public Network()
{
for (int i = 0; i < NETWORK_DEPTH; i++){
_neurons[i] = new Neuron[NETWORK_BREADTH];
for (int j = 0; j < _neurons[i].Length; j++) {
_neurons[i][j] = new Neuron(j%2 == 0 , j==0);
}
}
}
public Network(Network n)
{
for (int i = 0; i < _neurons.Length; i++){
_neurons[i] = new Neuron[NETWORK_BREADTH];
for (int j = 0; j < _neurons[i].Length; j++){
_neurons[i][j] = new Neuron(n._neurons[i][j]);
}
}
}
public Neuron(Neuron n)
{
_sum = n._sum;
_first = n._first;
if (_first) _values = new float[Network.FIRST_BREADTH];
for (int i = 0; i < n._values.Length; i++){
_values[i] = n._values[i];
}
}
public static void Crossover(Neuron n1, Neuron n2)
{
if (n1._sum != n2._sum){
n1._sum = !n1._sum;
n2._sum = !n2._sum;
}
else if (n1._first){
int border = Program.RandomGenerator.Next(Network.NETWORK_BREADTH);
for (int i = 0; i < border; i++){
float tmp = n1._values[i];
n1._values[i] = n2._values[i];
n2._values[i] = tmp;
}
}
else
for (int i = 0; i < n1._values.Length; i++){
n1._values[i] = (n1._values[i] + n2._values[i])/2;
n2._values[i] = n1._values[i];
}
}