SciPy

minimize(method=’Powell’)

scipy.optimize.minimize(fun, x0, args=(), method='Powell', tol=None, callback=None, options={'func': None, 'xtol': 0.0001, 'ftol': 0.0001, 'maxiter': None, 'maxfev': None, 'disp': False, 'direc': None, 'return_all': False})

Minimization of scalar function of one or more variables using the modified Powell algorithm.

See also

For documentation for the rest of the parameters, see scipy.optimize.minimize

Options
dispbool

Set to True to print convergence messages.

xtolfloat

Relative error in solution xopt acceptable for convergence.

ftolfloat

Relative error in fun(xopt) acceptable for convergence.

maxiter, maxfevint

Maximum allowed number of iterations and function evaluations. Will default to N*1000, where N is the number of variables, if neither maxiter or maxfev is set. If both maxiter and maxfev are set, minimization will stop at the first reached.

direcndarray

Initial set of direction vectors for the Powell method.

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