#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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 .
*/
#endregion
using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Drawing;
using System.Data;
using System.Linq;
using System.Text;
using System.Windows.Forms;
using System.Windows.Forms.DataVisualization.Charting;
using HeuristicLab.Common;
using System.Collections.Specialized;
using HeuristicLab.MainForm;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.MainForm.WindowsForms;
namespace HeuristicLab.Problems.DataAnalysis.Views {
[View("Scatter Plot View")]
[Content(typeof(DataAnalysisSolution), true)]
public partial class ScatterPlotView : AsynchronousContentView {
private const string DEFAULT_CAPTION = "Scatter Plot";
private const string ALL_SERIES = "All Samples";
private const string TRAINING_SERIES = "Training Samples";
private const string TEST_SERIES = "Test Samples";
public new DataAnalysisSolution Content {
get { return (DataAnalysisSolution)base.Content; }
set { base.Content = value; }
}
public ScatterPlotView()
: base() {
InitializeComponent();
this.Caption = DEFAULT_CAPTION;
this.chart.Series.Add(ALL_SERIES);
this.chart.Series[ALL_SERIES].LegendText = ALL_SERIES;
this.chart.Series[ALL_SERIES].ChartType = SeriesChartType.FastPoint;
this.chart.Series.Add(TRAINING_SERIES);
this.chart.Series[TRAINING_SERIES].LegendText = TRAINING_SERIES;
this.chart.Series[TRAINING_SERIES].ChartType = SeriesChartType.FastPoint;
this.chart.Series.Add(TEST_SERIES);
this.chart.Series[TEST_SERIES].LegendText = TEST_SERIES;
this.chart.Series[TEST_SERIES].ChartType = SeriesChartType.FastPoint;
this.chart.TextAntiAliasingQuality = TextAntiAliasingQuality.High;
this.chart.AxisViewChanged += new EventHandler(chart_AxisViewChanged);
//configure axis
this.chart.ChartAreas[0].AxisX.Title = "Estimated Values";
this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
this.chart.ChartAreas[0].CursorX.Interval = 0;
this.chart.ChartAreas[0].CursorY.Interval = 0;
this.chart.ChartAreas[0].AxisY.Title = "Target Values";
this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
this.chart.ChartAreas[0].AxisY.IsStartedFromZero = true;
}
protected override void RegisterContentEvents() {
base.RegisterContentEvents();
Content.EstimatedValuesChanged += new EventHandler(Content_EstimatedValuesChanged);
Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
}
protected override void DeregisterContentEvents() {
base.DeregisterContentEvents();
Content.EstimatedValuesChanged -= new EventHandler(Content_EstimatedValuesChanged);
Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
}
void Content_ProblemDataChanged(object sender, EventArgs e) {
UpdateChart();
}
void Content_EstimatedValuesChanged(object sender, EventArgs e) {
UpdateSeries();
}
protected override void OnContentChanged() {
base.OnContentChanged();
UpdateChart();
}
private void UpdateChart() {
if (InvokeRequired) Invoke((Action)UpdateChart);
else {
if (Content != null) {
this.Caption = Content.ItemName + " " + DEFAULT_CAPTION;
this.UpdateSeries();
if (!this.chart.Series.Any(s => s.Points.Count > 0))
this.ToggleSeriesData(this.chart.Series[TRAINING_SERIES]);
} else {
this.Caption = DEFAULT_CAPTION;
this.ClearChart();
}
}
}
private void UpdateSeries() {
if (InvokeRequired) Invoke((Action)UpdateSeries);
else {
string targetVariableName = Content.ProblemData.TargetVariable.Value;
Dataset dataset = Content.ProblemData.Dataset;
int trainingStart = Content.ProblemData.TrainingSamplesStart.Value;
int trainingEnd = Content.ProblemData.TrainingSamplesEnd.Value;
int testStart = Content.ProblemData.TestSamplesStart.Value;
int testEnd = Content.ProblemData.TestSamplesEnd.Value;
if (this.chart.Series[ALL_SERIES].Points.Count > 0)
this.chart.Series[ALL_SERIES].Points.DataBindXY(Content.EstimatedValues.ToArray(), "",
dataset[targetVariableName], "");
if (this.chart.Series[TRAINING_SERIES].Points.Count > 0)
this.chart.Series[TRAINING_SERIES].Points.DataBindXY(Content.EstimatedTrainingValues.ToArray(), "",
dataset.GetVariableValues(targetVariableName, trainingStart, trainingEnd), "");
if (this.chart.Series[TEST_SERIES].Points.Count > 0)
this.chart.Series[TEST_SERIES].Points.DataBindXY(Content.EstimatedTestValues.ToArray(), "",
dataset.GetVariableValues(targetVariableName, testStart, testEnd), "");
double max = Math.Max(Content.EstimatedValues.Max(), dataset.GetMax(targetVariableName));
double min = Math.Min(Content.EstimatedValues.Min(), dataset.GetMin(targetVariableName));
max = Math.Ceiling(max) * 1.2;
min = Math.Floor(min) * 0.8;
this.chart.ChartAreas[0].AxisX.Maximum = max;
this.chart.ChartAreas[0].AxisX.Minimum = min;
this.chart.ChartAreas[0].AxisY.Maximum = max;
this.chart.ChartAreas[0].AxisY.Minimum = min;
}
}
private void ClearChart() {
this.chart.Series[ALL_SERIES].Points.Clear();
this.chart.Series[TRAINING_SERIES].Points.Clear();
this.chart.Series[TEST_SERIES].Points.Clear();
}
private void ToggleSeriesData(Series series) {
if (series.Points.Count > 0) { //checks if series is shown
if (this.chart.Series.Any(s => s != series && s.Points.Count > 0)) {
series.Points.Clear();
}
} else if (Content != null) {
string targetVariableName = Content.ProblemData.TargetVariable.Value;
Dataset dataset = Content.ProblemData.Dataset;
int trainingStart = Content.ProblemData.TrainingSamplesStart.Value;
int trainingEnd = Content.ProblemData.TrainingSamplesEnd.Value;
int testStart = Content.ProblemData.TestSamplesStart.Value;
int testEnd = Content.ProblemData.TestSamplesEnd.Value;
IEnumerable predictedValues = null;
IEnumerable targetValues = null;
switch (series.Name) {
case ALL_SERIES:
predictedValues = Content.EstimatedValues;
targetValues = dataset[targetVariableName];
break;
case TRAINING_SERIES:
predictedValues = Content.EstimatedTrainingValues;
targetValues = dataset.GetVariableValues(targetVariableName, trainingStart, trainingEnd);
break;
case TEST_SERIES:
predictedValues = Content.EstimatedTestValues;
targetValues = dataset.GetVariableValues(targetVariableName, testStart, testEnd);
break;
}
series.Points.DataBindXY(predictedValues, "", targetValues, "");
this.chart.Legends[series.Legend].ForeColor = Color.Black;
}
}
private void chart_MouseDown(object sender, MouseEventArgs e) {
HitTestResult result = chart.HitTest(e.X, e.Y);
if (result.ChartElementType == ChartElementType.LegendItem) {
this.ToggleSeriesData(result.Series);
}
}
private void chart_MouseMove(object sender, MouseEventArgs e) {
HitTestResult result = chart.HitTest(e.X, e.Y);
if (result.ChartElementType == ChartElementType.LegendItem)
this.Cursor = Cursors.Hand;
else
this.Cursor = Cursors.Default;
}
private void chart_AxisViewChanged(object sender, System.Windows.Forms.DataVisualization.Charting.ViewEventArgs e) {
this.chart.ChartAreas[0].AxisX.ScaleView.Size = e.NewSize;
this.chart.ChartAreas[0].AxisY.ScaleView.Size = e.NewSize;
}
private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[ALL_SERIES].Points.Count == 0 ? Color.Gray : Color.Black;
e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[TRAINING_SERIES].Points.Count == 0 ? Color.Gray : Color.Black;
e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[TEST_SERIES].Points.Count == 0 ? Color.Gray : Color.Black;
}
}
}