simpeg.utils.GaussianMixtureWithPrior.score_samples_with_sensW#

GaussianMixtureWithPrior.score_samples_with_sensW(X, sensW)[source]#

Compute the weighted log probabilities for each sample.

[New function, modified from Scikit-Learn.mixture.gaussian_mixture.score_samples] Compute the weighted log probabilities for each sample.

Parameters:
X(n_samples, n_features) array_like

List of n_features-dimensional data points. Each row corresponds to a single data point.

sensW(n_samples) array_like

Sensitivity weights

Returns:
(n_samples) numpy.array

Log probabilities of each data point in X.