static void Main(string[] args)
{
Console.Title = "Neural Network Testing";
// Testing Neural Network giving it 3 input values for 100 times (testing with 520 neurons)
Random random = new Random();
for (int i = 0; i < 100; i++)
{
NeuroNetwork net = new NeuroNetwork(3, new int[] { 100, 200, 200, 20 }, 1, random);
double[] result = net.elaborate(new double[] { 0, .5, 0 });
foreach (double r in result)
{
if (r < .3)
{
Console.ForegroundColor = ConsoleColor.Red;
}
else if (r > .7)
{
Console.ForegroundColor = ConsoleColor.Green;
}
else
{
Console.ForegroundColor = ConsoleColor.White;
}
Console.WriteLine(r);
}
System.Threading.Thread.Sleep(10);
}
Console.ForegroundColor = ConsoleColor.White;
Console.Write("\nPress a key to exit...");
Console.ReadLine();
}
private void GenerateWeights(int weights)
{
for (int i = 0; i < weights; i++)
{
Weights[i] = NeuroNetwork.GetRandomWeight();
}
}
public void NtwrkSolve()
{
StringBuilder sb = new StringBuilder();
NeuroNetwork n = new NeuroNetwork();
Dictionary <int, NeuroSignal> input = new Dictionary <int, NeuroSignal>();
Dictionary <int, NeuroSignal> output = new Dictionary <int, NeuroSignal>();
input.Add(0, new NeuroSignal(0, 0.9)); output.Add(0, new NeuroSignal(0));
input.Add(1, new NeuroSignal(1, 0.1)); output.Add(1, new NeuroSignal(1));
input.Add(2, new NeuroSignal(2, 0.8)); output.Add(2, new NeuroSignal(2));
#region -> Log input data
{
sb.Append("Input data: {");
foreach (INeuroTransmitter val in input.Values)
{
sb.AppendFormat(" {0}", val);
}
sb.Append(" }");
sb.AppendLine();
}
#endregion
n.ProcessData(input.Values);
#region -> Log output data
{
sb.Append("Iteration #1: {");
foreach (INeuroTransmitter val in n.SynapticKnobs)
{
sb.AppendFormat(" {0}", val);
}
sb.Append(" }");
sb.AppendLine();
}
#endregion
string txActual = sb.ToString();
string txExpctd = Data.CalculationLog;
CompareResult(
txActual, txExpctd, subDirName,
"Calculation", "Calculation log changed");
}
