (1, 5)], +) +def test_populate_z(formal_integral_geometry, time_explosion, p, p_loc): + """ + Initializes the test of the cuda version + against the numba implementation of the + populate_z + """ + size = len(formal_integral_geometry.r_inner) + oz = np.zeros(size * 2) + expected_oz = np.zeros(size * 2) + oshell_id = np.zeros_like(oz, dtype=np.int64) + expected_oshell_id = np.zeros_like(oz, dtype=np.int64) + + expected = formal_integral_numba.populate_z( + formal_integral_geometry, + time_explosion, + p, + expected_oz, + expected_oshell_id, + ) + + actual = np.zeros(6) + populate_z_caller[1, 6]( + formal_integral_geometry.r_inner, + formal_integral_geometry.r_outer, + time_explosion, + p, + oz, + oshell_id, + actual, + ) + + ntest.assert_equal(actual[p_loc], expected) + ntest.assert_equal(oshell_id, expected_oshell_id) + ntest.assert_allclose(oz, expected_oz, atol=1e-4) + + +@cuda.jit +def populate_z_caller( + r_inner, r_outer, time_explosion, p, oz, oshell_id, actual +): + """ + This calls the CUDA function and fills out + the array + """ + x = cuda.grid(1) + actual[x] = formal_integral_cuda.populate_z_cuda( + r_inner, r_outer, time_explosion, p, oz, oshell_id + ) + + +@pytest.mark.parametrize( + "N", + [ + 100, + 1000, + 10000, + ], +) +def test_calculate_p_values(N): + """ + Initializes the test of the cuda version + against the numba implementation of the + calculate_p_values to 15 decimals. This is done as + both results have 15 digits of precision. + """ + r = 1.0 + + expected = formal_integral_numba.calculate_p_values(r, N) + + actual = np.zeros_like(expected, dtype=np.float64) + actual[::] = formal_integral_cuda.calculate_p_values(r, N) + + ntest.assert_allclose(actual, expected, rtol=1e-14) + + +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize("nu_insert", np.linspace(3e12, 3e16, 10)) +def test_line_search_cuda(nu_insert, verysimple_opacity_state): + """ + Initializes the test of the cuda version + against the numba implementation of the + line_search + """ + actual = np.zeros(1) + expected = np.zeros(1) + line_list_nu = verysimple_opacity_state.line_list_nu + + expected[0] = formal_integral_numba.line_search( + line_list_nu, nu_insert, len(line_list_nu) + ) + + line_search_cuda_caller[1, 1](line_list_nu, nu_insert, actual) + + ntest.assert_equal(actual, expected) + + +@cuda.jit +def line_search_cuda_caller(line_list_nu, nu_insert, actual): + """ + This calls the CUDA function and fills out + the array + """ + x = cuda.grid(1) + actual[x] = formal_integral_cuda.line_search_cuda( + line_list_nu, nu_insert, len(line_list_nu) + ) + + +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize( + "nu_insert", [*np.linspace(3e12, 3e16, 10), 288786721666522.1] +) +def test_reverse_binary_search(nu_insert, verysimple_opacity_state): + """ + Initializes the test of the cuda version + against the numba implementation of the + reverse_binary_search. The one extra input not included + in np.linspace a low edge case for testing. + """ + actual = np.zeros(1) + expected = np.zeros(1) + line_list_nu = verysimple_opacity_state.line_list_nu + + imin = 0 + imax = len(line_list_nu) - 1 + + expected[0] = formal_integral_numba.reverse_binary_search( + line_list_nu, nu_insert, imin, imax + ) + reverse_binary_search_cuda_caller[1, 1]( + line_list_nu, nu_insert, imin, imax, actual + ) + + ntest.assert_equal(actual, expected) + + +@cuda.jit +def reverse_binary_search_cuda_caller( + line_list_nu, nu_insert, imin, imax, actual +): + """ + This calls the CUDA function and fills out + the array + """ + x = cuda.grid(1) + actual[x] = formal_integral_cuda.reverse_binary_search_cuda( + line_list_nu, nu_insert, imin, imax + ) + + +# no_of_packets and iterations match what is used by config_verysimple +@pytest.mark.skipif( + not GPUs_available, reason="No GPU is available to test CUDA function" +) +@pytest.mark.parametrize(["no_of_packets", "iterations"], [(200000, 5)]) +def test_full_formal_integral( + no_of_packets, iterations, config_verysimple, simulation_verysimple +): + """ + This function initializes both the cuda and numba formal_integrator, + and the runs them and compares results to the 15th decimal place. + This is done as both results have 15 digits of precision. + """ + sim = simulation_verysimple + + formal_integrator_numba = FormalIntegrator( + sim.simulation_state, sim.plasma, sim.transport + ) + + formal_integrator_cuda = FormalIntegrator( + sim.simulation_state, sim.plasma, sim.transport + ) + + # The function calculate_spectrum sets this property, but in order to test the CUDA. + # version it is done manually, as well as to speed up the test. + formal_integrator_numba.interpolate_shells = max( + 2 * formal_integrator_numba.simulation_state.no_of_shells, 80 + ) + + formal_integrator_cuda.interpolate_shells = max( + 2 * formal_integrator_cuda.simulation_state.no_of_shells, 80 + ) + + res_numba = formal_integrator_numba.make_source_function() + att_S_ul_numba = res_numba[0].flatten(order="F") + Jred_lu_numba = res_numba[1].values.flatten(order="F") + Jblue_lu_numba = res_numba[2].flatten(order="F") + + res_cuda = formal_integrator_cuda.make_source_function() + att_S_ul_cuda = res_cuda[0].flatten(order="F") + Jred_lu_cuda = res_cuda[1].values.flatten(order="F") + Jblue_lu_cuda = res_cuda[2].flatten(order="F") + + formal_integrator_numba.generate_numba_objects() + # This is to force the for formal_integrator_numba to use the numba version + # as it is automatically set to the CUDA version when there is a GPU available + formal_integrator_numba.integrator = NumbaFormalIntegrator( + formal_integrator_numba.numba_radial_1d_geometry, + sim.simulation_state.time_explosion.cgs.value, + formal_integrator_numba.opacity_state, + formal_integrator_numba.points, + ) + + formal_integrator_cuda.generate_numba_objects() + + L_cuda = formal_integrator_cuda.integrator.formal_integral( + formal_integrator_cuda.simulation_state.t_inner, + sim.transport.transport_state.spectrum.frequency, + sim.transport.transport_state.spectrum.frequency.shape[0], + att_S_ul_cuda, + Jred_lu_cuda, + Jblue_lu_cuda, + formal_integrator_cuda.transport.tau_sobolevs_integ, + formal_integrator_cuda.transport.electron_densities_integ, + formal_integrator_cuda.points, + )[0] + + L_numba = formal_integrator_numba.integrator.formal_integral( + formal_integrator_numba.simulation_state.t_inner, + sim.transport.transport_state.spectrum.frequency, + sim.transport.transport_state.spectrum.frequency.shape[0], + att_S_ul_numba, + Jred_lu_numba, + Jblue_lu_numba, + formal_integrator_numba.transport.tau_sobolevs_integ, + formal_integrator_numba.transport.electron_densities_integ, + formal_integrator_numba.points, + )[0] + + ntest.assert_allclose(L_cuda, L_numba, rtol=1e-14) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_interaction.py b/tardis/transport/montecarlo/tests/test_interaction.py similarity index 65% rename from tardis/montecarlo/montecarlo_numba/tests/test_interaction.py rename to tardis/transport/montecarlo/tests/test_interaction.py index bcdaa8f1736..2c6b31ee955 100644 --- a/tardis/montecarlo/montecarlo_numba/tests/test_interaction.py +++ b/tardis/transport/montecarlo/tests/test_interaction.py @@ -1,19 +1,19 @@ import pytest import numpy.testing as npt import numpy as np -import tardis.montecarlo.montecarlo_numba.interaction as interaction -from tardis.montecarlo.montecarlo_numba.numba_interface import ( +import tardis.transport.montecarlo.interaction as interaction +from tardis.transport.montecarlo.numba_interface import ( LineInteractionType, ) -def test_thomson_scatter(packet, verysimple_numba_model): +def test_thomson_scatter(packet, verysimple_time_explosion): init_mu = packet.mu init_nu = packet.nu init_energy = packet.energy - time_explosion = verysimple_numba_model.time_explosion + time_explosion = verysimple_time_explosion - interaction.thomson_scatter(packet, time_explosion) + interaction.thomson_scatter(packet, time_explosion, False) assert np.abs(packet.mu - init_mu) > 1e-7 assert np.abs(packet.nu - init_nu) > 1e-7 @@ -31,17 +31,25 @@ def test_thomson_scatter(packet, verysimple_numba_model): def test_line_scatter( line_interaction_type, packet, - verysimple_numba_model, - verysimple_numba_plasma, + verysimple_time_explosion, + verysimple_opacity_state, ): init_mu = packet.mu init_nu = packet.nu init_energy = packet.energy - packet.initialize_line_id(verysimple_numba_plasma, verysimple_numba_model) - time_explosion = verysimple_numba_model.time_explosion + full_relativity = False + packet.initialize_line_id( + verysimple_opacity_state, verysimple_time_explosion, full_relativity + ) + time_explosion = verysimple_time_explosion interaction.line_scatter( - packet, time_explosion, line_interaction_type, verysimple_numba_plasma + packet, + time_explosion, + line_interaction_type, + verysimple_opacity_state, + continuum_processes_enabled=False, + enable_full_relativity=False, ) assert np.abs(packet.mu - init_mu) > 1e-7 @@ -81,20 +89,29 @@ def test_line_scatter( ) def test_line_emission( packet, - verysimple_numba_model, - verysimple_numba_plasma, + verysimple_time_explosion, + verysimple_opacity_state, test_packet, expected, ): emission_line_id = test_packet["emission_line_id"] packet.mu = test_packet["mu"] packet.energy = test_packet["energy"] - packet.initialize_line_id(verysimple_numba_plasma, verysimple_numba_model) + full_relativity = False + packet.initialize_line_id( + verysimple_opacity_state, + verysimple_time_explosion, + full_relativity, + ) - time_explosion = verysimple_numba_model.time_explosion + time_explosion = verysimple_time_explosion interaction.line_emission( - packet, emission_line_id, time_explosion, verysimple_numba_plasma + packet, + emission_line_id, + time_explosion, + verysimple_opacity_state, + full_relativity, ) assert packet.next_line_id == emission_line_id + 1 diff --git a/tardis/transport/montecarlo/tests/test_macro_atom.py b/tardis/transport/montecarlo/tests/test_macro_atom.py new file mode 100644 index 00000000000..5ef26f16b49 --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_macro_atom.py @@ -0,0 +1,34 @@ +import pytest +import tardis.transport.montecarlo.macro_atom as macro_atom +import numpy as np + + +@pytest.mark.parametrize( + ["seed", "expected"], + [(1963, 10015), (1, 9993), (2111963, 17296), (10000, 9993)], +) +def test_macro_atom( + static_packet, + verysimple_opacity_state, + verysimple_time_explosion, + set_seed_fixture, + seed, + expected, +): + set_seed_fixture(seed) + full_relativity = False + static_packet.initialize_line_id( + verysimple_opacity_state, + verysimple_time_explosion, + full_relativity, + ) + activation_level_id = verysimple_opacity_state.line2macro_level_upper[ + static_packet.next_line_id + ] + result, transition_type = macro_atom.macro_atom( + activation_level_id, + static_packet.current_shell_id, + verysimple_opacity_state, + ) + assert result == expected + assert transition_type == -1 # line transition diff --git a/tardis/montecarlo/tests/test_montecarlo.py b/tardis/transport/montecarlo/tests/test_montecarlo.py similarity index 71% rename from tardis/montecarlo/tests/test_montecarlo.py rename to tardis/transport/montecarlo/tests/test_montecarlo.py index 195344880d6..edf747124bf 100644 --- a/tardis/montecarlo/tests/test_montecarlo.py +++ b/tardis/transport/montecarlo/tests/test_montecarlo.py @@ -1,82 +1,37 @@ -""" -Unit tests for methods in `tardis/montecarlo/src/cmontecarlo.c`. -* `ctypes` library is used to wrap C methods and expose them to python. - - -Probable Reasons for Failing Tests: ------------------------------------ - -1. Change made in C struct declarations: - - Reflect the changes done in C structs, into Python counterparts. - - Check **tardis/montecarlo/struct.py**. - -2. Return type of any method changed: - - Modify the `restype` parameter in the test method here. - - For example: - ``` - clib.rpacket_doppler_factor.restype = c_double - ``` - -3. Underlying logic modified: - - Check whether the changes made in C method are logically correct. - - If the changes made were correct and necessary, update the corresponding - test case. - - -General Test Design Procedure: ------------------------------- - -Please follow this design procedure while adding a new test: - -1. Parametrization as per desire of code coverage. - - C tests have different flows controlled by conditional statements. - Parameters checked in conditions can be provided in different testcases. - - Keep consistency with variable names as (in order): - - `packet_params` - - `model_params` - - `expected_params` (`expected` if only one value to be asserted.) - - Suggested variable names can be compromised if readability of the test - increases. - -2. Test Method body: - - Keep name as `test_` + `(name of C method)`. - - Refer to method `test_rpacket_doppler_factor` below for description. -""" - - import os -import pytest + import numpy as np import pandas as pd -import tardis.montecarlo.montecarlo_numba.formal_integral as formal_integral -import tardis.montecarlo.montecarlo_numba.r_packet as r_packet -import tardis.montecarlo.montecarlo_numba.r_packet_transport as r_packet_transport -import tardis.montecarlo.montecarlo_numba.utils as utils -import tardis.montecarlo.montecarlo_configuration as mc -from tardis import constants as const -from tardis.montecarlo.montecarlo_numba.numba_interface import Estimators -from tardis.montecarlo.montecarlo_numba.numba_interface import RPacketTracker - +import pytest -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( - get_doppler_factor, - angle_aberration_LF_to_CMF, +import tardis.transport.montecarlo.formal_integral as formal_integral +import tardis.transport.montecarlo.r_packet as r_packet +import tardis.transport.montecarlo.utils as utils +import tardis.transport.montecarlo.r_packet_transport as r_packet_transport +from tardis import constants as const +from tardis.transport.montecarlo.estimators.radfield_mc_estimators import ( + RadiationFieldMCEstimators, +) +from tardis.transport.montecarlo.packet_trackers import RPacketTracker +from tardis.transport.frame_transformations import ( angle_aberration_CMF_to_LF, + angle_aberration_LF_to_CMF, + get_doppler_factor, ) - C_SPEED_OF_LIGHT = const.c.to("cm/s").value pytestmark = pytest.mark.skip(reason="Port from C to numba") from numpy.testing import ( - assert_almost_equal, assert_allclose, + assert_almost_equal, ) from tardis import __path__ as path + @pytest.fixture(scope="module") def continuum_compare_data_fname(): fname = "continuum_compare_data.hdf" @@ -108,6 +63,7 @@ def ff_emissivity(t_electron): return ff_emissivity + @pytest.fixture(scope="module") def ion_edges(): return [ @@ -128,6 +84,7 @@ def ion_edges(): }, ] + """ Important Tests: ---------------- @@ -152,7 +109,7 @@ def ion_edges(): 0.0, 0, 3, - {"result": 0}, # This one might need to check for a bounds error + {"result": 0}, # This one might need to check for a bounds error ), ], ) @@ -216,7 +173,7 @@ def test_line_search(nu, nu_insert, number_of_lines, expected_params): 8.0, 0, 3, - {"result": 0}, # this one too + {"result": 0}, # this one too ), ( [2.0, 4.0, 6.0, 7.0], @@ -230,131 +187,11 @@ def test_line_search(nu, nu_insert, number_of_lines, expected_params): def test_binary_search(x, x_insert, imin, imax, expected_params): obtained_result = 0 - obtained_result = formal_integral.binary_search( - x, x_insert, imin, imax - ) + obtained_result = formal_integral.binary_search(x, x_insert, imin, imax) assert obtained_result == expected_params["result"] -@pytest.mark.parametrize( - ["mu", "r", "inv_t_exp", "expected"], - [ - (0.3, 7.5e14, 1 / 5.2e7, 0.9998556693818854), - (-0.3, 0, 1 / 2.6e7, 1.0), - (0, 1, 1 / 2.6e7, 1.0), - ], -) -def test_get_doppler_factor(mu, r, inv_t_exp, expected): - # Set the params from test cases here - # TODO: add relativity tests - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - - obtained = get_doppler_factor(r, mu, time_explosion) - - # Perform required assertions - assert_almost_equal(obtained, expected) - - -@pytest.mark.parametrize(["mu", "r", "inv_t_exp"], [(-0.3, 5, 1e10)]) -def test_unphysical_doppler_factor(mu, r, inv_t_exp): - # Set the params from test cases here - # TODO: add relativity tests - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - with pytest.raises(r_packet.SuperluminalError): - obtained = get_doppler_factor(r, mu, time_explosion) - - -@pytest.mark.parametrize( - ["mu", "r", "inv_t_exp", "expected"], - [ - (0.3, 7.5e14, 1 / 5.2e7, 1 / 0.9998556693818854), - (-0.3, 0, 1 / 2.6e7, 1.0), - (0, 1, 1 / 2.6e7, 1.0), - ], -) -def test_get_inverse_doppler_factor(mu, r, inv_t_exp, expected): - # Set the params from test cases here - # TODO: add relativity tests - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - - obtained = r_packet.get_inverse_doppler_factor(r, mu, time_explosion) - - # Perform required assertions - assert_almost_equal(obtained, expected) - - -@pytest.mark.parametrize(["mu", "r", "inv_t_exp"], [(-0.3, 5, 1e10)]) -def test_unphysical_inverse_doppler_factor(mu, r, inv_t_exp): - # Set the params from test cases here - # TODO: add relativity tests - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - with pytest.raises(r_packet.SuperluminalError): - obtained = r_packet.get_inverse_doppler_factor(r, mu, time_explosion) - - -@pytest.mark.parametrize( - ["mu", "r", "inv_t_exp", "expected"], - [ - (-0.3, 10000000, 0.001, 1.0000001000692842), - (-0.3, 0, 1 / 2.6e7, 1.0), - (0, 1, 1 / 2.6e7, 1.0), - ], -) -def test_get_doppler_factor_full_relativity( - mu, r, inv_t_exp, expected -): - # Set the params from test cases here - # TODO: add relativity tests - mc.full_relativity = True - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - - obtained = get_doppler_factor(r, mu, time_explosion) - mc.full_relativity = False - # Perform required assertions - assert_almost_equal(obtained, expected) - - -@pytest.mark.parametrize( - ["mu", "r", "inv_t_exp", "expected"], - [ - (-0.3, 10000000, 0.001, 0.999999899930827), - (-0.3, 0, 1 / 2.6e7, 1.0), - (0, 1, 1 / 2.6e7, 1.0), - ], -) -def test_get_inverse_doppler_factor_full_relativity( - mu, r, inv_t_exp, expected -): - # Set the params from test cases here - # TODO: add relativity tests - mc.full_relativity = True - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - - obtained = r_packet.get_inverse_doppler_factor(r, mu, time_explosion) - mc.full_relativity = False - # Perform required assertions - assert_almost_equal(obtained, expected) - - def test_get_random_mu_different_output(): """ Ensure that different calls results @@ -401,9 +238,7 @@ def test_both_angle_aberrations(mu, r, time_explosion): energy = 0.9 packet = r_packet.RPacket(r, mu, nu, energy) packet.r = r - obtained_mu = angle_aberration_LF_to_CMF( - packet, time_explosion, mu - ) + obtained_mu = angle_aberration_LF_to_CMF(packet, time_explosion, mu) inverse_obtained_mu = angle_aberration_CMF_to_LF( packet, time_explosion, obtained_mu ) @@ -422,9 +257,7 @@ def test_both_angle_aberrations_inverse(mu, r, time_explosion): energy = 0.9 packet = r_packet.RPacket(r, mu, nu, energy) packet.r = r - obtained_mu = angle_aberration_CMF_to_LF( - packet, time_explosion, mu - ) + obtained_mu = angle_aberration_CMF_to_LF(packet, time_explosion, mu) inverse_obtained_mu = angle_aberration_LF_to_CMF( packet, time_explosion, obtained_mu ) @@ -493,7 +326,7 @@ def test_move_packet_across_shell_boundary_increment( [(0, 1, 0, 0), (0, 1, 1, 0), (0, 1, 0, 1)], ) def test_packet_energy_limit_one(distance_trace, time_explosion, mu, r): - initial_energy = 0.9 + initial_energy = 0.9 nu = 0.4 packet = r_packet.RPacket(r, mu, nu, initial_energy) new_energy = r_packet.calc_packet_energy( @@ -510,9 +343,7 @@ def test_packet_energy_limit_one(distance_trace, time_explosion, mu, r): ({"mu": -0.3, "r": 7.5e14}, {"d_boundary": 709376919351035.9}), ], ) -def test_compute_distance2boundary( - packet_params, expected_params -): +def test_compute_distance2boundary(packet_params, expected_params): mu = packet_params["mu"] r = packet_params["r"] r_inner = np.array([6.912e14, 8.64e14], dtype=np.float64) @@ -562,7 +393,7 @@ def test_compute_distance2line(packet_params, expected_params): time_explosion = 5.2e7 doppler_factor = get_doppler_factor( - packet.r, packet.mu, time_explosion + packet.r, packet.mu, time_explosion, False ) comov_nu = packet.nu * doppler_factor @@ -620,9 +451,7 @@ def test_compute_distance2line(packet_params, expected_params): ), ], ) -def test_move_packet( - packet_params, expected_params, full_relativity -): +def test_move_packet(packet_params, expected_params, full_relativity): distance = 1e13 r, mu, nu, energy = 7.5e14, 0.3, 0.4, 0.9 time_explosion = 5.2e7 @@ -632,16 +461,15 @@ def test_move_packet( packet.energy = packet_params["energy"] packet.r = packet_params["r"] # model.full_relativity = full_relativity - mc.full_relativity = full_relativity doppler_factor = get_doppler_factor( - packet.r, packet.mu, time_explosion + packet.r, packet.mu, time_explosion, full_relativity ) - numba_estimator = Estimators( + numba_estimator = RadiationFieldMCEstimators( packet_params["j"], packet_params["nu_bar"], 0, 0 ) r_packet_transport.move_r_packet( - packet, distance, time_explosion, numba_estimator + packet, distance, time_explosion, numba_estimator, full_relativity ) assert_almost_equal(packet.mu, expected_params["mu"]) @@ -653,7 +481,7 @@ def test_move_packet( expected_j *= doppler_factor expected_nubar *= doppler_factor - mc.full_relativity = False + mc.ENABLE_FULL_RELATIVITY = False assert_allclose( numba_estimator.j_estimator[packet.current_shell_id], @@ -739,8 +567,8 @@ def test_move_packet( ) def test_frame_transformations(mu, r, inv_t_exp, full_relativity): packet = r_packet.RPacket(r=r, mu=mu, energy=0.9, nu=0.4) - mc.full_relativity = bool(full_relativity) - mc.full_relativity = full_relativity + mc.ENABLE_FULL_RELATIVITY = bool(full_relativity) + mc.ENABLE_FULL_RELATIVITY = full_relativity inverse_doppler_factor = r_packet.get_inverse_doppler_factor( r, mu, 1 / inv_t_exp @@ -748,7 +576,7 @@ def test_frame_transformations(mu, r, inv_t_exp, full_relativity): r_packet.angle_aberration_CMF_to_LF(packet, 1 / inv_t_exp, packet.mu) doppler_factor = get_doppler_factor(r, mu, 1 / inv_t_exp) - mc.full_relativity = False + mc.ENABLE_FULL_RELATIVITY = False assert_almost_equal(doppler_factor * inverse_doppler_factor, 1.0) @@ -766,14 +594,12 @@ def test_frame_transformations(mu, r, inv_t_exp, full_relativity): ) def test_angle_transformation_invariance(mu, r, inv_t_exp): packet = r_packet.RPacket(r, mu, 0.4, 0.9) - mc.full_relativity = True + mc.ENABLE_FULL_RELATIVITY = True mu1 = angle_aberration_CMF_to_LF(packet, 1 / inv_t_exp, mu) - mu_obtained = angle_aberration_LF_to_CMF( - packet, 1 / inv_t_exp, mu1 - ) + mu_obtained = angle_aberration_LF_to_CMF(packet, 1 / inv_t_exp, mu1) - mc.full_relativity = False + mc.ENABLE_FULL_RELATIVITY = False assert_almost_equal(mu_obtained, mu) @@ -795,24 +621,26 @@ def test_compute_distance2line_relativistic( ): packet = r_packet.RPacket(r=r, nu=nu, mu=mu, energy=0.9) # packet.nu_line = nu_line - numba_estimator = Estimators( - runner.j_estimator, - runner.nu_bar_estimator, - runner.j_blue_estimator, - runner.Edotlu_estimator, + numba_estimator = RadiationFieldMCEstimators( + transport.j_estimator, + transport.nu_bar_estimator, + transport.j_blue_estimator, + transport.Edotlu_estimator, ) - mc.full_relativity = bool(full_relativity) + mc.ENABLE_FULL_RELATIVITY = bool(full_relativity) doppler_factor = get_doppler_factor(r, mu, t_exp) comov_nu = packet.nu * doppler_factor distance = r_packet.calculate_distance_line( packet, comov_nu, nu_line, t_exp ) - r_packet_transport.move_r_packet(packet, distance, t_exp, numba_estimator) + r_packet_transport.move_r_packet( + packet, distance, t_exp, numba_estimator, bool(full_relativity) + ) doppler_factor = get_doppler_factor(r, mu, t_exp) comov_nu = packet.nu * doppler_factor - mc.full_relativity = False + mc.ENABLE_FULL_RELATIVITY = False assert_allclose(comov_nu, nu_line, rtol=1e-14) @@ -860,4 +688,4 @@ def test_rpacket_tracking(index, seed, r, nu, mu, energy): assert test_rpacket.nu == tracked_rpacket_properties.nu assert test_rpacket.mu == tracked_rpacket_properties.mu assert test_rpacket.energy == tracked_rpacket_properties.energy - assert tracked_rpacket_properties.interact_id == 1 + assert tracked_rpacket_properties.num_interactions == 1 diff --git a/tardis/transport/montecarlo/tests/test_montecarlo_logger.py b/tardis/transport/montecarlo/tests/test_montecarlo_logger.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tardis/transport/montecarlo/tests/test_montecarlo_main_loop.py b/tardis/transport/montecarlo/tests/test_montecarlo_main_loop.py new file mode 100644 index 00000000000..295cf8b703a --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_montecarlo_main_loop.py @@ -0,0 +1,154 @@ +from copy import deepcopy + +import numpy.testing as npt +import pytest + +from tardis.simulation import Simulation + + +@pytest.mark.xfail(reason="To be implemented") +def test_montecarlo_radial1d(): + assert False + + +@pytest.fixture(scope="function") +def montecarlo_main_loop_config( + config_montecarlo_1e5_verysimple, +): + # Setup model config from verysimple + + config_montecarlo_1e5_verysimple.montecarlo.last_no_of_packets = 1e5 + config_montecarlo_1e5_verysimple.montecarlo.no_of_virtual_packets = 0 + config_montecarlo_1e5_verysimple.montecarlo.iterations = 1 + config_montecarlo_1e5_verysimple.plasma.line_interaction_type = "macroatom" + + del config_montecarlo_1e5_verysimple["config_dirname"] + return config_montecarlo_1e5_verysimple + + +def test_montecarlo_main_loop( + montecarlo_main_loop_config, + regression_data, + atomic_dataset, +): + atomic_dataset = deepcopy(atomic_dataset) + montecarlo_main_loop_simulation = Simulation.from_config( + montecarlo_main_loop_config, + atom_data=atomic_dataset, + virtual_packet_logging=False, + legacy_mode_enabled=True, + ) + montecarlo_main_loop_simulation.run_convergence() + montecarlo_main_loop_simulation.run_final() + + expected_hdf_store = regression_data.sync_hdf_store( + montecarlo_main_loop_simulation + ) + + # Load compare data from refdata + + expected_nu = expected_hdf_store[ + "/simulation/transport/transport_state/output_nu" + ] + expected_energy = expected_hdf_store[ + "/simulation/transport/transport_state/output_energy" + ] + expected_nu_bar_estimator = expected_hdf_store[ + "/simulation/transport/transport_state/nu_bar_estimator" + ] + expected_j_estimator = expected_hdf_store[ + "/simulation/transport/transport_state/j_estimator" + ] + expected_hdf_store.close() + transport_state = montecarlo_main_loop_simulation.transport.transport_state + actual_energy = transport_state.packet_collection.output_energies + actual_nu = transport_state.packet_collection.output_nus + actual_nu_bar_estimator = ( + transport_state.radfield_mc_estimators.nu_bar_estimator + ) + actual_j_estimator = transport_state.radfield_mc_estimators.j_estimator + + # Compare + npt.assert_allclose( + actual_nu_bar_estimator, expected_nu_bar_estimator, rtol=1e-13 + ) + npt.assert_allclose(actual_j_estimator, expected_j_estimator, rtol=1e-13) + npt.assert_allclose(actual_energy, expected_energy, rtol=1e-13) + npt.assert_allclose(actual_nu, expected_nu, rtol=1e-13) + + +def test_montecarlo_main_loop_vpacket_log( + montecarlo_main_loop_config, + regression_data, + atomic_dataset, +): + atomic_dataset = deepcopy(atomic_dataset) + montecarlo_main_loop_config.montecarlo.no_of_virtual_packets = 5 + + montecarlo_main_loop_simulation = Simulation.from_config( + montecarlo_main_loop_config, + atom_data=atomic_dataset, + virtual_packet_logging=True, + legacy_mode_enabled=True, + ) + montecarlo_main_loop_simulation.run_convergence() + montecarlo_main_loop_simulation.run_final() + + transport = montecarlo_main_loop_simulation.transport + + assert transport.montecarlo_configuration.ENABLE_VPACKET_TRACKING is True + + expected_hdf_store = regression_data.sync_hdf_store( + montecarlo_main_loop_simulation + ) + + expected_nu = expected_hdf_store[ + "/simulation/transport/transport_state/output_nu" + ] + expected_energy = expected_hdf_store[ + "/simulation/transport/transport_state/output_energy" + ] + expected_nu_bar_estimator = expected_hdf_store[ + "/simulation/transport/transport_state/nu_bar_estimator" + ] + expected_j_estimator = expected_hdf_store[ + "/simulation/transport/transport_state/j_estimator" + ] + expected_vpacket_log_nus = expected_hdf_store[ + "/simulation/transport/transport_state/virt_packet_nus" + ] + expected_vpacket_log_energies = expected_hdf_store[ + "/simulation/transport/transport_state/virt_packet_energies" + ] + + transport_state = transport.transport_state + + actual_energy = transport_state.packet_collection.output_energies + actual_nu = transport_state.packet_collection.output_nus + actual_nu_bar_estimator = transport_state.nu_bar_estimator + actual_j_estimator = transport_state.j_estimator + actual_vpacket_log_nus = transport_state.vpacket_tracker.nus + actual_vpacket_log_energies = transport_state.vpacket_tracker.energies + + expected_hdf_store.close() + # Compare + npt.assert_allclose( + actual_nu_bar_estimator, + expected_nu_bar_estimator, + rtol=1e-12, + atol=1e-15, + ) + npt.assert_allclose( + actual_j_estimator, expected_j_estimator, rtol=1e-12, atol=1e-15 + ) + npt.assert_allclose(actual_energy, expected_energy, rtol=1e-12, atol=1e-15) + npt.assert_allclose(actual_nu, expected_nu, rtol=1e-12, atol=1e-15) + npt.assert_allclose( + actual_vpacket_log_nus, expected_vpacket_log_nus, rtol=1e-12, atol=1e-15 + ) + npt.assert_allclose( + actual_vpacket_log_energies, + expected_vpacket_log_energies, + rtol=1e-12, + atol=1e-15, + ) diff --git a/tardis/transport/montecarlo/tests/test_nonhomologous.py b/tardis/transport/montecarlo/tests/test_nonhomologous.py new file mode 100644 index 00000000000..5a869b49fb0 --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_nonhomologous.py @@ -0,0 +1,35 @@ +import pytest +from numpy.testing import assert_almost_equal + +import tardis.transport.montecarlo.nonhomologous_grid as nonhomologous_grid + + +@pytest.mark.parametrize( + ["a", "b", "c", "d", "e", "threshold", "expected_roots"], + [ + ( + 0.0, + 0.0, + 0.0, + 2.0, + -1.0, + 0.0, + {"result": [0.5]}, + ), + ( + 1.0, + 2.0, + 0.0, + 2.0, + 0.0, + 0.0, + {"result": []}, + ), + (1.0, -14.0, 71.0, -154.0, 120.0, 2.5, {"result": [3, 4, 5]}), + ], +) +def test_quartic_roots(a, b, c, d, e, threshold, expected_roots): + obtained_roots = nonhomologous_grid.quartic_roots(a, b, c, d, e, threshold) + obtained_roots.sort() + + assert_almost_equal(obtained_roots, expected_roots["result"]) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_numba_formal_integral.py b/tardis/transport/montecarlo/tests/test_numba_formal_integral.py similarity index 65% rename from tardis/montecarlo/montecarlo_numba/tests/test_numba_formal_integral.py rename to tardis/transport/montecarlo/tests/test_numba_formal_integral.py index a20657a3d7c..2bc89946c73 100644 --- a/tardis/montecarlo/montecarlo_numba/tests/test_numba_formal_integral.py +++ b/tardis/transport/montecarlo/tests/test_numba_formal_integral.py @@ -6,22 +6,23 @@ import numpy.testing as ntest from tardis.util.base import intensity_black_body -import tardis.montecarlo.montecarlo_numba.formal_integral as formal_integral -from tardis.montecarlo.montecarlo_numba.numba_interface import NumbaModel +import tardis.transport.montecarlo.formal_integral as formal_integral +from tardis.model.geometry.radial1d import NumbaRadial1DGeometry + @pytest.mark.parametrize( - ["nu", "T"], + ["nu", "temperature"], [ (1e14, 1e4), (0, 1), (1, 1), ], ) -def test_intensity_black_body(nu, T): +def test_intensity_black_body(nu, temperature): func = formal_integral.intensity_black_body - actual = func(nu, T) + actual = func(nu, temperature) print(actual, type(actual)) - expected = intensity_black_body(nu, T) + expected = intensity_black_body(nu, temperature) ntest.assert_almost_equal(actual, expected) @@ -41,6 +42,7 @@ def test_trapezoid_integration(N): def calculate_z(r, p): return np.sqrt(r * r - p * p) + TESTDATA = [ { "r": np.linspace(1, 2, 3, dtype=np.float64), @@ -48,28 +50,34 @@ def calculate_z(r, p): { "r": np.linspace(0, 1, 3), }, - #{"r": np.linspace(1, 2, 10, dtype=np.float64)}, + # {"r": np.linspace(1, 2, 10, dtype=np.float64)}, ] @pytest.fixture(scope="function", params=TESTDATA) -def formal_integral_model(request): +def formal_integral_geometry(request): r = request.param["r"] - model = NumbaModel( - r[:-1], - r[1:], - 1/c.c.cgs.value) - return model + geometry = NumbaRadial1DGeometry( + r[:-1], + r[1:], + r[:-1] * c.c.cgs.value, + r[1:] * c.c.cgs.value, + ) + return geometry + + +@pytest.fixture(scope="function") +def time_explosion(): + return 1 / c.c.cgs.value + + +@pytest.mark.parametrize("p", [0.0, 0.5, 1.0]) +def test_calculate_z(formal_integral_geometry, time_explosion, p): -@pytest.mark.parametrize( - 'p', [0.0, 0.5, 1.0] -) -def test_calculate_z(formal_integral_model, p): - func = formal_integral.calculate_z - inv_t = 1.0 / formal_integral_model.time_explosion - size = len(formal_integral_model.r_outer) - r_outer = formal_integral_model.r_outer + inv_t = 1.0 / time_explosion + size = len(formal_integral_geometry.r_outer) + r_outer = formal_integral_geometry.r_outer for r in r_outer: actual = func(r, p, inv_t) @@ -81,24 +89,22 @@ def test_calculate_z(formal_integral_model, p): @pytest.mark.parametrize("p", [0, 0.5, 1]) -def test_populate_z_photosphere(formal_integral_model, p): +def test_populate_z_photosphere(formal_integral_geometry, time_explosion, p): """ Test the case where p < r[0] That means we 'hit' all shells from inside to outside. """ - integrator = formal_integral.FormalIntegrator( - formal_integral_model, None, None - ) + integrator = formal_integral.FormalIntegrator(time_explosion, None, None) func = formal_integral.populate_z - size = len(formal_integral_model.r_outer) - r_inner = formal_integral_model.r_inner - r_outer = formal_integral_model.r_outer + size = len(formal_integral_geometry.r_outer) + r_inner = formal_integral_geometry.r_inner + r_outer = formal_integral_geometry.r_outer p = r_inner[0] * p oz = np.zeros_like(r_inner) oshell_id = np.zeros_like(oz, dtype=np.int64) - N = func(formal_integral_model, p, oz, oshell_id) + N = func(formal_integral_geometry, time_explosion, p, oz, oshell_id) assert N == size ntest.assert_allclose(oshell_id, np.arange(0, size, 1)) @@ -107,18 +113,16 @@ def test_populate_z_photosphere(formal_integral_model, p): @pytest.mark.parametrize("p", [1e-5, 0.5, 0.99, 1]) -def test_populate_z_shells(formal_integral_model, p): +def test_populate_z_shells(formal_integral_geometry, time_explosion, p): """ Test the case where p > r[0] """ - integrator = formal_integral.FormalIntegrator( - formal_integral_model, None, None - ) + integrator = formal_integral.FormalIntegrator(time_explosion, None, None) func = formal_integral.populate_z - size = len(formal_integral_model.r_inner) - r_inner = formal_integral_model.r_inner - r_outer = formal_integral_model.r_outer + size = len(formal_integral_geometry.r_inner) + r_inner = formal_integral_geometry.r_inner + r_outer = formal_integral_geometry.r_outer p = r_inner[0] + (r_outer[-1] - r_inner[0]) * p idx = np.searchsorted(r_outer, p, side="right") @@ -144,7 +148,7 @@ def test_populate_z_shells(formal_integral_model, p): r_outer[np.arange(idx, size, 1)], p ) - N = func(formal_integral_model, p, oz, oshell_id) + N = func(formal_integral_geometry, time_explosion, p, oz, oshell_id) assert N == expected_N diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_numba_interface.py b/tardis/transport/montecarlo/tests/test_numba_interface.py similarity index 84% rename from tardis/montecarlo/montecarlo_numba/tests/test_numba_interface.py rename to tardis/transport/montecarlo/tests/test_numba_interface.py index 75b287e0faa..0b41c863eef 100644 --- a/tardis/montecarlo/montecarlo_numba/tests/test_numba_interface.py +++ b/tardis/transport/montecarlo/tests/test_numba_interface.py @@ -1,15 +1,18 @@ import pytest -import tardis.montecarlo.montecarlo_numba.numba_interface as numba_interface +import tardis.opacities.opacity_state as numba_interface import numpy.testing as npt import numpy as np @pytest.mark.parametrize("input_params", ["scatter", "macroatom", "downbranch"]) -def test_numba_plasma_initialize(nb_simulation_verysimple, input_params): +def test_opacity_state_initialize(nb_simulation_verysimple, input_params): line_interaction_type = input_params plasma = nb_simulation_verysimple.plasma - actual = numba_interface.numba_plasma_initialize( - plasma, line_interaction_type + actual = numba_interface.opacity_state_initialize( + plasma, + line_interaction_type, + disable_line_scattering=False, + continuum_processes_enabled=False, ) npt.assert_allclose( @@ -59,13 +62,12 @@ def test_configuration_initialize(): assert False -def test_VPacketCollection_set_properties(verysimple_3vpacket_collection): - +def test_VPacketCollection_add_packet(verysimple_3vpacket_collection): assert verysimple_3vpacket_collection.length == 0 nus = [3.0e15, 0.0, 1e15, 1e5] energies = [0.4, 0.1, 0.6, 1e10] - initial_mus = [.1, 0, 1, .9] + initial_mus = [0.1, 0, 1, 0.9] initial_rs = [3e42, 4.5e45, 0, 9.0e40] last_interaction_in_nus = np.array( [3.0e15, 0.0, 1e15, 1e5], dtype=np.float64 @@ -73,6 +75,7 @@ def test_VPacketCollection_set_properties(verysimple_3vpacket_collection): last_interaction_types = np.array([1, 1, 3, 2], dtype=np.int64) last_interaction_in_ids = np.array([100, 0, 1, 1000], dtype=np.int64) last_interaction_out_ids = np.array([1201, 123, 545, 1232], dtype=np.int64) + last_interaction_shell_ids = np.array([2, -1, 6, 0], dtype=np.int64) for ( nu, @@ -83,6 +86,7 @@ def test_VPacketCollection_set_properties(verysimple_3vpacket_collection): last_interaction_type, last_interaction_in_id, last_interaction_out_id, + last_interaction_shell_id, ) in zip( nus, energies, @@ -92,8 +96,9 @@ def test_VPacketCollection_set_properties(verysimple_3vpacket_collection): last_interaction_types, last_interaction_in_ids, last_interaction_out_ids, + last_interaction_shell_ids, ): - verysimple_3vpacket_collection.set_properties( + verysimple_3vpacket_collection.add_packet( nu, energy, initial_mu, @@ -102,6 +107,7 @@ def test_VPacketCollection_set_properties(verysimple_3vpacket_collection): last_interaction_type, last_interaction_in_id, last_interaction_out_id, + last_interaction_shell_id, ) npt.assert_array_equal( @@ -152,4 +158,10 @@ def test_VPacketCollection_set_properties(verysimple_3vpacket_collection): ], last_interaction_out_ids, ) + npt.assert_array_equal( + verysimple_3vpacket_collection.last_interaction_shell_id[ + : verysimple_3vpacket_collection.idx + ], + last_interaction_shell_ids, + ) assert verysimple_3vpacket_collection.length == 9 diff --git a/tardis/transport/montecarlo/tests/test_opacities.py b/tardis/transport/montecarlo/tests/test_opacities.py new file mode 100644 index 00000000000..07096d6e0c6 --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_opacities.py @@ -0,0 +1,102 @@ +import numpy.testing as npt +import pytest + +from tardis.opacities.opacities import ( + compton_opacity_calculation, + kappa_calculation, + pair_creation_opacity_calculation, + photoabsorption_opacity_calculation, +) + + +@pytest.mark.parametrize( + ["electron_number_density", "energy", "expected"], + [ + (1.0e11, 511.0, 2.865396624016367e-14), + (1e15, 255.5, 3.743906253489761e-10), + (1e5, 511.0e7, 4.318577913631238e-26), + ], +) +def test_compton_opacity_calculation(energy, electron_number_density, expected): + """ + Parameters + ---------- + energy : float + electron_number_density : float + """ + opacity = compton_opacity_calculation(energy, electron_number_density) + + npt.assert_almost_equal(opacity, expected) + + +@pytest.mark.parametrize( + ["ejecta_density", "energy", "iron_group_fraction", "expected"], + [ + (1.0, 511.0, 0.0, 0.00015028056615643418), + (1e-2, 255.5, 0.5, 8.903267700390038e-05), + (1e-2, 255.5, 0.25, 5.1069068712110425e-05), + (1e5, 511.0e7, 1.0, 0.0), + ], +) +def test_photoabsorption_opacity_calculation( + energy, ejecta_density, iron_group_fraction, expected +): + """ + Parameters + ---------- + energy : float + ejecta_density : float + iron_group_fraction : float + """ + opacity = photoabsorption_opacity_calculation( + energy, ejecta_density, iron_group_fraction + ) + + npt.assert_almost_equal(opacity, expected) + + +@pytest.mark.parametrize( + ["ejecta_density", "energy", "iron_group_fraction", "expected"], + [ + (1.0, 511.0, 0.0, 0.0), + (1e-2, 1500, 0.5, 2.743980356831218e-06), + (1e-2, 1200, 0.25, 8.846018943383742e-06), + (1e5, 511.0e7, 1.0, 1111355719.7411418), + ], +) +def test_pair_creation_opacity_calculation( + energy, ejecta_density, iron_group_fraction, expected +): + """ + Parameters + ---------- + energy : float + ejecta_density : float + iron_group_fraction : float + """ + opacity = pair_creation_opacity_calculation( + energy, ejecta_density, iron_group_fraction + ) + + npt.assert_almost_equal(opacity, expected) + + +@pytest.mark.parametrize( + ["energy", "expected"], + [ + (511.0, 1.0000021334560507), + (255.5, 0.5000010667280254), + (0.0, 0.0), + (511.0e7, 10000021.334560508), + ], +) +def test_kappa_calculation(energy, expected): + """ + + Parameters + ---------- + energy : float + expected : float + """ + kappa = kappa_calculation(energy) + npt.assert_almost_equal(kappa, expected) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_packet.py b/tardis/transport/montecarlo/tests/test_packet.py similarity index 75% rename from tardis/montecarlo/montecarlo_numba/tests/test_packet.py rename to tardis/transport/montecarlo/tests/test_packet.py index 2ffab56f6f2..df9ca7d6ba6 100644 --- a/tardis/montecarlo/montecarlo_numba/tests/test_packet.py +++ b/tardis/transport/montecarlo/tests/test_packet.py @@ -1,43 +1,50 @@ -import pytest import numpy as np +import pytest -import tardis.montecarlo.montecarlo_numba.r_packet as r_packet -import tardis.montecarlo.montecarlo_numba.calculate_distances as calculate_distances -import tardis.montecarlo.montecarlo_numba.frame_transformations as frame_transformations -import tardis.montecarlo.montecarlo_numba.opacities as opacities -import tardis.montecarlo.montecarlo_numba.r_packet_transport as r_packet_transport -from tardis.montecarlo.montecarlo_numba.estimators import ( +import tardis.opacities.opacities as opacities +import tardis.transport.frame_transformations as frame_transformations +import tardis.transport.geometry.calculate_distances as calculate_distances +import tardis.transport.montecarlo.estimators.radfield_mc_estimators +import tardis.transport.montecarlo.montecarlo_configuration as numba_config +import tardis.transport.montecarlo.numba_interface as numba_interface +import tardis.transport.montecarlo.r_packet as r_packet +import tardis.transport.montecarlo.utils as utils +import tardis.transport.frame_transformations as frame_transformations +import tardis.transport.geometry.calculate_distances as calculate_distances +import tardis.transport.montecarlo.r_packet_transport as r_packet_transport +from tardis import constants as const +from tardis.model.geometry.radial1d import NumbaRadial1DGeometry +from tardis.transport.montecarlo.estimators.radfield_estimator_calcs import ( update_line_estimators, ) -import tardis.montecarlo.montecarlo_numba.utils as utils - -import tardis.montecarlo.montecarlo_numba.numba_interface as numba_interface -from tardis import constants as const - -import tardis.montecarlo.montecarlo_numba.numba_config as numba_config - C_SPEED_OF_LIGHT = const.c.to("cm/s").value SIGMA_THOMSON = const.sigma_T.to("cm^2").value from numpy.testing import ( - assert_almost_equal, assert_allclose, + assert_almost_equal, ) @pytest.fixture(scope="function") -def model(): - return numba_interface.NumbaModel( +def geometry(): + return NumbaRadial1DGeometry( r_inner=np.array([6.912e14, 8.64e14], dtype=np.float64), r_outer=np.array([8.64e14, 1.0368e15], dtype=np.float64), - time_explosion=5.2e7, + v_inner=np.array([-1, -1], dtype=np.float64), + v_outer=np.array([-1, -1], dtype=np.float64), ) +@pytest.fixture(scope="function") +def time_explosion(): + return 5.2e7 + + @pytest.fixture(scope="function") def estimators(): - return numba_interface.Estimators( + return tardis.transport.montecarlo.estimators.radfield_mc_estimators.RadiationFieldMCEstimators( j_estimator=np.array([0.0, 0.0], dtype=np.float64), nu_bar_estimator=np.array([0.0, 0.0], dtype=np.float64), j_blue_estimator=np.array( @@ -46,6 +53,11 @@ def estimators(): Edotlu_estimator=np.array( [[0.0, 0.0, 1.0], [0.0, 0.0, 1.0]], dtype=np.float64 ), + photo_ion_estimator=np.empty((0, 0), dtype=np.float64), + stim_recomb_estimator=np.empty((0, 0), dtype=np.float64), + bf_heating_estimator=np.empty((0, 0), dtype=np.float64), + stim_recomb_cooling_estimator=np.empty((0, 0), dtype=np.float64), + photo_ion_estimator_statistics=np.empty((0, 0), dtype=np.int64), ) @@ -57,12 +69,12 @@ def estimators(): ({"mu": -0.3, "r": 7.5e14}, {"d_boundary": 709376919351035.9}), ], ) -def test_calculate_distance_boundary(packet_params, expected_params, model): +def test_calculate_distance_boundary(packet_params, expected_params, geometry): mu = packet_params["mu"] r = packet_params["r"] d_boundary = calculate_distances.calculate_distance_boundary( - r, mu, model.r_inner[0], model.r_outer[0] + r, mu, geometry.r_inner[0], geometry.r_outer[0] ) # Accuracy to within 0.1cm @@ -94,15 +106,13 @@ def test_calculate_distance_boundary(packet_params, expected_params, model): ], ) def test_calculate_distance_line( - packet_params, expected_params, static_packet, model + packet_params, expected_params, static_packet, time_explosion ): nu_line = packet_params["nu_line"] is_last_line = packet_params["is_last_line"] - time_explosion = model.time_explosion - doppler_factor = frame_transformations.get_doppler_factor( - static_packet.r, static_packet.mu, time_explosion + static_packet.r, static_packet.mu, time_explosion, False ) comov_nu = static_packet.nu * doppler_factor @@ -110,7 +120,12 @@ def test_calculate_distance_line( obtained_tardis_error = None try: d_line = calculate_distances.calculate_distance_line( - static_packet, comov_nu, is_last_line, nu_line, time_explosion + static_packet, + comov_nu, + is_last_line, + nu_line, + time_explosion, + enable_full_relativity=False, ) except utils.MonteCarloException: obtained_tardis_error = utils.MonteCarloException @@ -142,52 +157,6 @@ def test_calculate_tau_electron(electron_density, distance): assert_almost_equal(actual, expected) -@pytest.mark.parametrize( - ["mu", "r", "inv_t_exp", "expected"], - [ - (0.3, 7.5e14, 1 / 5.2e7, 0.9998556693818854), - (-0.3, 0, 1 / 2.6e7, 1.0), - (0, 1, 1 / 2.6e7, 1.0), - ], -) -def test_get_doppler_factor(mu, r, inv_t_exp, expected): - # Set the params from test cases here - # TODO: add relativity tests - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - - obtained = frame_transformations.get_doppler_factor(r, mu, time_explosion) - - # Perform required assertions - assert_almost_equal(obtained, expected) - - -@pytest.mark.parametrize( - ["mu", "r", "inv_t_exp", "expected"], - [ - (0.3, 7.5e14, 1 / 5.2e7, 1 / 0.9998556693818854), - (-0.3, 0, 1 / 2.6e7, 1.0), - (0, 1, 1 / 2.6e7, 1.0), - ], -) -def test_get_inverse_doppler_factor(mu, r, inv_t_exp, expected): - # Set the params from test cases here - # TODO: add relativity tests - time_explosion = 1 / inv_t_exp - - # Perform any other setups just before this, they can be additional calls - # to other methods or introduction of some temporary variables - - obtained = frame_transformations.get_inverse_doppler_factor( - r, mu, time_explosion - ) - - # Perform required assertions - assert_almost_equal(obtained, expected) - - def test_get_random_mu(set_seed_fixture): """ Ensure that different calls results @@ -243,30 +212,40 @@ def test_update_line_estimators( expected_Edotlu, ): update_line_estimators( - estimators, static_packet, cur_line_id, distance_trace, time_explosion + estimators, + static_packet, + cur_line_id, + distance_trace, + time_explosion, + enable_full_relativity=False, ) assert_allclose(estimators.j_blue_estimator, expected_j_blue) assert_allclose(estimators.Edotlu_estimator, expected_Edotlu) -@pytest.mark.xfail(reason="Need to fix estimator differences across runs") # TODO set RNG consistently +# TODO: update this test to use the correct trace_packet +@pytest.mark.xfail(reason="Need to fix estimator differences across runs") def test_trace_packet( packet, - verysimple_numba_model, - verysimple_numba_plasma, + verysimple_time_explosion, + verysimple_opacity_state, verysimple_estimators, set_seed_fixture, ): - set_seed_fixture(1963) - packet.initialize_line_id(verysimple_numba_plasma, verysimple_numba_model) + packet.initialize_line_id( + verysimple_opacity_state, verysimple_time_explosion + ) distance, interaction_type, delta_shell = r_packet_transport.trace_packet( packet, - verysimple_numba_model, - verysimple_numba_plasma, + verysimple_time_explosion, + verysimple_opacity_state, verysimple_estimators, + continuum_processes_enabled=False, + enable_full_relativity=False, + disable_line_scattering=False, ) assert delta_shell == 1 @@ -303,7 +282,7 @@ def test_move_r_packet( packet_params, expected_params, packet, - model, + time_explosion, estimators, ENABLE_FULL_RELATIVITY, ): @@ -316,10 +295,16 @@ def test_move_r_packet( numba_config.ENABLE_FULL_RELATIVITY = ENABLE_FULL_RELATIVITY r_packet_transport.move_r_packet.recompile() # This must be done as move_r_packet was jitted with ENABLE_FULL_RELATIVITY doppler_factor = frame_transformations.get_doppler_factor( - packet.r, packet.mu, model.time_explosion + packet.r, packet.mu, time_explosion, ENABLE_FULL_RELATIVITY ) - r_packet_transport.move_r_packet(packet, distance, model.time_explosion, estimators) + r_packet_transport.move_r_packet( + packet, + distance, + time_explosion, + estimators, + ENABLE_FULL_RELATIVITY, + ) assert_almost_equal(packet.mu, expected_params["mu"]) assert_almost_equal(packet.r, expected_params["r"]) @@ -397,5 +382,3 @@ def test_move_packet_across_shell_boundary_increment( packet, delta_shell, no_of_shells ) assert packet.current_shell_id == current_shell_id + delta_shell - - diff --git a/tardis/transport/montecarlo/tests/test_packet_source.py b/tardis/transport/montecarlo/tests/test_packet_source.py new file mode 100644 index 00000000000..41b3af595fb --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_packet_source.py @@ -0,0 +1,124 @@ +import os + +from astropy import units as u +import numpy as np +import pandas as pd +import pytest +from numpy.testing import assert_allclose + +from tardis.transport.montecarlo.packet_source import ( + BlackBodySimpleSource, + BlackBodySimpleSourceRelativistic, +) +from tardis.transport.montecarlo import ( + montecarlo_configuration as montecarlo_configuration, +) +from tardis.tests.fixtures.regression_data import RegressionData + + +class TestBlackBodySimpleSource: + @pytest.fixture(scope="class") + def blackbodysimplesource(self, request): + """ + Create BlackBodySimpleSource instance. + + Yields + ------- + tardis.transport.montecarlo.packet_source.BlackBodySimpleSource + """ + cls = type(self) + bb = BlackBodySimpleSource( + radius=123, + temperature=10000 * u.K, + base_seed=1963, + legacy_second_seed=2508, + legacy_mode_enabled=True, + ) + yield bb + + def test_bb_nus(self, regression_data, blackbodysimplesource): + actual_nus = blackbodysimplesource.create_packet_nus(100).value + expected_nus = regression_data.sync_ndarray(actual_nus) + assert_allclose(actual_nus, expected_nus) + + def test_bb_mus(self, regression_data, blackbodysimplesource): + actual_mus = blackbodysimplesource.create_packet_mus(100) + expected_mus = regression_data.sync_ndarray(actual_mus) + assert_allclose(actual_mus, expected_mus) + + def test_bb_energies(self, regression_data, blackbodysimplesource): + actual_unif_energies = blackbodysimplesource.create_packet_energies( + 100 + ).value + expected_unif_energies = regression_data.sync_ndarray( + actual_unif_energies + ) + assert_allclose(actual_unif_energies, expected_unif_energies) + + def test_bb_attributes(self, regression_data, blackbodysimplesource): + actual_bb = blackbodysimplesource + expected_bb = regression_data.sync_hdf_store(actual_bb)[ + "/black_body_simple_source/scalars" + ] + assert_allclose(expected_bb.base_seed, actual_bb.base_seed) + assert_allclose(expected_bb.temperature, actual_bb.temperature.value) + assert_allclose(expected_bb.radius, actual_bb.radius) + + +class TestBlackBodySimpleSourceRel: + @pytest.fixture(scope="class") + def blackbody_simplesource_relativistic(self): + """ + Create BlackBodySimpleSourceRelativistic instance. + + Yields + ------- + tardis.montecarlo.packet_source.BlackBodySimpleSourceRelativistic + """ + bb_rel = BlackBodySimpleSourceRelativistic( + time_explosion=1123187, + base_seed=1963, + legacy_second_seed=2508, + legacy_mode_enabled=True, + ) + bb_rel.temperature = 10000 * u.K + bb_rel.beta = 0.25 + yield bb_rel + + def test_bb_nus(self, regression_data, blackbody_simplesource_relativistic): + actual_nus = blackbody_simplesource_relativistic.create_packet_nus( + 100 + ).value + expected_nus = regression_data.sync_ndarray(actual_nus) + assert_allclose(actual_nus, expected_nus) + + def test_bb_energies( + self, regression_data, blackbody_simplesource_relativistic + ): + actual_unif_energies = ( + blackbody_simplesource_relativistic.create_packet_energies( + 100 + ).value + ) + gamma = np.sqrt(1 - blackbody_simplesource_relativistic.beta**2) ** -1 + expected_unif_energies = regression_data.sync_ndarray( + actual_unif_energies + ) + assert_allclose(actual_unif_energies, expected_unif_energies) + + def test_bb_mus(self, regression_data, blackbody_simplesource_relativistic): + blackbody_simplesource_relativistic._reseed(2508) + actual_mus = blackbody_simplesource_relativistic.create_packet_mus(10) + expected_mus = regression_data.sync_ndarray(actual_mus) + assert_allclose(actual_mus, expected_mus) + + def test_bb_attributes( + self, regression_data, blackbody_simplesource_relativistic + ): + actual_bb = blackbody_simplesource_relativistic + expected_bb = regression_data.sync_hdf_store(actual_bb)[ + "/black_body_simple_source/scalars" + ] + assert_allclose(expected_bb.base_seed, actual_bb.base_seed) + assert_allclose(expected_bb.temperature, actual_bb.temperature.value) + assert_allclose(expected_bb.time_explosion, actual_bb.time_explosion) diff --git a/tardis/transport/montecarlo/tests/test_r_packet.py b/tardis/transport/montecarlo/tests/test_r_packet.py new file mode 100644 index 00000000000..3e18d190740 --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_r_packet.py @@ -0,0 +1,73 @@ +from copy import deepcopy + +import numpy as np +import numpy.testing as npt +import pytest + +from tardis.base import run_tardis +from tardis.transport.montecarlo.packet_trackers import ( + rpacket_trackers_to_dataframe, +) + + +@pytest.fixture(scope="module") +def simulation_rpacket_tracking_enabled(config_verysimple, atomic_dataset): + config_verysimple.montecarlo.iterations = 3 + config_verysimple.montecarlo.no_of_packets = 4000 + config_verysimple.montecarlo.last_no_of_packets = -1 + config_verysimple.spectrum.virtual.virtual_packet_logging = True + config_verysimple.montecarlo.no_of_virtual_packets = 1 + config_verysimple.montecarlo.tracking.track_rpacket = True + config_verysimple.spectrum.num = 2000 + atomic_data = deepcopy(atomic_dataset) + sim = run_tardis( + config_verysimple, + atom_data=atomic_data, + show_convergence_plots=False, + ) + return sim + + +def test_rpacket_trackers_to_dataframe(simulation_rpacket_tracking_enabled): + sim = simulation_rpacket_tracking_enabled + transport_state = sim.transport.transport_state + rtracker_df = rpacket_trackers_to_dataframe(transport_state.rpacket_tracker) + + # check df shape and column names + assert rtracker_df.shape == ( + sum([len(tracker.r) for tracker in transport_state.rpacket_tracker]), + 8, + ) + npt.assert_array_equal( + transport_state.rpacket_tracker_df.columns.values, + np.array( + [ + "status", + "seed", + "r", + "nu", + "mu", + "energy", + "shell_id", + "interaction_type", + ] + ), + ) + + # check all data with rpacket_tracker + expected_rtrackers = [] + for rpacket in transport_state.rpacket_tracker: + for rpacket_step_no in range(len(rpacket.r)): + expected_rtrackers.append( + [ + rpacket.status[rpacket_step_no], + rpacket.seed, + rpacket.r[rpacket_step_no], + rpacket.nu[rpacket_step_no], + rpacket.mu[rpacket_step_no], + rpacket.energy[rpacket_step_no], + rpacket.shell_id[rpacket_step_no], + rpacket.interaction_type[rpacket_step_no], + ] + ) + npt.assert_array_equal(rtracker_df.to_numpy(), np.array(expected_rtrackers)) diff --git a/tardis/montecarlo/montecarlo_numba/tests/test_single_packet_loop.py b/tardis/transport/montecarlo/tests/test_single_packet_loop.py similarity index 65% rename from tardis/montecarlo/montecarlo_numba/tests/test_single_packet_loop.py rename to tardis/transport/montecarlo/tests/test_single_packet_loop.py index 2cf7f70f4ee..065b694c5f4 100644 --- a/tardis/montecarlo/montecarlo_numba/tests/test_single_packet_loop.py +++ b/tardis/transport/montecarlo/tests/test_single_packet_loop.py @@ -2,29 +2,32 @@ import numpy.testing as npt -from tardis.montecarlo.montecarlo_numba import RPacket -from tardis.montecarlo.montecarlo_numba.single_packet_loop import ( +from tardis.transport.montecarlo import RPacket +from tardis.transport.montecarlo.single_packet_loop import ( single_packet_loop, ) -@pytest.mark.xfail(reason='Need to fix estimator differences across runs') + +@pytest.mark.xfail(reason="Need to fix estimator differences across runs") # TODO set RNG consistently def test_verysimple_single_packet_loop( - verysimple_numba_model, - verysimple_numba_plasma, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, verysimple_estimators, verysimple_vpacket_collection, verysimple_packet_collection, ): + numba_radial_1d_geometry = verysimple_numba_radial_1d_geometry packet_collection = verysimple_packet_collection vpacket_collection = verysimple_vpacket_collection - numba_model = verysimple_numba_model - numba_plasma = verysimple_numba_plasma + time_explosion = verysimple_time_explosion + opacity_state = verysimple_opacity_state numba_estimators = verysimple_estimators i = 0 r_packet = RPacket( - verysimple_numba_model.r_inner[0], + numba_radial_1d_geometry.r_inner[0], packet_collection.packets_input_mu[i], packet_collection.packets_input_nu[i], packet_collection.packets_input_energy[i], @@ -32,8 +35,9 @@ def test_verysimple_single_packet_loop( ) single_packet_loop( r_packet, - numba_model, - numba_plasma, + numba_radial_1d_geometry, + time_explosion, + opacity_state, numba_estimators, vpacket_collection, ) diff --git a/tardis/transport/montecarlo/tests/test_vpacket.py b/tardis/transport/montecarlo/tests/test_vpacket.py new file mode 100644 index 00000000000..43906cf642e --- /dev/null +++ b/tardis/transport/montecarlo/tests/test_vpacket.py @@ -0,0 +1,165 @@ +import os +import pytest +import numpy as np +import pandas as pd +import tardis.transport.montecarlo.vpacket as vpacket +from tardis import constants as const + +from tardis.transport.frame_transformations import ( + get_doppler_factor, +) + +C_SPEED_OF_LIGHT = const.c.to("cm/s").value + +import numpy.testing as npt + + +@pytest.fixture(scope="function") +def v_packet(): + return vpacket.VPacket( + r=7.5e14, + nu=4e15, + mu=0.3, + energy=0.9, + current_shell_id=0, + next_line_id=0, + index=0, + ) + + +def v_packet_initialize_line_id(v_packet, opacity_state, time_explosion): + inverse_line_list_nu = opacity_state.line_list_nu[::-1] + doppler_factor = get_doppler_factor( + v_packet.r, v_packet.mu, time_explosion, False + ) + comov_nu = v_packet.nu * doppler_factor + next_line_id = len(opacity_state.line_list_nu) - np.searchsorted( + inverse_line_list_nu, comov_nu + ) + v_packet.next_line_id = next_line_id + + +def test_trace_vpacket_within_shell( + v_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, +): + # Give the vpacket a reasonable line ID + v_packet_initialize_line_id( + v_packet, verysimple_opacity_state, verysimple_time_explosion + ) + + ( + tau_trace_combined, + distance_boundary, + delta_shell, + ) = vpacket.trace_vpacket_within_shell( + v_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + enable_full_relativity=False, + continuum_processes_enabled=False, + ) + + npt.assert_almost_equal(tau_trace_combined, 8164850.891288479) + # changed from almost equal to allclose. Now seems to work. + npt.assert_allclose(distance_boundary, 843684056256104.1) + assert delta_shell == 1 + + +def test_trace_vpacket( + v_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, +): + # Set seed because of RNG in trace_vpacket + np.random.seed(1) + + # Give the vpacket a reasonable line ID + v_packet_initialize_line_id( + v_packet, verysimple_opacity_state, verysimple_time_explosion + ) + + tau_trace_combined = vpacket.trace_vpacket( + v_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + 10.0, + 0.0, + enable_full_relativity=False, + continuum_processes_enabled=False, + ) + + npt.assert_almost_equal(tau_trace_combined, 8164850.891288479) + # change from almost_equal to allclose. Now seems to work. + npt.assert_allclose(v_packet.r, 1286064000000000.0) + npt.assert_almost_equal(v_packet.nu, 4.0e15) + npt.assert_almost_equal(v_packet.energy, 0.0) + npt.assert_almost_equal(v_packet.mu, 0.8309726858508629) + assert v_packet.next_line_id == 2773 + assert v_packet.current_shell_id == 1 + + +# NEEDS TO TEST VPACKET COLLECTION OVERFLOW +@pytest.mark.xfail(reason="Needs to be implemented") +def test_trace_vpacket_volley( + packet, + verysimple_packet_collection, + verysimple_3vpacket_collection, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, +): + # Set seed because of RNG in trace_vpacket + np.random.seed(1) + + packet.initialize_line_id( + verysimple_opacity_state, verysimple_time_explosion + ) + + vpacket.trace_vpacket_volley( + packet, + verysimple_3vpacket_collection, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + enable_full_relativity=False, + tau_russian=10.0, + survival_probability=0.0, + continuum_processes_enabled=False, + ) + + +@pytest.fixture(scope="function") +def broken_packet(): + return vpacket.VPacket( + r=1286064000000000.0, + nu=1660428912896553.2, + mu=0.4916053094346575, + energy=2.474533071386993e-07, + index=3, + current_shell_id=0, + next_line_id=5495, + ) + + +def test_trace_bad_vpacket( + broken_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, +): + vpacket.trace_vpacket( + broken_packet, + verysimple_numba_radial_1d_geometry, + verysimple_time_explosion, + verysimple_opacity_state, + 10.0, + 0.0, + enable_full_relativity=False, + continuum_processes_enabled=False, + ) diff --git a/tardis/montecarlo/montecarlo_numba/utils.py b/tardis/transport/montecarlo/utils.py similarity index 81% rename from tardis/montecarlo/montecarlo_numba/utils.py rename to tardis/transport/montecarlo/utils.py index 8fb46c8e543..1bc4e1a6ccb 100644 --- a/tardis/montecarlo/montecarlo_numba/utils.py +++ b/tardis/transport/montecarlo/utils.py @@ -1,6 +1,6 @@ import numpy as np from numba import njit -from tardis.montecarlo.montecarlo_numba import ( +from tardis.transport.montecarlo import ( njit_dict_no_parallel, ) diff --git a/tardis/montecarlo/montecarlo_numba/vpacket.py b/tardis/transport/montecarlo/vpacket.py similarity index 54% rename from tardis/montecarlo/montecarlo_numba/vpacket.py rename to tardis/transport/montecarlo/vpacket.py index 487635bfdaa..c84aa74fd00 100644 --- a/tardis/montecarlo/montecarlo_numba/vpacket.py +++ b/tardis/transport/montecarlo/vpacket.py @@ -1,33 +1,32 @@ import math import numpy as np -from numba import float64, int64, boolean -from numba import njit, gdb +from numba import float64, int64, njit from numba.experimental import jitclass -from tardis.montecarlo.montecarlo_numba import njit_dict, njit_dict_no_parallel -from tardis.montecarlo import ( - montecarlo_configuration as montecarlo_configuration, +from tardis.opacities.opacities import ( + chi_continuum_calculator, ) - -from tardis.montecarlo.montecarlo_numba.r_packet import ( - PacketStatus, +from tardis.transport.frame_transformations import ( + angle_aberration_CMF_to_LF, + angle_aberration_LF_to_CMF, + get_doppler_factor, ) -from tardis.montecarlo.montecarlo_numba.r_packet_transport import \ - move_packet_across_shell_boundary - -from tardis.montecarlo.montecarlo_numba.calculate_distances import ( +from tardis.transport.geometry.calculate_distances import ( calculate_distance_boundary, calculate_distance_line, ) - -from tardis.montecarlo.montecarlo_numba.frame_transformations import ( - get_doppler_factor, - angle_aberration_LF_to_CMF, - angle_aberration_CMF_to_LF, +from tardis.transport.montecarlo import njit_dict_no_parallel +from tardis.transport.montecarlo.numba_config import ( + C_SPEED_OF_LIGHT, + SIGMA_THOMSON, +) +from tardis.transport.montecarlo.r_packet import ( + PacketStatus, +) +from tardis.transport.montecarlo.r_packet_transport import ( + move_packet_across_shell_boundary, ) - -from tardis.montecarlo.montecarlo_numba.opacities import calculate_tau_electron vpacket_spec = [ ("r", float64), @@ -42,7 +41,7 @@ @jitclass(vpacket_spec) -class VPacket(object): +class VPacket: def __init__( self, r, @@ -64,12 +63,19 @@ def __init__( @njit(**njit_dict_no_parallel) -def trace_vpacket_within_shell(v_packet, numba_model, numba_plasma): +def trace_vpacket_within_shell( + v_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + enable_full_relativity, + continuum_processes_enabled, +): """ Trace VPacket within one shell (relatively simple operation) """ - r_inner = numba_model.r_inner[v_packet.current_shell_id] - r_outer = numba_model.r_outer[v_packet.current_shell_id] + r_inner = numba_radial_1d_geometry.r_inner[v_packet.current_shell_id] + r_outer = numba_radial_1d_geometry.r_outer[v_packet.current_shell_id] distance_boundary, delta_shell = calculate_distance_boundary( v_packet.r, v_packet.mu, r_inner, r_outer @@ -79,43 +85,64 @@ def trace_vpacket_within_shell(v_packet, numba_model, numba_plasma): # e scattering initialization - cur_electron_density = numba_plasma.electron_density[ + cur_electron_density = opacity_state.electron_density[ v_packet.current_shell_id ] - tau_electron = calculate_tau_electron( - cur_electron_density, distance_boundary - ) - tau_trace_combined = tau_electron + chi_e = cur_electron_density * SIGMA_THOMSON # Calculating doppler factor doppler_factor = get_doppler_factor( - v_packet.r, v_packet.mu, numba_model.time_explosion + v_packet.r, + v_packet.mu, + time_explosion, + enable_full_relativity, ) + comov_nu = v_packet.nu * doppler_factor + + if continuum_processes_enabled: + ( + chi_bf_tot, + chi_bf_contributions, + current_continua, + x_sect_bfs, + chi_ff, + ) = chi_continuum_calculator( + opacity_state, comov_nu, v_packet.current_shell_id + ) + chi_continuum = chi_e + chi_bf_tot + chi_ff + + else: + chi_continuum = chi_e + + if enable_full_relativity: + chi_continuum *= doppler_factor + + tau_continuum = chi_continuum * distance_boundary + tau_trace_combined = tau_continuum + cur_line_id = start_line_id - for cur_line_id in range(start_line_id, len(numba_plasma.line_list_nu)): + for cur_line_id in range(start_line_id, len(opacity_state.line_list_nu)): # if tau_trace_combined > 10: ### FIXME ????? # break - nu_line = numba_plasma.line_list_nu[cur_line_id] + nu_line = opacity_state.line_list_nu[cur_line_id] # TODO: Check if this is what the C code does - tau_trace_line = numba_plasma.tau_sobolev[ + tau_trace_line = opacity_state.tau_sobolev[ cur_line_id, v_packet.current_shell_id ] - if cur_line_id == len(numba_plasma.line_list_nu) - 1: - is_last_line = True - else: - is_last_line = False + is_last_line = cur_line_id == len(opacity_state.line_list_nu) - 1 distance_trace_line = calculate_distance_line( v_packet, comov_nu, is_last_line, nu_line, - numba_model.time_explosion, + time_explosion, + enable_full_relativity, ) if distance_boundary <= distance_trace_line: @@ -124,7 +151,7 @@ def trace_vpacket_within_shell(v_packet, numba_model, numba_plasma): tau_trace_combined += tau_trace_line else: - if cur_line_id == (len(numba_plasma.line_list_nu) - 1): + if cur_line_id == (len(opacity_state.line_list_nu) - 1): cur_line_id += 1 v_packet.next_line_id = cur_line_id @@ -132,42 +159,58 @@ def trace_vpacket_within_shell(v_packet, numba_model, numba_plasma): @njit(**njit_dict_no_parallel) -def trace_vpacket(v_packet, numba_model, numba_plasma): +def trace_vpacket( + v_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + tau_russian, + survival_probability, + enable_full_relativity, + continuum_processes_enabled, +): """ Trace single vpacket. + Parameters ---------- v_packet - numba_model - numba_plasma + time_explosion + opacity_state Returns ------- """ - tau_trace_combined = 0.0 while True: ( tau_trace_combined_shell, distance_boundary, delta_shell, - ) = trace_vpacket_within_shell(v_packet, numba_model, numba_plasma) + ) = trace_vpacket_within_shell( + v_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + enable_full_relativity, + continuum_processes_enabled, + ) tau_trace_combined += tau_trace_combined_shell move_packet_across_shell_boundary( - v_packet, delta_shell, len(numba_model.r_inner) + v_packet, delta_shell, len(numba_radial_1d_geometry.r_inner) ) - if tau_trace_combined > montecarlo_configuration.tau_russian: + if tau_trace_combined > tau_russian: event_random = np.random.random() - if event_random > montecarlo_configuration.survival_probability: + if event_random > survival_probability: v_packet.energy = 0.0 v_packet.status = PacketStatus.EMITTED else: v_packet.energy = ( v_packet.energy - / montecarlo_configuration.survival_probability + / survival_probability * math.exp(-tau_trace_combined) ) tau_trace_combined = 0.0 @@ -188,7 +231,15 @@ def trace_vpacket(v_packet, numba_model, numba_plasma): @njit(**njit_dict_no_parallel) def trace_vpacket_volley( - r_packet, vpacket_collection, numba_model, numba_plasma + r_packet, + vpacket_collection, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + enable_full_relativity, + tau_russian, + survival_probability, + continuum_processes_enabled, ): """ Shoot a volley of vpackets (the vpacket collection specifies how many) @@ -200,16 +251,16 @@ def trace_vpacket_volley( [description] vpacket_collection : [type] [description] - numba_model : [type] + numba_radial_1d_geometry : [type] [description] - numba_plasma : [type] + time_explosion : [type] + [description] + opacity_state : [type] [description] """ - if (r_packet.nu < vpacket_collection.v_packet_spawn_start_frequency) or ( r_packet.nu > vpacket_collection.v_packet_spawn_end_frequency ): - return no_of_vpackets = vpacket_collection.number_of_vpackets @@ -217,37 +268,59 @@ def trace_vpacket_volley( return ### TODO theoretical check for r_packet nu within vpackets bins - is done somewhere else I think - if r_packet.r > numba_model.r_inner[0]: # not on inner_boundary - r_inner_over_r = numba_model.r_inner[0] / r_packet.r + if ( + r_packet.r > numba_radial_1d_geometry.r_inner[0] + ): # not on inner_boundary + r_inner_over_r = numba_radial_1d_geometry.r_inner[0] / r_packet.r mu_min = -math.sqrt(1 - r_inner_over_r * r_inner_over_r) v_packet_on_inner_boundary = False - if montecarlo_configuration.full_relativity: + if enable_full_relativity: mu_min = angle_aberration_LF_to_CMF( - r_packet, numba_model.time_explosion, mu_min + r_packet, time_explosion, mu_min ) else: v_packet_on_inner_boundary = True mu_min = 0.0 + if enable_full_relativity: + inv_c = 1 / C_SPEED_OF_LIGHT + inv_t = 1 / time_explosion + beta_inner = numba_radial_1d_geometry.r_inner[0] * inv_t * inv_c + mu_bin = (1.0 - mu_min) / no_of_vpackets r_packet_doppler_factor = get_doppler_factor( - r_packet.r, r_packet.mu, numba_model.time_explosion + r_packet.r, + r_packet.mu, + time_explosion, + enable_full_relativity, ) for i in range(no_of_vpackets): v_packet_mu = mu_min + i * mu_bin + np.random.random() * mu_bin if v_packet_on_inner_boundary: # The weights are described in K&S 2014 - weight = 2 * v_packet_mu / no_of_vpackets + if not enable_full_relativity: + weight = 2 * v_packet_mu / no_of_vpackets + else: + weight = ( + 2 + * (v_packet_mu + beta_inner) + / (2 * beta_inner + 1) + / no_of_vpackets + ) + else: weight = (1 - mu_min) / (2 * no_of_vpackets) # C code: next line, angle_aberration_CMF_to_LF( & virt_packet, storage); - if montecarlo_configuration.full_relativity: + if enable_full_relativity: v_packet_mu = angle_aberration_CMF_to_LF( - r_packet, numba_model.time_explosion, v_packet_mu + r_packet, time_explosion, v_packet_mu ) v_packet_doppler_factor = get_doppler_factor( - r_packet.r, v_packet_mu, numba_model.time_explosion + r_packet.r, + v_packet_mu, + time_explosion, + enable_full_relativity, ) # transform between r_packet mu and v_packet_mu @@ -257,6 +330,10 @@ def trace_vpacket_volley( v_packet_nu = r_packet.nu * doppler_factor_ratio v_packet_energy = r_packet.energy * weight * doppler_factor_ratio + # TODO: Make sure we have a new continuum object for each vpacket + # comov_nu = v_packet_nu * v_packet_doppler_factor + # continuum.calculate(comov_nu, r_packet.current_shell_id) + v_packet = VPacket( r_packet.r, v_packet_mu, @@ -267,11 +344,20 @@ def trace_vpacket_volley( i, ) - tau_vpacket = trace_vpacket(v_packet, numba_model, numba_plasma) + tau_vpacket = trace_vpacket( + v_packet, + numba_radial_1d_geometry, + time_explosion, + opacity_state, + tau_russian, + survival_probability, + enable_full_relativity, + continuum_processes_enabled, + ) v_packet.energy *= math.exp(-tau_vpacket) - vpacket_collection.set_properties( + vpacket_collection.add_packet( v_packet.nu, v_packet.energy, v_packet_mu, @@ -280,4 +366,5 @@ def trace_vpacket_volley( r_packet.last_interaction_type, r_packet.last_line_interaction_in_id, r_packet.last_line_interaction_out_id, + r_packet.last_line_interaction_shell_id, ) diff --git a/tardis/transport/tests/test_doppler_factor.py b/tardis/transport/tests/test_doppler_factor.py new file mode 100644 index 00000000000..f057e1686f8 --- /dev/null +++ b/tardis/transport/tests/test_doppler_factor.py @@ -0,0 +1,193 @@ +import pytest +import numpy as np + +import tardis.transport.frame_transformations as frame_transformations +import tardis.transport.montecarlo.r_packet as r_packet + +from numpy.testing import ( + assert_almost_equal, +) + + +@pytest.mark.parametrize( + ["mu", "r", "inv_t_exp", "expected"], + [ + (0.3, 7.5e14, 1 / 5.2e7, 0.9998556693818854), + (-0.3, 0, 1 / 2.6e7, 1.0), + (0, 1, 1 / 2.6e7, 1.0), + ], +) +def test_get_doppler_factor(mu, r, inv_t_exp, expected): + """ + Checks the get_doppler_factor function. + + Parameters + ---------- + mu : float + Angle of movement of the packet. + r : float + Radius of the position of the packet. + inv_t_exp : float + Inverse of t_explosion. + expected : float + Expected value of the doppler factor. + """ + # Set the params from test cases here + time_explosion = 1 / inv_t_exp + + # Perform any other setups just before this, they can be additional calls + # to other methods or introduction of some temporary variables + + obtained = frame_transformations.get_doppler_factor( + r, mu, time_explosion, False + ) + + # Perform required assertions + assert_almost_equal(obtained, expected) + + +@pytest.mark.parametrize( + ["mu", "beta", "expected"], + [ + (0.3, 0.2, 0.94), + (-0.3, 0, 1.0), + (0, 0.8, 1.0), + ], +) +def test_get_doppler_factor_partial_relativity(mu, beta, expected): + """ + Checks the get_doppler_factor_partial_relativity. + + Parameters + ---------- + mu : float + Angle of movement of the packet. + beta : float + Velocity over speed of light for the packet. + expected : float + Expected value of the doppler factor. + """ + obtained = frame_transformations.get_doppler_factor_partial_relativity( + mu, beta + ) + assert_almost_equal(obtained, expected) + + +@pytest.mark.parametrize( + ["mu", "beta", "expected"], + [ + (0.3, 0.2, 0.95938348), + (-0.3, 0, 1.0), + (0, 0.8, 1.6666667), + ], +) +def test_get_doppler_factor_full_relativity(mu, beta, expected): + """ + Checks the get_doppler_factor_full_relativity. + + Parameters + ---------- + mu : float + Angle of movement of the packet. + beta : float + Velocity over speed of light for the packet. + expected : float + Expected value of the doppler factor. + """ + obtained = frame_transformations.get_doppler_factor_full_relativity( + mu, beta + ) + assert_almost_equal(obtained, expected) + + +@pytest.mark.parametrize( + ["mu", "r", "inv_t_exp", "expected"], + [ + (0.3, 7.5e14, 1 / 5.2e7, 1 / 0.9998556693818854), + (-0.3, 0, 1 / 2.6e7, 1.0), + (0, 1, 1 / 2.6e7, 1.0), + ], +) +def test_get_inverse_doppler_factor(mu, r, inv_t_exp, expected): + """ + Checks the get_inverse_doppler_factor function. + + Parameters + ---------- + mu : float + Angle of movement of the packet. + r : float + Radius of the position of the packet. + inv_t_exp : float + Inverse of t_explosion. + expected : float + Expected value of the inverse doppler factor. + """ + # Set the params from test cases here + time_explosion = 1 / inv_t_exp + + # Perform any other setups just before this, they can be additional calls + # to other methods or introduction of some temporary variables + + obtained = frame_transformations.get_inverse_doppler_factor( + r, mu, time_explosion, enable_full_relativity=False + ) + + # Perform required assertions + assert_almost_equal(obtained, expected) + + +@pytest.mark.parametrize( + ["mu", "beta", "expected"], + [ + (0.3, 0.2, 1 / 0.94), + (-0.3, 0, 1.0), + (0, 0.8, 1.0), + ], +) +def test_get_inverse_doppler_factor_partial_relativity(mu, beta, expected): + """ + Checks the get_inverse_doppler_factor_partial_relativity function. + + Parameters + ---------- + mu : float + Angle of movement of the packet. + beta : float + Velocity over speed of light for the packet. + expected : float + Expected value of the inverse doppler factor. + """ + obtained = ( + frame_transformations.get_inverse_doppler_factor_partial_relativity( + mu, beta + ) + ) + assert_almost_equal(obtained, expected) + + +@pytest.mark.parametrize( + ["mu", "beta", "expected"], + [ + (0.3, 0.2, 1.0818579), + (-0.3, 0, 1.0), + (0, 0.8, 1.6666667), + ], +) +def test_get_inverse_doppler_factor_full_relativity(mu, beta, expected): + """ + Checks the get_inverse_doppler_factor_full_relativity function. + + Parameters + ---------- + mu : float + Angle of movement of the packet. + beta : float + Velocity over speed of light for the packet. + expected : float + Expected value of the inverse doppler factor. + """ + obtained = frame_transformations.get_inverse_doppler_factor_full_relativity( + mu, beta + ) + assert_almost_equal(obtained, expected) diff --git a/tardis/util/__init__.py b/tardis/util/__init__.py index 6dd4694b3ef..e1b28566f74 100644 --- a/tardis/util/__init__.py +++ b/tardis/util/__init__.py @@ -1 +1,3 @@ -# Utilities for TARDIS +""" +Utilities for TARDIS. +""" diff --git a/tardis/util/base.py b/tardis/util/base.py index 3f36f80d9e1..8e21da9d667 100644 --- a/tardis/util/base.py +++ b/tardis/util/base.py @@ -9,13 +9,16 @@ import yaml from tardis import constants from astropy import units as u -from pyne import nucname +from radioactivedecay import Nuclide, DEFAULTDATA +from radioactivedecay.utils import parse_nuclide, Z_DICT import tardis from tardis.io.util import get_internal_data_path from IPython import get_ipython, display import tqdm import tqdm.notebook +import functools +import warnings k_B_cgs = constants.k_B.cgs.value c_cgs = constants.c.cgs.value @@ -29,7 +32,11 @@ ATOMIC_SYMBOLS_DATA = ( pd.read_csv( get_internal_data_path("atomic_symbols.dat"), - delim_whitespace=True, + # The argument `delim_whitespace` was changed to `sep` + # because the first one is deprecated since version 2.2.0. + # The regular expression means: the separation is one or + # more spaces together (simple space, tabs, new lines). + sep=r"\s+", names=["atomic_number", "symbol"], ) .set_index("atomic_number") @@ -180,7 +187,7 @@ def calculate_luminosity( ) flux_density = np.trapz(flux, wavelength) * (flux_unit * wavelength_unit) - luminosity = (flux_density * 4 * np.pi * distance ** 2).to("erg/s") + luminosity = (flux_density * 4 * np.pi * distance**2).to("erg/s") return luminosity.value, wavelength.min(), wavelength.max() @@ -191,7 +198,7 @@ def create_synpp_yaml(radial1d_mdl, fname, shell_no=0, lines_db=None): Parameters ---------- - radial1d_mdl : Radial1DModel + radial1d_mdl : SimulationState Inputted object that will be read into YAML file fname : str File name for the synpp yaml @@ -240,10 +247,10 @@ def create_synpp_yaml(radial1d_mdl, fname, shell_no=0, lines_db=None): ) yaml_reference["output"]["min_wl"] = float( - radial1d_mdl.runner.spectrum.wavelength.to("angstrom").value.min() + radial1d_mdl.transport.spectrum.wavelength.to("angstrom").value.min() ) yaml_reference["output"]["max_wl"] = float( - radial1d_mdl.runner.spectrum.wavelength.to("angstrom").value.max() + radial1d_mdl.transport.spectrum.wavelength.to("angstrom").value.max() ) # raise Exception("there's a problem here with units what units does synpp expect?") @@ -284,19 +291,19 @@ def create_synpp_yaml(radial1d_mdl, fname, shell_no=0, lines_db=None): yaml.dump(yaml_reference, stream=f, explicit_start=True) -def intensity_black_body(nu, T): +def intensity_black_body(nu, temperature): """ Calculate the intensity of a black-body according to the following formula .. math:: - I(\\nu, T) = \\frac{2h\\nu^3}{c^2}\\frac{1} + I(\\nu, temperature) = \\frac{2h\\nu^3}{c^2}\\frac{1} {e^{h\\nu \\beta_\\textrm{rad}} - 1} Parameters ---------- nu : float Frequency of light - T : float + temperature : float Temperature in kelvin Returns @@ -304,8 +311,8 @@ def intensity_black_body(nu, T): Intensity : float Returns the intensity of the black body """ - beta_rad = 1 / (k_B_cgs * T) - coefficient = 2 * h_cgs / c_cgs ** 2 + beta_rad = 1 / (k_B_cgs * temperature) + coefficient = 2 * h_cgs / c_cgs**2 intensity = ne.evaluate( "coefficient * nu**3 / " "(exp(h_cgs * nu * beta_rad) -1 )" ) @@ -386,7 +393,7 @@ def species_string_to_tuple(species_string): f"Given ion number ('{ion_number_string}') could not be parsed" ) - if ion_number > atomic_number: + if ion_number - 1 > atomic_number: raise ValueError( "Species given does not exist: ion number > atomic number" ) @@ -491,6 +498,33 @@ def reformat_element_symbol(element_string): return element_string[0].upper() + element_string[1:].lower() +def is_valid_nuclide_or_elem(input_nuclide): + """ + Parses nuclide string into symbol - mass number format and returns + whether the nuclide is either contained in the decay dataset or is a + raw element string. + + Parameters + ---------- + input_nuclide : str or int + Nuclide name string or element string. + + Returns + ------- + bool + Bool indicating if the input nuclide is contained in the decay dataset + or is a valid element. + """ + + try: + parse_nuclide(input_nuclide, DEFAULTDATA.nuclides, "ICRP-107") + is_nuclide = True + except: + is_nuclide = True if input_nuclide in Z_DICT.values() else False + + return is_nuclide + + def quantity_linspace(start, stop, num, **kwargs): """ Essentially the same input parameters as linspace, but @@ -546,7 +580,7 @@ def convert_abundances_format(fname, delimiter=r"\s+"): # Drop shell index column df.drop(df.columns[0], axis=1, inplace=True) # Assign header row - df.columns = [nucname.name(i) for i in range(1, df.shape[1] + 1)] + df.columns = [Z_DICT[i] for i in range(1, df.shape[1] + 1)] return df @@ -671,6 +705,14 @@ def update_packet_pbar(i, current_iteration, no_of_packets, total_iterations): packet_pbar.update(i) +def refresh_packet_pbar(): + """ + Refresh packet progress bar after each iteration. + + """ + packet_pbar.refresh() + + def update_iterations_pbar(i): """ Update progress bar for each iteration. @@ -725,3 +767,21 @@ def fix_bar_layout(bar, no_of_packets=None, total_iterations=None): bar.reset(total=total_iterations) else: pass + + +def deprecated(func): + """ + A decorator to add a deprecation warning to a function that is no longer used + + Parameters + ---------- + + func : function + """ + + @functools.wraps(func) + def wrapper(*args, **kwargs): + warnings.warn("This function is deprecated.", DeprecationWarning) + return func(*args, **kwargs) + + return wrapper diff --git a/tardis/visualization/__init__.py b/tardis/visualization/__init__.py index 4b806fdd147..19e4faadeac 100644 --- a/tardis/visualization/__init__.py +++ b/tardis/visualization/__init__.py @@ -7,5 +7,6 @@ shell_info_from_hdf, ) from tardis.visualization.widgets.line_info import LineInfoWidget +from tardis.visualization.widgets.grotrian import GrotrianWidget from tardis.visualization.widgets.custom_abundance import CustomAbundanceWidget from tardis.visualization.tools.sdec_plot import SDECPlotter diff --git a/tardis/visualization/tools/convergence_plot.py b/tardis/visualization/tools/convergence_plot.py index 56655036647..baac3ea0722 100644 --- a/tardis/visualization/tools/convergence_plot.py +++ b/tardis/visualization/tools/convergence_plot.py @@ -1,7 +1,9 @@ """Convergence Plots to see the convergence of the simulation in real time.""" + from collections import defaultdict import matplotlib.cm as cm import matplotlib.colors as clr +import numpy as np import plotly.graph_objects as go from IPython.display import display import matplotlib as mpl @@ -310,10 +312,12 @@ def build(self, display_plot=True): def update_plasma_plots(self): """Update plasma convergence plots every iteration.""" # convert velocity to km/s - x = self.iterable_data["velocity"].to(u.km / u.s).value.tolist() + velocity_km_s = ( + self.iterable_data["velocity"].to(u.km / u.s).value.tolist() + ) # add luminosity data in hover data in plasma plots - customdata = len(x) * [ + customdata = len(velocity_km_s) * [ "<br>" + "Emitted Luminosity: " + f'{self.value_data["Emitted"][-1]:.4g}' @@ -327,9 +331,12 @@ def update_plasma_plots(self): # add a radiation temperature vs shell velocity trace to the plasma plot self.plasma_plot.add_scatter( - x=x, - y=self.iterable_data["t_rad"], + x=velocity_km_s, + y=np.append( + self.iterable_data["t_rad"], self.iterable_data["t_rad"][-1:] + ), line_color=self.plasma_colorscale[self.current_iteration - 1], + line_shape="hv", row=1, col=1, name=self.current_iteration, @@ -341,9 +348,10 @@ def update_plasma_plots(self): # add a dilution factor vs shell velocity trace to the plasma plot self.plasma_plot.add_scatter( - x=x, - y=self.iterable_data["w"], + x=velocity_km_s, + y=np.append(self.iterable_data["w"], self.iterable_data["w"][-1:]), line_color=self.plasma_colorscale[self.current_iteration - 1], + line_shape="hv", row=1, col=2, legendgroup=f"group-{self.current_iteration}", @@ -424,7 +432,7 @@ def update(self, export_convergence_plots=False, last=False): # the display function expects a Widget, while # fig.show() returns None, which causes the TraitError. - if export_convergence_plots: + if export_convergence_plots and (self.plasma_plot is not None): with suppress(TraitError): display( widgets.VBox( diff --git a/tardis/visualization/tools/sdec_plot.py b/tardis/visualization/tools/sdec_plot.py index 75dd2bdf21a..578c64fe66a 100644 --- a/tardis/visualization/tools/sdec_plot.py +++ b/tardis/visualization/tools/sdec_plot.py @@ -4,28 +4,26 @@ This plot is a spectral diagnostics plot similar to those originally proposed by M. Kromer (see, for example, Kromer et al. 2013, figure 4). """ -import numpy as np -import pandas as pd -import astropy.units as u -import astropy.modeling.blackbody as abb +import logging -import matplotlib.pyplot as plt +import astropy.units as u import matplotlib.cm as cm import matplotlib.colors as clr +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd import plotly.graph_objects as go +from astropy.modeling.models import BlackBody from tardis.util.base import ( atomic_number2element_symbol, element_symbol2atomic_number, - species_string_to_tuple, - species_tuple_to_string, - roman_to_int, int_to_roman, + roman_to_int, + species_string_to_tuple, ) from tardis.visualization import plot_util as pu -import logging - logger = logging.getLogger(__name__) @@ -90,6 +88,7 @@ def __init__( Time of simulation, having unit of s (second) """ # Save packets properties in a dataframe for easier data manipulation + packet_nus = u.Quantity(packet_nus, u.Hz) self.packets_df = pd.DataFrame( { "nus": packet_nus, @@ -165,26 +164,31 @@ def from_simulation(cls, sim, packets_mode): lines_df = sim.plasma.atomic_data.lines.reset_index().set_index( "line_id" ) - r_inner = sim.model.r_inner - t_inner = sim.model.t_inner - time_of_simulation = sim.runner.time_of_simulation + transport_state = sim.transport.transport_state + r_inner = sim.simulation_state.geometry.r_inner_active + t_inner = sim.simulation_state.packet_source.temperature + time_of_simulation = ( + transport_state.packet_collection.time_of_simulation * u.s + ) if packets_mode == "virtual": return cls( - last_interaction_type=sim.runner.virt_packet_last_interaction_type, - last_line_interaction_in_id=sim.runner.virt_packet_last_line_interaction_in_id, - last_line_interaction_out_id=sim.runner.virt_packet_last_line_interaction_out_id, - last_line_interaction_in_nu=sim.runner.virt_packet_last_interaction_in_nu, + last_interaction_type=transport_state.vpacket_tracker.last_interaction_type, + last_line_interaction_in_id=transport_state.vpacket_tracker.last_interaction_in_id, + last_line_interaction_out_id=transport_state.vpacket_tracker.last_interaction_out_id, + last_line_interaction_in_nu=transport_state.vpacket_tracker.last_interaction_in_nu, lines_df=lines_df, - packet_nus=u.Quantity(sim.runner.virt_packet_nus, "Hz"), + packet_nus=u.Quantity( + transport_state.vpacket_tracker.nus, "Hz" + ), packet_energies=u.Quantity( - sim.runner.virt_packet_energies, "erg" + transport_state.vpacket_tracker.energies, "erg" ), r_inner=r_inner, - spectrum_delta_frequency=sim.runner.spectrum_virtual.delta_frequency, - spectrum_frequency_bins=sim.runner.spectrum_virtual._frequency, - spectrum_luminosity_density_lambda=sim.runner.spectrum_virtual.luminosity_density_lambda, - spectrum_wavelength=sim.runner.spectrum_virtual.wavelength, + spectrum_delta_frequency=transport_state.spectrum_virtual.delta_frequency, + spectrum_frequency_bins=transport_state.spectrum_virtual._frequency, + spectrum_luminosity_density_lambda=transport_state.spectrum_virtual.luminosity_density_lambda, + spectrum_wavelength=transport_state.spectrum_virtual.wavelength, t_inner=t_inner, time_of_simulation=time_of_simulation, ) @@ -192,29 +196,32 @@ def from_simulation(cls, sim, packets_mode): elif packets_mode == "real": # Packets-specific properties need to be only for those packets # which got emitted + transport_state = sim.transport.transport_state return cls( - last_interaction_type=sim.runner.last_interaction_type[ - sim.runner.emitted_packet_mask + last_interaction_type=transport_state.last_interaction_type[ + transport_state.emitted_packet_mask ], - last_line_interaction_in_id=sim.runner.last_line_interaction_in_id[ - sim.runner.emitted_packet_mask + last_line_interaction_in_id=transport_state.last_line_interaction_in_id[ + transport_state.emitted_packet_mask ], - last_line_interaction_out_id=sim.runner.last_line_interaction_out_id[ - sim.runner.emitted_packet_mask + last_line_interaction_out_id=transport_state.last_line_interaction_out_id[ + transport_state.emitted_packet_mask ], - last_line_interaction_in_nu=sim.runner.last_interaction_in_nu[ - sim.runner.emitted_packet_mask + last_line_interaction_in_nu=transport_state.last_interaction_in_nu[ + transport_state.emitted_packet_mask ], lines_df=lines_df, - packet_nus=sim.runner.output_nu[sim.runner.emitted_packet_mask], - packet_energies=sim.runner.output_energy[ - sim.runner.emitted_packet_mask + packet_nus=transport_state.packet_collection.output_nus[ + transport_state.emitted_packet_mask + ], + packet_energies=transport_state.packet_collection.output_energies[ + transport_state.emitted_packet_mask ], r_inner=r_inner, - spectrum_delta_frequency=sim.runner.spectrum.delta_frequency, - spectrum_frequency_bins=sim.runner.spectrum._frequency, - spectrum_luminosity_density_lambda=sim.runner.spectrum.luminosity_density_lambda, - spectrum_wavelength=sim.runner.spectrum.wavelength, + spectrum_delta_frequency=transport_state.spectrum.delta_frequency, + spectrum_frequency_bins=transport_state.spectrum._frequency, + spectrum_luminosity_density_lambda=transport_state.spectrum.luminosity_density_lambda, + spectrum_wavelength=transport_state.spectrum.wavelength, t_inner=t_inner, time_of_simulation=time_of_simulation, ) @@ -247,63 +254,67 @@ def from_hdf(cls, hdf_fpath, packets_mode): .set_index("line_id") ) r_inner = u.Quantity( - hdf["/simulation/model/r_inner"].to_numpy(), "cm" + hdf["/simulation/simulation_state/r_inner"].to_numpy(), "cm" ) # Convert pd.Series to np.array to construct quantity from it - t_inner = u.Quantity(hdf["/simulation/model/scalars"].t_inner, "K") + t_inner = u.Quantity( + hdf["/simulation/simulation_state/scalars"].t_inner, "K" + ) time_of_simulation = u.Quantity( - hdf["/simulation/runner/scalars"].time_of_simulation, "s" + hdf["/simulation/transport/scalars"].time_of_simulation, "s" ) if packets_mode == "virtual": return cls( last_interaction_type=hdf[ - "/simulation/runner/virt_packet_last_interaction_type" + "/simulation/transport/transport_state/virt_packet_last_interaction_type" ], last_line_interaction_in_id=hdf[ - "/simulation/runner/virt_packet_last_line_interaction_in_id" + "/simulation/transport/transport_state/virt_packet_last_line_interaction_in_id" ], last_line_interaction_out_id=hdf[ - "/simulation/runner/virt_packet_last_line_interaction_out_id" + "/simulation/transport/transport_state/virt_packet_last_line_interaction_out_id" ], last_line_interaction_in_nu=u.Quantity( hdf[ - "/simulation/runner/virt_packet_last_interaction_in_nu" + "/simulation/transport/transport_state/virt_packet_last_interaction_in_nu" ].to_numpy(), "Hz", ), lines_df=lines_df, packet_nus=u.Quantity( - hdf["/simulation/runner/virt_packet_nus"].to_numpy(), + hdf[ + "/simulation/transport/transport_state/virt_packet_nus" + ].to_numpy(), "Hz", ), packet_energies=u.Quantity( hdf[ - "/simulation/runner/virt_packet_energies" + "/simulation/transport/transport_state/virt_packet_energies" ].to_numpy(), "erg", ), r_inner=r_inner, spectrum_delta_frequency=u.Quantity( hdf[ - "/simulation/runner/spectrum_virtual/scalars" + "/simulation/transport/transport_state/spectrum_virtual/scalars" ].delta_frequency, "Hz", ), spectrum_frequency_bins=u.Quantity( hdf[ - "/simulation/runner/spectrum_virtual/_frequency" + "/simulation/transport/transport_state/spectrum_virtual/_frequency" ].to_numpy(), "Hz", ), spectrum_luminosity_density_lambda=u.Quantity( hdf[ - "/simulation/runner/spectrum_virtual/luminosity_density_lambda" + "/simulation/transport/transport_state/spectrum_virtual/luminosity_density_lambda" ].to_numpy(), "erg / s cm", # luminosity_density_lambda is saved in hdf in CGS ).to("erg / s AA"), spectrum_wavelength=u.Quantity( hdf[ - "/simulation/runner/spectrum_virtual/wavelength" + "/simulation/transport/transport_state/spectrum_virtual/wavelength" ].to_numpy(), "cm", # wavelength is saved in hdf in CGS ).to("AA"), @@ -313,61 +324,61 @@ def from_hdf(cls, hdf_fpath, packets_mode): elif packets_mode == "real": emitted_packet_mask = hdf[ - "/simulation/runner/emitted_packet_mask" + "/simulation/transport/transport_state/emitted_packet_mask" ].to_numpy() return cls( # First convert series read from hdf to array before masking # to eliminate index info which creates problems otherwise last_interaction_type=hdf[ - "/simulation/runner/last_interaction_type" + "/simulation/transport/transport_state/last_interaction_type" ].to_numpy()[emitted_packet_mask], last_line_interaction_in_id=hdf[ - "/simulation/runner/last_line_interaction_in_id" + "/simulation/transport/transport_state/last_line_interaction_in_id" ].to_numpy()[emitted_packet_mask], last_line_interaction_out_id=hdf[ - "/simulation/runner/last_line_interaction_out_id" + "/simulation/transport/transport_state/last_line_interaction_out_id" ].to_numpy()[emitted_packet_mask], last_line_interaction_in_nu=u.Quantity( hdf[ - "/simulation/runner/last_interaction_in_nu" + "/simulation/transport/transport_state/last_interaction_in_nu" ].to_numpy()[emitted_packet_mask], "Hz", ), lines_df=lines_df, packet_nus=u.Quantity( - hdf["/simulation/runner/output_nu"].to_numpy()[ - emitted_packet_mask - ], + hdf[ + "/simulation/transport/transport_state/output_nu" + ].to_numpy()[emitted_packet_mask], "Hz", ), packet_energies=u.Quantity( - hdf["/simulation/runner/output_energy"].to_numpy()[ - emitted_packet_mask - ], + hdf[ + "/simulation/transport/transport_state/output_energy" + ].to_numpy()[emitted_packet_mask], "erg", ), r_inner=r_inner, spectrum_delta_frequency=u.Quantity( hdf[ - "/simulation/runner/spectrum/scalars" + "/simulation/transport/transport_state/spectrum/scalars" ].delta_frequency, "Hz", ), spectrum_frequency_bins=u.Quantity( hdf[ - "/simulation/runner/spectrum/_frequency" + "/simulation/transport/transport_state/spectrum/_frequency" ].to_numpy(), "Hz", ), spectrum_luminosity_density_lambda=u.Quantity( hdf[ - "/simulation/runner/spectrum/luminosity_density_lambda" + "/simulation/transport/transport_state/spectrum/luminosity_density_lambda" ].to_numpy(), "erg / s cm", ).to("erg / s AA"), spectrum_wavelength=u.Quantity( hdf[ - "/simulation/runner/spectrum/wavelength" + "/simulation/transport/transport_state/spectrum/wavelength" ].to_numpy(), "cm", ).to("AA"), @@ -415,23 +426,23 @@ def from_simulation(cls, sim): ------- SDECPlotter """ - if sim.runner.virt_logging: + if sim.transport.transport_state.virt_logging: return cls( - dict( - virtual=SDECData.from_simulation(sim, "virtual"), - real=SDECData.from_simulation(sim, "real"), - ) + { + "virtual": SDECData.from_simulation(sim, "virtual"), + "real": SDECData.from_simulation(sim, "real"), + } ) else: return cls( - dict( - virtual=None, - real=SDECData.from_simulation(sim, "real"), - ) + { + "virtual": None, + "real": SDECData.from_simulation(sim, "real"), + } ) @classmethod - def from_hdf(cls, hdf_fpath): + def from_hdf(cls, hdf_fpath, packets_mode=None): """ Create an instance of SDECPlotter from a simulation HDF file. @@ -439,17 +450,39 @@ def from_hdf(cls, hdf_fpath): ---------- hdf_fpath : str Valid path to the HDF file where simulation is saved + packets_mode : {'virtual', 'real'}, optional + Mode of packets to be considered, either real or virtual. If not + specified, both modes are returned Returns ------- SDECPlotter """ - return cls( - dict( - virtual=SDECData.from_hdf(hdf_fpath, "virtual"), - real=SDECData.from_hdf(hdf_fpath, "real"), - ) + assert packets_mode in [None, "virtual", "real"], ( + "Invalid value passed to packets_mode. Only " + "allowed values are 'virtual', 'real' or None" ) + if packets_mode == "virtual": + return cls( + { + "virtual": SDECData.from_hdf(hdf_fpath, "virtual"), + "real": None, + } + ) + elif packets_mode == "real": + return cls( + { + "virtual": None, + "real": SDECData.from_hdf(hdf_fpath, "real"), + } + ) + else: + return cls( + { + "virtual": SDECData.from_hdf(hdf_fpath, "virtual"), + "real": SDECData.from_hdf(hdf_fpath, "real"), + } + ) def _parse_species_list(self, species_list): """ @@ -463,12 +496,11 @@ def _parse_species_list(self, species_list): (e.g. Si I - V), or any combination of these (e.g. species_list = [Si II, Fe I-V, Ca]) """ - if species_list is not None: # check if there are any digits in the species list. If there are, then exit. # species_list should only contain species in the Roman numeral # format, e.g. Si II, and each ion must contain a space - if any(char.isdigit() for char in " ".join(species_list)) == True: + if any(char.isdigit() for char in " ".join(species_list)) is True: raise ValueError( "All species must be in Roman numeral form, e.g. Si II" ) @@ -594,7 +626,7 @@ def _calculate_plotting_data( self.plot_frequency = self.data[packets_mode].spectrum_frequency # Filter their plottable range based on packet_wvl_range specified - if packet_wvl_range: + if packet_wvl_range is not None: packet_nu_range = packet_wvl_range.to("Hz", u.spectral()) # Index of value just before the 1st value that is > packet_nu_range[1] @@ -694,7 +726,7 @@ def _calculate_plotting_data( # Repeat this for the emission and absorption dfs # This will require creating a temporary list that includes 'noint' and 'escatter' # packets, because you don't want them dropped or included in 'other' - temp = [species for species in self._species_list] + temp = list(self._species_list) temp.append("noint") temp.append("escatter") mask = np.in1d( @@ -718,7 +750,7 @@ def _calculate_plotting_data( axis=1, ) - temp = [species for species in self._species_list] + temp = list(self._species_list) mask = np.in1d( np.array(list(self.absorption_luminosities_df.keys())), temp ) @@ -868,7 +900,7 @@ def _calculate_emission_luminosities(self, packets_mode, packet_wvl_range): self.data[packets_mode].packets_df["nus"][ self.packet_nu_range_mask ][mask_noint], - bins=self.plot_frequency_bins, + bins=self.plot_frequency_bins.value, weights=weights[mask_noint], density=False, ) @@ -901,7 +933,7 @@ def _calculate_emission_luminosities(self, packets_mode, packet_wvl_range): self.data[packets_mode].packets_df["nus"][ self.packet_nu_range_mask ][mask_escatter], - bins=self.plot_frequency_bins, + bins=self.plot_frequency_bins.value, weights=weights[mask_escatter], density=False, ) @@ -938,7 +970,7 @@ def _calculate_emission_luminosities(self, packets_mode, packet_wvl_range): # Histogram of specific species hist_el = np.histogram( group["nus"], - bins=self.plot_frequency_bins, + bins=self.plot_frequency_bins.value, weights=group["energies"] / self.lum_to_flux / self.data[packets_mode].time_of_simulation, @@ -1026,7 +1058,7 @@ def _calculate_absorption_luminosities( # Histogram of specific species hist_el = np.histogram( group["last_line_interaction_in_nu"], - bins=self.plot_frequency_bins, + bins=self.plot_frequency_bins.value, weights=group["energies"] / self.lum_to_flux / self.data[packets_mode].time_of_simulation, @@ -1064,13 +1096,15 @@ def _calculate_photosphere_luminosity(self, packets_mode): Luminosity density lambda (or Flux) of photosphere (inner boundary of TARDIS simulation) """ + bb_lam = BlackBody( + self.data[packets_mode].t_inner, + scale=1.0 * u.erg / (u.cm**2 * u.AA * u.s * u.sr), + ) + L_lambda_ph = ( - abb.blackbody_lambda( - self.plot_wavelength, - self.data[packets_mode].t_inner, - ) + bb_lam(self.plot_wavelength) * 4 - * np.pi ** 2 + * np.pi**2 * self.data[packets_mode].r_inner[0] ** 2 * u.sr ).to("erg / (AA s)") @@ -1089,6 +1123,7 @@ def generate_plot_mpl( cmapname="jet", nelements=None, species_list=None, + blackbody_photosphere=True, ): """ Generate Spectral element DEComposition (SDEC) Plot using matplotlib. @@ -1132,13 +1167,14 @@ def generate_plot_mpl( Must be given in Roman numeral format. Can include specific ions, a range of ions, individual elements, or any combination of these: e.g. ['Si II', 'Ca II', 'C', 'Fe I-V'] + blackbody_photosphere: bool + Whether to include the blackbody photosphere in the plot. Default value is True Returns ------- matplotlib.axes._subplots.AxesSubplot Axis on which SDEC Plot is created """ - # If species_list and nelements requested, tell user that nelements is ignored if species_list is not None and nelements is not None: logger.info( @@ -1189,7 +1225,7 @@ def generate_plot_mpl( if distance is None: raise ValueError( """ - Distance must be specified if an observed_spectrum is given + Distance must be specified if an observed_spectrum is given so that the model spectrum can be converted into flux space correctly. """ ) @@ -1210,17 +1246,18 @@ def generate_plot_mpl( ) # Plot photosphere - self.ax.plot( - self.plot_wavelength.value, - self.photosphere_luminosity.value, - "--r", - label="Blackbody Photosphere", - ) + if blackbody_photosphere: + self.ax.plot( + self.plot_wavelength.value, + self.photosphere_luminosity.value, + "--r", + label="Blackbody Photosphere", + ) # Set legends and labels self.ax.legend(fontsize=12) self.ax.set_xlabel(r"Wavelength $[\mathrm{\AA}]$", fontsize=12) - if distance: # Set y-axis label for flux + if distance is not None: # Set y-axis label for flux self.ax.set_ylabel( r"$F_{\lambda}$ [erg $\mathrm{s^{-1}}$ $\mathrm{cm^{-2}}$ $\mathrm{\AA^{-1}}$]", fontsize=12, @@ -1295,23 +1332,25 @@ def _plot_emission_mpl(self): cmap=self.cmap, linewidth=0, ) - except: + except KeyError: # Add notifications that this species was not in the emission df if self._species_list is None: - logger.info( + info_msg = ( f"{atomic_number2element_symbol(identifier)}" f" is not in the emitted packets; skipping" ) + logger.info(info_msg) else: # Get the ion number and atomic number for each species ion_number = identifier % 100 atomic_number = (identifier - ion_number) / 100 - logger.info( + info_msg = ( f"{atomic_number2element_symbol(atomic_number)}" f"{int_to_roman(ion_number + 1)}" f" is not in the emitted packets; skipping" ) + logger.info(info_msg) def _plot_absorption_mpl(self): """Plot absorption part of the SDEC Plot using matplotlib.""" @@ -1351,27 +1390,28 @@ def _plot_absorption_mpl(self): linewidth=0, ) - except: + except KeyError: # Add notifications that this species was not in the emission df if self._species_list is None: - logger.info( + info_msg = ( f"{atomic_number2element_symbol(identifier)}" f" is not in the absorbed packets; skipping" ) + logger.info(info_msg) else: # Get the ion number and atomic number for each species ion_number = identifier % 100 atomic_number = (identifier - ion_number) / 100 - logger.info( + info_msg = ( f"{atomic_number2element_symbol(atomic_number)}" f"{int_to_roman(ion_number + 1)}" f" is not in the absorbed packets; skipping" ) + logger.info(info_msg) def _show_colorbar_mpl(self): """Show matplotlib colorbar with labels of elements mapped to colors.""" - color_values = [ self.cmap(species_counter / len(self._species_name)) for species_counter in range(len(self._species_name)) @@ -1445,13 +1485,11 @@ def _make_colorbar_colors(self): if previous_atomic_number == 0: # If this is the first species being plotted, then take note of the atomic number # don't update the colour index - color_counter = color_counter previous_atomic_number = atomic_number elif previous_atomic_number in self._keep_colour: # If the atomic number is in the list of elements that should all be plotted in the same colour # then don't update the colour index if this element has been plotted already if previous_atomic_number == atomic_number: - color_counter = color_counter previous_atomic_number = atomic_number else: # Otherwise, increase the colour counter by one, because this is a new element @@ -1485,6 +1523,7 @@ def generate_plot_ply( cmapname="jet", nelements=None, species_list=None, + blackbody_photosphere=True, ): """ Generate interactive Spectral element DEComposition (SDEC) Plot using plotly. @@ -1528,12 +1567,14 @@ def generate_plot_ply( Must be given in Roman numeral format. Can include specific ions, a range of ions, individual elements, or any combination of these: e.g. ['Si II', 'Ca II', 'C', 'Fe I-V'] + blackbody_photosphere: bool + Whether to include the blackbody photosphere in the plot. Default value is True + Returns ------- plotly.graph_objs._figure.Figure Figure object on which SDEC Plot is created """ - # If species_list and nelements requested, tell user that nelements is ignored if species_list is not None and nelements is not None: logger.info( @@ -1575,13 +1616,13 @@ def generate_plot_ply( x=self.plot_wavelength.value, y=self.modeled_spectrum_luminosity.value, mode="lines", - line=dict( - color="blue", - width=1, - ), + line={ + "color": "blue", + "width": 1, + }, name=f"{packets_mode.capitalize()} Spectrum", hovertemplate="(%{x:.2f}, %{y:.3g})", - hoverlabel=dict(namelength=-1), + hoverlabel={"namelength": -1}, ) ) @@ -1590,7 +1631,7 @@ def generate_plot_ply( if distance is None: raise ValueError( """ - Distance must be specified if an observed_spectrum is given + Distance must be specified if an observed_spectrum is given so that the model spectrum can be converted into flux space correctly. """ ) @@ -1607,28 +1648,29 @@ def generate_plot_ply( y=observed_spectrum_flux.value, name="Observed Spectrum", line={"color": "black", "width": 1.2}, - hoverlabel=dict(namelength=-1), + hoverlabel={"namelength": -1}, hovertemplate="(%{x:.2f}, %{y:.3g})", ) # Plot photosphere - self.fig.add_trace( - go.Scatter( - x=self.plot_wavelength.value, - y=self.photosphere_luminosity.value, - mode="lines", - line=dict(width=1.5, color="red", dash="dash"), - name="Blackbody Photosphere", - hoverlabel=dict(namelength=-1), - hovertemplate="(%{x:.2f}, %{y:.3g})", + if blackbody_photosphere: + self.fig.add_trace( + go.Scatter( + x=self.plot_wavelength.value, + y=self.photosphere_luminosity.value, + mode="lines", + line={"width": 1.5, "color": "red", "dash": "dash"}, + name="Blackbody Photosphere", + hoverlabel={"namelength": -1}, + hovertemplate="(%{x:.2f}, %{y:.3g})", + ) ) - ) self._show_colorbar_ply() # Set label and other layout options xlabel = pu.axis_label_in_latex("Wavelength", u.AA) - if distance: # Set y-axis label for flux + if distance is not None: # Set y-axis label for flux ylabel = pu.axis_label_in_latex( "F_{\\lambda}", u.Unit("erg/(s cm**2 AA)"), only_text=False ) @@ -1637,11 +1679,11 @@ def generate_plot_ply( "L_{\\lambda}", u.Unit("erg/(s AA)"), only_text=False ) self.fig.update_layout( - xaxis=dict( - title=xlabel, - exponentformat="none", - ), - yaxis=dict(title=ylabel, exponentformat="e"), + xaxis={ + "title": xlabel, + "exponentformat": "none", + }, + yaxis={"title": ylabel, "exponentformat": "e"}, height=graph_height, ) @@ -1690,7 +1732,7 @@ def _plot_emission_ply(self): name="Electron Scatter Only", fillcolor="#8F8F8F", stackgroup="emission", - hoverlabel=dict(namelength=-1), + hoverlabel={"namelength": -1}, hovertemplate="(%{x:.2f}, %{y:.3g})", ) ) @@ -1720,37 +1762,38 @@ def _plot_emission_ply(self): y=self.emission_luminosities_df[identifier], mode="none", name=species_name + " Emission", - hovertemplate=f"<b>{species_name} Emission </b>" + hovertemplate=f"<b>{species_name:s} Emission<br>" # noqa: ISC003 + "(%{x:.2f}, %{y:.3g})<extra></extra>", fillcolor=self.to_rgb255_string( self._color_list[species_counter] ), stackgroup="emission", showlegend=False, - hoverlabel=dict(namelength=-1), + hoverlabel={"namelength": -1}, ) ) - except: + except KeyError: # Add notifications that this species was not in the emission df if self._species_list is None: - logger.info( + info_msg = ( f"{atomic_number2element_symbol(identifier)}" f" is not in the emitted packets; skipping" ) + logger.info(info_msg) else: # Get the ion number and atomic number for each species ion_number = identifier % 100 atomic_number = (identifier - ion_number) / 100 - logger.info( + info_msg = ( f"{atomic_number2element_symbol(atomic_number)}" f"{int_to_roman(ion_number + 1)}" f" is not in the emitted packets; skipping" ) + logger.info(info_msg) def _plot_absorption_ply(self): """Plot absorption part of the SDEC Plot using plotly.""" - # If 'other' column exists then plot as silver if "other" in self.absorption_luminosities_df.keys(): self.fig.add_trace( @@ -1778,34 +1821,36 @@ def _plot_absorption_ply(self): y=self.absorption_luminosities_df[identifier] * -1, mode="none", name=species_name + " Absorption", - hovertemplate=f"<b>{species_name} Absorption </b>" + hovertemplate=f"<b>{species_name:s} Absorption<br>" # noqa: ISC003 + "(%{x:.2f}, %{y:.3g})<extra></extra>", fillcolor=self.to_rgb255_string( self._color_list[species_counter] ), stackgroup="absorption", showlegend=False, - hoverlabel=dict(namelength=-1), + hoverlabel={"namelength": -1}, ) ) - except: + except KeyError: # Add notifications that this species was not in the emission df if self._species_list is None: - logger.info( + info_msg = ( f"{atomic_number2element_symbol(identifier)}" f" is not in the absorbed packets; skipping" ) + logger.info(info_msg) else: # Get the ion number and atomic number for each species ion_number = identifier % 100 atomic_number = (identifier - ion_number) / 100 - logger.info( + info_msg = ( f"{atomic_number2element_symbol(atomic_number)}" f"{int_to_roman(ion_number + 1)}" f" is not in the absorbed packets; skipping" ) + logger.info(info_msg) def _show_colorbar_ply(self): """Show plotly colorbar with labels of elements mapped to colors.""" @@ -1827,21 +1872,21 @@ def _show_colorbar_ply(self): (colorscale_bins[species_counter + 1], color) ) - coloraxis_options = dict( - colorscale=categorical_colorscale, - showscale=True, - cmin=0, - cmax=len(self._species_name), - colorbar=dict( - title="Elements", - tickvals=np.arange(0, len(self._species_name)) + 0.5, - ticktext=self._species_name, + coloraxis_options = { + "colorscale": categorical_colorscale, + "showscale": True, + "cmin": 0, + "cmax": len(self._species_name), + "colorbar": { + "title": "Elements", + "tickvals": np.arange(0, len(self._species_name)) + 0.5, + "ticktext": self._species_name, # to change length and position of colorbar - len=0.75, - yanchor="top", - y=0.75, - ), - ) + "len": 0.75, + "yanchor": "top", + "y": 0.75, + }, + } # Plot an invisible one point scatter trace, to make colorbar show up scatter_point_idx = pu.get_mid_point_idx(self.plot_wavelength) diff --git a/tardis/visualization/tools/tests/test_convergence_plot.py b/tardis/visualization/tools/tests/test_convergence_plot.py index 00043cb7837..bb69e23e68b 100644 --- a/tardis/visualization/tools/tests/test_convergence_plot.py +++ b/tardis/visualization/tools/tests/test_convergence_plot.py @@ -1,5 +1,10 @@ """Tests for Convergence Plots.""" + +from copy import deepcopy + import pytest +from tardis.tests.test_util import monkeysession +from tardis import run_tardis from tardis.visualization.tools.convergence_plot import ( ConvergencePlots, transition_colors, @@ -139,7 +144,9 @@ def test_update_plasma_plots(convergence_plots): # check values for t_rad subplot assert convergence_plots.plasma_plot.data[index].xaxis == "x" assert convergence_plots.plasma_plot.data[index].yaxis == "y" - assert convergence_plots.plasma_plot.data[index].y == tuple(t_rad_val) + assert ( + convergence_plots.plasma_plot.data[index].y[:-1] == tuple(t_rad_val) + ).all() assert convergence_plots.plasma_plot.data[index].x == tuple( velocity.to(u.km / u.s).value ) @@ -148,7 +155,9 @@ def test_update_plasma_plots(convergence_plots): # check values for w subplot assert convergence_plots.plasma_plot.data[index].xaxis == "x2" assert convergence_plots.plasma_plot.data[index].yaxis == "y2" - assert convergence_plots.plasma_plot.data[index].y == tuple(w_val) + assert ( + convergence_plots.plasma_plot.data[index].y[:-1] == tuple(w_val) + ).all() assert convergence_plots.plasma_plot.data[index].x == tuple( velocity.to(u.km / u.s).value ) @@ -205,3 +214,19 @@ def test_override_plot_parameters(convergence_plots): assert ( convergence_plots.plasma_plot["layout"]["xaxis2"]["showgrid"] == False ) + + +def test_convergence_plot_command_line( + config_verysimple, atomic_dataset, monkeysession +): + monkeysession.setattr( + "tardis.simulation.base.is_notebook", + lambda: False, + ) + atomic_data = deepcopy(atomic_dataset) + with pytest.raises(RuntimeError): + run_tardis( + config_verysimple, + atom_data=atomic_data, + show_convergence_plots=True, + ) diff --git a/tardis/visualization/tools/tests/test_sdec_plot.py b/tardis/visualization/tools/tests/test_sdec_plot.py index 1a4fd79f4ec..a92454a89fc 100644 --- a/tardis/visualization/tools/tests/test_sdec_plot.py +++ b/tardis/visualization/tools/tests/test_sdec_plot.py @@ -1,16 +1,17 @@ """Tests for SDEC Plots.""" -from tardis.base import run_tardis -import pytest -import pandas as pd -import numpy as np import os from copy import deepcopy -from tardis.visualization.tools.sdec_plot import SDECData, SDECPlotter + import astropy.units as u +import numpy as np +import pandas as pd +import pytest +import tables from matplotlib.collections import PolyCollection from matplotlib.lines import Line2D -import tables -import re + +from tardis.base import run_tardis +from tardis.visualization.tools.sdec_plot import SDECPlotter def make_valid_name(testid): @@ -143,7 +144,7 @@ def observed_spectrum(self): observed_spectrum_wavelength, observed_spectrum_flux = test_data.T observed_spectrum_wavelength = observed_spectrum_wavelength * u.AA observed_spectrum_flux = ( - observed_spectrum_flux * u.erg / (u.s * u.cm ** 2 * u.AA) + observed_spectrum_flux * u.erg / (u.s * u.cm**2 * u.AA) ) return observed_spectrum_wavelength, observed_spectrum_flux @@ -158,6 +159,7 @@ def test_parse_species_list(self, request, plotter, species): plotter : tardis.visualization.tools.sdec_plot.SDECPlotter species : list """ + # THIS NEEDS TO BE RUN FIRST. NOT INDEPENDENT TESTS plotter._parse_species_list(species) subgroup_name = make_valid_name(request.node.callspec.id) if request.config.getoption("--generate-reference"): @@ -408,12 +410,14 @@ def test_generate_plot_mpl( species_list : list of str """ subgroup_name = make_valid_name("mpl" + request.node.callspec.id) + if distance is None: + observed_spectrum = None fig = plotter.generate_plot_mpl( packets_mode=packets_mode, packet_wvl_range=packet_wvl_range, distance=distance, show_modeled_spectrum=show_modeled_spectrum, - observed_spectrum=observed_spectrum if distance else None, + observed_spectrum=observed_spectrum, nelements=nelements, species_list=species_list, ) @@ -549,12 +553,16 @@ def test_generate_plot_ply( species_list : list of str """ subgroup_name = make_valid_name("ply" + request.node.callspec.id) + if distance is not None: + observed_spectrum = observed_spectrum + else: + observed_spectrum = None fig = plotter.generate_plot_ply( packets_mode=packets_mode, packet_wvl_range=packet_wvl_range, distance=distance, show_modeled_spectrum=show_modeled_spectrum, - observed_spectrum=observed_spectrum if distance else None, + observed_spectrum=observed_spectrum, nelements=nelements, species_list=species_list, ) diff --git a/tardis/visualization/widgets/custom_abundance.py b/tardis/visualization/widgets/custom_abundance.py index 62ab7b6ed35..82a986cf41f 100644 --- a/tardis/visualization/widgets/custom_abundance.py +++ b/tardis/visualization/widgets/custom_abundance.py @@ -6,21 +6,27 @@ import ipywidgets as ipw import plotly.graph_objects as go from astropy import units as u -from pyne import nucname +from radioactivedecay import Nuclide +from radioactivedecay.utils import Z_DICT, elem_to_Z from pathlib import Path import tardis -from tardis.util.base import quantity_linspace -from tardis.io.config_reader import Configuration -from tardis.model import Radial1DModel -from tardis.model.density import ( +from tardis.io.model.readers.generic_readers import read_uniform_abundances +from tardis.util.base import ( + quantity_linspace, + is_valid_nuclide_or_elem, + is_notebook, +) +from tardis.io.configuration.config_reader import Configuration +from tardis.model import SimulationState +from tardis.io.model.parse_density_configuration import ( calculate_power_law_density, calculate_exponential_density, ) -from tardis.io.config_validator import validate_dict -from tardis.io.parsers.csvy import load_csvy -from tardis.io.model_reader import ( - read_uniform_abundances, +from tardis.io.atom_data.base import AtomData +from tardis.io.configuration.config_validator import validate_dict +from tardis.io.model.readers.csvy import load_csvy +from tardis.io.model.readers.csvy import ( parse_csv_abundances, ) from tardis.util.base import atomic_number2element_symbol, quantity_linspace @@ -181,7 +187,7 @@ def from_csvy(cls, fpath): ) @classmethod - def from_yml(cls, fpath): + def from_yml(cls, fpath, atom_data=None): """Create a new CustomAbundanceWidgetData instance with data from YAML file. @@ -195,22 +201,29 @@ def from_yml(cls, fpath): CustomAbundanceWidgetData """ config = Configuration.from_yaml(fpath) - + if atom_data is None: + atom_data = AtomData.from_hdf(config.atom_data) if hasattr(config, "csvy_model"): - model = Radial1DModel.from_csvy(config) + simulation_state = SimulationState.from_csvy( + config, atom_data=atom_data + ) else: - model = Radial1DModel.from_config(config) + simulation_state = SimulationState.from_config( + config, atom_data=atom_data + ) - velocity = model.velocity - density_t_0 = model.homologous_density.time_0 - density = model.homologous_density.density_0 - abundance = model.raw_abundance - isotope_abundance = model.raw_isotope_abundance + velocity = simulation_state.velocity + density_t_0 = simulation_state.time_explosion + density = simulation_state.density + abundance = simulation_state.abundance + isotopic_mass_fraction = ( + simulation_state.composition.isotopic_mass_fraction + ) # Combine elements and isotopes to one DataFrame abundance["mass_number"] = "" abundance.set_index("mass_number", append=True, inplace=True) - abundance = pd.concat([abundance, isotope_abundance]) + abundance = pd.concat([abundance, isotopic_mass_fraction]) abundance.sort_index(inplace=True) return cls( @@ -268,8 +281,10 @@ def from_simulation(cls, sim): ------- CustomAbundanceWidgetData """ - abundance = sim.model.raw_abundance.copy() - isotope_abundance = sim.model.raw_isotope_abundance.copy() + abundance = sim.simulation_state.abundance.copy() + isotope_abundance = ( + sim.simulation_state.composition.raw_isotope_abundance.copy() + ) # integrate element and isotope to one DataFrame abundance["mass_number"] = "" @@ -277,9 +292,9 @@ def from_simulation(cls, sim): abundance = pd.concat([abundance, isotope_abundance]) abundance.sort_index(inplace=True) - velocity = sim.model.velocity - density_t_0 = sim.model.homologous_density.time_0 - density = sim.model.homologous_density.density_0 + velocity = sim.simulation_state.velocity + density_t_0 = sim.simulation_state.time_explosion + density = sim.simulation_state.density return cls( density_t_0=density_t_0, @@ -999,9 +1014,7 @@ def input_symb_eventhandler(self, obj): return try: - if nucname.iselement(element_symbol_string) or nucname.isnuclide( - element_symbol_string - ): + if is_valid_nuclide_or_elem(element_symbol_string): self.symb_warning.layout.visibility = "hidden" self.btn_add_element.disabled = False return @@ -1024,12 +1037,13 @@ def on_btn_add_element(self, obj): """ element_symbol_string = self.input_symb.value.capitalize() - if element_symbol_string in nucname.name_zz: - z = nucname.name_zz[element_symbol_string] + if element_symbol_string in Z_DICT.values(): + z = elem_to_Z(element_symbol_string) self.data.abundance.loc[(z, ""), :] = 0 else: - mass_no = nucname.anum(element_symbol_string) - z = nucname.znum(element_symbol_string) + nuc = Nuclide(element_symbol_string) + mass_no = nuc.A + z = nuc.Z self.data.abundance.loc[(z, mass_no), :] = 0 self.data.abundance.sort_index(inplace=True) @@ -1276,109 +1290,114 @@ def display(self, cmap="jet"): ipywidgets.widgets.widget_box.VBox A box that contains all the widgets in the GUI. """ - # --------------Combine widget components-------------- - self.box_editor = ipw.HBox( - [ - ipw.VBox(self.input_items), - ipw.VBox(self.checks, layout=ipw.Layout(margin="0 0 0 10px")), - ] - ) - - box_add_shell = ipw.HBox( - [ - self.input_v_start, - self.input_v_end, - self.btn_add_shell, - self.overwrite_warning, - ], - layout=ipw.Layout(margin="0 0 0 50px"), - ) - - box_head = ipw.HBox( - [self.dpd_shell_no, self.btn_prev, self.btn_next, box_add_shell] - ) + if not is_notebook(): + print("Please use a notebook to display the widget") + else: + # --------------Combine widget components-------------- + self.box_editor = ipw.HBox( + [ + ipw.VBox(self.input_items), + ipw.VBox( + self.checks, layout=ipw.Layout(margin="0 0 0 10px") + ), + ] + ) - box_add_element = ipw.HBox( - [self.input_symb, self.btn_add_element, self.symb_warning], - layout=ipw.Layout(margin="0 0 0 80px"), - ) + box_add_shell = ipw.HBox( + [ + self.input_v_start, + self.input_v_end, + self.btn_add_shell, + self.overwrite_warning, + ], + layout=ipw.Layout(margin="0 0 0 50px"), + ) - help_note = ipw.HTML( - value="<p style='text-indent: 40px'>* Select a checkbox " - "to lock the abundance of corresponding element. </p>" - "<p style='text-indent: 40px'> On clicking the 'Normalize' " - "button, the locked abundance(s) will <b>not be normalized</b>." - " </p>", - indent=True, - ) + box_head = ipw.HBox( + [self.dpd_shell_no, self.btn_prev, self.btn_next, box_add_shell] + ) - self.abundance_note = ipw.HTML( - description="(The following abundances are for the innermost " - "shell in selected range.)", - layout=ipw.Layout(visibility="hidden"), - style={"description_width": "initial"}, - ) + box_add_element = ipw.HBox( + [self.input_symb, self.btn_add_element, self.symb_warning], + layout=ipw.Layout(margin="0 0 0 80px"), + ) - box_norm = ipw.HBox([self.btn_norm, self.norm_warning]) + help_note = ipw.HTML( + value="<p style='text-indent: 40px'>* Select a checkbox " + "to lock the abundance of corresponding element. </p>" + "<p style='text-indent: 40px'> On clicking the 'Normalize' " + "button, the locked abundance(s) will <b>not be normalized</b>." + " </p>", + indent=True, + ) - box_apply = ipw.VBox( - [ - ipw.Label(value="Apply abundance(s) to:"), - self.rbs_single_apply, - ipw.HBox( - [ - self.rbs_multi_apply, - self.irs_shell_range, - self.abundance_note, - ] - ), - ], - layout=ipw.Layout(margin="0 0 15px 50px"), - ) + self.abundance_note = ipw.HTML( + description="(The following abundances are for the innermost " + "shell in selected range.)", + layout=ipw.Layout(visibility="hidden"), + style={"description_width": "initial"}, + ) - box_features = ipw.VBox([box_norm, help_note]) - box_abundance = ipw.VBox( - [ - box_apply, - ipw.HBox([self.box_editor, box_features]), - box_add_element, - ] - ) - box_density = self.density_editor.display() + box_norm = ipw.HBox([self.btn_norm, self.norm_warning]) + + box_apply = ipw.VBox( + [ + ipw.Label(value="Apply abundance(s) to:"), + self.rbs_single_apply, + ipw.HBox( + [ + self.rbs_multi_apply, + self.irs_shell_range, + self.abundance_note, + ] + ), + ], + layout=ipw.Layout(margin="0 0 15px 50px"), + ) - main_tab = ipw.Tab([box_abundance, box_density]) - main_tab.set_title(0, "Edit Abundance") - main_tab.set_title(1, "Edit Density") + box_features = ipw.VBox([box_norm, help_note]) + box_abundance = ipw.VBox( + [ + box_apply, + ipw.HBox([self.box_editor, box_features]), + box_add_element, + ] + ) + box_density = self.density_editor.display() - hint = ipw.HTML( - value="<b><font size='3'>Save model as file: </font></b>" - ) - box_output = ipw.VBox( - [ - hint, - self.input_i_time_0, - ipw.HBox( - [self.input_path, self.btn_output, self.ckb_overwrite] - ), - ] - ) + main_tab = ipw.Tab([box_abundance, box_density]) + main_tab.set_title(0, "Edit Abundance") + main_tab.set_title(1, "Edit Density") - # Initialize the widget and plot colormap - self.plot_cmap = cmap - self.update_line_color() - self.read_abundance() - self.density_editor.read_density() + hint = ipw.HTML( + value="<b><font size='3'>Save model as file: </font></b>" + ) + box_output = ipw.VBox( + [ + hint, + self.input_i_time_0, + ipw.HBox( + [self.input_path, self.btn_output, self.ckb_overwrite] + ), + ] + ) - return ipw.VBox( - [ - self.tbs_scale, - self.fig, - box_head, - main_tab, - box_output, - self.error_view, - ] - ) + # Initialize the widget and plot colormap + self.plot_cmap = cmap + self.update_line_color() + self.read_abundance() + self.density_editor.read_density() + + return ipw.VBox( + [ + self.tbs_scale, + self.fig, + box_head, + main_tab, + box_output, + self.error_view, + ] + ) @error_view.capture(clear_output=True) def to_csvy(self, path, overwrite): diff --git a/tardis/visualization/widgets/grotrian.py b/tardis/visualization/widgets/grotrian.py new file mode 100644 index 00000000000..6c3558f769c --- /dev/null +++ b/tardis/visualization/widgets/grotrian.py @@ -0,0 +1,1211 @@ +""" +Grotrian Diagram Widget for TARDIS simulation models. + +This widget displays a Grotrian Diagram of the last line interactions of the simulation packets +""" +from tardis.analysis import LastLineInteraction +from tardis.util.base import species_tuple_to_string, species_string_to_tuple +from tardis.util.base import int_to_roman +import plotly.graph_objects as go +from plotly.subplots import make_subplots +import numpy as np +import pandas as pd +import matplotlib +import matplotlib.pyplot as plt +from astropy import units as u +import ipywidgets as ipw + +ANGSTROM_SYMBOL = "\u212B" + + +def is_zero_defined(transform): + """ + Utility function to decide if a certain transform is defined at zero + + Parameters + ---------- + transform : function + + Returns + ------- + bool + True if transform is defined at 0 else False + """ + if transform in [np.log, np.log10]: + return True + return False + + +def standardize( + values, + transform=lambda x: x, + min_value=None, + max_value=None, + zero_undefined_offset=0, +): + """ + Utility function to standardize displayed values like wavelengths, num_packets, levels populations to the range [0, 1] + This helps in computing visual elements like widths, colors, etc. + + Parameters + ---------- + values : pandas.Series + The data to standardize + transform : function, optional + Transformations like np.log, np.exp, etc. to apply on the data. Defaults to identity + min_value : float, optional + The lower bound of the range + max_value : float, optional + The upper bound of the range + zero_undefined_offset : int, optional + This is useful for log transformation because log(0) is -inf. + Hence, value=0 gives y=0 while the + output for other values start at `zero_undefined_offset` (y = log(value) + zero_undefined_offset) + Default value is 0 + + Returns + ------- + pandas.Series + Values after standardization + """ + zero_undefined = is_zero_defined(transform) # Is function defined at 0? + + if zero_undefined and zero_undefined_offset == 0: + raise ValueError( + "If zero of the transformation is undefined, then provide an offset greater than 0" + ) + + # Compute lower and upper bounds of values + if min_value is None: + if zero_undefined: + min_value = ( + values[values > 0].min() if len(values[values > 0]) > 0 else 0 + ) + else: + min_value = values.min() if len(values) > 0 else 0 + if max_value is None: + if zero_undefined: + max_value = ( + values[values > 0].max() if len(values[values > 0]) > 0 else 0 + ) + else: + max_value = values.max() if len(values) > 0 else 0 + + # Apply transformation if given + transformed_min_value = ( + transform(min_value) if (min_value > 0 or not zero_undefined) else 0 + ) + transformed_max_value = ( + transform(max_value) if (max_value > 0 or not zero_undefined) else 0 + ) + transformed_values = transform(values) + + # Compute range + value_range = transformed_max_value - transformed_min_value + + # Apply standardization + if value_range > 0: + transformed_values = ( + transformed_values - transformed_min_value + ) / value_range + if zero_undefined: + transformed_values = transformed_values + zero_undefined_offset + transformed_values = np.where(values == 0, 0, transformed_values) + else: + # If only single value present in table, then place it at 0 + transformed_values = 0 * values + + return transformed_values + + +class GrotrianPlot: + """ + Class for the Grotrian Diagram + + Parameters + ---------- + atom_data : pandas.DataFrame + Mapping from atomic number to symbol and name + level_energy_data : pandas.Series + Level energies (in eV) indexed by (atomic_number, ion_number, level_number) + level_population_data : pandas.DataFrame + Level populations indexed by (atomic_number, ion_number, level_number) + and each column representing the supernova shell + line_interaction_analysis : tardis.analysis.LastLineInteraction + LastLineInteraction object with the appropriate filters + + Configurable Attributes + ----------------------- + atomic_number : int + Atomic number of the ion for which the diagram is plotted + Note: User should set the atomic_number and ion_number together using set_ion function. + ion_number : int + Ion number of the ion for which the diagram is plotted + Note: User should set the atomic_number and ion_number together using set_ion function. + shell : int or None + The supernova shell to filter on. + If None, the level populations are averaged across all shells, + and all last line interaction are considered + Default value is None + max_levels : int + The maximum number of levels to plot. + Default value is 10 + level_diff_threshold : float + The percentage threshold under which levels are merged + Default value is 1% (0.01) + min_wavelength : float + The minimum wavelength allowed for the transitions + max_wavelength : float + The maximum wavelength allowed for the transitions + filter_mode : {"packet_out_nu", "packet_in_nu"} + The type of wavelength to apply wavelength range filter on + Default value is packet_out_nu + y_scale : {"Log", "Linear"} + The scale to plot the energy levels on the y-axis + Default value is Log + cmapname : str + The name of the colormap used to denote wavelengths. Default value is "rainbow" + level_width_scale : float + The multiplier to convert standardized level populations to level widths + Default value is 3 + level_width_offset : float + The offset for level widths (to add to the scaled standardized level populations) + Default value is 1 + transition_width_scale : float + The multiplier to convert standardized packet count to transition widths + Default value is 2 + transition_width_offset : float + The offset for transition widths (to add to the scaled standardized packet counts) + Default value is 1 + """ + + FILTER_MODES = ("packet_out_nu", "packet_in_nu") + FILTER_MODES_DESC = ("Emitted Wavelength", "Absorbed Wavelength") + Y_SCALE_OPTION = {"Linear": (lambda x: x), "Log": np.log} + + @classmethod + def from_simulation(cls, sim, **kwargs): + """ + Creates a GrotrianPlot object from a Simulation object + + Parameters + ---------- + sim : tardis.simulation.Simulation + TARDIS simulation object + + Returns + ------- + tardis.visualization.widgets.grotrian.GrotrianPlot + GrotrianPlot object + """ + atom_data = sim.plasma.atomic_data.atom_data + level_energy_data = pd.Series( + sim.plasma.atomic_data.levels.energy * u.erg.to(u.electronvolt), + name="energy", + ) + level_population_data = sim.plasma.level_number_density + line_interaction_analysis = { + filter_mode: LastLineInteraction.from_simulation(sim, filter_mode) + for filter_mode in cls.FILTER_MODES + } + return cls( + atom_data=atom_data, + level_energy_data=level_energy_data, + level_population_data=level_population_data, + line_interaction_analysis=line_interaction_analysis, + **kwargs, + ) + + def __init__( + self, + atom_data, + level_energy_data, + level_population_data, + line_interaction_analysis, + ): + # Set data members + self._atom_data = atom_data + self._level_energy_data = level_energy_data + self._level_population_data = level_population_data + self._line_interaction_analysis = line_interaction_analysis + + # Max number of levels to display + self._max_levels = 10 + + # Energy difference threshold below which levels are merged + self._level_diff_threshold = 0.01 + + # Filter mode for the wavelength range + self._min_wavelength = None + self._max_wavelength = None + self._filter_mode = self.FILTER_MODES[0] + + # Selected Species + self._atomic_number = None + self._ion_number = None + self._shell = None + + ### Define default parameters for visual elements related to energy levels + self.level_width_scale, self.level_width_offset = 3, 1 + self._level_width_transform = np.log # Scale of the level widths + self._population_spacer = np.geomspace # To space width bar counts + ### Scale of the y-axis + self._y_scale = "Log" + self._y_coord_transform = self.Y_SCALE_OPTION[self._y_scale] + + ### Define default parameters for visual elements related to transitions + self.transition_width_scale, self.transition_width_offset = 2, 1 + self._transition_width_transform = np.log # Scale of the arrow widths + self._transition_count_spacer = ( + np.geomspace + ) # To space width bar counts + self.arrowhead_size = 9 + + ### Define default parameters for visual elements related to wavelengths + self.cmapname = "rainbow" + self._wavelength_color_transform = np.log # Scale of wavelength color + self._wavelength_spacer = np.geomspace # To space colorbar wavelengths + + # Coordinate end points of levels + self.x_min, self.x_max = 0, 1 + + @property + def min_wavelength(self): + return self._min_wavelength + + @min_wavelength.setter + def min_wavelength(self, value): + self._min_wavelength = value + self._compute_transitions() + + @property + def max_wavelength(self): + return self._max_wavelength + + @max_wavelength.setter + def max_wavelength(self, value): + self._max_wavelength = value + self._compute_transitions() + + def reset_selected_plot_wavelength_range(self): + """ + Resets the wavelength range of the selected plot + """ + self.min_wavelength = None + self.max_wavelength = None + + @property + def max_levels(self): + return self._max_levels + + @max_levels.setter + def max_levels(self, value): + assert type(value) is int + self._max_levels = value + self._compute_level_data() + self.reset_selected_plot_wavelength_range() # calls _compute_transitions() as well + + @property + def level_diff_threshold(self): + return self._level_diff_threshold + + @level_diff_threshold.setter + def level_diff_threshold(self, value): + assert 0 >= value and value < 1 + self._level_diff_threshold = value + self._compute_level_data() + self._compute_transitions() + + @property + def filter_mode(self): + return self._filter_mode + + @filter_mode.setter + def filter_mode(self, value): + assert value in self.FILTER_MODES + + # Set the atomic_number and ion_number in the appropriate analysis object + self._line_interaction_analysis[value].set_ion( + self.atomic_number, self.ion_number + ) + self._line_interaction_analysis[value].shell = self.shell + + self._filter_mode = value + + self._compute_transitions() + + @property + def atomic_number(self): + if self._atomic_number is None: + raise ValueError("Atomic number is not set") + return self._atomic_number + + def set_ion(self, atomic_number, ion_number): + """ + Sets the atomic number and ion number + """ + assert type(atomic_number) is int and type(ion_number) is int + if (atomic_number, ion_number) not in self._level_energy_data.index or ( + atomic_number, + ion_number, + ) not in self._level_population_data.index: + raise ValueError( + "The (atomic_number, ion_number) pair doesn't exist in model" + ) + self._line_interaction_analysis[self.filter_mode].set_ion( + atomic_number, ion_number + ) + + self._atomic_number = atomic_number + self._ion_number = ion_number + self._compute_level_data() + + # Reset any custom wavelengths if user changes ion + self.reset_selected_plot_wavelength_range() # Also computes transition lines so we don't need to call it "_compute_transitions()" explicitly + + @property + def ion_number(self): + if self._ion_number is None: + raise ValueError("Ion number is not set") + return self._ion_number + + @property + def atomic_name(self): + return self._atom_data.loc[self.atomic_number]["name"] + + @property + def atomic_symbol(self): + return self._atom_data.loc[self.atomic_number]["symbol"] + + @property + def shell(self): + return self._shell + + @shell.setter + def shell(self, value): + assert value is None or type(value) is int + self._line_interaction_analysis[self.filter_mode].shell = value + self._shell = value + self._compute_level_data() + self._compute_transitions() + + @property + def y_scale(self): + return self._y_scale + + @y_scale.setter + def y_scale(self, value): + assert value in self.Y_SCALE_OPTION + self._y_scale = value + self._y_coord_transform = self.Y_SCALE_OPTION[self._y_scale] + + def _compute_transitions(self): + """ + Computes the excitation/de-excitation line transition data for the arrows in the widget + """ + ### Get the excitation/de-excitation transitions from LastLineInteraction object + excite_lines = ( + self._line_interaction_analysis[self.filter_mode] + .last_line_in.reset_index() + .groupby(["level_number_lower", "level_number_upper"]) + .agg( + num_electrons=("line_id", "count"), # Take count of lines + wavelength=("wavelength", "first"), # Take first of wavelengths + ) + .reset_index() + ) + + deexcite_lines = ( + self._line_interaction_analysis[self.filter_mode] + .last_line_out.reset_index() + .groupby(["level_number_lower", "level_number_upper"]) + .agg( + num_electrons=("line_id", "count"), # Take count of lines + wavelength=("wavelength", "first"), # Take first of wavelengths + ) + .reset_index() + ) + + ### Filter transitions to only include transitions up to the self.max_levels + excite_lines = excite_lines.loc[ + excite_lines.level_number_upper <= self.max_levels + ] + deexcite_lines = deexcite_lines.loc[ + deexcite_lines.level_number_upper <= self.max_levels + ] + + ### Map the levels to merged levels + excite_lines[ + "merged_level_number_lower" + ] = excite_lines.level_number_lower.map(self.level_mapping) + excite_lines[ + "merged_level_number_upper" + ] = excite_lines.level_number_upper.map(self.level_mapping) + deexcite_lines[ + "merged_level_number_lower" + ] = deexcite_lines.level_number_lower.map(self.level_mapping) + deexcite_lines[ + "merged_level_number_upper" + ] = deexcite_lines.level_number_upper.map(self.level_mapping) + + ### Group by level pairs + excite_lines = ( + excite_lines.groupby( + ["merged_level_number_lower", "merged_level_number_upper"] + ) + .agg( + wavelength=("wavelength", "mean"), # Take mean of wavelength + num_electrons=("num_electrons", "sum"), # Take sum of counts + ) + .reset_index() + ) + deexcite_lines = ( + deexcite_lines.groupby( + ["merged_level_number_lower", "merged_level_number_upper"] + ) + .agg( + wavelength=("wavelength", "mean"), # Take mean of wavelength + num_electrons=("num_electrons", "sum"), # Take sum of counts + ) + .reset_index() + ) + + ### Remove the rows where start and end (merged) level is the same + excite_lines = excite_lines.loc[ + excite_lines.merged_level_number_lower + != excite_lines.merged_level_number_upper + ] + deexcite_lines = deexcite_lines.loc[ + deexcite_lines.merged_level_number_lower + != deexcite_lines.merged_level_number_upper + ] + + ### Compute default wavelengths if not set by user + if len(excite_lines) + len(deexcite_lines) > 0: + if self.min_wavelength is None: # Compute default wavelength + self._min_wavelength = np.min( + np.concatenate( + (excite_lines.wavelength, deexcite_lines.wavelength) + ) + ) + if self.max_wavelength is None: # Compute default wavelength + self._max_wavelength = np.max( + np.concatenate( + (excite_lines.wavelength, deexcite_lines.wavelength) + ) + ) + + ### Remove the rows outside the wavelength range for the plot + excite_lines = excite_lines.loc[ + (excite_lines.wavelength >= self.min_wavelength) + & (excite_lines.wavelength <= self.max_wavelength) + ] + deexcite_lines = deexcite_lines.loc[ + (deexcite_lines.wavelength >= self.min_wavelength) + & (deexcite_lines.wavelength <= self.max_wavelength) + ] + + ### Compute the standardized log number of electrons for arrow line width + transition_width_coefficient = standardize( + np.concatenate( + (excite_lines.num_electrons, deexcite_lines.num_electrons) + ), + transform=self._transition_width_transform, + zero_undefined_offset=1e-3, + ) + excite_lines[ + "transition_width_coefficient" + ] = transition_width_coefficient[: len(excite_lines)] + deexcite_lines[ + "transition_width_coefficient" + ] = transition_width_coefficient[len(excite_lines) :] + + self.excite_lines = excite_lines + self.deexcite_lines = deexcite_lines + + def _compute_level_data(self): + """ + Computes the level population data for the horizontal platforms in the widget + """ + ### Get energy levels and convert to eV + raw_energy_levels = self._level_energy_data.loc[ + self.atomic_number, self.ion_number + ].loc[0 : self.max_levels] + + ### Get level populations + raw_level_populations = self._level_population_data.loc[ + self.atomic_number, self.ion_number + ].loc[0 : self.max_levels] + + ### Average out the level populations across all zones, if zone not selected + if self.shell is None: + raw_level_populations = raw_level_populations.mean(axis=1) + else: + raw_level_populations = raw_level_populations[self.shell] + + raw_level_populations = pd.Series( + raw_level_populations, name="population" + ) + + ### Join level populations and energy values + raw_level_data = pd.merge( + raw_energy_levels, + raw_level_populations, + left_index=True, + right_index=True, + ) + + ### Merge the levels if energy difference is less than threshold + # Get new level numbers + # TODO: Find a better way to find close levels (less than 0.03 diff in y-coord) + raw_level_data["merged_level_number"] = ( + (raw_level_data["energy"] + 1).pct_change().abs() + > self.level_diff_threshold + ).cumsum() + + # Group data with new level numbers + self.level_data = ( + raw_level_data.reset_index() + .groupby("merged_level_number") + .agg( + energy=( + "energy", + "mean", + ), # Set energy as mean of merged levels + population=("population", "sum"), + ) + ) # Add the populations of merged levels + + ### Standardize the level populations to get width coefficient of levels + self.level_data["level_width_coefficient"] = standardize( + self.level_data.population, + transform=self._level_width_transform, + zero_undefined_offset=1e-3, + ) + + ### Create a mapping from original levels to merged levels + self.level_mapping = raw_level_data.merged_level_number + + def _draw_energy_levels(self): + """ + Draws the horizontal energy levels on the widget + """ + # Transform energies and standardize result to get y-coordinate in range [0, 1] + self.level_data["y_coord"] = standardize( + self.level_data.energy, + transform=self._y_coord_transform, + zero_undefined_offset=0.1, + ) + + ### Create the energy levels from level data + for level_number, level_info in self.level_data.iterrows(): + # Add the horizontal line + self.fig.add_trace( + go.Scatter( + x=np.linspace(self.x_min - 0.05, self.x_max + 0.05, 10), + y=level_info.y_coord * np.ones(10), + mode="lines", + hovertemplate=f"Energy: {level_info.energy:.2e} eV<br>" + + f"Population: {level_info.population:.2e}" + + "<extra></extra>", + line=dict( + color="black", + width=level_info.level_width_coefficient + * self.level_width_scale + + self.level_width_offset, + ) + if level_info.population > 0 + else dict(color="grey", dash="dash"), + showlegend=False, + ), + row=1, + col=2, + ) + + # Add label for energy + self.fig.add_annotation( + x=self.x_max + 0.1, + y=level_info.y_coord, + text=f"{level_number}", + showarrow=False, + xref="x2", + yref="y2", + ) + + def _draw_population_width_scale(self): + """ + Displays the level population width reference bar + """ + ### Create width scale + ### Find lower and upper bounds of populations and corresponding widths + min_population_idx = self.level_data.population[ + self.level_data.population > 0 + ].idxmin() + max_population_idx = self.level_data.population.idxmax() + + min_population = self.level_data.population[min_population_idx] + max_population = self.level_data.population[max_population_idx] + + min_width = ( + self.level_data.level_width_coefficient[min_population_idx] + * self.level_width_scale + + self.level_width_offset + ) + max_width = ( + self.level_data.level_width_coefficient[max_population_idx] + * self.level_width_scale + + self.level_width_offset + ) + + ### Space the populations (log) and corresponding widths (linear) equally + scale_granularity = 10 # Number of scale ticks to display + population_ticks = self._population_spacer( + min_population, max_population, scale_granularity + ) + width_ticks = np.linspace(min_width, max_width, scale_granularity) + y_positions = np.linspace(0, 1, scale_granularity) + + ### Draw the scale lines + for population, width, y_pos in zip( + population_ticks, width_ticks, y_positions + ): + self.fig.add_shape( + type="line", + line_width=width, + x0=0.1, + x1=0.2, + y0=y_pos, + y1=y_pos, + xref="x1", + yref="y1", + ) + self.fig.add_annotation( + x=0.35, + y=y_pos, + text=f"{population:.1e}", + showarrow=False, + xref="x1", + yref="y1", + ) + # Add title of the width bar + self.fig.add_annotation( + x=0.28, + y=-0.08, + text="Populations", + showarrow=False, + xref="x1", + yref="y1", + ) + + def _draw_transitions(self, is_excitation): + """ + Draws the transition arrows on the widget + """ + lines = self.excite_lines if is_excitation else self.deexcite_lines + lines["color_coefficient"] = standardize( + lines.wavelength, + transform=self._wavelength_color_transform, + zero_undefined_offset=1e-5, + min_value=self.min_wavelength, + max_value=self.max_wavelength, + ) + + self._cmap = plt.get_cmap(self.cmapname) # Float to color map + + ### Plot excitation transitions + for _, line_info in lines.iterrows(): + lower, upper = ( + line_info.merged_level_number_lower, + line_info.merged_level_number_upper, + ) + wavelength, transition_width_coefficient = ( + line_info.wavelength, + line_info.transition_width_coefficient, + ) + energy_lower, energy_upper = ( + self.level_data.loc[lower].energy, + self.level_data.loc[upper].energy, + ) + + # Get the end x-coordinate (proportional to energy difference between levels) + merged_max_energy_level = self.level_data.energy.max() + x_end = ( + (energy_upper - energy_lower) + * (self.x_max - self.x_min) + / (merged_max_energy_level - energy_lower) + ) + + # Get the appropriate y-coordinate (computed in _draw_energy_levels) + y_lower = self.level_data.loc[lower].y_coord + y_upper = self.level_data.loc[upper].y_coord + + # Get the end arrow color (proportional to log wavelength) + color_coef = line_info.color_coefficient + color = matplotlib.colors.rgb2hex(self._cmap(color_coef)[:3]) + + # Draw arrow + self.fig.add_trace( + go.Scatter( + x=[self.x_min, x_end], + y=[y_lower, y_upper] + if is_excitation + else [y_upper, y_lower], + hovertemplate=f"Count: {int(line_info.num_electrons)}<br>" + + f"Wavelength: {wavelength:.2e} {ANGSTROM_SYMBOL}" + + "<extra></extra>", + marker=dict( + size=self.arrowhead_size, + color=color, + symbol="arrow-up", + angleref="previous", + ), + line=dict( + color=color, + width=transition_width_coefficient + * self.transition_width_scale + + self.transition_width_offset, + ), + ), + row=1, + col=2, + ) + + def _draw_transition_width_scale(self): + """ + Displays the transition count width reference bar + """ + ### Find lower and upper bounds of num_electrons and corresponding widths + max_num_electrons = np.max( + np.concatenate( + ( + self.excite_lines.num_electrons, + self.deexcite_lines.num_electrons, + ) + ) + ) + min_num_electrons = np.min( + np.concatenate( + ( + self.excite_lines.num_electrons, + self.deexcite_lines.num_electrons, + ) + ) + ) + + max_width_coefficient = np.max( + np.concatenate( + ( + self.excite_lines.transition_width_coefficient, + self.deexcite_lines.transition_width_coefficient, + ) + ) + ) + min_width_coefficient = np.min( + np.concatenate( + ( + self.excite_lines.transition_width_coefficient, + self.deexcite_lines.transition_width_coefficient, + ) + ) + ) + + min_width = ( + min_width_coefficient * self.transition_width_scale + + self.transition_width_offset + ) + max_width = ( + max_width_coefficient * self.transition_width_scale + + self.transition_width_offset + ) + + ### Space the num_electrons (log) and corresponding widths (linear) equally + scale_granularity = 10 + num_electrons_ticks = self._transition_count_spacer( + min_num_electrons, max_num_electrons, scale_granularity + ) + width_ticks = np.linspace(min_width, max_width, scale_granularity) + y_positions = np.linspace(0, 1, scale_granularity) + + ### Draw the width bar + for num_electrons, width, y_pos in zip( + num_electrons_ticks, width_ticks, y_positions + ): + self.fig.add_shape( + type="line", + line_width=width, + x0=0.65, + x1=0.75, + y0=y_pos, + y1=y_pos, + xref="x1", + yref="y1", + ) + self.fig.add_annotation( + x=0.9, + y=y_pos, + text=f"{num_electrons:.1e}", + showarrow=False, + xref="x1", + yref="y1", + ) + # Add title of the width bar + self.fig.add_annotation( + x=0.83, + y=-0.08, + text="#Packets", + showarrow=False, + xref="x1", + yref="y1", + ) + + def _draw_transition_color_scale(self): + """ + Displays the transition wavelength colorbar + """ + # Add a dummy Scatter trace to display colorbar + tickvals = self._wavelength_spacer( + self.min_wavelength, self.max_wavelength, 10 + ) + ticktext = [f"{val:.1e}" for val in tickvals] + self.fig.add_trace( + go.Scatter( + x=[None], + y=[None], + mode="markers", + marker=dict( + colorscale=self.cmapname, + showscale=True, + cmin=self._wavelength_color_transform(self.min_wavelength), + cmax=self._wavelength_color_transform(self.max_wavelength), + colorbar=dict( + title=dict( + text=f"Wavelength ({ANGSTROM_SYMBOL})<br> ", + font_size=12, + ), + thickness=5, + tickvals=self._wavelength_color_transform(tickvals), + ticktext=ticktext, + outlinewidth=0, + ), + ), + hoverinfo="none", + ), + row=1, + col=2, + ) + + def display(self): + """ + Function to draw the plot and the reference scales (calls other draw methods independently) + """ + ### Create figure and set metadata + self.fig = go.FigureWidget( + make_subplots( + rows=1, + cols=2, + column_width=[0.3, 0.7], + specs=[[{}, {}]], + horizontal_spacing=0.14, + ) + ) + + # Update fig layout + self.fig.update_layout( + title=( + f"Energy Level Diagram for {self.atomic_name} {int_to_roman(self.ion_number + 1)} " + f"(Shell: {self.shell if self.shell is not None else 'All'})" + ), + title_x=0.5, + plot_bgcolor="white", + autosize=False, + width=1000, + height=700, + margin=dict(), + showlegend=False, + ) + + # Remove ticklabels in the reference bars subplot + self.fig.update_yaxes( + showticklabels=False, fixedrange=True, row=1, col=1 + ) + self.fig.update_xaxes( + showticklabels=False, fixedrange=True, row=1, col=1 + ) + + ### Create energy level platforms and width reference scale + self._draw_energy_levels() + self._draw_population_width_scale() + + # Remove ticklabels from x-axis + self.fig.update_xaxes( + showticklabels=False, fixedrange=True, row=1, col=2 + ) + # Update y-ticks to reflect actual energy values + self.fig.update_yaxes( + title=dict(text="Energy (eV)", standoff=5), + range=[0, None], + tickmode="array", + tickvals=self.level_data.y_coord, + ticktext=[f"{energy:.2e}" for energy in self.level_data.energy], + fixedrange=True, + row=1, + col=2, + ) + + # Add separator between width scales + self.fig.add_shape( + type="line", + line=dict(color="grey", dash="dash"), + line_width=0.5, + x0=0.55, + x1=0.55, + y0=0, + y1=1, + xref="x1", + yref="y1", + ) + + ### Create transition lines and corresponding width and color scales + if len(self.excite_lines) > 0: + self._draw_transitions(is_excitation=True) + + if len(self.deexcite_lines) > 0: + self._draw_transitions(is_excitation=False) + + if len(self.excite_lines) + len(self.deexcite_lines) > 0: + self._draw_transition_width_scale() + self._draw_transition_color_scale() + + return self.fig + + +class GrotrianWidget: + """ + A wrapper class for the Grotrian Diagram, containing the Grotrian Plot and the IpyWidgets + + Parameters + ---------- + plot : tardis.visualization.widgets.grotrian.GrotrianPlot + GrotrianPlot object + num_shells : int + Number of shells in the sim.simulation_state.v_inner + """ + + @classmethod + def from_simulation(cls, sim, **kwargs): + """ + Creates a GrotrianWidget object from a Simulation object + + Parameters + ---------- + sim : tardis.simulation.Simulation + TARDIS simulation object + + Returns + ------- + tardis.visualization.widgets.grotrian.GrotrianWidget + GrotrianWidget object + """ + plot = GrotrianPlot.from_simulation(sim, **kwargs) + num_shells = len(sim.simulation_state.v_inner) + return cls(plot, num_shells, **kwargs) + + def __init__(self, plot, num_shells, **kwargs): + self.plot = plot + self.num_shells = num_shells + + species_list = self._get_species() + self.ion_selector = ipw.Dropdown( + options=species_list, + index=0, + description="Ion", + ) + self.plot.set_ion(*species_string_to_tuple(self.ion_selector.value)) + self.ion_selector.observe( + self._ion_change_handler, + names="value", + ) + self.ion_selector.observe( + self._wavelength_resetter, + names="value", + ) + + shell_list = ["All"] + [str(i) for i in range(1, num_shells + 1)] + self.shell_selector = ipw.Dropdown( + options=shell_list, + index=0, + description="Shell", + ) + self.shell_selector.observe( + lambda change: self._change_handler( + "shell", None if change["new"] == "All" else int(change["new"]) + ), + names="value", + ) + self.shell_selector.observe( + self._wavelength_resetter, + names="value", + ) + + self.max_level_selector = ipw.BoundedIntText( + value=plot.max_levels, + min=1, + max=40, + step=1, + description="Max Levels", + ) + self.max_level_selector.observe( + lambda change: self._change_handler("max_levels", change["new"]), + names="value", + ) + self.max_level_selector.observe( + self._wavelength_resetter, + names="value", + ) + + self.y_scale_selector = ipw.ToggleButtons( + options=GrotrianPlot.Y_SCALE_OPTION.keys(), + index=1, + description="Y-Scale", + layout=ipw.Layout(width="auto"), + style={"button_width": "100px"}, + ) + self.y_scale_selector.observe( + lambda change: self._change_handler("y_scale", change["new"]), + names="value", + ) + + self.wavelength_range_selector = ipw.FloatRangeSlider( + value=[self.plot.min_wavelength, self.plot.max_wavelength], + min=self.plot.min_wavelength, + max=self.plot.max_wavelength, + step=0.1, + description="Wavelength", + layout=ipw.Layout(width="605px"), + readout_format=".1e", + ) + self.wavelength_range_selector.observe( + self._wavelength_change_handler, + names="value", + ) + + def _get_species(self): + """ + Computes the ions list for the ion dropdown of the plot + """ + line_interaction_analysis = self.plot._line_interaction_analysis + selected_species_group = line_interaction_analysis[ + self.plot.filter_mode + ].last_line_in.groupby(["atomic_number", "ion_number"]) + + if selected_species_group.groups: + selected_species_symbols = [ + species_tuple_to_string(item) + for item in selected_species_group.groups.keys() + ] + return selected_species_symbols + + def _change_handler(self, attribute, value): + """ + Generic function to update the configurable attributes of GrotrianPlot object + + Parameters + ---------- + attribute : str + The name of the attribute of the GrotrianPlot object + value : + The new value of the attribute + """ + index = self.fig.children.index(self.plot.fig) + setattr(self.plot, attribute, value) # Set the value of the attribute + + # Set the updated plot in the figure + children_list = list(self.fig.children) + children_list[index] = self.plot.display() + self.fig.children = tuple(children_list) + + def _ion_change_handler(self, change): + """ + Function to update ion of GrotrianPlot object + + Parameters + ---------- + change : dict + Change information of the event + """ + atomic_number, ion_number = species_string_to_tuple(change["new"]) + index = self.fig.children.index(self.plot.fig) + self.plot.set_ion(atomic_number, ion_number) + + # Set the updated plot in the figure + children_list = list(self.fig.children) + children_list[index] = self.plot.display() + self.fig.children = tuple(children_list) + # self._wavelength_resetter() + + def _wavelength_change_handler(self, change): + """ + Function to update the wavelength range of GrotrianPlot object + + Parameters + ---------- + change : dict + Change information of the event + """ + min_wavelength, max_wavelength = change["new"] + index = self.fig.children.index(self.plot.fig) + setattr(self.plot, "min_wavelength", min_wavelength) + setattr(self.plot, "max_wavelength", max_wavelength + 1) + + # Set the updated plot in the figure + children_list = list(self.fig.children) + children_list[index] = self.plot.display() + self.fig.children = tuple(children_list) + + def _wavelength_resetter(self, change): + """ + Resets the range of the wavelength slider whenever the ion, level or shell changes + """ + min_wavelength = self.plot.min_wavelength + max_wavelength = self.plot.max_wavelength + + if min_wavelength is None or max_wavelength is None: + self.wavelength_range_selector.layout.visibility = "hidden" + return + + elif min_wavelength == max_wavelength: + self.wavelength_range_selector.layout.visibility = "visible" + self.wavelength_range_selector.disabled = True + else: + self.wavelength_range_selector.layout.visibility = "visible" + self.wavelength_range_selector.disabled = False + + self.wavelength_range_selector.min = 0.0 + self.wavelength_range_selector.max = max_wavelength + self.wavelength_range_selector.min = min_wavelength + self.wavelength_range_selector.value = [ + self.wavelength_range_selector.min, + self.wavelength_range_selector.max, + ] + + def display(self): + """ + Function to render the Grotrian Widget containing the plot and IpyWidgets together + """ + fig = self.plot.display() + self.fig = ipw.VBox( + [ + ipw.HBox( + [ + self.ion_selector, + self.shell_selector, + self.max_level_selector, + ] + ), + ipw.HBox( + [self.y_scale_selector, self.wavelength_range_selector] + ), + fig, + ] + ) + return self.fig diff --git a/tardis/visualization/widgets/grotrian_mockup.ipynb b/tardis/visualization/widgets/grotrian_mockup.ipynb new file mode 100644 index 00000000000..870181cebc7 --- /dev/null +++ b/tardis/visualization/widgets/grotrian_mockup.ipynb @@ -0,0 +1,1030 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Iterations: 0/? 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id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.1e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.479</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.47</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.12e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.178</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.185</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.1e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.113</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.112</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0839</td>\n", + " <td id=\"T_903d2c7c_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0856</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe34a06a340>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.1e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.47</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.47</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.12e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.185</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.178</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.112</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.112</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0856</td>\n", + " <td id=\"T_909c4acc_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.086</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe32ae78970>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.47</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.472</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.14e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.178</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.175</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.112</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.111</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.086</td>\n", + " <td id=\"T_90f88e0e_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.084</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe3490fa8b0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.472</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.469</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.14e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.15e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.175</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.17</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.111</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.109</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.08e+04</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.084</td>\n", + " <td id=\"T_91522fb8_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0822</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe33ca6c130>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.1e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.469</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.475</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.15e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.14e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.17</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.177</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.109</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.112</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.08e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.06e+04</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0822</td>\n", + " <td id=\"T_91af1188_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0878</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe34a275340>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.1e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.475</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.472</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.14e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.12e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.177</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.184</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.1e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.112</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.114</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.06e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.06e+04</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0878</td>\n", + " <td id=\"T_92094f36_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0859</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe33ca6c760>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.472</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.467</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.12e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.184</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.176</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.1e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.114</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.11</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.06e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.08e+04</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0859</td>\n", + " <td id=\"T_9264b808_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0821</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe33e14a280>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.467</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.466</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.176</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.18</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.11</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.111</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.08e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.08e+04</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0821</td>\n", + " <td id=\"T_92bfc3f6_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0841</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe33ca6c940>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.466</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.469</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.18</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.182</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.1e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.111</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.113</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.08e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0841</td>\n", + " <td id=\"T_93197964_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0854</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe33ca76850>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.1e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.469</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.484</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.182</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.181</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.1e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.1e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.113</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.113</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0854</td>\n", + " <td id=\"T_93757750_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0858</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe32a3438e0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.1e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.484</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.472</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.181</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.177</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.1e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.1e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.113</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.113</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.06e+04</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0858</td>\n", + " <td id=\"T_93d0c9ac_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0858</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe3490fa130>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.1e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.472</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.468</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.14e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.177</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.175</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.1e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.113</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.11</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.06e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.08e+04</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0858</td>\n", + " <td id=\"T_942b52b4_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0816</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe33ca81970>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.468</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.464</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.14e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.175</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.177</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.11e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.1e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.11</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.113</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.08e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0816</td>\n", + " <td id=\"T_9485557a_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0848</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe34a05ecd0>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<style type=\"text/css\" >\n", + "</style><table id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88d\" ><thead> <tr> <th class=\"index_name level0\" >Shell No.</th> <th class=\"col_heading level0 col0\" >t_rad</th> <th class=\"col_heading level0 col1\" >next_t_rad</th> <th class=\"col_heading level0 col2\" >w</th> <th class=\"col_heading level0 col3\" >next_w</th> </tr></thead><tbody>\n", + " <tr>\n", + " <th id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88dlevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow0_col0\" class=\"data row0 col0\" >1.11e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow0_col1\" class=\"data row0 col1\" >1.11e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow0_col2\" class=\"data row0 col2\" >0.464</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow0_col3\" class=\"data row0 col3\" >0.466</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88dlevel0_row1\" class=\"row_heading level0 row1\" >5</th>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow1_col0\" class=\"data row1 col0\" >1.13e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow1_col1\" class=\"data row1 col1\" >1.13e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow1_col2\" class=\"data row1 col2\" >0.177</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow1_col3\" class=\"data row1 col3\" >0.177</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88dlevel0_row2\" class=\"row_heading level0 row2\" >10</th>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow2_col0\" class=\"data row2 col0\" >1.1e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow2_col1\" class=\"data row2 col1\" >1.11e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow2_col2\" class=\"data row2 col2\" >0.113</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow2_col3\" class=\"data row2 col3\" >0.111</td>\n", + " </tr>\n", + " <tr>\n", + " <th id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88dlevel0_row3\" class=\"row_heading level0 row3\" >15</th>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow3_col0\" class=\"data row3 col0\" >1.07e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow3_col1\" class=\"data row3 col1\" >1.07e+04</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow3_col2\" class=\"data row3 col2\" >0.0848</td>\n", + " <td id=\"T_94dfa7be_3cbc_11ee_aa43_12e413fbf88drow3_col3\" class=\"data row3 col3\" >0.0853</td>\n", + " </tr>\n", + " </tbody></table>" + ], + "text/plain": [ + "<pandas.io.formats.style.Styler at 0x7fe3490fa130>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "### Run Simulation\n", + "config = Configuration.from_yaml(\"../../../docs/tardis_example.yml\")\n", + "atom_data = AtomData.from_hdf(\n", + " os.path.join(get_data_dir(), \"kurucz_cd23_chianti_H_He.h5\")\n", + ")\n", + "model = SimulationState.from_config(config, atom_data=atom_data)\n", + "plasma = assemble_plasma(config, model, atom_data=atom_data)\n", + "sim = Simulation.from_config(\n", + " config, model=model, plasma=plasma, atom_data=atom_data\n", + ")\n", + "sim.run_convergence()\n", + "sim.run_final()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c91528c218b440f7912a8f3a8674e48e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(HBox(children=(Dropdown(description='Ion', options=('O I', 'O II', 'O III', 'Mg II', 'Si II', '…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "diag = GrotrianWidget.from_simulation(sim)\n", + "diag.display()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tardis/visualization/widgets/line_info.py b/tardis/visualization/widgets/line_info.py index 69f852ae958..e605e4e1679 100644 --- a/tardis/visualization/widgets/line_info.py +++ b/tardis/visualization/widgets/line_info.py @@ -10,7 +10,11 @@ import ipywidgets as ipw from tardis.analysis import LastLineInteraction -from tardis.util.base import species_tuple_to_string, species_string_to_tuple +from tardis.util.base import ( + species_tuple_to_string, + species_string_to_tuple, + is_notebook, +) from tardis.visualization.widgets.util import ( create_table_widget, TableSummaryLabel, @@ -124,18 +128,21 @@ def from_simulation(cls, sim): ------- LineInfoWidget object """ + transport_state = sim.transport.transport_state return cls( lines_data=sim.plasma.lines.reset_index().set_index("line_id"), line_interaction_analysis={ - filter_mode: LastLineInteraction.from_model(sim, filter_mode) + filter_mode: LastLineInteraction.from_simulation( + sim, filter_mode + ) for filter_mode in cls.FILTER_MODES }, - spectrum_wavelength=sim.runner.spectrum.wavelength, - spectrum_luminosity_density_lambda=sim.runner.spectrum.luminosity_density_lambda.to( + spectrum_wavelength=transport_state.spectrum.wavelength, + spectrum_luminosity_density_lambda=transport_state.spectrum.luminosity_density_lambda.to( "erg/(s AA)" ), - virt_spectrum_wavelength=sim.runner.spectrum_virtual.wavelength, - virt_spectrum_luminosity_density_lambda=sim.runner.spectrum_virtual.luminosity_density_lambda.to( + virt_spectrum_wavelength=transport_state.spectrum_virtual.wavelength, + virt_spectrum_luminosity_density_lambda=transport_state.spectrum_virtual.luminosity_density_lambda.to( "erg/(s AA)" ), ) @@ -328,7 +335,7 @@ class variable :code:`GROUP_MODES` (default value is for ( line_id, count, - ) in grouped_line_interactions.size().iteritems(): + ) in grouped_line_interactions.size().items(): current_line_in = self.lines_data.loc[line_id[0]] current_line_out = self.lines_data.loc[line_id[1]] last_line_interaction_string.append( @@ -350,7 +357,7 @@ class variable :code:`GROUP_MODES` (default value is for ( line_id, count, - ) in grouped_line_interactions.size().iteritems(): + ) in grouped_line_interactions.size().items(): current_line_in = self.lines_data.loc[line_id] last_line_interaction_string.append( f"exc. {int(current_line_in.level_number_lower):02d}-" @@ -368,7 +375,7 @@ class variable :code:`GROUP_MODES` (default value is for ( line_id, count, - ) in grouped_line_interactions.size().iteritems(): + ) in grouped_line_interactions.size().items(): current_line_out = self.lines_data.loc[line_id] last_line_interaction_string.append( f"de-exc. {int(current_line_out.level_number_upper):02d}-" @@ -665,68 +672,71 @@ def display(self): ipywidgets.Box Line info widget containing all component widgets """ - # Set widths of widgets - self.species_interactions_table.layout.width = "350px" - self.last_line_counts_table.layout.width = "450px" - self.total_packets_label.update_and_resize(0) - self.group_mode_dropdown.layout.width = "auto" - - # Attach event listeners to widgets - spectrum_trace = self.figure_widget.data[0] - spectrum_trace.on_selection(self._spectrum_selection_handler) - self.filter_mode_buttons.observe( - self._filter_mode_toggle_handler, names="index" - ) - self.species_interactions_table.on( - "selection_changed", self._species_intrctn_selection_handler - ) - self.group_mode_dropdown.observe( - self._group_mode_dropdown_handler, names="index" - ) + if not is_notebook(): + print("Please use a notebook to display the widget") + else: + # Set widths of widgets + self.species_interactions_table.layout.width = "350px" + self.last_line_counts_table.layout.width = "450px" + self.total_packets_label.update_and_resize(0) + self.group_mode_dropdown.layout.width = "auto" - selection_box_symbol = ( - "<span style='display: inline-block; " - f"background-color: {self.COLORS['selection_area']}; " - f"border: 1px solid {self.COLORS['selection_border']}; " - "width: 0.8em; height: 1.2em; vertical-align: middle;'></span>" - ) + # Attach event listeners to widgets + spectrum_trace = self.figure_widget.data[0] + spectrum_trace.on_selection(self._spectrum_selection_handler) + self.filter_mode_buttons.observe( + self._filter_mode_toggle_handler, names="index" + ) + self.species_interactions_table.on( + "selection_changed", self._species_intrctn_selection_handler + ) + self.group_mode_dropdown.observe( + self._group_mode_dropdown_handler, names="index" + ) - table_container_left = ipw.VBox( - [ - self.ui_control_description( - "Filter selected wavelength range " - f"( {selection_box_symbol} ) by" - ), - self.filter_mode_buttons, - self.species_interactions_table, - ], - layout=dict(margin="0px 15px"), - ) + selection_box_symbol = ( + "<span style='display: inline-block; " + f"background-color: {self.COLORS['selection_area']}; " + f"border: 1px solid {self.COLORS['selection_border']}; " + "width: 0.8em; height: 1.2em; vertical-align: middle;'></span>" + ) - table_container_right = ipw.VBox( - [ - self.ui_control_description("Group packet counts by"), - self.group_mode_dropdown, - self.last_line_counts_table, - self.total_packets_label.widget, - ], - layout=dict(margin="0px 15px"), - ) + table_container_left = ipw.VBox( + [ + self.ui_control_description( + "Filter selected wavelength range " + f"( {selection_box_symbol} ) by" + ), + self.filter_mode_buttons, + self.species_interactions_table, + ], + layout=dict(margin="0px 15px"), + ) - return ipw.VBox( - [ - self.figure_widget, - ipw.Box( - [ - table_container_left, - table_container_right, - ], - layout=dict( - display="flex", - align_items="flex-start", - justify_content="center", - height="420px", + table_container_right = ipw.VBox( + [ + self.ui_control_description("Group packet counts by"), + self.group_mode_dropdown, + self.last_line_counts_table, + self.total_packets_label.widget, + ], + layout=dict(margin="0px 15px"), + ) + + return ipw.VBox( + [ + self.figure_widget, + ipw.Box( + [ + table_container_left, + table_container_right, + ], + layout=dict( + display="flex", + align_items="flex-start", + justify_content="center", + height="420px", + ), ), - ), - ] - ) + ] + ) diff --git a/tardis/visualization/widgets/shell_info.py b/tardis/visualization/widgets/shell_info.py index 336c8f580cf..811386be4ae 100644 --- a/tardis/visualization/widgets/shell_info.py +++ b/tardis/visualization/widgets/shell_info.py @@ -1,8 +1,9 @@ from tardis.base import run_tardis -from tardis.io.atom_data.util import download_atom_data +from tardis.io.atom_data.atom_web_download import download_atom_data from tardis.util.base import ( atomic_number2element_symbol, species_tuple_to_string, + is_notebook, ) from tardis.visualization.widgets.util import create_table_widget @@ -18,7 +19,7 @@ class BaseShellInfo: def __init__( self, t_radiative, - w, + dilution_factor, abundance, number_density, ion_number_density, @@ -30,7 +31,7 @@ def __init__( ---------- t_radiative : array_like Radiative Temperature of each shell of simulation - w : array_like + dilution_factor : array_like Dilution Factor (W) of each shell of simulation model abundance : pandas.DataFrame Fractional abundance of elements where row labels are atomic number @@ -46,7 +47,7 @@ def __init__( number, ion number, level number) and column labels are shell number """ self.t_radiative = t_radiative - self.w = w + self.dilution_factor = dilution_factor self.abundance = abundance self.number_density = number_density self.ion_number_density = ion_number_density @@ -62,7 +63,10 @@ def shells_data(self): simulation model """ shells_temp_w = pd.DataFrame( - {"Rad. Temp.": self.t_radiative, "W": self.w} + { + "Rad. Temp.": self.t_radiative, + "Dilution Factor": self.dilution_factor, + } ) shells_temp_w.index = range( 1, len(self.t_radiative) + 1 @@ -184,8 +188,8 @@ def __init__(self, sim_model): TARDIS Simulation object produced by running a simulation """ super().__init__( - sim_model.model.t_radiative, - sim_model.model.w, + sim_model.simulation_state.t_radiative, + sim_model.simulation_state.dilution_factor, sim_model.plasma.abundance, sim_model.plasma.number_density, sim_model.plasma.ion_number_density, @@ -210,8 +214,8 @@ def __init__(self, hdf_fpath): """ with pd.HDFStore(hdf_fpath, "r") as sim_data: super().__init__( - sim_data["/simulation/model/t_radiative"], - sim_data["/simulation/model/w"], + sim_data["/simulation/simulation_state/t_radiative"], + sim_data["/simulation/simulation_state/dilution_factor"], sim_data["/simulation/plasma/abundance"], sim_data["/simulation/plasma/number_density"], sim_data["/simulation/plasma/ion_number_density"], @@ -435,53 +439,56 @@ def display( ipywidgets.Box Shell info widget containing all component widgets """ - # CSS properties of the layout of shell info tables container - tables_container_layout = dict( - display="flex", - align_items="flex-start", - justify_content="space-between", - ) - tables_container_layout.update(layout_kwargs) + if not is_notebook(): + print("Please use a notebook to display the widget") + else: + # CSS properties of the layout of shell info tables container + tables_container_layout = dict( + display="flex", + align_items="flex-start", + justify_content="space-between", + ) + tables_container_layout.update(layout_kwargs) - # Setting tables' widths - self.shells_table.layout.width = shells_table_width - self.element_count_table.layout.width = element_count_table_width - self.ion_count_table.layout.width = ion_count_table_width - self.level_count_table.layout.width = level_count_table_width + # Setting tables' widths + self.shells_table.layout.width = shells_table_width + self.element_count_table.layout.width = element_count_table_width + self.ion_count_table.layout.width = ion_count_table_width + self.level_count_table.layout.width = level_count_table_width - # Attach event listeners to table widgets - self.shells_table.on( - "selection_changed", self.update_element_count_table - ) - self.element_count_table.on( - "selection_changed", self.update_ion_count_table - ) - self.ion_count_table.on( - "selection_changed", self.update_level_count_table - ) + # Attach event listeners to table widgets + self.shells_table.on( + "selection_changed", self.update_element_count_table + ) + self.element_count_table.on( + "selection_changed", self.update_ion_count_table + ) + self.ion_count_table.on( + "selection_changed", self.update_level_count_table + ) - # Putting all table widgets in a container styled with tables_container_layout - shell_info_tables_container = ipw.Box( - [ - self.shells_table, - self.element_count_table, - self.ion_count_table, - self.level_count_table, - ], - layout=ipw.Layout(**tables_container_layout), - ) - self.shells_table.change_selection([1]) + # Putting all table widgets in a container styled with tables_container_layout + shell_info_tables_container = ipw.Box( + [ + self.shells_table, + self.element_count_table, + self.ion_count_table, + self.level_count_table, + ], + layout=ipw.Layout(**tables_container_layout), + ) + self.shells_table.change_selection([1]) - # Notes text explaining how to interpret tables widgets' data - text = ipw.HTML( - "<b>Frac. Ab.</b> denotes <i>Fractional Abundances</i> (i.e all " - "values sum to 1)<br><b>W</b> denotes <i>Dilution Factor</i> and " - "<b>Rad. Temp.</b> is <i>Radiative Temperature (in K)</i>" - ) + # Notes text explaining how to interpret tables widgets' data + text = ipw.HTML( + "<b>Frac. Ab.</b> denotes <i>Fractional Abundances</i> (i.e all " + "values sum to 1)<br><b>W</b> denotes <i>Dilution Factor</i> and " + "<b>Rad. Temp.</b> is <i>Radiative Temperature (in K)</i>" + ) - # Put text horizontally before shell info container - shell_info_widget = ipw.VBox([text, shell_info_tables_container]) - return shell_info_widget + # Put text horizontally before shell info container + shell_info_widget = ipw.VBox([text, shell_info_tables_container]) + return shell_info_widget def shell_info_from_simulation(sim_model): diff --git a/tardis/visualization/widgets/tests/test_custom_abundance.py b/tardis/visualization/widgets/tests/test_custom_abundance.py new file mode 100644 index 00000000000..d05586c8d4e --- /dev/null +++ b/tardis/visualization/widgets/tests/test_custom_abundance.py @@ -0,0 +1,252 @@ +"""Tests for custom abundance widget.""" +from pathlib import Path +import pytest +import tardis +import numpy as np +import numpy.testing as npt + +from tardis.tests.test_util import monkeysession +from tardis.visualization.widgets.custom_abundance import ( + CustomAbundanceWidgetData, + CustomYAML, + CustomAbundanceWidget, +) + + +@pytest.fixture(scope="module") +def yml_data(example_configuration_dir: Path, atomic_dataset): + """Fixture to contain a CustomAbundanceWidgetData + instance generated from a YAML file tardis_configv1_verysimple.yml. + + Returns + ------- + CustomAbundanceWidgetData + CustomAbundanceWidgetData generated from a YAML + """ + yml_path = example_configuration_dir / "tardis_configv1_verysimple.yml" + + return CustomAbundanceWidgetData.from_yml( + yml_path, atom_data=atomic_dataset + ) + + +@pytest.fixture(scope="module") +def caw(yml_data, monkeysession): + """Fixture to contain a CustomAbundanceWidget + instance generated from a YAML file tardis_configv1_verysimple.yml. + + Returns + ------- + CustomAbundanceWidget + CustomAbundanceWidget generated from a YAML + """ + caw = CustomAbundanceWidget(yml_data) + monkeysession.setattr( + "tardis.visualization.widgets.custom_abundance.is_notebook", + lambda: True, + ) + caw.display() + return caw + + +class TestCustomAbundanceWidgetData: + def test_get_symbols(self, yml_data): + """Tests the atomic symbols for the YAML CustomAbundanceWidgetData""" + symbols = yml_data.get_symbols() + npt.assert_array_equal(symbols, ["O", "Mg", "Si", "S", "Ar", "Ca"]) + + +class TestCustomAbundanceWidget: + def test_update_input_item_value(self, caw): + """Tests updating an input item value + + Parameters + ---------- + caw : CustomAbundanceWidget + """ + caw.update_input_item_value(0, 0.33333) + assert caw.input_items[0].value == 0.333 + + def test_read_abundance(self, caw): + """Tests reading an abundance + + Parameters + ---------- + caw : CustomAbundanceWidget + """ + caw.data.abundance[0] = 0.2 + caw.read_abundance() + for i in range(caw.no_of_elements): + assert caw.input_items[i].value == 0.2 + + def test_update_abundance_plot(self, caw): + """Tests plotting an abundance array + + Parameters + ---------- + caw : CustomAbundanceWidget + """ + caw.data.abundance.iloc[0, :] = 0.2 + caw.update_abundance_plot(0) + + npt.assert_array_equal( + caw.fig.data[2].y, np.array([0.2] * (caw.no_of_shells + 1)) + ) + + def test_bound_locked_sum_to_1(self, caw): + """Trigger checkbox eventhandler and input_item eventhandler + to test `bound_locked_sum_to_1()` function. + """ + # bound checked input to 1 + caw.checks[0].value = True + caw.checks[1].value = True + caw.input_items[0].value = 0.5 + caw.input_items[1].value = 0.6 + assert caw.input_items[1].value == 0.5 + + # bound to 1 when input is checked + caw.checks[2].value = True + assert caw.input_items[2].value == 0 + + @pytest.mark.parametrize( + "v0, v1, expected", + [ + (11000, 11450, "hidden"), + (11100, 11200, "hidden"), + (11000, 11451, "visible"), + ], + ) + def test_overwrite_existing_shells(self, caw, v0, v1, expected): + """Trigger velocity input box handler to test whether overwriting + existing shell. + """ + caw.input_v_start.value = v0 + caw.input_v_end.value = v1 + + assert caw.overwrite_warning.layout.visibility == expected + + @pytest.mark.skip( + reason="Problem with cutting model in restructure. See TARDIS issue 2390" + ) + @pytest.mark.parametrize( + "multishell_edit, expected_x, expected_y, expected_width", + [ + (False, [19775], [1], [450]), + (True, (11225, 15500), (1, 1), (450, 9000)), + ], + ) + def test_update_bar_diagonal( + self, caw, multishell_edit, expected_x, expected_y, expected_width + ): + """Tests updating the bar figure + + Parameters + ---------- + caw : CustomAbundanceWidget + multishell_edit : bool + expected_x : list + expected_y : list + expected_width : list + """ + if multishell_edit: + caw.irs_shell_range.disabled = False # update_bar_diagonal() will be called when status of irs_shell_range is changed + caw.irs_shell_range.value = (1, 20) + + assert caw.shell_no == caw.irs_shell_range.value[0] + assert caw.btn_next.disabled == True + assert caw.btn_prev.disabled == True + else: + caw.shell_no = 20 + caw.update_bar_diagonal() + + npt.assert_array_almost_equal(caw.fig.data[0].x, expected_x) + npt.assert_array_almost_equal(caw.fig.data[0].width, expected_width) + npt.assert_array_almost_equal(caw.fig.data[0].y, expected_y) + + @pytest.mark.parametrize( + "multishell_edit, inputs, locks, expected", + [ + (False, [0, 0, 0, 0, 0, 0, 0], [False] * 6, [0, 0, 0, 0, 0, 0, 0]), + ( + False, + [0.1, 0.2, 0, 0, 0, 0, 0], + [True] + [False] * 5, + [0.1, 0.9, 0, 0, 0, 0, 0], + ), + ( + False, + [0.1, 0.2, 0.3, 0.4, 0.5, 0.6], + [False] * 6, + [0.0476, 0.0952, 0.143, 0.19, 0.238, 0.286], + ), + ( + False, + [0.1, 0.2, 0.3, 0.4, 0.5, 0.6], + [True] * 2 + [False] * 4, + [0.1, 0.2, 0.117, 0.156, 0.194, 0.233], + ), + ( + True, + [0.1, 0.2, 0.3, 0.4, 0.5, 0.6], + [True] * 2 + [False] * 4, + [0.1, 0.2, 0.117, 0.156, 0.194, 0.233], + ), + ], + ) + def test_on_btn_norm(self, caw, multishell_edit, inputs, locks, expected): + """Tests the normalisation button + + Parameters + ---------- + caw : CustomAbundanceWidget + multishell_edit : bool + inputs : list + locks : list + expected : list + """ + if multishell_edit: + caw.rbs_multi_apply.index = 0 + for i, item in enumerate(caw.input_items): + item.value = inputs[i] + caw.checks[i].value = locks[i] + + caw.on_btn_norm(None) + + for i, item in enumerate(caw.input_items): + assert item.value == expected[i] + + start_no = caw.irs_shell_range.value[0] + end_no = caw.irs_shell_range.value[1] + + for i, v in enumerate(expected): + line = caw.fig.data[2 + i].y[start_no - 1 : end_no] + unique_v = set(line) + assert len(unique_v) == 1 + unique_v = float("{:.3g}".format(list(unique_v)[0])) + assert unique_v == v + else: + for i, item in enumerate(caw.input_items): + item.value = inputs[i] + caw.checks[i].value = locks[i] + + caw.on_btn_norm(None) + + for i, item in enumerate(caw.input_items): + assert item.value == expected[i] + + +class TestCustomYAML: + def test_create_fields_dict(self): + """Test creating fields in the YAML""" + custom_yaml = CustomYAML("test", 0, 0, 0, 0) + custom_yaml.create_fields_dict(["H", "He"]) + datatype_dict = { + "fields": [ + {"name": "velocity", "unit": "km/s"}, + {"name": "density", "unit": "g/cm^3"}, + {"name": "H", "desc": "fractional H abundance"}, + {"name": "He", "desc": "fractional He abundance"}, + ] + } + + assert custom_yaml.datatype == datatype_dict diff --git a/tardis/visualization/widgets/tests/test_line_info.py b/tardis/visualization/widgets/tests/test_line_info.py index 112ca1ee191..87686c3af29 100644 --- a/tardis/visualization/widgets/tests/test_line_info.py +++ b/tardis/visualization/widgets/tests/test_line_info.py @@ -4,6 +4,7 @@ from plotly.callbacks import Points, BoxSelector from tardis.visualization.widgets.line_info import LineInfoWidget from tardis.util.base import species_string_to_tuple +from tardis.tests.test_util import monkeysession @pytest.fixture(scope="class") @@ -141,12 +142,15 @@ class TestLineInfoWidgetEvents: None, # No selection of wavelength range ], ) - def liw_with_selection(self, simulation_verysimple, request): + def liw_with_selection(self, simulation_verysimple, request, monkeysession): """ Makes different wavelength range selection on figure (specified by params) after creating a LineInfoWidget object. """ liw = LineInfoWidget.from_simulation(simulation_verysimple) + monkeysession.setattr( + "tardis.visualization.widgets.line_info.is_notebook", lambda: True + ) # To attach event listeners to component widgets of line_info_widget _ = liw.display() diff --git a/tardis/visualization/widgets/tests/test_shell_info.py b/tardis/visualization/widgets/tests/test_shell_info.py index 91b9b41cfe7..7a99374dbc5 100644 --- a/tardis/visualization/widgets/tests/test_shell_info.py +++ b/tardis/visualization/widgets/tests/test_shell_info.py @@ -2,6 +2,7 @@ import numpy as np import pandas.testing as pdt +from tardis.tests.test_util import monkeysession from tardis.visualization.widgets.shell_info import ( BaseShellInfo, SimulationShellInfo, @@ -13,8 +14,8 @@ @pytest.fixture(scope="class") def base_shell_info(simulation_verysimple): return BaseShellInfo( - simulation_verysimple.model.t_radiative, - simulation_verysimple.model.w, + simulation_verysimple.simulation_state.t_radiative, + simulation_verysimple.simulation_state.dilution_factor, simulation_verysimple.plasma.abundance, simulation_verysimple.plasma.number_density, simulation_verysimple.plasma.ion_number_density, @@ -39,15 +40,16 @@ class TestBaseShellInfo: def test_shells_data(self, base_shell_info, simulation_verysimple): shells_data = base_shell_info.shells_data() assert shells_data.shape == ( - len(simulation_verysimple.model.t_radiative), + len(simulation_verysimple.simulation_state.t_radiative), 2, ) assert np.allclose( - shells_data.iloc[:, 0].map(np.float), - simulation_verysimple.model.t_radiative.value, + shells_data.iloc[:, 0].map(np.float64), + simulation_verysimple.simulation_state.t_radiative.value, ) assert np.allclose( - shells_data.iloc[:, 1].map(np.float), simulation_verysimple.model.w + shells_data.iloc[:, 1].map(np.float64), + simulation_verysimple.simulation_state.dilution_factor, ) @pytest.mark.parametrize("shell_num", [1, 20]) @@ -60,7 +62,7 @@ def test_element_count_data( 2, ) assert np.allclose( - element_count_data.iloc[:, -1].map(np.float), + element_count_data.iloc[:, -1].map(np.float64), simulation_verysimple.plasma.abundance[shell_num - 1], ) @@ -81,7 +83,7 @@ def test_ion_count_data( ) assert ion_count_data.shape == (len(sim_ion_number_density), 2) assert np.allclose( - ion_count_data.iloc[:, -1].map(np.float), + ion_count_data.iloc[:, -1].map(np.float64), sim_ion_number_density / sim_element_number_density, ) @@ -111,7 +113,7 @@ def test_level_count_data( ) assert level_count_data.shape == (len(sim_level_number_density), 1) assert np.allclose( - level_count_data.iloc[:, 0].map(np.float), + level_count_data.iloc[:, 0].map(np.float64), sim_level_number_density / sim_ion_number_density, ) @@ -137,8 +139,11 @@ class TestShellInfoWidget: select_ion_num = 3 @pytest.fixture(scope="class") - def shell_info_widget(self, base_shell_info): + def shell_info_widget(self, base_shell_info, monkeysession): shell_info_widget = ShellInfoWidget(base_shell_info) + monkeysession.setattr( + "tardis.visualization.widgets.shell_info.is_notebook", lambda: True + ) # To attach event listeners to table widgets of shell_info_widget _ = shell_info_widget.display() return shell_info_widget diff --git a/tardis/visualization/widgets/util.py b/tardis/visualization/widgets/util.py index 5592c71b09b..c354ebbf38d 100644 --- a/tardis/visualization/widgets/util.py +++ b/tardis/visualization/widgets/util.py @@ -130,8 +130,8 @@ def __init__(self, target_table, table_col_widths, label_key, label_value): Notes ----- - TableSummaryLabel can only be created for a table with two columns - (including index as 1st column) as of now + TableSummaryLabel can only be created for a table with two + columns (including index as 1st column) as of now """ if len(table_col_widths) != 2: raise NotImplementedError( @@ -157,8 +157,8 @@ def update_and_resize(self, value): value : int Value to be shown in label - Note - ---- + Notes + ----- The width resizing operation is highly dependent on qgrid tables' layout. So it may not remain precise if there happens any CSS change in upcoming versions of qgrid. diff --git a/tardis_env3.yml b/tardis_env3.yml index 88ce01c41d9..8882a45d094 100644 --- a/tardis_env3.yml +++ b/tardis_env3.yml @@ -4,17 +4,21 @@ channels: - conda-forge dependencies: - - python=3.7 + + # WARNING: any change to this section must be applied to the conda-forge + # package recipe at https://github.com/conda-forge/tardis-sn-feedstock + + - python - setuptools - setuptools_scm - pip - - numpy=1.19 - - scipy=1.5 - - pandas=1.0 - - astropy=3 - - numba=0.53 + - numpy + - scipy + - pandas + - astropy + - numba - numexpr - - pyne=0.7=nomoab_openmc* # Issue #1537 + - radioactivedecay # Plasma - networkx @@ -22,22 +26,21 @@ dependencies: # I/O - pyyaml - - jsonschema=3 # Issue #1807 - - pytables + - jsonschema + - hdf5 - h5py - - pickle5 # Issue #1566 + - pytables - requests - tqdm # Widgets & Visualization - - jupyter - - matplotlib + - notebook + - matplotlib-base - ipywidgets - plotly - qgrid -# - pyside2 # (Qt GUI) Issue #1652 -# --- Not required for conda-forge package and Numba integration pipeline --- + # --- Packages not required for conda-forge recipe --- # tardis-sn/nuclear dependencies - beautifulsoup4 @@ -56,21 +59,19 @@ dependencies: - nbconvert - nbformat - nbsphinx - - docutils=0.16 # Issue #1522 - snakeviz + - dot2tex # Test/Coverage - pytest - pytest-cov - pytest-html - - python-dokuwiki - coverage # Code quality - - black=21.12b0 + - black =22.3 + - ruff # Other - git-lfs - - pip: - - dot2tex # conda-forge package requires python>=3.8