Initial commit. Basic structure in place, need to implement logic.

examples/basic.rs

@@ -0,0 +1,56 @@
+use kickscore as ks;
+
+fn main() {
+    let mut model = ks::BinaryModel {};
+
+    // Spike's skill does not change over time.
+    let k_spike = ks::kernel::Constant::new(0.5);
+
+    // Tom's skill changes over time, with "jagged" (non-smooth) dynamics.
+    let k_tom = ks::kernel::Exponential::new(1.0, 1.0);
+
+    // Jerry's skill has a constant offset and smooth dynamics.
+    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)),
+    ];
+
+    // Now we are ready to add the items in the model.
+    model.add_item("Spike", k_spike);
+    model.add_item("Tom", k_tom);
+    model.add_item("Jerry", k_jerry);
+
+    // At first, Jerry beats Tom a couple of times.
+    model.observe(&["Jerry"], &["Tom"], 0.0);
+    model.observe(&["Jerry"], &["Tom"], 0.9);
+
+    // Then, Tom beats Spike, and then Jerry.
+    model.observe(&["Tom"], &["Spike"], 1.7);
+    model.observe(&["Tom"], &["Jerry"], 2.1);
+
+    // Finally, Jerry beats Tom, and then Tom + Spike.
+    model.observe(&["Jerry"], &["Tom"], 3.0);
+    model.observe(&["Jerry"], &["Tom", "Spike"], 3.5);
+
+    model.fit(true);
+
+    // We can predict a future outcome...
+    let (p_win, p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], 4.0);
+    println!(
+        "Chances that Jerry beats Tom at t = 4.0: {:.1}%",
+        100.0 * p_win
+    );
+
+    // ... or simulate what could have happened in the past.
+    let (p_win, p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], 2.0);
+    println!(
+        "Chances that Jerry beats Tom at t = 2.0: {:.1}%",
+        100.0 * p_win
+    );
+
+    let (p_win, p_los) = model.probabilities(&[&"Jerry"], &[&"Tom"], -1.0);
+    println!(
+        "Chances that Jerry beats Tom at t = -1.0: {:.1}%",
+        100.0 * p_win
+    );
+}