Struct argmin::solver::newton::newton_method::Newton

pub struct Newton { /* fields omitted */ }

Newton's method iteratively finds the stationary points of a function f by using a second order approximation of f at the current point.

Example

References:

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

Methods

impl Newton

pub fn new() -> Self

Constructor

pub fn set_gamma(self, gamma: f64) -> Result<Self, Error>

set gamma

Trait Implementations

impl Default for Newton

fn default() -> Newton

Returns the "default value" for a type.

impl Serialize for Newton

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

Serialize this value into the given Serde serializer.

impl<O> Solver<O> for Newton where
    O: ArgminOp,
    O::Param: ArgminScaledSub<O::Param, f64, O::Param>,
    O::Hessian: ArgminInv<O::Hessian> + ArgminDot<O::Param, O::Param>, 

const NAME: &'static str

fn next_iter(
    &mut self,
    op: &mut OpWrapper<O>,
    state: &IterState<O>
) -> Result<ArgminIterData<O>, Error>

Computes one iteration of the algorithm.

fn init(
    &mut self,
    _op: &mut OpWrapper<O>,
    _state: &IterState<O>
) -> Result<Option<ArgminIterData<O>>, Error>

Initializes 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

impl<'de> Deserialize<'de> for Newton

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

Deserialize this value from the given Serde deserializer.