public void Reproduction()
{
Pair <int, double, double[]>[] tempPool;
tempPool = new Pair <int, double, double[]> [popSize];
for (int i = 0; i < popSize; i++)
{
int[] selectedList = DifferentialSelection(i);
var newSolution = DifferentialCrossover(selectedList, i);
FitnessCal(newSolution);
tempPool[i] = newSolution.Item1 > pool[i].Item1 ? newSolution : Copy.DeepCopy(pool[i]);
tempPool[i].Item0 = i;
}
Array.Clear(pool, 0, pool.Length);
pool = tempPool;
}
public double ProbabilityFinder(double[] probabilityArray, int index, double entropy)
{
//Stop when 1. no remain prob. return 1;
//2. number of labels reached the max return 1;
//3. if it can't find the valid prob,ie. in the below range and timeout
// return -1
// The generated probability should make entropy - newEntropy > 0
// Should no smaller than maximum of the sum of the rest infromation
// After successfully generate a prob., call itself and pass in next index
int numOfLabels = probabilityArray.Length;
while (true)
{
if (index == numOfLabels - 1)
{
double probLeft = 1 - probabilityArray.Sum();
probabilityArray[index] += probLeft;
return(1.0);
}
double sum = probabilityArray.Sum();
if (Math.Round(sum, 4) == 1)
{
return(1.0);
}
int retryTimes = 2000;
bool success = false;
double rnd = -1;
while (retryTimes > 0)
{
retryTimes -= 1;
rnd = GlobalVar.rnd.NextDouble() * (1 - sum);
double[] tmpProbList = Copy.DeepCopy(
probabilityArray);
tmpProbList[index] += rnd;
double testEntropy = EntropyCalculation(tmpProbList);
double remainProb = 1 - sum - rnd;
double[] arrayOfProbabilities = Enumerable.Repeat(
remainProb / (numOfLabels - index - 1), numOfLabels - index - 1).ToArray();
var tmpProbList2 = tmpProbList.Select((x, i) =>
{
if (i > index)
{
return(x + arrayOfProbabilities[i - index - 1]);
}
return(x);
}).ToArray();
double maxEntTest = EntropyCalculation(tmpProbList2);
if (entropy > testEntropy && maxEntTest > entropy)
{
probabilityArray[index] += rnd;
success = true;
break;
}
}
double ret = -2;
if (success == true)
{
Console.WriteLine(index);
ret = ProbabilityFinder(probabilityArray, index + 1, entropy);
if (ret == 1.0)
{
return(1.0);
}
else
{
probabilityArray[index] -= rnd;
}
}
else
{
return(-1);
}
}
}