Struct BacktrackingLineSearch 

pub struct BacktrackingLineSearch<P, G, L, F> { /* private fields */ }

Backtracking line search

The Backtracking line search is a method which finds a step length from a given point along a given direction, such that this step length obeys the Armijo (sufficient decrease) condition.

Requirements on the optimization problem

The optimization problem is required to implement CostFunction and Gradient.

References

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

Wikipedia: https://en.wikipedia.org/wiki/Backtracking_line_search

Implementations

impl<P, G, L, F> BacktrackingLineSearch<P, G, L, F>

where F: ArgminFloat,

pub fn new(condition: L) -> Self

Construct a new instance of BacktrackingLineSearch

Example

let backtracking: BacktrackingLineSearch<Vec<f64>, Vec<f64>, _, f64> =
    BacktrackingLineSearch::new(ArmijoCondition::new(0.0001f64));

pub fn rho(self, rho: F) -> Result<Self, Error>

Set contraction factor rho

This factor must be in (0, 1).

Example

let backtracking = backtracking.rho(0.5)?;

Trait Implementations

impl<P: Clone, G: Clone, L: Clone, F: Clone> Clone for BacktrackingLineSearch<P, G, L, F>

fn clone(&self) -> BacktrackingLineSearch<P, G, L, F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<P: Debug, G: Debug, L: Debug, F: Debug> Debug for BacktrackingLineSearch<P, G, L, F>

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

Formats the value using the given formatter.

impl<'de, P, G, L, F> Deserialize<'de> for BacktrackingLineSearch<P, G, L, F>

where P: Deserialize<'de>, G: Deserialize<'de>, L: 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, G, L, F> LineSearch<G, F> for BacktrackingLineSearch<P, G, L, F>

where F: ArgminFloat,

fn search_direction(&mut self, search_direction: G)

Set search direction

fn initial_step_length(&mut self, alpha: F) -> Result<(), Error>

Set initial step length

impl<P: PartialEq, G: PartialEq, L: PartialEq, F: PartialEq> PartialEq for BacktrackingLineSearch<P, G, L, F>

fn eq(&self, other: &BacktrackingLineSearch<P, G, L, F>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<P, G, L, F> Serialize for BacktrackingLineSearch<P, G, L, F>

where P: Serialize, G: Serialize, L: 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, G, L, F> Solver<O, IterState<P, G, (), (), (), F>> for BacktrackingLineSearch<P, G, L, F>

where P: Clone + ArgminScaledAdd<G, F, P>, G: ArgminScaledAdd<G, F, G>, O: CostFunction<Param = P, Output = F> + Gradient<Param = P, Gradient = G>, L: LineSearchCondition<G, G, F>, F: ArgminFloat,

fn name(&self) -> &str

Name of the solver. Mainly used in Observers.

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

Initializes the algorithm.

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

Computes a single iteration of the algorithm and has access to the optimization problem definition and the internal state of the solver. Returns an updated state and optionally a KV which holds key-value pairs used in Observers.

fn terminate( &mut self, state: &IterState<P, G, (), (), (), F>, ) -> TerminationStatus

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

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

Checks whether basic termination reasons apply.

impl<P: Eq, G: Eq, L: Eq, F: Eq> Eq for BacktrackingLineSearch<P, G, L, F>

impl<P, G, L, F> StructuralPartialEq for BacktrackingLineSearch<P, G, L, F>