Fmt.

src/factor_graph.rs

@@ -101,7 +101,10 @@ impl PriorFactor {
     }
 
     pub fn start(&self, variable_arena: &mut VariableArena) {
-        variable_arena.get_mut(self.variable).unwrap().update_value(self.id, self.gaussian);
+        variable_arena
+            .get_mut(self.variable)
+            .unwrap()
+            .update_value(self.id, self.gaussian);
     }
 }
 
@@ -146,7 +149,10 @@ impl LikelihoodFactor {
 
         let gaussian = Gaussian::from_pi_tau(a * (x.pi() - fx.pi()), a * (x.tau() - fx.tau()));
 
-        variable_arena.get_mut(self.mean).unwrap().update_message(self.id, gaussian);
+        variable_arena
+            .get_mut(self.mean)
+            .unwrap()
+            .update_message(self.id, gaussian);
     }
 
     pub fn update_value(&self, variable_arena: &mut VariableArena) {
@@ -164,7 +170,10 @@ impl LikelihoodFactor {
 
         let gaussian = Gaussian::from_pi_tau(a * (y.pi() - fy.pi()), a * (y.tau() - fy.tau()));
 
-        variable_arena.get_mut(self.value).unwrap().update_message(self.id, gaussian);
+        variable_arena
+            .get_mut(self.value)
+            .unwrap()
+            .update_message(self.id, gaussian);
     }
 }
 
@@ -224,7 +233,10 @@ impl SumFactor {
 
         let gaussian = Gaussian::from_pi_tau(new_pi, new_tau);
 
-        variable_arena.get_mut(variable).unwrap().update_message(self.id, gaussian);
+        variable_arena
+            .get_mut(variable)
+            .unwrap()
+            .update_message(self.id, gaussian);
     }
 
     pub fn update_sum(&self, variable_arena: &mut VariableArena) {
@@ -372,6 +384,9 @@ impl TruncateFactor {
 
         let gaussian = Gaussian::from_pi_tau(c / m_w, (d + sqrt_c * v) / m_w);
 
-        variable_arena.get_mut(self.variable).unwrap().update_value(self.id, gaussian);
+        variable_arena
+            .get_mut(self.variable)
+            .unwrap()
+            .update_value(self.id, gaussian);
     }
 }

src/lib.rs

@@ -1,5 +1,5 @@
-extern crate statrs;
 extern crate noisy_float;
+extern crate statrs;
 
 mod factor_graph;
 mod gaussian;
@@ -28,7 +28,6 @@ const DRAW_PROBABILITY: f64 = 0.10;
 ///  A basis to check reliability of the result.
 const DELTA: f64 = 0.0001;
 
-
 fn draw_margin(p: f64, beta: f64, total_players: f64) -> f64 {
     math::icdf((p + 1.0) / 2.0) * total_players.sqrt() * beta
 }
@@ -78,7 +77,8 @@ pub fn rate(rating_groups: &[&[Gaussian]]) {
 
     for (i, rating) in flatten_ratings.iter().enumerate() {
         let variable = ss[i];
-        let gaussian = Gaussian::from_mu_sigma(rating.mu(), (rating.sigma().powi(2) + tau_sqr).sqrt());
+        let gaussian =
+            Gaussian::from_mu_sigma(rating.mu(), (rating.sigma().powi(2) + tau_sqr).sqrt());
 
         skill.push(PriorFactor::new(
             &mut variable_arena,

src/math.rs

@@ -1,4 +1,4 @@
-use statrs::distribution::{Normal, Univariate, Continuous};
+use statrs::distribution::{Continuous, Normal, Univariate};
 
 const S2PI: f64 = 2.50662827463100050242E0;
 
@@ -137,7 +137,6 @@ pub fn icdf(x: f64) -> f64 {
     ndtri(x)
 }
 
-
 #[cfg(test)]
 mod tests {
     use super::*;