sklearn.metrics.pairwise.paired_manhattan_distances

sklearn.metrics.pairwise.paired_manhattan_distances(X, Y)

Compute the paired L1 distances between X and Y.

Distances are calculated between (X[0], Y[0]), (X[1], Y[1]), …, (X[n_samples], Y[n_samples]).

Read more in the User Guide.

Parameters:

X{array-like, sparse matrix} of shape (n_samples, n_features)

An array-like where each row is a sample and each column is a feature.

Y{array-like, sparse matrix} of shape (n_samples, n_features)

An array-like where each row is a sample and each column is a feature.

Returns:

distancesndarray of shape (n_samples,)

L1 paired distances between the row vectors of X and the row vectors of Y.

Examples

>>> from sklearn.metrics.pairwise import paired_manhattan_distances
>>> import numpy as np
>>> X = np.array([[1, 1, 0], [0, 1, 0], [0, 0, 1]])
>>> Y = np.array([[0, 1, 0], [0, 0, 1], [0, 0, 0]])
>>> paired_manhattan_distances(X, Y)
array([1., 2., 1.])