/// <summary>
/// This method is called when DataContex of the ModelPage is changed, or when the different model
/// in different project is changed.
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private async void ModelPage_DataContextChanged(object sender, DependencyPropertyChangedEventArgs e)
{
try
{
//for the old DataContex we should save the state
if (e.OldValue != null)
{
//set wait cursor
MainWindow.SetCursor(true);
MLConfigController model = e.OldValue as MLConfigController;
if (model != null && !model.Deleted)
{
model.Save();
}
//model.Dispose();
}
//for new model we should show previously stored state
if (e.NewValue != null)
{
MLConfigController model = e.NewValue as MLConfigController;
evaluation.DataContext = null;
evaluation.DataContext = model;
model.Init();
//disable testing in case metadata is not presented
if (model.TestData == null || model.TestData.Where(x => x.Kind == ANNdotNET.Core.DataKind.Feature).Count() == 0)
{
testTab.Visibility = Visibility.Collapsed;
}
//restore cursor
MainWindow.SetCursor(false);
if (trainingTab.SelectedIndex == 2)
{
//force the tab page to evaluate model if available
await evaluation.EvaluateModel();
}
}
}
catch (System.Exception ex)
{
//restore cursor
MainWindow.SetCursor(false);
await Application.Current.Dispatcher.BeginInvoke(
DispatcherPriority.Background,
new Action(
() =>
{
var appCnt = App.Current.MainWindow.DataContext as AppController;
appCnt.ReportException(ex);
}
));
}
}
private void deleteModel(MLConfigController model)
{
if (MessageBox.Show($"Are you sure you want to delete '{model.Name}' model and all related files?", "ANNdotNET", MessageBoxButton.YesNo) == MessageBoxResult.Yes)
{
var cont = DataContext as AppController;
if (cont == null)
{
return;
}
cont.DeleteModel(model);
}
}
internal void DeleteModel(MLConfigController mlconfigController)
{
try
{
var prj = AppModel.Project[1] as ANNProjectController;
prj.Models.Remove(mlconfigController);
mlconfigController.Delete();
}
catch (Exception ex)
{
if (ReportException != null)
{
ReportException(ex);
}
}
}
private void onCreateModel(object sender, ExecutedRoutedEventArgs e)
{
try
{
var prj = ActiveViewModel as ANNProjectController;
if (prj != null)
{
var m = new MLConfigController(ActiveModelChanged);
prj.CreateMLConfig(m);
}
return;
}
catch (Exception ex)
{
ReportException(ex);
}
}
private void duplicateModel(MLConfigController model)
{
}
private void renameModel(MLConfigController model)
{
model.IsEditing = true;
}
public async Task <ModelEvaluation> EvaluateModel()
{
try
{
MainWindow.SetCursor(true);
MLConfigController pCont = this.DataContext as MLConfigController;
var appCnt = anndotnet.wnd.App.Current.MainWindow.DataContext as AppController;
appCnt.ModelEvaluationAction(false);
//send model evaluation in the background
var modeEval = await Task <ModelEvaluation> .Run(() => pCont.EvaluateModel());
appCnt.ModelEvaluationAction(true);
PrepareGraphs(modeEval);
for (int i = 0; i < modeEval.TrainingValue.Count; i++)
{
actualTraining.AddPoint(modeEval.TrainingValue[i]);
predictedTraining.AddPoint(modeEval.ModelValueTraining[i]);
}
for (int i = 0; i < modeEval.ValidationValue.Count; i++)
{
actualValidation.AddPoint(modeEval.ValidationValue[i]);
predictedValidation.AddPoint(modeEval.ModelValueValidation[i]);
}
//Refresh the charts
trainingGraph.RestoreScale(trainingGraph.GraphPane);
validationGraph.RestoreScale(validationGraph.GraphPane);
//regression
if (modeEval.ModelOutputDim == 1)
{
var itm = trainingItems.Items[0] as Regression;
itm.Visibility = Visibility.Visible;
var itm2 = trainingItems.Items[1] as BinaryClassification;
itm2.Visibility = Visibility.Collapsed;
var itm3 = trainingItems.Items[2] as Multiclass;
itm3.Visibility = Visibility.Collapsed;
itm.DataContext = modeEval.TrainPerformance;
//validation set
var itm11 = validatingItems.Items[0] as Regression;
itm11.Visibility = Visibility.Visible;
var itm21 = validatingItems.Items[1] as BinaryClassification;
itm21.Visibility = Visibility.Collapsed;
var itm31 = validatingItems.Items[2] as Multiclass;
itm31.Visibility = Visibility.Collapsed;
itm11.DataContext = modeEval.ValidationPerformance;
}//binary classification
else if (modeEval.ModelOutputDim == 2)
{
var itm = trainingItems.Items[0] as Regression;
itm.Visibility = Visibility.Collapsed;
var itm2 = trainingItems.Items[1] as BinaryClassification;
itm2.Visibility = Visibility.Visible;
var itm3 = trainingItems.Items[2] as Multiclass;
itm3.Visibility = Visibility.Collapsed;
itm2.DataContext = modeEval.TrainPerformance;
var itm11 = validatingItems.Items[0] as Regression;
itm11.Visibility = Visibility.Collapsed;
var itm21 = validatingItems.Items[1] as BinaryClassification;
itm21.Visibility = Visibility.Visible;
var itm31 = validatingItems.Items[2] as Multiclass;
itm31.Visibility = Visibility.Collapsed;
itm21.DataContext = modeEval.ValidationPerformance;
}//multi-class classification
else if (modeEval.ModelOutputDim > 2)
{
var itm = trainingItems.Items[0] as Regression;
itm.Visibility = Visibility.Collapsed;
var itm2 = trainingItems.Items[1] as BinaryClassification;
itm2.Visibility = Visibility.Collapsed;
var itm3 = trainingItems.Items[2] as Multiclass;
itm3.Visibility = Visibility.Visible;
itm3.DataContext = modeEval.TrainPerformance;
var itm11 = validatingItems.Items[0] as Regression;
itm11.Visibility = Visibility.Collapsed;
var itm21 = validatingItems.Items[1] as BinaryClassification;
itm21.Visibility = Visibility.Collapsed;
var itm31 = validatingItems.Items[2] as Multiclass;
itm31.Visibility = Visibility.Visible;
itm31.DataContext = modeEval.ValidationPerformance;
}
return(modeEval);
}
catch (Exception ex)
{
AppController appCont = App.Current.MainWindow.DataContext as AppController;
appCont.ReportException(ex);
return(null);
}
finally
{
MainWindow.SetCursor(false);
await Application.Current.Dispatcher.BeginInvoke(
DispatcherPriority.Background,
new Action(
() =>
{
MainWindow.SetCursor(false);
}
));
}
}