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‎.readthedocs.yaml

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# Read the Docs configuration file
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version: 2
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sphinx:
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builder: html
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configuration: doc/source/conf.py
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build:
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os: ubuntu-22.04
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tools:
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python: "3.8"
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python:
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system_packages: True
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install:
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- method: pip
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path: .
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extra_requirements:
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- lotkavolterra_example
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- docs

‎.travis.yml

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‎README.md

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# pySELFI #
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[![arXiv](https://img.shields.io/badge/astro--ph.CO-arxiv%3A1902.10149-B31B1B.svg?style=flat)](https://arxiv.org/abs/1902.10149)
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[![arXiv](https://img.shields.io/badge/astro--ph.CO-arxiv%3A2209.11057-B31B1B.svg?style=flat)](https://arxiv.org/abs/2209.11057)
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[![GitHub version](https://img.shields.io/github/tag/florent-leclercq/pyselfi.svg?label=version)](https://github.com/florent-leclercq/pyselfi)
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[![GitHub commits](https://img.shields.io/github/commits-since/florent-leclercq/pyselfi/v1.2.svg)](https://github.com/florent-leclercq/pyselfi/commits)
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[![GitHub commits](https://img.shields.io/github/commits-since/florent-leclercq/pyselfi/v2.0.svg)](https://github.com/florent-leclercq/pyselfi/commits)
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[![DOI](https://zenodo.org/badge/197575311.svg)](https://zenodo.org/badge/latestdoi/197575311)
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[![GPLv3 license](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://github.com/florent-leclercq/pyselfi/blob/master/LICENSE)
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[![PyPI version](https://badge.fury.io/py/pyselfi.svg)](https://badge.fury.io/py/pyselfi)
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[![Docs](https://readthedocs.org/projects/pyselfi/badge/)](http://pyselfi.readthedocs.io/en/latest/)
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[![Build Status](https://travis-ci.com/florent-leclercq/pyselfi.svg?branch=master)](https://travis-ci.com/florent-leclercq/pyselfi)
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[![Website florent-leclercq.eu](https://img.shields.io/website-up-down-green-red/http/pyselfi.florent-leclercq.eu.svg)](http://pyselfi.florent-leclercq.eu/)
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Simulator Expansion for Likelihood-Free Inference (SELFI): a python implementation.
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## Documentation ##
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The code's homepage is [http://pyselfi.florent-leclercq.eu](http://pyselfi.florent-leclercq.eu). The documentation is available on readthedocs at [https://pyselfi.readthedocs.io/](https://pyselfi.readthedocs.io/). Limited user-support may be asked from the main author, Florent Leclercq.
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The code's homepage is [https://pyselfi.florent-leclercq.eu](https://pyselfi.florent-leclercq.eu). The documentation is available on readthedocs at [https://pyselfi.readthedocs.io/](https://pyselfi.readthedocs.io/). Limited user-support may be asked from the main author, Florent Leclercq.
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## Contributors ##
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* Florent Leclercq, florent.leclercq@polytechnique.org
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* Florent Leclercq, florent.leclercq@iap.fr
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## Reference ##
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To acknowledge the use of pySELFI in research papers, please cite its [doi:10.5281/zenodo.3341588](https://doi.org/10.5281/zenodo.3341588) (or for the latest version, see the badge above), as well as the paper <a href="https://arxiv.org/abs/1902.10149" target="blank">Leclercq <i>et al.</i> (2019)</a>:
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To acknowledge the use of pySELFI in research papers, please cite its [doi:10.5281/zenodo.3341588](https://doi.org/10.5281/zenodo.3341588) (or for the latest version, see the badge above), as well as the papers [Leclercq <i>et al.</i> (2019)](https://arxiv.org/abs/1902.10149) and [Leclercq (2022)](https://arxiv.org/abs/2209.11057):
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*Primordial power spectrum and cosmology from black-box galaxy surveys*<br/>
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* *Primordial power spectrum and cosmology from black-box galaxy surveys*<br/>
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F. Leclercq, W. Enzi, J. Jasche, A. Heavens<br/>
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<a href="http://dx.doi.org/10.1093/mnras/stz2718" target="blank">MNRAS <b>490</b>, 4237 (2019)</a>, <a href="http://arxiv.org/abs/1902.10149" target="blank">arXiv:1902.10149</a> [<a href="http://arxiv.org/abs/1902.10149" target="blank">astro-ph.CO</a>] [<a href="https://ui.adsabs.harvard.edu/?#abs/2019MNRAS.490.4237L" target="blank">ADS</a>] [<a href="http://arxiv.org/pdf/1902.10149" class="document" target="blank">pdf</a>]
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* *Simulation-based inference of Bayesian hierarchical models while checking for model misspecification*<br/>
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F. Leclercq<br/>
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Proceedings of the <a href="https://maxent22.see.asso.fr/" target="blank">41st International Conference on Bayesian and Maximum Entropy methods in Science and Engineering (MaxEnt2022)</a>, 18-22 July 2022, Paris, France<br />
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<a href="https://doi.org/10.3390/psf2022005004" target="blank"> Physical Sciences Forum <b>5</b>, 4 (2022)</a>, <a href="https://arxiv.org/abs/2209.11057" target="blank">arXiv:2209.11057</a> [<a href="https://arxiv.org/abs/2209.11057" target="blank">astro-ph.CO</a>] [<a href="https://ui.adsabs.harvard.edu/?#abs/2022arXiv220911057L" target="blank">ADS</a>] [<a href="https://arxiv.org/pdf/2209.11057" class="document" target="blank">pdf</a>]
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@ARTICLE{pySELFI,
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author = {{Leclercq}, Florent and {Enzi}, Wolfgang and {Jasche}, Jens and {Heavens}, Alan},
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title = "{Primordial power spectrum and cosmology from black-box galaxy surveys}",
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journal = {\mnras},
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keywords = {methods: statistical, cosmological parameters, large-scale structure of Universe, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
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year = "2019",
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month = "Dec",
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volume = {490},
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number = {3},
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pages = {4237-4253},
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doi = {10.1093/mnras/stz2718},
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archivePrefix = {arXiv},
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eprint = {1902.10149},
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primaryClass = {astro-ph.CO},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.4237L},
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adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@ARTICLE{pySELFI1,
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author = {{Leclercq}, Florent and {Enzi}, Wolfgang and {Jasche}, Jens and {Heavens}, Alan},
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title = "{Primordial power spectrum and cosmology from black-box galaxy surveys}",
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journal = {\mnras},
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keywords = {methods: statistical, cosmological parameters, large-scale structure of Universe, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
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year = "2019",
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month = "Dec",
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volume = {490},
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number = {3},
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pages = {4237-4253},
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doi = {10.1093/mnras/stz2718},
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archivePrefix = {arXiv},
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eprint = {1902.10149},
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primaryClass = {astro-ph.CO},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.4237L},
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}
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@ARTICLE{pySELFI2,
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author = {{Leclercq}, Florent},
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title = "{Simulation-based inference of Bayesian hierarchical models while checking for model misspecification}",
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journal = {Physical Sciences Forum},
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keywords = {Statistics - Methodology, Astrophysics - Instrumentation and Methods for Astrophysics, Mathematics - Statistics Theory, Quantitative Biology - Populations and Evolution, Statistics - Machine Learning},
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year = "2022",
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month = "Sep",
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volume = {5},
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pages = {4},
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doi = {10.3390/psf2022005004},
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archivePrefix = {arXiv},
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eprint = {2209.11057},
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primaryClass = {stat.ME},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220911057L},
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}
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## License ##
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This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. By downloading and using pySELFI, you agree to the [LICENSE](LICENSE), distributed with the source code in a text file of the same name.
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This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. By downloading and using pySELFI, you agree to the [LICENSE](https://github.com/florent-leclercq/pyselfi/blob/master/LICENSE), distributed with the source code in a text file of the same name.

‎doc/source/api/blackboxes/lotkavolterra.rst

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pyselfi_examples.lotkavolterra.model.blackbox_LV module
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=======================================================
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.. automodule:: pyselfi_examples.lotkavolterra.model.blackbox_LV
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/source/api/blackboxes_api.rst

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Gaussian random field
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---------------------
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Modules are located in ``pyselfi_examples/grf/model/``.
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Modules are located in ``src/pyselfi_examples/grf/model/``.
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.. currentmodule:: pyselfi_examples.grf.model
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Galaxy survey
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-------------
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Modules are located in ``pyselfi_examples/simbelmyne/model/``.
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Modules are located in ``src/pyselfi_examples/simbelmyne/model/``.
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.. currentmodule:: pyselfi_examples.simbelmyne.model
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blackboxes/simbelmyne
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Lotka-Volterra system
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---------------------
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Modules are located in ``src/pyselfi_examples/lotkavolterra/model/``.
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.. currentmodule:: pyselfi_examples.lotkavolterra.model
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.. autosummary::
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blackbox_LV
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.. toctree::
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:hidden:
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:maxdepth: 2
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blackboxes/lotkavolterra

‎doc/source/api/inference_api.rst

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Primordial power spectrum
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-------------------------
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Modules are located in ``pyselfi/power_spectrum/``.
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Modules are located in ``src/pyselfi/power_spectrum/``.
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power_spectrum/prior
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power_spectrum/selfi
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Lotka-Volterra system
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---------------------
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Modules are located in ``src/pyselfi/lotkavolterra/``.
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.. currentmodule:: pyselfi
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.. autosummary::
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lotkavolterra.prior
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lotkavolterra.selfi
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.. toctree::
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:hidden:
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:maxdepth: 2
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lotkavolterra/prior
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lotkavolterra/selfi

‎doc/source/api/lotkavolterra/prior.rst

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pyselfi.lotkavolterra.prior module
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===================================
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.. automodule:: pyselfi.lotkavolterra.prior
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/source/api/lotkavolterra/selfi.rst

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pyselfi.lotkavolterra.selfi module
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===================================
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.. automodule:: pyselfi.lotkavolterra.selfi
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/source/conf.py

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#!/usr/bin/env python
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#-------------------------------------------------------------------------------------
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# pySELFI v1.2 -- doc/source/conf.py
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# Copyright (C) 2019-2019 Florent Leclercq.
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#
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# pySELFI v2.0 -- doc/source/conf.py
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# Copyright (C) 2019-2023 Florent Leclercq.
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#
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# This file is part of the pySELFI distribution
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# (https://github.com/florent-leclercq/pyselfi/)
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, version 3.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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# General Public License for more details.
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#
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#
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# The text of the license is located in the root directory of the source package.
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#-------------------------------------------------------------------------------------
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# -- Project information -----------------------------------------------------
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project = 'pySELFI'
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copyright = '2018-2019, Florent Leclercq'
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copyright = '2018-2023, Florent Leclercq'
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author = 'Florent Leclercq'
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# The full version, including alpha/beta/rc tags
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release = '1.2'
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release = '2.0'
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# -- General configuration ---------------------------------------------------
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#
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# This is also used if you do content translation via gettext catalogs.
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language = None
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language = 'en'
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# List of patterns, relative to source directory, that match files and
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‎doc/source/description.rst

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|arXiv| |GitHub version| |GitHub commits| |DOI| |GPLv3 license| |PyPI version| |Docs| |Build Status| |Website florent-leclercq.eu|
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|arXiv1| |arXiv2| |GitHub version| |GitHub commits| |DOI| |GPLv3 license| |PyPI version| |Docs| |Website florent-leclercq.eu|
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.. |arXiv| image:: https://img.shields.io/badge/astro--ph.CO-arxiv%3A1902.10149-B31B1B.svg?style=flat
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.. |arXiv1| image:: https://img.shields.io/badge/astro--ph.CO-arxiv%3A1902.10149-B31B1B.svg?style=flat
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:target: https://arxiv.org/abs/1902.10149
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.. |arXiv2| image:: https://img.shields.io/badge/astro--ph.CO-arxiv%3A2209.11057-B31B1B.svg?style=flat
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:target: https://arxiv.org/abs/2209.11057
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.. |GitHub version| image:: https://img.shields.io/github/tag/florent-leclercq/pyselfi.svg?label=version
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:target: https://github.com/florent-leclercq/pyselfi
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.. |GitHub commits| image:: https://img.shields.io/github/commits-since/florent-leclercq/pyselfi/v1.2.svg
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.. |GitHub commits| image:: https://img.shields.io/github/commits-since/florent-leclercq/pyselfi/v2.0.svg
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.. |Docs| image:: https://readthedocs.org/projects/pyselfi/badge/
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.. |Build Status| image:: https://travis-ci.com/florent-leclercq/pyselfi.svg?branch=master
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:target: https://travis-ci.com/florent-leclercq/pyselfi
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:target: http://pyselfi.florent-leclercq.eu/
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