scipy.linalg.diagsvd

scipy.linalg.diagsvd(s, M, N)

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

Parameters:

s : (M,) or (N,) array_like

Singular values

M : int

Size of the matrix whose singular values are s.

N : int

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

>>> 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]])