private void LoadFromXMLButton_Click(object sender, RoutedEventArgs e)
{
if (mainWindow.neuralNetwork != null)
{
SaveWarning warning = new SaveWarning();
warning.ShowDialog();
if (warning.OverrideNetwork)
{
OpenFileDialog file = new OpenFileDialog();
file.CheckFileExists = true;
file.Multiselect = false;
file.Filter = "XML (.xml)|*.xml";
file.ShowDialog();
mainWindow.neuralNetwork = NeuralNetwork.LoadNetworkFromXML(file.FileName);
}
}
else
{
OpenFileDialog file = new OpenFileDialog();
file.CheckFileExists = true;
file.Multiselect = false;
file.Filter = "XML (.xml)|*.xml";
file.ShowDialog();
mainWindow.neuralNetwork = NeuralNetwork.LoadNetworkFromXML(file.FileName);
}
}
private void CreateNetworkButton_Click(object sender, RoutedEventArgs e)
{
//check if learning rate is set
double learningRate;
if (!Double.TryParse(LearningRateTextBox.Text, out learningRate))
{
consoleTextBox.AppendText("Learning rate must be set and must be in a correct format (x,xxx) ! \n");
return;
}
for (int lay = 1; lay < layerDisplay.Items.Count; lay++)
{
if ((layerDisplay.Items[lay] as NetworkLayerDescriptor).neurons == 0)
{
consoleTextBox.AppendText("Network´s layer cant have 0 neurons ! \n");
return;
}
}
neuralNetwork = window.neuralNetwork;
SaveWarning saveWarning;
//if there allready is a network, ask user to save it
if (neuralNetwork != null)
{
saveWarning = new SaveWarning();
saveWarning.ShowDialog();
if (saveWarning.OverrideNetwork)
{
List <int> layers = new List <int>();
List <ActivationFunctions> activationFunctions = new List <ActivationFunctions>();
for (int lay = 1; lay < layerDisplay.Items.Count; lay++)
{
layers.Add((layerDisplay.Items[lay] as NetworkLayerDescriptor).neurons);
activationFunctions.Add((ActivationFunctions)Enum.Parse(typeof(ActivationFunctions), (layerDisplay.Items[lay] as NetworkLayerDescriptor).selectedIndex.ToString()));
}
window.neuralNetwork = new NeuralNetwork(layers.ToArray(), learningRate, activationFunctions);
this.neuralNetwork = window.neuralNetwork;
consoleTextBox.AppendText("Network succesfully created ! \n");
}
else
{
consoleTextBox.AppendText("Creation canceled \n");
}
}
//if there is no network, create a new one
else
{
List <int> layers = new List <int>();
List <ActivationFunctions> activationFunctions = new List <ActivationFunctions>();
for (int lay = 1; lay < layerDisplay.Items.Count; lay++)
{
layers.Add((layerDisplay.Items[lay] as NetworkLayerDescriptor).neurons);
activationFunctions.Add((ActivationFunctions)Enum.Parse(typeof(ActivationFunctions), (layerDisplay.Items[lay] as NetworkLayerDescriptor).selectedIndex.ToString()));
}
window.neuralNetwork = new NeuralNetwork(layers.ToArray(), learningRate, activationFunctions);
this.neuralNetwork = window.neuralNetwork;
consoleTextBox.AppendText("Network succesfully created ! \n");
}
}
