extern crate intel_mkl_src;

use approx::assert_abs_diff_eq;
use kickscore as ks;

#[test]
fn kickscore_basic() {
    let mut model = ks::BinaryModel::new(ks::BinaryModelObservation::Probit);

    let k_spike = ks::kernel::Constant::new(0.5);

    let k_tom = ks::kernel::Exponential::new(1.0, 1.0);

    let k_jerry: Vec<Box<dyn ks::Kernel>> = vec![
        Box::new(ks::kernel::Constant::new(1.0)),
        Box::new(ks::kernel::Matern52::new(0.5, 1.0)),
    ];

    model.add_item("Spike", Box::new(k_spike));
    model.add_item("Tom", Box::new(k_tom));
    model.add_item("Jerry", Box::new(k_jerry));

    model.observe(&["Jerry"], &["Tom"], 0.0);
    model.observe(&["Jerry"], &["Tom"], 0.9);

    model.observe(&["Tom"], &["Spike"], 1.7);
    model.observe(&["Tom"], &["Jerry"], 2.1);

    model.observe(&["Jerry"], &["Tom"], 3.0);
    model.observe(&["Jerry"], &["Tom", "Spike"], 3.5);

    model.fit();

    let (p_win, _p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], 4.0);

    assert_abs_diff_eq!(p_win, 0.7299975928462964, epsilon = f64::EPSILON);

    let (p_win, _p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], 2.0);

    assert_abs_diff_eq!(p_win, 0.4455095363120037, epsilon = f64::EPSILON);

    let (p_win, _p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], -1.0);

    assert_abs_diff_eq!(p_win, 0.903756079972532, epsilon = f64::EPSILON);
}