scipy.sparse.

kron#

scipy.sparse.kron(A, B, format=None)[source]#

Sparse representation of the Kronecker product of A and B.

Computes the Kronecker product, a composite sparse array made of blocks consisting of the second input array multiplied by each element of the first input array.

Warning

kron is switching to the sparse array interface.

For the case where no input arrays are sparse, this function is switching to returning a sparse array instead of sparse matrix. Control the sparse return class by making at least one input sparse, e.g., kron(coo_matrix(A), B), or kron(coo_array(A), B). That removes any deprecation warnings as well. For more general information about sparrays, see Migration from spmatrix to sparray. Handling of this no sparse input case will change no earlier than v1.20.

Parameters:

Asparse or dense array: first array of the product
Bsparse or dense array: second array of the product
formatstr, optional (default: ‘bsr’ or ‘coo’): format of the result (e.g. “csr”) If None, choose ‘bsr’ for relatively dense 2D arrays and ‘coo’ for others

Returns:

sparse matrix or array: kronecker product in a sparse format. Returns a sparse matrix unless either A or B is a sparse array in which case returns a sparse array.

Examples

>>> import numpy as np
>>> import scipy as sp
>>> A = sp.sparse.csr_array(np.array([[0, 2], [5, 0]]))
>>> B = sp.sparse.csr_array(np.array([[1, 2], [3, 4]]))
>>> sp.sparse.kron(A, B).toarray()
array([[ 0,  0,  2,  4],
       [ 0,  0,  6,  8],
       [ 5, 10,  0,  0],
       [15, 20,  0,  0]])

>>> sp.sparse.kron(A, [[1, 2], [3, 4]]).toarray()
array([[ 0,  0,  2,  4],
       [ 0,  0,  6,  8],
       [ 5, 10,  0,  0],
       [15, 20,  0,  0]])