46 lines
1.3 KiB
Rust
46 lines
1.3 KiB
Rust
extern crate intel_mkl_src;
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use approx::assert_abs_diff_eq;
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use kickscore as ks;
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#[test]
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fn kickscore_basic() {
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let mut model = ks::BinaryModel::new(ks::BinaryModelObservation::Probit);
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let k_spike = ks::kernel::Constant::new(0.5);
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let k_tom = ks::kernel::Exponential::new(1.0, 1.0);
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let k_jerry: Vec<Box<dyn ks::Kernel>> = vec![
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Box::new(ks::kernel::Constant::new(1.0)),
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Box::new(ks::kernel::Matern52::new(0.5, 1.0)),
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];
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model.add_item("Spike", Box::new(k_spike));
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model.add_item("Tom", Box::new(k_tom));
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model.add_item("Jerry", Box::new(k_jerry));
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model.observe(&["Jerry"], &["Tom"], 0.0);
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model.observe(&["Jerry"], &["Tom"], 0.9);
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model.observe(&["Tom"], &["Spike"], 1.7);
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model.observe(&["Tom"], &["Jerry"], 2.1);
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model.observe(&["Jerry"], &["Tom"], 3.0);
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model.observe(&["Jerry"], &["Tom", "Spike"], 3.5);
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model.fit();
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let (p_win, _p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], 4.0);
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assert_abs_diff_eq!(p_win, 0.7299975928462964, epsilon = f64::EPSILON);
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let (p_win, _p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], 2.0);
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assert_abs_diff_eq!(p_win, 0.4455095363120037, epsilon = f64::EPSILON);
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let (p_win, _p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], -1.0);
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assert_abs_diff_eq!(p_win, 0.903756079972532, epsilon = f64::EPSILON);
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}
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