private void FillDemoPlots()
{
Random rand = new Random();
if (true)
{
var plt = new ScottPlot.Plot(600, 400);
int pointCount = 51;
double[] xs = DataGen.Consecutive(pointCount);
double[] sin = DataGen.Sin(pointCount);
double[] cos = DataGen.Cos(pointCount);
plt.PlotScatter(xs, sin, label: "sin");
plt.PlotScatter(xs, cos, label: "cos");
plt.Legend();
plt.Title("Scatter Plot Quickstart");
plt.YLabel("Vertical Units");
plt.XLabel("Horizontal Units");
var pv1 = new ScottPlot.WpfPlot();
pv1.Height = 200;
plt.Title("Scatter Plot Quickstart");
plt.YLabel("Vertical Units");
plt.XLabel("Horizontal Units");
StackPanelCharts.Children.Add(pv1);
}
if (true)
{
var pv1 = new ScottPlot.WpfPlot();
pv1.Height = 200;
pv1.plt.PlotSignal(DataGen.RandomWalk(rand, 100));
var plt = pv1.plt;
int pointCount = 51;
double[] xs = DataGen.Consecutive(pointCount);
double[] sin = DataGen.Sin(pointCount);
double[] cos = DataGen.Cos(pointCount);
plt.PlotScatter(xs, sin, label: "sin");
plt.PlotScatter(xs, cos, label: "cos");
plt.Legend();
plt.Title("Scatter Plot Quickstart");
plt.YLabel("Vertical Units");
plt.XLabel("Horizontal Units");
StackPanelCharts.Children.Add(pv1);
}
}
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_SMA_Candlestick()
{
Random rand = new Random(0);
double[] xs = DataGen.Consecutive(150);
OHLC[] ohlcs = DataGen.RandomStockPrices(rand, xs.Length);
double[] sma20 = ScottPlot.Statistics.Finance.SMA(ohlcs, 20);
double[] sma50 = ScottPlot.Statistics.Finance.SMA(ohlcs, 50);
// replace timestamps with a series of numbers starting at 0
for (int i = 0; i < ohlcs.Length; i++)
{
ohlcs[i].time = i;
}
var plt = new ScottPlot.Plot(600, 400);
plt.PlotCandlestick(ohlcs);
plt.PlotScatter(xs, sma20, label: "20 day SMA",
color: Color.Blue, markerSize: 0, lineWidth: 2);
plt.PlotScatter(xs, sma50, label: "50 day SMA",
color: Color.Maroon, markerSize: 0, lineWidth: 2);
plt.Title("Simple Moving Average (SMA)");
plt.YLabel("Price");
plt.XLabel("Days");
plt.Legend();
plt.AxisAutoX(.03);
TestTools.SaveFig(plt);
}
public void SaveScottPlotTestFromWebsite()
{
string saveFileLocation = "C:\\Temp\\Quickstart_Quickstart_Scatter.png";
var plt = new ScottPlot.Plot(600, 400);
int pointCount = 51;
double[] xs = DataGen.Consecutive(pointCount);
double[] sin = DataGen.Sin(pointCount);
double[] cos = DataGen.Cos(pointCount);
plt.AddScatter(sin, cos, label: "sin");
plt.AddScatter(xs, cos, label: "cos");
plt.Legend();
plt.Title("Scatter Plot Quickstart");
plt.YLabel("Vertical Units");
plt.XLabel("Horizontal Units");
plt.SaveFig(saveFileLocation);
Assert.IsTrue(System.IO.File.Exists(saveFileLocation));
System.IO.File.Delete(saveFileLocation);
}
public void Test_Bollinger_Bands()
{
Random rand = new Random(0);
double[] xs = DataGen.Consecutive(150);
OHLC[] ohlcs = DataGen.RandomStockPrices(rand, xs.Length);
(var sma, var bolL, var bolU) = ScottPlot.Statistics.Finance.Bollinger(ohlcs);
// replace timestamps with a series of numbers starting at 0
for (int i = 0; i < ohlcs.Length; i++)
{
ohlcs[i].time = i;
}
var plt = new ScottPlot.Plot(600, 400);
plt.PlotCandlestick(ohlcs);
plt.PlotFill(xs, bolL, xs, bolU, fillColor: Color.Blue, fillAlpha: .1);
plt.PlotScatter(xs, bolL, color: Color.Navy, markerSize: 0);
plt.PlotScatter(xs, bolU, color: Color.Navy, markerSize: 0);
plt.PlotScatter(xs, sma, color: Color.Navy, markerSize: 0, lineStyle: LineStyle.Dash);
plt.Title("Bollinger Bands");
plt.YLabel("Price");
plt.XLabel("Days");
plt.Legend();
plt.AxisAutoX(.03);
TestTools.SaveFig(plt);
}
public void Test_Bollinger_Bands()
{
Random rand = new Random(0);
double[] xs = DataGen.Consecutive(150);
OHLC[] ohlcs = DataGen.RandomStockPrices(rand, xs.Length);
// calculate moving average X and Ys
(var sma, var bolL, var bolU) = ScottPlot.Statistics.Finance.Bollinger(ohlcs, 20);
double[] xs2 = xs.Skip(20).ToArray();
// replace timestamps with a series of numbers starting at 0
for (int i = 0; i < ohlcs.Length; i++)
{
ohlcs[i].DateTime = DateTime.FromOADate(i);
}
var plt = new ScottPlot.Plot(600, 400);
plt.AddCandlesticks(ohlcs);
plt.AddFill(xs2, bolL, xs2, bolU, color: Color.FromArgb(10, Color.Blue));
plt.AddScatter(xs2, bolL, color: Color.Navy, markerSize: 0, label: "Bollinger Bands");
plt.AddScatter(xs2, bolU, color: Color.Navy, markerSize: 0);
plt.AddScatter(xs2, sma, color: Color.Navy, markerSize: 0, lineStyle: LineStyle.Dash, label: "SMA 20");
plt.Title("Moving Average and Standard Deviation");
plt.YLabel("Price");
plt.XLabel("Days");
plt.Legend();
plt.AxisAutoX(.03);
TestTools.SaveFig(plt);
}
public void Test_SaveFig_OutputScaling()
{
var plt = new ScottPlot.Plot();
plt.AddSignal(DataGen.Sin(51), label: "sin");
plt.AddSignal(DataGen.Cos(51), label: "cos");
plt.Title("Scaled Figure Demo");
plt.XLabel("Horizontal Axis");
plt.YLabel("Vertical Axis");
plt.Legend();
System.Drawing.Bitmap bmpA = plt.Render(400, 300);
Assert.AreEqual(400, bmpA.Width);
Assert.AreEqual(300, bmpA.Height);
System.Drawing.Bitmap bmpB = plt.Render(400, 300, scale: .5);
Assert.AreEqual(200, bmpB.Width);
Assert.AreEqual(150, bmpB.Height);
System.Drawing.Bitmap bmpC = plt.Render(400, 300, scale: 2);
Assert.AreEqual(800, bmpC.Width);
Assert.AreEqual(600, bmpC.Height);
System.Drawing.Bitmap bmpD = plt.Render(300, 400, scale: 2);
Assert.AreEqual(600, bmpD.Width);
Assert.AreEqual(800, bmpD.Height);
System.Drawing.Bitmap legendNormal = plt.RenderLegend();
System.Drawing.Bitmap legendBig = plt.RenderLegend(scale: 2);
Assert.Greater(legendBig.Width, legendNormal.Width);
Assert.Greater(legendBig.Height, legendNormal.Height);
}
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 PlottablePopulations(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.Ticks(fontSize: 18);
// additional plot styling
plt.Title("Life Expectancy in 2007", fontSize: 26);
plt.YLabel("Age (years)", fontSize: 18);
plt.Legend(location: legendLocation.lowerRight);
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
TestTools.SaveFig(plt);
}
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_DefinedSpacing_NumericAxis()
{
int pointCount = 20;
// create a series of day numbers
double[] days = ScottPlot.DataGen.Consecutive(pointCount);
// simulate data for each date
double[] values = new double[pointCount];
Random rand = new Random(0);
for (int i = 1; i < pointCount; i++)
{
values[i] = values[i - 1] + rand.NextDouble();
}
var pltDefault = new ScottPlot.Plot();
pltDefault.Title("Default xSpacing");
pltDefault.AddScatter(days, values);
var pltTest = new ScottPlot.Plot();
pltTest.Title("xSpacing = 1 unit");
pltTest.AddScatter(days, values);
// force inter-tick distance on a numerical axis
pltTest.XAxis.ManualTickSpacing(1);
//TestTools.SaveFig(pltDefault);
//TestTools.SaveFig(pltTest);
}
public void Test_Axis_ModeratelySmallNumbers()
{
var plt = new ScottPlot.Plot(400, 300);
plt.Title("Moderately Small (e-8)");
double[] xs = { 1e-8, 2e-8, 3e-8, 4e-8 };
double[] ys = { 1e-8, 4e-8, 3e-8, 6e-8 };
plt.PlotScatter(xs, ys);
TestTools.SaveFig(plt);
}
public void Test_Axis_ExtremelySmallNumbers()
{
var plt = new ScottPlot.Plot(400, 300);
plt.Title("Extremely Small (e-20)");
double[] xs = { 1e-20, 2e-20, 3e-20, 4e-20 };
double[] ys = { 1e-20, 4e-20, 3e-20, 6e-20 };
plt.PlotScatter(xs, ys);
TestTools.SaveFig(plt);
}
static public void RunJolka(List <Solver <string> > backtracks, List <Solver <string> > backtrackfws, string heuristicB = "", string heuristicBF = "", string type = "")
{
var plt = new ScottPlot.Plot(1280, 720);
List <double> xlist = new List <double>();
List <double> yfwlist = new List <double>();
List <double> ylist = new List <double>();
foreach (var el in backtrackfws)
{
xlist.Add(el.solvedPuzzle.Puzzle.id);
if (type == "time")
{
yfwlist.Add(el.solvedPuzzle.elapsed.TotalMilliseconds);
}
else
{
yfwlist.Add(el.solvedPuzzle.Puzzle.steps);
}
}
foreach (var el in backtracks)
{
if (type == "time")
{
ylist.Add(el.solvedPuzzle.elapsed.TotalMilliseconds);
}
else
{
ylist.Add(el.solvedPuzzle.Puzzle.steps);
}
}
double[] xs = xlist.ToArray();
ylist.Insert(2, (double)1);
double[] dataB = Tools.Log10(ylist.ToArray());
double[] dataBF = Tools.Log10(yfwlist.ToArray());
plt.PlotBar(xs, dataB, label: "Backtrack w/ " + heuristicB, barWidth: .3, xOffset: -0.2, showValues: true);
plt.PlotBar(xs, dataBF, label: "Backtrack with forward w/ " + heuristicBF, barWidth: .3, xOffset: 0.2, showValues: true);
plt.Title(type + " over Jolka id");
plt.Ticks(useExponentialNotation: false, useMultiplierNotation: false, logScaleY: true);
plt.Axis(y1: 0);
plt.XTicks(new string[] { "0", "1", "2", "3", "4" });
if (type == "time")
{
plt.YLabel("Execution time [10 ^ y ms]");
}
else
{
plt.YLabel("Steps [10 ^ y]");
}
plt.XLabel("Jolka ID");
plt.Legend(location: legendLocation.upperRight);
plt.SaveFig(heuristicB + heuristicBF + type + "JolkaBvsBF" + ".png");
}
/// <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_Layout()
{
int pointCount = 50;
double[] dataXs = DataGen.Consecutive(pointCount);
double[] dataSin = DataGen.Sin(pointCount);
double[] dataCos = DataGen.Cos(pointCount);
var plt = new ScottPlot.Plot();
plt.PlotScatter(dataXs, dataSin);
plt.PlotScatter(dataXs, dataCos);
plt.Title("Very Complicated Data");
plt.XLabel("Experiment Duration");
plt.YLabel("Productivity");
TestTools.SaveFig(plt);
}
/// <summary>
/// Return a new Plot with all the same Plottables (and some of the styles) of this one.
/// </summary>
public Plot Copy()
{
// This is typically only called when you right-click a plot in a control and hit "open in new window".
// All state from the old plot must be copied to the new plot.
Plot plt2 = new Plot(settings.Width, settings.Height);
var settings2 = plt2.GetSettings(false);
// Copying state of plottables is easy because they contain their own state.
settings2.Plottables.AddRange(settings.Plottables);
// TODO: copy axes, since they now carry their own state too.
plt2.Title(settings.XAxis2.Title.Label);
plt2.XLabel(settings.XAxis.Title.Label);
plt2.YLabel(settings.YAxis.Title.Label);
plt2.AxisAuto();
return(plt2);
}
/// <summary>
/// Return a new Plot with all the same Plottables (and some of the styles) of this one.
/// This is called when you right-click a plot in a control and hit "open in new window".
/// </summary>
public Plot Copy()
{
Settings oldSettings = settings;
Plot oldPlot = this;
Plot newPlot = new Plot(oldSettings.Width, oldSettings.Height);
foreach (IPlottable oldPlottable in oldPlot.GetPlottables())
{
newPlot.Add(oldPlottable);
}
newPlot.AxisAuto();
newPlot.XLabel(oldSettings.XAxis.Label());
newPlot.YLabel(oldSettings.YAxis.Label());
newPlot.Title(oldSettings.XAxis2.Label());
return(newPlot);
}
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");
}
public void Test_DefinedSpacing_DateTimeAxis()
{
int pointCount = 20;
// create a series of dates
double[] dates = new double[pointCount];
var firstDay = new DateTime(2020, 1, 22);
for (int i = 0; i < pointCount; i++)
{
dates[i] = firstDay.AddDays(i).ToOADate();
}
// simulate data for each date
double[] values = new double[pointCount];
Random rand = new Random(0);
for (int i = 1; i < pointCount; i++)
{
values[i] = values[i - 1] + rand.NextDouble();
}
var pltDefault = new ScottPlot.Plot();
pltDefault.Title("Default xSpacing");
pltDefault.AddScatter(dates, values);
pltDefault.XAxis.DateTimeFormat(true);
var pltTest = new ScottPlot.Plot();
pltTest.Title("xSpacing = 1 day");
pltTest.AddScatter(dates, values);
pltTest.XAxis.DateTimeFormat(true);
pltTest.XAxis.TickLabelStyle(rotation: 45);
pltTest.Layout(bottom: 60); // need extra height to accomodate rotated labels
// force 1 tick per day on a DateTime axis
pltTest.XAxis.ManualTickSpacing(1, ScottPlot.Ticks.DateTimeUnit.Day);
//TestTools.SaveFig(pltDefault);
//TestTools.SaveFig(pltTest);
}
public void Test_Layout_LabelsWithLineBreaks()
{
int pointCount = 50;
double[] dataXs = DataGen.Consecutive(pointCount);
double[] dataSin = DataGen.Sin(pointCount);
double[] dataCos = DataGen.Cos(pointCount);
var plt = new ScottPlot.Plot();
plt.PlotScatter(dataXs, dataSin);
plt.PlotScatter(dataXs, dataCos);
string labelWithLineBreak = "Line One\nLine Two";
plt.Title(labelWithLineBreak, fontSize: 30);
plt.XLabel(labelWithLineBreak);
plt.YLabel(labelWithLineBreak);
TestTools.SaveFig(plt);
}
static public void RunSudoku(double[] difficulty, double[] dataB, double[] dataBF, string heuristicB = "", string heuristicBF = "", string type = "")
{
var plt = new ScottPlot.Plot(1280, 720);
int pointCount = dataB.Length;
plt.PlotBar(difficulty, dataB, label: "Backtrack w/ " + heuristicB, barWidth: .3, xOffset: -0.2);
plt.PlotBar(difficulty, dataBF, label: "Backtrack with forward w/ " + heuristicBF, barWidth: .3, xOffset: 0.2);
plt.Title("Average " + type + " over sudoku difficulty");
plt.Axis(y1: 0);
if (type == "time")
{
plt.YLabel("Execution time [ms]");
}
else
{
plt.YLabel("Steps");
}
plt.XLabel("Difficulty");
plt.Legend(location: legendLocation.upperRight);
plt.Ticks(useExponentialNotation: false, useMultiplierNotation: false);
plt.SaveFig(heuristicB + heuristicBF + type + "BvsBF" + ".png");
}
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);
}
private ScottPlot.Plot TestColormap(Colorset cset, int lineWidth, bool dark = false)
{
var plt = new ScottPlot.Plot(600, 400);
for (int i = 0; i < cset.Count(); i++)
{
double[] ys = DataGen.Sin(51,
//mult: 1 - .5 * i / cset.Count(),
phase: -i / Math.PI / cset.Count());
plt.PlotSignal(ys, color: cset.GetColor(i), markerSize: 0, lineWidth: lineWidth);
}
if (dark)
{
plt.Style(Style.Gray1);
plt.Style(darkColor, darkColor);
}
plt.Title($"Colorset '{cset.Name}' has {cset.Count()} colors");
plt.AxisAuto(0);
return(plt);
}
private ScottPlot.Plot TestColormap(Palette cset, int lineWidth, bool dark = false)
{
var plt = new ScottPlot.Plot(600, 400);
for (int i = 0; i < cset.Count(); i++)
{
double[] ys = DataGen.Sin(51, phase: -i / Math.PI / cset.Count());
var sig = plt.AddSignal(ys, color: cset.GetColor(i));
sig.MarkerSize = 0;
sig.LineWidth = lineWidth;
}
if (dark)
{
plt.Style(Style.Gray1);
plt.Style(darkColor, darkColor);
}
plt.Title($"Colorset '{cset.Name}' has {cset.Count()} colors");
plt.AxisAuto(0);
return(plt);
}
public void Test_PolygonVsSignal_AlignmentWithLargeValues()
{
double[] xs = { 1e6 + 75, 1e6 + 250, 1e6 + 280, 1e6 + 100 };
double[] ys = { 1e6 - 100, 1e6 - 75, 1e6 - 200, 1e6 - 220 };
var plt = new ScottPlot.Plot(320, 240);
plt.AddPolygon(xs, ys, fillColor: Color.LightGreen);
var sig = plt.AddSignal(
ys: new double[] { ys[0], ys[1] },
sampleRate: 1.0 / (xs[1] - xs[0]),
color: Color.Blue);
sig.MarkerSize = 0;
sig.OffsetX = xs[0];
plt.Grid(false);
plt.Frameless();
plt.XAxis.Ticks(false);
plt.YAxis.Ticks(false);
plt.Title("Large Value Signal");
TestTools.SaveFig(plt);
}
public void Test_scatter_10kPoints()
{
double[] pointCounts = { 10, 100, 1000, 10000 };
const int REPS = 10;
double[] speeds = new double[pointCounts.Length];
for (int i = 0; i < pointCounts.Length; i++)
{
int pointCount = (int)pointCounts[i];
var plt = new ScottPlot.Plot();
Random rand = new Random(0);
double[] xs = DataGen.Random(rand, pointCount);
double[] ys = DataGen.RandomWalk(rand, pointCount);
plt.AddScatter(xs, ys);
plt.Render(lowQuality: true);
List <double> times = new List <double>();
for (int j = 0; j < REPS; j++)
{
plt.Render(lowQuality: true);
times.Add(plt.GetSettings(false).BenchmarkMessage.MSec);
}
var stats = new ScottPlot.Statistics.Population(times.ToArray());
speeds[i] = stats.mean;
Console.WriteLine($"Rendered {pointCount} points in {stats.mean} ms");
}
var plt2 = new ScottPlot.Plot(400, 300);
plt2.Title("Scatter Plot Benchmark");
plt2.YLabel("Time (ms)");
plt2.XLabel("Number of Points");
plt2.AddScatter(pointCounts, speeds);
TestTools.SaveFig(plt2);
}
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 PlottablePopulations(plottableMultiSeries);
// plot the multi-series
var plt = new ScottPlot.Plot();
plt.Add(customPlottable);
plt.XTicks(labels: groupLabels);
plt.Ticks(fontSize: 18);
// additional plot styling
plt.Title("Life Expectancy", fontSize: 26);
plt.YLabel("Age (years)", fontSize: 18);
plt.Legend(location: legendLocation.lowerRight);
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
TestTools.SaveFig(plt);
}
private void btnSubmitHilos_Click(object sender, EventArgs e)
{
txtResFact.Clear();
lblResponse.Text = "";
BigInteger numero = 0;
int iteraciones = 0;
try
{
numero = int.Parse(numeroFact.Text);
iteraciones = int.Parse(numItera.Text);
}
catch (Exception)
{
numero = 0;
iteraciones = 0;
}
if (numero > 0 && iteraciones > 0)
{
txtResFact.Visible = false;
Dictionary <double[], string> response = new Dictionary <double[], string>();
lblError.Visible = false;
string formated = string.Format("{0}", numero);
//OBTENER Numero Hilos, Tiempo en ms , y el string con info completa
response = Principal.ObtenerFactoriales(numero, iteraciones);
//PARA GRAFICA
var plt = new ScottPlot.Plot(600, 400);
double[] tiempos = new double[response.Count];
double[] hilos = new double[response.Count];
int i = 0;
foreach (double[] val in response.Keys)
{
hilos[i] = val[0];
tiempos[i] = val[1];
i++;
}
plt.PlotScatter(hilos, tiempos);
plt.Legend();
plt.Title("Hilos vs Tiempo de Obtener Factorial");
plt.YLabel("Tiempo(ms)");
plt.XLabel("Hilos");
string nombreImagen = string.Format("../../{0}_{1}_Grafica.png", numero, iteraciones);
try
{
plt.SaveFig(nombreImagen);
lblConfirmed.Text = "Se ha guardado la gráfica en png";
}
catch (Exception)
{
lblConfirmed.Text = "No se ha podido guardar la información";
}
lblConfirmed.Visible = true;
//IMPRIMIR EN FORMS
foreach (string val in response.Values)
{
lblResponse.Text += string.Format($"{val} \n");
Console.WriteLine(val);
}
}
else
{
lblError.Visible = true;
}
}
