public void Test_AutoAxis_ShrinkWhenNeeded()
{
Random rand = new Random(0);
var plt = new ScottPlot.Plot();
// small area
plt.PlotLine(-5, -5, 5, 5);
plt.AxisAuto();
var limitsA = new ScottPlot.Config.AxisLimits2D(plt.Axis());
Console.WriteLine($"limits A: {limitsA}");
// expand to large area
plt.Axis(-123, 123, -123, 123);
var limitsB = new ScottPlot.Config.AxisLimits2D(plt.Axis());
Console.WriteLine($"limits B: {limitsB}");
// shrink back to small area
plt.AxisAuto();
var limitsC = new ScottPlot.Config.AxisLimits2D(plt.Axis());
Console.WriteLine($"limits C: {limitsC}");
Assert.That(limitsB.xSpan > limitsC.xSpan);
Assert.That(limitsB.ySpan > limitsC.ySpan);
Assert.That(limitsA.xSpan == limitsC.xSpan);
Assert.That(limitsA.ySpan == limitsC.ySpan);
}
public string Figure_66_CPH()
{
string name = System.Reflection.MethodBase.GetCurrentMethod().Name.Replace("Figure_", "");
string fileName = System.IO.Path.GetFullPath($"{outputFolderName}/{name}.png");
Random rand = new Random(0);
double[] values1 = ScottPlot.DataGen.RandomNormal(rand, pointCount: 1000, mean: 50, stdDev: 20);
double[] values2 = ScottPlot.DataGen.RandomNormal(rand, pointCount: 1000, mean: 45, stdDev: 25);
var hist1 = new ScottPlot.Histogram(values1, min: 0, max: 100);
var hist2 = new ScottPlot.Histogram(values2, min: 0, max: 100);
var plt = new ScottPlot.Plot(width, height);
plt.Title("Cumulative Probability Histogram");
plt.YLabel("Probability (fraction)");
plt.XLabel("Value (units)");
plt.PlotStep(hist1.bins, hist1.cumulativeFrac, lineWidth: 1.5, label: "sample A");
plt.PlotStep(hist2.bins, hist2.cumulativeFrac, lineWidth: 1.5, label: "sample B");
plt.Legend();
plt.Axis(null, null, 0, 1);
plt.SaveFig(fileName);
Console.WriteLine($"Saved: {System.IO.Path.GetFileName(fileName)}");
return(name + ":" + ScottPlot.Tools.BitmapHash(plt.GetBitmap()));
}
public void Test_PlottableBar2_MultiSeries()
{
double[,] values = new double[, ] {
{ 15, 22, 45, 17 }, { 37, 21, 29, 13 }
};
string[] rowLabels = new string[] { "men", "women" };
string[] colLabels = new string[] { "always", "regularly", "sometimes", "never" };
Assert.AreEqual(values.GetLength(0), rowLabels.Length);
Assert.AreEqual(values.GetLength(1), colLabels.Length);
var plt = new ScottPlot.Plot(400, 300);
// create and add an experimental plottable (not in the ScottPlot namespace)
var pltBar = new PlottableBar2(rowLabels, colLabels, values);
plt.Add(pltBar);
plt.Title("How often do you read reviews?");
plt.XTicks(colLabels);
plt.Ticks(useMultiplierNotation: false);
plt.Axis(-1, colLabels.Length, 0, null);
plt.Grid(enableVertical: false);
TestTools.SaveFig(plt);
}
public void Test_PlottableBar2_SingleSeries()
{
double[,] values = new double[, ] {
{ 7, 12, 40, 40, 100, 125, 172, 550, 560, 600, 2496, 2789 }
};
string[] rowLabels = new string[] { null };
string[] colLabels = new string[] { "ant", "bird", "mouse", "human", "cat", "dog", "frog", "lion", "elephant", "horse", "shark", "hippo" };
Assert.AreEqual(values.GetLength(0), rowLabels.Length);
Assert.AreEqual(values.GetLength(1), colLabels.Length);
var plt = new ScottPlot.Plot(400, 300);
// create and add an experimental plottable (not in the ScottPlot namespace)
var pltBar = new PlottableBar2(rowLabels, colLabels, values);
plt.Add(pltBar);
plt.Title("Body-to-Brain Mass Ratio");
plt.XTicks(colLabels);
plt.Axis(-1, colLabels.Length, 0, null);
plt.Grid(enableVertical: false);
// customize ticks to display better at high density
plt.Ticks(useMultiplierNotation: false);
plt.Ticks(xTickRotation: 45);
plt.Layout(xLabelHeight: 40);
TestTools.SaveFig(plt);
}
static void DisplayTicks(double low, double high)
{
var plt = new ScottPlot.Plot();
plt.Axis(low, high);
var ticks = new ScottPlot.TickCollection(plt.GetSettings());
Console.WriteLine(ticks);
}
public void Test_AutoAxis_ExpandYonly()
{
Random rand = new Random(0);
var plt = new ScottPlot.Plot();
// small area
plt.PlotLine(-5, -5, 5, 5);
plt.AxisAuto();
var limitsA = new ScottPlot.Config.AxisLimits2D(plt.Axis());
// large area
plt.PlotLine(-99, -99, 99, 99);
plt.AxisAuto(yExpandOnly: true);
var limitsB = new ScottPlot.Config.AxisLimits2D(plt.Axis());
Assert.That(limitsA.xSpan == limitsB.xSpan);
Assert.That(limitsA.ySpan < limitsB.ySpan);
}
public void Test_SignalXY_RenderLimits()
{
Random rand = new Random(0);
double[] xs = ScottPlot.DataGen.Consecutive(100_000);
double[] ys = ScottPlot.DataGen.RandomWalk(rand, 100_000);
var plt = new ScottPlot.Plot(500, 350);
plt.PlotSignalXY(xs, ys, minRenderIndex: 4000, maxRenderIndex: 5000);
plt.Axis(y1: -200, y2: 200);
TestTools.SaveFig(plt);
}
/// <summary>
/// Initialize <see cref="ScottPlot.Plot"/> object.
/// </summary>
/// <param name="formsPlot">Where to fit the fig to.</param>
/// <param name="labelTitle">Fig label.</param>
/// <param name="labelX">X axis label.</param>
/// <param name="labelY">Y axis label.</param>
/// <returns></returns>
private ScottPlot.Plot PlotInitialize(ScottPlot.FormsPlot formsPlot,
string labelTitle, string labelX, string labelY)
{
ScottPlot.Plot plt = formsPlot.plt;
plt.Grid(enable: false);
plt.Style(figBg: Color.Transparent, dataBg: Color.White);
plt.Title(labelTitle);
plt.XLabel(labelX);
plt.YLabel(labelY);
plt.Axis(null, null, 0, null);
formsPlot.Render();
return(plt);
}
public void Figure_01c_Defined_Axis_Limits()
{
string name = System.Reflection.MethodBase.GetCurrentMethod().Name.Replace("Figure_", "");
string fileName = System.IO.Path.GetFullPath($"{outputFolderName}/{name}.png");
var plt = new ScottPlot.Plot(width, height);
plt.PlotScatter(dataXs, dataSin);
plt.PlotScatter(dataXs, dataCos);
plt.Axis(2, 8, .2, 1.1); // x1, x2, y1, y2
plt.SaveFig(fileName);
Console.WriteLine($"Saved: {System.IO.Path.GetFileName(fileName)}");
}
public void Test_AutoAxis_WorksAfterClear()
{
var plt = new ScottPlot.Plot();
plt.PlotPoint(0.1, 0.1);
plt.PlotPoint(-0.1, -0.1);
plt.AxisAuto();
plt.GetBitmap(); // force a render
Assert.Greater(plt.Axis()[0], -5);
plt.PlotPoint(999, 999);
plt.PlotPoint(-999, -999);
plt.AxisAuto();
plt.GetBitmap(); // force a render
Assert.Less(plt.Axis()[0], -800);
plt.Clear();
plt.PlotPoint(0.1, 0.1);
plt.PlotPoint(-0.1, -0.1);
plt.GetBitmap(); // force a render
Assert.Greater(plt.Axis()[0], -5);
}
public void Test_DataContainsNan_Scatter()
{
double[] xs = new double[] { 1, double.NaN, 3, 4, 5, 6 };
double[] ys = new double[] { 1, 4, 9, 16, double.NaN, 36 };
var plt = new ScottPlot.Plot();
plt.PlotScatter(xs, ys);
plt.AxisAuto();
var ax = plt.Axis();
Console.WriteLine($"Automatic axis limits: x1={ax[0]}, x2={ax[0]}, y1={ax[0]}, y2={ax[0]}");
plt.Axis(-2, 7, -10, 40);
string name = System.Reflection.MethodBase.GetCurrentMethod().Name;
string filePath = System.IO.Path.GetFullPath(name + ".png");
plt.SaveFig(filePath);
Console.WriteLine($"Saved {filePath}");
}
public void Test_PlotTicks_OffsetNotation()
{
var plt = new ScottPlot.Plot();
plt.Axis(1e10, 1e10 + 10, 1e10, 1e10 + 10);
plt.XLabel("Horizontal Axis Label");
plt.YLabel("Vertical Axis Label");
var before = new MeanPixel(plt);
plt.Ticks(useOffsetNotation: true);
var after = new MeanPixel(plt);
TestTools.SaveFig(plt);
Assert.That(after.IsDifferentThan(before));
}
public void Test_Filter_BandStop()
{
double[] Filtered = FftSharp.Filter.BandStop(Values, SampleRate, 1900, 2100);
var plt = new ScottPlot.Plot(600, 400);
plt.PlotScatter(TimesMsec, Values, label: "Original");
plt.PlotScatter(TimesMsec, Filtered, label: "Band-Pass", lineWidth: 2);
plt.YLabel("Signal Value");
plt.XLabel("Time (milliseconds)");
plt.Legend();
plt.Axis(x1: 4, x2: 6);
TestTools.SaveFig(plt);
}
public void Test_PlotTicks_ExponentialNotation()
{
var plt = new ScottPlot.Plot();
plt.Axis(-1e10, 1e10, -1e10, 1e10);
plt.XLabel("Horizontal Axis Label");
plt.YLabel("Vertical Axis Label");
plt.Ticks(useMultiplierNotation: true);
var before = new MeanPixel(plt);
plt.Ticks(useExponentialNotation: false);
var after = new MeanPixel(plt);
TestTools.SaveFig(plt);
Assert.That(after.IsDifferentThan(before));
}
public void Test_Bar_ShowValuesHorizontal()
{
double[] xs = { 1, 2, 3, 4, 5 };
double[] ys1 = { 10, 15, 12, 6, 8, };
double[] ys2 = { 6, 8, 8, 9, 5 };
var plt = new ScottPlot.Plot(400, 300);
plt.PlotBar(xs, ys1, xOffset: -.20, barWidth: 0.3, showValues: true, label: "Series A", horizontal: true);
plt.PlotBar(xs, ys2, xOffset: +.20, barWidth: 0.3, showValues: true, label: "Series B", horizontal: true);
plt.Grid(lineStyle: ScottPlot.LineStyle.Dot, enableVertical: false);
plt.Legend(location: ScottPlot.legendLocation.upperRight);
plt.Axis(x1: 0);
TestTools.SaveFig(plt);
}
public void Test_OHLC_SetWidth()
{
var ohlcs = new ScottPlot.OHLC[]
{
// open, high, low, close, time, timeSpan
new ScottPlot.OHLC(273, 275, 264, 265, 1, 1),
new ScottPlot.OHLC(267, 276, 265, 274, 2.5, 2),
new ScottPlot.OHLC(277, 280, 275, 278, 4, 1),
};
var plt = new ScottPlot.Plot(400, 300);
plt.Grid(false);
plt.PlotOHLC(ohlcs, autoWidth: false);
plt.Axis(-1, 5);
TestTools.SaveFig(plt);
}
public void Test_AxisAutoX_Repeated()
{
double[] xs = { 1, 2, 3, 4, 5 };
double[] ys = { 1, 4, 9, 16, 25 };
var plt = new ScottPlot.Plot(400, 300);
plt.PlotScatter(xs, ys);
plt.Axis(-5, 10, -15, 40);
for (int i = 0; i < 10; i++)
{
plt.AxisAutoX();
}
TestTools.SaveFig(plt);
}
public void Test_PlotTicks_DateTime()
{
var plt = new ScottPlot.Plot();
DateTime dt1 = new DateTime(2020, 1, 1);
DateTime dt2 = new DateTime(2020, 12, 25);
plt.Axis(dt1.ToOADate(), dt2.ToOADate(), dt1.ToOADate(), dt2.ToOADate());
plt.XLabel("Horizontal Axis Label");
plt.YLabel("Vertical Axis Label");
var before = new MeanPixel(plt);
plt.Ticks(dateTimeX: true, dateTimeY: true);
var after = new MeanPixel(plt);
TestTools.SaveFig(plt);
Assert.That(after.IsDifferentThan(before));
}
public void Test_Candle_CustomColors()
{
var ohlcs = new ScottPlot.OHLC[]
{
// open, high, low, close, time, timeSpan
new ScottPlot.OHLC(273, 275, 264, 265, 1, 1),
new ScottPlot.OHLC(267, 276, 265, 274, 2.5, 2),
new ScottPlot.OHLC(277, 280, 275, 278, 4, 1),
};
var colorUp = System.Drawing.ColorTranslator.FromHtml("#9926a69a");
var colorDown = System.Drawing.ColorTranslator.FromHtml("#99ef5350");
var plt = new ScottPlot.Plot(400, 300);
plt.PlotCandlestick(ohlcs, colorUp, colorDown, autoWidth: false);
plt.Axis(-1, 5);
TestTools.SaveFig(plt);
}
public void Test_AscendingUnevenlySpacedXs_ShouldRenderWell()
{
// generate random, ascending, unevenly-spaced data
Random rand = new Random(0);
int pointCount = 100_000;
double[] ys = new double[pointCount];
double[] xs = new double[pointCount];
for (int i = 1; i < ys.Length; i++)
{
ys[i] = ys[i - 1] + rand.NextDouble() - .5;
xs[i] = xs[i - 1] + rand.NextDouble();
}
var plt = new ScottPlot.Plot(500, 350);
plt.PlotSignalXY(xs, ys);
plt.Axis(20530, 20560, -61, -57);
TestTools.SaveFig(plt);
}
public void TestGroup_Axes()
{
Console.Write($"Axis adjustments (auto, pan, zoom) ... ");
plt.Clear();
plt.PlotScatter(xs, ys);
plt.AxisAuto();
double[] axesBefore = new double[4];
Array.Copy(plt.Axis(), axesBefore, 4);
plt.Axis(-1, 1, -1, 1);
Debug.Assert(axesAreDifferent(axesBefore, plt.Axis()));
plt.AxisAuto();
Debug.Assert(!axesAreDifferent(axesBefore, plt.Axis()));
plt.AxisPan(1, 2);
Debug.Assert(axesAreDifferent(axesBefore, plt.Axis()));
plt.AxisAuto();
Debug.Assert(!axesAreDifferent(axesBefore, plt.Axis()));
plt.AxisZoom(2, 3);
Debug.Assert(axesAreDifferent(axesBefore, plt.Axis()));
plt.AxisAuto();
Debug.Assert(!axesAreDifferent(axesBefore, plt.Axis()));
Pass();
}
/// <summary>
/// The left plot is mainly used for spectra.
/// </summary>
/// <param name="x"></param>
/// <param name="y"></param>
/// <param name="fitGraphics">Skip by null or
/// <see cref="SpectraProcessor.FitGraphics.Empty"/></param>
/// <param name="xLabel">Fill null >> default from <see cref="Constants"/>.</param>
/// <param name="yLabel">Fill null >> default from <see cref="Constants"/>.</param>
private void PlotLeft(double[] x, double[] y,
SpectraProcessor.FitGraphics fitGraphics,
string xLabel = null, string yLabel = null)
{
if (plotLeft == null)
{
return;
}
if (x.Length != y.Length)
{
return;
}
plotLeft.XLabel(xLabel ?? constants.PlotLeft_XLabel);
plotLeft.YLabel(yLabel ?? constants.PlotLeft_YLabel);
plotLeft.AxisAuto(horizontalMargin: .9, verticalMargin: .5);
plotLeft.Axis(null, null, 0, null);
plotLeft.Clear();
plotLeft.PlotScatter(x, y, markerSize: 0, color: Color.Red, lineWidth: 0.1);
if (!SpectraProcessor.FitGraphics.IsNullOrEmpty(fitGraphics))
{
// Plot fit lines and crossing point.
plotLeft.PlotScatter(fitGraphics.LeftLineXs, fitGraphics.LeftLineYs,
markerSize: 0, color: Color.Black);
plotLeft.PlotScatter(fitGraphics.RightLineXs, fitGraphics.RightLineYs,
markerSize: 0, color: Color.Black);
plotLeft.PlotPoint(fitGraphics.Intersection.X, fitGraphics.Intersection.Y,
markerSize: 5, color: Color.Blue);
// Mark points where fitting occured.
double[] xFit, yFit;
// Left line.
(xFit, yFit) = fitGraphics.MarkedPlotLeft(x, y);
plotLeft.PlotScatter(xFit, yFit, markerSize: 3, color: Color.Black, lineWidth: 0);
// Right line.
(xFit, yFit) = fitGraphics.MarkedPlotRight(x, y);
plotLeft.PlotScatter(xFit, yFit, markerSize: 3, color: Color.Black, lineWidth: 0);
}
formsPlotLeft.Render();
}
public string Figure_65_Histogram()
{
string name = System.Reflection.MethodBase.GetCurrentMethod().Name.Replace("Figure_", "");
string fileName = System.IO.Path.GetFullPath($"{outputFolderName}/{name}.png");
Random rand = new Random(0);
double[] values1 = ScottPlot.DataGen.RandomNormal(rand, pointCount: 1000, mean: 50, stdDev: 20);
var hist1 = new ScottPlot.Histogram(values1, min: 0, max: 100);
var plt = new ScottPlot.Plot(width, height);
plt.Title("Histogram");
plt.YLabel("Count (#)");
plt.XLabel("Value (units)");
plt.PlotBar(hist1.bins, hist1.counts, barWidth: 1);
plt.Axis(null, null, 0, null);
plt.SaveFig(fileName);
Console.WriteLine($"Saved: {System.IO.Path.GetFileName(fileName)}");
return(name + ":" + ScottPlot.Tools.BitmapHash(plt.GetBitmap()));
}
public void Test_Bar_Stacked()
{
double[] xs = { 1, 2, 3, 4, 5 };
double[] valuesA = { 1, 2, 3, 2, 1, };
double[] valuesB = { 3, 3, 2, 1, 3 };
// to simulate stacking, shift B up by A
double[] valuesB2 = new double[valuesB.Length];
for (int i = 0; i < valuesB.Length; i++)
{
valuesB2[i] = valuesA[i] + valuesB[i];
}
var plt = new ScottPlot.Plot(400, 300);
plt.PlotBar(xs, valuesB2, label: "Series B"); // plot the uppermost bar first
plt.PlotBar(xs, valuesA, label: "Series A"); // plot lower bars last (in front)
plt.Legend(location: ScottPlot.legendLocation.upperRight);
plt.Axis(y2: 7);
plt.Title("Stacked Bar Charts");
TestTools.SaveFig(plt);
}
public string Figure_62_Plot_Bar_Data_Fancy()
{
string name = System.Reflection.MethodBase.GetCurrentMethod().Name.Replace("Figure_", "");
string fileName = System.IO.Path.GetFullPath($"{outputFolderName}/{name}.png");
// generate some more complex data
Random rand = new Random(0);
int pointCount = 10;
double[] Xs = new double[pointCount];
double[] dataA = new double[pointCount];
double[] errorA = new double[pointCount];
double[] XsB = new double[pointCount];
double[] dataB = new double[pointCount];
double[] errorB = new double[pointCount];
for (int i = 0; i < pointCount; i++)
{
Xs[i] = i * 10;
dataA[i] = rand.NextDouble() * 100;
dataB[i] = rand.NextDouble() * 100;
errorA[i] = rand.NextDouble() * 10;
errorB[i] = rand.NextDouble() * 10;
}
var plt = new ScottPlot.Plot(width, height);
plt.Title("Multiple Bar Plots");
plt.Grid(false);
// we customize barWidth and xOffset to squeeze grouped bars together
plt.PlotBar(Xs, dataA, errorY: errorA, label: "data A", barWidth: 3.2, xOffset: -2);
plt.PlotBar(Xs, dataB, errorY: errorB, label: "data B", barWidth: 3.2, xOffset: 2);
plt.Axis(null, null, 0, null);
plt.Legend();
plt.SaveFig(fileName);
Console.WriteLine($"Saved: {System.IO.Path.GetFileName(fileName)}");
return(name + ":" + ScottPlot.Tools.BitmapHash(plt.GetBitmap()));
}
/// <summary>
/// The right plot is mainly used for temperature history.
/// </summary>
/// <param name="x"></param>
/// <param name="y"></param>
/// <param name="xLabel">Fill null >> default from <see cref="Constants"/>.</param>
/// <param name="yLabel">Fill null >> default from <see cref="Constants"/>.</param>
private void PlotRight(double[] x, double[] y, string xLabel = null, string yLabel = null)
{
if (plotRight == null)
{
return;
}
double length;
if (x.Length == y.Length)
{
length = x.Length;
}
else
{
return;
}
if (length > 0)
{
double?timesMin, timesMax, temperaturesMin, temperaturesMax; // Axis limits.
if (length == 1)
{
timesMin = x[0] - 1;
timesMax = x[0] + 1;
temperaturesMin = y.Min() - 1;
temperaturesMax = y.Max() + 1;
}
else
{
timesMin = timesMax = temperaturesMin = temperaturesMax = null;
bool timesEqual = x.Min() == x.Max();
bool temperaturesEqual = y.Min() == y.Max();
if (timesEqual)
{
timesMin = x.Min() - 1;
timesMax = x.Max() + 1;
}
if (temperaturesEqual)
{
temperaturesMin = y.Min() - 1;
temperaturesMax = y.Max() + 1;
}
if (!(timesEqual || temperaturesEqual)) // Main case.
{
plotRight.AxisAuto(.9, .5);
if (x.Min() >= 0)
{
timesMin = 0d;
}
;
}
}
plotRight.Axis(timesMin, timesMax, temperaturesMin, temperaturesMax);
plotRight.XLabel(xLabel ?? constants.PlotRight_XLabel);
plotRight.YLabel(yLabel ?? constants.PlotRight_YLabel);
plotRight.Clear();
plotRight.PlotScatter(x, y, color: Color.Red);
}
formsPlotRight.Render();
}
