Struct ConvergenceCriteria 

pub struct ConvergenceCriteria {
    pub tolerance: f64,
    pub gradient_tolerance: f64,
    pub parameter_tolerance: f64,
    pub max_iterations: usize,
    pub min_iterations: usize,
    pub function_tolerance: f64,
    pub patience: usize,
}

Convergence criteria for optimization algorithms

Fields

tolerance: f64

gradient_tolerance: f64

parameter_tolerance: f64

max_iterations: usize

min_iterations: usize

function_tolerance: f64

patience: usize

Implementations

impl ConvergenceCriteria

pub fn new() -> Self

Create new convergence criteria with default values

pub fn with_tolerance(self, tol: f64) -> Self

Set gradient tolerance

pub fn with_gradient_tolerance(self, tol: f64) -> Self

Set gradient tolerance

pub fn with_parameter_tolerance(self, tol: f64) -> Self

Set parameter tolerance

pub fn with_max_iterations(self, max_iter: usize) -> Self

Set maximum iterations

pub fn with_min_iterations(self, min_iter: usize) -> Self

Set minimum iterations

pub fn with_function_tolerance(self, tol: f64) -> Self

Set function tolerance

pub fn with_patience(self, patience: usize) -> Self

Set patience for early stopping

pub fn is_converged( &self, iteration: usize, current_f: f64, previous_f: Option<f64>, gradient: Option<&ArrayView1<'_, f64>>, parameter_change: Option<f64>, no_improvement_count: usize, ) -> ConvergenceStatus

Check if convergence is achieved

Trait Implementations

impl Clone for ConvergenceCriteria

fn clone(&self) -> ConvergenceCriteria

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ConvergenceCriteria

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

Formats the value using the given formatter.

impl Default for ConvergenceCriteria

fn default() -> Self

Returns the “default value” for a type.