public string generateNNGraph(string matrixRef, int NumberInputsNodes, int NumberHiddenNodes, int NumberOutputNodes,
int NumberOfEpochs, double LearningRate_eta, string title, int oneCol, string oneLab, int twoCol, string twoLab, string fileName)
{
var matrixComp = Value(matrixRef);
if (matrixComp.GetType() == typeof(string))
{
return("Could not find variable " + matrixRef);
}
MatrixData _graphData = (MatrixData)matrixComp;
double[] x = _graphData.GetColumnCopy <double>(0);
double[] y = _graphData.GetColumnCopy <double>(1);
double[] y1 = _graphData.GetColumnCopy <double>(2);
double xMax = _graphData.Max(0);
var plot = new PLStream();
plot.width(1);
plot.sdev("svg");
plot.sfnam(fileName + ".svg");
plot.scolbg(255, 255, 255);
plot.init();
plot.env(0, xMax, 0, 105, AxesScale.Independent, AxisBox.BoxTicksLabelsAxes);
Dictionary <int, string> cols = new Dictionary <int, string>();
cols.Add(0, "black");
cols.Add(1, "red");
cols.Add(2, "yellow");
cols.Add(3, "green");
cols.Add(4, "aquamarine");
cols.Add(5, "pink");
cols.Add(6, "wheat");
cols.Add(7, "grey");
cols.Add(8, "brown");
cols.Add(9, "blue");
cols.Add(10, "BlueViolet");
cols.Add(11, "cyan");
cols.Add(12, "turquoise");
cols.Add(13, "magenta");
cols.Add(14, "salmon");
cols.Add(15, "white");
plot.col0(1);
plot.lab("Epoch", "Accuracy %", title);
plot.ptex(xMax - 10, 25, 1.0, 0, 1, "Input Nodes: " + NumberInputsNodes);
plot.ptex(xMax - 10, 20, 1.0, 0, 1, "Hidden Nodes: " + NumberHiddenNodes);
plot.ptex(xMax - 10, 15, 1.0, 0, 1, "Output Nodes: " + NumberOutputNodes);
plot.ptex(xMax - 10, 10, 1.0, 0, 1, "Epochs: " + NumberOfEpochs);
plot.ptex(xMax - 10, 5, 1.0, 0, 1, "Learning Rate: " + LearningRate_eta);
plot.col0(1);
plot.col0(oneCol);
plot.line(x, y);
plot.ptex(xMax - 10, 35, 1.0, 0, 1, cols[oneCol] + ": " + oneLab);
plot.col0(oneCol);
plot.col0(twoCol);
plot.line(x, y1);
plot.ptex(xMax - 10, 30, 1.0, 0, 1, cols[twoCol] + ": " + twoLab);
plot.col0(twoCol);
plot.eop();
return(Directory.GetCurrentDirectory() + "\\" + fileName + ".svg");
}
public static void PlotRegressionChart(PlotChartGeneratorModel generationModel)
{
using (var pl = new PLStream())
{
pl.sdev("pngcairo");
pl.sfnam(generationModel.ImageName);
// use white background with black foreground
pl.spal0("cmap0_alternate.pal");
// Initialize plplot
pl.init();
// set axis limits
pl.env(generationModel.MinLimitX, generationModel.MaxLimitX, generationModel.MinLimitY, generationModel.MaxLimitY,
AxesScale.Independent, AxisBox.CustomXYBoxTicksLabels);
// Set scaling for mail title text 125% size of default
//pl.schr(0, 1.25);
// The main title
pl.lab(generationModel.LabelX, generationModel.LabelY, generationModel.Title);
// plot using different colors
// see http://plplot.sourceforge.net/examples.php?demo=02 for palette indices
pl.col0(1);
// This code is the symbol to paint
char code = (char)9;
double yTotal = 0;
double xTotal = 0;
double xyMultiTotal = 0;
double xSquareTotal = 0;
var totalNumber = 0;
generationModel.PointsList.ForEach(pointsList =>
{
double y0 = 0;
double x0 = 0;
totalNumber += pointsList.Points.Count();
// plot using other color
pl.col0(pointsList.Color);
pointsList.Points.ForEach(point =>
{
var x = new double[1];
var y = new double[1];
x[0] = point.X;
y[0] = point.Y;
if (pointsList.PaintDots)
{
// Paint a dot
pl.poin(x, y, code);
}
else
{
if (!generationModel.DrawRegressionLine)
{
// Draw lines between points
pl.join(x0, y0, point.X, point.Y);
x0 = point.X;
y0 = point.Y;
}
}
xTotal += point.X;
yTotal += point.Y;
xyMultiTotal += point.X * point.Y;
xSquareTotal += point.X * point.X;
});
});
// Regression Line calculation explanation:
// https://www.khanacademy.org/math/statistics-probability/describing-relationships-quantitative-data/more-on-regression/v/regression-line-example
if (generationModel.DrawRegressionLine)
{
if (generationModel.RegressionPointsList != null)
{
var xArray = generationModel.RegressionPointsList.Points.Select(dp => dp.X).ToArray();
var yArray = generationModel.RegressionPointsList.Points.Select(dp => dp.Y).ToArray();
pl.col0(generationModel.RegressionPointsList.Color);
pl.line(xArray, yArray);
}
else
{
double minY = yTotal / totalNumber;
double minX = xTotal / totalNumber;
double minXY = xyMultiTotal / totalNumber;
double minXsquare = xSquareTotal / totalNumber;
double m = ((minX * minY) - minXY) / ((minX * minX) - minXsquare);
double b = minY - (m * minX);
double x1 = generationModel.MinLimitX;
//Function for Y1 in the line
double y1 = (m * x1) + b;
double x2 = generationModel.MaxLimitX;
//Function for Y2 in the line
double y2 = (m * x2) + b;
var xArray = new double[2];
var yArray = new double[2];
xArray[0] = x1;
yArray[0] = y1;
xArray[1] = x2;
yArray[1] = y2;
pl.col0(4);
pl.line(xArray, yArray);
}
}
if (generationModel.DashedPoint != null)
{
pl.col0(CommonConstants.PPLplotColorGreen);
pl.width(2);
// Horizontal Line should go from (0,DashedPoint.Y) to (DashedPoint.X, DashedPoint.Y)
DrawDashedLined(pl, 0, generationModel.DashedPoint.Y, generationModel.DashedPoint.X, generationModel.DashedPoint.Y);
// Vertical Line should go from (DashedPoint.X,0) to (DashedPoint.X, DashedPoint.Y)
DrawDashedLined(pl, generationModel.DashedPoint.X, 0, generationModel.DashedPoint.X, generationModel.DashedPoint.Y);
}
// end page (writes output to disk)
pl.eop();
// output version of PLplot
pl.gver(out var verText);
} // the pl object is disposed here
// Open Chart File In Microsoft Photos App (Or default app, like browser for .svg)
Console.WriteLine("Showing chart...");
var p = new Process();
string chartFileNamePath = @".\" + generationModel.ImageName;
p.StartInfo = new ProcessStartInfo(chartFileNamePath)
{
UseShellExecute = true
};
p.Start();
}
private static void PlotTrades(string name, int totalBars, RangeBarModel[] prices, TradeModel[] orders, bool byTime,
PLStream pl)
{
var priceCount = prices.Length;
var priceX = new double[priceCount];
var priceY = new double[priceCount];
var priceTimestamp = new double[priceCount];
for (var j = 0; j < priceCount; j++)
{
var price = prices[j];
priceTimestamp[j] = price.Timestamp;
priceX[j] = byTime ? price.Timestamp : j;
priceY[j] = price.CurrentPrice;
}
var buys = orders
.Where(x => x.Amount > 0)
.OrderBy(x => x.Timestamp)
.ToArray();
var sells = orders
.Where(x => x.Amount < 0)
.OrderBy(x => x.Timestamp)
.ToArray();
var buysCount = buys.Length;
var buyX = new double[buysCount];
var buyY = new double[buysCount];
for (var j = 0; j < buysCount; j++)
{
var order = buys[j];
var priceIndex = Array.IndexOf(priceTimestamp, order.Timestamp);
buyX[j] = byTime ? order.Timestamp : priceIndex;
buyY[j] = Math.Abs(order.Price);
}
var sellsCount = sells.Length;
var sellX = new double[sellsCount];
var sellY = new double[sellsCount];
for (var j = 0; j < sellsCount; j++)
{
var order = sells[j];
var priceIndex = Array.IndexOf(priceTimestamp, order.Timestamp);
sellX[j] = byTime ? order.Timestamp : priceIndex;
sellY[j] = Math.Abs(order.Price);
}
// set axis limits
var xMin = byTime ? prices.First().Timestamp - 10000 : 0;
var xMax = byTime ? prices.Last().Timestamp + 10000 : prices.Length + 1;
var yMin = prices.Min(x => x.CurrentPrice);
var yMax = prices.Max(x => x.CurrentPrice);
yMin = yMin - (yMin * 0.001);
yMax = yMax + (yMax * 0.001);
pl.col0(8);
// Set scaling for mail title text 125% size of default
//pl.schr(0, 1.25);
pl.env(xMin, xMax, yMin, yMax, AxesScale.Independent, AxisBox.BoxTicksLabelsAxes);
// The main title
if (byTime)
{
pl.lab($"Timestamp (to {prices.LastOrDefault()?.TimestampDate:d})", "Price", name);
}
else
{
pl.lab($"Bars (first {prices.Length} of {totalBars})", "Price", name);
}
//pl.timefmt("%s");
// plot using different colors
// see http://plplot.sourceforge.net/examples.php?demo=02 for palette indices
pl.col0(3);
pl.width(0.4);
//pl.poin(buyX, buyY, (char)8);
for (int i = 0; i < buyX.Length; i++)
{
pl.line(new[]
{
buyX[i], buyX[i],
}, new[]
{
yMin, buyY[i]
});
}
pl.col0(14);
//pl.poin(sellX, sellY, (char)9);
for (int j = 0; j < sellX.Length; j++)
{
pl.line(new[]
{
sellX[j], sellX[j],
}, new[]
{
sellY[j], yMax,
});
}
pl.col0(7);
pl.width(1);
pl.line(priceX, priceY);
}
public string GenerateGraph()
{
double[] x = _graphData.GetColumnCopy <double>(0);
double[] y = _graphData.GetColumnCopy <double>(1);
double[] y1 = _graphData.GetColumnCopy <double>(2);
double xMax = _graphData.Max(0);
//double yMax = _graphData.Max(1);
//yMax = (_graphData.Max(2) > yMax)? _graphData.Max(2) : yMax;
//double yMin = _graphData.Min(1);
//yMin = (_graphData.Min(2) < yMin)? _graphData.Min(2): yMin;
var plot = new PLStream();
plot.width(1);
plot.sdev("svg");
plot.sfnam("Test.svg");
plot.scolbg(255, 255, 255);
plot.init();
plot.env(0, xMax, 0, 105, AxesScale.Independent, AxisBox.BoxTicksLabelsAxes);
//####### PLPlot colour guide:
//0 black (default background)
//1 red (default foreground)
//2 yellow
//3 green
//4 aquamarine
//5 pink
//6 wheat
//7 grey
//8 brown
//9 blue
//10 BlueViolet
//11 cyan
//12 turquoise
//13 magenta
//14 salmon
//15 white
plot.col0(1);
if (!(_testingData == null))
{
plot.lab("Epoch", "Accuracy %", "Test vs Train Accuracy");
}
else
{
plot.lab("Epoch", "Accuracy %", "Test vs Val Accuracy");
}
plot.ptex(xMax - 10, 25, 1.0, 0, 1, "Input Nodes: " + NumberInputsNodes);
plot.ptex(xMax - 10, 20, 1.0, 0, 1, "Hidden Nodes: " + NumberHiddenNodes);
plot.ptex(xMax - 10, 15, 1.0, 0, 1, "Output Nodes: " + NumberOutputNodes);
plot.ptex(xMax - 10, 10, 1.0, 0, 1, "Epochs: " + NumberOfEpochs);
plot.ptex(xMax - 10, 5, 1.0, 0, 1, "Learning Rate: " + LearningRate_eta);
plot.col0(1);
plot.col0(9);
plot.line(x, y);
plot.ptex(xMax - 10, 35, 1.0, 0, 1, "Blue: Train");
plot.col0(9);
plot.col0(3);
plot.line(x, y1);
if (!(_testingData == null))
{
plot.ptex(xMax - 10, 30, 1.0, 0, 1, "Green: Test");
}
else
{
plot.ptex(xMax - 10, 30, 1.0, 0, 1, "Green: Val");
}
plot.col0(3);
plot.eop();
return("Saved \"Test.svg\"");
}