khatri_rao(a, b)

A column-wise Kronecker product of two matrices

Notes

The mathematical definition of the Khatri-Rao product is:

$$(A_{ij} \bigotimes B_{ij})_{ij}$$

which is the Kronecker product of every column of A and B, e.g.:

c = np.vstack([np.kron(a[:, k], b[:, k]) for k in range(b.shape[1])]).T

Parameters

a: (n, k) array_like :

Input array

b: (m, k) array_like :

Input array

Returns

c: (n*m, k) ndarray

Khatri-rao product of a and b.

Khatri-rao product

See Also

kron

Kronecker product

Examples

>>> from scipy import linalg
... a = np.array([[1, 2, 3], [4, 5, 6]])
... b = np.array([[3, 4, 5], [6, 7, 8], [2, 3, 9]])
... linalg.khatri_rao(a, b)
array([[ 3,  8, 15],
       [ 6, 14, 24],
       [ 2,  6, 27],
       [12, 20, 30],
       [24, 35, 48],
       [ 8, 15, 54]])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.linalg._matfuncs.khatri_rao

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

GitHub : /scipy/linalg/_matfuncs.py#672
type: <class 'function'>
Commit: