public void Test_RenderingArtifacts_Demonstrate()
{
// Due to a bug in System.Drawing the drawing of perfectly straight lines is
// prone to rendering artifacts (diagonal lines) when anti-aliasing is off.
// https://github.com/swharden/ScottPlot/issues/327
// https://github.com/swharden/ScottPlot/issues/401
var plt = new ScottPlot.Plot(400, 300);
plt.Grid(xSpacing: 2, ySpacing: 2, color: Color.Red);
plt.Axis(-13, 13, -10, 10);
// create conditions to reveal rendering artifact
plt.AntiAlias(false, false, false);
plt.Grid(enableVertical: false);
// save the figure (bmpData + bmpFigure)
TestTools.SaveFig(plt);
// save the data bitmap too
string gfxFilePath = System.IO.Path.GetFullPath("diag.png");
plt.GetSettings(false).bmpData.Save(gfxFilePath, ImageFormat.Png);
Console.WriteLine($"SAVED: {gfxFilePath}");
}
public void Test_PlottablePopulations_Population()
{
// This example will display a single population: mean age of every country in europe in 2007
// This example has 1 series that contains 1 population.
// for this example we will simulate countries by creating random data
Random rand = new Random(0);
var ages = new Population(rand, 44, 78, 2);
var customPlottable = new PopulationPlot(ages);
// plot the multi-series
var plt = new ScottPlot.Plot(400, 300);
plt.Add(customPlottable);
plt.XAxis.Ticks(false);
// additional plot styling
plt.Title("Life Expectancy in European Countries in 2007");
plt.YLabel("Age (years)");
plt.Legend(location: Alignment.LowerRight);
plt.Grid(lineStyle: LineStyle.Dot);
plt.XAxis.Grid(false);
TestTools.SaveFig(plt);
}
public void Test_Bar_MultiSeries()
{
Random rand = new Random(0);
string[] groupNames = { "one", "two", "three", "four", "five" };
string[] seriesNames = { "alpha", "beta", "gamma" };
int groupCount = groupNames.Length;
double[] xs = DataGen.Consecutive(groupCount);
double[] ys1 = DataGen.RandomNormal(rand, groupCount, 20, 5);
double[] ys2 = DataGen.RandomNormal(rand, groupCount, 20, 5);
double[] ys3 = DataGen.RandomNormal(rand, groupCount, 20, 5);
double[] err1 = DataGen.RandomNormal(rand, groupCount, 5, 2);
double[] err2 = DataGen.RandomNormal(rand, groupCount, 5, 2);
double[] err3 = DataGen.RandomNormal(rand, groupCount, 5, 2);
var plt = new ScottPlot.Plot(600, 400);
plt.PlotBarGroups(
groupLabels: groupNames,
seriesLabels: seriesNames,
ys: new double[][] { ys1, ys2, ys3 },
yErr: new double[][] { err1, err2, err3 });
plt.Axis(y1: 0);
plt.Grid(enableVertical: false, lineStyle: LineStyle.Dot);
plt.Legend(location: Alignment.UpperRight);
TestTools.SaveFig(plt);
}
public static void PlotMonthlyChange(List <MonthlyClosedDifference> series, string propertyName, string folderName, string fileName)
{
// get and convert specific property of a list of objects to array of doubles
PropertyInfo prop = typeof(MonthlyClosedDifference).GetProperty(propertyName);
double[] valSeries = series.Select(x => Convert.ToDouble(prop.GetValue(x))).ToArray();
// months to x values and labels
double[] x = DataGen.Consecutive(series.Count());
string[] labels = series.Select(x => x.Month).ToArray();
var plt = new ScottPlot.Plot(1000, 700);
plt.Title(propertyName, fontName: "Segoe UI Light", color: Color.Black);
plt.Ticks(dateTimeX: false, fontName: "Cascadia Mono");
plt.Grid(xSpacing: 1);
// apply custom axis tick labels
plt.XTicks(x, labels);
// create folder if not exists
System.IO.Directory.CreateDirectory(folderName);
plt.PlotBar(x, valSeries, fillColor: Color.Orange);
plt.SaveFig($"./{folderName}/{fileName}.png");
}
public static void PlotOHLC(List <StockHistoryDay> stockHistory, string folderName, string fileName)
{
List <ScottPlot.OHLC> valSeriesList = new List <ScottPlot.OHLC>();
foreach (StockHistoryDay stockHistoryDay in stockHistory)
{
ScottPlot.OHLC ohlc = new ScottPlot.OHLC(
stockHistoryDay.Open,
stockHistoryDay.High,
stockHistoryDay.Low,
stockHistoryDay.Close,
stockHistoryDay.Date
);
valSeriesList.Add(ohlc);
}
ScottPlot.OHLC[] valSeries = valSeriesList.ToArray();
var plt = new ScottPlot.Plot(1000, 700);
plt.Title("MSFT", fontName: "Segoe UI Light", color: Color.Black);
plt.Ticks(dateTimeX: true, fontName: "Cascadia Mono");
// grids at every 7 days
plt.Grid(xSpacing: 7, xSpacingDateTimeUnit: ScottPlot.Config.DateTimeUnit.Day);
plt.SetCulture(shortDatePattern: "M\\/dd");
// create folder if not exists
System.IO.Directory.CreateDirectory(folderName);
plt.PlotOHLC(valSeries);
plt.SaveFig($"./{folderName}/{fileName}.png");
}
public void Test_PlottablePopulations_Series()
{
// This example will display age, grouped by location.
// This example has 1 series that contains 5 population objects.
// for this example we will simulate countries by creating random data
Random rand = new Random(0);
var ages = new Population[]
{
new Population(rand, 54, 53, 5), // africa
new Population(rand, 35, 72, 3), // americas
new Population(rand, 48, 72, 4), // asia
new Population(rand, 44, 78, 2), // europe
new Population(rand, 14, 81, 1), // oceania
};
var customPlottable = new PopulationPlot(ages, color: System.Drawing.Color.CornflowerBlue);
// plot the multi-series
var plt = new ScottPlot.Plot();
plt.Add(customPlottable);
plt.XTicks(labels: new string[] { "Africas", "Americas", "Asia", "Europe", "Oceania" });
plt.XAxis.TickLabelStyle(fontSize: 18);
plt.YAxis.TickLabelStyle(fontSize: 18);
// additional plot styling
plt.XAxis2.Label(label: "Life Expectancy in 2007", size: 26);
plt.YAxis.Label(label: "Age (years)", size: 18);
plt.Legend(location: Alignment.LowerRight);
plt.Grid(lineStyle: LineStyle.Dot);
plt.XAxis.Grid(false);
TestTools.SaveFig(plt);
}
static void Main(string[] args)
{
BendStiffener bendStiffener = new BendStiffener
{
max_k = 0.3f,
D1 = 0.7,
d1 = 0.18,
d2 = 0.2,
L1 = 0.1,
L2 = 2.3,
L3 = 0.2,
EIp = 1e4,
Es = 4.5e6,
F = 2e4,
q = 0.52
};
int N = 10000;
Vector <double>[] res = bendStiffener.bvpsolver_zzz(bendStiffener.Ode_to_solve, 0.0, bendStiffener.q, 0.0, 5.0, N);
double[] x = Vector <double> .Build.Dense(N, i => i * 5.0 / N).ToArray();
double[] y = new double[N];
double[] dydx = new double[N];
for (int i = 0; i < N; i++)
{
double[] temp = res[i].ToArray();
y[i] = temp[0];
dydx[i] = temp[1];
//Console.WriteLine(t[i]);
}
var plt = new ScottPlot.Plot(800, 600);
//plt.PlotScatter(x, y, label: "y", markerShape: (MarkerShape)Enum.Parse(typeof(MarkerShape), "none"));
plt.PlotScatter(x, dydx, label: "dydx", markerShape: (MarkerShape)Enum.Parse(typeof(MarkerShape), "none"));
plt.Grid(false);
plt.Legend(fontSize: 10);
//plt.PlotSignal(new[,] { x, y });
plt.SaveFig("quickstart.png");
Console.WriteLine("plot finished"); // gives 164,537981852489
//Test
//Console.WriteLine(y[N / 10]); // gives 164,537981852489
//Console.WriteLine(Math.Exp(-1) + 3 * Math.Exp(4) - 5.0 / 2 + 23.0 / 8); //gives 164,537329540604, which is y(1)
Console.ReadKey();
}
/// <summary>
/// Method for plotting data to .png
/// </summary>
/// <param name="dataPoints"></param>
public static void Graph(double[,] dataPoints)
{
double[] DataError = new double[dataPoints.GetUpperBound(0) + 1];
double[] DataAccuracy = new double[dataPoints.GetUpperBound(0) + 1];
double[] dataXs = new double[dataPoints.GetUpperBound(0) + 1];
for (int i = 0; i < dataXs.Length; i++)
{
dataXs[i] = i;
DataError[i] = dataPoints[i, 0];
DataAccuracy[i] = dataPoints[i, 1];
}
/// plot the data
///
var plt_acc = new ScottPlot.Plot(800, 600);
var plt_loss = new ScottPlot.Plot(800, 600);
plt_acc.PlotScatter(dataXs, DataAccuracy, label: "Accuracy");
plt_loss.PlotScatter(dataXs, DataError, label: "Error rate");
plt_acc.Grid(xSpacing: 20, ySpacing: .1);
plt_loss.Grid(xSpacing: 5, ySpacing: .1);
plt_acc.Legend(location: legendLocation.upperLeft);
plt_loss.Legend(location: legendLocation.upperLeft);
plt_acc.Title("Accuracy");
plt_loss.Title("Loss");
plt_acc.XLabel("Epoch");
plt_acc.YLabel("Accuracy");
plt_loss.XLabel("Epoch");
plt_loss.YLabel("Loss");
plt_acc.SaveFig("NN_acc.png");
plt_loss.SaveFig("NN_loss.png");
Process.Start(new ProcessStartInfo(@"NN_acc.png")
{
UseShellExecute = true
});
Process.Start(new ProcessStartInfo(@"NN_loss.png")
{
UseShellExecute = true
});
}
public void Test_PolygonVsScatter_Alignment()
{
double[] xs = { 75, 250, 280, 100 };
double[] ys = { -100, -75, -200, -220 };
var plt = new ScottPlot.Plot(320, 240);
plt.PlotPolygon(xs, ys, fillColor: Color.LightGreen);
plt.PlotLine(xs[0], ys[0], xs[1], ys[1], Color.Blue);
plt.Grid(false);
plt.Frame(false);
plt.Ticks(false, false);
plt.Title("Line/Scatter");
TestTools.SaveFig(plt);
}
public void Test_ScaleBar_Simple()
{
var plt = new ScottPlot.Plot(400, 300);
plt.PlotSignal(DataGen.Sin(51));
plt.PlotSignal(DataGen.Cos(51, mult: 1.5));
plt.PlotScaleBar(5, .25, "5 ms", "250 pA");
plt.Grid(false);
plt.Frame(false);
plt.Ticks(false, false);
plt.AxisAuto(0);
plt.LayoutFrameless();
TestTools.SaveFig(plt);
}
public void Test_Population_CurveSideways()
{
Random rand = new Random(0);
var ages = new ScottPlot.Statistics.Population(rand, 44, 78, 2);
double[] curveXs = DataGen.Range(ages.minus3stDev, ages.plus3stDev, .1);
double[] curveYs = ages.GetDistribution(curveXs);
var plt = new ScottPlot.Plot(400, 300);
plt.PlotScatter(DataGen.Random(rand, ages.values.Length), ages.values,
markerSize: 10, markerShape: MarkerShape.openCircle, lineWidth: 0);
plt.PlotScatter(curveYs, curveXs, markerSize: 0);
plt.Grid(lineStyle: LineStyle.Dot);
TestTools.SaveFig(plt);
}
public void GenerateMultipleBoxAndWhiskers(List <List <ResultModel> > allResults, List <int> xValues, string plotTitle, string plotName = "results")
{
var plt = new ScottPlot.Plot(600, 400);
var poulations = new ScottPlot.Statistics.Population[allResults.Count];
var p = 0;
foreach (var results in allResults)
{
var ys = new double[results.Count];
var i = 0;
foreach (var r in results)
{
ys[i] = r.Fitness;
i++;
}
var pop = new ScottPlot.Statistics.Population(ys);
poulations[p] = pop;
p++;
}
var popSeries = new ScottPlot.Statistics.PopulationSeries(poulations);
plt.PlotPopulations(popSeries, "scores");
// improve the style of the plot
plt.Title(plotTitle);
plt.YLabel("Solution energy");
var ticks = new string[xValues.Count];
var j = 0;
foreach (var iterations in xValues)
{
ticks[j] = iterations.ToString();
j++;
}
plt.XTicks(ticks);
plt.Legend();
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
plt.SaveFig($"{plotName}.png");
}
private string MakeGraph(string[] labels, double[] values)
{
double[] xs = DataGen.Consecutive(labels.Count());
var plt = new ScottPlot.Plot(1920, 1080);
plt.PlotBar(xs, values);
// customize the plot to make it look nicer
plt.Grid(enableVertical: false, lineStyle: LineStyle.Dot);
plt.XTicks(xs, labels);
plt.Ticks(fontSize: 25, xTickRotation: 45);
plt.Layout(yScaleWidth: 80, titleHeight: 50, xLabelHeight: 200, y2LabelWidth: 20);
string path = "graph.png";
plt.SaveFig(path);
return path;
}
public void Test_PolygonVsSignal_AlignmentWithLargeValues()
{
double[] xs = { 1e6 + 75, 1e6 + 250, 1e6 + 280, 1e6 + 100 };
double[] ys = { 1e6 - 100, 1e6 - 75, 1e6 - 200, 1e6 - 220 };
var plt = new ScottPlot.Plot(320, 240);
plt.PlotPolygon(xs, ys, fillColor: Color.LightGreen);
plt.PlotSignal(
ys: new double[] { ys[0], ys[1] },
sampleRate: 1.0 / (xs[1] - xs[0]),
xOffset: xs[0],
color: Color.Blue,
markerSize: 0
);
plt.Grid(false);
plt.Frame(false);
plt.Ticks(false, false);
plt.Title("Large Value Signal");
TestTools.SaveFig(plt);
}
public void Test_PolygonVsSignal_AlignmentWithLargeValues()
{
double[] xs = { 1e6 + 75, 1e6 + 250, 1e6 + 280, 1e6 + 100 };
double[] ys = { 1e6 - 100, 1e6 - 75, 1e6 - 200, 1e6 - 220 };
var plt = new ScottPlot.Plot(320, 240);
plt.AddPolygon(xs, ys, fillColor: Color.LightGreen);
var sig = plt.AddSignal(
ys: new double[] { ys[0], ys[1] },
sampleRate: 1.0 / (xs[1] - xs[0]),
color: Color.Blue);
sig.MarkerSize = 0;
sig.OffsetX = xs[0];
plt.Grid(false);
plt.Frameless();
plt.XAxis.Ticks(false);
plt.YAxis.Ticks(false);
plt.Title("Large Value Signal");
TestTools.SaveFig(plt);
}
static void Main(string[] args)
{
int N = 10000;
Vector <double> y0 = Vector <double> .Build.Dense(new[] { -7.0 / 4.0, 55.0 / 8.0 });
//Func<double, Vector<double>, Vector<double>> der = DerivativeMaker();
Vector <double>[] res = RungeKutta.FourthOrder(y0, 0, 10, N, DerivativeMaker_zzz2);
double[] t = Vector <double> .Build.Dense(N, i => i * 10.0 / N).ToArray();
double[] x = new double[N];
double[] y = new double[N];
for (int i = 0; i < N; i++)
{
double[] temp = res[i].ToArray();
x[i] = temp[0];
y[i] = temp[1];
//Console.WriteLine(t[i]);
}
var plt = new ScottPlot.Plot(800, 600);
plt.PlotScatter(t, x, label: "x", markerShape: (MarkerShape)Enum.Parse(typeof(MarkerShape), "none"));
plt.PlotScatter(t, y, label: "y", markerShape: (MarkerShape)Enum.Parse(typeof(MarkerShape), "none"));
plt.Grid(false);
plt.Legend(fontSize: 10);
//plt.PlotSignal(new[,] { x, y });
plt.SaveFig("quickstart.png");
//Test
Console.WriteLine(y[N / 10]); // gives 164,537981852489
Console.WriteLine(Math.Exp(-1) + 3 * Math.Exp(4) - 5.0 / 2 + 23.0 / 8); //gives 164,537329540604, which is y(1)
Console.ReadKey();
}
public void Test_PlottablePopulations_MultiSeries()
{
// This example will display age, grouped by location, and by year.
// This example has 3 series (years), each of which has 5 population objects (locations).
// for this example we will simulate countries by creating random data
Random rand = new Random(0);
// start by collecting series data as Population[] arrays
var ages1957 = new Population[]
{
new Population(rand, 54, 42, 4), // africa
new Population(rand, 35, 56, 6), // americas
new Population(rand, 48, 47, 5), // asia
new Population(rand, 44, 66, 2), // europe
new Population(rand, 14, 70, 1), // oceania
};
var ages1987 = new Population[]
{
new Population(rand, 54, 52, 8), // africa
new Population(rand, 35, 70, 3), // americas
new Population(rand, 48, 66, 3), // asia
new Population(rand, 44, 75, 2), // europe
new Population(rand, 14, 75, 1), // oceania
};
var ages2007 = new Population[]
{
new Population(rand, 54, 53, 5), // africa
new Population(rand, 35, 72, 3), // americas
new Population(rand, 48, 72, 4), // asia
new Population(rand, 44, 78, 2), // europe
new Population(rand, 14, 81, 1), // oceania
};
// now create a PopulationSeries object for each series
string[] groupLabels = new string[] { "Africa", "Americas", "Asia", "Europe", "Oceania" };
var series1957 = new PopulationSeries(ages1957, "1957", color: System.Drawing.Color.Red);
var series1987 = new PopulationSeries(ages1987, "1987", color: System.Drawing.Color.Green);
var series2007 = new PopulationSeries(ages2007, "2007", color: System.Drawing.Color.Blue);
// now collect all the series into a MultiSeries
var multiSeries = new PopulationSeries[] { series1957, series1987, series2007 };
var plottableMultiSeries = new PopulationMultiSeries(multiSeries);
var customPlottable = new PopulationPlot(plottableMultiSeries);
// plot the multi-series
var plt = new ScottPlot.Plot();
plt.Add(customPlottable);
plt.XTicks(labels: groupLabels);
plt.XAxis.TickLabelStyle(fontSize: 18);
plt.YAxis.TickLabelStyle(fontSize: 18);
// additional plot styling
plt.XAxis2.Label(label: "Life Expectancy", size: 26);
plt.YAxis.Label(label: "Age (years)", size: 18);
plt.Legend(location: Alignment.LowerRight);
plt.Grid(lineStyle: LineStyle.Dot);
plt.XAxis.Grid(false);
TestTools.SaveFig(plt);
}
