def compute_pvalue(self): difference = smooth_difference(self.random_frequencies, self.data_x, self.data_y) return mahalanobis_distance(difference, 2 * self.num_random_features)
def compute_pvalue(self): _, dimension = numpy.shape(self.data_x) obs = self.vector_of_differences(dimension) return mahalanobis_distance(obs, self.number_of_frequencies)