bundles / numpy 2.4.3 / numpy / linalg / _linalg / _multi_svd_norm

function

`numpy.linalg._linalg:_multi_svd_norm`

source: /numpy/linalg/_linalg.py :2566

Signature

def _multi_svd_norm ( x , row_axis , col_axis , op , initial = None )

Summary

Compute a function of the singular values of the 2-D matrices in x.

Extended Summary

This is a private utility function used by numpy.linalg.norm().

Parameters

x : ndarray
row_axis, col_axis : int: The axes of x that hold the 2-D matrices.
op : callable: This should be either numpy.amin or numpy.amax or numpy.sum.

Returns

result : float or ndarray: If x is 2-D, the return values is a float. Otherwise, it is an array with x.ndim - 2 dimensions. The return values are either the minimum or maximum or sum of the singular values of the matrices, depending on whether op is numpy.amin or numpy.amax or numpy.sum.

Aliases

numpy.linalg._linalg._multi_svd_norm