Struct argmin::solver::linesearch::BacktrackingLineSearch
source · pub struct BacktrackingLineSearch<P, G, L, F> { /* private fields */ }
Expand description
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§
source§impl<P, G, L, F> BacktrackingLineSearch<P, G, L, F>where
F: ArgminFloat,
impl<P, G, L, F> BacktrackingLineSearch<P, G, L, F>where F: ArgminFloat,
Trait Implementations§
source§impl<P: Clone, G: Clone, L: Clone, F: Clone> Clone for BacktrackingLineSearch<P, G, L, F>
impl<P: Clone, G: Clone, L: Clone, F: Clone> Clone for BacktrackingLineSearch<P, G, L, F>
source§fn clone(&self) -> BacktrackingLineSearch<P, G, L, F>
fn clone(&self) -> BacktrackingLineSearch<P, G, L, F>
Returns a copy of the value. Read more
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source
. Read moresource§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>,
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>,
source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where __D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
source§impl<P, G, L, F> LineSearch<P, F> for BacktrackingLineSearch<P, G, L, F>where
F: ArgminFloat,
impl<P, G, L, F> LineSearch<P, F> for BacktrackingLineSearch<P, G, L, F>where F: ArgminFloat,
source§fn search_direction(&mut self, search_direction: P)
fn search_direction(&mut self, search_direction: P)
Set search direction
source§impl<P: PartialEq, G: PartialEq, L: PartialEq, F: PartialEq> PartialEq<BacktrackingLineSearch<P, G, L, F>> for BacktrackingLineSearch<P, G, L, F>
impl<P: PartialEq, G: PartialEq, L: PartialEq, F: PartialEq> PartialEq<BacktrackingLineSearch<P, G, L, F>> for BacktrackingLineSearch<P, G, L, F>
source§fn eq(&self, other: &BacktrackingLineSearch<P, G, L, F>) -> bool
fn eq(&self, other: &BacktrackingLineSearch<P, G, L, F>) -> bool
This method tests for
self
and other
values to be equal, and is used
by ==
.source§impl<P, G, L, F> Serialize for BacktrackingLineSearch<P, G, L, F>where
P: Serialize,
G: Serialize,
L: Serialize,
F: Serialize,
impl<P, G, L, F> Serialize for BacktrackingLineSearch<P, G, L, F>where P: Serialize, G: Serialize, L: Serialize, F: Serialize,
source§impl<O, P, G, L, F> Solver<O, IterState<P, G, (), (), F>> for BacktrackingLineSearch<P, G, L, F>where
P: Clone + SerializeAlias + ArgminScaledAdd<P, F, P>,
G: SerializeAlias + ArgminScaledAdd<P, F, P>,
O: CostFunction<Param = P, Output = F> + Gradient<Param = P, Gradient = G>,
L: LineSearchCondition<P, G, F> + SerializeAlias,
F: ArgminFloat,
impl<O, P, G, L, F> Solver<O, IterState<P, G, (), (), F>> for BacktrackingLineSearch<P, G, L, F>where P: Clone + SerializeAlias + ArgminScaledAdd<P, F, P>, G: SerializeAlias + ArgminScaledAdd<P, F, P>, O: CostFunction<Param = P, Output = F> + Gradient<Param = P, Gradient = G>, L: LineSearchCondition<P, G, F> + SerializeAlias, F: ArgminFloat,
source§const NAME: &'static str = "Backtracking line search"
const NAME: &'static str = "Backtracking line search"
Name of the solver. Mainly used in Observers.
source§fn init(
&mut self,
problem: &mut Problem<O>,
state: IterState<P, G, (), (), F>
) -> Result<(IterState<P, G, (), (), F>, Option<KV>), Error>
fn init( &mut self, problem: &mut Problem<O>, state: IterState<P, G, (), (), F> ) -> Result<(IterState<P, G, (), (), F>, Option<KV>), Error>
Initializes the algorithm. Read more
source§fn next_iter(
&mut self,
problem: &mut Problem<O>,
state: IterState<P, G, (), (), F>
) -> Result<(IterState<P, G, (), (), F>, Option<KV>), Error>
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.source§fn terminate(&mut self, state: &IterState<P, G, (), (), F>) -> TerminationStatus
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
. Read moresource§fn terminate_internal(&mut self, state: &I) -> TerminationStatus
fn terminate_internal(&mut self, state: &I) -> TerminationStatus
Checks whether basic termination reasons apply. Read more