scipy 1.8.0 Pypi GitHub Homepage
Other Docs
ParametersReturns
singular_leading_submatrix(A, U, k)

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).

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

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/optimize/_trustregion_exact.py#144
type: <class 'function'>
Commit: