ZCA whitening (http://ufldl.stanford.edu/wiki/index.php/Implementing_PCA/Whitening)

gistfile1.py

import numpy as np
from scipy import linalg

class ZCA():
    """
    Performs ZCA. Based on
    https://gist.github.com/duschendestroyer/5170087
    """
    def __init__(self, regularization=10**-5):
        self.regularization = regularization

    def fit(self, X):
        X = np.array(X)
        X = X.astype(np.float32)

        self._mean = np.mean(X, axis=0)
        X -= self._mean
        sigma = np.dot(X.T,X) / X.shape[1]
        U, S, V = linalg.svd(sigma)
        tmp = np.dot(U, np.diag(1/np.sqrt(S+self.regularization)))
        self._components = np.dot(tmp, U.T)
        return self

    def transform(self, X):
        X = np.array(X)
        X = X.astype(np.float32)

        X_transformed = X - self._mean
        X_transformed = np.dot(X_transformed, self._components.T)
        return X_transformed

removed dependency on sklearn