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PxMCMC

PxMCMC: A Python package for proximal Markov Chain Monte Carlo - Published in JOSS (2023)

https://github.com/auggiemarignier/pxmcmc

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
    4 of 4 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

bayesian-inference inverse-problems mcmc proximal-algorithms python

Scientific Fields

Mathematics Computer Science - 84% confidence
Earth and Environmental Sciences Physical Sciences - 83% confidence
Last synced: 4 months ago · JSON representation

Repository

Solving inverse problems with Proximal Markov Chain Monte Carlo

Basic Info
Statistics
  • Stars: 8
  • Watchers: 2
  • Forks: 2
  • Open Issues: 1
  • Releases: 2
Topics
bayesian-inference inverse-problems mcmc proximal-algorithms python
Created almost 5 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.md

PyPI version Documentation Status test status DOI

Python ProxMCMC

Installation

Available on pypi

bash pip install pxmcmc

If installing from source it recommended to use poetry

bash git clone https://github.com/auggiemarignier/pxmcmc cd pxmcmc poetry install source <ENVIRONMENT_LOCATION>/bin/activate pytest

Documentation

Full documentation available on readthedocs.

Examples

Examples of how to use this code with sample data are found in the experiments directory. Please start with the earthtopography example, which will quickly run something to get you going!

bash cd experiments/earthtopography python main.py --infile ETOPO1_Ice_hpx_256.fits python plot.py myula_synthesis_<timestamp>.hdf5 .

The phasevel and weaklensing examples replicate the work shown in this paper.

Contributing

Contributions to the package are encouraged! If you wish to contribute, are experiencing problems with the code or need further support, please open an issue to start a discussion. Changes will be integrated via pull requests.

CITATION

If you use this package in your work please cite the following papers

Marignier (2023) PxMCMC: A Python package for proximal Markov Chain Monte Carlo, Journal of Open Source Software, 0(0), 5582. https://doi.org/10.21105/joss.05582

Marignier et al., Posterior sampling for inverse imaging problems on the sphere in seismology and cosmology, RAS Techniques and Instruments, Volume 2, Issue 1, January 2023, Pages 20–32, https://doi.org/10.1093/rasti/rzac010

Owner

  • Login: auggiemarignier
  • Kind: user

JOSS Publication

PxMCMC: A Python package for proximal Markov Chain Monte Carlo
Published
July 26, 2023
DOI
Volume 8, Issue 87, Page 5582
Authors
Augustin Marignier ORCID
Research School of Earth Sciences, Australian National University, Australia
Editor
Marcel Stimberg ORCID
Tags
MCMC imaging geophysics astrophysics
View PDF Review Thread Software Archive

GitHub Events

Total
  • Watch event: 3
Last Year
  • Watch event: 3

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 468
  • Total Committers: 4
  • Avg Commits per committer: 117.0
  • Development Distribution Score (DDS): 0.126
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Auggie Marignier a****4@u****k 409
auggiemarignier a****r@a****u 37
zcfbllm z****m@l****k 13
zcfbllm z****m@l****k 9
Committer Domains (Top 20 + Academic)
login13.myriad.ucl.ac.uk: 1 login12.myriad.ucl.ac.uk: 1 anu.edu.au: 1 ucl.ac.uk: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 6
  • Total pull requests: 13
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 9 days
  • Total issue authors: 4
  • Total pull request authors: 1
  • Average comments per issue: 1.33
  • Average comments per pull request: 1.31
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • jeremiecoullon (2)
  • auggiemarignier (2)
  • mattpitkin (1)
  • WillSturgeon (1)
Pull Request Authors
  • auggiemarignier (13)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 15 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 8
  • Total maintainers: 1
pypi.org: pxmcmc

Proximal Markov Chain Monte Carlo

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 15 Last month
Rankings
Dependent packages count: 10.1%
Average: 21.1%
Dependent repos count: 21.6%
Forks count: 22.7%
Stargazers count: 25.1%
Downloads: 26.0%
Maintainers (1)
auggiem23
Last synced: 4 months ago

Dependencies

poetry.lock pypi
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  • python-dateutil 2.8.2
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pyproject.toml pypi
  • black ^19.10b0 develop
  • flake8 ^3.7.9 develop
  • pytest ^5.2 develop
  • pytest-cases ^2.0.4 develop
  • Cartopy ^0.19.0
  • astropy ^5.0.4
  • greatcirclepaths ^1.1.0
  • h5py ^3.3.0
  • matplotlib ^3.4.2
  • numpy ^1.21.1
  • pys2let ^2.2.3
  • pyssht ^1.4.0
  • python >=3.8, <3.10
  • scipy ~1.7.0
  • sphinx ^4
  • sphinx-rtd-theme 0.5^
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