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);
}
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");
}
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");
}
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 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_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);
}
