`scipy.linalg._decomp_svd:diagsvd`

source: /scipy/linalg/_decomp_svd.py :259

Signature

def diagsvd ( s , M , N )

Summary

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

Extended Summary

The documentation is written assuming array arguments are of specified "core" shapes. However, array argument(s) of this function may have additional "batch" dimensions prepended to the core shape. In this case, the array is treated as a batch of lower-dimensional slices; see linalg_batch for details. Note that calls with zero-size batches are unsupported and will raise a ValueError.

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

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)
diagsvd(vals, 4, 3)

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Aliases

scipy.linalg.diagsvd