Struct argmin::solver::conjugategradient::ConjugateGradient

pub struct ConjugateGradient<P, F> { /* private fields */ }

Conjugate Gradient method

A solver for systems of linear equations with a symmetric and positive-definite matrix.

Solves systems of the form A * x = b where x and b are vectors and A is a symmetric and positive-definite matrix.

Requires an initial parameter vector.

Requirements on the optimization problem

The optimization problem is required to implement Operator.

Reference

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

Implementations

impl<P, F> ConjugateGradient<P, F>

where F: ArgminFloat,

pub fn new(b: P) -> Self

Constructs an instance of ConjugateGradient

Takes b, the right hand side of A * x = b as input.

Example

let cg: ConjugateGradient<_, f64> = ConjugateGradient::new(b);

pub fn get_prev_p(&self) -> Result<&P, Error>

Return the previous search direction (Needed by NewtonCG)

Returns an error if the field p_prev is not initialized.

Example

let p_prev: Result<_, _> = cg.get_prev_p();

Trait Implementations

impl<P: Clone, F: Clone> Clone for ConjugateGradient<P, F>

fn clone(&self) -> ConjugateGradient<P, F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'de, P, F> Deserialize<'de> for ConjugateGradient<P, F>

where P: 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, F> Serialize for ConjugateGradient<P, F>

where P: 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<P, O, R, F> Solver<O, IterState<P, (), (), (), R, F>> for ConjugateGradient<P, F>

where O: Operator<Param = P, Output = P>, P: Clone + ArgminDot<P, F> + ArgminSub<P, R> + ArgminScaledAdd<P, F, P> + ArgminConj, R: ArgminMul<F, R> + ArgminMul<F, P> + ArgminConj + ArgminDot<R, F> + ArgminScaledAdd<P, F, R>, F: ArgminFloat + ArgminL2Norm<F>,

fn next_iter( &mut self, problem: &mut Problem<O>, state: IterState<P, (), (), (), R, F> ) -> Result<(IterState<P, (), (), (), R, F>, Option<KV>), Error>

Perform one iteration of CG algorithm

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

Name of the solver. Mainly used in Observers.

fn init( &mut self, problem: &mut Problem<O>, state: IterState<P, (), (), (), R, F> ) -> Result<(IterState<P, (), (), (), R, F>, Option<KV>), Error>

Initializes the algorithm.

fn terminate_internal(&mut self, state: &I) -> TerminationStatus

Checks whether basic termination reasons apply.

fn terminate(&mut self, _state: &I) -> TerminationStatus

Used to implement stopping criteria, in particular criteria which are not covered by (terminate_internal.