Changeset 15926 for branches/2913_MatlabScriptProblemInstanceProvider/HeuristicLab.Problems.Instances.DataAnalysis.Views/3.3/Regression/Matlab/RegressionMatlabImportDialog.cs

Timestamp:

05/02/18 13:14:16 (6 years ago)

Author:

rhanghof

Message:

#2913:

• Added the support for importing different Matlab datatypes.
• Added some classes and changed the import dialog for importing double arrays.

File:

• branches/2913_MatlabScriptProblemInstanceProvider/HeuristicLab.Problems.Instances.DataAnalysis.Views/3.3/Regression/Matlab/RegressionMatlabImportDialog.cs (modified) (10 diffs)

branches/2913_MatlabScriptProblemInstanceProvider/HeuristicLab.Problems.Instances.DataAnalysis.Views/3.3/Regression/Matlab/RegressionMatlabImportDialog.cs

@@ -19 +19 @@
 namespace HeuristicLab.Problems.Instances.DataAnalysis.Views.Regression.Matlab {
   public partial class RegressionMatlabImportDialog : Form {
+    private const int TAB_INDEX_TIMESERIES = 0;
+    private const int TAB_INDEX_DOUBLE_ARRAYS = 1;
+
     private IMatlabConnector _mlConnector;
+
+    private IMLVariablesLoader _variablesLoader;
+    private IMLVariablesLoader _timeseriesLoader;
+    private IMLVariablesLoader _doubleArraysLoader;
+
+    private CancellationTokenSource _cts = new CancellationTokenSource();
+
     public event EventHandler<EventArgs<string>> StatusChangedEvent;
     public event EventHandler<EventArgs<string>> ErrorOccuredEvent;
-
-
 
     /// <summary>
@@ -49 +57 @@
     }
 
-    private IList<KeyValuePair<string, MLDatatype>> _selectedVariables;
-
-    public IEnumerable<KeyValuePair<string, MLDatatype>> SelectedVariables {
+    private IList<MLVariableInfo> _selectedTimeseries;
+    private IList<MLVariableInfo> _selectedDoubleArrays;
+
+    public IEnumerable<MLVariableInfo> SelectedVariables {
       get {
-        return _selectedVariables;
+        return _variablesLoader.SelectedVariables;
       }
     }
@@ -60 +69 @@
       InitializeComponent();
 
-      _selectedVariables = new List<KeyValuePair<string, MLDatatype>>();
+      _selectedTimeseries = new List<MLVariableInfo>();
+      _selectedDoubleArrays = new List<MLVariableInfo>();
       _values = new Dataset();
 
       this.FormClosed += (s, e) => DisposeMatlabConnector();
       OpenFileButton.Click += OpenFileButtonClick;
-      VariablesListBox.ItemCheck += (s, e) => BeginInvoke((MethodInvoker)(() => CheckedItemsChanged(s, e)));
+
+      DatatypeSelectorTabControl.SelectedIndexChanged += (s, e) => BeginInvoke((MethodInvoker)(() => DatatypeSelectorTabControlTabIndexChanged(s, e)));
+
       LoadValuesButton.Click += LoadValuesButtonClick;
       TrainingTestTrackBar.ValueChanged += TrainingTestTrackBarValueChanged;
+
       StatusChangedEvent += (s, e) => BeginInvoke((MethodInvoker)(() => StatusLabel.Text = e.Value));
       ErrorOccuredEvent += (s, e) => BeginInvoke((MethodInvoker)(() => {
@@ -74 +87 @@
         ErrorTextBox.Visible = true;
       }));
-    }
-
-    private void CheckedItemsChanged(object sender, ItemCheckEventArgs e) {
-      _selectedVariables.Clear();
-      foreach (KeyValuePair<string, MLDatatype> item in VariablesListBox.CheckedItems) {
-        if (item.Value == MLDatatype.Timeseries) {
-          _selectedVariables.Add(item);
-        }
-      }
-      LoadValuesButton.Enabled = VariablesListBox.CheckedIndices.Count > 0;
-    }
-
-    #region Events
-
+
+      _timeseriesLoader = new MLTimeseriesLoader(this, TimeseriesListBox);
+      _timeseriesLoader.NumberOfSelectedVariablesChanged += NumberOfSelectedVariablesChanged;
+      _doubleArraysLoader = new MLDoubleArrayLoader(this, DoubleArraysListBox);
+      _doubleArraysLoader.NumberOfSelectedVariablesChanged += NumberOfSelectedVariablesChanged;
+
+      _variablesLoader = _timeseriesLoader;
+
+    }
+
+    #region Methods for Events
+
+    private void NumberOfSelectedVariablesChanged(object s, EventArgs<int> e) {
+      LoadValuesButton.Enabled = e.Value > 0;
+    }
+
+    private void DatatypeSelectorTabControlTabIndexChanged(object s, EventArgs e) {
+      switch (DatatypeSelectorTabControl.SelectedIndex) {
+        case TAB_INDEX_TIMESERIES:
+          _variablesLoader = _timeseriesLoader;
+          break;
+        case TAB_INDEX_DOUBLE_ARRAYS:
+          _variablesLoader = _doubleArraysLoader;
+          break;
+      }
+
+      LoadValuesButton.Enabled = _variablesLoader.SelectedVariables.Count() > 0;
+    }
 
     private void LoadValuesButtonClick(object sender, EventArgs e) {
+      _cts.Cancel();
+      _cts = new CancellationTokenSource();
       LoadValuesAsync();
     }
@@ -106 +135 @@
     }
     #endregion
-    
+
     /// <summary>
     /// Fires the ErrorOccuredEvent with the given text message.
@@ -127 +156 @@
       if (_mlConnector == null) {
         _mlConnector = MatlabApiFactory.CreateMatlabConnector();
+        _mlConnector.ErrorOccuredEvent += ErrorOccured;
       }
     }
@@ -141 +171 @@
 
 
-
     /// <summary>
     /// This method reads all available variables form the selected matlab scirpt and puts them into the list view.
@@ -147 +176 @@
     private async void GetVariableNamesAsync() {
       UpdateStatus("Opening Matlab");
-
       var path = openFileDialog.FileName;
       ProblemTextBox.Text = path;
@@ -156 +184 @@
 
       UpdateStatus("Loading variable names");
-      var variablesListBoxItems = VariablesListBox.Items;
-      variablesListBoxItems.Clear();
-      foreach (var item in variables) {
-        variablesListBoxItems.Add(item, false);
-      }
+      _timeseriesLoader.DisplayVariables(variables);
+      _doubleArraysLoader.DisplayVariables(variables);
       UpdateStatus("Done");
     }
 
-    /// <summary>
-    /// Loads the values of the selected timeseries values and displays them at the preview control.
-    /// </summary>
     private async void LoadValuesAsync() {
+      UpdateStatus("Loading values from Matlab");
       try {
-        PreviewDatasetMatrix.Content = new Dataset();
-
-        UpdateStatus("Loading values from Matlab");
-        var vals = await Task.Run<List<MLTimeseries>>(() => {
-          var values = new List<MLTimeseries>();
-          foreach (KeyValuePair<string, MLDatatype> item in VariablesListBox.CheckedItems) {
-            if (item.Value == MLDatatype.Timeseries) {
-              var val = _mlConnector.GetTimeseries(item.Key);
-              if (val != null) {
-                values.Add(val);
-              }
-            }
-          }
-          return values;
-        });
-
-        UpdateStatus("Converting values");
-        DisplayLoadedValuesAsync(await Task.Run<MLTimeseries>(() => new MLTimeseries(vals)));
-        ErrorTextBox.Text = String.Empty;
-        ErrorTextBox.Visible = false;
-        OkButton.Enabled = true;
+        // As there can be a huge amount of data, it should be freed before reallocating it.
+        OkButton.Enabled = false;
+        _values = new Dataset();
+        PreviewDatasetMatrix.Content = _values;
+        TargetVariableComboBox.DataSource = new List<string>();
+        TargetVariableComboBox.SelectedText = "";
+        GC.Collect();
+        var token = _cts.Token;
+        var ds = await Task.Run<Dataset>(() => _variablesLoader.GetPreviewDataset(_mlConnector, token), token);
+        GC.Collect();
+
+        if (ds != null) {
+          _values = ds;
+          PreviewDatasetMatrix.Content = _values;
+          TargetVariableComboBox.DataSource = _values.VariableNames;
+
+          ErrorTextBox.Text = String.Empty;
+          ErrorTextBox.Visible = false;
+          OkButton.Enabled = true;
+        }        
       } catch (Exception ex) {
         if (ex is IOException || ex is InvalidOperationException || ex is ArgumentException) {
           ErrorOccured(ex.Message);
+        } else if (ex is OutOfMemoryException) {
+          ErrorOccured(ex.Message + " Amount of the given data is too big.");
         } else {
           throw;
@@ -199 +223 @@
       UpdateStatus("Done");
     }
-
-    /// <summary>
-    /// Displays the values of a given timeseries at the preview dataset matrix.
-    /// </summary>
-    /// <param name="timeseries"></param>
-    private async void DisplayLoadedValuesAsync(MLTimeseries timeseries) {
-      PreviewDatasetMatrix.Content = null;
-      IEnumerable<string> variableNamesWithType = GetVariableNamesWithType(timeseries);
-      var values = await Task.Run<double[,]>(() => GetValuesForDataset(timeseries));
-      _values = new Dataset(variableNamesWithType, values);
-      PreviewDatasetMatrix.Content = _values;
-      SetPossibleTargetVariables(timeseries);
-    }
-
-    /// <summary>
-    /// Sets the entries of the combobox for the target variable.
-    /// </summary>
-    /// <param name="timeseries"></param>
-    protected void SetPossibleTargetVariables(MLTimeseries timeseries) {
-      if (timeseries != null) {
-        TargetVariableComboBox.DataSource = timeseries.DataHeader;
-      }
-    }
-
-    /// <summary>
-    /// Returns a list with all selected variable names for the preview dataset.
-    /// </summary>
-    /// <param name="timeseries"></param>
-    /// <returns></returns>
-    private IEnumerable<string> GetVariableNamesWithType(MLTimeseries timeseries) {
-      IList<string> variableNamesWithType = timeseries.DataHeader.ToList();
-      variableNamesWithType.Insert(0, "time");
-      return variableNamesWithType;
-    }
-
-    /// <summary>
-    /// Returns a two dimensional double array which contains the values including the timestamps of the given timeseries.
-    /// Array[value, variable] 
-    /// If the amount of the data is too big, a OutOfMemoryException exception is being thrown. 
-    /// This exception is being cought and a message will be shown at the error message box.
-    /// </summary>
-    /// <param name="timeseries"></param>
-    /// <returns></returns>
-    private double[,] GetValuesForDataset(MLTimeseries timeseries) {
-      try {
-        double[,] datasetValues = new double[timeseries.Count, timeseries.DataHeader.Length + 1];
-
-        int i = 0;
-        foreach (var item in timeseries.Data) {
-          datasetValues[i, 0] = item.Key;
-          for (int j = 1; j < datasetValues.GetLength(1); j++) {
-            datasetValues[i, j] = item.Value[j - 1];
-          }
-          i++;
-        }
-        return datasetValues;
-      } catch (OutOfMemoryException ex) {
-        ErrorOccured(ex.Message + " Amount of the given data is too big.");
-      }
-      return new double[0, timeseries.DataHeader.Length + 1];
-    }
   }
 }