scipy.optimize.

fmin_slsqp#

scipy.optimize.fmin_slsqp(func, x0, eqcons=(), f_eqcons=None, ieqcons=(), f_ieqcons=None, bounds=(), fprime=None, fprime_eqcons=None, fprime_ieqcons=None, args=(), iter=100, acc=1e-06, iprint=1, disp=None, full_output=0, epsilon=np.float64(1.4901161193847656e-08), callback=None)[source]#

Minimize a function using Sequential Least Squares Programming

Python interface function for the SLSQP Optimization subroutine originally implemented by Dieter Kraft.

Parameters:

funccallable f(x,*args)

Objective function. Must return a scalar.

x01-D ndarray of float

Initial guess for the independent variable(s).

eqconslist, optional

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

f_eqconscallable 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.

ieqconslist, optional

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

f_ieqconscallable 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.

boundslist, 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.

fprimecallable f(x,*args), optional

A function that evaluates the partial derivatives of func.

fprime_eqconscallable 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_ieqconscallable 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) ).

argssequence, optional

Additional arguments passed to func and fprime.

iterint, optional

The maximum number of iterations.

accfloat, optional

Requested accuracy.

iprintint, optional

The verbosity of fmin_slsqp :

iprint <= 0 : Silent operation
iprint == 1 : Print summary upon completion (default)
iprint >= 2 : Print status of each iterate and summary

dispint, optional

Overrides the iprint interface (preferred).

full_outputbool, optional

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

epsilonfloat, optional

The step size for finite-difference derivative estimates.

callbackcallable, optional

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

Returns:

outndarray of float: The final minimizer of func.
fxndarray of float, if full_output is true: The final value of the objective function.
itsint, if full_output is true: The number of iterations.
imodeint, if full_output is true: The exit mode from the optimizer (see below).
smodestring, if full_output is true: Message describing the exit mode from the optimizer.