private void trainButton_Click(object sender, RoutedEventArgs e)
{
batchSize = batchsizeTextBox.Text;
steps = stepsTextBox.Text;
// Construct hidden layers
for (int i = 1; i < layerCreatorListBox.Items.Count - 1; i++)
{
hiddenLayers += $"{layerCreatorListBox.Items[i].ToString().Split(' ')[0]} ";
}
Console.WriteLine(hiddenLayers);
if (frameworkComboBox.SelectedIndex == 0)
{
// Tensorflow
PythonService python = new PythonService();
string args = $"{datasetFullPath} {featureCount} {classCount + 1} {batchSize} {steps} -l {hiddenLayers}";
python.RunCommand(TENSORFLOWTRAINING, args);
testrunResultsTextBlock.Text = "Neural Network Trained!";
trainButton.IsEnabled = false;
untrainButton.IsEnabled = true;
// Run bokeh plots
}
else if (frameworkComboBox.SelectedIndex == 1)
{
// SKlearn
}
}
private void runtestButton_Click(object sender, RoutedEventArgs e)
{
testsetPercentage = datasetPercentageTextBox.Text;
// Tensorflow
PythonService python = new PythonService();
string args = $"{datasetFullPath} {testsetPercentage} {featureCount} {classCount + 1} -l {hiddenLayers}";
python.RunCommand(TENSORFLOWTESTING, args);
testrunResultsTextBlock.Text = $"Accuracy: {python.LastResult}";
}
private void LoadBokehPlot(string datasetPath)
{
string feature1 = horizonalAxisComboBox.SelectedValue.ToString();
string feature2 = verticalAxisComboBox.SelectedValue.ToString();
PythonService python = new PythonService();
string args = $"{datasetPath} {feature1} {feature2}";
python.RunCommand(BOKEHPLOTTING, args);
if (firstWebpageload == false)
{
bokehHTMLBrowser.Source = new Uri(@"http://localhost/blahblah.html");
firstWebpageload = true;
}
else
{
bokehHTMLBrowser.Reload(true);
}
}
