private bool CalcQ()
{
BestA = 0.0;
BestB = 0.0;
BestC = 0.0;
var f = new DoubleParameterizedDelegate(AnalysisFunctions.ThreeParameterExponential);
var fitter = new OneVariableFunctionFitter <TrustRegionMinimizer>(f);
var lvect = new DoubleVector();
var kvect = new DoubleVector();
foreach (var pt in SpmVals)
{
lvect.Append(pt.X);
kvect.Append(pt.Y);
}
var start = new DoubleVector(0.1, 0.1, 0.1);
DoubleVector solution = fitter.Fit(lvect, kvect, start);
BestA = solution[0];
BestB = solution[1];
BestC = solution[2];
q = BestA;
return(true);
}
private DoubleVector FitData(double[] xDataRaw, double[] yDataRaw)
{
DoubleParameterizedFunction func = new Function();
var f = new DoubleParameterizedDelegate(
func.Evaluate);
var fitter =
new OneVariableFunctionFitter <TrustRegionMinimizer>(f);
DoubleVector x = new DoubleVector(xDataRaw);
DoubleVector y = new DoubleVector(yDataRaw);
DoubleVector init = new DoubleVector((yDataRaw.Min()).ToString() + " " + 0.5 + " " + ((yDataRaw.Max() - yDataRaw.Min())).ToString());
DoubleVector solution = fitter.Fit(x, y, init);
double[] yData = new double[xDataRaw.Length * 600];
double[] xData = new double[xDataRaw.Length * 600];
for (int g = 0; g < yData.Length; g++)
{
double rads = ((xDataCourse[0] + g)) * 2 * Math.PI / 180;
yData[g] = MyFunction(solution, (rads));
xData[g] = xDataCourse[0] + g;
Console.Writeline("x: " + xData[g] + " y: " + yData[g]);
}
return(solution);
}
