private float Inheritance(double min, double max, double mode,
double noise, Random rand)
{
//Get noise around inheritance using triangular ditribution
double Max = Math.Min(mode + noise, max);
double Min = Math.Max(mode - noise, min);
BetaScaled Distribution = BetaScaled.PERT(Min, Max, mode, rand);
return((float)Distribution.Sample());
}
//Functions for birth
private float[] InitialDistributions(SimParams par, float noise, float initial, float max, float min)
{
float[] DistArray = new float[par.NumBirds];
if (noise != 0)
{
float Max = Math.Min(initial + noise, max);
float Min = Math.Max(initial - noise, min);
BetaScaled Dist = BetaScaled.PERT(Min, Max, initial, par.Rand);
for (int i = 0; i < par.NumBirds; i++)
{
DistArray[i] = (float)Dist.Sample();
}
}
else
{
DistArray = Enumerable.Repeat(initial, par.NumBirds).ToArray();
}
return(DistArray);
}
public void Initialize(Tuple <object, object, object> data)
{
export = data;
this.Distribution = BetaScaled.PERT((double)data.Item1, (double)data.Item2, (double)data.Item3);
}
public BetaPertDistribution(double min, double max, double mostLikely)
{
this.Distribution = BetaScaled.PERT(min, max, mostLikely);
export = new Tuple <object, object, object>(min, max, mostLikely);
}