Added OnNewGeneration event

GeneticAlgorithm.UnitTests/SearchTests.cs

@@ -1,7 +1,9 @@
 using System;
+using System.Collections.Generic;
 using System.Linq;
 using System.Threading;
 using System.Threading.Tasks;
+using GeneticAlgorithm.Interfaces;
 using Microsoft.VisualStudio.TestTools.UnitTesting;
 
 namespace GeneticAlgorithm.UnitTests
@@ -86,10 +88,45 @@ public void HistoryIsRightTest()
                     .IncludeAllHistory().Build();
 
             var result = searchEngine.Search();
+
+            AssertHasEvaluation(result.History, population);
+        }
 
-            for (int i = 0; i < population.Length; i++)
-            for (int j = 0; j < population[i].Length; j++)
-                Assert.AreEqual(population[i][j], result.History[i][j].Evaluate());
+        [TestMethod]
+        public void OnNewGenerationEventTest()
+        {
+            var population = new[] { new double[] { 1, 1, 1 }, new double[] { 2, 2, 2 }, new double[] { 2, 3, 2 } };
+            var populationManager = new TestPopulationManager(population);
+            var searchEngine =
+                new TestGeneticSearchEngineBuilder(population[0].Length, population.Length - 1, populationManager)
+                    .Build();
+
+            var actualPopulation = new List<IChromosome[]>();
+            var actualEvaluations = new List<double[]>();
+            searchEngine.OnNewGeneration += (c, d) =>
+            {
+                actualEvaluations.Add(d);
+                actualPopulation.Add(c);
+            };
+
+            searchEngine.Search();
+
+            AssertAreTheSame(actualEvaluations, population);
+            AssertHasEvaluation(actualPopulation, population);
+        }
+
+        private void AssertHasEvaluation(List<IChromosome[]> chromosomes, double[][] evaluations)
+        {
+            for (int i = 0; i < chromosomes.Count; i++)
+            for (int j = 0; j < chromosomes[0].Length; j++)
+                Assert.AreEqual(evaluations[i][j], chromosomes[i][j].Evaluate());
+        }
+
+        private void AssertAreTheSame(List<double[]> collection1, double[][] collection2)
+        {
+            for (int i = 0; i < collection1.Count; i++)
+            for (int j = 0; j < collection1[0].Length; j++)
+                Assert.AreEqual(collection1[i][j], collection2[i][j]);
         }
     }
 }

GeneticAlgorithm/GeneticSearchEngine.cs

@@ -14,6 +14,11 @@ public class GeneticSearchEngine
         private readonly IChildrenGenerator childrenGenerator;
         private readonly GeneticSearchOptions options;
 
+        /// <summary>
+        /// This even is risen for every new generation. It's arguments are the population and their evaluations.
+        /// </summary>
+        public event Action<IChromosome[], double[]> OnNewGeneration; 
+
         public GeneticSearchEngine(GeneticSearchOptions options, IPopulationGenerator populationGenerator, IChildrenGenerator childrenGenerator)
         {
             this.options = options;
@@ -48,7 +53,7 @@ public GeneticSearchResult Search()
                     EvaluatePopulation();
                 }
 
-                UpdateStopAndRenewalManagers();
+                UpdateNewGeneration();
 
                 NormilizeEvaluations();
                 GenerateChildren();
@@ -60,12 +65,20 @@ public GeneticSearchResult Search()
             return new GeneticSearchResult(population.GetChromosomes(), history, stopwatch.Elapsed, generation);
         }
 
-        private void UpdateStopAndRenewalManagers()
+        /// <summary>
+        /// Update everyone that needs to know about the new generation
+        /// </summary>
+        private void UpdateNewGeneration()
         {
+            var chromosomes = population.GetChromosomes();
+            var evaluations = population.GetEvaluations();
+
             foreach (var stopManager in options.StopManagers)
-                stopManager.AddGeneration(population.GetChromosomes(), population.GetEvaluations());
+                stopManager.AddGeneration(chromosomes, evaluations);
             foreach (var populationRenwalManager in options.PopulationRenwalManagers)
-                populationRenwalManager.AddGeneration(population.GetChromosomes(), population.GetEvaluations());
+                populationRenwalManager.AddGeneration(chromosomes, evaluations);
+
+            OnNewGeneration?.Invoke(chromosomes, evaluations);
         }
 
         private void GenerateChildren()

GreatestVectorTests/BassicTests.cs

@@ -6,7 +6,7 @@ namespace GreatestVectorTests
     [TestClass]
     public class BassicTests
     {
-        public const int POPULATION_SIZE = 100;
+        private const int POPULATION_SIZE = 100;
 
         [TestMethod]
         public void BassicTest()

GreatestVectorTests/NumberVectorBassicPopulationGenerator.cs

@@ -14,9 +14,9 @@ class NumberVectorBassicPopulationGenerator : IPopulationGenerator
 
         public IEnumerable<IChromosome> GeneratePopulation(int size)
         {
-            var population = new IChromosome[BassicTests.POPULATION_SIZE];
+            var population = new IChromosome[size];
 
-            for (int i = 0; i < BassicTests.POPULATION_SIZE; i++)
+            for (int i = 0; i < size; i++)
                 population[i] = GetChromosome();
 
             return population;

README.md

@@ -23,6 +23,7 @@ Your chromosomes will need to implement the IChromosome classes.
 ### ICrossoverManager
 
 You'll need to implement the ICrossoverManager class. This tells the engine how to perform crossovers for your chromosomes.
+You can read more about corossovers [here](https://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)).
 
 ```CSharp
     public interface ICrossoverManager
@@ -57,6 +58,23 @@ var searchEngine = new GeneticSearchEngineBuilder(POPULATION_SIZE, MAX_GENERATIO
 var result = searchEngine.Search();
 ```
 
+## Events
+
+### OnNewGeneration
+
+This event is called once for every new generations. It's arguments are the generation's population, and their evaluations.
+This is a good way for GUIs to visually show the argument's progress, or just show the search progress.
+
+Example:
+```CSharp
+var searchEngine = new GeneticSearchEngineBuilder(POPULATION_SIZE, MAX_GENERATIONS, crossoverManager, populationGenerator).Build();
+searchEngine.OnNewGeneration += (IChromosome[] c,double[] d) =>
+{
+    // Do some work here
+};
+var result = searchEngine.Search();
+```
+
 ## Search Options
 Let's see how we can configure our search engine to better match our needs.