public static void logOuts(List <double[]> ins, List <double[]> outs, NN.neuralNet myNN)
{
for (int i = 0; i < ins.Count; i++)
{
double[] output = myNN.forward(ins[i]);
for (int j = 0; j < output.Length; j++)
{
Console.WriteLine(output.arrayToString() + "," + outs[i].arrayToString());
}
}
}
public static void logFail(List <double[]> ins, List <double[]> outs, NN.neuralNet myNN)
{
for (int i = 0; i < ins.Count; i++)
{
double[] output = myNN.forward(ins[i]);
for (int j = 0; j < output.Length; j++)
{
//if (((int)Math.Round(output[j],1)) != (int)Math.Round(outs[i][j])) { Console.WriteLine(output.arrayToString() + "," + outs[i].arrayToString()); return; }
//if (((int)Math.Round(output[j])) != (int)Math.Round(outs[i][j])) { Console.WriteLine(output.arrayToString() + "," + outs[i].arrayToString()); return; }
if (!binaryCompare(output[j], outs[i][j], .08))
{
Console.WriteLine(output.arrayToString() + "," + outs[i].arrayToString()); return;
}
}
}
}
public static bool good(List <double[]> ins, List <double[]> outs, NN.neuralNet myNN)
{
for (int i = 0; i < ins.Count; i++)
{
double[] output = myNN.forward(ins[i]);
//Console.WriteLine(output.arrayToString()+","+outs[i].arrayToString());
for (int j = 0; j < output.Length; j++)
{
//Console.WriteLine(((int)Math.Round(output[j])) + "," + (int)Math.Round(outs[i][j]));
//if ((((int)Math.Round(output[j], 1))) != ((int)Math.Round(outs[i][j]))) return false;
//if ((((int)Math.Round(output[j]))) != ((int)Math.Round(outs[i][j]))) return false;
if (!binaryCompare(output[j], outs[i][j], .08))
{
return(false);
}
}
}
return(true);
}