bundles / scipy 1.17.1 / scipy / optimize / _trustregion_exact / singular_leading_submatrix

function

`scipy.optimize._trustregion_exact:singular_leading_submatrix`

source: /scipy/optimize/_trustregion_exact.py :148

Signature

def singular_leading_submatrix ( A , U , k )

Summary

Compute term that makes the leading k by k submatrix from A singular.

Parameters

A : ndarray: Symmetric matrix that is not positive definite.
U : ndarray: Upper triangular matrix resulting of an incomplete Cholesky decomposition of matrix A.
k : int: Positive integer such that the leading k by k submatrix from A is the first non-positive definite leading submatrix.

Returns

delta : float: Amount that should be added to the element (k, k) of the leading k by k submatrix of A to make it singular.
v : ndarray: A vector such that v.T B v = 0. Where B is the matrix A after delta is added to its element (k, k).

Aliases

scipy.optimize._trustregion_exact.singular_leading_submatrix