View gaga-phsp on Snyk Open Source Advisor

Package Health Score

72 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Sustainable

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Popularity

Limited

GitHub Stars: 66
Forks: 48
Contributors: 30

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package gaga-phsp, we found that it has been starred 66 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 18, 2024
Direct Vulnerabilities: 0
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0
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Indirect Vulnerabilities: 0
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0
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0
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License Risk: 0
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0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

LGPL-3.0

Non-Permissive License

We noticed that this project uses a license which requires less permissive conditions such as disclosing the source code, stating changes or redistributing the source under the same license. It is advised to further consult the license terms before use.

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 53
Open PR: 25
Last Release: 1 month ago
Last Commit: 15 hours ago

Further analysis of the maintenance status of gaga-phsp based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that gaga-phsp demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 30
Funding: No

With more than 10 contributors for the gaga-phsp repository, this is possibly a sign for a growing and inviting community.

We found a way for you to contribute to the project! Looks like gaga-phsp is missing a Code of Conduct.

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Package

Python Versions Compatibility: >=3.8

Age: 5 years
Latest Release: 1 month ago
Dependencies: 7 Direct
Versions: 16
Maintainers: 0
Wheels: OS Independent

Readme

GAGA = GAN for GATE

pip install gaga-phsp

Scripts associated with the publication : Phys Med Biol. 2019 doi: https://doi.org/10.1088/1361-6560/ab3fc1 Generative adversarial networks (GAN) for compact beam source modelling in Monte Carlo simulations Sarrut D, Krah N, Letang JM. https://www.ncbi.nlm.nih.gov/pubmed/31470418

A method is proposed and evaluated to model large and inconvenient phase space files used in Monte Carlo simulations by a compact Generative Adversarial Network (GAN). The GAN is trained based on a phase space dataset to create a neural network, called Generator (G), allowing G to mimic the multidimensional data distribution of the phase space. At the end of the training process, G is stored with about 0.5 million weights, around 10MB, instead of few GB of the initial file. Particles are then generated with G to replace the phase space dataset.  This concept is applied to beam models from linear accelerators (linacs) and from brachytherapy seed models. Simulations using particles from the reference phase space on one hand and those generated by the GAN on the other hand were compared. 3D distributions of deposited energy obtained from source distributions generated by the GAN were close to the reference ones, with less than 1% of voxel-by-voxel relative difference. Sharp parts such as the brachytherapy emission lines in the energy spectra were not perfectly modeled by the GAN. Detailed statistical properties and limitations of the GAN-generated particles still require further investigation, but the proposed exploratory approach is already promising and paves the way for a wide range of applications

Tests in opengate (https://github.com/OpenGATE/opengate): see test066.

gaga-phsp dependencies

click colorama gatetools matplotlib pathlib scipy tqdm

FAQs

What is gaga-phsp?

Python tools for GATE GAN simulations. Visit Snyk Advisor to see a full health score report for gaga-phsp, including popularity, security, maintenance & community analysis.

Is gaga-phsp popular?

The python package gaga-phsp receives a total of 643 weekly downloads. As such, gaga-phsp popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is gaga-phsp well maintained?

We found that gaga-phsp demonstrated a healthy version release cadence and project activity. It has a community of 30 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is gaga-phsp safe to use?

The python package gaga-phsp was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 18 December-2024, at 22:42 (UTC).

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gaga-phsp

Python tools for GATE GAN simulations For more information about how to use this package see README

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Readme

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Readme

gaga-phsp dependencies

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