Quwarm

# Примечание: проверки на обратимость ковариационных матриц отсутствуют

import numpy as np


def mahalanobis(point_from, point_to, inverse_covariance_matrix):
    delta = point_from - point_to
    return max(np.float64(0), np.dot(np.dot(delta, inverse_covariance_matrix), delta)) ** 0.5

Quwarm

import numpy as np


def prekopcsac_lemire(class_):
    m, n = class_.shape
    r = np.corrcoef(class_, rowvar=False)
    # CALC standardized class_
    mean_vec = class_.mean(axis=0)
    std_vec = class_.std(axis=0, ddof=1)
    smx = (class_ - np.tile(mean_vec, (m, 1))) / np.tile(std_vec, (m, 1))