It represents the set of constraints of the form:
f_eq(x) = 0 f_ineq(x) <= 0
where f_eq
and f_ineq
are evaluated by a single function, see below.
The class is supposed to be instantiated by factory methods, which should prepare the parameters listed below.
Number of equality and inequality constraints respectively.
Function defining the constraints. The signature is fun(x) -> c_eq, c_ineq
, where c_eq
is ndarray with :None:None:`n_eq` components and c_ineq
is ndarray with :None:None:`n_ineq` components.
Function to evaluate the Jacobian of the constraint. The signature is jac(x) -> J_eq, J_ineq
, where J_eq
and J_ineq
are either ndarray of csr_matrix of shapes (n_eq, n) and (n_ineq, n), respectively.
Function to evaluate the Hessian of the constraints multiplied by Lagrange multipliers, that is dot(f_eq, v_eq) + dot(f_ineq, v_ineq)
. The signature is hess(x, v_eq, v_ineq) -> H
, where H
has an implied shape (n, n) and provide a matrix-vector product operation H.dot(p)
.
Mask indicating which inequality constraints should be kept feasible.
Canonical constraint to use with trust-constr algorithm.
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