Struct MaybeThreadPool 

pub struct MaybeThreadPool {
    pub thread_pool: ThreadPool,
}

A wrapper struct which conditionally contains a thread pool if the rayon feature is enabled.

Fields

thread_pool: ThreadPool

The underlying ThreadPool

Trait Implementations

impl CostFunction<MaybeThreadPool, LadduError> for LikelihoodEvaluator

fn evaluate( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<Float, LadduError>

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

impl CostFunction<MaybeThreadPool, LadduError> for NLL

fn evaluate( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<Float, LadduError>

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

impl CostFunction<MaybeThreadPool, LadduError> for StochasticNLL

fn evaluate( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<Float, LadduError>

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

impl Debug for MaybeThreadPool

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

Formats the value using the given formatter.

impl Gradient<MaybeThreadPool, LadduError> for LikelihoodEvaluator

fn gradient( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<DVector<Float>, LadduError>

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

fn hessian( &self, x: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, args: &U, ) -> Result<Matrix<f64, Dyn, Dyn, VecStorage<f64, Dyn, Dyn>>, E>

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

impl Gradient<MaybeThreadPool, LadduError> for NLL

fn gradient( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<DVector<Float>, LadduError>

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

fn hessian( &self, x: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, args: &U, ) -> Result<Matrix<f64, Dyn, Dyn, VecStorage<f64, Dyn, Dyn>>, E>

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

impl Gradient<MaybeThreadPool, LadduError> for StochasticNLL

fn gradient( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<DVector<Float>, LadduError>

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

fn hessian( &self, x: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, args: &U, ) -> Result<Matrix<f64, Dyn, Dyn, VecStorage<f64, Dyn, Dyn>>, E>

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

impl LogDensity<MaybeThreadPool, LadduError> for LikelihoodEvaluator

fn log_density( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<Float, LadduError>

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

impl LogDensity<MaybeThreadPool, LadduError> for NLL

fn log_density( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<Float, LadduError>

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

impl LogDensity<MaybeThreadPool, LadduError> for StochasticNLL

fn log_density( &self, parameters: &DVector<Float>, args: &MaybeThreadPool, ) -> Result<Float, LadduError>

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