HOGBEN

v3.1.1

Holistic Optimization for Generating Better Experimental Neutrons - a package for optimzing neutron experiments using the Fisher information For more information about how to use this package see README

Latest version published 10 days ago

License: BSD-3-Clause

PyPI

GitHub

Package Health Score

66 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Limited

Popularity

Limited

GitHub Stars: 6
Forks: 3
Contributors: 6

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package HOGBEN, we found that it has been starred 6 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 15, 2024
Direct Vulnerabilities: 0
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0
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0
M
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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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

BSD-3-Clause

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 36
Open PR: 2
Last Release: 10 days ago
Last Commit: 10 days ago

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

We found that HOGBEN 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

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 6
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.10

Age: 3 years
Latest Release: 10 days ago
Dependencies: 13 Direct
Versions: 12
Maintainers: 1
Wheels: OS Independent

Readme

HOGBEN

Holistic Optimization for Gaining Better Evidence from Neutrons

About the Project

For the original repositories that this work is based on, see fisher-information and experimental-design.

Using the Fisher information (FI), the design of neutron reflectometry experiments can be optimised, leading to greater confidence in parameters of interest and better use of experimental time. This package contains modules and data for optimising the design of a wide range of reflectometry experiments.

Please refer to the notebooks for an introduction on how to use the code.

This repository is named after Lancelot Hogben, whose relentless opposition of eugenics (and vocal criticism of Ronald Fisher's views on it) we applaud.

Citation

Please cite the following article if you intend on including elements of this work in your own publications:

Durant, J. H., Wilkins, L. and Cooper, J. F. K. Optimising experimental design in neutron reflectometry. arXiv:2108.05605 (2021).

Or with BibTeX as:

@misc{Durant2021,
   title         = {Optimising experimental design in neutron reflectometry}, 
   author        = {Durant, J. H. and Wilkins, L. and Cooper, J. F. K.},
   year          = {2021},
   eprint        = {2108.05605},
   archivePrefix = {arXiv},
   primaryClass  = {physics.data-an}
}

Contact

Jos Cooper - jos.cooper@ess.eu
Sjoerd Stendahl - sjoerd.stendahl@physics.uu.se
James Durant - james.durant@warwick.ac.uk
Lucas Wilkins - lucas.wilkins@stfc.ac.uk

Acknowledgements

We thank Luke Clifton for his assistance and expertise in fitting the lipid monolayer and lipid bilayer data sets.

License

Distributed under the BSD 3-Clause License. See license for more information.

HOGBEN dependencies

bumps corner dynesty emcee importlib-resources matplotlib numpy periodictable pillow refl1d refnx scipy tqdm

FAQs

What is HOGBEN?

Holistic Optimization for Generating Better Experimental Neutrons - a package for optimzing neutron experiments using t... Visit Snyk Advisor to see a full health score report for HOGBEN, including popularity, security, maintenance & community analysis.

Is HOGBEN popular?

The python package HOGBEN receives a total of 331 weekly downloads. As such, HOGBEN popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is HOGBEN well maintained?

We found that HOGBEN demonstrated a healthy version release cadence and project activity. It has a community of 6 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is HOGBEN safe to use?

The python package HOGBEN 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 25 November-2024, at 18:02 (UTC).

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Readme

HOGBEN

About the Project

Citation

Contact

Acknowledgements

License

HOGBEN dependencies

FAQs

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Is HOGBEN popular?

Is HOGBEN well maintained?

Is HOGBEN safe to use?

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Source Code

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