Vous êtes un professionnel et vous avez besoin d'une formation ? RAG (Retrieval-Augmented Generation)
et Fine Tuning d'un LLM Voir le programme détaillé

Classe « Covariance »

Méthode scipy.stats.Covariance.whiten

Signature de la méthode whiten

def whiten(self, x) 

Description

help(Covariance.whiten)

Perform a whitening transformation on data.

"Whitening" ("white" as in "white noise", in which each frequency has
equal magnitude) transforms a set of random variables into a new set of
random variables with unit-diagonal covariance. When a whitening
transform is applied to a sample of points distributed according to
a multivariate normal distribution with zero mean, the covariance of
the transformed sample is approximately the identity matrix.

Parameters
----------
x : array_like
    An array of points. The last dimension must correspond with the
    dimensionality of the space, i.e., the number of columns in the
    covariance matrix.

Returns
-------
x_ : array_like
    The transformed array of points.

References
----------
.. [1] "Whitening Transformation". Wikipedia.
       https://en.wikipedia.org/wiki/Whitening_transformation
.. [2] Novak, Lukas, and Miroslav Vorechovsky. "Generalization of
       coloring linear transformation". Transactions of VSB 18.2
       (2018): 31-35. :doi:`10.31490/tces-2018-0013`

Examples
--------
>>> import numpy as np
>>> from scipy import stats
>>> rng = np.random.default_rng()
>>> n = 3
>>> A = rng.random(size=(n, n))
>>> cov_array = A @ A.T  # make matrix symmetric positive definite
>>> precision = np.linalg.inv(cov_array)
>>> cov_object = stats.Covariance.from_precision(precision)
>>> x = rng.multivariate_normal(np.zeros(n), cov_array, size=(10000))
>>> x_ = cov_object.whiten(x)
>>> np.cov(x_, rowvar=False)  # near-identity covariance
array([[0.97862122, 0.00893147, 0.02430451],
       [0.00893147, 0.96719062, 0.02201312],
       [0.02430451, 0.02201312, 0.99206881]])

Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
Les fondamentaux Voir le programme détaillé