Function

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Trait Function 

Source 
pub trait Function<U, E> {
    // Required method
    fn evaluate(&self, x: &[Float], user_data: &mut U) -> Result<Float, E>;

    // Provided methods
    fn evaluate_bounded(
        &self,
        x: &[Float],
        bounds: Option<&Vec<Bound>>,
        user_data: &mut U,
    ) -> Result<Float, E> { ... }
    fn gradient(
        &self,
        x: &[Float],
        user_data: &mut U,
    ) -> Result<DVector<Float>, E> { ... }
    fn gradient_bounded(
        &self,
        x: &[Float],
        bounds: Option<&Vec<Bound>>,
        user_data: &mut U,
    ) -> Result<DVector<Float>, E> { ... }
    fn hessian(
        &self,
        x: &[Float],
        user_data: &mut U,
    ) -> Result<DMatrix<Float>, E> { ... }
    fn hessian_bounded(
        &self,
        x: &[Float],
        bounds: Option<&Vec<Bound>>,
        user_data: &mut U,
    ) -> Result<DMatrix<Float>, E> { ... }
}
Expand description

A trait which describes a function $f(\mathbb{R}^n) \to \mathbb{R}$

Such a function may also take a user_data: &mut U field which can be used to pass external arguments to the function during minimization, or can be modified by the function itself.

The Function trait takes a generic T which represents a numeric scalar, a generic U representing the type of user data/arguments, and a generic E representing any possible errors that might be returned during function execution.

There is also a default implementation of a gradient function which uses a central finite-difference method to evaluate derivatives. If an exact gradient is known, it can be used to speed up gradient-dependent algorithms.

Required Methods§

Source

fn evaluate(&self, x: &[Float], user_data: &mut U) -> Result<Float, E>

The evaluation of the function at a point x with the given arguments/user data.

§Errors

Returns an Err(E) if the evaluation fails. Users should implement this trait to return a std::convert::Infallible if the function evaluation never fails.

Provided Methods§

Source

fn evaluate_bounded( &self, x: &[Float], bounds: Option<&Vec<Bound>>, user_data: &mut U, ) -> Result<Float, E>

The evaluation of the function at a point x with the given arguments/user data. This function assumes x is an internal, unbounded vector, but performs a coordinate transform to bound x when evaluating the function.

§Errors

Returns an Err(E) if the evaluation fails. Users should implement this trait to return a std::convert::Infallible if the function evaluation never fails.

Source

fn gradient(&self, x: &[Float], user_data: &mut U) -> Result<DVector<Float>, E>

The evaluation of the gradient at a point x with the given arguments/user data.

§Errors

Returns an Err(E) if the evaluation fails. See Function::evaluate for more information.

Source

fn gradient_bounded( &self, x: &[Float], bounds: Option<&Vec<Bound>>, user_data: &mut U, ) -> Result<DVector<Float>, E>

The evaluation of the gradient at a point x with the given arguments/user data. This function assumes x is an internal, unbounded vector, but performs a coordinate transform to bound x when evaluating the function.

§Errors

Returns an Err(E) if the evaluation fails. See Function::evaluate for more information.

Source

fn hessian(&self, x: &[Float], user_data: &mut U) -> Result<DMatrix<Float>, E>

The evaluation of the hessian at a point x with the given arguments/user data.

§Errors

Returns an Err(E) if the evaluation fails. See Function::evaluate for more information.

Source

fn hessian_bounded( &self, x: &[Float], bounds: Option<&Vec<Bound>>, user_data: &mut U, ) -> Result<DMatrix<Float>, E>

The evaluation of the hessian at a point x with the given arguments/user data. This function assumes x is an internal, unbounded vector, but performs a coordinate transform to bound x when evaluating the function.

§Errors

Returns an Err(E) if the evaluation fails. See Function::evaluate for more information.

Implementors§