solve_trust_region_2d(B, g, Delta)

The problem is reformulated as a 4th order algebraic equation, the solution of which is found by numpy.roots.

Parameters

B : ndarray, shape (2, 2)

Symmetric matrix, defines a quadratic term of the function.

g : ndarray, shape (2,)

Defines a linear term of the function.

Delta : float

Radius of a trust region.

Returns

p : ndarray, shape (2,)

Found solution.

newton_step : bool

Whether the returned solution is the Newton step which lies within the trust region.

Solve a general trust-region problem in 2 dimensions.

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

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GitHub : /scipy/optimize/_lsq/common.py#171
type: <class 'function'>
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