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Module « scipy.optimize »

Fonction fmin_slsqp - module scipy.optimize

Signature de la fonction fmin_slsqp

def 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) 

Description

help(scipy.optimize.fmin_slsqp)

Minimize a function using Sequential Least Squares Programming

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

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 <= 0 : Silent operation
    * iprint == 1 : Print summary upon completion (default)
    * iprint >= 2 : Print 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.

Returns
-------
out : ndarray of float
    The final minimizer of func.
fx : ndarray of float, if full_output is true
    The final value of the objective function.
its : int, if full_output is true
    The number of iterations.
imode : int, if full_output is true
    The exit mode from the optimizer (see below).
smode : string, if full_output is true
    Message describing the exit mode from the optimizer.

See also
--------
minimize: Interface to minimization algorithms for multivariate
    functions. See the 'SLSQP' `method` in particular.

Notes
-----
Exit modes are defined as follows:

- ``-1`` : Gradient evaluation required (g & a)
- ``0`` : Optimization terminated successfully
- ``1`` : Function evaluation required (f & c)
- ``2`` : More equality constraints than independent variables
- ``3`` : More than 3*n iterations in LSQ subproblem
- ``4`` : Inequality constraints incompatible
- ``5`` : Singular matrix E in LSQ subproblem
- ``6`` : Singular matrix C in LSQ subproblem
- ``7`` : Rank-deficient equality constraint subproblem HFTI
- ``8`` : Positive directional derivative for linesearch
- ``9`` : Iteration limit reached

Examples
--------
Examples are given :ref:`in the tutorial <tutorial-sqlsp>`.

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