private void propagateSignal(Signal excitedNodes)
{
for (int i = 0; i < excitedNodes.Count(); i++) {
int nodeToExcite = (int)(excitedNodes[i] * propagationStrength[i] + excitedNodes.Count()) % excitationState.Count();
excitationState[nodeToExcite] *= excitedNodes[i] * propagationStrength[i];
}
}
/// <summary>Uses Scott's choice algorithm to assign bin width:
/// http://en.wikipedia.org/wiki/Histogram#Number_of_bins_and_width</summary>
public Histogram(Signal data)
{
this.data = data;
var bS = (3.5 * data.StandardDeviation()) / Math.Pow(data.Count(), .33333333333333);
if(bS <= 0)
bS = .01;
this.binSize = bS;
for (int i = 0; i < data.Count(); i++) {
IncrementAt((int)Math.Floor(data[i] / binSize));
}
}
public Histogram(Signal data, double binSize)
{
this.data = data;
this.binSize = binSize;
for (int i = 0; i < data.Count(); i++) {
IncrementAt((int)Math.Floor(data[i] / binSize));
}
}
public static Signal CityDevelopment(int startingCities, int iterations, double b = .1)
{
Signal cities = new Signal();
for (int i = 0; i < startingCities; i++) {
cities.Add(1);
}
for (int i = 0; i < iterations - startingCities; i++) {
if (rand.NextDouble() < b) {
cities.Add(1);
} else {
var randNum = (double)rand.Next(0, i+startingCities);
for (int j = 0; j < cities.Count(); j++) {
randNum -= cities[j];
if (randNum < 0) {
cities[j]++;
break;
}
}
}
}
return cities;
}