private Point2DDouble[] CalcDistributionDataPoints(double[] valArr)
{
// Square root is a fairly good choice for automatically determining the category count based on number of values being analysed.
// See http://en.wikipedia.org/wiki/Histogram (section: Number of bins and width).
int categoryCount = (int)Math.Sqrt(valArr.Length);
FrequencyDistributionData fdd = Utilities.CalculateDistribution(valArr, categoryCount);
// Create array of distribution plot points.
Point2DDouble[] pointArr = new Point2DDouble[fdd.FrequencyArray.Length];
double incr = fdd.Increment;
double x = fdd.Min + (incr/2.0);
for(int i=0; i<fdd.FrequencyArray.Length; i++, x+=incr)
{
pointArr[i].X = x;
pointArr[i].Y = fdd.FrequencyArray[i];
}
return pointArr;
}
/// <summary>
/// Updates an Point2DDouble array by sorting an array of values and copying the sorted values over the existing values in pointArr.
/// Optionally creates the Point2DDouble array if it is null or is the wrong size.
/// </summary>
private void UpdateRankedDataPoints(double[] valArr, ref Point2DDouble[] pointArr)
{
// Sort values (largest first).
Array.Sort(valArr, delegate(double x, double y)
{
if(x > y) {
return -1;
}
if(x < y) {
return 1;
}
return 0;
});
// Ensure point cache is ready.
if(null == pointArr || pointArr.Length != valArr.Length)
{
pointArr = new Point2DDouble[valArr.Length];
for(int i=0; i<valArr.Length; i++)
{
pointArr[i].X = i;
pointArr[i].Y = valArr[i];
}
}
else
{ // Copy sorted values into _specieSizePointArray.
for(int i=0; i<valArr.Length; i++) {
pointArr[i].Y = valArr[i];
}
}
}