adrt

adrt: approximate discrete Radon transform for Python - Published in JOSS (2023)

https://github.com/karlotness/adrt

Science Score: 100.0%

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

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 13 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org
  • Committers with academic emails
    5 of 6 committers (83.3%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords from Contributors

turing-machine standardization pde mesh parallel interpretability evolutionary-algorithms ode pypi simulations

Scientific Fields

Mathematics Computer Science - 84% confidence
Last synced: 4 months ago · JSON representation ·

Repository

Fast approximate discrete Radon transform for NumPy arrays

Basic Info
  • Host: GitHub
  • Owner: karlotness
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: master
  • Homepage: https://adrt.readthedocs.io
  • Size: 1.05 MB
Statistics
  • Stars: 8
  • Watchers: 3
  • Forks: 1
  • Open Issues: 0
  • Releases: 4
Created over 5 years ago · Last pushed 5 months ago
Metadata Files
Readme License Citation

README.md

Approximate Discrete Radon Transform

adrt on PyPI adrt on conda-forge Documentation Tests JOSS Paper

Fast approximate discrete Radon transform for NumPy arrays.

  • Documentation: https://adrt.readthedocs.io/en/latest/
  • Source Code: https://github.com/karlotness/adrt
  • Bug Reports: https://github.com/karlotness/adrt/issues

This library provides an implementation of an approximate discrete Radon transform (ADRT) and related routines as a Python module operating on NumPy arrays. Implemented routines include: the forward ADRT, a back-projection operation, and several inverse transforms. The package documentation contains usage examples, and sample applications.

Installation

Install from PyPI using pip: console $ python -m pip install adrt or from conda-forge: console $ conda install -c conda-forge adrt

For further details on installation or building from source, consult the documentation.

Citation

If you use this software in your research, please cite our associated JOSS paper.

BibTeX @article{adrt, title={adrt: approximate discrete {R}adon transform for {P}ython}, author={Karl Otness and Donsub Rim}, journal={Journal of Open Source Software}, publisher={The Open Journal}, year=2023, doi={10.21105/joss.05083}, url={https://doi.org/10.21105/joss.05083}, volume=8, number=83, pages=5083, }

References

This implementation is based on descriptions in several publications: - Martin L. Brady, A Fast Discrete Approximation Algorithm for the Radon Transform Related Databases, SIAM Journal on Computing, 27. - William H. Press, Discrete Radon transform has an exact, fast inverse and generalizes to operations other than sums along lines, Proceedings of the National Academy of Sciences, 103. - Donsub Rim, Exact and fast inversion of the approximate discrete Radon transform from partial data, Applied Mathematics Letters, 102.

License

This software is distributed under the 3-clause BSD license. See LICENSE.txt for the license text.

We also make available several pre-built binary copies of this software. The binary build for Windows includes additional license terms for runtime code included as part of the software. Review the LICENSE.txt file in the binary build package for more information.

Owner

  • Name: Karl Otness
  • Login: karlotness
  • Kind: user
  • Location: New York, NY
  • Company: NYU

PhD student at NYU, researching applications of ML to simulations and climate with researchers at @m2lines

JOSS Publication

adrt: approximate discrete Radon transform for Python
Published
March 16, 2023
Volume 8, Issue 83, Page 5083
Authors
Karl Otness ORCID
New York University, New York, NY, USA
Donsub Rim ORCID
Washington University in St. Louis, St. Louis, MO, USA
Editor
Patrick Diehl ORCID
Tags
numerical algorithms fast transforms image processing Radon transform approximate discrete Radon transform

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software in your work, please cite our JOSS paper."
authors:
- family-names: "Otness"
  given-names: "Karl"
  orcid: "https://orcid.org/0000-0001-8534-2648"
- family-names: "Rim"
  given-names: "Donsub"
  orcid: "https://orcid.org/0000-0002-6721-2070"
title: "adrt: approximate discrete Radon transform for Python"
doi: "10.5281/zenodo.7738253"
url: "https://github.com/karlotness/adrt"
preferred-citation:
  type: article
  authors:
  - family-names: "Otness"
    given-names: "Karl"
    orcid: "https://orcid.org/0000-0001-8534-2648"
  - family-names: "Rim"
    given-names: "Donsub"
    orcid: "https://orcid.org/0000-0002-6721-2070"
  title: "adrt: approximate discrete Radon transform for Python"
  doi: "10.21105/joss.05083"
  url: "https://doi.org/10.21105/joss.05083"
  publisher:
    name: "The Open Journal"
  journal: "Journal of Open Source Software"
  volume: 8
  number: 83
  pages: 5083
  year: 2023

GitHub Events

Total
  • Release event: 1
  • Watch event: 2
  • Delete event: 4
  • Push event: 9
  • Pull request event: 3
  • Create event: 5
Last Year
  • Release event: 1
  • Watch event: 2
  • Delete event: 4
  • Push event: 9
  • Pull request event: 3
  • Create event: 5

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 1,356
  • Total Committers: 6
  • Avg Commits per committer: 226.0
  • Development Distribution Score (DDS): 0.088
Past Year
  • Commits: 68
  • Committers: 2
  • Avg Commits per committer: 34.0
  • Development Distribution Score (DDS): 0.015
Top Committers
Name Email Commits
Karl Otness k****s@n****u 1,237
dsrim r****m@w****u 112
dependabot[bot] 4****] 3
Daniel S. Katz d****z@i****g 2
dsrim d****5@c****u 1
Don Rim d****3@n****u 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 4
  • Total pull requests: 5
  • Average time to close issues: 7 days
  • Average time to close pull requests: about 16 hours
  • Total issue authors: 2
  • Total pull request authors: 2
  • Average comments per issue: 3.0
  • Average comments per pull request: 0.4
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 4
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: about 16 hours
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 1
Top Authors
Issue Authors
  • zhangjy-ge (2)
  • fruzsinaagocs (2)
Pull Request Authors
  • dependabot[bot] (6)
  • danielskatz (1)
Top Labels
Issue Labels
Pull Request Labels
dependencies (6) github_actions (6)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 372 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 5
  • Total maintainers: 2
pypi.org: adrt

Fast approximate discrete Radon transform for NumPy arrays

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 372 Last month
Rankings
Dependent packages count: 10.1%
Average: 21.2%
Dependent repos count: 21.5%
Downloads: 21.7%
Stargazers count: 23.1%
Forks count: 29.8%
Maintainers (2)
Last synced: 4 months ago

Dependencies

.github/workflows/release.yml actions
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  • actions/setup-python v4 composite
  • actions/upload-artifact v3 composite
.github/workflows/test.yml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
docs/requirements.txt pypi
  • matplotlib >=3.6.1,<4
  • numpy *
  • packaging *
  • scikit-image *
  • scipy *
  • sphinx >=5.3.0,<6
  • sphinx-rtd-theme >=1.1.1,<2
tools/download_catch2_requirements.txt pypi
  • requests *
pyproject.toml pypi
  • numpy >=1.22,<2
setup.py pypi
tests/requirements.txt pypi
  • more-itertools * test
  • pytest >=6 test
  • scipy * test