Struct Quadratic 

pub struct Quadratic {
    pub final_x: Option<[Number; 2]>,
    pub final_obj: Number,
}

Fields

final_x: Option<[Number; 2]>

final_obj: Number

Trait Implementations

impl Debug for Quadratic

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Quadratic

fn default() -> Self

Returns the “default value” for a type.

impl TNLP for Quadratic

fn get_nlp_info(&mut self) -> Option<NlpInfo>

Required. Problem dimensions and triplet index style.

fn get_bounds_info(&mut self, b: BoundsInfo<'_>) -> bool

Required. Variable / constraint bounds.

fn get_starting_point(&mut self, sp: StartingPoint<'_>) -> bool

Required. Initial primal (and optionally dual) point.

fn eval_f(&mut self, x: &[Number], _new_x: bool) -> Option<Number>

Required. Objective value at x.

fn eval_grad_f( &mut self, x: &[Number], _new_x: bool, grad: &mut [Number], ) -> bool

Required. Objective gradient at x into grad_f.

fn eval_g(&mut self, _x: &[Number], _new_x: bool, _g: &mut [Number]) -> bool

Required. Constraint values g(x).

fn eval_jac_g( &mut self, _x: Option<&[Number]>, _new_x: bool, _mode: SparsityRequest<'_>, ) -> bool

Required. Jacobian of g. Sparsity vs. values selected by mode. x and new_x are unused on the structure call.

fn eval_h( &mut self, _x: Option<&[Number]>, _new_x: bool, obj_factor: Number, _lambda: Option<&[Number]>, _new_lambda: bool, mode: SparsityRequest<'_>, ) -> bool

Required for exact Hessian, optional for L-BFGS. Hessian of the Lagrangian. Default returns false (signals to %Ipopt that quasi-Newton must be used).

fn finalize_solution(&mut self, sol: Solution<'_>, _d: &IpoptData, _q: &IpoptCq)

Required. Receives the final iterate after solve.

fn get_var_con_metadata( &mut self, _var: &mut MetaData, _con: &mut MetaData, ) -> bool

Provide variable/constraint metadata (e.g. idx_names). Default: no metadata.

fn get_scaling_parameters(&mut self, _req: ScalingRequest<'_>) -> bool

User-supplied scaling, used only when nlp_scaling_method=user-scaling. Default: declines.

fn get_variables_linearity(&mut self, _types: &mut [Linearity]) -> bool

Variable linearity tags (used by Bonmin, not by Ipopt).

fn get_objective_variables_linearity( &mut self, _types: &mut [Linearity], ) -> bool

Per-variable linearity with respect to the objective only (a pounce extension; upstream has no objective-scoped query). NonLinear iff the objective’s nonlinear part depends on the variable; a variable that enters the objective only linearly (or not at all) is Linear even when it is nonlinear in a constraint. Consumed by presolve’s Phase-0 objective-coupling guard, which must not mistake constraint-only nonlinearity for objective coupling. Default: declines (slice untouched).

fn get_constraints_linearity(&mut self, _types: &mut [Linearity]) -> bool

Constraint linearity tags. Used by adaptive-mu’s nlp_scaling_method=equilibration-based.

fn get_number_of_nonlinear_variables(&mut self) -> i32

Number of variables that appear nonlinearly. Returning -1 means “treat all as nonlinear” (the Ipopt default).

fn get_list_of_nonlinear_variables( &mut self, _pos_nonlin_vars: &mut [i32], ) -> bool

List of nonlinear variable indices, in the index style returned from Self::get_nlp_info.

fn derivative_proofs(&mut self) -> DerivativeProofs

What this model can prove about the constancy of its own derivatives (gh #588, phase Q6).

fn wants_intermediate_callback(&self) -> bool

Does Self::intermediate_callback do anything with its payload?

fn update_with_barrier(&mut self, _mu: f64) -> bool

A model whose functions are coupled to the barrier parameter: called by the interior-point loop after every μ update with the new μ. Return true when the model’s functions changed as a result; the loop then discards every evaluation cached at the current point and resets the line search (the filter’s entries were measured against the old functions). The bounds must not change.

fn intermediate_callback( &mut self, _stats: IterStats, _ip_data: &IpoptData, _ip_cq: &IpoptCq, ) -> bool

Per-iteration intermediate callback. Returning false requests early termination with User_Requested_Stop.

fn wants_current_iterate(&self) -> bool

Will Self::intermediate_callback read the live iterate (crate::live_iterate::with_current_user_iterate, the C API’s GetIpoptCurrentIterate / GetIpoptCurrentViolations)?

fn finalize_metadata(&mut self, _var: &MetaData, _con: &MetaData)

Final metadata pass — called just before Self::finalize_solution. Default does nothing.

fn is_presolve_wrapper(&self) -> bool

Whether this TNLP is already an explicit generic-presolve wrapper.

fn scaling_factors(&self) -> Option<Vec<f64>>

The per-variable scaling factors this decorator applies, if it is a scaling wrapper (gh#486). Consumers that read the algorithm’s iterate rather than the finalize_solution payload see scaled coordinates and need these to undo the substitution. A transparent decorator should forward the inner answer.

fn presolve_infeasibility_proof(&self) -> Option<InfeasibilityProof>

A proof that this problem has no feasible point, if presolve found one. None (the default) means “not proved” — which is not the same as “feasible”.