Struct OptimResult 

#[non_exhaustive]
pub struct OptimResult<F> {
    pub x: Vec<F>,
    pub value: F,
    pub gradient: Vec<F>,
    pub gradient_norm: F,
    pub iterations: usize,
    pub func_evals: usize,
    pub termination: TerminationReason,
    pub diagnostics: SolverDiagnostics,
}

Result of an optimization run.

Marked #[non_exhaustive] so we can add fields without further breaking-change releases. Construct via the solver entry points (lbfgs, newton, trust_region, …) — never with a struct literal.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

x: Vec<F>

Solution point.

value: F

Objective value at the solution.

gradient: Vec<F>

Gradient at the solution.

gradient_norm: F

Norm of the gradient at the solution.

iterations: usize

Number of outer iterations performed.

func_evals: usize

Total number of objective function evaluations.

termination: TerminationReason

Reason for termination.

diagnostics: SolverDiagnostics

Per-solver diagnostic counters surfacing internal events that would otherwise be silent (curvature pair filtering, gamma clamps, line-search backtracks, Newton fallback steps, trust- region radius shrinks, CG inner iterations).

Use this to detect when a solver reports GradientNorm convergence but actually spent most of its work in fallback or filtering paths — a sign that the problem doesn’t suit the chosen solver.

Trait Implementations

impl<F: Clone> Clone for OptimResult<F>

fn clone(&self) -> OptimResult<F>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<F: Debug> Debug for OptimResult<F>

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

Formats the value using the given formatter.