bulk_kulczynski_binary_distance#

skfp.distances.bulk_kulczynski_binary_distance(X: ndarray, Y: ndarray | None = None) → ndarray#

Bulk Kulczynski distance for vectors of binary values.

Computes the pairwise Kulczynski 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 first array and j-th row from second array.

See also kulczynski_binary_distance().

Parameters:

  • X (ndarray) – First binary input array, of shape \(m \times m\)

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

Returns:

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

Return type:

ndarray

See also

kulczynski_binary_distance()

Kulczynski distance function for two vectors

Examples

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

>>> X = np.array([[1, 0, 1], [1, 0, 1]])
>>> dist = bulk_kulczynski_binary_distance(X)
>>> dist
array([[0., 0.],
       [0., 0.]])