private double[] GetDiscretizationSupport()
{
bool minInfinite = double.IsInfinity(BaseDistribution.Support.Min);
bool maxInfinite = double.IsInfinity(BaseDistribution.Support.Max);
double tolerance = CommonRandomMath.GetTolerance(InnerSamples);
double min = minInfinite ? GetSupport(true, tolerance) : BaseDistribution.Support.Min;
double max = maxInfinite ? GetSupport(false, tolerance) : BaseDistribution.Support.Max;
min = (min * Coefficient) + Offset;
max = (max * Coefficient) + Offset;
if (min > max)
{
double temp = min;
min = max;
max = temp;
}
return(new double[] { min, max });
}
private static PrivateCoordinates Resample(PrivateCoordinates coordinates)
{
var pdf = coordinates.PDFCoordinates;
int length = coordinates.XCoordinates.Length;
double min = coordinates.XCoordinates[0];
double max = coordinates.XCoordinates[length - 1];
double step = (max - min) / (length - 1);
AnalyzeInfinities(pdf, step);
Normalize(pdf, step);
double[] cdf = GetCDF(pdf, step);
double tolerance = CommonRandomMath.GetTolerance(length);
var minI = 0;
var maxI = length - 1;
for (int i = 0; i < length - 1; i++)
{
var c = cdf[i];
if (c < tolerance)
{
if (pdf[i] == 0)
{
minI = i + 1;
}
else
{
minI = i;
}
}
if (c > 1 - tolerance)
{
if (pdf[i] == 0)
{
maxI = i - 1;
}
else
{
maxI = i;
}
break;
}
}
min = coordinates.XCoordinates[minI];
max = coordinates.XCoordinates[maxI];
int r = maxI - minI + 1;
if (r != length)
{
double[] newX = CommonRandomMath.GenerateXAxis(min, max, length, out _);
double[] newY = new double[r];
for (int i = 0; i < r; i++)
{
newY[i] = coordinates.PDFCoordinates[i + minI];
}
newY = CommonRandomMath.Resample(newY, length);
return(new PrivateCoordinates {
XCoordinates = newX, PDFCoordinates = newY
});
}
else
{
return(coordinates);
}
}
