bulk_dice_count_distance#

skfp.distances.bulk_dice_count_distance(X: list | ndarray | csr_array, Y: list | ndarray | csr_array | None = None) → ndarray#

Bulk Dice distance for vectors of count values.

Computes the pairwise Dice distance between count 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 dice_count_distance().

Parameters:

  • X (ndarray or CSR sparse array) – First count input array or sparse matrix, of shape \(m \times d\)

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

Returns:

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

Return type:

ndarray

See also

dice_count_distance()

Dice distance function for two vectors

Examples

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

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