pyEQUIB

pyEQUIB - Python Package for Plasma Diagnostics and Abundance Analysis

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Description

The pyEQUIB library is a collection of Python programs developed to perform plasma diagnostics and abundance analysis using emission line fluxes measured in ionzed nebulae. It uses the AtomNeb Python Package to read collision strengths and transition probabilities for collisionally excited lines (CEL), and recombination coefficients for recombination lines (RL). This Python package can be used to determine interstellar extinctions, electron temperatures, electron densities, and ionic abundances from the measured fluxes of emission lines. It mainly contains the follwing API functions written purely in Python:

Installation

Dependent Python Packages

This package requires the following packages:

  • To get this package with the AtomNeb FITS files, you can simply use git command as follows:
git clone --recursive https://github.com/equib/pyEQUIB

To install the last version, all you should need to do is

$ python setup.py install

To install the stable version, you can use the preferred installer program (pip):

$ pip install pyequib

or you can install it from the cross-platform package manager conda:

$ conda install -c conda-forge pyequib

How to Use

The Documentation of the Python functions provides in detail in the API Documentation (equib.github.io/pyEQUIB/doc).

See Jupyter Notebooks: Notebooks.ipynb

Run Jupyter Notebooks on Binder:

https://mybinder.org/badge_logo.svg

There are three main object units:

Documentation

For more information on how to use the API functions from the pyEQUIB libray, please read the API Documentation published on equib.github.io/pyEQUIB.

References

Citation

Using the pyEQUIB Python package in a scholarly publication? Please cite thess papers:

@article{Danehkar2020,
  author = {{Danehkar}, Ashkbiz},
  title = {pyEQUIB Python Package, an addendum to proEQUIB: IDL Library
           for Plasma Diagnostics and Abundance Analysis},
  journal = {Journal of Open Source Software},
  volume = {5},
  number = {55},
  pages = {2798},
  year = {2020},
  doi = {10.21105/joss.02798}
}

and if you use the proEQUIB IDL library:

@article{Danehkar2018,
  author = {{Danehkar}, Ashkbiz},
  title = {proEQUIB: IDL Library for Plasma Diagnostics and Abundance Analysis},
  journal = {Journal of Open Source Software},
  volume = {3},
  number = {32},
  pages = {899},
  year = {2018},
  doi = {10.21105/joss.00899}
}

Learn More

Documentation https://pyequib.readthedocs.io/
Repository https://github.com/equib/pyEQUIB
Issues & Ideas https://github.com/equib/pyEQUIB/issues
Conda-Forge https://anaconda.org/conda-forge/pyequib
PyPI https://pypi.org/project/pyequib/
DOI 10.21105/joss.02798
Archive 10.5281/zenodo.4287575