private void learnBtn_Click(object sender, RoutedEventArgs e)
{
if (network == null)
{
learningStatus.Content = "Stwórz najpierw sieć";
return;
}
if (!weightsLoaded)
{
learningStatus.Content = "Załaduj najpierw wagi";
return;
}
if (learning == null)
{
learningStatus.Content = "Załaduj najpierw próbki uczące";
return;
}
if (!FormValidation.isBetaValid(betaBox, out string betaMessage))
{
learningStatus.Content = betaMessage;
return;
}
if (!FormValidation.isLearningFactorValid(learningFactorBox, out string LearningFactorMessage))
{
learningStatus.Content = LearningFactorMessage;
return;
}
if (!FormValidation.isEpochAmountValid(epochAmountBox, out string epochMessage))
{
learningStatus.Content = epochMessage;
return;
}
epochAmount = int.Parse(epochAmountBox.Text);
beta = double.Parse(betaBox.Text);
learningFactor = double.Parse(learningFactorBox.Text);
BackgroundWorker worker = new BackgroundWorker();
worker.WorkerReportsProgress = true;
worker.ProgressChanged += worker_ProgressChanged;
worker.DoWork += worker_DoWork;
if (worker.IsBusy == true)
{
learningStatus.Content = "Poczekaj na zakończenie procesu uczenia";
return;
}
progressBar.Visibility = Visibility.Visible;
worker.RunWorkerAsync();
}
private void outputBtn_Click(object sender, RoutedEventArgs e)
{
if (network == null)
{
resultBox.Text = "Najpierw stwórz sieć";
return;
}
if (!FormValidation.isBetaValid(inputBetaBox, out string message))
{
resultBox.Text = message;
return;
}
if (!FormValidation.isInputValid(configuration, inputBox, out string inputMessage))
{
resultBox.Text = inputMessage;
return;
}
if (!FormValidation.isMinValid(minBox, out string minMessage))
{
resultBox.Text = minMessage;
return;
}
if (!FormValidation.isMaxValid(minBox, out string maxMessage))
{
resultBox.Text = maxMessage;
return;
}
double min = double.Parse(minBox.Text);
double max = double.Parse(maxBox.Text);
double inputBeta = double.Parse(inputBetaBox.Text);
var inputs = Tools.convertStringToDoubleList(inputBox.Text);
double output = network.calculateOutput(inputs, inputBeta);
double denormalizedOutput = Tools.getDenormalizedValue(output, min, max);
resultBox.Text = denormalizedOutput.ToString();
}