``pub struct NelderMead<P, F> { /* private fields */ }``
Expand description

The Nelder-Mead method a heuristic search method for nonlinear optimization problems which does not require derivatives.

The method is based on simplices which consist of n+1 vertices for an optimization problem with n dimensions. The function to be optimized is evaluated at all vertices. Based on these cost function values the behavior of the cost function is extrapolated in order to find the next point to be evaluated.

The following actions are possible:

1. Reflection (Parameter `alpha`, defaults to `1`, configurable via `with_alpha`)
2. Expansion (Parameter `gamma`, defaults to `2`, configurable via `with_gamma`)
3. Contraction inside or outside (Parameter `rho`, defaults to `0.5`, configurable via `with_rho`)
4. Shrink (Parameter `sigma`, defaults to `0.5`, configurable via `with_sigma`)

### Requirements on the optimization problem

The optimization problem is required to implement `CostFunction`.

## Implementations§

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### impl<P, F> NelderMead<P, F>where P: Clone + ArgminAdd<P, P> + ArgminSub<P, P> + ArgminMul<F, P>, F: ArgminFloat,

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#### pub fn new(params: Vec<P>) -> Self

Construct a new instance of `NelderMead`

Takes a vector of parameter vectors. The number of parameter vectors must be `n + 1` where `n` is the number of optimization parameters.

##### Example
``let nm: NelderMead<Vec<f64>, f64> = NelderMead::new(vec_of_parameters);``
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#### pub fn with_sd_tolerance(self, tol: F) -> Result<Self, Error>

Set sample standard deviation tolerance

Must be non-negative and defaults to `EPSILON`.

##### Example
``````let nm: NelderMead<Vec<f64>, f64> =
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#### pub fn with_alpha(self, alpha: F) -> Result<Self, Error>

Set alpha parameter for reflection

Must be larger than 0 and defaults to 1.

##### Example
``````let nm: NelderMead<Vec<f64>, f64> =
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#### pub fn with_gamma(self, gamma: F) -> Result<Self, Error>

Set gamma for expansion

Must be larger than 1 and defaults to 2.

##### Example
``````let nm: NelderMead<Vec<f64>, f64> =
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#### pub fn with_rho(self, rho: F) -> Result<Self, Error>

Set rho for contraction

Must be in (0, 0.5] and defaults to 0.5.

##### Example
``````let nm: NelderMead<Vec<f64>, f64> =
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#### pub fn with_sigma(self, sigma: F) -> Result<Self, Error>

Set sigma for shrinking

Must be in (0, 1] and defaults to 0.5.

##### Example
``````let nm: NelderMead<Vec<f64>, f64> =

## Trait Implementations§

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### impl<P: Clone, F: Clone> Clone for NelderMead<P, F>

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

Returns a copy of the value. Read more
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#### fn clone_from(&mut self, source: &Self)

Performs copy-assignment from `source`. Read more
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### impl<'de, P, F> Deserialize<'de> for NelderMead<P, F>where P: Deserialize<'de>, F: Deserialize<'de>,

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#### fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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### impl<P, F> Serialize for NelderMead<P, F>where P: Serialize, F: Serialize,

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

Serialize this value into the given Serde serializer. Read more
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### impl<O, P, F> Solver<O, IterState<P, (), (), (), F>> for NelderMead<P, F>where O: CostFunction<Param = P, Output = F>, P: Clone + SerializeAlias + ArgminSub<P, P> + ArgminAdd<P, P> + ArgminMul<F, P>, F: ArgminFloat + Sum<F>,

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#### const NAME: &'static str = "Nelder-Mead method"

Name of the solver. Mainly used in Observers.
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#### fn next_iter( &mut self, problem: &mut Problem<O>, state: IterState<P, (), (), (), F> ) -> Result<(IterState<P, (), (), (), 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.
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#### fn terminate( &mut self, _state: &IterState<P, (), (), (), F> ) -> TerminationStatus

Used to implement stopping criteria, in particular criteria which are not covered by (`terminate_internal`. Read more
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#### fn terminate_internal(&mut self, state: &I) -> TerminationStatus

Checks whether basic termination reasons apply. Read more

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## Blanket Implementations§

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### impl<T> Any for Twhere T: 'static + ?Sized,

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#### fn type_id(&self) -> TypeId

Gets the `TypeId` of `self`. Read more
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### impl<T> Borrow<T> for Twhere T: ?Sized,

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#### fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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### impl<T> BorrowMut<T> for Twhere T: ?Sized,

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#### fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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### impl<T> From<T> for T

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#### fn from(t: T) -> T

Returns the argument unchanged.

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### impl<T, U> Into<U> for Twhere U: From<T>,

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#### fn into(self) -> U

Calls `U::from(self)`.

That is, this conversion is whatever the implementation of `From<T> for U` chooses to do.

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### impl<T> ToOwned for Twhere T: Clone,

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#### type Owned = T

The resulting type after obtaining ownership.
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#### fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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#### fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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### impl<T, U> TryFrom<U> for Twhere U: Into<T>,

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#### type Error = Infallible

The type returned in the event of a conversion error.
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#### fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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### impl<T, U> TryInto<U> for Twhere U: TryFrom<T>,

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#### type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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#### fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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