`scipy.optimize._constraints:PreparedConstraint`

source: build-install/usr/lib/python3.14/site-packages/scipy/optimize/_constraints.py:356

Signature

class PreparedConstraint(constraint, x0, sparse_jacobian = None, finite_diff_bounds = (-inf, inf))

Members

Summary

Constraint prepared from a user defined constraint.

Extended Summary

On creation it will check whether a constraint definition is valid and the initial point is feasible. If created successfully, it will contain the attributes listed below.

Parameters

constraint : {NonlinearConstraint, LinearConstraint`, Bounds}: Constraint to check and prepare.
x0 : array_like: Initial vector of independent variables.
sparse_jacobian : bool or None, optional: If bool, then the Jacobian of the constraint will be converted to the corresponded format if necessary. If None (default), such conversion is not made.
finite_diff_bounds : 2-tuple, optional: Lower and upper bounds on the independent variables for the finite difference approximation, if applicable. Defaults to no bounds.

Attributes

fun : {VectorFunction, LinearVectorFunction, IdentityVectorFunction}: Function defining the constraint wrapped by one of the convenience classes.
bounds : 2-tuple: Contains lower and upper bounds for the constraints --- lb and ub. These are converted to ndarray and have a size equal to the number of the constraints.
keep_feasible : ndarray: Array indicating which components must be kept feasible with a size equal to the number of the constraints.

Aliases

scipy.optimize._constraints.PreparedConstraint