Struct GoldenSectionSearch

pub struct GoldenSectionSearch<F> { /* private fields */ }

Golden-section search

The golden-section search is a technique for finding an extremum (minimum or maximum) of a function inside a specified interval.

The method operates by successively narrowing the range of values on the specified interval, which makes it relatively slow, but very robust. The technique derives its name from the fact that the algorithm maintains the function values for four points whose three interval widths are in the ratio 2-φ:2φ-3:2-φ where φ is the golden ratio. These ratios are maintained for each iteration and are maximally efficient.

The min_bound and max_bound arguments define values that bracket the expected minimum. The init_estimate argument is the initial estimate of the minimum that is required to be larger than min_bound and smaller than max_bound.

References:

Wikipedia

Implementations

impl<F> GoldenSectionSearch<F>

where F: ArgminFloat,

pub fn new(min_bound: F, max_bound: F) -> Self

Constructor

pub fn tolerance(self, tol: F) -> Self

Set tolerance

Trait Implementations

impl<F: Clone> Clone for GoldenSectionSearch<F>

fn clone(&self) -> GoldenSectionSearch<F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'de, F> Deserialize<'de> for GoldenSectionSearch<F>

where 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<F> Serialize for GoldenSectionSearch<F>

where 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, F> Solver<O> for GoldenSectionSearch<F>

where O: ArgminOp<Output = F, Param = F, Float = F>, F: ArgminFloat,

const NAME: &'static str = "Golden-section search"

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