bundles / scipy latest / scipy / linalg / _flapack / sgesdd

lapack_function

`scipy.linalg._flapack:sgesdd`

source: build-install/usr/lib/python3.14/site-packages/scipy/linalg/_flapack.cpython-314-x86_64-linux-gnu.so

Signature

def sgesdd(a, compute_uv = 1, full_matrices = 1, lwork = Ellipsis, overwrite_a = 0)

Summary

Compute the singular value decomposition a = u @ diag(s) @ vt by divide-and-conquer (LAPACK sgesdd).

Parameters

a : ndarray: Matrix of shape (m, n).
compute_uv : int, optional: If nonzero, singular vectors are computed. Default is 1.
full_matrices : int, optional: If nonzero, full-sized u and vt are computed. Default is 1.
lwork : int, optional: Size of the workspace. Default is routine-specific. Use gesdd_lwork for the optimal value.
overwrite_a : int, optional: If nonzero, a may be overwritten in place. Default is 0.

Returns

u : ndarray: Left singular vectors; a (1, 1) placeholder when compute_uv is 0.
s : ndarray: Singular values of a, in descending order.
vt : ndarray: Right singular vectors, transposed; a placeholder when compute_uv is 0.
info : int: 0 on success; if negative, the -info-th argument had an illegal value; if positive, the algorithm failed to converge.

Aliases

scipy.linalg._flapack.sgesdd