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_condition_3_13(A_1_norm, n0, m_max, ell)

Notes

This is condition (3.13) in Al-Mohy and Higham (2011).

Parameters

A_1_norm : float

The precomputed 1-norm of A.

n0 : int

Number of columns in the _expm_multiply_* B matrix.

m_max : int

A value related to a bound.

ell : int

The number of columns used in the 1-norm approximation. This is usually taken to be small, maybe between 1 and 5.

Returns

value : bool

Indicates whether or not the condition has been met.

A helper function for the _expm_multiply_* functions.

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/sparse/linalg/_expm_multiply.py#477
type: <class 'function'>
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