basin 2.0.0

Numerical optimization in pure Rust, with pluggable linear-algebra backends and WASM support.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106

//! Scalar solvers use the same checked records and lifecycle as vector solvers.

use basin::{
    Brent, BrentDerivative, CostFunction, EvalCounts, Executor,
    FirstOrderState, GoldenSection, Gradient, GradientState, PointState,
    Solver, State,
};
use std::convert::Infallible;

struct Quadratic;

impl basin::ProblemConstraints for Quadratic {
    type Constraints = basin::Constraints<basin::BoxBounds<f64>>;
    fn constraint_set(
        &self,
    ) -> <Self::Constraints as basin::ConstraintDescription>::Borrowed<'_> {
        basin::Constraints::new()
            .with_bounds(basin::BoxBounds::new(Some(&-1.0), Some(&2.0)))
    }
}
impl CostFunction for Quadratic {
    type Param = f64;
    type Output = f64;
    type Error = Infallible;

    fn cost(&self, x: &f64) -> Result<f64, Infallible> {
        Ok((x - 0.25).powi(2))
    }
}

impl Gradient for Quadratic {
    type Gradient = f64;

    fn gradient(&self, x: &f64) -> Result<f64, Infallible> {
        Ok(2.0 * (x - 0.25))
    }
}

fn check_point_solver<So>(solver: So)
where
    So: Solver<Quadratic, PointState<f64>, Error: std::fmt::Debug>,
{
    let initial = Executor::new(Quadratic, solver, PointState::new(0.5))
        .require_evaluated_state()
        .max_iter(0)
        .run_with_solver()
        .unwrap();
    assert_eq!(initial.state.iter(), 0);
    assert!(initial.state.current().is_some());
    assert_eq!(initial.state.counts(), &initial.counts);
    assert_eq!(initial.state.cost_evals(), initial.counts.cost_evals);

    let resumed =
        Executor::resume_from_checkpoint(Quadratic, initial.into_checkpoint())
            .require_evaluated_state()
            .max_iter(4)
            .run_with_solver()
            .unwrap();
    assert_eq!(resumed.state.iter(), 4);
    assert_eq!(resumed.state.counts(), &resumed.counts);
    let (x, cost) = resumed.state.current().unwrap();
    assert_eq!(cost, Quadratic.cost(x).unwrap());
    let (best, best_cost) = resumed.state.best().unwrap();
    assert_eq!(best_cost, Quadratic.cost(best).unwrap());

    let fresh = Executor::new(Quadratic, resumed.solver, resumed.state)
        .require_evaluated_state()
        .max_iter(0)
        .run_with_solver()
        .unwrap();
    assert_eq!(fresh.state.iter(), 0);
    assert!(fresh.counts.cost_evals > 0);
    assert_eq!(fresh.state.counts(), &fresh.counts);
    assert_eq!(fresh.state.best_iter(), 0);
}

#[test]
fn cost_only_scalar_solvers_share_point_progress() {
    check_point_solver(Brent::new());
    check_point_solver(GoldenSection::new());
}

#[test]
fn derivative_brent_publishes_matching_scalar_gradient() {
    let result = Executor::new(
        Quadratic,
        BrentDerivative::new(),
        FirstOrderState::new(0.5),
    )
    .require_evaluated_state()
    .max_iter(10)
    .run_with_solver()
    .unwrap();
    let (x, cost, gradient) = result.state.current().unwrap();
    assert_eq!(cost, Quadratic.cost(x).unwrap());
    assert_eq!(*gradient, Quadratic.gradient(x).unwrap());
    assert_eq!(result.state.gradient(), Some(gradient));
    assert_eq!(result.state.counts(), &result.counts);
    assert_eq!(result.state.gradient_evals(), result.counts.gradient_evals);
    assert_eq!(result.counts, {
        let mut counts = EvalCounts::default();
        counts.cost_evals = result.counts.cost_evals;
        counts.gradient_evals = result.counts.cost_evals;
        counts
    });
}