pub struct Solution {
pub final_point: Array1<f64>,
pub final_value: f64,
pub final_gradient: Option<Array1<f64>>,
pub final_hessian: Option<Array2<f64>>,
pub final_gradient_norm: Option<f64>,
pub final_step_norm: Option<f64>,
pub stationarity_kind: StationarityKind,
pub iterations: usize,
pub func_evals: usize,
pub grad_evals: usize,
pub hess_evals: usize,
}Expand description
A summary of a successful solver run.
Note that for non-convex functions, convergence to a local minimum is not guaranteed.
Fields§
§final_point: Array1<f64>The point at which the minimum value was found.
final_value: f64The minimum value of the objective function.
final_gradient: Option<Array1<f64>>The gradient at the final point when the solver is gradient-based.
final_hessian: Option<Array2<f64>>The Hessian at the final point when the solver tracks one.
final_gradient_norm: Option<f64>The projected gradient norm at the final point when available.
final_step_norm: Option<f64>The final accepted fixed-point step norm when available.
stationarity_kind: StationarityKindThe meaning of the stationarity metric for this solution.
iterations: usizeThe total number of iterations performed.
func_evals: usizeThe total number of times the objective function was evaluated.
grad_evals: usizeThe total number of times the gradient was evaluated.
hess_evals: usizeThe total number of times a Hessian was supplied directly by the objective.
Trait Implementations§
Auto Trait Implementations§
impl Freeze for Solution
impl RefUnwindSafe for Solution
impl Send for Solution
impl Sync for Solution
impl Unpin for Solution
impl UnsafeUnpin for Solution
impl UnwindSafe for Solution
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more