bulk_simpson_binary_distance#

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

Bulk Simpson distance for vectors of binary values.

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 first array and j-th row from second array.

See also simpson_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 Simpson distance values. Shape is \(m \times n\) if two arrays are passed, or \(m \times m\) otherwise.

Return type:

ndarray

See also

simpson_binary_distance()

Simpson distance function for two vectors

Examples

>>> from skfp.distances import bulk_simpson_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_simpson_binary_distance(X, Y)
>>> dist
array([[0., 0.],
       [0., 0.]])

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