Fixed a bug, and added a custom solve function (using lapacke).

examples/abcdef.rs

@@ -0,0 +1,66 @@
+extern crate intel_mkl_src;
+
+use kickscore as ks;
+
+fn main() {
+    let mut model = ks::BinaryModel::new(ks::BinaryModelObservation::Probit);
+
+    for player in &["A", "B", "C", "D", "E", "F"] {
+        let kernel: 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(player, Box::new(kernel));
+    }
+
+    model.observe(&["A"], &["B"], 0.0);
+
+    model.fit();
+
+    for player in &["A", "B", "C", "D", "E", "F"] {
+        let (mu, sigma) = model.item_score(player, 1.25);
+
+        println!("{}: mu={} sigma={}", player, mu, sigma);
+    }
+
+    model.observe(&["C"], &["D"], 0.25);
+
+    model.fit();
+
+    for player in &["A", "B", "C", "D", "E", "F"] {
+        let (mu, sigma) = model.item_score(player, 1.25);
+
+        println!("{}: mu={} sigma={}", player, mu, sigma);
+    }
+
+    model.observe(&["E"], &["F"], 0.50);
+
+    model.fit();
+
+    for player in &["A", "B", "C", "D", "E", "F"] {
+        let (mu, sigma) = model.item_score(player, 1.25);
+
+        println!("{}: mu={} sigma={}", player, mu, sigma);
+    }
+
+    model.observe(&["B"], &["C"], 0.75);
+
+    model.fit();
+
+    for player in &["A", "B", "C", "D", "E", "F"] {
+        let (mu, sigma) = model.item_score(player, 1.25);
+
+        println!("{}: mu={} sigma={}", player, mu, sigma);
+    }
+
+    model.observe(&["D"], &["E"], 1.00);
+
+    model.fit();
+
+    for player in &["A", "B", "C", "D", "E", "F"] {
+        let (mu, sigma) = model.item_score(player, 1.25);
+
+        println!("{}: mu={} sigma={}", player, mu, sigma);
+    }
+}