scipy.linalg.lapack.dgelsd#
- scipy.linalg.lapack.dgelsd(a, b, lwork, size_iwork, cond=-1.0, overwrite_a=0, overwrite_b=0) = <flapack function dgelsd>#
Solve a least-squares problem by divide-and-conquer SVD (LAPACK
dgelsd).- Parameters:
- andarray
Matrix of shape
(m, n).- bndarray
Right-hand side(s) with
max(m, n)rows.- lworkint
Size of the workspace. Use
gelsd_lworkfor the required value.- size_iworkint
Size of the integer workspace, as reported by
gelsd_lwork.- condfloat, optional
Singular values below
condtimes the largest are treated as zero. Default is -1.0, which uses machine precision.- overwrite_aint, optional
If nonzero, a may be overwritten in place. Default is 0.
- overwrite_bint, optional
If nonzero, b may be overwritten in place. Default is 0.
- Returns:
- xndarray
Minimum-norm solution in the first
nrows.- sndarray
Singular values of a, in descending order.
- rankint
Effective rank of a, determined using cond.
- infoint
0 on success; if negative, the
-info-th argument had an illegal value; if positive, the algorithm failed to converge.