scipy.optimize._slsqp_py:fmin_slsqp

Parameters

func : callable f(x,*args)

Objective function. Must return a scalar.

x0 : 1-D ndarray of float

Initial guess for the independent variable(s).

eqcons : list, optional

A list of functions of length n such that eqcons[j](x,*args) == 0.0 in a successfully optimized problem.

f_eqcons : callable f(x,*args), optional

Returns a 1-D array in which each element must equal 0.0 in a successfully optimized problem. If f_eqcons is specified, eqcons is ignored.

ieqcons : list, optional

A list of functions of length n such that ieqcons[j](x,*args) >= 0.0 in a successfully optimized problem.

f_ieqcons : callable f(x,*args), optional

Returns a 1-D ndarray in which each element must be greater or equal to 0.0 in a successfully optimized problem. If f_ieqcons is specified, ieqcons is ignored.

bounds : list, optional

A list of tuples specifying the lower and upper bound for each independent variable [(xl0, xu0),(xl1, xu1),...] Infinite values will be interpreted as large floating values.

fprime : callable ``f(x,*args)``, optional

A function that evaluates the partial derivatives of func.

fprime_eqcons : callable ``f(x,*args)``, optional

A function of the form f(x, *args) that returns the m by n array of equality constraint normals. If not provided, the normals will be approximated. The array returned by fprime_eqcons should be sized as ( len(eqcons), len(x0) ).

fprime_ieqcons : callable ``f(x,*args)``, optional

A function of the form f(x, *args) that returns the m by n array of inequality constraint normals. If not provided, the normals will be approximated. The array returned by fprime_ieqcons should be sized as ( len(ieqcons), len(x0) ).

args : sequence, optional

Additional arguments passed to func and fprime.

iter : int, optional

The maximum number of iterations.

acc : float, optional

Requested accuracy.

iprint : int, optional

The verbosity of fmin_slsqp :

• iprint <= 0Silent operation

• iprint == 1Print summary upon completion (default)

• iprint >= 2Print status of each iterate and summary

disp : int, optional

Overrides the iprint interface (preferred).

full_output : bool, optional

If False, return only the minimizer of func (default). Otherwise, output final objective function and summary information.

epsilon : float, optional

The step size for finite-difference derivative estimates.

callback : callable, optional

Called after each iteration, as callback(x), where x is the current parameter vector.