scipy-psdm

Transform an ill-conditioned quadratic matrix into a positive semi-definite matrix.

Installation

The scipy-psdm git repo is available as PyPi package

pip install scipy-psdm

Usage

Lurie-Goldberg Algorithm to transform an ill-conditioned quadratic matrix into a positive semi-definite matrix.

import scipy_psdm as psdm
import numpy as np

# A matrix with subjectively set correlations
mat = [[ 1.   , -0.948,  0.099, -0.129],
       [-0.948,  1.   , -0.591,  0.239],
       [ 0.099, -0.591,  1.   ,  0.058],
       [-0.129,  0.239,  0.058,  1.   ]]
mat = np.array(mat)

# Convert to a positive semi-definite matrix
rho = psdm.approximate_correlation_matrix(mat)
print(rho.round(3))

Generate correlated random numbers

import scipy_psdm as psdm
X, rho = psdm.randcorr(n_obs=100, n_vars=5, random_state=42)

# compare
import numpy as np
print(rho.round(3))
print(np.corrcoef(X, rowvar=False).round(3))

Check the examples folder for notebooks.

Appendix

Install a virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip3 install -r requirements.txt
pip3 install -r requirements-dev.txt
pip3 install -r requirements-demo.txt

(If your git repo is stored in a folder with whitespaces, then don’t use the subfolder .venv. Use an absolute path without whitespaces.)

Python commands

Start virtual env: source .venv/bin/activate
Jupyter for the examples: jupyter lab
Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')
Run Unit Tests: pytest -v

Publish

pandoc README.md --from markdown --to rst -s -o README.rst
python setup.py sdist
twine upload -r pypi dist/*

Clean up

find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv

Support

Please open an issue for support.

Contributing

Please contribute using Github Flow. Create a branch, add commits, and open a pull request.

Contributers

@KikeM Enrique Millán Valbuena

Metadata

Release files for scipy-psdm 0.2.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for scipy-psdm 0.2.2
File	Size	Uploaded
scipy-psdm-0.2.2.tar.gz	5.3 kB	Jul 20, 2022	Details

Release files / scipy-psdm-0.2.2.tar.gz

Download URL	scipy-psdm-0.2.2.tar.gz
Size	5.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`311db90e5585c3701606671da00b60c9842832791e173d264d9b294e1faba661`
BLAKE2b-256 checksum How to use checksums	`6fa99d7a5f5bdc53037a059b06a7f38c495444d013eadb7536b5bf2a21bbe489`
Upload date	Jul 20, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.3.0 pkginfo/1.8.3 requests/2.28.1 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.64.0 CPython/3.7.9`