Struct MinimizeResult 

pub struct MinimizeResult<T: Float> {
    pub x: Tensor<T>,
    pub f_val: T,
    pub grad: Option<Tensor<T>>,
    pub iterations: usize,
    pub f_evals: usize,
    pub g_evals: usize,
    pub converged: bool,
}

Result of a multi-dimensional minimization algorithm.

Examples

let f = |x: &Tensor<f64>| { let s = x.as_slice(); s[0] * s[0] + s[1] * s[1] };
let g = |x: &Tensor<f64>| {
    let s = x.as_slice();
    Tensor::from_vec(vec![2.0 * s[0], 2.0 * s[1]], vec![2]).unwrap()
};
let x0 = Tensor::from_vec(vec![3.0_f64, 4.0], vec![2]).unwrap();
let result = bfgs(f, g, &x0, &MinimizeOptions::default()).unwrap();
assert!(result.converged);

Fields

x: Tensor<T>

The estimated minimizer.

f_val: T

The function value at the minimizer.

grad: Option<Tensor<T>>

The gradient at the minimizer (if available).

iterations: usize

Number of iterations performed.

f_evals: usize

Number of function evaluations.

g_evals: usize

Number of gradient evaluations.

converged: bool

Whether the algorithm converged.

Trait Implementations

impl<T: Clone + Float> Clone for MinimizeResult<T>

fn clone(&self) -> MinimizeResult<T>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T: Debug + Float> Debug for MinimizeResult<T>

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

Formats the value using the given formatter.