diagsvd(s, 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

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

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]])

See :

Back References

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

scipy.linalg._decomp_svd.svdvals scipy.linalg._decomp_svd.svd scipy.linalg._decomp_svd.diagsvd

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