dual_annealing(func, bounds, args=(), maxiter=1000, minimizer_kwargs=None, initial_temp=5230.0, restart_temp_ratio=2e-05, visit=2.62, accept=-5.0, maxfun=10000000.0, seed=None, no_local_search=False, callback=None, x0=None)

Notes

Parameters

func : callable

bounds : sequence or `Bounds`

args : tuple, optional

maxiter : int, optional

minimizer_kwargs : dict, optional

initial_temp : float, optional

restart_temp_ratio : float, optional

visit : float, optional

accept : float, optional

maxfun : int, optional

seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional

no_local_search : bool, optional

callback : callable, optional

x0 : ndarray, shape(n,), optional

Returns

res : OptimizeResult

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/_dual_annealing.py#435
type: <class 'function'>
Commit: