public void getTransition(CAState a, CAState b, int n)
{
CAState temp = new CAState(a);
for (int i = 0; i < n; ++i)
{
getTransition(temp, b);
temp.copyFrom(b);
}
}
public float getHeat(CAState a, int p)
{
CAState b = new CAState(a);
CAState c = new CAState(a);
float r = 0.0f;
for (int i = 0; i < p; ++i)
{
getTransition(b, c);
r += b.getDifference(c);
b.copyFrom(c);
}
return(r / p);
}
public int getPeriod(CAState a)
{
CAState b = new CAState(a);
CAState c = new CAState(a);
for (int i = 0; i < 1000; ++i)
{
getTransition(b, c);
b.copyFrom(c);
if (b.getRelativeDifference(a) == 0)
{
return(i + 1);
}
}
return(0);
}
//private void evaluateFitness(CAState state)
//{
// CAState temp0 = new CAState();
// CAState temp1 = new CAState();
// temp0.copyFrom(state);
// for (int k=0; k<period; ++k)
// {
// rule_set.getTransition(temp0, temp1);
// temp0.copyFrom(temp1);
// }
// float oscillatorness = 1.0f - temp0.getDifference(state);
// //float density = (float)(population[j].numberOfLiveCells()) / (CAState.Width * CAState.Height);
// int nas = state.numberOfLiveCells();
// int min_nas = 20;
// float density = (nas > min_nas) ? 1.0f : nas / min_nas;
// float t = 0.75f;
// state.fitness = t * oscillatorness + (1.0f - t) * density;
//}
// no state should look more like the first than the end state
private void evaluateFitness(CAState state)
{
float oscillatorness = 0.0f;
CAState temp0 = new CAState(state);
CAState temp1 = new CAState(state);
float[] f = new float[period];
for (int k = 0; k < period; ++k)
{
rule_set.getTransition(temp0, temp1);
temp0.copyFrom(temp1);
f[k] = fitness_weights[k] * (1.0f - temp0.getRelativeDifference(state));
oscillatorness += f[k];
}
float final_difference = temp0.getRelativeDifference(state);
if (final_difference == 0)
{
state.fitness = 1.0f;
return;
}
//oscillatorness = 1.0f - final_difference;
//float oscillatorness = Math.Max(0, 1.0f - final_difference - 20*(final_difference - min_difference));
//if (final_difference == min_difference)
//{
// oscillatorness = 1.0f - final_difference + (final_difference - min_difference);
//}
//else
//{
// oscillatorness = Math.Max(1.0f - 10.0f*min_difference, 0);
//}
//float density = (float)(population[j].numberOfLiveCells()) / (CAState.Width * CAState.Height);
int nas = state.numberOfLiveCells();
int min_nas = 20;
float density = (nas > min_nas) ? 1.0f : nas / min_nas;
float t = 0.8f;
state.fitness = t * oscillatorness + (1.0f - t) * density;
}
public static void printOscillator(CAState c, CARuleSet rule_set)
{
CAState temp0 = new CAState(c);
CAState temp1 = new CAState(c);
while (true)
{
Console.WriteLine(temp0.ToString());
Console.WriteLine();
rule_set.getTransition(temp0, temp1);
if (temp1.getRelativeDifference(c) == 0)
{
break;
}
temp0.copyFrom(temp1);
}
}
public static void saveImages(CAState c, CARuleSet rule_set, String path)
{
CAState temp0 = new CAState(c);
CAState temp1 = new CAState(c);
int i = 0;
while (true)
{
Bitmap image = temp0.toImage(c.Width * 100, c.Height * 100);
image.Save(path + "/" + i + ".bmp");
rule_set.getTransition(temp0, temp1);
if (temp1.getRelativeDifference(c) == 0)
{
break;
}
temp0.copyFrom(temp1);
++i;
}
}