X-PSI

X-PSI: A Python package for neutron star X-ray pulse simulation and inference - Published in JOSS (2023)

https://github.com/xpsi-group/xpsi

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 7 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
    5 of 19 committers (26.3%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

astronomical-algorithms astronomy astrophysical-simulation astrophysics likelihood-functions modeling parameter-estimation posterior-sampling sampling statistics-modeling x-ray-astronomy

Keywords from Contributors

gravitational-lenses

Scientific Fields

Mathematics Computer Science - 32% confidence
Last synced: 4 months ago · JSON representation

Repository

X-PSI: X-ray Pulse Simulation and Inference

Basic Info
  • Host: GitHub
  • Owner: xpsi-group
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 514 MB
Statistics
  • Stars: 41
  • Watchers: 2
  • Forks: 21
  • Open Issues: 29
  • Releases: 7
Topics
astronomical-algorithms astronomy astrophysical-simulation astrophysics likelihood-functions modeling parameter-estimation posterior-sampling sampling statistics-modeling x-ray-astronomy
Created over 6 years ago · Last pushed 4 months ago
Metadata Files
Readme Changelog License

README.rst

.. _readme:


X-PSI
=====

**An open-source package for neutron star**
**\ X-ray Pulse Simulation and Inference.**

|Python version| |Build Status Main| |Docs| |GitHub Release| |Repo status|

|joss| |doi|

X-PSI is designed to simulate rotationally-modified (pulsed) surface 
X-ray emission from neutron stars, taking into account relativistic 
effects on the emitted radiation. This can then be used to perform 
Bayesian statistical inference on real or simulated astronomical data 
sets. Model parameters of interest may include neutron star mass and 
radius (useful to constrain the properties of ultradense nuclear matter) 
or the system geometry and properties of the hot emitting surface-regions. 
To achieve this, X-PSI couples code for likelihood functionality (simulation) 
with existing open-source software for posterior sampling (inference).

It provides the following functionality:

* Simulation of time- and energy resolved X-ray emission (pulse profiles) from the surfaces of neutron stars.
* The facility to implement multiple models for surface patterns, atmospheres, and different instruments.
* Coupling of pulse simulation functionality to statistical sampling software to infer spacetime and geometric parameters from pulse profile data.
* An extensive suite of post-processing software to visualize posteriors and measures of model quality.



For more details on current and planned capabilities, check out the 
`X-PSI documentation `_.

Installation and Testing
------------------------

X-PSI has a complex set of dependencies, and is therefore currently best 
installed from source. The documentation provides
`step-by-step installation instructions `_
for Linux and for limited MacOS systems.

Documentation
-------------

The documentation for X-PSI, including a wide range of tutorials and scripts for 
running X-PSI on HPC systems, can be found at `https://xpsi-group.github.io/xpsi/ `_.

How to get in touch or get involved
-----------------------------------

We always welcome contributions and feedback! We are especially interested in 
hearing from you if

* something breaks,
* you spot bugs, 
* if there is missing functionality, or,
* you have suggestions for future development.

To get in touch, please `open an issue `_.
Even better, if you have code you'd be interested in contributing, please send a 
`pull request `_ (or get in touch 
and we'll help guide you through the process!). 

For more information, you can take a look at the documentation's 
`Contributing page `_. Please also 
make sure you take a look at the `Code of Conduct `_. 


Citing X-PSI
-----------
If you find this package useful in your research, please provide the appropriate acknowledgment 
and citation. `Our documentation `_ provides 
more detail, including links to appropriate papers and BibTeX entries.

Copyright and Licensing
-----------------------
All content © 2016-2025 the authors. 
The code is distributed under the GNU General Public License v3.0; see `LICENSE `_ for details.

Legacy
------ 
An earlier version (pre-v0.5) of this project was named:
A prototype open-source package for neutron star X-ray Pulsation Simulation
and Inference.

.. |Python version| image:: https://img.shields.io/badge/Python-%3E=3.9-blue.svg
   :target: https://www.python.org/downloads/release/python-390/
.. |Build Status Main| image:: https://github.com/xpsi-group/xpsi/workflows/CI%20Tests/badge.svg
   :target: https://github.com/xpsi-group/xpsi/actions/
.. |Docs| image:: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat
   :target: https://xpsi-group.github.io/xpsi/index.html
.. |GitHub release| image:: https://img.shields.io/github/v/release/xpsi-group/xpsi
   :target: https://github.com/xpsi-group/xpsi/releases/latest
.. |Repo status| image:: https://www.repostatus.org/badges/latest/active.svg
   :alt: Project Status: Active – The project has reached a stable, usable state and is being actively developed.
   :target: https://www.repostatus.org/#active
.. |joss| image:: https://joss.theoj.org/papers/10.21105/joss.04977/status.svg
   :target: https://doi.org/10.21105/joss.04977
.. |doi| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.7632628.svg
   :target: https://doi.org/10.5281/zenodo.7632628

Owner

  • Name: xpsi-group
  • Login: xpsi-group
  • Kind: organization

X-PSI: X-ray Pulse Simulation and Inference

JOSS Publication

X-PSI: A Python package for neutron star X-ray pulse simulation and inference
Published
February 14, 2023
Volume 8, Issue 82, Page 4977
Authors
Thomas E. Riley ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Devarshi Choudhury ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Tuomo Salmi ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Serena Vinciguerra ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Yves Kini ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Bas Dorsman ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Anna L. Watts ORCID
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1090GE Amsterdam, The Netherlands
Daniela Huppenkothen ORCID
SRON Netherlands Institute for Space Research, Niels Bohrweg 4, NL-2333 CA Leiden, the Netherlands
Sebastien Guillot ORCID
Institut de Recherche en Astrophysique et Planétologie, UPS-OMP, CNRS, CNES, 9 avenue du Colonel Roche, BP 44346, F-31028 Toulouse Cedex 4, France
Editor
Axel Donath ORCID
Tags
astrostatistics neutron stars

GitHub Events

Total
  • Fork event: 3
  • Create event: 110
  • Commit comment event: 6
  • Release event: 2
  • Issues event: 201
  • Watch event: 5
  • Delete event: 94
  • Member event: 3
  • Issue comment event: 272
  • Push event: 482
  • Pull request review event: 153
  • Pull request review comment event: 27
  • Pull request event: 198
Last Year
  • Fork event: 3
  • Create event: 110
  • Commit comment event: 6
  • Release event: 2
  • Issues event: 201
  • Watch event: 5
  • Delete event: 94
  • Member event: 3
  • Issue comment event: 272
  • Push event: 482
  • Pull request review event: 153
  • Pull request review comment event: 27
  • Pull request event: 198

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 884
  • Total Committers: 19
  • Avg Commits per committer: 46.526
  • Development Distribution Score (DDS): 0.568
Past Year
  • Commits: 158
  • Committers: 12
  • Avg Commits per committer: 13.167
  • Development Distribution Score (DDS): 0.772
Top Committers
Name Email Commits
Thomas E. Riley T****y@u****l 382
Tuomo Salmi t****1@g****m 138
Daniela Huppenkothen d****n@s****l 65
Devarshi Choudhury d****8@g****m 57
Sebastien Guillot s****0@g****m 56
Anna Watts A****s@u****l 48
lmauviard l****n@m****r 36
Bas Dorsman s****6@g****m 33
Serena Vinciguerra s****a@u****l 15
Mariska Hoogkamer m****8@h****m 14
yveskini k****s@g****m 11
ckazantsev c****v@i****u 10
denis-gc d****l@g****m 5
pstammler p****r@i****u 5
serenavinciguerra89 s****9@g****m 5
AlexKurek a****k@u****l 1
Yves Kini y****i@u****l 1
Tuomo Salmi t****3@i****l 1
Dan F-M f****y@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 211
  • Total pull requests: 260
  • Average time to close issues: 6 months
  • Average time to close pull requests: 17 days
  • Total issue authors: 18
  • Total pull request authors: 15
  • Average comments per issue: 1.17
  • Average comments per pull request: 1.43
  • Merged pull requests: 225
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 102
  • Pull requests: 186
  • Average time to close issues: 11 days
  • Average time to close pull requests: 6 days
  • Issue authors: 14
  • Pull request authors: 11
  • Average comments per issue: 0.61
  • Average comments per pull request: 1.44
  • Merged pull requests: 160
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • sguillot (48)
  • thjsal (39)
  • DevarshiChoudhury (31)
  • drannawatts (21)
  • lmauviard (13)
  • Basdorsman (13)
  • MHoogkamer (8)
  • denis-gc (7)
  • ckazantsev (6)
  • yveskini (5)
  • serenavinciguerra89 (5)
  • dhuppenkothen (4)
  • evertrol (3)
  • ychatonnier (3)
  • pstammler (2)
Pull Request Authors
  • thjsal (75)
  • drannawatts (35)
  • sguillot (31)
  • DevarshiChoudhury (28)
  • lmauviard (18)
  • Basdorsman (16)
  • ckazantsev (16)
  • MHoogkamer (12)
  • denis-gc (9)
  • pstammler (8)
  • yveskini (4)
  • serenavinciguerra89 (3)
  • dhuppenkothen (3)
  • dfm (1)
  • AlexKurek (1)
Top Labels
Issue Labels
documentation (62) enhancement (57) bug (40) hackweek2024 (40) Clean up crew 2025 (19) postprocessing (13) python3 (11) hackweek2023 (9) bugfix (9) question (5) good first issue (5) hackweek_spring2025 (4) installation (3) tests (3) hackweek2022 (1) testing / refactoring 2025 (1) need for speed 2025 (1)
Pull Request Labels
bugfix (27) enhancement (21) documentation (21) Clean up crew 2025 (14) no-changelog-needed (8) python3 (5) hackweek2023 (5) postprocessing (4) hackweek2024 (4) ready-for-changelog (1)

Dependencies

.github/workflows/build_docs.yml actions
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  • crazy-max/ghaction-github-pages v3 composite
  • mamba-org/provision-with-micromamba main composite
.github/workflows/ci_tests.yml actions
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  • mamba-org/provision-with-micromamba main composite
.github/workflows/joss.yml actions
  • actions/checkout v2 composite
  • actions/upload-artifact v1 composite
  • openjournals/openjournals-draft-action master composite
environment.yml conda
  • cython ~=0.29
  • fgivenx
  • getdist
  • h5py
  • matplotlib
  • mpi4py
  • nestcheck
  • numpy
  • pymultinest
  • pytest
  • scipy
  • wrapt
setup.py pypi
  • numpy *