Initial commit: v0.1.0

2025-06-07 08:31:12 +00:00 · 2025-01-10 17:03:16 +01:00 · 2025-01-10 17:03:16 +01:00 · c041384662
commit c041384662
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--- a/docs/_sources/CONTRIBUTING.md.txt
+++ b/docs/_sources/CONTRIBUTING.md.txt
@ -0,0 +1,58 @@
+# Contributing to SelfiSys
+
+We welcome contributions to the SelfiSys repository! Please follow these guidelines when contributing.
+
+---
+
+## Reporting Issues
+
+If you find a bug or have a suggestion, please open an issue in the [GitHub repository](https://github.com/hoellin/selfisys_public). Include as much detail as possible:
+- Steps to reproduce the issue
+- Expected vs. actual behaviour
+- Relevant error messages or logs (if applicable)
+- Suggestions for improvement (if applicable)
+
+If you are unsure whether your issue is a bug or have questions about the code, you are welcome to open an issue for discussion.
+
+## Submitting Contributions
+
+1. Fork the repository and create a new branch for your changes.
+2. Ensure your contributions are well-documented and adhere to the highest coding standards.
+3. Test your changes thoroughly before submitting:
+   - Ensure Jupyter notebooks run without errors from top to bottom.
+   - Validate new functionality or fixes using appropriate test cases.
+4. Before submitting a pull request, synchronise your fork with the main repository to incorporate upstream changes.
+   - Add the main repository as a remote.
+        ```bash
+        git remote add upstream https://github.com/hoellin/selfisys_public.git
+        ```
+    - Fetch the latest changes from the upstream repository.
+        ```bash
+        git fetch upstream
+        ```
+    - Merge the changes into your local repository.
+        ```bash
+        git merge upstream/main
+        ```
+5. Open a pull request describing your changes to the main repository.
+
+## Style Guidelines
+
+Follow best practices for Python coding and Jupyter notebooks.
+
+### Python code
+
+Refer to the [PEP 8 Style Guide](https://pep8.org/) for Python coding standards.
+
+### Jupyter Notebooks
+
+- Use clear and concise Markdown cells to explain code and results.
+- Avoid leaving unnecessary output (e.g., debugging print statements).
+- Ensure notebooks are runnable from top to bottom.
+- For tips on creating clean and effective Jupyter notebooks, see [Jupyter Notebook Best Practices](https://realpython.com/jupyter-notebook-best-practices/).
+
+---
+
+## Questions?
+
+If you have any questions or need further clarification, feel free to [contact the authors](mailto:tristan.hoellinger@iap.fr).
--- a/docs/_sources/README.md.txt
+++ b/docs/_sources/README.md.txt
@ -0,0 +1,83 @@
+# SelfiSys: Assess the Impact of Systematic Effects in Galaxy Surveys
+
+[![arXiv](https://img.shields.io/badge/astro--ph.CO-arxiv%3A2412.04443-B31B1B.svg?style=flat)](https://arxiv.org/abs/2412.04443)
+[![GPLv3 license](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://github.com/hoellin/selfisys_public/blob/main/LICENSE)
+[![GitHub version](https://img.shields.io/github/tag/hoellin/selfisys_public.svg?label=version)](https://github.com/hoellin/selfisys_public)
+[![GitHub last commit](https://img.shields.io/github/last-commit/hoellin/selfisys_public.svg)](https://github.com/hoellin/selfisys_public/commits/main)
+
+
+**SelfiSys** is a Python package designed to address the issue of model misspecification in field-based, implicit likelihood cosmological inference.
+
+It leverages the inferred initial matter power spectrum, enabling a thorough diagnosis of systematic effects in large-scale spectroscopic galaxy surveys.
+
+## Key Features
+
+- **Custom hidden-box forward models**
+
+We provide a `HiddenBox` class to simulate realistic spectroscopic galaxy surveys. It accommodates fully non-linear gravitational evolution, and incorporates multiple systematic effects observed in real-world survey, e.g., misspecified galaxy bias, survey mask, selection functions, dust extinction, line interlopers, or inaccurate gravity solver.
+
+- **Diagnosis of systematic effects**
+
+Diagnose the impact of systematic effects using the inferred initial matter power spectrum, prior to performing cosmological inference.
+
+- **Cosmological inference**
+
+Perform inference of cosmological parameters using Approximate Bayesian Computation (ABC) with a Population Monte Carlo (PMC) sampler.
+
+---
+
+## Documentation
+
+The documentation, including a detailed API reference, is available at [hoellin.github.io/selfisys_public](https://hoellin.github.io/selfisys_public/).
+
+For practical examples demonstrating how to use SelfiSys, visit the [SelfiSys Examples Repository](https://github.com/hoellin/selfisys_examples).
+
+## Contributors
+
+- **Tristan Hoellinger**, [tristan.hoellinger@iap.fr](mailto:tristan.hoellinger@iap.fr)  
+  Principal developer and maintainer, Institut d’Astrophysique de Paris (IAP).
+  
+For information on contributing, refer to [CONTRIBUTING.md](CONTRIBUTING.md).
+
+## References
+
+If you use the SelfiSys package in your research, please cite the following paper and feel free to [contact the authors](mailto:tristan.hoellinger@iap.fr) for feedback, collaboration opportunities, or other inquiries.
+
+**Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum**
+*Hoellinger, T. and Leclercq, F., 2024*
+[arXiv:2412.04443](https://arxiv.org/abs/2412.04443) [[astro-ph.CO]](https://arxiv.org/abs/2412.04443) [[ADS]](https://ui.adsabs.harvard.edu/abs/arXiv:2412.04443) [[pdf]](https://arxiv.org/pdf/2412.04443)
+
+BibTeX entry for citation:
+```bibtex
+@ARTICLE{hoellinger2024diagnosing,
+      author = {Hoellinger, Tristan and Leclercq, Florent},
+      title = "{Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum}",
+      journal = {arXiv e-prints},
+   keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
+         year = 2024,
+      month = dec,
+         eid = {arXiv:2412.04443},
+      pages = {arXiv:2412.04443},
+         doi = {10.48550/arXiv.2412.04443},
+archivePrefix = {arXiv},
+      eprint = {2412.04443},
+primaryClass = {astro-ph.CO},
+      adsurl = {https://ui.adsabs.harvard.edu/abs/2024arXiv241204443H},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+```
+
+## Requirements
+
+The code is written in Python 3.10 and depends on the following packages:
+- [`pySELFI`](https://pyselfi.readthedocs.io/en/latest/): Python implementation of the Simulator Expansion for Likelihood-Free Inference.
+- [`Simbelmynë`](https://simbelmyne.readthedocs.io/en/latest/): A hierarchical probabilistic simulator for generating synthetic galaxy survey data.
+- [`ELFI`](https://elfi.readthedocs.io/en/latest/): A statistical software package for likelihood-free inference, implementing in particular Approximate Bayesian Computation (ABC) with a Population Monte Carlo (PMC) sampler.
+
+A comprehensive list of dependencies, including version specifications to ensure reproducibility, will be provided in a yaml file, along with installation instructions, in a future release.
+
+---
+
+## License
+
+This software is distributed under the GPLv3 Licence. Please review the [LICENSE](https://github.com/hoellin/selfisys_public/blob/main/LICENSE) file in the repository to understand the terms of use and ensure compliance. By downloading and using this software, you agree to the terms of the licence.
--- a/docs/_sources/REFERENCES.md.txt
+++ b/docs/_sources/REFERENCES.md.txt
@ -0,0 +1,44 @@
+# References
+
+If you use the SelfiSys package in your research, please cite the following paper and feel free to [contact the authors](mailto:tristan.hoellinger@iap.fr) for feedback, collaboration opportunities, or other inquiries.
+
+**Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum**
+*Hoellinger, T. and Leclercq, F., 2024*
+[arXiv:2412.04443](https://arxiv.org/abs/2412.04443) [[astro-ph.CO]](https://arxiv.org/abs/2412.04443) [[ADS]](https://ui.adsabs.harvard.edu/abs/arXiv:2412.04443) [[pdf]](https://arxiv.org/pdf/2412.04443)
+
+BibTeX entry for citation:
+```bibtex
+@ARTICLE{hoellinger2024diagnosing,
+      author = {Hoellinger, Tristan and Leclercq, Florent},
+      title = "{Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum}",
+      journal = {arXiv e-prints},
+   keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
+         year = 2024,
+      month = dec,
+         eid = {arXiv:2412.04443},
+      pages = {arXiv:2412.04443},
+         doi = {10.48550/arXiv.2412.04443},
+archivePrefix = {arXiv},
+      eprint = {2412.04443},
+primaryClass = {astro-ph.CO},
+      adsurl = {https://ui.adsabs.harvard.edu/abs/2024arXiv241204443H},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+```
+
+Other references relevant to the SelfiSys pipeline and cited in the code are listed below.
+
+- **[jasche2010bayesian]**
+Jasche, J., Kitaura, F. S., Wandelt, B. D., and Enßlin, T. A., “Bayesian power-spectrum inference for large-scale structure data”, <i>Monthly Notices of the Royal Astronomical Society</i>, vol. 406, no. 1, OUP, pp. 60–85, 2010. [doi:10.1111/j.1365-2966.2010.16610.x](https://doi.org/10.48550/arXiv.0911.2493).
+
+- **[gil2015power]**
+Gil-Marín, H., “The power spectrum and bispectrum of SDSS DR11 BOSS galaxies - I. Bias and gravity”, <i>Monthly Notices of the Royal Astronomical Society</i>, vol. 451, no. 1, OUP, pp. 539–580, 2015. [doi:10.1093/mnras/stv961](https://doi.org/10.48550/arXiv.1407.5668).
+
+- **[howlett2015clustering]**
+Howlett, C., Ross, A. J., Samushia, L., Percival, W. J., and Manera, M., “The clustering of the SDSS main galaxy sample - II. Mock galaxy catalogues and a measurement of the growth of structure from redshift space distortions at z = 0.15”, <i>Monthly Notices of the Royal Astronomical Society</i>, vol. 449, no. 1, OUP, pp. 848–866, 2015. [doi:10.1093/mnras/stu2693](https://doi.org/10.48550/arXiv.1409.3238).
+
+- **[leclercq2019primordial]**
+Florent Leclercq, Wolfgang Enzi, Jens Jasche, Alan Heavens, Primordial power spectrum and cosmology from black-box galaxy surveys, Monthly Notices of the Royal Astronomical Society, Volume 490, Issue 3, December 2019, Pages 4237–4253, [doi:10.1093/mnras/stz2718](https://doi.org/10.1093/mnras/stz2718).
+
+- **[hoellinger2024diagnosing]**
+Hoellinger, T. and Leclercq, F., “Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum”, <i>arXiv e-prints</i>, Art. no. arXiv:2412.04443, 2024. [doi.org:10.48550/arXiv.2412.04443](https://doi.org/10.48550/arXiv.2412.04443).
--- a/docs/_sources/index.rst.txt
+++ b/docs/_sources/index.rst.txt
@ -0,0 +1,95 @@
+SelfiSys: Assess the Impact of Systematic Effects in Galaxy Surveys
+===================================================================
+
+.. image:: https://img.shields.io/badge/astro--ph.CO-arxiv%3A2412.04443-B31B1B.svg
+   :target: https://arxiv.org/abs/2412.04443
+   :alt: arXiv
+
+.. image:: https://img.shields.io/github/v/tag/hoellin/selfisys_public.svg?label=version
+   :target: https://github.com/hoellin/selfisys_public/releases
+   :alt: GitHub Release
+
+.. image:: https://img.shields.io/github/last-commit/hoellin/selfisys_public
+   :target: https://github.com/hoellin/selfisys_public/commits/main
+   :alt: Last Commit
+
+.. image:: https://img.shields.io/badge/License-GPLv3-blue.svg
+   :target: https://github.com/hoellin/selfisys_public/blob/main/LICENSE
+   :alt: License
+
+**SelfiSys** is a Python package designed to address the issue of model misspecification in field-based, implicit likelihood cosmological inference.
+
+It leverages the inferred initial matter power spectrum, enabling a thorough diagnosis of systematic effects in large-scale spectroscopic galaxy surveys.
+
+Key Features
+------------
+
+- **Custom hidden-box forward models**
+   We provide a `HiddenBox` class to simulate realistic spectroscopic galaxy surveys. It accommodates fully non-linear gravitational evolution, and incorporates multiple systematic effects observed in real-world survey, e.g., misspecified galaxy bias, survey mask, selection functions, dust extinction, line interlopers, or inaccurate gravity solver.
+- **Diagnosis of systematic effects**
+   Diagnose the impact of systematic effects using the inferred initial matter power spectrum, prior to performing cosmological inference.
+- **Cosmological inference**
+   Perform inference of cosmological parameters using Approximate Bayesian Computation (ABC) with a Population Monte Carlo (PMC) sampler.
+
+For practical examples demonstrating how to use SelfiSys, visit the `SelfiSys Examples Repository <https://github.com/hoellin/selfisys_examples>`_.
+
+References
+----------
+
+If you use the SelfiSys package in your research, please cite the following paper and feel free to `contact the authors <mailto:tristan.hoellinger@iap.fr>`_ for feedback, collaboration opportunities, or other inquiries.
+
+**Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum**
+*Hoellinger, T. and Leclercq, F., arXiv e-prints*, 2024
+`arXiv:2412.04443 <https://arxiv.org/abs/2412.04443>`_  
+`[astro-ph.CO] <https://arxiv.org/abs/2412.04443>`_  
+`[ADS] <https://ui.adsabs.harvard.edu/abs/arXiv:2412.04443>`_  
+`[pdf] <https://arxiv.org/pdf/2412.04443>`_
+
+Contributors
+------------
+
+- **Tristan Hoellinger**  
+  `tristan.hoellinger@iap.fr <mailto:tristan.hoellinger@iap.fr>`_
+  
+  Principal developer and maintainer, Institut d’Astrophysique de Paris (IAP).
+
+License
+-------
+
+This software is distributed under the GPLv3 Licence. Please review the `LICENSE <https://github.com/hoellin/selfisys_public/blob/main/LICENSE>`_ file in the repository to understand the terms of use and ensure compliance. By downloading and using this software, you agree to the terms of the licence.
+
+Requirements
+------------
+
+The code is written in Python 3.10 and depends on the following packages:
+
+- `pySELFI <https://pyselfi.readthedocs.io/en/latest/>`_: Python implementation of the Simulator Expansion for Likelihood-Free Inference.
+- `Simbelmynë <https://simbelmyne.readthedocs.io/en/latest/>`_: A hierarchical probabilistic simulator for generating synthetic galaxy survey data.
+- `ELFI <https://elfi.readthedocs.io/en/latest/>`_: A statistical software package for likelihood-free inference, implementing Approximate Bayesian Computation (ABC) with a Population Monte Carlo (PMC) sampler.
+
+A comprehensive list of dependencies, along with installation instructions, will be provided in a future release.
+
+.. toctree::
+   :maxdepth: 2
+   :caption: API Documentation
+
+   selfisys.hiddenbox
+   selfisys.normalise_hb
+   selfisys.prior
+   selfisys.selection_functions
+   selfisys.selfi_interface
+   selfisys.sbmy_interface
+   selfisys.grf
+   selfisys.utils
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contribute
+
+   ../../CONTRIBUTING.md
+
+.. toctree::
+   :maxdepth: 2
+   :caption: References
+
+   ../../REFERENCES.md
--- a/docs/_sources/selfisys.global_parameters.rst.txt
+++ b/docs/_sources/selfisys.global_parameters.rst.txt
@ -0,0 +1,7 @@
+global_parameters
+=================
+
+.. automodule:: selfisys.global_parameters
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.grf.rst.txt
+++ b/docs/_sources/selfisys.grf.rst.txt
@ -0,0 +1,7 @@
+grf
+===
+
+.. automodule:: selfisys.grf
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.hiddenbox.rst.txt
+++ b/docs/_sources/selfisys.hiddenbox.rst.txt
@ -0,0 +1,7 @@
+hiddenbox
+=========
+
+.. automodule:: selfisys.hiddenbox
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.normalise_hb.rst.txt
+++ b/docs/_sources/selfisys.normalise_hb.rst.txt
@ -0,0 +1,7 @@
+normalise_hb
+============
+
+.. automodule:: selfisys.normalise_hb
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.prior.rst.txt
+++ b/docs/_sources/selfisys.prior.rst.txt
@ -0,0 +1,7 @@
+prior
+=====
+
+.. automodule:: selfisys.prior
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.rst.txt
+++ b/docs/_sources/selfisys.rst.txt
@ -0,0 +1,93 @@
+selfisys package
+================
+
+Subpackages
+-----------
+
+.. toctree::
+   :maxdepth: 4
+
+   selfisys.utils
+
+Submodules
+----------
+
+selfisys.global\_parameters module
+----------------------------------
+
+.. automodule:: selfisys.global_parameters
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.grf module
+-------------------
+
+.. automodule:: selfisys.grf
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.hiddenbox module
+-------------------------
+
+.. automodule:: selfisys.hiddenbox
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.normalise\_hb module
+-----------------------------
+
+.. automodule:: selfisys.normalise_hb
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.prior module
+---------------------
+
+.. automodule:: selfisys.prior
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.sbmy\_interface module
+-------------------------------
+
+.. automodule:: selfisys.sbmy_interface
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.selection\_functions module
+------------------------------------
+
+.. automodule:: selfisys.selection_functions
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.selfi\_interface module
+--------------------------------
+
+.. automodule:: selfisys.selfi_interface
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.setup\_model module
+----------------------------
+
+.. automodule:: selfisys.setup_model
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Module contents
+---------------
+
+.. automodule:: selfisys
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.sbmy_interface.rst.txt
+++ b/docs/_sources/selfisys.sbmy_interface.rst.txt
@ -0,0 +1,7 @@
+sbmy_interface
+==============
+
+.. automodule:: selfisys.sbmy_interface
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.selection_functions.rst.txt
+++ b/docs/_sources/selfisys.selection_functions.rst.txt
@ -0,0 +1,7 @@
+selection_functions
+===================
+
+.. automodule:: selfisys.selection_functions
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.selfi_interface.rst.txt
+++ b/docs/_sources/selfisys.selfi_interface.rst.txt
@ -0,0 +1,7 @@
+selfi_interface
+===============
+
+.. automodule:: selfisys.selfi_interface
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.setup_model.rst.txt
+++ b/docs/_sources/selfisys.setup_model.rst.txt
@ -0,0 +1,7 @@
+setup_model
+===========
+
+.. automodule:: selfisys.setup_model
+   :members:
+   :undoc-members:
+   :show-inheritance:
--- a/docs/_sources/selfisys.utils.rst.txt
+++ b/docs/_sources/selfisys.utils.rst.txt
@ -0,0 +1,101 @@
+selfisys.utils package
+======================
+
+Submodules
+----------
+
+selfisys.utils.examples\_utils module
+-------------------------------------
+
+.. automodule:: selfisys.utils.examples_utils
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.logger module
+----------------------------
+
+.. automodule:: selfisys.utils.logger
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.low\_level module
+--------------------------------
+
+.. automodule:: selfisys.utils.low_level
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.parser module
+----------------------------
+
+.. automodule:: selfisys.utils.parser
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.path\_utils module
+---------------------------------
+
+.. automodule:: selfisys.utils.path_utils
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.plot\_examples module
+------------------------------------
+
+.. automodule:: selfisys.utils.plot_examples
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.plot\_params module
+----------------------------------
+
+.. automodule:: selfisys.utils.plot_params
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.plot\_utils module
+---------------------------------
+
+.. automodule:: selfisys.utils.plot_utils
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.timestepping module
+----------------------------------
+
+.. automodule:: selfisys.utils.timestepping
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.tools module
+---------------------------
+
+.. automodule:: selfisys.utils.tools
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+selfisys.utils.workers module
+-----------------------------
+
+.. automodule:: selfisys.utils.workers
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Module contents
+---------------
+
+.. automodule:: selfisys.utils
+   :members:
+   :undoc-members:
+   :show-inheritance: