public static Plot CreateAdvancedStatisticsPlot()
{
var plt = new ScottPlot.Plot(600, 400);
// create some sample data to represent test scores
Random rand = new Random(0);
double[] scores = DataGen.RandomNormal(rand, 250, 85, 5);
// create a Population object from the data
var pop = new ScottPlot.Statistics.Population(scores);
// display the original values scattered vertically
double[] ys = DataGen.RandomNormal(rand, pop.values.Length, stdDev: .15);
plt.PlotScatter(pop.values, ys, markerSize: 10,
markerShape: MarkerShape.openCircle, lineWidth: 0);
// display the bell curve for this distribution
double[] curveXs = DataGen.Range(pop.minus3stDev, pop.plus3stDev, .1);
double[] curveYs = pop.GetDistribution(curveXs);
plt.PlotScatter(curveXs, curveYs, markerSize: 0, lineWidth: 2);
// improve the style of the plot
plt.Title($"Test Scores (mean: {pop.mean:0.00} +/- {pop.stDev:0.00}, n={pop.n})");
plt.XLabel("Score");
plt.Grid(lineStyle: LineStyle.Dot);
return(plt);
//plt.SaveFig("Advanced_Statistics_Population.png");
}
public void Test_Population_CurveSideways()
{
Random rand = new Random(0);
var ages = new ScottPlot.Statistics.Population(rand, 44, 78, 2);
double[] curveXs = DataGen.Range(ages.minus3stDev, ages.plus3stDev, .1);
double[] curveYs = ages.GetDistribution(curveXs);
var plt = new ScottPlot.Plot(400, 300);
plt.PlotScatter(DataGen.Random(rand, ages.values.Length), ages.values,
markerSize: 10, markerShape: MarkerShape.openCircle, lineWidth: 0);
plt.PlotScatter(curveYs, curveXs, markerSize: 0);
plt.Grid(lineStyle: LineStyle.Dot);
TestTools.SaveFig(plt);
}
public void Render(Plot plt)
{
// create some sample data to represent test scores
Random rand = new Random(0);
double[] scores = DataGen.RandomNormal(rand, 35, 85, 5);
// create a Population object and plot it
var pop = new ScottPlot.Statistics.Population(scores);
plt.PlotPopulations(pop, "scores");
// improve the style of the plot
plt.Title($"Test Scores (mean: {pop.mean:0.00} +/- {pop.stDev:0.00}, n={pop.n})");
plt.YLabel("Score");
plt.Ticks(displayTicksX: false);
plt.Legend();
plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
}
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($"{plotName}.png");
}
public void GenerateSingleBoxAndWhiskers(List <ResultModel> results, string plotName = "results")
{
var plt = new Plot(600, 400);
var ys = new double[results.Count];
var i = 0;
foreach (var r in results)
{
ys[i] = r.Fitness;
i++;
}
plt.Title("Solution energy");
plt.YLabel("Solution energy");
var pop = new ScottPlot.Statistics.Population(ys);
plt.PlotPopulations(pop, "scores");
plt.SaveFig($"{plotName}.png");
}
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 PlotParameters AddSeriesFromString(string dataString, DrawSettings drawSettings, Dictionary <string, object> metadata)
{
object data = new object();
string[] raw = dataString.Split(new char[] { ',', '\n' });
if (!drawSettings.dateXAxis)
{
List <double> serialData = raw.Where(m => double.TryParse(m, out _)).Select(m => double.Parse(m)).ToList();
if (drawSettings.type == PlotType.scatter || drawSettings.type == PlotType.bar)
{
double[] xs = new double[serialData.Count / 2];
double[] ys = new double[serialData.Count / 2];
for (int i = 0; i < serialData.Count; i++)
{
int row = i / 2;
int col = i % 2;
if (col == 0)
{
xs[row] = serialData[i];
}
else
{
ys[row] = serialData[i];
}
data = new double[][] { xs, ys };
}
}
else if (drawSettings.type == PlotType.signal || drawSettings.type == PlotType.histogram)
{
data = serialData.ToArray();
}
else if (drawSettings.type == PlotType.box_whisker)
{
ScottPlot.Statistics.Population dataPopulation = new ScottPlot.Statistics.Population(serialData.ToArray());
data = dataPopulation;
}
if (drawSettings.type == PlotType.scatter && drawSettings.polarCoordinates)
{
(((double[][])data)[0], ((double[][])data)[1]) = ScottPlot.Tools.ConvertPolarCoordinates(((double[][])data)[0], ((double[][])data)[1]);
}
}
else
{
if (drawSettings.type == PlotType.scatter || drawSettings.type == PlotType.bar)
{
List <DateTime> dataX = new List <DateTime>();
List <double> dataY = new List <double>();
int successfullyParsed = 0;
for (int i = 0; i < raw.Length; i++)
{
if (successfullyParsed % 2 == 0)
{
DateTime temp;
if (DateTime.TryParse(raw[i], out temp))
{
dataX.Add(temp);
successfullyParsed++;
}
}
else
{
double temp;
if (double.TryParse(raw[i], out temp))
{
dataY.Add(temp);
successfullyParsed++;
}
}
}
long totalDistanceTicks = 0;
for (int i = 0; i < dataX.Count; i++)
{
if (i == dataX.Count - 1)
{
break;
}
totalDistanceTicks += Math.Abs(dataX[i].Ticks - dataX[i + 1].Ticks);
}
long averageTickDistance = totalDistanceTicks / (dataX.Count - dataX.Count % 2); //The fact that this is rounded doesn't matter, bc ticks are so obsenely small
long averageSecondsDistance = averageTickDistance / 10_000_000;
metadata["numTimeUnits"] = 1;
if (averageSecondsDistance > 0.75 * 86400 * 365)
{
metadata["timeUnit"] = ScottPlot.Config.DateTimeUnit.Year;
}
else if (averageSecondsDistance > 0.75 * 86400 * 30)
{
metadata["timeUnit"] = ScottPlot.Config.DateTimeUnit.Month;
}
else if (averageSecondsDistance > 0.75 * 86400)
{
metadata["timeUnit"] = ScottPlot.Config.DateTimeUnit.Day;
}
else if (averageSecondsDistance > 0.75 * 3600)
{
metadata["timeUnit"] = ScottPlot.Config.DateTimeUnit.Hour;
}
else if (averageSecondsDistance > 0.75 * 60)
{
metadata["timeUnit"] = ScottPlot.Config.DateTimeUnit.Minute;
}
else
{
metadata["timeUnit"] = ScottPlot.Config.DateTimeUnit.Second;
}
metadata["startDate"] = dataX[0];
metadata["numTimeUnits"] = (dataX.Count / 30) + 1;
double[] dataXDouble = dataX.Select((dt, i) => dt.ToOADate()).ToArray();
data = new double[][] { dataXDouble, dataY.ToArray() };
}
}
PlotParameters plotParams = new PlotParameters {
data = data, drawSettings = drawSettings, metaData = metadata
};
series.Add(plotParams);
((MainWindow)this.MainWindow).RenderPlot();
return(plotParams);
}
private void formsPlot1_Load(object sender, EventArgs e)
{
// this is the plotting place - all in the Load
// string tname1 = "WXROVER";
// string tname2 = "WXIN";
// int pointcount = 5000;
// double[,] tempData;
int cnt = 0;
// double[] t1 = new double[Globals.pointcount];
// double[] t2 = new double[Globals.pointcount];
// a couple of local lists
List <double> orgs = new List <double> {
};
List <double> chks = new List <double> {
};
classWXstnChk WXchk = new classWXstnChk(); //make an object WXck
WXchk.cnxstring("192.168.1.15", "DAWES_SQL2008", "WeatherStation", "WeatherStation", "Esp32a.b."); //a constructor - no arguments
//go get the data
Globals.tempData = WXchk.getTemperatureData(Globals.pointcount, Globals.tname1, Globals.tname2); //this gets the data as an XY pair
//there will be a lot of duplcates in this array. Lets remove the dupes - done in the SQL
//for scotterplot to work, these need to be in two separate Arrays, so we seperate them out in
//this loop and we might as well get rid of the empty slots
//maybe this would also work
// double [] tab1 = new double[tempData.Length];
for (int i = 0; i < pointcount - 1; i++)
{
if (Globals.tempData[i, 0] > 0)
{
t1[i] = tempData[i, 0];
t2[i] = tempData[i, 1];
t1qq[i] = tempData[i, 0];
t2qq[i] = tempData[i, 1];
//might as well put the data in the grid
dgXY.Rows.Add();
try
{
dgXY.Rows[i].Cells["dgXYrecord"].Value = i.ToString(); //puts the record no on the dgXY
dgXY.Rows[i].Cells["dgXYx"].Value = t1[i];
dgXY.Rows[i].Cells["dgXYy"].Value = t2[i];
}
catch { }
cnt += 1;
}
}//end of for loop
// we have two arrays lets sort them to form a QQ plot
Array.Sort(t1qq);
Array.Sort(t2qq);
// the arrays are declared a certain size and are now full of 0's
//this will reduce them down to just data.
// if there is no data in the arrays then cnt will = 0
if (cnt == 0)
{
MessageBox.Show("No Data in your selection.", "No data", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
return;
}
Array.Resize(ref t1, cnt);
Array.Resize(ref t2, cnt);
cntG = cnt;
// int aa = cnt;
int ab = t2.GetLength(0);
// create a Population object from the data
var popt1 = new ScottPlot.Statistics.Population(t1);
var popt2 = new ScottPlot.Statistics.Population(t2);
// now lets fill the stats box
lblT1.Text = tname1;
lblT2.Text = tname2;
lblMeanT1.Text = Math.Round(popt1.mean, 2).ToString();
lblMeanT2.Text = Math.Round(popt2.mean, 2).ToString();
lblMedT1.Text = Math.Round(popt1.median, 2).ToString();
lblMedT2.Text = Math.Round(popt2.median, 2).ToString();
lblQ3T1.Text = popt1.Q3.ToString();
lblq3table2.Text = popt1.Q3.ToString();
lblQ1t1.Text = popt1.Q1.ToString();
lblQ1T2.Text = popt2.Q1.ToString();
lblstderrT1.Text = Math.Round(popt1.stdErr, 2).ToString();
lblstderrT2.Text = Math.Round(popt2.stdErr, 2).ToString();
lblstdevT1.Text = Math.Round(popt1.stDev, 2).ToString();
lblstdevT2.Text = Math.Round(popt2.stDev, 2).ToString();
lblIQRt1.Text = Math.Round(popt1.IQR, 2).ToString();
lblIQRt2.Text = Math.Round(popt2.IQR, 2).ToString();
lblNtn1.Text = cnt.ToString(); //opt1.aa.ToString();
// lblNtn2.Text = ab.ToString(); // popt2.count.ToString();
//this gives us the regression line and the correlation coeficient
var model = new ScottPlot.Statistics.LinearRegressionLine(t1, t2);
string line = $"Y={model.slope:0.0000}X + {model.offset:0.0}";
lblLine.Text = line;
lblCorrel.Text = $"R² = {model.rSquared:0.0000}";
formsPlot1.plt.Title($"ScarpWeather Temperature XY Plot");
formsPlot1.plt.XLabel(tname1);
formsPlot1.plt.YLabel(tname2);
//formsPlot1.plt.AxisAuto(horizontalMargin: 0, verticalMargin: 0.5);
// xmin,xmax,ymin,ymax
int axisMin, axisMax;
axisMin = (int)popt1.min - 2; //get some data from the arrays
//axisMin = 0;
axisMax = (int)popt1.max + 2;
formsPlot1.plt.Axis(axisMin, axisMax, axisMin, axisMax); //defines the min and max of the chart
// formsPlot1.plt.Axis(15,40,15,40);
formsPlot1.plt.Legend(); // got ot have this be we toggle it with hte context menu
//this draws the scatter plot
XYplotPoints = formsPlot1.plt.PlotScatter(t1, t2, Color.DarkCyan, lineWidth: 0, markerSize: 5, label: "XYData");
//draw the QQ plot
QQplotPoints = formsPlot1.plt.PlotScatter(t1qq, t2qq, Color.DarkGreen, lineWidth: 0, markerSize: 5, label: "QQData");
QQplotPoints.visible = false;
// draws the regresion line
//if (plotRegression)
regLine = formsPlot1.plt.PlotLine(model.slope, model.offset, (axisMin, axisMax), lineWidth: 2, label: "Regression", color: Color.BlueViolet);
//plot a 45 degree line = X=Y
XequalsYLine = formsPlot1.plt.PlotLine(1.0, 0.0, (0, 100), Color.Goldenrod, lineWidth: 2, label: "X=Y", lineStyle: ScottPlot.LineStyle.Dot); //uses the equation of the line to plot
//the 10% error lines
errorLineA = formsPlot1.plt.PlotLine(0, 0, 100.0 - 0.1 * 100, 100, color: Color.OrangeRed, lineWidth: 2, label: "10%error", lineStyle: ScottPlot.LineStyle.Dash);
errorLineB = formsPlot1.plt.PlotLine(0, 0, 100, 100.0 - 0.1 * 100, color: Color.OrangeRed, lineWidth: 2, lineStyle: ScottPlot.LineStyle.Dash);
formsPlot1.Render();//draw the chart on the PC screen
}//end function
