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arjunsavel/cortecs

cortecs

status arXiv PyPI version Conda Version Tests codecov Maintainability License: MIT Code style: black pre-commit CodeQL Documentation Status Paper compilation GitHub repo size PyPI - Python Version

A Python package for decreasing the memory footprint of opacity functions. The primary functionality is compressing opacity functions with varying flexibility. Current methods include

  • polynomial fitting
  • PCA-based fitting
  • neural network fitting

All fits are currently made in along the temperature and pressure axes.

Additionally, cortecs can chunk up opacity functions. The radiative transfer problem can often be cast as embarassingly parallel, so each chunk can be sent to a different CPU.

Installation instructions

cortecs can be installed via pip:

pip install cortecs

or conda:

conda install -c conda-forge cortecs

or from source:

git clone
cd cortecs
pip install -e .

To install from source with optional neural network support:

pip install -e .[neural_networks]