diagsvd — SciPy v1.15.3 Manual (original) (raw)

scipy.linalg.

scipy.linalg.diagsvd(s, M, N)[source]#

Construct the sigma matrix in SVD from singular values and size M, N.

Parameters:

s(M,) or (N,) array_like

Singular values

Mint

Size of the matrix whose singular values are s.

Nint

Size of the matrix whose singular values are s.

Returns:

S(M, N) ndarray

The S-matrix in the singular value decomposition

See also

svd

Singular value decomposition of a matrix

svdvals

Compute singular values of a matrix.

Examples

import numpy as np from scipy.linalg import diagsvd vals = np.array([1, 2, 3]) # The array representing the computed svd diagsvd(vals, 3, 4) array([[1, 0, 0, 0], [0, 2, 0, 0], [0, 0, 3, 0]]) diagsvd(vals, 4, 3) array([[1, 0, 0], [0, 2, 0], [0, 0, 3], [0, 0, 0]])