#![cfg(feature = "ndarray")]
use basin::problems::BoothBoxed;
use basin::{
Backtracking, BasicState, Executor, ProjectedGradientDescent, ProjectedGradientTolerance,
TerminationReason,
};
use ndarray::Array1;
#[test]
fn slack_bounds_recover_unconstrained_minimum() {
let lower = Array1::from(vec![-5.0, -5.0]);
let upper = Array1::from(vec![5.0, 5.0]);
let problem = BoothBoxed::<Array1<f64>>::new(lower, upper);
let initial = Array1::from(vec![0.0, 0.0]);
let result = Executor::new(
problem,
ProjectedGradientDescent::with_line_search(Backtracking::new()),
BasicState::new(initial),
)
.max_iter(2000)
.run();
assert!(
(result.param()[0] - 1.0).abs() < 1e-4,
"x[0] = {}",
result.param()[0]
);
assert!(
(result.param()[1] - 3.0).abs() < 1e-4,
"x[1] = {}",
result.param()[1]
);
}
#[test]
fn tight_bounds_converge_to_box_corner() {
let lower = Array1::from(vec![-1.0, -1.0]);
let upper = Array1::from(vec![1.0, 1.0]);
let problem = BoothBoxed::<Array1<f64>>::new(lower, upper);
let initial = Array1::from(vec![0.0, 0.0]);
let result = Executor::new(
problem,
ProjectedGradientDescent::with_line_search(Backtracking::new()),
BasicState::new(initial),
)
.max_iter(2000)
.run();
assert!(
(result.param()[0] - 1.0).abs() < 1e-6,
"x[0] = {}",
result.param()[0]
);
assert!(
(result.param()[1] - 1.0).abs() < 1e-6,
"x[1] = {}",
result.param()[1]
);
}
#[test]
fn infeasible_initial_param_is_projected_at_init() {
let lower = Array1::from(vec![-1.0, -1.0]);
let upper = Array1::from(vec![1.0, 1.0]);
let problem = BoothBoxed::<Array1<f64>>::new(lower, upper);
let initial = Array1::from(vec![10.0, 10.0]);
let result = Executor::new(
problem,
ProjectedGradientDescent::new(0.01),
BasicState::new(initial),
)
.max_iter(0)
.run();
assert_eq!(result.reason, TerminationReason::MaxIter);
assert_eq!(result.param()[0], 1.0);
assert_eq!(result.param()[1], 1.0);
}
#[test]
fn projected_gradient_tolerance_triggers_at_corner_minimum() {
let lower = Array1::from(vec![-1.0, -1.0]);
let upper = Array1::from(vec![1.0, 1.0]);
let problem = BoothBoxed::<Array1<f64>>::new(lower.clone(), upper.clone());
let initial = Array1::from(vec![0.0, 0.0]);
let result = Executor::new(
problem,
ProjectedGradientDescent::with_line_search(Backtracking::new()),
BasicState::new(initial),
)
.max_iter(2000)
.terminate_on(ProjectedGradientTolerance::new(lower, upper, 1e-7))
.run();
assert_eq!(result.reason, TerminationReason::ProjectedGradientTolerance);
}