improvement/parameter-dependency-on-every-iteration

.github/workflows/main_pipeline.yml

@@ -16,7 +16,7 @@ jobs:
       uses: actions/setup-python@v5
       with:
         python-version: 3.11
-    - uses: pre-commit/action@v3.0.0
+    - uses: pre-commit/action@v3.0.1
   ci:
     strategy:
       fail-fast: false

.github/workflows/publish_pypi.yml

@@ -10,6 +10,6 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Build and publish to pypi
-        uses: JRubics/poetry-publish@v1.17
+        uses: JRubics/poetry-publish@v2.0
         with:
           pypi_token: ${{ secrets.PYPI_API_TOKEN }}

.pre-commit-config.yaml

@@ -16,19 +16,16 @@ repos:
       - id: detect-private-key
       - id: forbid-new-submodules
       - id: check-docstring-first
-  - repo: https://github.com/asottile/reorder-python-imports
-    rev: v3.12.0
-    hooks:
-      - id: reorder-python-imports
+
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.15
+    rev: v0.3.4
     hooks:
       - id: ruff
         args: [ --fix ]
       - id: ruff-format
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: 'v1.8.0'
+    rev: 'v1.9.0'
     hooks:
     -   id: mypy
         args: [--strict, --ignore-missing-imports, --allow-untyped-decorators, --allow-subclassing-any]

examples/blueprint_example/src/example_blueprint_main.py

@@ -7,6 +7,7 @@
 executor class tailored for the NlBlueprint team and utility functions for pre-
 submission setup and post-run cleanup.
 """
+
 import os
 import shutil
 from typing import Any

examples/blueprint_example/src/processing_function.py

@@ -3,6 +3,7 @@
 the cost function defined in total_cost and writes it, together with the optimization
 parameters to a csv file in a format that can be read by smart-stopos and use to
 generate new sets of parameters."""
+
 import os
 import pickle
 from argparse import ArgumentParser

examples/blueprint_example/src/unified_simulation_script_state_with_translation.py

@@ -10,6 +10,7 @@
 saved, how many runs per data point to simulate, the name of the saved file and whether
 the simulation results should be plotted.
 """
+
 import copy
 import os
 import pickle

examples/run_examples.py

@@ -5,6 +5,7 @@
 If the `main`-method takes an argument `no_output` this will be passed as `True`
 to avoid creating plots etc.
 """
+
 import importlib
 import inspect
 import os

examples/wobbly_function/analyse_function_output.py

@@ -3,6 +3,7 @@
 
 csv_output.csv.
 """
+
 import csv
 import os
 from argparse import ArgumentParser

examples/wobbly_function/example_wobbly_bayesian.py

@@ -1,5 +1,6 @@
 """This module demonstrates the process for a blackbox bayesian optimization using the
 Yotse framework."""
+
 from bayes_opt import UtilityFunction
 
 from examples.wobbly_function.example_wobbly_main import remove_files_after_run

examples/wobbly_function/example_wobbly_main.py

@@ -4,6 +4,7 @@
 It leverages genetic algorithms for the optimization process, handles file management,
 and cleans up after execution, showcasing a very basic use-case.
 """
+
 import os
 import shutil
 from typing import Any

examples/wobbly_function/example_wobbly_param_switching.py

@@ -1,5 +1,6 @@
 """This module demonstrates the process for parameter switching during optimization
 using the Yotse framework."""
+
 from examples.wobbly_function.example_wobbly_main import remove_files_after_run
 from examples.wobbly_function.example_wobbly_main import wobbly_pre
 from yotse.execution import Executor
@@ -63,11 +64,11 @@ def main() -> None:
     print("Solution after first GA: ", solution)
 
     # Switching active params from param 1 & 2 to param 2 & 3
-    param_switch_example.experiment.parameters[0].parameter_active = False
-    param_switch_example.experiment.parameters[2].parameter_active = True
+    param_switch_example.experiment.set_parameter_activity("x", False)
+    param_switch_example.experiment.set_parameter_activity("z", True)
     # create new datapoints with new active params and write them to experiment
     param_switch_example.experiment.data_points = (
-        param_switch_example.experiment.create_datapoint_c_product()
+        param_switch_example.experiment.create_initial_active_param_cprod()
     )
     # todo: maybe nice additional functionality could be that this is done automatically when params have changed.
 

examples/wobbly_function/example_wobbly_resume.py

@@ -4,6 +4,7 @@
 It initializes the optimization process, runs for a few generations, and then showcases
 how to resume the process from where it left off.
 """
+
 from examples.wobbly_function.example_wobbly_main import remove_files_after_run
 from examples.wobbly_function.example_wobbly_main import wobbly_pre
 from yotse.execution import Executor
@@ -27,9 +28,9 @@ def main() -> None:
 
     # write resume parameter to experiment
     resume_experiment = wobbly_pre()
-    resume_experiment.system_setup.cmdline_arguments[
-        "--resume"
-    ] = stop_resume_example.aux_dir
+    resume_experiment.system_setup.cmdline_arguments["--resume"] = (
+        stop_resume_example.aux_dir
+    )
 
     resume_example = Executor(experiment=resume_experiment)
     for i in range(

examples/wobbly_function/example_wobbly_whitebox.py

@@ -1,5 +1,6 @@
 """This module demonstrates the process for a whitebox optimization using the Yotse
 framework."""
+
 import random
 from typing import Any
 

examples/wobbly_function/wobbly_function.py

@@ -2,6 +2,7 @@
 Usage:
     python3 function.py -filebasename <folder-to-store-output>/<somefilebasename> -x 3 -y 5.5
 """
+
 import csv
 from argparse import ArgumentParser
 from typing import Any