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); }