Merge branch 'hotfix/0.16.1'

Cargo.toml

@@ -7,7 +7,7 @@ categories = ["algorithms"]
 repository = "https://github.com/lucidfrontier45/localsearch"
 license-file = "LICENSE"
 readme = "README.md"
-version = "0.16.0"
+version = "0.16.1"
 edition = "2021"
 
 # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html

examples/quadratic_model.rs

@@ -28,7 +28,6 @@ impl QuadraticModel {
 
     fn evaluate_solution(&self, solution: &SolutionType) -> NotNan<f64> {
         let score = (0..self.k)
-            .into_iter()
             .map(|i| (solution[i] - self.centers[i]).powf(2.0))
             .sum();
         NotNan::new(score).unwrap()

examples/tsp_model.rs

@@ -111,7 +111,6 @@ impl OptModel for TSPModel {
             .distance_matrix
             .keys()
             .copied()
-            .into_iter()
             .flat_map(|(i, j)| [i, j])
             .collect::<HashSet<_>>()
             .into_iter()
@@ -235,7 +234,6 @@ fn main() {
     let input_file = args.get(1).unwrap();
     let coords = read_lines(input_file)
         .unwrap()
-        .into_iter()
         .map(|line| {
             let line = line.unwrap();
             let splt = line.split(' ').collect::<Vec<_>>();
@@ -363,7 +361,6 @@ fn main() {
     let opt_route_file = args.get(2).unwrap();
     let opt_solution = read_lines(opt_route_file)
         .unwrap()
-        .into_iter()
         .map(|line| {
             let i: usize = line.unwrap().parse().unwrap();
             i

src/optim/simulated_annealing.rs

@@ -44,6 +44,7 @@ impl SimulatedAnnealingOptimizer {
 }
 
 impl SimulatedAnnealingOptimizer {
+    #[allow(clippy::too_many_arguments)]
     /// Start optimization with given temperature range
     ///
     /// - `model` : the model to optimize

src/optim/tabu_search.rs

@@ -83,6 +83,7 @@ where
     M: OptModel,
     T: TabuList<M>,
 {
+    #[allow(clippy::too_many_arguments)]
     /// Start optimization
     ///
     /// - `model` : the model to optimize

src/tests.rs

@@ -24,7 +24,6 @@ impl QuadraticModel {
 
     fn evaluate_solution(&self, solution: &SolutionType) -> ScoreType {
         let score = (0..self.k)
-            .into_iter()
             .map(|i| (solution[i] - self.centers[i]).powf(2.0))
             .sum();
         NotNan::new(score).unwrap()