public void Render(Plot plt)
{
// create some sample data to represent test scores
Random rand = new Random(0);
double[] scoresA = DataGen.RandomNormal(rand, 35, 85, 5);
double[] scoresB = DataGen.RandomNormal(rand, 42, 87, 3);
double[] scoresC = DataGen.RandomNormal(rand, 23, 92, 3);
// create a unique PopulationSeries for each set of scores
var seriesA = new Statistics.PopulationSeries(new Statistics.Population[] { new Statistics.Population(scoresA) }, "Class A");
var seriesB = new Statistics.PopulationSeries(new Statistics.Population[] { new Statistics.Population(scoresB) }, "Class B");
var seriesC = new Statistics.PopulationSeries(new Statistics.Population[] { new Statistics.Population(scoresC) }, "Class C");
// create a MultiSeries from all the individual series
var multiSeries = new Statistics.PopulationMultiSeries(new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC });
plt.PlotPopulations(multiSeries);
// improve the style of the plot
plt.Title($"Test Scores by Class");
plt.YLabel("Score");
plt.Ticks(displayTicksX: false);
plt.Legend();
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
}
public void ExecuteRecipe(Plot plt)
{
// create sample data to represent test scores
Random rand = new Random(0);
double[] scoresA = DataGen.RandomNormal(rand, 35, 72, 7);
double[] scoresB = DataGen.RandomNormal(rand, 42, 57, 10);
double[] scoresC = DataGen.RandomNormal(rand, 23, 79, 5);
// To create a population series we need to start with an array of populations.
// In this example each population series just has one population in it.
var popsA = new Statistics.Population[] { new Statistics.Population(scoresA) };
var popsB = new Statistics.Population[] { new Statistics.Population(scoresB) };
var popsC = new Statistics.Population[] { new Statistics.Population(scoresC) };
// create a PopulationSeries for each set of scores, naming it in the process
var seriesA = new Statistics.PopulationSeries(popsA, "Class A");
var seriesB = new Statistics.PopulationSeries(popsB, "Class B");
var seriesC = new Statistics.PopulationSeries(popsC, "Class C");
var seriesArray = new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC };
// create a MultiSeries object by passing in the array of series objects and plot it
var multiSeries = new Statistics.PopulationMultiSeries(seriesArray);
var popPlot = plt.AddPopulations(multiSeries);
// now customize its public fields to extensively customize its display options
popPlot.DistributionCurve = true;
popPlot.DistributionCurveLineStyle = LineStyle.Dash;
popPlot.ScatterOutlineColor = System.Drawing.Color.Transparent;
popPlot.DataFormat = ScottPlot.Plottable.PopulationPlot.DisplayItems.ScatterAndBox;
popPlot.DataBoxStyle = ScottPlot.Plottable.PopulationPlot.BoxStyle.BarMeanStDev;
// colors are managed at the population series level:
foreach (var popSeries in popPlot.MultiSeries.multiSeries)
{
popSeries.color = Tools.GetRandomColor(rand);
}
// improve the style of the plot
plt.Legend(location: Alignment.LowerLeft);
plt.XAxis.Ticks(false);
plt.XAxis.Grid(false);
plt.YAxis.MajorGrid(lineStyle: LineStyle.Dot);
plt.SetAxisLimits(yMin: 0);
}
public void Render(Plot plt)
{
// create some sample data to represent test scores
Random rand = new Random(0);
double[] scoresA = DataGen.RandomNormal(rand, 35, 72, 7);
double[] scoresB = DataGen.RandomNormal(rand, 42, 57, 10);
double[] scoresC = DataGen.RandomNormal(rand, 23, 79, 5);
// create a unique PopulationSeries for each set of scores
var seriesA = new Statistics.PopulationSeries(new Statistics.Population[] { new Statistics.Population(scoresA) }, "Class A");
var seriesB = new Statistics.PopulationSeries(new Statistics.Population[] { new Statistics.Population(scoresB) }, "Class B");
var seriesC = new Statistics.PopulationSeries(new Statistics.Population[] { new Statistics.Population(scoresC) }, "Class C");
// create a MultiSeries from all the individual series
var multiSeries = new Statistics.PopulationMultiSeries(new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC });
// save the plottable and modify its properties to customize display style
var popPlot = plt.PlotPopulations(multiSeries);
popPlot.displayDistributionCurve = true;
popPlot.distributionCurveLineStyle = LineStyle.Dash;
popPlot.scatterOutlineColor = System.Drawing.Color.Transparent;
popPlot.displayItems = Plottable.PopulationPlot.DisplayItems.ScatterAndBox;
popPlot.boxStyle = Plottable.PopulationPlot.BoxStyle.BarMeanStDev;
plt.SetAxisLimits(yMin: 0);
// colors are managed at the population series level:
foreach (var popSeries in popPlot.popMultiSeries.multiSeries)
{
popSeries.color = Tools.GetRandomColor(rand);
}
// improve the style of the plot
plt.Title($"Test Scores by Class");
plt.YLabel("Score");
plt.Legend(location: Alignment.LowerLeft);
plt.Ticks(displayTicksX: false);
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
}
public void Render(Plot plt)
{
// create some sample data to represent test scores.
Random rand = new Random(0);
// Each class (A, B, C) is a series.
// Each semester (fall, spring, summer A, summer B) is a group.
double[] scoresAfall = DataGen.RandomNormal(rand, 35, 85, 5);
double[] scoresBfall = DataGen.RandomNormal(rand, 42, 87, 5);
double[] scoresCfall = DataGen.RandomNormal(rand, 23, 82, 5);
double[] scoresAspring = DataGen.RandomNormal(rand, 35, 84, 3);
double[] scoresBspring = DataGen.RandomNormal(rand, 42, 88, 3);
double[] scoresCspring = DataGen.RandomNormal(rand, 23, 84, 3);
double[] scoresAsumA = DataGen.RandomNormal(rand, 35, 80, 5);
double[] scoresBsumA = DataGen.RandomNormal(rand, 42, 90, 5);
double[] scoresCsumA = DataGen.RandomNormal(rand, 23, 85, 5);
double[] scoresAsumB = DataGen.RandomNormal(rand, 35, 91, 2);
double[] scoresBsumB = DataGen.RandomNormal(rand, 42, 93, 2);
double[] scoresCsumB = DataGen.RandomNormal(rand, 23, 90, 2);
// Collect multiple populations into a PopulationSeries.
// All populations in a series will be styled the same and appear once in the legend.
var popsA = new Statistics.Population[] {
new Statistics.Population(scoresAfall),
new Statistics.Population(scoresAspring),
new Statistics.Population(scoresAsumA),
new Statistics.Population(scoresAsumB)
};
var popsB = new Statistics.Population[] {
new Statistics.Population(scoresBfall),
new Statistics.Population(scoresBspring),
new Statistics.Population(scoresBsumA),
new Statistics.Population(scoresBsumB)
};
var popsC = new Statistics.Population[] {
new Statistics.Population(scoresCfall),
new Statistics.Population(scoresCspring),
new Statistics.Population(scoresCsumA),
new Statistics.Population(scoresCsumB)
};
var seriesA = new Statistics.PopulationSeries(popsA, "Class A");
var seriesB = new Statistics.PopulationSeries(popsB, "Class B");
var seriesC = new Statistics.PopulationSeries(popsC, "Class C");
var allSeries = new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC };
// create a MultiSeries from multiple population series and plot it
var multiSeries = new Statistics.PopulationMultiSeries(allSeries);
plt.PlotPopulations(multiSeries);
// improve the style of the plot
plt.Title($"Test Scores by Class");
plt.YLabel("Score");
plt.XTicks(new string[] { "Fall", "Spring", "Summer A", "Summer B" });
plt.Legend();
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
}
public void ExecuteRecipe(Plot plt)
{
// Each class (A, B, C) is a series.
// Each semester (fall, spring, summer A, summer B) is a group.
// create sample data to represent test scores for each class in each semester
Random rand = new Random(0);
double[] scoresAfall = DataGen.RandomNormal(rand, 35, 85, 5);
double[] scoresBfall = DataGen.RandomNormal(rand, 42, 87, 5);
double[] scoresCfall = DataGen.RandomNormal(rand, 23, 82, 5);
double[] scoresAspring = DataGen.RandomNormal(rand, 35, 84, 3);
double[] scoresBspring = DataGen.RandomNormal(rand, 42, 88, 3);
double[] scoresCspring = DataGen.RandomNormal(rand, 23, 84, 3);
double[] scoresAsumA = DataGen.RandomNormal(rand, 35, 80, 5);
double[] scoresBsumA = DataGen.RandomNormal(rand, 42, 90, 5);
double[] scoresCsumA = DataGen.RandomNormal(rand, 23, 85, 5);
double[] scoresAsumB = DataGen.RandomNormal(rand, 35, 91, 2);
double[] scoresBsumB = DataGen.RandomNormal(rand, 42, 93, 2);
double[] scoresCsumB = DataGen.RandomNormal(rand, 23, 90, 2);
// Collect multiple populations into a PopulationSeries.
// All populations in a series will be styled the same and appear once in the legend.
var popsA = new Statistics.Population[] {
new Statistics.Population(scoresAfall),
new Statistics.Population(scoresAspring),
new Statistics.Population(scoresAsumA),
new Statistics.Population(scoresAsumB)
};
var popsB = new Statistics.Population[] {
new Statistics.Population(scoresBfall),
new Statistics.Population(scoresBspring),
new Statistics.Population(scoresBsumA),
new Statistics.Population(scoresBsumB)
};
var popsC = new Statistics.Population[] {
new Statistics.Population(scoresCfall),
new Statistics.Population(scoresCspring),
new Statistics.Population(scoresCsumA),
new Statistics.Population(scoresCsumB)
};
// create a population series for each array of populations and give it a label
var seriesA = new Statistics.PopulationSeries(popsA, "Class A");
var seriesB = new Statistics.PopulationSeries(popsB, "Class B");
var seriesC = new Statistics.PopulationSeries(popsC, "Class C");
var allSeries = new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC };
// create a MultiSeries from multiple population series and plot it
var multiSeries = new Statistics.PopulationMultiSeries(allSeries);
plt.AddPopulations(multiSeries);
// improve the style of the plot
string[] groupNames = new string[] { "Fall", "Spring", "Summer A", "Summer B" };
plt.XTicks(groupNames);
plt.XAxis.Grid(false);
plt.Legend();
}
