Struct GradientComputer 

pub struct GradientComputer {
    pub method: GradientMethod,
    pub epsilon: f64,
    pub parallel: bool,
}

Gradient computation utilities

Fields

method: GradientMethod

epsilon: f64

parallel: bool

Implementations

impl GradientComputer

pub fn new() -> Self

Create new gradient computer

pub fn with_method(self, method: GradientMethod) -> Self

Set gradient method

pub fn with_epsilon(self, eps: f64) -> Self

Set finite difference epsilon

pub fn with_parallel(self, parallel: bool) -> Self

Enable parallel computation

pub fn compute_gradient<F>( &self, f: F, x: &ArrayView1<'_, f64>, ) -> UtilsResult<Array1<f64>>

where F: Fn(&ArrayView1<'_, f64>) -> f64 + Sync,

Compute numerical gradient using finite differences

pub fn compute_jacobian<F>( &self, f: F, x: &ArrayView1<'_, f64>, m: usize, ) -> UtilsResult<Array2<f64>>

where F: Fn(&ArrayView1<'_, f64>) -> Array1<f64> + Sync,

Compute Jacobian matrix for vector-valued functions

Trait Implementations

impl Clone for GradientComputer

fn clone(&self) -> GradientComputer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GradientComputer

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

Formats the value using the given formatter.

impl Default for GradientComputer

fn default() -> Self

Returns the “default value” for a type.