bundles / scipy 2.0.0.dev0+git20260907.41eeb59 / scipy / linalg / _decomp_svd / orth
function
scipy.linalg._decomp_svd:orth
source: build-install/usr/lib/python3.14/site-packages/scipy/linalg/_decomp_svd.py:362
Signature
def orth(A, rcond = None)Summary
Construct an orthonormal basis for the range of A using SVD.
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. The NEP 5 signature of this function is (i,j)->(i,j).
Parameters
A: (M, N) array_likeInput array
rcond: float, optionalRelative condition number. Singular values
ssmaller thanrcond * max(s)are considered zero. Default: floating point eps * max(M,N).
Returns
Q: (M, K) ndarrayOrthonormal basis for the range of A. K = effective rank of A, as determined by rcond
Examples
import numpy as np from scipy.linalg import orth A = np.array([[2, 0, 0], [0, 5, 0]]) # rank 2 array orth(A) orth(A.T)✓
array([[0., 1.],
[1., 0.],
[0., 0.]])
See also
- null_space
Matrix null space
- svd
Singular value decomposition of a matrix
Aliases
scipy.linalg.orth