Small clean up

examples/abcdef.rs

@@ -5,11 +5,11 @@ use kickscore as ks;
 fn main() {
     let mut model = ks::model::Binary::probit();
 
-    for player in &["A", "B", "C", "D", "E", "F"] {
-        let kernel: [Box<dyn ks::Kernel>; 2] = [
-            Box::new(ks::kernel::Constant::new(1.0)),
-            Box::new(ks::kernel::Matern52::new(0.5, 1.0)),
-        ];
+    for player in ["A", "B", "C", "D", "E", "F"] {
+        let kernel = (
+            ks::kernel::Constant::new(1.0),
+            ks::kernel::Matern52::new(0.5, 1.0),
+        );
 
         model.add_item(player, kernel);
     }
@@ -18,7 +18,7 @@ fn main() {
 
     model.fit();
 
-    for player in &["A", "B", "C", "D", "E", "F"] {
+    for player in ["A", "B", "C", "D", "E", "F"] {
         let (mu, sigma) = model.item_score(player, 1.25);
 
         println!("{}: mu={} sigma={}", player, mu, sigma);
@@ -28,7 +28,7 @@ fn main() {
 
     model.fit();
 
-    for player in &["A", "B", "C", "D", "E", "F"] {
+    for player in ["A", "B", "C", "D", "E", "F"] {
         let (mu, sigma) = model.item_score(player, 1.25);
 
         println!("{}: mu={} sigma={}", player, mu, sigma);
@@ -38,7 +38,7 @@ fn main() {
 
     model.fit();
 
-    for player in &["A", "B", "C", "D", "E", "F"] {
+    for player in ["A", "B", "C", "D", "E", "F"] {
         let (mu, sigma) = model.item_score(player, 1.25);
 
         println!("{}: mu={} sigma={}", player, mu, sigma);
@@ -48,7 +48,7 @@ fn main() {
 
     model.fit();
 
-    for player in &["A", "B", "C", "D", "E", "F"] {
+    for player in ["A", "B", "C", "D", "E", "F"] {
         let (mu, sigma) = model.item_score(player, 1.25);
 
         println!("{}: mu={} sigma={}", player, mu, sigma);
@@ -58,7 +58,7 @@ fn main() {
 
     model.fit();
 
-    for player in &["A", "B", "C", "D", "E", "F"] {
+    for player in ["A", "B", "C", "D", "E", "F"] {
         let (mu, sigma) = model.item_score(player, 1.25);
 
         println!("{}: mu={} sigma={}", player, mu, sigma);

src/fitter/recursive.rs

@@ -7,6 +7,7 @@ use crate::kernel::Kernel;
 
 use super::Fitter;
 
+#[derive(Clone)]
 pub struct Recursive<K> {
     ts_new: Vec<f64>,
     kernel: K,
@@ -232,7 +233,7 @@ impl<K: Kernel> Fitter for Recursive<K> {
             self.ts
                 .iter()
                 .position(|tc| t <= tc)
-                .unwrap_or_else(|| self.ts.len())
+                .unwrap_or(self.ts.len())
         });
 
         for (i, nxt) in locations.into_iter().enumerate() {
@@ -415,7 +416,7 @@ mod tests {
     }
 
     fn data_loglik() -> f64 {
-        -17.357282245711051
+        -17.35728224571105
     }
 
     fn data_ts_pred() -> &'static [f64] {

src/storage.rs

@@ -3,7 +3,7 @@ use std::collections::HashMap;
 use crate::item::Item;
 
 /*
-pub trait Storage {
+pub trait Backend {
     type Key;
 
     type IterKeys: