Better implementation of niches when m is 0.

Martin1887 · Jan 13, 2021 · f3e2ce5 · f3e2ce5
1 parent c5eefa2
commit f3e2ce5
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Showing 2 changed files with 17 additions and 26 deletions.
diff --git a/oxigen/Cargo.toml b/oxigen/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "oxigen"
-version = "2.1.1"
+version = "2.1.2"
 authors = ["Martin1887 <marcos.martin.pozo.delgado@gmail.com>"]
 description = "Fast, parallel, extensible and adaptable genetic algorithm library."
 repository = "https://github.com/Martin1887/oxigen"

diff --git a/oxigen/src/population_refitness.rs b/oxigen/src/population_refitness.rs
@@ -77,35 +77,26 @@ impl<T: PartialEq + Send + Sync, G: Genotype<T>> PopulationRefitness<T, G>
                 let current_ind = &population[individual_index].ind;
                 let current_fitness = &population[individual_index].fitness;
                 let mut current_fitness = current_fitness.unwrap().original_fitness;
-                /*
-                let avg_sim: f64 = population
-                    .par_iter()
-                    .enumerate()
-                    .filter(|(i, _ind)| *i != individual_index)
-                    .map(|(_i, ind)| current_ind.similarity(&ind.0))
-                    .sum::<f64>()
-                    / (population.len() as f64 - 1.0);
-                */
-                let m = population
-                    .par_iter()
-                    .enumerate()
-                    .filter(|(i, _ind)| *i != individual_index)
-                    .map(|(_i, ind)| current_ind.distance(&ind.ind))
-                    .map(|d| {
-                        if d >= sigma.0 {
-                            0.0
-                        } else {
-                            1.0 - (d / sigma.0).powf(alfa.0)
-                        }
-                    })
-                    .sum::<f64>();
                 if current_fitness > 0.0 {
+                    let mut m = population
+                        .par_iter()
+                        .enumerate()
+                        .filter(|(i, _ind)| *i != individual_index)
+                        .map(|(_i, ind)| current_ind.distance(&ind.ind))
+                        .map(|d| {
+                            if d >= sigma.0 {
+                                0.0
+                            } else {
+                                1.0 - (d / sigma.0).powf(alfa.0)
+                            }
+                        })
+                        .sum::<f64>();
                     current_fitness =
                         current_fitness.powf(beta.rate(generation, progress, n_solutions));
-                    if m > 0.0 {
-                        current_fitness /= m;
+                    if m == 0.0 {
+                        m = f64::EPSILON;
                     }
-                    current_fitness
+                    current_fitness / m
                 } else {
                     current_fitness
                 }