private static List <double> ClassifyByJenksFisher(int numBreaks, List <ValueCountTuple> tuples)
{
var breaksArray = new List <double>(numBreaks);
if (numBreaks == 0)
{
return(breaksArray);
}
// Avoid array <-> list conversations
breaksArray.AddRange(Enumerable.Repeat(0.0d, numBreaks));
var classificator = new NaturalBreaks(tuples, numBreaks);
if (numBreaks > 1)
{
// Runs the actual calculation
classificator.CalculateAll();
var lastClassBreakIndex = classificator.FindMaxBreakIndex(classificator._bufferSize - 1, 0, classificator._bufferSize);
while (--numBreaks != 0)
{
// Assign the break values to the result
breaksArray[numBreaks] = tuples[lastClassBreakIndex + numBreaks].Value;
if (numBreaks > 1)
{
classificator._classBreaksIndex -= classificator._bufferSize;
lastClassBreakIndex = classificator._classBreaks[classificator._classBreaksIndex + lastClassBreakIndex];
}
}
}
breaksArray[0] = tuples[0].Value;
return(breaksArray);
}
private static double ApplyJenks(ref List <double> refList)
{
int[] groupCorrection = { 1, 1, 1, 2, 4, 7, 9, 10, 10, 10 };
// Check if the speed list is empty.
if (refList.Count == 0)
{
throw new InvalidOperationException("Empty list");
}
var corr = NaturalBreaks.CreateNaturalBreaksArray(refList, 10);
var groupList = new List <int>(refList.Count);
foreach (var cur in refList)
{
for (var j = 1; j < corr.Count + 1; j++)
{
if (j == corr.Count || cur < corr[j])
{
groupList.Add(j - 1);
break;
}
}
}
var jenksVar = refList.Select((t, i) => t * groupCorrection[groupList[i]]).Sum();
var GroupCount = 0;
for (var i = 0; i < 10; i++)
{
GroupCount += groupList.Count(x => x == i) * groupCorrection[i];
}
return(jenksVar / GroupCount);
}