Module « scipy.optimize »

Classe « LinearConstraint »

Informations générales

Héritage

builtins.object
    LinearConstraint

Définition

class LinearConstraint(builtins.object):

Description _{[extrait de LinearConstraint.__doc__]}

Linear constraint on the variables.

    The constraint has the general inequality form::

        lb <= A.dot(x) <= ub

    Here the vector of independent variables x is passed as ndarray of shape
    (n,) and the matrix A has shape (m, n).

    It is possible to use equal bounds to represent an equality constraint or
    infinite bounds to represent a one-sided constraint.

    Parameters
    ----------
    A : {array_like, sparse matrix}, shape (m, n)
        Matrix defining the constraint.
    lb, ub : array_like
        Lower and upper bounds on the constraint. Each array must have the
        shape (m,) or be a scalar, in the latter case a bound will be the same
        for all components of the constraint. Use ``np.inf`` with an
        appropriate sign to specify a one-sided constraint.
        Set components of `lb` and `ub` equal to represent an equality
        constraint. Note that you can mix constraints of different types:
        interval, one-sided or equality, by setting different components of
        `lb` and `ub` as  necessary.
    keep_feasible : array_like of bool, optional
        Whether to keep the constraint components feasible throughout
        iterations. A single value set this property for all components.
        Default is False. Has no effect for equality constraints.
    

Constructeur(s)

Signature du constructeur	Description
__init__(self, A, lb, ub, keep_feasible=False)

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe object

__delattr__, __dir__, __format__, __getattribute__, __hash__, __init_subclass__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__