differential_evolution(func, bounds, args=(), strategy='best1bin', maxiter=1000, popsize=15, tol=0.01, mutation=(0.5, 1), recombination=0.7, seed=None, callback=None, disp=False, polish=True, init='latinhypercube', atol=0, updating='immediate', workers=1, constraints=(), x0=None, *, integrality=None, vectorized=False)

Notes

Parameters

func : callable

bounds : sequence or `Bounds`

args : tuple, optional

strategy : str, optional

maxiter : int, optional

popsize : int, optional

tol : float, optional

mutation : float or tuple(float, float), optional

recombination : float, optional

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

disp : bool, optional

callback : callable, `callback(xk, convergence=val)`, optional

polish : bool, optional

init : str or array-like, optional

atol : float, optional

updating : {'immediate', 'deferred'}, optional

workers : int or map-like callable, optional

constraints : {NonLinearConstraint, LinearConstraint, Bounds}

x0 : None or array-like, optional

integrality : 1-D array, optional

vectorized : bool, optional

Returns

res : OptimizeResult

Examples

See :

Back References

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

scipy.optimize._optimize:brute

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