void Seat_1_Update() //座墊-熱點計算更新
{
this.Seat_1 = new PlotModel {
Title = ""
};
Seat_1.PlotAreaBorderColor = OxyColors.Transparent;
Seat_1.Axes.Add(new OxyPlot.Axes.LinearColorAxis
{
Palette = OxyPalettes.Rainbow(500)
});
Seat_1.Axes.Add(new LinearAxis()
{
Position = AxisPosition.Bottom,
IsAxisVisible = false
});
Seat_1.Axes.Add(new LinearAxis()
{
Position = AxisPosition.Left,
IsAxisVisible = false
});
#region 顏色距陣計算
// generate 1d normal distribution
var singleDataSeat_1 = new double[100];
Random rndSeat_1 = new Random();
for (int x = 0; x < 100; ++x)
{
singleDataSeat_1[x] = Math.Exp((-1.0 / 2.0) * Math.Pow(((double)x - 50.0) / Convert.ToDouble(rndSeat_1.Next(900, 1200)), 2.0));
}
// generate 2d normal distribution
for (int x = 0; x < 100; ++x)
{
for (int y = 0; y < 100; ++y)
{
data_Seat_1[y, x] = singleDataSeat_1[x] * singleDataSeat_1[(y + 30) % 100] * 100;
}
}
#endregion
var heatMapSeat_1_Series = new HeatMapSeries
{
X0 = 0,
X1 = 99,
Y0 = 0,
Y1 = 99,
Interpolate = true,
RenderMethod = HeatMapRenderMethod.Bitmap,
Data = data_Seat_1
};
this.Seat_1.Series.Add(heatMapSeat_1_Series);
}
public void PlotMirror(double w, double h)
{
var model = new PlotModel();
model.PlotType = PlotType.Cartesian;
OxyPlot.Series.ScatterSeries sser = new OxyPlot.Series.ScatterSeries()
{
MarkerType = MarkerType.Square,
BinSize = 2,
MarkerSize = 0.75
};
sser.ItemsSource = m_Points;
model.Series.Add(sser);
model.Axes.Add(new OxyPlot.Axes.LinearAxis {
Position = AxisPosition.Bottom, Maximum = w / 2.0, Minimum = -w / 2.0, Title = "x, [mm]"
});
model.Axes.Add(new OxyPlot.Axes.LinearAxis {
Position = AxisPosition.Left, Maximum = h / 2.0, Minimum = -h / 2.0, Title = "y, [mm]"
});
model.Axes.Add(new OxyPlot.Axes.LinearColorAxis {
Position = AxisPosition.Right,
Palette = OxyPalettes.Rainbow(200),
});
m_Canvas.Model = model;
m_Canvas.InvalidatePlot(true);
}
public static PlotModel PolarHeatMapRotatedCounterClockwisePi()
{
var model = new PlotModel {
Title = "Polar heat map", PlotMargins = new OxyThickness(40, 80, 40, 40), PlotType = PlotType.Polar, PlotAreaBorderThickness = new OxyThickness(0)
};
var matrix = new double[2, 2];
matrix[0, 0] = 0;
matrix[0, 1] = 2;
matrix[1, 0] = 1.5;
matrix[1, 1] = 0.2;
model.Axes.Add(new AngleAxis {
StartAngle = Math.PI, EndAngle = Math.PI + 360, Minimum = 0, Maximum = 360, MajorStep = 30, MinorStep = 15
});
model.Axes.Add(new MagnitudeAxis {
Minimum = 0, Maximum = 100, MajorStep = 25, MinorStep = 5
});
model.Axes.Add(new LinearColorAxis {
Position = AxisPosition.Right, Palette = OxyPalettes.Rainbow(500), HighColor = OxyColors.Gray, LowColor = OxyColors.Black
});
model.Series.Add(new PolarHeatMapSeries {
Data = matrix, Angle0 = 30, Angle1 = 150, Magnitude0 = 0, Magnitude1 = 80, Interpolate = false
});
return(model);
}
public static PlotModel PolarHeatMapLinearAxes()
{
var model = new PlotModel {
Title = "Polar heat map on linear axes"
};
var matrix = new double[2, 2];
matrix[0, 0] = 0;
matrix[0, 1] = 2;
matrix[1, 0] = 1.5;
matrix[1, 1] = 0.2;
model.Axes.Add(new LinearAxis {
Position = AxisPosition.Bottom, Minimum = -100, Maximum = 100
});
model.Axes.Add(new LinearAxis {
Position = AxisPosition.Left, Minimum = 0, Maximum = 100
});
model.Axes.Add(new LinearColorAxis {
Position = AxisPosition.Right, Palette = OxyPalettes.Rainbow(500), HighColor = OxyColors.Gray, LowColor = OxyColors.Black
});
model.Series.Add(new PolarHeatMapSeries {
Data = matrix, Angle0 = 30, Angle1 = 150, Magnitude0 = 0, Magnitude1 = 80, Interpolate = true
});
return(model);
}
public PlotModel MagnifierColorImage(Image <Bgr, byte> colorImage)
{
CreateAxisForPlot();
plotImage.Axes.Add(new LinearColorAxis
{
Palette = OxyPalettes.Rainbow(255 * 255 * 255)
});
var dataGreen = GenerateColorPixel(colorImage, 1);
var dataRed = GenerateColorPixel(colorImage, 2);
var dataBlue = GenerateColorPixel(colorImage, 0);
var heatMapSeriesBlue = new HeatMapSeries
{
X0 = 0,
X1 = 8,
Y0 = 0,
Y1 = 8,
XAxisKey = "xAxis",
YAxisKey = "yAxis",
RenderMethod = HeatMapRenderMethod.Rectangles,
LabelFontSize = 0.2,
Interpolate = true,
Data = dataBlue
};
var heatMapSeriesGreen = new HeatMapSeries
{
X0 = 0,
X1 = 8,
Y0 = 0,
Y1 = 8,
XAxisKey = "xAxis",
YAxisKey = "yAxis",
RenderMethod = HeatMapRenderMethod.Rectangles,
LabelFontSize = 0.2,
Interpolate = true,
Data = dataGreen
};
var heatMapSeriesRed = new HeatMapSeries
{
X0 = 0,
X1 = 8,
Y0 = 0,
Y1 = 8,
XAxisKey = "xAxis",
YAxisKey = "yAxis",
RenderMethod = HeatMapRenderMethod.Rectangles,
LabelFontSize = 0.2,
Interpolate = true,
Data = dataRed
};
plotImage.Series.Add(heatMapSeriesBlue);
plotImage.Series.Add(heatMapSeriesGreen);
plotImage.Series.Add(heatMapSeriesRed);
return(plotImage);
}
public static void AssignDefaultColors(
this PlotModel plotModel,
bool isBaseDark,
int nSeries
)
{
var palette = isBaseDark
? OxyPalettes.Cool(nSeries)
: OxyPalettes.Rainbow(nSeries);
plotModel.DefaultColors = palette.Colors;
}
/// <summary>
/// Create the palette list.
/// </summary>
private void CreatePaletteList()
{
PaletteList = new BindingList <OxyPalette>();
PaletteList.Add(OxyPalettes.BlackWhiteRed(64));
PaletteList.Add(OxyPalettes.BlueWhiteRed(64));
PaletteList.Add(OxyPalettes.BlueWhiteRed31);
PaletteList.Add(OxyPalettes.Cool(64));
PaletteList.Add(OxyPalettes.Gray(64));
PaletteList.Add(OxyPalettes.Hot(64));
PaletteList.Add(OxyPalettes.Hue64);
PaletteList.Add(OxyPalettes.HueDistinct(64));
PaletteList.Add(OxyPalettes.Jet(64));
PaletteList.Add(OxyPalettes.Rainbow(64));
}
public MainViewModel()
{
this.MyModel = new PlotModel {
Title = "ContourSeries"
};
this.MyModel.Axes.Add(new LinearColorAxis
{
Position = OxyPlot.Axes.AxisPosition.Right,
//Palette = OxyPalettes.Jet(500)
Palette = OxyPalettes.Rainbow(100)
});
double x0 = -3.1;
double x1 = 3.1;
double y0 = -3;
double y1 = 3;
//generate values
Func <double, double, double> peaks = (x, y) => 3 * (1 - x) * (1 - x) * Math.Exp(-(x * x) - (y + 1) * (y + 1)) - 10 * (x / 5 - x * x * x - y * y * y * y * y) * Math.Exp(-x * x - y * y) - 1.0 / 3 * Math.Exp(-(x + 1) * (x + 1) - y * y);
var xx = ArrayBuilder.CreateVector(x0, x1, 100);
var yy = ArrayBuilder.CreateVector(y0, y1, 100);
var peaksData = ArrayBuilder.Evaluate(peaks, xx, yy);
var heatMapSeries = new HeatMapSeries
{
X0 = x0,
X1 = x1,
Y0 = y0,
Y1 = y1,
Interpolate = true,
RenderMethod = HeatMapRenderMethod.Bitmap,
Data = peaksData
};
this.MyModel.Series.Add(heatMapSeries);
var cs = new ContourSeries
{
Color = OxyColors.Black,
LabelBackground = OxyColors.Transparent,
ColumnCoordinates = yy,
RowCoordinates = xx,
Data = peaksData
};
this.MyModel.Series.Add(cs);
}
public override async Task OnInitializing()
{
var heatMapPlotModel = new Chart.PlotModel {
Title = "HeatMapSeries"
};
// Color axis (the X and Y axes are generated automatically)
heatMapPlotModel.Axes.Add(new LinearColorAxis
{
Palette = OxyPalettes.Rainbow(100)
});
// generate 1d normal distribution
var singleData = new double[100];
for (int x = 0; x < 100; ++x)
{
singleData[x] = Math.Exp((-1.0 / 2.0) * Math.Pow(((double)x - 50.0) / 20.0, 2.0));
}
// generate 2d normal distribution
var data = new double[100, 100];
for (int x = 0; x < 100; ++x)
{
for (int y = 0; y < 100; ++y)
{
data[y, x] = singleData[x] * singleData[(y + 30) % 100] * 100;
}
}
var heatMapSeries = new Chart.HeatMap
{
X0 = 0,
X1 = 99,
Y0 = 0,
Y1 = 99,
Interpolate = true,
RenderMethod = HeatMapRenderMethod.Bitmap,
Data = data
};
heatMapPlotModel.Series.Add(heatMapSeries);
await base.OnInitializing();
await heatMapPlotView.Add(heatMapPlotModel);
}
private PlotModel InitialPolarScatterModel(string title = null)
{
var model = new PlotModel
{
Title = title,
PlotType = PlotType.Polar,
PlotAreaBorderThickness = new OxyThickness(0),
PlotMargins = new OxyThickness(60, 20, 4, 40)
};
model.Axes.Add(
new AngleAxis
{
Title = "Angle",
MajorStep = Math.PI / 4,
MinorStep = Math.PI / 16,
MajorGridlineStyle = LineStyle.Solid,
MinorGridlineStyle = LineStyle.Solid,
FormatAsFractions = true,
FractionUnit = Math.PI,
FractionUnitSymbol = "π",
Minimum = 0,
Maximum = 2 * Math.PI
});
model.Axes.Add(new MagnitudeAxis
{
Title = "Magnitude",
MajorGridlineStyle = LineStyle.Solid,
MinorGridlineStyle = LineStyle.Solid,
//Minimum = 0,
//Maximum = 100,
});
model.Axes.Add(new LinearColorAxis() // TODO Slot毎に上下限が変わるので色の変化も変えたほうが良いと思う
{
Position = AxisPosition.Left,
Palette = OxyPalettes.Rainbow(16),
//Minimum = 2000,
//Maximum = 4000,
HighColor = OxyColors.Magenta,
LowColor = OxyColors.Green
});
model.Series.Add(new ScatterSeries() // Order(ZIndex) が存在しない為、SeriesIndex順に描画される。その為、Zoneの前に実データを入れておく為、ここで暫定定義。後からSortで対応してもいいんだけどね
{
TrackerKey = Constants.TrackerKeyPlotData,
});
AddZoneSeries(model);
return(model);
}
private void InitializeMainForm()
{
PlotModel plotModel = new PlotModel
{
Title = "EEG Data",
DefaultColors = OxyPalettes.Rainbow(this.channelCount).Colors,
LegendPlacement = LegendPlacement.Outside,
LegendPosition = LegendPosition.BottomLeft,
LegendMaxWidth = 900.0,
LegendMaxHeight = 100.0
};
plotModel.Axes.Add(new LinearAxis
{
Key = "X Axis",
Position = AxisPosition.Bottom,
MajorGridlineStyle = LineStyle.Solid,
MinorGridlineStyle = LineStyle.Dash,
Title = "Time",
TextColor = OxyColors.Transparent,
Minimum = 0.0,
Maximum = (double)this.visData.GTEC_SAMPLE_BUFFER_SIZE,
IsPanEnabled = false,
IsZoomEnabled = false
});
var tmp = new LinearAxis();
plotModel.Axes.Add(new LinearAxis
{
Key = "Y Axis",
Position = AxisPosition.Left
//AbsoluteMaximum = 1000,
//AbsoluteMinimum = -1000
});
this.visData.visMainSeries = new LineSeries[this.channelCount];
for (int i = 0; i < this.channelCount; i++)
{
this.visData.visMainSeries[i] = new LineSeries
{
LineStyle = LineStyle.Solid,
StrokeThickness = 1.0
};
plotModel.Series.Add(this.visData.visMainSeries[i]);
}
this.visMainPlot.Model = plotModel;
}
public static PlotModel LinearHeatMap()
{
var model = new PlotModel {
Title = "Heatmap"
};
// Color axis (the X and Y axes are generated automatically)
model.Axes.Add(new LinearColorAxis
{
Palette = OxyPalettes.Rainbow(100)
});
// generate 1d normal distribution
var singleData = new double[100];
for (int x = 0; x < 100; ++x)
{
singleData[x] = Math.Exp((-1.0 / 2.0) * Math.Pow(((double)x - 50.0) / 20.0, 2.0));
}
// generate 2d normal distribution
var data = new double[100, 100];
for (int x = 0; x < 100; ++x)
{
for (int y = 0; y < 100; ++y)
{
data[y, x] = singleData[x] * singleData[(y + 30) % 100] * 100;
}
}
var heatMapSeries = new HeatMapSeries
{
X0 = 0,
X1 = 99,
Y0 = 0,
Y1 = 99,
Interpolate = true,
RenderMethod = HeatMapRenderMethod.Bitmap,
Data = data
};
model.Series.Add(heatMapSeries);
return(model);
}
public static Points2DCollectionsViewer BuildViewer(IEnumerable <Point2D> PointsWithTag, string Title, int min, int max)
{
Points2DCollectionsViewer viewer = new Points2DCollectionsViewer();
viewer.Text = Title;
var model = new PlotModel {
Title = viewer.Text
};
var scatterSeries = new ScatterSeries {
MarkerType = MarkerType.Circle
};
foreach (var point in PointsWithTag)
{
scatterSeries.Points.Add(new ScatterPoint(point.x, point.y, 2, TagToValue(point.Tag)));
}
model.Series.Add(scatterSeries);
model.Axes.Add(new LinearColorAxis {
Position = AxisPosition.Right, Palette = OxyPalettes.Rainbow(TagToValueDict.Count() + 1)
});
model.Axes.Add(new LinearAxis()
{
Minimum = min, Maximum = max, Position = AxisPosition.Bottom
});
model.Axes.Add(new LinearAxis()
{
Minimum = min, Maximum = max, Position = AxisPosition.Left
});
viewer.plotView.Model = model;
return(viewer);
}
private OxyPalette GetPalette(int numberOfColors) => _appSettings.IsBaseDark ? OxyPalettes.Cool(numberOfColors) : OxyPalettes.Rainbow(numberOfColors);
/// <summary>
/// Generates an OxyPlot plot model.
/// </summary>
/// <param name="yMin">Minimum value for the vertical axis. If NaN will find the lowest value.</param>
/// <param name="yMax">Maximum value for the vertical axis. If NaN will find the highest value.</param>
/// <returns></returns>
public PlotModel Plot(double yMin, double yMax)
{
// Check if experiment has run yet
if (results == null)
{
throw new InvalidOperationException("Experiment has not been run yet.");
}
// Check if yMin is valid
if (double.IsNaN(yMin))
{
yMin = double.PositiveInfinity;
}
// Check if yMax is valid
if (double.IsNaN(yMax))
{
yMax = double.NegativeInfinity;
}
// Expand yMin and yMax so all values fit
for (int i = 0; i < N; i++)
{
if (i != HorizontalAxis)
{
double min = GetStatistics(i).Select(statistic => statistic.Min).Min();
if (yMin > min)
{
yMin = min;
}
double max = GetStatistics(i).Select(statistic => statistic.Max).Max();
if (yMax < max)
{
yMax = max;
}
}
}
// Arbitrary small value to prevent clipping
yMin -= 0.001;
yMax += 0.001;
// Create OxyPlot series
List <Series> series = new List <Series>();
for (int i = 0; i < N; i++)
{
if (i != HorizontalAxis)
{
var color = OxyPalettes.Rainbow(N).Colors[i];
var mySeries = new ErrorLineSeries()
{
Color = color,
MarkerFill = color,
MarkerSize = 5,
MarkerStroke = OxyColors.White,
MarkerType = MarkerType.Diamond,
Title = Labels[i],
ErrorValues = GetStatistics(i).Select(statistic => statistic.StdDev).ToList(),
ErrorWidth = 0.1,
};
mySeries.Points.AddRange(GetStatistics(i).Select((statistic, j) => new DataPoint(GetStatistics(HorizontalAxis)[j].Mean, statistic.Mean)).ToList());
series.Add(mySeries);
}
}
// Create OxyPlot model
var plotModel = new PlotModel()
{
Title = string.Join(", ", Meta),
LegendSymbolLength = 16,
LegendPlacement = OxyPlot.LegendPlacement.Outside
};
plotModel.Axes.Add(new LinearAxis()
{
Minimum = yMin,
Maximum = yMax,
Position = AxisPosition.Left,
MajorGridlineStyle = LineStyle.Solid,
});
plotModel.Axes.Add(new LinearAxis()
{
Minimum = GetStatistics(HorizontalAxis).Select(statistic => statistic.Min).Min(),
Maximum = GetStatistics(HorizontalAxis).Select(statistic => statistic.Max).Max(),
Position = AxisPosition.Bottom,
MajorGridlineStyle = LineStyle.Solid,
Title = Labels[HorizontalAxis],
});
foreach (var sery in series)
{
plotModel.Series.Add(sery);
}
return(plotModel);
}
private void Plot_btn_Click(object sender, RoutedEventArgs e)
{
try
{
var tmp = new PlotModel {
Title = "Contour Plot", Subtitle = "f(x1,x2)"
};
tmp.Axes.Add(new LinearColorAxis
{
Position = OxyPlot.Axes.AxisPosition.Right,
//Palette = OxyPalettes.Jet(500)
Palette = OxyPalettes.Rainbow(100)
});
double[] PVBmax = ParsePVB(PVBmax_TextBox.Text, ';');
double[] PVBmin = ParsePVB(PVBmin_TextBox.Text, ';');
bool errFlag = false;
for (int i = 0; i < PVBmax.Length; i++)
{
if (PVBmax[i] <= PVBmin[i])
{
errFlag = true;
}
}
String fun_str = ObjFun_ComboBox.Text.ToString();
Function fn = new Function(fun_str);
double x1_min;
double x1_max;
double x2_min;
double x2_max;
double tmpMaxValue = Double.MinValue;
if (PVBmin.GetLength(0) == 2 && !errFlag)
{
x1_min = PVBmin[0];
x1_max = PVBmax[0];
x2_min = PVBmin[1];
x2_max = PVBmax[1];
var x1x1 = ArrayBuilder.CreateVector(x1_min, x1_max, 100);
var x2x2 = ArrayBuilder.CreateVector(x2_min, x2_max, 100);
double[,] peaksData = new double[x1x1.GetLength(0), x2x2.GetLength(0)];
double[] xy_tab = new double[2];
for (int i = 0; i < x1x1.GetLength(0); i++)
{
for (int j = 0; j < x2x2.GetLength(0); j++)
{
xy_tab[0] = x1x1[i];
xy_tab[1] = x2x2[j];
peaksData[i, j] = HarmonyTool.EvaluateFun(fn, xy_tab);
if (peaksData[i, j] > tmpMaxValue)
{
tmpMaxValue = peaksData[i, j];
}
}
}
var heatMapSeries = new HeatMapSeries
{
X0 = x1_min,
X1 = x1_max,
Y0 = x2_min,
Y1 = x2_max,
Interpolate = true,
RenderMethod = HeatMapRenderMethod.Bitmap,
Data = peaksData
};
tmp.Series.Add(heatMapSeries);
var cs = new ContourSeries
{
Color = OxyColors.Black,
LabelBackground = OxyColors.Transparent,
ColumnCoordinates = x1x1,
RowCoordinates = x2x2,
Data = peaksData
};
tmp.Series.Add(cs);
if (solutionCheckBox.IsChecked == true)
{
var sc = new ScatterSeries
{
MarkerType = MarkerType.Circle
};
sc.BinSize = 10;
sc.MarkerType = MarkerType.Cross;
sc.MarkerStrokeThickness = 3;
sc.MarkerStroke = OxyColors.Black;
double x1 = bestSolution[0];
double x2 = bestSolution[1];
sc.Points.Add(new OxyPlot.Series.ScatterPoint(x1, x2, 5, tmpMaxValue));
tmp.Series.Add(sc);
}
GetMainViewModel().MyModel = tmp;
}
else
{
MessageBox.Show("Number of variables does not equal n = 2 or PVB not given correctly! Check forms", "Exception", MessageBoxButton.OK, MessageBoxImage.Information);
}
}
catch (Exception ex)
{
MessageBox.Show("A handled exception just occurred: " + ex.Message + "\n Check if forms are filled properly! Domain of function has to be set in PVB forms", "Exception", MessageBoxButton.OK, MessageBoxImage.Information);
}
}
public static OxyPaletteMap CreateFromName(string name)
{
OxyPalette palette = null;
var numPoints = 2;
switch (name)
{
case "BlackWhiteRed":
{
numPoints = 3;
palette = OxyPalettes.BlackWhiteRed(NUM_COLORS);
break;
}
case "BlueWhiteRed":
{
numPoints = 3;
palette = OxyPalettes.BlueWhiteRed(NUM_COLORS);
break;
}
case "Cool":
{
numPoints = 3;
palette = OxyPalettes.Cool(NUM_COLORS);
break;
}
case "Gray":
{
numPoints = 2;
palette = OxyPalettes.Gray(NUM_COLORS);
break;
}
case "Hot":
{
numPoints = 5;
palette = OxyPalettes.Hot(NUM_COLORS);
break;
}
case "Hue":
{
numPoints = 7;
palette = OxyPalettes.Hue(NUM_COLORS);
break;
}
case "Jet":
{
numPoints = 5;
palette = OxyPalettes.Jet(NUM_COLORS);
break;
}
case "Rainbow":
{
numPoints = 7;
palette = OxyPalettes.Rainbow(NUM_COLORS);
break;
}
default:
{
return(null);
break;
}
}
var colorPoints = new Color[7];
var brush = new LinearGradientBrush();
brush.StartPoint = new Point(0, 0.5);
brush.EndPoint = new Point(1, 0.5);
var division = (NUM_COLORS / (numPoints - 1)) - 1;
for (int i = 0; i < numPoints; i++)
{
var oxyColor = palette.Colors[(division * i)];
colorPoints[i] = Color.FromArgb(oxyColor.A, oxyColor.R, oxyColor.G, oxyColor.B);
brush.GradientStops.Add(new GradientStop(colorPoints[i], ((double)i / (numPoints - 1))));
}
return(new OxyPaletteMap(name, brush, palette));
}
private static PlotModel GetPlot(string name)
{
// RESOLUTION AND TICK SIZE
int dpi = (int)(dpi_min + _random.NextDouble() * (dpi_max - dpi_min));
int[] figsize = new[] { (int)(figsize_min + _random.NextDouble() * (figsize_max - figsize_min)), (int)(figsize_min + _random.NextDouble() * (figsize_max - figsize_min)) };
List <double> tick_size = new List <double> {
(tick_size_width_min + _random.NextDouble() * (tick_size_width_max - tick_size_width_min)), (tick_size_length_min + _random.NextDouble() * (tick_size_length_max - tick_size_length_min))
};
tick_size.Sort();
// ACTUAL POINTS
var points_nb = (int)(points_nb_min + (Math.Pow(_random.NextDouble(), 1.5)) * (points_nb_max - points_nb_min));
var x_scale = (int)(x_min_top + _random.NextDouble() * (x_max_top - x_min_top));
var y_scale = (int)(y_min_top + _random.NextDouble() * (y_max_top - y_min_top));
var x_scale_range = x_scale + (int)(_random.NextDouble() * x_scale_range_max);
var y_scale_range = y_scale + (int)(_random.NextDouble() * y_scale_range_max);
var x_min_temp = (-_random.NextDouble() + _random.NextDouble()) * Math.Pow(10, x_scale);
var x_max_temp = (-_random.NextDouble() + _random.NextDouble()) * Math.Pow(10, x_scale_range);
var x_min = Math.Min(x_min_temp, x_max_temp);
var x_max = Math.Max(x_min_temp, x_max_temp);
var y_min_temp = (-_random.NextDouble() + _random.NextDouble()) * Math.Pow(10, y_scale);
var y_max_temp = (-_random.NextDouble() + _random.NextDouble()) * Math.Pow(10, y_scale_range);
var y_min = Math.Min(y_min_temp, y_max_temp);
var y_max = Math.Max(y_min_temp, y_max_temp);
var xs = UniformContinuousDistribution.Random(x_min, x_max, points_nb, _random);
double[] ys = new double[0];
var distribution = Resources.point_dist[_random.Next(4)];
if (distribution == "uniform")
{
ys = UniformContinuousDistribution.Random(y_min, y_max, points_nb, _random);
}
else if (distribution == "linear")
{
ys = xs.Multiply((Math.Max(y_max, -y_min) / (Math.Max(x_max, -x_min)))).Multiply((double)Resources.updown[_random.Next(2)])
.Add(UniformContinuousDistribution.Random(0, 1, points_nb, _random).Add(y_min).Multiply((y_max - y_min)).Multiply(_random.NextDouble() / 2.0));
}
else if (distribution == "quadratic")
{
ys = xs.Pow(2).Multiply(1.0 / (Math.Max(x_max, -x_min))).Pow(2).Multiply(Math.Max(y_max, -y_min)).Multiply((double)Resources.updown[_random.Next(2)])
.Add(UniformContinuousDistribution.Random(0, 1, points_nb, _random).Add(y_min).Multiply((y_max - y_min)).Multiply(_random.NextDouble() / 2.0));
}
else if (distribution == "binormal")
{
double stdDev = Math.Max(y_max, -y_min) / Math.Max(x_max, -x_min);
double correl = (double)Resources.updown[_random.Next(2)] * _random.NextDouble();
xs = NormalDistribution.Random(x_max - x_min, stdDev, points_nb, _random);
ys = correl.Multiply(xs).Add(NormalDistribution.Random(y_max - y_min, stdDev, points_nb, _random).Multiply(Math.Sqrt(1 - correl * correl)));
}
// POINTS VARIATION
var nb_points_var = 1 + (int)(_random.NextDouble() * max_points_variations);
var nb_points_var_colors = 1 + (int)(_random.NextDouble() * nb_points_var);
var nb_points_var_markers = 1 + (int)(_random.NextDouble() * (nb_points_var - nb_points_var_colors));
var nb_points_var_size = Math.Max(1, 1 + nb_points_var - nb_points_var_colors - nb_points_var_markers);
var rand_color_number = _random.NextDouble();
OxyColor[] colors = new OxyColor[nb_points_var_colors];
OxyColor[] tempPalette;
if (rand_color_number <= 0.5)
{
tempPalette = OxyPalettes.Rainbow(nb_points_var_colors * 20).Colors.ToArray();
}
else if (rand_color_number > 0.5 && rand_color_number <= 0.7)
{
tempPalette = OxyPalettes.Hue(nb_points_var_colors * 20).Colors.ToArray(); // gnuplot
}
else if (rand_color_number > 0.7 && rand_color_number <= 0.8)
{
tempPalette = OxyPalettes.Hot(nb_points_var_colors * 20).Colors.ToArray(); // copper
}
else
{
tempPalette = OxyPalettes.Jet(nb_points_var_colors * 20).Colors.ToArray(); // gray
}
for (int i = 0; i < nb_points_var_colors; i++)
{
colors[i] = tempPalette[_random.Next(nb_points_var_colors * 20)];
}
var s_set = (size_points_min.Add(UniformContinuousDistribution.Random(0, 1, nb_points_var_size, _random).Multiply(size_points_max - size_points_min)));
var markers_subset = new List <MarkerType>();
for (int i = 0; i < nb_points_var_markers; i++)
{
markers_subset.Add(Resources.Markers[_random.Next(Resources._markersCount)]);
}
var markers_empty = _random.NextDouble() > 0.75;
var markers_empty_ratio = new[] { 0.0, 0.5, 0.7 }[_random.Next(3)];
// PAD BETWEEN TICKS AND LABELS
double pad_x = Math.Max(tick_size[1] + 0.5, (int)(pad_min + _random.NextDouble() * (pad_max - pad_min)));
double pad_y = Math.Max(tick_size[1] + 0.5, (int)(pad_min + _random.NextDouble() * (pad_max - pad_min)));
TickStyle direction_ticks_x = Resources.DirectionTicks[_random.Next(Resources._directionTicksCount)];
TickStyle direction_ticks_y = Resources.DirectionTicks[_random.Next(Resources._directionTicksCount)];
// FONT AND SIZE FOR LABELS (tick labels, axes labels and title)
string font = Resources.FontList[_random.Next(Resources._fontListCount)];
int size_ticks = (int)(tick_label_size_min + _random.NextDouble() * (tick_label_size_max - tick_label_size_min));
int size_axes = (int)(axes_label_size_min + _random.NextDouble() * (axes_label_size_max - axes_label_size_min));
int size_title = (int)(title_size_min + _random.NextDouble() * (title_size_max - title_size_min));
//var ticks_font = font_manager.FontProperties(fname = font, style = 'normal', size = size_ticks, weight = 'normal', stretch = 'normal');
//var axes_font = font_manager.FontProperties(fname = font, style = 'normal', size = size_axes, weight = 'normal', stretch = 'normal');
//var title_font = font_manager.FontProperties(fname = font, style = 'normal', size = size_title, weight = 'normal', stretch = 'normal');
// TEXTS FOR AXIS LABELS AND TITLE
int label_x_length = (int)(axes_label_length_min + _random.NextDouble() * (axes_label_length_max - axes_label_length_min));
int label_y_length = (int)(axes_label_length_min + _random.NextDouble() * (axes_label_length_max - axes_label_length_min));
int title_length = (int)(title_length_min + _random.NextDouble() * (title_length_max - title_length_min));
string x_label = RandomString(label_x_length);
string y_label = RandomString(label_y_length);
string title = RandomString(title_length);
// BUILDING THE PLOT
PlotModel model = new PlotModel
{
Title = title,
TitleFont = font,
TitleFontSize = size_title,
DefaultColors = colors,
PlotAreaBorderThickness = new OxyThickness(0)
};
model.Axes.Add(new LinearColorAxis {
Position = AxisPosition.None, Palette = new OxyPalette(colors), Minimum = 0, Maximum = colors.Length - 1
});
// TICKS STYLE AND LOCATION (X AXIS)
LineStyle lineStyle = Resources.LineStyles[_random.Next(Resources._lineStylesCount)];
var xAxis = new LinearAxis
{
Position = _random.NextDouble() > 0.5 ? AxisPosition.Top : AxisPosition.Bottom,
TickStyle = direction_ticks_x,
MajorGridlineStyle = lineStyle,
MajorTickSize = tick_size[1],
MinorTickSize = (_random.NextDouble() > 77) ? 0.75 * _random.NextDouble() * tick_size[1] : 0,
Angle = _random.NextDouble() > 0.77 ? _random.NextDouble() * (double)Resources.updown[_random.Next(2)] * 90 : 0,
Font = font,
FontSize = size_ticks,
TitleFont = font,
TitleFontSize = size_axes,
Title = _random.NextDouble() > 0.80 ? "" : x_label,
PositionAtZeroCrossing = (_random.NextDouble() > 0.77),
IsAxisVisible = true,
AxislineColor = OxyColors.Black,
AxislineStyle = LineStyle.Solid
};
model.Axes.Add(xAxis);
// TICKS STYLE AND LOCATION (Y AXIS)
var yAxis = new LinearAxis
{
Position = _random.NextDouble() > 0.5 ? AxisPosition.Right : AxisPosition.Left,
TickStyle = direction_ticks_y,
MajorGridlineStyle = lineStyle,
MajorTickSize = tick_size[1],
MinorTickSize = (_random.NextDouble() > 77) ? 0.75 * _random.NextDouble() * tick_size[1] : 0,
Angle = _random.NextDouble() > 0.77 ? _random.NextDouble() * 90 : 0,
Font = font,
FontSize = size_ticks,
TitleFont = font,
TitleFontSize = size_axes,
Title = _random.NextDouble() > 0.80 ? "" : y_label,
PositionAtZeroCrossing = (_random.NextDouble() > 0.77),
IsAxisVisible = true,
AxislineColor = OxyColors.Black,
AxislineStyle = LineStyle.Solid
};
model.Axes.Add(yAxis);
MarkerType markerType = Resources.Markers[_random.Next(Resources._markersCount)];
var scatterSerie = new ScatterSeries()
{
MarkerType = markerType,
MarkerStrokeThickness = _random.Next(10, 31) / 10,
};
if (markerType != MarkerType.Cross && markerType != MarkerType.Plus && markerType != MarkerType.Star)
{
if (_random.NextDouble() > 0.5)
{
scatterSerie.MarkerStroke = OxyColors.Black;
}
}
List <double> s = new List <double>();
for (int i = 0; i < points_nb; i++)
{
var s_ = s_set[_random.Next(s_set.Length)];
var c_ = colors[_random.Next(colors.Length)];
var m_ = Resources.Markers[_random.Next(Resources._markersCount)];
bool e_ = false;
if (markers_empty)
{
e_ = _random.NextDouble() > markers_empty_ratio;
}
scatterSerie.Points.Add(new ScatterPoint(xs[i], ys[i], s_, _random.Next(colors.Length)));
}
model.Series.Add(scatterSerie);
return(model);
}
public static PlotModel ColorMapRainbow16()
{
return(CreateRandomScatterSeriesWithColorAxisPlotModel(2500, OxyPalettes.Rainbow(16), MarkerType.Square, AxisPosition.Right, OxyColors.Undefined, OxyColors.Undefined));
}
public PlotView getScatteredPlot(string[,] dataArray, string title, int xColumn, int yColumn, int colorColumn, int regressionIndex, bool logX, bool logY)
{
string xTitle = ucLoadFile.Instance.getCurrentColumnNames()[xColumn];
string yTitle = ucLoadFile.Instance.getCurrentColumnNames()[yColumn];
string colorTitle = "No grouping selected";
if (colorColumn != -1)
{
colorTitle = ucLoadFile.Instance.getCurrentColumnNames()[colorColumn];
}
// Getting unique group names when color grouping required and groups are strings
ArrayList groupNames = getGroupNames(dataArray, colorColumn);
//Populating scatter plot with data from selected columns
var model = new PlotModel {
Title = title
};
var scatterSeries = new ScatterSeries {
MarkerType = MarkerType.Circle
};
for (int r = 0; r < dataArray.GetLength(0); r++)
{ // x axis
double xDouble = 0;
bool isNumberX = double.TryParse(dataArray[r, xColumn], out xDouble);
var x = xDouble;
// y axis
double yDouble = 0;
bool isNumberY = double.TryParse(dataArray[r, yColumn], out yDouble);
var y = yDouble;
// color grouping
double colorValue = 0;
bool isNumberColor = true;
if (colorColumn != -1)
{
double colorDouble = 0;
isNumberColor = double.TryParse(dataArray[r, colorColumn], out colorDouble);
colorValue = colorDouble;
}
var size = 3;
if (!isNumberColor && !String.IsNullOrEmpty(dataArray[r, colorColumn]))
{
scatterSeries.Points.Add(new ScatterPoint(x, y, size, groupNames.IndexOf(dataArray[r, colorColumn])));
}
else
{
scatterSeries.Points.Add(new ScatterPoint(x, y, size, colorValue));
}
}
// Handling of selection of axis scaling
if (logX && !logY)
{
var logAxisX = new LogarithmicAxis()
{
Position = AxisPosition.Bottom, Title = xTitle + ", Log(x)", UseSuperExponentialFormat = false, Base = 10, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
var linearAxisY = new LinearAxis()
{
Position = AxisPosition.Left, Title = yTitle, UseSuperExponentialFormat = false, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
model.Axes.Add(logAxisX);
model.Axes.Add(linearAxisY);
}
else if (!logX && logY)
{
var linearAxisX = new LinearAxis()
{
Position = AxisPosition.Bottom, Title = xTitle, UseSuperExponentialFormat = false, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
var logAxisY = new LogarithmicAxis()
{
Position = AxisPosition.Left, Title = yTitle + ", Log(y)", UseSuperExponentialFormat = false, Base = 10, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
model.Axes.Add(linearAxisX);
model.Axes.Add(logAxisY);
}
else if (logX && logY)
{
var logAxisX = new LogarithmicAxis()
{
Position = AxisPosition.Bottom, Title = xTitle + ", Log(x)", UseSuperExponentialFormat = false, Base = 10, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
var logAxisY = new LogarithmicAxis()
{
Position = AxisPosition.Left, Title = yTitle + ", Log(y)", UseSuperExponentialFormat = false, Base = 10, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
model.Axes.Add(logAxisY);
model.Axes.Add(logAxisX);
}
else
{
var linearAxisX = new LinearAxis()
{
Position = AxisPosition.Bottom, Title = xTitle, UseSuperExponentialFormat = false, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
var linearAxisY = new LinearAxis()
{
Position = AxisPosition.Left, Title = yTitle, UseSuperExponentialFormat = false, MajorGridlineStyle = LineStyle.Dot, MajorGridlineColor = OxyColors.Gray
};
model.Axes.Add(linearAxisX);
model.Axes.Add(linearAxisY);
}
model.Series.Clear();
model.Annotations.Clear();
model.Series.Add(scatterSeries);
// Adding regression graph when selected
if (regressionIndex == 1)
{
double[] xClmn = parseDataArrayToDouble(ucLoadFile.Instance.getDataColumn(xColumn, dataArray));
Func <double, double> pwr = getPowerRegression(dataArray, xColumn, yColumn);
string label = "pwr rgssn y=" + Math.Round(a, 3).ToString() + "*" + "x pwr" + Math.Round(b, 3).ToString() + ", r=" + Math.Round(r, 2).ToString();
FunctionSeries fsPwrRegression = new FunctionSeries(pwr, xClmn.Min() - 0.1, xClmn.Max(), 0.01, label);
fsPwrRegression.Color = OxyColors.DeepSkyBlue;
model.Series.Add(fsPwrRegression);
}
if (regressionIndex == 2)
{
double[] xClmn = parseDataArrayToDouble(ucLoadFile.Instance.getDataColumn(xColumn, dataArray));
Func <double, double> lnr = getLinearRegression(dataArray, xColumn, yColumn);
string bstring = Math.Round(b, 3).ToString();
if (b <= 0.0009)
{
bstring = Math.Round(b * 1000000, 3).ToString() + "m";
}
string label = "lnr rgssn y=" + Math.Round(a, 3).ToString() + "+" + bstring + "*x, r=" + Math.Round(r, 2).ToString();
FunctionSeries fsLinearRegression = new FunctionSeries(lnr, xClmn.Min() - 0.1, xClmn.Max(), 0.01, label);
fsLinearRegression.Color = OxyColors.DeepSkyBlue;
model.Series.Add(fsLinearRegression);
}
// Adding special axis for color coding
model.Axes.Add(new LinearColorAxis
{
Position = AxisPosition.Top,
Palette = OxyPalettes.Rainbow(200),
Title = colorTitle,
TitlePosition = 0.2,
});
PlotView plotView = new PlotView();
// Adding assembled model into plot view
plotView.Model = model;
return(plotView);
}
public static PlotModel Rainbow7()
{
return(HeatMapSeriesExamples.CreatePeaks(OxyPalettes.Rainbow(7), false));
}
public static PlotModel ColorMapRainbow16()
{
return(CreateRandomScatterSeriesWithColorAxisPlotModel(2500, OxyPalettes.Rainbow(16)));
}
private PlotModel InitialScatterModel(string title = null)
{
var model = new PlotModel()
{
Title = title,
LegendPlacement = LegendPlacement.Outside,
};
var xAxis = new LinearAxis()
{
Minimum = -1, Maximum = 1, Position = AxisPosition.Bottom, MajorGridlineStyle = LineStyle.Solid, MinorGridlineStyle = LineStyle.Automatic, Title = "x"
};
model.Axes.Add(xAxis);
var yAxis = new LinearAxis()
{
Minimum = -1, Maximum = 1, Position = AxisPosition.Left, MajorGridlineStyle = LineStyle.Solid, MinorGridlineStyle = LineStyle.Automatic, Title = "y"
};
model.Axes.Add(yAxis);
var s1 = new ScatterSeries()
{
Title = "Diamond",
MarkerType = MarkerType.Diamond,
MarkerStrokeThickness = 0,
BinSize = 1,
};
var random = new Random(Environment.TickCount);
for (int i = 0; i < 50; i++)
{
var x = random.NextDouble();
var y = random.NextDouble();
var z = random.NextDouble();
s1.Points.Add(new ScatterPoint(x, y)
{
Value = z
});
}
model.Series.Add(s1);
model.Axes.Add(new LinearColorAxis {
Position = AxisPosition.Right, Palette = OxyPalettes.Rainbow(16), Minimum = -1, Maximum = 1, HighColor = OxyColors.Magenta, LowColor = OxyColors.Green
});
var s2 = new ScatterSeries
{
Title = "star",
MarkerType = MarkerType.Star,
MarkerSize = 6,
};
for (int i = 0; i < 50; i++)
{
var x = random.NextDouble();
int odd = (int)(x * 100) % 2;
x = x * ((odd == 0) ? 1: -1);
var y = random.NextDouble();
odd = (int)(y * 100) % 2;
y = y * ((odd == 0) ? 1 : -1);
var z = random.NextDouble();
odd = (int)(z * 100) % 2;
z = z * ((odd == 0) ? 1 : -1);
s2.Points.Add(new ScatterPoint(x, y)
{
Value = z
});
}
model.Series.Add(s2);
return(model);
}
