cobyqa.models.Models#
- class cobyqa.models.Models(pb, options)[source]#
Models for a nonlinear optimization problem.
- Attributes:
ceq_val
Values of the nonlinear equality constraint functions at the interpolation points.
cub_val
Values of the nonlinear inequality constraint functions at the interpolation points.
fun_val
Values of the objective function at the interpolation points.
interpolation
Interpolation set.
m_nonlinear_eq
Number of nonlinear equality constraints.
m_nonlinear_ub
Number of nonlinear inequality constraints.
n
Dimension of the problem.
npt
Number of interpolation points.
target_init
Whether a nearly feasible interpolation point has been found with an objective function value below the target.
Methods
ceq
(x[, mask])Evaluate the quadratic models of the nonlinear equality functions at a given point.
ceq_curv
(v[, mask])Evaluate the curvature of the quadratic models of the nonlinear equality functions along a given direction.
ceq_grad
(x[, mask])Evaluate the gradients of the quadratic models of the nonlinear equality functions at a given point.
ceq_hess
([mask])Evaluate the Hessian matrices of the quadratic models of the nonlinear equality functions.
ceq_hess_prod
(v[, mask])Evaluate the right product of the Hessian matrices of the quadratic models of the nonlinear equality functions with a given vector.
cub
(x[, mask])Evaluate the quadratic models of the nonlinear inequality functions at a given point.
cub_curv
(v[, mask])Evaluate the curvature of the quadratic models of the nonlinear inequality functions along a given direction.
cub_grad
(x[, mask])Evaluate the gradients of the quadratic models of the nonlinear inequality functions at a given point.
cub_hess
([mask])Evaluate the Hessian matrices of the quadratic models of the nonlinear inequality functions.
cub_hess_prod
(v[, mask])Evaluate the right product of the Hessian matrices of the quadratic models of the nonlinear inequality functions with a given vector.
denominators
(x_new[, k])Compute the denominator of the derivative-free symmetric Broyden update.
fun
(x)Evaluate the quadratic model of the objective function at a given point.
fun_alt_grad
(x)Evaluate the gradient of the alternative quadratic model of the objective function at a given point.
fun_curv
(v)Evaluate the curvature of the quadratic model of the objective function along a given direction.
fun_grad
(x)Evaluate the gradient of the quadratic model of the objective function at a given point.
fun_hess
()Evaluate the Hessian matrix of the quadratic model of the objective function.
Evaluate the right product of the Hessian matrix of the quadratic model of the objective function with a given vector.
Set the quadratic models of the objective function, nonlinear inequality constraints, and nonlinear equality constraints to the alternative quadratic models.
shift_x_base
(new_x_base, options)Shift the base point without changing the interpolation set.
update_interpolation
(k_new, x_new, fun_val, ...)Update the interpolation set.