'normalize the random variable, i.e. subtract mean and rescale
The distribution will have zero mean and sigma equal to correlation
Parameters
x : array-like, 1d or 2d
Data to be whitened, if 2d then each row contains an independent
sample of the multivariate random vector
Returns
(x - self.mean)/std_sigma
Notes
See Also
whiten : rescale random variable, standardize without subtracting mean.'

def normalize(self, x):

    std_ = np.atleast_2d(self.std_sigma)
    return ((x - self.mean) / std_)
