use std;
use ndarray::{Array1, Array2};
use ndarray_linalg::Inverse;
use errors::*;
use prelude::*;
use problem::ArgminProblem;
use result::ArgminResult;
use termination::TerminationReason;
pub struct Newton<'a> {
gamma: f64,
max_iters: u64,
state: Option<NewtonState<'a>>,
}
struct NewtonState<'a> {
problem: &'a ArgminProblem<'a, Array1<f64>, f64, Array2<f64>>,
param: Array1<f64>,
iter: u64,
}
impl<'a> NewtonState<'a> {
pub fn new(
problem: &'a ArgminProblem<'a, Array1<f64>, f64, Array2<f64>>,
param: Array1<f64>,
) -> Self {
NewtonState {
problem: problem,
param: param,
iter: 0_u64,
}
}
}
impl<'a> Newton<'a> {
pub fn new() -> Self {
Newton {
gamma: 1.0,
max_iters: std::u64::MAX,
state: None,
}
}
pub fn max_iters(&mut self, max_iters: u64) -> &mut Self {
self.max_iters = max_iters;
self
}
}
impl<'a> ArgminSolver<'a> for Newton<'a> {
type Parameter = Array1<f64>;
type CostValue = f64;
type Hessian = Array2<f64>;
type StartingPoints = Self::Parameter;
type ProblemDefinition = &'a ArgminProblem<'a, Self::Parameter, Self::CostValue, Self::Hessian>;
fn init(
&mut self,
problem: Self::ProblemDefinition,
init_param: &Self::StartingPoints,
) -> Result<()> {
self.state = Some(NewtonState::new(problem, init_param.clone()));
Ok(())
}
fn next_iter(&mut self) -> Result<ArgminResult<Self::Parameter, Self::CostValue>> {
let mut state = self.state.take().unwrap();
let g = (state.problem.gradient.unwrap())(&state.param);
let h_inv = (state.problem.hessian.unwrap())(&state.param).inv()?;
state.param = state.param - self.gamma * h_inv.dot(&g);
state.iter += 1;
let mut out = ArgminResult::new(state.param.clone(), std::f64::NAN, state.iter);
self.state = Some(state);
out.set_termination_reason(self.terminate());
Ok(out)
}
make_terminate!(self,
self.state.as_ref().unwrap().iter >= self.max_iters, TerminationReason::MaxItersReached;
);
make_run!(
Self::ProblemDefinition,
Self::StartingPoints,
Self::Parameter,
Self::CostValue
);
}
impl<'a> Default for Newton<'a> {
fn default() -> Self {
Self::new()
}
}