GPU-accelerated Lomb-Scargle implementations.
ARCHIVE NOTICE
This repository is no longer being maintained.
Before installing any dependencies or writing code, it's a great idea to create a
virtual environment. LINCC-Frameworks engineers primarily use conda to manage virtual
environments. If you have conda installed locally, you can run the following to
create and activate a new environment.
>> conda create env -n <env_name> python=3.10
>> conda activate <env_name>
This project depends on CUDA-Python. It has a couple of requirements that must be installed manually. They are outlined here: https://nvidia.github.io/cuda-python/install.html#runtime-requirements
Perhaps it goes without saying, you'll need an Nvidia GPU to run on.
Once you have created a new environment, you can install this project for local development using the following commands:
>> pip install -e .'[dev]'
>> pre-commit install
>> conda install pandoc
Notes:
- The single quotes around
'[dev]'may not be required for your operating system. pre-commit installwill initialize pre-commit for this local repository, so that a set of tests will be run prior to completing a local commit. For more information, see the Python Project Template documentation on pre-commit- Install
pandocallows you to verify that automatic rendering of Jupyter notebooks into documentation for ReadTheDocs works as expected. For more information, see the Python Project Template documentation on Sphinx and Python Notebooks
