private static ScatterSeries CreateRandomScatterSeries(int n, MarkerType markerType, bool setSize, bool setValue, LinearColorAxis colorAxis)
{
var s1 = new ScatterSeries
{
MarkerType = markerType,
MarkerSize = 6,
ColorAxisKey = colorAxis != null ? colorAxis.Key : "nix"
};
var random = new Random(13);
for (int i = 0; i < n; i++)
{
var p = new ScatterPoint((random.NextDouble() * 2.2) - 1.1, random.NextDouble());
if (setSize)
{
p.Size = (random.NextDouble() * 5) + 5;
}
if (setValue)
{
p.Value = (random.NextDouble() * 2.2) - 1.1;
}
s1.Points.Add(p);
}
return s1;
}
private static PlotModel CreateRandomScatterSeriesWithColorAxisPlotModel(int n, OxyPalette palette, MarkerType markerType, AxisPosition colorAxisPosition, OxyColor highColor, OxyColor lowColor)
{
var model = new PlotModel { Title = string.Format("ScatterSeries (n={0})", n), Background = OxyColors.LightGray };
var colorAxis = new LinearColorAxis { Position = colorAxisPosition, Palette = palette, Minimum = -1, Maximum = 1, HighColor = highColor, LowColor = lowColor };
model.Axes.Add(colorAxis);
model.Series.Add(CreateRandomScatterSeries(n, markerType, false, true, colorAxis));
return model;
}
public static PlotModel TwoScatterSeries()
{
var model = new PlotModel { Title = "Two ScatterSeries (with and without values)", Subtitle = "With values (squares), without values (triangles)" };
var colorAxis = new LinearColorAxis { Position = AxisPosition.Right, Key = "ColorAxis", Palette = OxyPalettes.Jet(30), Minimum = -1, Maximum = 1 };
model.Axes.Add(colorAxis);
model.Series.Add(CreateRandomScatterSeries(50, MarkerType.Triangle, false, false, null));
model.Series.Add(CreateRandomScatterSeries(50, MarkerType.Square, false, true, colorAxis));
return model;
}
public Heatmap(string title, string xTitle, string yTitle, double[,] data)
: base(title)
{
var model = new PlotModel
{
Title = title,
};
OxyPalette palette = OxyPalettes.Hot(200);
var colorAxis = new LinearColorAxis
{
InvalidNumberColor = OxyColors.Gray,
Position = AxisPosition.Right,
Palette = palette
};
model.Axes.Add(colorAxis);
var xAxis = new LinearAxis
{
Position = AxisPosition.Bottom,
Title = xTitle
};
model.Axes.Add(xAxis);
var yAxis = new LinearAxis
{
Title = yTitle
};
model.Axes.Add(yAxis);
var series = new HeatMapSeries
{
X0 = 0,
X1 = 1,
Y0 = 0,
Y1 = 1,
FontSize = .2
};
int width = data.GetLength(0);
int height = data.GetLength(1);
series.Data = new double[width, height];
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
series.Data[i, j] = data[i, j];
}
}
model.Series.Add(series);
Model = model;
}
public static PlotModel ConfusionMatrix()
{
// Example provided by Pau Climent Pérez
// See also http://en.wikipedia.org/wiki/Confusion_matrix
var data = new double[3, 3];
data[0, 0] = 1;
data[1, 1] = 0.8;
data[1, 2] = 0.2;
data[2, 2] = 1;
// I guess this is where the confusion comes from?
data = data.Transpose();
string[] cat1 = { "class A", "class B", "class C" };
var model = new PlotModel { Title = "Confusion Matrix" };
var palette = OxyPalette.Interpolate(50, OxyColors.White, OxyColors.Black);
var lca = new LinearColorAxis { Position = AxisPosition.Right, Palette = palette, HighColor = OxyColors.White, LowColor = OxyColors.White };
model.Axes.Add(lca);
var axis1 = new CategoryAxis { Position = AxisPosition.Top, Title = "Actual class" };
axis1.Labels.AddRange(cat1);
model.Axes.Add(axis1);
// We invert this axis, so that they look "symmetrical"
var axis2 = new CategoryAxis { Position = AxisPosition.Left, Title = "Predicted class" };
axis2.Labels.AddRange(cat1);
axis2.Angle = -90;
axis2.StartPosition = 1;
axis2.EndPosition = 0;
model.Axes.Add(axis2);
var hms = new HeatMapSeries
{
Data = data,
Interpolate = false,
LabelFontSize = 0.25,
X0 = 0,
X1 = data.GetLength(1) - 1,
Y0 = 0,
Y1 = data.GetLength(0) - 1,
};
model.Series.Add(hms);
return model;
}
public static PlotModel ColorCodingOnScatterPlots()
{
var model = new PlotModel { Title = "Colour coding on scatter plots" };
var colorAxis = new LinearColorAxis { Position = AxisPosition.Right, Palette = OxyPalettes.Jet(500), Minimum = 0, Maximum = 5, HighColor = OxyColors.Gray, LowColor = OxyColors.Black };
model.Axes.Add(colorAxis);
var s4 = new ScatterSeries { MarkerType = MarkerType.Circle };
s4.Points.Add(new ScatterPoint(3, 5, 5, 0));
s4.Points.Add(new ScatterPoint(5, 5, 7, 0));
s4.Points.Add(new ScatterPoint(2, 4, 5, 0.3));
s4.Points.Add(new ScatterPoint(3, 3, 8, 0));
s4.Points.Add(new ScatterPoint(3, 2, 5, 0));
s4.Points.Add(new ScatterPoint(3, 5, 8, 1));
s4.Points.Add(new ScatterPoint(2, 2, 3, 5));
s4.Points.Add(new ScatterPoint(1, 4, 4, 1));
s4.Points.Add(new ScatterPoint(4, 3, 5, 3));
s4.Points.Add(new ScatterPoint(0, 0, 1, 1));
s4.Points.Add(new ScatterPoint(8, 8, 1, 1));
model.Series.Add(s4);
return model;
}
public void TestMsFeatureScatterPlot(string path1, string path2, string pngPath)
{
// Convert relative paths to absolute paths
path1 = GetPath(path1);
path2 = GetPath(path2);
pngPath = GetPath(pngPath);
var fiOutput = new FileInfo(pngPath);
var didirectory = fiOutput.Directory;
if (didirectory == null)
throw new DirectoryNotFoundException(pngPath);
if (!didirectory.Exists)
didirectory.Create();
var aligner = new LcmsWarpFeatureAligner();
var baselineMs = UmcLoaderFactory.LoadMsFeatureData(path1);
var aligneeMs = UmcLoaderFactory.LoadMsFeatureData(path2);
var finder = FeatureFinderFactory.CreateFeatureFinder(FeatureFinderType.TreeBased);
var tolerances = new FeatureTolerances
{
FragmentationWindowSize = .5,
Mass = 13,
DriftTime = .3,
Net = .01
};
var options = new LcmsFeatureFindingOptions(tolerances);
options.MaximumNetRange = .002;
var baseline = finder.FindFeatures(baselineMs, options, null);
var alignee = finder.FindFeatures(aligneeMs, options, null);
var alignmentResults = aligner.Align(baseline, alignee);
var plotModel1 = new PlotModel
{
Subtitle = "Interpolated, cartesian axes",
Title = "HeatMapSeries"
};
var palette = OxyPalettes.Hot(200);
var linearColorAxis1 = new LinearColorAxis
{
InvalidNumberColor = OxyColors.Gray,
Position = AxisPosition.Right,
Palette = palette
};
plotModel1.Axes.Add(linearColorAxis1);
// linearColorAxis1.
var linearAxis1 = new LinearAxis {Position = AxisPosition.Bottom};
plotModel1.Axes.Add(linearAxis1);
var linearAxis2 = new LinearAxis();
plotModel1.Axes.Add(linearAxis2);
var heatMapSeries1 = new HeatMapSeries
{
X0 = 0,
X1 = 1,
Y0 = 0,
Y1 = 1,
FontSize = .2
};
var scores = alignmentResults.heatScores;
var width = scores.GetLength(0);
var height = scores.GetLength(1);
heatMapSeries1.Data = new double[width, height];
var seriesData = heatMapSeries1.Data;
for (var i = 0; i < width; i++)
{
for (var j = 0; j < height; j++)
{
seriesData[i, j] = Convert.ToDouble(scores[i, j]);
}
}
plotModel1.Series.Add(heatMapSeries1);
var svg = new SvgExporter();
var svgString = svg.ExportToString(plotModel1);
var xml = new XmlDocument();
xml.LoadXml(svgString);
var x = SvgDocument.Open(xml); // Svg.SvgDocument();
var bmp = x.Draw();
bmp.Save(pngPath);
var heatmap = HeatmapFactory.CreateAlignedHeatmap(alignmentResults.heatScores);
var netHistogram = HistogramFactory.CreateHistogram(alignmentResults.netErrorHistogram, "NET Error", "NET Error");
var massHistogram = HistogramFactory.CreateHistogram(alignmentResults.massErrorHistogram, "Mass Error", "Mass Error (ppm)");
var baseName = Path.Combine(didirectory.FullName, Path.GetFileNameWithoutExtension(fiOutput.Name));
var encoder = new SvgEncoder();
PlotImageUtility.SaveImage(heatmap, baseName + "_heatmap.svg", encoder);
PlotImageUtility.SaveImage(netHistogram, baseName + "_netHistogram.svg", encoder);
PlotImageUtility.SaveImage(massHistogram, baseName + "_massHistogram.svg", encoder);
}
private async void createPlotModel()
{
await Task.Run(() =>
{
this.dataTable = DatabaseAccesserEcolog.GetResult(createQuery());
});
calculateEnergyParameter();
calculateTimeParameter();
var plotModel = new PlotModel();
plotModel.Subtitle = "SemananticLink: " + semantciLink.Semantics + ", Direction: " + direction.Direction;
plotModel.Title = "Semantic Matrix";
var linearColorAxis = new LinearColorAxis();
linearColorAxis.HighColor = OxyColors.Gray;
linearColorAxis.LowColor = OxyColors.Black;
linearColorAxis.Position = AxisPosition.Right;
plotModel.Axes.Add(linearColorAxis);
var linearAxis1 = new LinearAxis();
linearAxis1.Title = "Time";
linearAxis1.Unit = "s";
linearAxis1.Position = AxisPosition.Bottom;
plotModel.Axes.Add(linearAxis1);
var linearAxis2 = new LinearAxis();
linearAxis2.Title = "Lost Energy";
linearAxis2.Unit = "kWh";
plotModel.Axes.Add(linearAxis2);
var heatMapSeries1 = new HeatMapSeries();
heatMapSeries1.LabelFormatString = "0";
heatMapSeries1.X0 = minExcludedTime;
heatMapSeries1.X1 = maxExcludedTime;
heatMapSeries1.Y0 = minExcludedEnergy;
heatMapSeries1.Y1 = maxExcludedEnergy;
heatMapSeries1.LabelFontSize = 0.2;
heatMapSeries1.Data = new Double[classNumber + 1, classNumber + 1];
int count = 0; // for debug
double preTimeLevel = 0;
double currentTimeLevel = minExcludedTime;
for (int i = 0; i < classNumber + 1; i++)
{
double preEnergyLevel = 0;
double currentEnergyLevel = minExcludedEnergy;
for (int j = 0; j < classNumber + 1; j++)
{
heatMapSeries1.Data[i, j] = dataTable.AsEnumerable()
.Where(x => x.Field<double>("SumLostEnergy") > preEnergyLevel)
.Where(x => x.Field<double>("SumLostEnergy") <= currentEnergyLevel)
.Where(x => x.Field<int>("TIME") > preTimeLevel)
.Where(x => x.Field<int>("TIME") <= currentTimeLevel).Count();
count += (int)heatMapSeries1.Data[i, j];
if (j == 0)
{
preEnergyLevel = minExcludedEnergy;
}
else
{
preEnergyLevel += classWidthEnergy;
}
currentEnergyLevel += classWidthEnergy;
}
if (i == 0)
{
preTimeLevel = minExcludedTime;
}
else
{
preTimeLevel += classWidthTime;
}
currentTimeLevel += classWidthTime;
}
plotModel.Series.Add(heatMapSeries1);
this.ProgressBarVisibility = System.Windows.Visibility.Collapsed;
this.PlotModel = plotModel;
}
public void TestLcmsWarpAlignment(string path1, string path2, string svgPath)
{
// Convert relative paths to absolute paths
path1 = GetPath(path1);
path2 = GetPath(path2);
svgPath = GetPath(HEATMAP_RESULTS_FOLDER_BASE + svgPath);
var aligner = new LcmsWarpFeatureAligner();
var baselineMs = UmcLoaderFactory.LoadMsFeatureData(path1);
var aligneeMs = UmcLoaderFactory.LoadMsFeatureData(path2);
var finder = FeatureFinderFactory.CreateFeatureFinder(FeatureFinderType.TreeBased);
var tolerances = new FeatureTolerances
{
FragmentationWindowSize = .5,
Mass = 13,
DriftTime = .3,
Net = .01
};
var options = new LcmsFeatureFindingOptions(tolerances)
{
MaximumNetRange = .002
};
var baseline = finder.FindFeatures(baselineMs, options, null);
var alignee = finder.FindFeatures(aligneeMs, options, null);
var data = aligner.Align(baseline, alignee);
var plotModel1 = new PlotModel
{
Subtitle = "Interpolated, cartesian axes",
Title = "HeatMapSeries"
};
var palette = OxyPalettes.Hot(200);
var linearColorAxis1 = new LinearColorAxis
{
InvalidNumberColor = OxyColors.Gray,
Position = AxisPosition.Right,
Palette = palette
};
plotModel1.Axes.Add(linearColorAxis1);
// linearColorAxis1.
var linearAxis1 = new LinearAxis {Position = AxisPosition.Bottom};
plotModel1.Axes.Add(linearAxis1);
var linearAxis2 = new LinearAxis();
plotModel1.Axes.Add(linearAxis2);
var heatMapSeries1 = new HeatMapSeries
{
X0 = 0,
X1 = 1,
Y0 = 0,
Y1 = 1,
FontSize = .2
};
var scores = data.heatScores;
var width = scores.GetLength(0);
var height = scores.GetLength(1);
heatMapSeries1.Data = new double[width, height];
for (var i = 0; i < width; i++)
{
for (var j = 0; j < height; j++)
{
heatMapSeries1.Data[i, j] = Convert.ToDouble(scores[i, j]);
}
}
plotModel1.Series.Add(heatMapSeries1);
var svg = new SvgExporter();
var svgString = svg.ExportToString(plotModel1);
using (var writer = File.CreateText(svgPath + ".svg"))
{
writer.Write(svgString);
}
}
public void TestSimpleCreation()
{
var plotModel1 = new PlotModel
{
PlotType = PlotType.Cartesian,
Subtitle = "Interpolated, cartesian axes",
Title = "HeatMapSeries"
};
var palette = OxyPalettes.Hot(200);
var linearColorAxis1 = new LinearColorAxis
{
InvalidNumberColor = OxyColors.Gray,
Position = AxisPosition.Right,
Palette = palette
};
plotModel1.Axes.Add(linearColorAxis1);
var linearAxis1 = new LinearAxis {Position = AxisPosition.Bottom};
plotModel1.Axes.Add(linearAxis1);
var linearAxis2 = new LinearAxis();
plotModel1.Axes.Add(linearAxis2);
var heatMapSeries1 = new HeatMapSeries
{
X0 = 0.0,
X1 = 1.0,
Y0 = 0.0,
Y1 = 1.0,
FontSize = .2,
Data = new Double[2, 3]
};
//heatMapSeries1.LabelFontSize = 0.2;
heatMapSeries1.Data[0, 0] = 0;
heatMapSeries1.Data[0, 1] = 10.2;
heatMapSeries1.Data[0, 2] = 20.4;
heatMapSeries1.Data[1, 0] = 0.1;
heatMapSeries1.Data[1, 1] = 0.3;
heatMapSeries1.Data[1, 2] = 0.2;
plotModel1.Series.Add(heatMapSeries1);
var svg = new SvgExporter();
var svgString = svg.ExportToString(plotModel1);
var xml = new XmlDocument();
xml.LoadXml(svgString);
var x = SvgDocument.Open(xml); // Svg.SvgDocument();
var bmp = x.Draw();
bmp.Save(GetPath(HEATMAP_RESULTS_FOLDER_BASE + "testbmp.jpg"));
var encoder = new PngPlotModelEncoder();
encoder.SaveImage(plotModel1, GetPath(HEATMAP_RESULTS_FOLDER_BASE + "mine.png"));
}
void setupTrackPlot(OxyPlot.Wpf.PlotView plot)
{
var plotModel = new PlotModel { };
plot.Model = plotModel;
var songPointsFull = new List<ScatterPoint>();
var songSeries = new ScatterSeries();
songSeries.ItemsSource = songPointsFull;
songSeries.MarkerType = MarkerType.Square;
songSeries.MarkerSize = 0.1;
plotModel.Series.Add(songSeries);
var x_axis = new OxyPlot.Axes.LinearAxis()
{
Key = "XAxis",
Position = OxyPlot.Axes.AxisPosition.Bottom,
IsAxisVisible = false,
//AbsoluteMaximum = 1800,
//AbsoluteMinimum = -1,
//MinorStep = 10,
};
var y_axis = new LinearColorAxis()
{
Key = "YAxis",
Position = OxyPlot.Axes.AxisPosition.Left,
Palette = OxyPalettes.Hue(12),
Minimum = 0,
Maximum = 12,
IsAxisVisible = false
};
plot.ActualController.UnbindAll();
plotModel.IsLegendVisible = false;
plotModel.Axes.Add(x_axis);
plotModel.Axes.Add(y_axis);
}