spsa 0.1.0

Simultaneous perturbation stochastic approximation
Documentation 
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use approx::assert_relative_eq;
use spsa::{Optimizer, Options, Target, TargetExt};
use rand::{Rng, SeedableRng, thread_rng};
use rand::rngs::StdRng;

#[test]
fn simple_fn() {
    pub struct SimpleFunction;

    impl Target for SimpleFunction {
        fn evaluate(&mut self, data: &[f64]) -> f64 {
            let x = data[0];
            let y = data[1];
            1.0 - (x + 1.0) * (x + 1.0) - (y - 1.0) * (y - 1.0)
        }
    }

    let mut optimizer = Optimizer::new();
    let mut input = [0.0, 0.0];

    optimizer.optimize(SimpleFunction,&mut input, Options::default());

    assert_relative_eq!(input[0], -1.0, epsilon = 1e-6);
    assert_relative_eq!(input[1],  1.0, epsilon = 1e-6);
}

#[test]
fn noisy_fn() {
    pub struct NoisyFunction(StdRng);

    impl Target for NoisyFunction {
        fn evaluate(&mut self, data: &[f64]) -> f64 {
            let x = data[0];
            let y = data[1];

            1.0 - (x + 1.0) * (x + 1.0) - (y - 1.0) * (y - 1.0) + self.0.gen_range(-0.001..0.001)
        }
    }

    let mut optimizer = Optimizer::new();
    let mut input = [0.0, 0.0];

    optimizer.optimize(NoisyFunction(StdRng::from_rng(thread_rng()).unwrap()).oversample(2),&mut input, Options::default());

    assert_relative_eq!(input[0], -1.0, epsilon = 1e-3);
    assert_relative_eq!(input[1],  1.0, epsilon = 1e-3);
}