Struct argmin::solver::goldensectionsearch::GoldenSectionSearch [−][src]
pub struct GoldenSectionSearch<F> { /* fields omitted */ }
Expand description
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:
Implementations
Trait Implementations
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
impl<O, F> Solver<O> for GoldenSectionSearch<F> where
O: ArgminOp<Output = F, Param = F, Float = F>,
F: ArgminFloat,
impl<O, F> Solver<O> for GoldenSectionSearch<F> where
O: ArgminOp<Output = F, Param = F, Float = F>,
F: ArgminFloat,
Auto Trait Implementations
impl<F> RefUnwindSafe for GoldenSectionSearch<F> where
F: RefUnwindSafe,
impl<F> Send for GoldenSectionSearch<F> where
F: Send,
impl<F> Sync for GoldenSectionSearch<F> where
F: Sync,
impl<F> Unpin for GoldenSectionSearch<F> where
F: Unpin,
impl<F> UnwindSafe for GoldenSectionSearch<F> where
F: UnwindSafe,
Blanket Implementations
Mutably borrows from an owned value. Read more