From 8affc6af9dc10f4466e6d3318df593fa01319c61 Mon Sep 17 00:00:00 2001
From: "a.croix" <croix.alexandre@gmail.com>
Date: Mon, 18 Feb 2019 17:25:24 +0100
Subject: [PATCH] Fix style
---
.../java/wowa/training/SolutionDistance.java | 36 +++++++------------
.../be/cylab/java/wowa/training/Trainer.java | 17 ++++-----
.../be/cylab/java/wowa/training/Utils.java | 12 +++----
3 files changed, 26 insertions(+), 39 deletions(-)
diff --git a/src/main/java/be/cylab/java/wowa/training/SolutionDistance.java b/src/main/java/be/cylab/java/wowa/training/SolutionDistance.java
index 3b375c3..dd10c6d 100644
--- a/src/main/java/be/cylab/java/wowa/training/SolutionDistance.java
+++ b/src/main/java/be/cylab/java/wowa/training/SolutionDistance.java
@@ -17,13 +17,14 @@ public class SolutionDistance implements Comparable<SolutionDistance> {
this.weights_w = new double[weights_number];
this.weights_p = new double[weights_number];
}
+
@Override
public String toString() {
return "SolutionDistance{" +
- "weights_w=" + Arrays.toString(weights_w) +
- ", weights_p=" + Arrays.toString(weights_p) +
- ", distance=" + distance +
- '}';
+ "weights_w=" + Arrays.toString(weights_w)
+ + ", weights_p=" + Arrays.toString(weights_p)
+ + ", distance=" + distance
+ + '}';
}
public void computeScoreTo(List<double[]> data, double[] expected) {
@@ -33,7 +34,7 @@ public class SolutionDistance implements Comparable<SolutionDistance> {
}
- public void randomlyMutateWithProbability(double probability) {
+ public void randomlyMutateWithProbability(final double probability) {
double tos = Math.random();
if (tos > probability) {
// do nothing
@@ -41,21 +42,21 @@ public class SolutionDistance implements Comparable<SolutionDistance> {
}
//new weight value and position
- double new_weight_value = Math.random();
- int randomIndex = Utils.randomInteger(0, this.weights_p.length -1);
+ double newWeightValue = Math.random();
+ int randomIndex = Utils.randomInteger(0, this.weights_p.length - 1);
//Select w or p weights
- int weight_selection = Utils.randomInteger(0, 1);
- if (weight_selection == 0) {
- this.weights_w[randomIndex] = new_weight_value;
+ int weightSelection = Utils.randomInteger(0, 1);
+ if (weightSelection == 0) {
+ this.weights_w[randomIndex] = newWeightValue;
} else {
- this.weights_p[randomIndex] = new_weight_value;
+ this.weights_p[randomIndex] = newWeightValue;
}
this.normalize();
}
@Override
- public int compareTo(SolutionDistance solution) {
+ public int compareTo(final SolutionDistance solution) {
return this.getDistance() > solution.getDistance() ? -1 : this.getDistance() < solution.getDistance() ? 1 : 0;
}
@@ -66,19 +67,8 @@ public class SolutionDistance implements Comparable<SolutionDistance> {
}
- public double[] getWeights_w() {
- return weights_w;
- }
-
- public double[] getWeights_p() {
- return weights_p;
- }
-
public double getDistance() {
return distance;
}
- public void setDistance(double distance) {
- this.distance = distance;
- }
}
diff --git a/src/main/java/be/cylab/java/wowa/training/Trainer.java b/src/main/java/be/cylab/java/wowa/training/Trainer.java
index 2e7e2dd..bbcd0b5 100644
--- a/src/main/java/be/cylab/java/wowa/training/Trainer.java
+++ b/src/main/java/be/cylab/java/wowa/training/Trainer.java
@@ -12,7 +12,7 @@ public class Trainer {
this.parameters = parameters;
}
- public SolutionDistance run(List<double[]> data, double[] expected) {
+ public SolutionDistance run(final List<double[]> data, final double[] expected) {
List<SolutionDistance> current_population = this.generateInitialPopulationAndComputeDistances(this.getParameters().getPopulationSize(), data, expected);
Collections.sort(current_population);
@@ -37,7 +37,7 @@ public class Trainer {
return best_solution;
}
- public SolutionDistance findBestSolution(List<SolutionDistance> solutions) {
+ public SolutionDistance findBestSolution(final List<SolutionDistance> solutions) {
SolutionDistance best_solution = new SolutionDistance(solutions.get(0).weights_p.length);
for (SolutionDistance solution : solutions) {
@@ -78,7 +78,7 @@ public class Trainer {
if (solutions.size() < count) {
- throw new IllegalArgumentException("Not enough elements in population to select "+ count + "parents");
+ throw new IllegalArgumentException("Not enough elements in population to select " + count + "parents");
}
while (selected_elements.size() < count) {
double tos = Math.random();
@@ -95,7 +95,7 @@ public class Trainer {
return selected_elements;
}
- private List<SolutionDistance> tournamentSelection(List<SolutionDistance> solutions, List<SolutionDistance> selected_elements, int count){
+ private List<SolutionDistance> tournamentSelection(List<SolutionDistance> solutions, List<SolutionDistance> selected_elements, int count) {
while (selected_elements.size() < count) {
Collections.sort(solutions);
@@ -134,11 +134,10 @@ public class Trainer {
solutions.remove(0);
solutions.remove(1);
- if(selectionMethod == TrainerParameters.SELECTION_METHOD_RWS) {
+ if (selectionMethod == TrainerParameters.SELECTION_METHOD_RWS) {
return this.rouletteWheelSelection(solutions, selected_parents, count - 2);
- }
- else if (selectionMethod == TrainerParameters.SELECTION_METHOD_TOS) {
+ } else if (selectionMethod == TrainerParameters.SELECTION_METHOD_TOS) {
return this.tournamentSelection(solutions, selected_parents, count - 2);
}
throw new IllegalArgumentException("Invalid selection method");
@@ -162,7 +161,7 @@ public class Trainer {
double beta = Math.random();
solutions = this.reproduce(solutions.get(dad), solutions.get(mom), solutions, cut_position, beta);
}
- while(solutions.size() > this.getParameters().getPopulationSize()) {
+ while (solutions.size() > this.getParameters().getPopulationSize()) {
solutions.remove(solutions.get(solutions.size() - 1));
}
return solutions;
@@ -243,6 +242,4 @@ public class Trainer {
}
-
-
}
diff --git a/src/main/java/be/cylab/java/wowa/training/Utils.java b/src/main/java/be/cylab/java/wowa/training/Utils.java
index 680f633..27a5b87 100644
--- a/src/main/java/be/cylab/java/wowa/training/Utils.java
+++ b/src/main/java/be/cylab/java/wowa/training/Utils.java
@@ -7,7 +7,7 @@ import java.util.Random;
public class Utils {
- public static double[] normalizeWeights(double[] weights) {
+ public static double[] normalizeWeights(final double[] weights) {
double sum_weight = Utils.sumArrayElements(weights);
double[] weightsNormalized = new double[weights.length];
for (int i = 0; i < weights.length; i++) {
@@ -16,7 +16,7 @@ public class Utils {
return weightsNormalized;
}
- public static double findMaxDistance(List<SolutionDistance> solutions) {
+ public static double findMaxDistance(final List<SolutionDistance> solutions) {
double max = Double.NEGATIVE_INFINITY;
for (SolutionDistance solution : solutions) {
if(solution.getDistance() > max) {
@@ -26,7 +26,7 @@ public class Utils {
return max;
}
- public static double findMinDistance(List<SolutionDistance> solutions) {
+ public static double findMinDistance(final List<SolutionDistance> solutions) {
double min = Double.POSITIVE_INFINITY;
for (SolutionDistance solution : solutions) {
if (solution.getDistance() < min){
@@ -36,7 +36,7 @@ public class Utils {
return min;
}
- public static double sumTotalDistance(List<SolutionDistance> solutions) {
+ public static double sumTotalDistance(final List<SolutionDistance> solutions) {
double sum = 0;
for (SolutionDistance solution : solutions) {
sum += solution.getDistance();
@@ -44,7 +44,7 @@ public class Utils {
return sum;
}
- public static double sumArrayElements(double[] array) {
+ public static double sumArrayElements(final double[] array) {
float sum = 0;
for (double weight : array) {
sum += weight;
@@ -52,7 +52,7 @@ public class Utils {
return sum;
}
- public static int randomInteger(int min, int max) {
+ public static int randomInteger(final int min, final int max) {
if (min >= max) {
throw new IllegalArgumentException("Max must be greater then min");
}
--
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