revanalyzer.vectorizers.silhouette_vectorizer.SilhouetteVectorizer

class revanalyzer.vectorizers.silhouette_vectorizer.SilhouetteVectorizer(resolution, n=1, norm=2)

Bases: BasicVectorizer

Class describing persistence silhouette vectorizer.

Input:

resolution (int): number of samples for the weighted average;

n (int): power parameter in weighted funtion (d-b)^n, default = 1;

norm (int): Norm of vectors used in REV analysis. The same, as parameter ‘ord’ in numpy.linalg.norm function, default: 2.

Methods

vectorize

Vectorize the vector metric values for a given pair of subsamples.

vectorize(v1, v2)

Vectorize the vector metric values for a given pair of subsamples.

Input:

v1 (list(dtype = float)): data for the first subsample;

v2 (list(dtype = float)): data for the second subsample.

Output:

(list(dtype = float), list(dtype = float), float): a tuple, in which the first two elements are vectorized metric values for a given pair of subsamples, and the last one is the normalized distance between these vectors.