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whitening

The package implements in Python with a sklearn-like interface the whitening methods:

  • ZCA
  • PCA
  • Cholesky
  • ZCA-cor
  • PCA-cor

discussed in [KLS2018].

Usage

from whitening import whiten
import numpy as np
X = np.random.random((10000, 15)) # data array
trf = whiten().fit(X, method = "zca")
X_whitened = trf.transform(X)
X_reconstructed = trf.inverse_transform(X_whitened)
assert(np.allclose(X, X_reconstructed)) # True

Installation

git clone https://github.com/remolek/whitening.git
cd whitening; python setup.py install

Requirements

  • NumPy
  • SciPy
  • scikit-learn

Licence

GPLv3

Authors

'whitening' was rewritten by Jeremi Ochab

based on:

  1. https://CRAN.R-project.org/package=whitening by Korbinian Strimmer, Takoua Jendoubi, Agnan Kessy, Alex Lewin
  2. Python implementation https://gist.github.com/joelouismarino/ce239b5601fff2698895f48003f7464b by Joe Marino
  3. sklearn interface from https://github.com/mwv/zca by Maarten Versteegh
[KLS2018]Kessy, Lewin, and Strimmer (2018) ``Optimal whitening and decorrelation'', https://doi.org/10.1080/00031305.2016.1277159.