bulk_simpson_binary_distance#

Bulk Simpson distance for binary matrices.

Computes the pairwise Simpson distance between binary matrices. If one array is passed, distances are computed between its rows. For two arrays, distances are between their respective rows, with i-th row and j-th column in output corresponding to i-th row from the first array and j-th row from the second array.

See also simpson_binary_distance().

Parameters:

X (ndarray or CSR sparse array) – First binary input array, of shape \(m \times d\).
Y (ndarray or CSR sparse array, default=None) – Second binary input array, of shape \(n \times d\). If not passed, distances are computed between rows of X.

Returns:

distances – Array with pairwise Simpson distance values. Shape is \(m \times n\) if two arrays are passed, or \(m \times m\) otherwise.

Return type:

ndarray

Examples

>>> from skfp.distances import bulk_simpson_binary_distance
>>> import numpy as np
>>> X = np.array([[1, 0, 1], [1, 0, 1]])
>>> dist = bulk_simpson_binary_distance(X)
>>> dist
array([[0., 0.],
       [0., 0.]])

>>> from scipy.sparse import csr_array
>>> X = csr_array([[1, 0, 1], [1, 0, 1]])
>>> dist = bulk_simpson_binary_distance(X)
>>> dist
array([[0., 0.],
       [0., 0.]])