Package Health Score

78 / 100

security
No known security issues
popularity
Small
maintenance
Healthy
community
Sustainable

Popularity

Small

GitHub Stars: 10
Forks: 2
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package qp-prob, we found that it has been starred 10 times.

Security

No known security issues

Security and license risk for latest version

Release Date: May 29, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 28
Open PR: 2
Last Release: 18 days ago
Last Commit: 1 month ago

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

We found that qp-prob 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: Yes
Code of Conduct: No
Contributors: 20
Funding: No

With more than 10 contributors for the qp-prob 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 qp-prob is missing a Code of Conduct.

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Package

Python Versions Compatibility: >=3.9

Age: 2 years
Latest Release: 18 days ago
Dependencies: 5 Direct
Versions: 14
Maintainers: 3
Wheels: OS Independent

Readme

qp

Quantile parametrization for probability distribution functions.

GitHub release (latest SemVer) GitHub Workflow Status Read the Docs

Motivation

In a scientific inference we typically seek to characterize the posterior probability density function (PDF) for our parameter(s), which means we need to find a suitable, calculable approximation to it. Popular choices include an ensemble of samples, a histogram estimator based on those samples, or (in 1 dimensional problems) a tabulation of the PDF on a regular parameter grid. qp is a python package that supports these approximations, as well as the “quantile parameterization” from which the package gets its name.

The scipy.stats package provides an interface to many probability distributions for parameterized analytic forms (e.g., Gaussians, LogNormal Distributions, etc...) qp extends that functionality to numerically-evaluated forms, such as the histograms and interpolated grids mentioned above.

Examples

Here are some example notebooks to help new users explore qp functionality.

Basic Demo (raw notebook)
Practical Example (raw notebook)
Using Metrics (raw notebook)
Using iterarors (raw notebook)
Quantile parameterization (raw notebook)

Also the read the docs page has significantly more information: Read the Docs

People

Alex Malz (NYU)
Phil Marshall (SLAC)
Eric Charles (SLAC)
Sam Schmidt (UC Davis)

License, Contributing etc

The code in this repo is available for re-use under the MIT license, which means that you can do whatever you like with it, just don't blame us. If you end up using any of the code or ideas you find here in your academic research, please cite us as Malz et al, ApJ 156 1 35. If you are interested in this project, please do drop us a line via the hyperlinked contact names above, or by writing us an issue. To get started contributing to the qp project, just fork the repo - pull requests are always welcome!

qp-prob dependencies

deprecated numpy pytdigest scipy tables-io

FAQs

What is qp-prob?

. Visit Snyk Advisor to see a full health score report for qp-prob, including popularity, security, maintenance & community analysis.

Is qp-prob popular?

The python package qp-prob receives a total of 3,166 weekly downloads. As such, qp-prob popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is qp-prob well maintained?

We found that qp-prob demonstrated a healthy version release cadence and project activity. It has a community of 20 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is qp-prob safe to use?

The python package qp-prob 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 13 June-2024, at 12:32 (UTC).

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qp-prob

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Package Health Score

Popularity

Direct Usage Popularity

Security

Security and license risk for latest version

Maintenance

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Community

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Package

Readme

qp

Motivation

Examples

People

License, Contributing etc

qp-prob dependencies

FAQs

What is qp-prob?

Is qp-prob popular?

Is qp-prob well maintained?

Is qp-prob safe to use?

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Package Health Score

Direct Usage Popularity

Security and license risk for latest version

Commit Frequency

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Readme

qp

Motivation

Examples

People

License, Contributing etc

qp-prob dependencies

FAQs

What is qp-prob?

Is qp-prob popular?

Is qp-prob well maintained?

Is qp-prob safe to use?

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Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

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