'Return the average log-likelihood of all samples.
See. "Pattern Recognition and Machine Learning"
by C. Bishop, 12.2.1 p. 574
or http://www.miketipping.com/papers/met-mppca.pdf
Parameters
X : array, shape(n_samples, n_features)
The data.
Returns
ll : float
Average log-likelihood of the samples under the current model'

def score(self, X, y=None):

    return np.mean(self.score_samples(X))
