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ParametersBackRef

Parameters

lb : array_like

A 1-D NumPy ndarray containing lower bounds of the generated components. Neither NaN or inf are allowed.

ub : array_like

A 1-D NumPy ndarray containing upper bounds for the generated components. Neither NaN or inf are allowed.

visiting_param : float

Parameter for visiting distribution. Default value is 2.62. Higher values give the visiting distribution a heavier tail, this makes the algorithm jump to a more distant region. The value range is (1, 3]. It's value is fixed for the life of the object.

rand_gen : {`~numpy.random.RandomState`, `~numpy.random.Generator`}

A RandomState , Generator object for using the current state of the created random generator container.

Class used to generate new coordinates based on the distorted Cauchy-Lorentz distribution. Depending on the steps within the strategy chain, the class implements the strategy for generating new location changes.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.optimize._dual_annealing.StrategyChain

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/_dual_annealing.py#22
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