source: branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionInteractiveRangeEstimatorView.cs @ 13823

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;
using System.Windows.Forms.DataVisualization.Charting;
using HeuristicLab.Collections;
using HeuristicLab.Data;
using HeuristicLab.MainForm;
using HeuristicLab.MainForm.WindowsForms;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.DataAnalysis.Views;
using HeuristicLab.Visualization.ChartControlsExtensions;

namespace HeuristicLab.Algorithms.DataAnalysis.Views {
  [View("Interactive Estimator")]
  [Content(typeof(GaussianProcessRegressionSolution))]
  public partial class GaussianProcessRegressionSolutionInteractiveRangeEstimatorView
    : DataAnalysisSolutionEvaluationView {

    private const int DrawingSteps = 1000;

    private const string EstimatedMeanSeriesName = "Estimated Mean";
    private const string EstimatedVarianceSeriesName = "95% Conficence Interval";

    private readonly List<string> dimensionNames;
    private readonly ObservableList<DensityTrackbar> dimensionTrackbars;

    private int ActiveDimension {
      get { return dimensionTrackbars.FindIndex(tb => tb.Checked); }
    }

    public new GaussianProcessRegressionSolution Content {
      get { return (GaussianProcessRegressionSolution)base.Content; }
      set { base.Content = value; }
    }

    public GaussianProcessRegressionSolutionInteractiveRangeEstimatorView()
      : base() {
      dimensionNames = new List<string>();

      dimensionTrackbars = new ObservableList<DensityTrackbar>();
      dimensionTrackbars.ItemsAdded += (sender, args) => {
        ForEach(args.Items.Select(i => i.Value), RegisterEvents);
      };
      dimensionTrackbars.ItemsRemoved += (sender, args) => {
        ForEach(args.Items.Select(i => i.Value), DeregisterEvents);
      };
      dimensionTrackbars.CollectionReset += (sender, args) => {
        ForEach(args.OldItems.Select(i => i.Value), DeregisterEvents);
        ForEach(args.Items.Select(i => i.Value), RegisterEvents);
      };


      InitializeComponent();

      // Avoid additional horizontal scrollbar
      var vertScrollWidth = SystemInformation.VerticalScrollBarWidth;
      tableLayoutPanel.Padding = new Padding(0, 0, vertScrollWidth, 0);

      // Configure axis
      chart.CustomizeAllChartAreas();
      chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
      chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
      chart.ChartAreas[0].CursorX.Interval = 1;

      chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
      chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
      chart.ChartAreas[0].CursorY.Interval = 0;
    }

    private void RedrawChart() {
      chart.Series.Clear();
      chart.ChartAreas[0].AxisX.StripLines.Clear();
      if (Content == null || ActiveDimension < 0) return;

      double minX = dimensionTrackbars[ActiveDimension].Limits.Lower;
      double maxX = dimensionTrackbars[ActiveDimension].Limits.Upper;
      decimal stepSize = (decimal)((maxX - minX) / DrawingSteps);

      // Build dataset
      var activeXs = Enumerable.Range(0, DrawingSteps).Select(i => (decimal)minX + i * stepSize).ToList();
      var fixedXs = dimensionTrackbars.Select(tb => tb.Value).ToList();
      var values = new double[DrawingSteps, dimensionNames.Count];
      for (int r = 0; r < DrawingSteps; r++) {
        for (int c = 0; c < dimensionNames.Count; c++) {
          values[r, c] = (double)(c == ActiveDimension ? activeXs[r] : fixedXs[c]);
        }
      }
      var dataset = new Dataset(dimensionNames, values);

      // Estimations
      var model = Content.Model;
      var means = model.GetEstimatedValues(dataset, Enumerable.Range(0, DrawingSteps)).ToList();
      var variances = model.GetEstimatedVariances(dataset, Enumerable.Range(0, DrawingSteps)).ToList();

      // Charting config
      chart.ChartAreas[0].AxisX.Minimum = minX;
      chart.ChartAreas[0].AxisX.Maximum = maxX;
      chart.ChartAreas[0].AxisX.Interval = (maxX - minX) / 10;

      // ToDo only databind and put config in codebehind
      chart.Series.Add(EstimatedVarianceSeriesName);
      chart.Series[EstimatedVarianceSeriesName].LegendText = EstimatedVarianceSeriesName;
      chart.Series[EstimatedVarianceSeriesName].ChartType = SeriesChartType.Range;
      chart.Series[EstimatedVarianceSeriesName].EmptyPointStyle.Color = chart.Series[EstimatedVarianceSeriesName].Color;

      chart.Series.Add(EstimatedMeanSeriesName);
      chart.Series[EstimatedMeanSeriesName].LegendText = EstimatedMeanSeriesName;
      chart.Series[EstimatedMeanSeriesName].ChartType = SeriesChartType.FastLine;

      // Charting databind
      var lower = means.Zip(variances, GetLowerConfBound).ToList();
      var upper = means.Zip(variances, GetUpperConfBound).ToList();
      chart.Series[EstimatedVarianceSeriesName].Points.DataBindXY(activeXs, lower, upper);
      chart.Series[EstimatedMeanSeriesName].Points.DataBindXY(activeXs, means);

      // Update StripLines
      var trainingValues = Content.ProblemData.Dataset.GetDoubleValues(dimensionNames[ActiveDimension],
        Content.ProblemData.TrainingIndices);
      var trainingRange = new DoubleRange(trainingValues.Min(), trainingValues.Max());
      if (minX < trainingRange.Start)
        CreateAndAddStripLine(minX, trainingRange.Start, Color.FromArgb(40, 223, 58, 2), Color.Transparent);
      if (maxX > trainingRange.End)
        CreateAndAddStripLine(trainingRange.End, maxX, Color.FromArgb(40, 223, 58, 2), Color.Transparent);

      // Update axis description
      chart.ChartAreas[0].AxisX.Title = dimensionNames[ActiveDimension];
    }

    private void CreateAndAddStripLine(double start, double end, Color color, Color secondColor) {
      StripLine stripLine = new StripLine {
        BackColor = color,
        BackSecondaryColor = secondColor,
        StripWidth = end - start,
        IntervalOffset = start
      };
      chart.ChartAreas[0].AxisX.StripLines.Add(stripLine);
    }

    private void UpdateConfigurationControls() {
      tableLayoutPanel.SuspendRepaint();
      tableLayoutPanel.SuspendLayout();

      tableLayoutPanel.RowCount = 0;
      tableLayoutPanel.Controls.Clear();

      dimensionNames.Clear();
      dimensionTrackbars.Clear();

      if (Content == null) {
        tableLayoutPanel.ResumeLayout(true);
        tableLayoutPanel.ResumeRepaint(true);
        return;
      }

      dimensionNames.AddRange(Content.ProblemData.AllowedInputVariables);
      var ranges = new List<DoubleLimit>();
      for (int i = 0; i < dimensionNames.Count; i++) {
        var values = Content.ProblemData.Dataset.GetDoubleValues(dimensionNames[i], Content.ProblemData.AllIndices);
        double min, max, interval;
        ChartUtil.CalculateAxisInterval(values.Min(), values.Max(), 10, out min, out max, out interval);
        ranges.Add(new DoubleLimit(min, max));
      }

      tableLayoutPanel.RowCount = dimensionNames.Count;
      while (tableLayoutPanel.RowStyles.Count < dimensionNames.Count)
        tableLayoutPanel.RowStyles.Add(new RowStyle(SizeType.AutoSize));

      for (int i = 0; i < dimensionNames.Count; i++) {
        var name = dimensionNames[i];
        var trainingData =
          Content.ProblemData.Dataset.GetDoubleValues(name, Content.ProblemData.TrainingIndices).ToList();

        var dimensionTrackbar = new DensityTrackbar(name, ranges[i], trainingData);

        // events registered automatically
        dimensionTrackbars.Add(dimensionTrackbar);

        dimensionTrackbar.Anchor = AnchorStyles.Top | AnchorStyles.Left | AnchorStyles.Right;
        tableLayoutPanel.Controls.Add(dimensionTrackbar, 0, i);
      }

      if (dimensionTrackbars.Any())
        dimensionTrackbars.First().Checked = true;

      tableLayoutPanel.ResumeLayout(true);
      tableLayoutPanel.ResumeRepaint(true);
    }

    private void RegisterEvents(DensityTrackbar trackbar) {
      trackbar.CheckedChanged += DimensionTrackbar_CheckedChanged;
      trackbar.ValueChanged += DimensionTrackbar_ValueChanged;
      trackbar.LimitsChanged += DimensionTrackbar_LimitsChanged;
    }

    private void DeregisterEvents(DensityTrackbar trackbar) {
      trackbar.CheckedChanged -= DimensionTrackbar_CheckedChanged;
      trackbar.ValueChanged -= DimensionTrackbar_ValueChanged;
      trackbar.LimitsChanged -= DimensionTrackbar_LimitsChanged;
    }

    private void DimensionTrackbar_CheckedChanged(object sender, EventArgs e) {
      var trackBarSender = sender as DensityTrackbar;
      if (trackBarSender == null || !trackBarSender.Checked) return;
      // Uncheck all others
      foreach (var tb in dimensionTrackbars.Except(new[] { trackBarSender }))
        tb.Checked = false;
      RedrawChart();
    }

    private void DimensionTrackbar_LimitsChanged(object sender, EventArgs e) {
      RedrawChart();
    }

    private void DimensionTrackbar_ValueChanged(object sender, EventArgs e) {
      RedrawChart();
    }

    #region Events

    protected override void RegisterContentEvents() {
      base.RegisterContentEvents();
      Content.ModelChanged += Content_ModelChanged;
      Content.ProblemDataChanged += Content_ProblemDataChanged;
    }

    protected override void DeregisterContentEvents() {
      base.DeregisterContentEvents();
      Content.ModelChanged -= Content_ModelChanged;
      Content.ProblemDataChanged -= Content_ProblemDataChanged;
    }

    protected override void OnContentChanged() {
      base.OnContentChanged();
      UpdateConfigurationControls();
      RedrawChart();
    }

    private void Content_ModelChanged(object sender, EventArgs e) {
      RedrawChart();
    }

    private void Content_ProblemDataChanged(object sender, EventArgs e) {
      UpdateConfigurationControls();
      RedrawChart();
    }

    private void Chart_MouseDoubleClick(object sender, MouseEventArgs e) {
      var result = chart.HitTest(e.X, e.Y);
      if (true || result.ChartArea != null && (result.ChartElementType == ChartElementType.PlottingArea ||
                                               result.ChartElementType == ChartElementType.Gridlines) ||
          result.ChartElementType == ChartElementType.StripLines) {
        foreach (var axis in result.ChartArea.Axes)
          axis.ScaleView.ZoomReset(int.MaxValue);
      }
    }

    private void chart_MouseMove(object sender, MouseEventArgs e) {
      //HitTestResult result = chart.HitTest(e.X, e.Y);
      //if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
      //  Cursor = Cursors.Hand;
      //else
      //  Cursor = Cursors.Default;
    }

    private void chart_MouseDown(object sender, MouseEventArgs e) {
      //HitTestResult result = chart.HitTest(e.X, e.Y);
      //if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
      //  ToggleSeriesData(result.Series);
      //}
    }

    private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
      //if (chart.Series.Count != 4) return;
      //e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[EstimatedMeanSeriesName].Points.Count == 0 ? Color.Gray : Color.Black;
      //e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
      //e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
      //e.LegendItems[3].Cells[1].ForeColor = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
    }

    #endregion

    #region Helper

    private double GetLowerConfBound(double m, double s2) {
      return m - 1.96 * Math.Sqrt(s2);
    }

    private double GetUpperConfBound(double m, double s2) {
      return m + 1.96 * Math.Sqrt(s2);
    }

    public static void ForEach<T>(IEnumerable<T> source, Action<T> action) {
      foreach (T item in source)
        action(item);
    }

    #endregion
  }
}