Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/bio-phys/hplusminus

Statistical tests to detect and quantify correlations in residuals when fitting models to one-dimensional data.

https://github.com/bio-phys/hplusminus

Science Score: 23.0%

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

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 3 committers (66.7%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (16.2%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

Statistical tests to detect and quantify correlations in residuals when fitting models to one-dimensional data.

Basic Info
  • Host: GitHub
  • Owner: bio-phys
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.75 MB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created over 5 years ago · Last pushed over 5 years ago
Metadata Files
Readme License

README.md

hplusminus

PyPI Build Status

Copyright (C) 2020 Juergen Koefinger, Max Planck Institute of Biophysics, Frankfurt am Main, Germany

With contributions from Klaus Reuter, Max Planck Computing and Data Facility, Garching, Germany.

Released under the MIT Licence, see the file LICENSE.txt.

Reference

Powerful statistical tests for ordered data \ Juergen Koefinger and Gerhard Hummer \ Preprint: https://doi.org/10.26434/chemrxiv.13373351 (2020)

Requirements

  • Python 3
  • Jupyter (for Jupyter notebooks only)
  • Python modules (can be installed with pip or conda):
    • numpy
    • scipy
    • mpmath
    • matplotlib (for Jupyter notebooks only)

Installation

The hplusminus package can be installed in the following ways:

pip installation

To install via pip please run:

bash pip install --user hplusminus

Installation from source

After downloading and unpacking the source tarball please run:

bash python setup.py install --user

Python script

hplusminus_tests.py

Python 3 script to evaluate test statistics for normalized residuals. This script contains the central functionality.

See help for more information and usage:

bash python hplusminus_tests.py -h `

Example for alternative model

bash python hplusminus_tests.py ./examples/alternative_model_normalized_residuals.txt

Example for true model

bash python hplusminus_tests.py ./examples/true_model_normalized_residuals.txt

Jupyter notebooks

Notebooks in the directory ./ipynb/ serve to explore the capabilties of our statistical tests. See notebooks themselves for more details on purpose and usage.

hplusminus_tests.ipynb

Evaluate statistical tests.

Addtionally to the functionality of hplusminus_tests.py, the notebook provides plots of normalized residuals and signs and a bar-plot to visually compare the p-values of the various tests.

hplusminusstatisticalpower.ipynb

Calculate statistical power for all tests and given model

generatemodelsfor_residuals.ipynb

Generate models for residuals, which can be used with the Python script hplusminus_tests.py and the Jupyter notebooks hplusminus_tests.ipyn and hplusminusstatisticalpower.ipynb.

Python package hplusminus

tests.py

Python 3 module file containing functions for the convenient evaluation of the statistical tests.

io.py

Python 3 module file for input and output.

rld.py

Python 3 module file for the calculation of the Shannon information (neg. log-probabilities) of all test statistics (rld for Run-Length Distribution). Required by Python script hplusminus_tests.py and Jupyter notebooks hplusminus_tests.ipynb and hplusminusstatisticalpower.ipynb.

sid.py

Python 3 module file for the calculation of p-values using the gamma distribution approximation of the cumulative Shannon information distributions (SID). Required by Python script hplusminus_tests.py and Jupyter notebooks hplusminus_tests.ipynb and hplusminusstatisticalpower.ipynb.

Directories

./hplusminus/

Python module hplusminus

./examples/

Examples for normalized residuals generated with generatemodelsfor_residuals.ipynb.

./hplusminus/gsp/

Numpy binary files containing B-spline parameters (knots and coefficients) for gamma distribution parameters for all tests. Information is read from these files. No need for user interaction.

./ipynb

Directory containing Jupyter notebooks.

./ipynb/data/

Directory used by Jupyter notebooks for input/output.

Owner

  • Name: bio-phys
  • Login: bio-phys
  • Kind: organization

GitHub Events

Total
Last Year

Committers

Last synced: over 3 years ago

All Time
  • Total Commits: 44
  • Total Committers: 3
  • Avg Commits per committer: 14.667
  • Development Distribution Score (DDS): 0.295
Top Committers
Name Email Commits
Klaus Reuter k****r@m****e 31
jkoefinger j****r@b****e 11
Juergen Koefinger 3****r@u****m 2
Committer Domains (Top 20 + Academic)
biophys.mpg.de: 1 mpcdf.mpg.de: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 1
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 minute
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • 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
  • andreashlarsen (1)
Pull Request Authors
  • reuterk (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

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

evaluate test statistics for normalized residuals

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 5 Last month
Rankings
Dependent packages count: 10.0%
Dependent repos count: 21.7%
Average: 28.7%
Forks count: 29.8%
Stargazers count: 31.9%
Downloads: 50.2%
Maintainers (1)
klaus.reuter
Last synced: 11 months ago

Dependencies

requirements.txt pypi
  • mpmath *
  • numpy *
  • scipy *