def 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):
 solver = DifferentialEvolutionSolver(func, bounds, args=args, strategy=strategy, maxiter=maxiter, popsize=popsize, tol=tol, mutation=mutation, recombination=recombination, seed=seed, polish=polish, callback=callback, disp=disp, init=init, atol=atol)
 return solver.solve()

def 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 ) : solver = DifferentialEvolutionSolver ( func , bounds , args = args , strategy = strategy , maxiter = maxiter , popsize = popsize , tol = tol , mutation = mutation , recombination = recombination , seed = seed , polish = polish , callback = callback , disp = disp , init = init , atol = atol ) return solver . solve ( )
finds the global minimum of a multivariate function .