public override void Build()
{
if (save)
{
writerEnv = UIO.CreateStreamWriter(GeneratePath(task, true), "GeneSessionResults.csv", false);
UIO.WriteLine(writerEnv, "Generation;Angle Random Rotation;Wind");
}
Debug.Log("Build DroneSession");
signal = new ControlSignal();
tsignal = new ThrustSignal();
tmpBuildCustomWeights = new List <Matrix <float> >();
externalEvaluations = Vector <float> .Build.Dense(populationSize);
//Debug.Log(fromTask);
taskObject = (DroneTask)Activator.CreateInstance(Type.GetType("Lexmou.MachineLearning.Drone" + task), rndGenerator, fromTask);
//Debug.Log(taskObject.fromTask);
dronePopulation = new GameObject[populationSize];
droneRigid = new Rigidbody[populationSize];
targetPosition = new Vector3[populationSize];
mlpPopulation = new MultiLayerMathsNet[populationSize];
gene = new Genetic(seed, rndGenerator, populationSize, taskObject.individualSize, initialValueWeights, mutationRate, randomIndividualsRate, bestIndividualsRate, emptyRate, GeneratePath(task, false), save);
if (loadGeneration != 0)
{
float[,] floatArr = new float[taskObject.individualSize - taskObject.rowIndex, populationSize];
Debug.Log(taskObject.fromTask);
//Debug.Log(taskObject.individualSize);
gene.LoadGeneration(GeneratePath(taskObject.fromTask, true), loadGeneration, floatArr, taskObject.rowIndex);
gene.generation = loadGeneration;
}
}
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);
}