private void bttnEvaluate_Click(object sender, RoutedEventArgs e)
{
try
{
var trainingFile = new DataFile(ApplicationSingleton.Instance.Config);
trainingFile.LoadExcel(ApplicationSingleton.Instance.Config.EvaluationFile);
double[][] evalInput = trainingFile.GenerateInputData();
var evalOutput = new double[evalInput.Length][];
var genome = ApplicationSingleton.Instance.GenomePopulation.BestGenome;
double sc = ApplicationSingleton.Instance.Config.Model.Score(genome, evalInput,
trainingFile.GenerateIdealData());
for (int row = 0; row < evalInput.Length; row++)
{
double[] output = ApplicationSingleton.Instance.Config.Model.Compute(evalInput[row], genome);
for (int col = 0; col < output.Length; col++)
{
evalOutput[row] = output;
}
}
trainingFile.WriteExcel(ApplicationSingleton.Instance.Config.EvaluationOutputFile, evalOutput);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, ex.GetType().Name);
}
}
private void bttnTrain_Click(object sender, RoutedEventArgs e)
{
try
{
var trainingFile = new DataFile(ApplicationSingleton.Instance.Config);
trainingFile.LoadExcel(ApplicationSingleton.Instance.Config.TrainingFile);
double[][] trainingInput = trainingFile.GenerateInputData();
double[][] trainingIdeal = trainingFile.GenerateIdealData();
ApplicationSingleton.Instance.Train = new GeneticTraining(
ApplicationSingleton.Instance.GenomePopulation,
trainingInput,
trainingIdeal);
ApplicationSingleton.Instance.Train.Start();
ApplicationSingleton.Instance.Train.AddListener(this);
UpdateButtons();
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, ex.GetType().Name);
}
}
private void bttnGeneratePop_Click(object sender, RoutedEventArgs e)
{
try
{
using (new WaitCursor())
{
var pop = new Population();
pop.Init(ApplicationSingleton.Instance.Config);
ApplicationSingleton.Instance.GenomePopulation = pop;
pop.Generate();
lblBestScore.Content = ApplicationSingleton.Instance.GenomePopulation.BestGenome.Score;
var trainingFile = new DataFile(ApplicationSingleton.Instance.Config);
trainingFile.LoadExcel(ApplicationSingleton.Instance.Config.TrainingFile);
double[][] trainingInput = trainingFile.GenerateInputData();
double[][] trainingIdeal = trainingFile.GenerateIdealData();
pop.ScoreAll(trainingInput, trainingIdeal);
UpdateButtons();
}
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, ex.GetType().Name);
}
}
private void bttnTrain_Click(object sender, RoutedEventArgs e)
{
try
{
var trainingFile = new DataFile(ApplicationSingleton.Instance.Config);
trainingFile.LoadExcel(ApplicationSingleton.Instance.Config.TrainingFile);
double[][] trainingInput = trainingFile.GenerateInputData();
double[][] trainingIdeal = trainingFile.GenerateIdealData();
ApplicationSingleton.Instance.Train = new GeneticTraining(
ApplicationSingleton.Instance.GenomePopulation,
trainingInput,
trainingIdeal);
ApplicationSingleton.Instance.Train.Start();
ApplicationSingleton.Instance.Train.AddListener(this);
UpdateButtons();
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, ex.GetType().Name);
}
}
