# PISCOLA: Python for Intelligent Supernova-COsmology Light-curve Analysis
**Supernova light-curve fitting code in python**
Although the main purpose of PISCOLA is to fit type Ia supernovae, it can be used to fit other types of supernovae or even other transients.
[](https://github.com/temuller/piscola)
[](https://piscola.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/temuller/piscola/blob/master/LICENSE)
[](https://github.com/temuller/piscola/actions/workflows/main.yml)
[](https://raw.githubusercontent.com/temuller/piscola/master/coverage.svg)
[](https://pypi.org/project/piscola/)
[](https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.3266M/abstract)
Read the full documentation at: [piscola.readthedocs.io](http://piscola.readthedocs.io/). See below for a summary.
___
## Installation
PISCOLA can be installed in the usual ways, via pip:
```
pip install piscola
```
or from source:
```
git clone https://github.com/temuller/piscola.git
cd piscola
pip install .
```
### Requirements
PISCOLA has the following requirements:
```
numpy
pandas
matplotlib
peakutils
requests
sfdmap
extinction
astropy
scipy
george
pickle5
pytest (optional: for testing the code)
```
### Tests
To run the tests, go to the parent directory and run the following command:
```
pytest -v
```
## Using PISCOLA
PISCOLA can fit the supernova light curves and correct them in a few lines of code:
```python
sn = piscola.call_sn(<sn_file>)
sn.fit()
```
The light-curve parameters are saved in a dictionary and can be accessed directly:
```python
sn.lc_parameters # dictionary
sn.dm15
```
You can find an example of input file in the [data](https://github.com/temuller/piscola/tree/master/data) directory.
## Citing PISCOLA
If you make use of PISCOLA in your projects, please cite [Müller-Bravo et al. (2022)](https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.3266M/abstract). See below for the bibtex format:
```code
@ARTICLE{2022MNRAS.512.3266M,
author = {{M{\"u}ller-Bravo}, Tom{\'a}s E. and {Sullivan}, Mark and {Smith}, Mathew and {Frohmaier}, Chris and {Guti{\'e}rrez}, Claudia P. and {Wiseman}, Philip and {Zontou}, Zoe},
title = "{PISCOLA: a data-driven transient light-curve fitter}",
journal = {\mnras},
keywords = {supernovae: general, cosmology: observations, distance scale, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
year = 2022,
month = may,
volume = {512},
number = {3},
pages = {3266-3283},
doi = {10.1093/mnras/stab3065},
archivePrefix = {arXiv},
eprint = {2110.11340},
primaryClass = {astro-ph.HE},
adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.3266M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
```
## Contributing and raising an issue
The recommended way is to use the [issues](https://github.com/temuller/piscola/issues) page or send a pull request. Otherwise, you can contact me directly.
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"description": "# PISCOLA: Python for Intelligent Supernova-COsmology Light-curve Analysis\n\n**Supernova light-curve fitting code in python**\n\nAlthough the main purpose of PISCOLA is to fit type Ia supernovae, it can be used to fit other types of supernovae or even other transients.\n\n[](https://github.com/temuller/piscola)\n[](https://piscola.readthedocs.io/en/latest/?badge=latest)\n[](https://github.com/temuller/piscola/blob/master/LICENSE)\n[](https://github.com/temuller/piscola/actions/workflows/main.yml)\n[](https://raw.githubusercontent.com/temuller/piscola/master/coverage.svg)\n\n[](https://pypi.org/project/piscola/)\n[](https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.3266M/abstract)\n\nRead the full documentation at: [piscola.readthedocs.io](http://piscola.readthedocs.io/). See below for a summary.\n\n___\n## Installation\n\nPISCOLA can be installed in the usual ways, via pip:\n\n```\npip install piscola\n```\n\nor from source:\n\n```\ngit clone https://github.com/temuller/piscola.git\ncd piscola\npip install .\n```\n\n### Requirements\n\nPISCOLA has the following requirements:\n\n```\nnumpy\npandas\nmatplotlib\npeakutils\nrequests\nsfdmap\nextinction\nastropy\nscipy\ngeorge\npickle5\npytest (optional: for testing the code)\n```\n\n### Tests\n\nTo run the tests, go to the parent directory and run the following command:\n\n```\npytest -v\n```\n\n## Using PISCOLA\n\nPISCOLA can fit the supernova light curves and correct them in a few lines of code:\n\n\n```python\nsn = piscola.call_sn(<sn_file>)\nsn.fit()\n```\n\nThe light-curve parameters are saved in a dictionary and can be accessed directly:\n\n```python\nsn.lc_parameters # dictionary\nsn.dm15\n```\n\nYou can find an example of input file in the [data](https://github.com/temuller/piscola/tree/master/data) directory.\n\n## Citing PISCOLA\n\nIf you make use of PISCOLA in your projects, please cite [M\u00fcller-Bravo et al. (2022)](https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.3266M/abstract). See below for the bibtex format:\n\n```code\n@ARTICLE{2022MNRAS.512.3266M,\n author = {{M{\\\"u}ller-Bravo}, Tom{\\'a}s E. and {Sullivan}, Mark and {Smith}, Mathew and {Frohmaier}, Chris and {Guti{\\'e}rrez}, Claudia P. and {Wiseman}, Philip and {Zontou}, Zoe},\n title = \"{PISCOLA: a data-driven transient light-curve fitter}\",\n journal = {\\mnras},\n keywords = {supernovae: general, cosmology: observations, distance scale, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},\n year = 2022,\n month = may,\n volume = {512},\n number = {3},\n pages = {3266-3283},\n doi = {10.1093/mnras/stab3065},\narchivePrefix = {arXiv},\n eprint = {2110.11340},\n primaryClass = {astro-ph.HE},\n adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.3266M},\n adsnote = {Provided by the SAO/NASA Astrophysics Data System}\n}\n```\n\n## Contributing and raising an issue\n\nThe recommended way is to use the [issues](https://github.com/temuller/piscola/issues) page or send a pull request. Otherwise, you can contact me directly.\n",
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