#region License Information
/* HeuristicLab
* Copyright (C) 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;
using System.Collections.Generic;
using System.Drawing;
using System.Globalization;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;
using System.Windows.Forms;
using System.Windows.Forms.DataVisualization.Charting;
using HeuristicLab.Common;
using HeuristicLab.MainForm.WindowsForms;
using HeuristicLab.Visualization.ChartControlsExtensions;
namespace HeuristicLab.Problems.DataAnalysis.Views {
public partial class PartialDependencePlot : UserControl, IPartialDependencePlot {
private ModifiableDataset sharedFixedVariables; // used for synchronizing variable values between charts
private ModifiableDataset internalDataset; // holds the x values for each point drawn
private CancellationTokenSource cancelCurrentRecalculateSource;
private readonly List solutions;
private readonly Dictionary seriesCache;
private readonly Dictionary ciSeriesCache;
private readonly ToolStripMenuItem configToolStripMenuItem;
private readonly PartialDependencePlotConfigurationDialog configurationDialog;
#region Properties
public string XAxisTitle {
get { return chart.ChartAreas[0].AxisX.Title; }
set { chart.ChartAreas[0].AxisX.Title = value; }
}
public string YAxisTitle {
get { return chart.ChartAreas[0].AxisY.Title; }
set { chart.ChartAreas[0].AxisY.Title = value; }
}
public bool ShowLegend {
get { return chart.Legends[0].Enabled; }
set { chart.Legends[0].Enabled = value; }
}
public bool ShowCursor {
get { return chart.Annotations[0].Visible; }
set {
chart.Annotations[0].Visible = value;
if (!value) chart.Titles[0].Text = string.Empty;
}
}
public bool ShowConfigButton {
get { return configurationButton.Visible; }
set { configurationButton.Visible = value; }
}
private int xAxisTicks = 5;
public int XAxisTicks {
get { return xAxisTicks; }
set {
if (value != xAxisTicks) {
xAxisTicks = value;
SetupAxis(chart, chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, FixedXAxisMin, FixedXAxisMax);
RecalculateInternalDataset();
}
}
}
private double? fixedXAxisMin;
public double? FixedXAxisMin {
get { return fixedXAxisMin; }
set {
if ((value.HasValue && fixedXAxisMin.HasValue && !value.Value.IsAlmost(fixedXAxisMin.Value)) || (value.HasValue != fixedXAxisMin.HasValue)) {
fixedXAxisMin = value;
SetupAxis(chart, chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, FixedXAxisMin, FixedXAxisMax);
RecalculateInternalDataset();
// set the vertical line position
if (VerticalLineAnnotation.X <= fixedXAxisMin) {
var axisX = chart.ChartAreas[0].AxisX;
var step = (axisX.Maximum - axisX.Minimum) / drawingSteps;
VerticalLineAnnotation.X = axisX.Minimum + step;
}
}
}
}
private double? fixedXAxisMax;
public double? FixedXAxisMax {
get { return fixedXAxisMax; }
set {
if ((value.HasValue && fixedXAxisMax.HasValue && !value.Value.IsAlmost(fixedXAxisMax.Value)) || (value.HasValue != fixedXAxisMax.HasValue)) {
fixedXAxisMax = value;
SetupAxis(chart, chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, FixedXAxisMin, FixedXAxisMax);
RecalculateInternalDataset();
// set the vertical line position
if (VerticalLineAnnotation.X >= fixedXAxisMax) {
var axisX = chart.ChartAreas[0].AxisX;
var step = (axisX.Maximum - axisX.Minimum) / drawingSteps;
VerticalLineAnnotation.X = axisX.Maximum - step;
}
}
}
}
private int yAxisTicks = 5;
public int YAxisTicks {
get { return yAxisTicks; }
set {
if (value != yAxisTicks) {
yAxisTicks = value;
SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
RecalculateInternalDataset();
}
}
}
private double? fixedYAxisMin;
public double? FixedYAxisMin {
get { return fixedYAxisMin; }
set {
if ((value.HasValue && fixedYAxisMin.HasValue && !value.Value.IsAlmost(fixedYAxisMin.Value)) || (value.HasValue != fixedYAxisMin.HasValue)) {
fixedYAxisMin = value;
SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
}
}
}
private double? fixedYAxisMax;
public double? FixedYAxisMax {
get { return fixedYAxisMax; }
set {
if ((value.HasValue && fixedYAxisMax.HasValue && !value.Value.IsAlmost(fixedYAxisMax.Value)) || (value.HasValue != fixedYAxisMax.HasValue)) {
fixedYAxisMax = value;
SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
}
}
}
private double trainingMin = -1;
private double trainingMax = 1;
private int drawingSteps = 1000;
public int DrawingSteps {
get { return drawingSteps; }
set {
if (value != drawingSteps) {
drawingSteps = value;
RecalculateInternalDataset();
ResizeAllSeriesData();
}
}
}
private string freeVariable;
public string FreeVariable {
get { return freeVariable; }
set {
if (value == freeVariable) return;
if (solutions.Any(s => !s.ProblemData.Dataset.DoubleVariables.Contains(value))) {
throw new ArgumentException("Variable does not exist in the ProblemData of the Solutions.");
}
freeVariable = value;
RecalculateInternalDataset();
}
}
private double yMin;
public double YMin {
get { return yMin; }
}
private double yMax;
public double YMax {
get { return yMax; }
}
public bool IsZoomed {
get { return chart.ChartAreas[0].AxisX.ScaleView.IsZoomed; }
}
private VerticalLineAnnotation VerticalLineAnnotation {
get { return (VerticalLineAnnotation)chart.Annotations.SingleOrDefault(x => x is VerticalLineAnnotation); }
}
internal ElementPosition InnerPlotPosition {
get { return chart.ChartAreas[0].InnerPlotPosition; }
}
#endregion
public event EventHandler ChartPostPaint;
public PartialDependencePlot() {
InitializeComponent();
solutions = new List();
seriesCache = new Dictionary();
ciSeriesCache = new Dictionary();
// Configure axis
chart.CustomizeAllChartAreas();
chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = false;
chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = false;
chart.ChartAreas[0].Axes.ToList().ForEach(x => { x.ScaleView.Zoomable = false; });
configToolStripMenuItem = new ToolStripMenuItem("Configuration");
configToolStripMenuItem.Click += config_Click;
chart.ContextMenuStrip.Items.Add(new ToolStripSeparator());
chart.ContextMenuStrip.Items.Add(configToolStripMenuItem);
configurationDialog = new PartialDependencePlotConfigurationDialog(this);
Disposed += Control_Disposed;
}
private void Control_Disposed(object sender, EventArgs e) {
if (cancelCurrentRecalculateSource != null)
cancelCurrentRecalculateSource.Cancel();
}
public void Configure(IEnumerable solutions, ModifiableDataset sharedFixedVariables, string freeVariable, int drawingSteps, bool initializeAxisRanges = true) {
if (!SolutionsCompatible(solutions))
throw new ArgumentException("Solutions are not compatible with the problem data.");
this.freeVariable = freeVariable;
this.drawingSteps = drawingSteps;
this.solutions.Clear();
this.solutions.AddRange(solutions);
// add an event such that whenever a value is changed in the shared dataset,
// this change is reflected in the internal dataset (where the value becomes a whole column)
if (this.sharedFixedVariables != null) {
this.sharedFixedVariables.ItemChanged -= sharedFixedVariables_ItemChanged;
this.sharedFixedVariables.Reset -= sharedFixedVariables_Reset;
}
this.sharedFixedVariables = sharedFixedVariables;
this.sharedFixedVariables.ItemChanged += sharedFixedVariables_ItemChanged;
this.sharedFixedVariables.Reset += sharedFixedVariables_Reset;
RecalculateTrainingLimits(initializeAxisRanges);
RecalculateInternalDataset();
chart.Series.Clear();
seriesCache.Clear();
ciSeriesCache.Clear();
foreach (var solution in this.solutions) {
var series = CreateSeries(solution);
seriesCache.Add(solution, series.Item1);
if (series.Item2 != null)
ciSeriesCache.Add(solution, series.Item2);
}
// Set cursor and x-axis
// Make sure to allow a small offset to be able to distinguish the vertical line annotation from the axis
var defaultValue = sharedFixedVariables.GetDoubleValue(freeVariable, 0);
var step = (trainingMax - trainingMin) / drawingSteps;
var minimum = chart.ChartAreas[0].AxisX.Minimum;
var maximum = chart.ChartAreas[0].AxisX.Maximum;
if (defaultValue <= minimum)
VerticalLineAnnotation.X = minimum + step;
else if (defaultValue >= maximum)
VerticalLineAnnotation.X = maximum - step;
else
VerticalLineAnnotation.X = defaultValue;
if (ShowCursor)
chart.Titles[0].Text = FreeVariable + " : " + defaultValue.ToString("G5", CultureInfo.CurrentCulture);
ResizeAllSeriesData();
OrderAndColorSeries();
}
public async Task RecalculateAsync(bool updateOnFinish = true, bool resetYAxis = true) {
if (IsDisposed
|| sharedFixedVariables == null || !solutions.Any() || string.IsNullOrEmpty(freeVariable)
|| trainingMin > trainingMax || drawingSteps == 0)
return;
calculationPendingTimer.Start();
// cancel previous recalculate call
if (cancelCurrentRecalculateSource != null)
cancelCurrentRecalculateSource.Cancel();
cancelCurrentRecalculateSource = new CancellationTokenSource();
var cancellationToken = cancelCurrentRecalculateSource.Token;
// Update series
try {
var limits = await UpdateAllSeriesDataAsync(cancellationToken);
chart.Invalidate();
yMin = limits.Lower;
yMax = limits.Upper;
// Set y-axis
if (resetYAxis)
SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
UpdateOutOfTrainingRangeStripLines();
calculationPendingTimer.Stop();
calculationPendingLabel.Visible = false;
if (updateOnFinish)
Update();
} catch (OperationCanceledException) {
} catch (AggregateException ae) {
if (!ae.InnerExceptions.Any(e => e is OperationCanceledException))
throw;
}
}
public void UpdateTitlePosition() {
var title = chart.Titles[0];
var plotArea = InnerPlotPosition;
title.Visible = plotArea.Width != 0;
title.Position.X = plotArea.X + (plotArea.Width / 2);
}
private static void SetupAxis(EnhancedChart chart, Axis axis, double minValue, double maxValue, int ticks, double? fixedAxisMin, double? fixedAxisMax) {
//guard if only one distinct value is present
if (minValue.IsAlmost(maxValue)) {
minValue = minValue - 0.5;
maxValue = minValue + 0.5;
}
double axisMin, axisMax, axisInterval;
ChartUtil.CalculateAxisInterval(minValue, maxValue, ticks, out axisMin, out axisMax, out axisInterval);
axis.Minimum = fixedAxisMin ?? axisMin;
axis.Maximum = fixedAxisMax ?? axisMax;
axis.Interval = (axis.Maximum - axis.Minimum) / ticks;
chart.ChartAreas[0].RecalculateAxesScale();
}
private void RecalculateTrainingLimits(bool initializeAxisRanges) {
//Set min and max to the interval ranges
trainingMin = solutions.Select(s => s.ProblemData.VariableRanges.GetInterval(freeVariable).LowerBound).Max();
trainingMax = solutions.Select(s => s.ProblemData.VariableRanges.GetInterval(freeVariable).UpperBound).Min();
if (initializeAxisRanges) {
double xmin, xmax, xinterval;
//guard if only one distinct value is present
if (trainingMin.IsAlmost(trainingMax))
ChartUtil.CalculateAxisInterval(trainingMin - 0.5, trainingMax + 0.5, XAxisTicks, out xmin, out xmax, out xinterval);
else
ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out xmin, out xmax, out xinterval);
FixedXAxisMin = xmin;
FixedXAxisMax = xmax;
}
}
private void RecalculateInternalDataset() {
if (sharedFixedVariables == null)
return;
// we expand the range in order to get nice tick intervals on the x axis
double xmin, xmax, xinterval;
//guard if only one distinct value is present
if (trainingMin.IsAlmost(trainingMax))
ChartUtil.CalculateAxisInterval(trainingMin - 0.5, trainingMin + 0.5, XAxisTicks, out xmin, out xmax, out xinterval);
else
ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out xmin, out xmax, out xinterval);
if (FixedXAxisMin.HasValue) xmin = FixedXAxisMin.Value;
if (FixedXAxisMax.HasValue) xmax = FixedXAxisMax.Value;
double step = (xmax - xmin) / drawingSteps;
var xvalues = new List();
for (int i = 0; i < drawingSteps; i++)
xvalues.Add(xmin + i * step);
if (sharedFixedVariables == null)
return;
var variables = sharedFixedVariables.VariableNames.ToList();
var values = new List();
foreach (var varName in variables) {
if (varName == FreeVariable) {
values.Add(xvalues);
} else if (sharedFixedVariables.VariableHasType(varName)) {
values.Add(Enumerable.Repeat(sharedFixedVariables.GetDoubleValue(varName, 0), xvalues.Count).ToList());
} else if (sharedFixedVariables.VariableHasType(varName)) {
values.Add(Enumerable.Repeat(sharedFixedVariables.GetStringValue(varName, 0), xvalues.Count).ToList());
}
}
internalDataset = new ModifiableDataset(variables, values);
}
private Tuple CreateSeries(IRegressionSolution solution) {
var series = new Series {
ChartType = SeriesChartType.Line,
Name = solution.ProblemData.TargetVariable + " " + solutions.IndexOf(solution)
};
series.LegendText = series.Name;
var confidenceBoundSolution = solution as IConfidenceRegressionSolution;
Series confidenceIntervalSeries = null;
if (confidenceBoundSolution != null) {
confidenceIntervalSeries = new Series {
ChartType = SeriesChartType.Range,
YValuesPerPoint = 2,
Name = "95% Conf. Interval " + series.Name,
IsVisibleInLegend = false
};
}
return Tuple.Create(series, confidenceIntervalSeries);
}
private void OrderAndColorSeries() {
chart.SuspendRepaint();
chart.Series.Clear();
// Add mean series for applying palette colors
foreach (var solution in solutions) {
chart.Series.Add(seriesCache[solution]);
}
chart.Palette = ChartColorPalette.BrightPastel;
chart.ApplyPaletteColors();
chart.Palette = ChartColorPalette.None;
// Add confidence interval series before its corresponding series for correct z index
foreach (var solution in solutions) {
Series ciSeries;
if (ciSeriesCache.TryGetValue(solution, out ciSeries)) {
var series = seriesCache[solution];
ciSeries.Color = Color.FromArgb(40, series.Color);
int idx = chart.Series.IndexOf(seriesCache[solution]);
chart.Series.Insert(idx, ciSeries);
}
}
chart.ResumeRepaint(true);
}
private async Task UpdateAllSeriesDataAsync(CancellationToken cancellationToken) {
var updateTasks = solutions.Select(solution => UpdateSeriesDataAsync(solution, cancellationToken));
double min = double.MaxValue, max = double.MinValue;
foreach (var update in updateTasks) {
var limit = await update;
if (limit.Lower < min) min = limit.Lower;
if (limit.Upper > max) max = limit.Upper;
}
return new DoubleLimit(min, max);
}
private Task UpdateSeriesDataAsync(IRegressionSolution solution, CancellationToken cancellationToken) {
return Task.Run(() => {
var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList();
var yvalues = solution.Model.GetEstimatedValues(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList();
double min = double.MaxValue, max = double.MinValue;
var series = seriesCache[solution];
for (int i = 0; i < xvalues.Count; i++) {
series.Points[i].SetValueXY(xvalues[i], yvalues[i]);
if (yvalues[i] < min) min = yvalues[i];
if (yvalues[i] > max) max = yvalues[i];
}
cancellationToken.ThrowIfCancellationRequested();
var confidenceBoundSolution = solution as IConfidenceRegressionSolution;
if (confidenceBoundSolution != null) {
var confidenceIntervalSeries = ciSeriesCache[solution];
var variances = confidenceBoundSolution.Model.GetEstimatedVariances(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList();
for (int i = 0; i < xvalues.Count; i++) {
var lower = yvalues[i] - 1.96 * Math.Sqrt(variances[i]);
var upper = yvalues[i] + 1.96 * Math.Sqrt(variances[i]);
confidenceIntervalSeries.Points[i].SetValueXY(xvalues[i], lower, upper);
if (lower < min) min = lower;
if (upper > max) max = upper;
}
}
cancellationToken.ThrowIfCancellationRequested();
return new DoubleLimit(min, max);
}, cancellationToken);
}
private void ResizeAllSeriesData() {
if (internalDataset == null)
return;
var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList();
foreach (var solution in solutions)
ResizeSeriesData(solution, xvalues);
}
private void ResizeSeriesData(IRegressionSolution solution, IList xvalues = null) {
if (xvalues == null)
xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList();
var series = seriesCache[solution];
series.Points.SuspendUpdates();
series.Points.Clear();
for (int i = 0; i < xvalues.Count; i++)
series.Points.Add(new DataPoint(xvalues[i], 0.0));
series.Points.ResumeUpdates();
Series confidenceIntervalSeries;
if (ciSeriesCache.TryGetValue(solution, out confidenceIntervalSeries)) {
confidenceIntervalSeries.Points.SuspendUpdates();
confidenceIntervalSeries.Points.Clear();
for (int i = 0; i < xvalues.Count; i++)
confidenceIntervalSeries.Points.Add(new DataPoint(xvalues[i], new[] { -1.0, 1.0 }));
confidenceIntervalSeries.Points.ResumeUpdates();
}
}
public async Task AddSolutionAsync(IRegressionSolution solution) {
if (!SolutionsCompatible(solutions.Concat(new[] { solution })))
throw new ArgumentException("The solution is not compatible with the problem data.");
if (solutions.Contains(solution))
return;
solutions.Add(solution);
RecalculateTrainingLimits(true);
var series = CreateSeries(solution);
seriesCache.Add(solution, series.Item1);
if (series.Item2 != null)
ciSeriesCache.Add(solution, series.Item2);
ResizeSeriesData(solution);
OrderAndColorSeries();
await RecalculateAsync();
var args = new EventArgs(solution);
OnSolutionAdded(this, args);
}
public async Task RemoveSolutionAsync(IRegressionSolution solution) {
if (!solutions.Remove(solution))
return;
RecalculateTrainingLimits(true);
seriesCache.Remove(solution);
ciSeriesCache.Remove(solution);
await RecalculateAsync();
var args = new EventArgs(solution);
OnSolutionRemoved(this, args);
}
private static bool SolutionsCompatible(IEnumerable solutions) {
var refSolution = solutions.First();
var refSolVars = refSolution.ProblemData.Dataset.VariableNames;
foreach (var solution in solutions.Skip(1)) {
var variables1 = solution.ProblemData.Dataset.VariableNames;
if (!variables1.All(refSolVars.Contains))
return false;
foreach (var factorVar in variables1.Where(solution.ProblemData.Dataset.VariableHasType)) {
var distinctVals = refSolution.ProblemData.Dataset.GetStringValues(factorVar).Distinct();
if (solution.ProblemData.Dataset.GetStringValues(factorVar).Any(val => !distinctVals.Contains(val))) return false;
}
}
return true;
}
private void UpdateOutOfTrainingRangeStripLines() {
var axisX = chart.ChartAreas[0].AxisX;
var lowerStripLine = axisX.StripLines[0];
var upperStripLine = axisX.StripLines[1];
lowerStripLine.IntervalOffset = axisX.Minimum;
lowerStripLine.StripWidth = Math.Abs(trainingMin - axisX.Minimum);
upperStripLine.IntervalOffset = trainingMax;
upperStripLine.StripWidth = Math.Abs(axisX.Maximum - trainingMax);
}
#region Events
public event EventHandler> SolutionAdded;
public void OnSolutionAdded(object sender, EventArgs args) {
var added = SolutionAdded;
if (added == null) return;
added(sender, args);
}
public event EventHandler> SolutionRemoved;
public void OnSolutionRemoved(object sender, EventArgs args) {
var removed = SolutionRemoved;
if (removed == null) return;
removed(sender, args);
}
public event EventHandler VariableValueChanged;
public void OnVariableValueChanged(object sender, EventArgs args) {
var changed = VariableValueChanged;
if (changed == null) return;
changed(sender, args);
}
public event EventHandler ZoomChanged;
public void OnZoomChanged(object sender, EventArgs args) {
var changed = ZoomChanged;
if (changed == null) return;
changed(sender, args);
}
private void sharedFixedVariables_ItemChanged(object o, EventArgs e) {
if (o != sharedFixedVariables) return;
var variables = sharedFixedVariables.VariableNames.ToList();
var rowIndex = e.Value;
var columnIndex = e.Value2;
var variableName = variables[columnIndex];
if (variableName == FreeVariable) return;
if (internalDataset.VariableHasType(variableName)) {
var v = sharedFixedVariables.GetDoubleValue(variableName, rowIndex);
var values = new List(Enumerable.Repeat(v, internalDataset.Rows));
internalDataset.ReplaceVariable(variableName, values);
} else if (internalDataset.VariableHasType(variableName)) {
var v = sharedFixedVariables.GetStringValue(variableName, rowIndex);
var values = new List(Enumerable.Repeat(v, internalDataset.Rows));
internalDataset.ReplaceVariable(variableName, values);
} else {
// unsupported type
throw new NotSupportedException();
}
}
private void sharedFixedVariables_Reset(object sender, EventArgs e) {
var newValue = sharedFixedVariables.GetDoubleValue(FreeVariable, 0);
VerticalLineAnnotation.X = newValue;
UpdateCursor(); // triggers update of InternalDataset
}
private void chart_AnnotationPositionChanging(object sender, AnnotationPositionChangingEventArgs e) {
var step = (trainingMax - trainingMin) / drawingSteps;
double newLocation = step * (long)Math.Round(e.NewLocationX / step);
var axisX = chart.ChartAreas[0].AxisX;
if (newLocation >= axisX.Maximum)
newLocation = axisX.Maximum - step;
if (newLocation <= axisX.Minimum)
newLocation = axisX.Minimum + step;
e.NewLocationX = newLocation;
UpdateCursor();
}
private void chart_AnnotationPositionChanged(object sender, EventArgs e) {
UpdateCursor();
}
private void UpdateCursor() {
var x = VerticalLineAnnotation.X;
if (!sharedFixedVariables.GetDoubleValue(FreeVariable, 0).IsAlmost(x))
sharedFixedVariables.SetVariableValue(x, FreeVariable, 0);
if (ShowCursor) {
chart.Titles[0].Text = FreeVariable + " : " + x.ToString("G5", CultureInfo.CurrentCulture);
chart.Update();
}
OnVariableValueChanged(this, EventArgs.Empty);
}
private void chart_MouseMove(object sender, MouseEventArgs e) {
bool hitCursor = chart.HitTest(e.X, e.Y).ChartElementType == ChartElementType.Annotation;
chart.Cursor = hitCursor ? Cursors.VSplit : Cursors.Default;
}
private async void chart_DragDrop(object sender, DragEventArgs e) {
var data = e.Data.GetData(HeuristicLab.Common.Constants.DragDropDataFormat);
if (data != null) {
var solution = data as IRegressionSolution;
if (!solutions.Contains(solution))
await AddSolutionAsync(solution);
}
}
private void chart_DragEnter(object sender, DragEventArgs e) {
if (!e.Data.GetDataPresent(HeuristicLab.Common.Constants.DragDropDataFormat)) return;
e.Effect = DragDropEffects.None;
var data = e.Data.GetData(HeuristicLab.Common.Constants.DragDropDataFormat);
var regressionSolution = data as IRegressionSolution;
if (regressionSolution != null) {
e.Effect = DragDropEffects.Copy;
}
}
private void calculationPendingTimer_Tick(object sender, EventArgs e) {
calculationPendingLabel.Visible = true;
Update();
}
private void config_Click(object sender, EventArgs e) {
configurationDialog.ShowDialog(this);
OnZoomChanged(this, EventArgs.Empty);
}
private void chart_SelectionRangeChanged(object sender, CursorEventArgs e) {
OnZoomChanged(this, EventArgs.Empty);
}
private void chart_Resize(object sender, EventArgs e) {
UpdateTitlePosition();
}
private void chart_PostPaint(object sender, ChartPaintEventArgs e) {
if (ChartPostPaint != null)
ChartPostPaint(this, EventArgs.Empty);
}
#endregion
}
}