dpnp.kron

dpnp.kron(a, b)[source]

Kronecker product of two arrays.

Computes the Kronecker product, a composite array made of blocks of the second array scaled by the first.

For full documentation refer to numpy.kron.

Parameters:

a ({dpnp.ndarray, usm_ndarray, scalar}) -- First input array. Both inputs a and b can not be scalars at the same time.
b ({dpnp.ndarray, usm_ndarray, scalar}) -- Second input array. Both inputs a and b can not be scalars at the same time.

Returns:

out -- Returns the Kronecker product.

Return type:

dpnp.ndarray

See also

dpnp.outer: Returns the outer product of two arrays.

Examples

>>> import dpnp as np
>>> a = np.array([1, 10, 100])
>>> b = np.array([5, 6, 7])
>>> np.kron(a, b)
array([  5,   6,   7, ..., 500, 600, 700])
>>> np.kron(b, a)
array([  5,  50, 500, ...,   7,  70, 700])

>>> np.kron(np.eye(2), np.ones((2,2)))
array([[1.,  1.,  0.,  0.],
       [1.,  1.,  0.,  0.],
       [0.,  0.,  1.,  1.],
       [0.,  0.,  1.,  1.]])

>>> a = np.arange(100).reshape((2,5,2,5))
>>> b = np.arange(24).reshape((2,3,4))
>>> c = np.kron(a,b)
>>> c.shape
(2, 10, 6, 20)
>>> I = (1,3,0,2)
>>> J = (0,2,1)
>>> J1 = (0,) + J             # extend to ndim=4
>>> S1 = (1,) + b.shape
>>> K = tuple(np.array(I) * np.array(S1) + np.array(J1))
>>> c[K] == a[I]*b[J]
array(True)