Struct NonlinearConjugateGradient

pub struct NonlinearConjugateGradient<P, L, B, F> { /* private fields */ }

The nonlinear conjugate gradient is a generalization of the conjugate gradient method for nonlinear optimization problems.

Example

References:

[0] Jorge Nocedal and Stephen J. Wright (2006). Numerical Optimization. Springer. ISBN 0-387-30303-0.

Implementations

impl<P, L, B, F> NonlinearConjugateGradient<P, L, B, F>

where P: Default, F: ArgminFloat,

pub fn new(linesearch: L, beta_method: B) -> Result<Self, Error>

Constructor (Polak Ribiere Conjugate Gradient (PR-CG))

pub fn restart_iters(self, iters: u64) -> Self

Specifiy the number of iterations after which a restart should be performed This allows the algorithm to “forget” previous information which may not be helpful anymore.

pub fn restart_orthogonality(self, v: F) -> Self

Set the value for the orthogonality measure. Setting this parameter leads to a restart of the algorithm (setting beta = 0) after two consecutive search directions are not orthogonal anymore. In other words, if this condition is met:

|\nabla f_k^T * \nabla f_{k-1}| / | \nabla f_k ||^2 >= v

A typical value for v is 0.1.

Trait Implementations

impl<P: Clone, L: Clone, B: Clone, F: Clone> Clone for NonlinearConjugateGradient<P, L, B, F>

fn clone(&self) -> NonlinearConjugateGradient<P, L, B, F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'de, P, L, B, F> Deserialize<'de> for NonlinearConjugateGradient<P, L, B, F>

where P: Deserialize<'de>, L: Deserialize<'de>, B: Deserialize<'de>, F: Deserialize<'de>,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<P, L, B, F> Serialize for NonlinearConjugateGradient<P, L, B, F>

where P: Serialize, L: Serialize, B: Serialize, F: Serialize,

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<O, P, L, B, F> Solver<O> for NonlinearConjugateGradient<P, L, B, F>

where O: ArgminOp<Param = P, Output = F, Float = F>, P: Clone + Default + Serialize + DeserializeOwned + ArgminSub<O::Param, O::Param> + ArgminDot<O::Param, O::Float> + ArgminScaledAdd<O::Param, O::Float, O::Param> + ArgminAdd<O::Param, O::Param> + ArgminMul<F, O::Param> + ArgminNorm<O::Float>, O::Hessian: Default, L: Clone + ArgminLineSearch<O::Param, O::Float> + Solver<OpWrapper<O>>, B: ArgminNLCGBetaUpdate<O::Param, O::Float>, F: ArgminFloat,

const NAME: &'static str = "Nonlinear Conjugate Gradient"

Name of the solver

fn init( &mut self, op: &mut OpWrapper<O>, state: &IterState<O>, ) -> Result<Option<ArgminIterData<O>>, Error>

Initializes the algorithm

fn next_iter( &mut self, op: &mut OpWrapper<O>, state: &IterState<O>, ) -> Result<ArgminIterData<O>, Error>

Computes one iteration of the algorithm.

fn terminate_internal(&mut self, state: &IterState<O>) -> TerminationReason

Checks whether basic termination reasons apply.

fn terminate(&mut self, _state: &IterState<O>) -> TerminationReason

Checks whether the algorithm must be terminated