Struct HSFunction 

pub struct HSFunction<R: RealScalar, const D: DifferentiationLevel> { /* private fields */ }

Trait Implementations

impl<R: RealScalar, const D: DifferentiationLevel> CostFunction<R> for HSFunction<R, D>

fn cost(&mut self, params: &[R]) -> R

Calculates the cost for the given parameters.

impl<R: RealScalar, const D: DifferentiationLevel> Function for HSFunction<R, D>

fn num_params(&self) -> usize

impl<R: RealScalar, const D: DifferentiationLevel> Gradient<R> for HSFunction<R, D>

fn gradient_into(&mut self, params: &[R], grad_out: RowMut<'_, R>)

Calculates the gradient for the given parameters.

fn cost_and_gradient_into(&mut self, params: &[R], grad_out: RowMut<'_, R>) -> R

Calculates the cost and gradient for the given parameters.

fn allocate_gradient(&self) -> Row<R>

impl<R: RealScalar, const D: DifferentiationLevel> Hessian<R> for HSFunction<R, D>

fn hessian_into(&mut self, _params: &[R], _hess_out: MatMut<'_, R>)

Calculates the Hessian for the given parameters.

fn cost_gradient_and_hessian_into( &mut self, _params: &[R], _grad_out: RowMut<'_, R>, _hess_out: MatMut<'_, R>, ) -> R

Calculates the cost, gradient, and Hessian for the given parameters.

fn allocate_hessian(&self) -> Mat<R>

impl<R: RealScalar, const D: DifferentiationLevel> Jacobian<R> for HSFunction<R, D>

fn residuals_and_jacobian_into( &mut self, params: &[R], residuals_out: ColMut<'_, R>, jacobian_out: MatMut<'_, R>, )

Calculates the residuals and Jacobian for the given parameters.

fn jacobian_into(&mut self, params: &[R], jacobian_out: MatMut<'_, R>)

Calculates the Jacobian for the given parameters.

fn allocate_jacobian(&self) -> Mat<R>

impl<R: RealScalar, const D: DifferentiationLevel> ResidualFunction<R> for HSFunction<R, D>

fn num_residuals(&self) -> usize

fn residuals_into(&mut self, params: &[R], residuals_out: ColMut<'_, R>)

Calculates the residuals for the given parameters.

fn allocate_residual(&self) -> Col<R>