public void EvaluationTest()
{
Vector <float> externalEvaluations = Vector <float> .Build.DenseOfArray(new float[2] {
1.0f, 0.0f
});
geneSeed.Evaluation(externalEvaluations, "max");
Assert.AreEqual(0, geneSeed.GetBestIndividualIndex());
geneSeed.Evaluation(externalEvaluations, "min");
}
public void SelectionTest()
{
int size = 3;
float[] arr = new float[size];
for (int i = 0; i < size; i++)
{
arr[i] = 1.0f;
}
arr[size - 1] = 2.0f;
Vector <float> externalEvaluations = Vector <float> .Build.DenseOfArray(arr);
Genetic gene = new Genetic(seed, null, size, 3, 0.1f, 0.34f, 0.34f);
gene.Evaluation(externalEvaluations, "max");
Debug.Log(gene.GetPopulation());
gene.Selection();
Debug.Log(gene.GetPopulation());
}
public void SaveTest()
{
Vector <float> externalEvaluations = Vector <float> .Build.DenseOfArray(new float[2] {
0.0f, 1.0f
});
geneRndGenerator.Evaluation(externalEvaluations, "max");
geneRndGenerator.SaveGeneration();
float[,] floatArr = new float[geneRndGenerator.individualSize, geneRndGenerator.populationSize];
float[] floatArrBest = new float[geneRndGenerator.individualSize];
geneRndGenerator.LoadGeneration(1, floatArr);
geneRndGenerator.LoadBest(1, floatArrBest);
Matrix <float> result = Matrix <float> .Build.DenseOfArray(floatArr);
Vector <float> resultBest = Vector <float> .Build.DenseOfArray(floatArrBest);
Assert.AreEqual(geneRndGenerator.GetPopulation(), result);
Assert.AreEqual(geneRndGenerator.GetBestIndividual(), resultBest);
Debug.Log(geneRndGenerator.GetPopulation());
Debug.Log(result);
}