// method to shuffle data during training
void ShuffleData()
{
int numShuffles = Inputs.Count();
int inputCount = Inputs[0].GetLength(0);
int outputCount = Outputs[0].GetLength(0);
int index1;
int index2;
double[] tempInput;
double[] tempOutput;
for (int i = 0; i < numShuffles; i++)
{
tempInput = new double[inputCount];
tempOutput = new double[outputCount];
index1 = Prob.Next(numShuffles);
index2 = Prob.Next(numShuffles);
for (int j = 0; j < inputCount; j++)
{
tempInput[j] = trainingInputs[index1][j];
trainingInputs[index1][j] = trainingInputs[index2][j];
trainingInputs[index2][j] = tempInput[j];
}
for (int j = 0; j < outputCount; j++)
{
tempOutput[j] = trainingOutputs[index1][j];
trainingOutputs[index1][j] = trainingOutputs[index2][j];
trainingOutputs[index2][j] = tempOutput[j];
}
}
}
// method to mutate one weight matrix
double[,] MutateOneMatrix(double[,] matrix, int numMutations)
{
// find dimensions of matrix
int dim1 = matrix.GetLength(0);
int dim2 = matrix.GetLength(1);
// create and populate copied weight matrix
double[,] output = new double[dim1, dim2];
for (int i = 0; i < dim1; i++)
{
for (int j = 0; j < dim2; j++)
{
output[i, j] = matrix[i, j];
}
}
// for each mutation, randomly select one value and mutate it
int tempDim1;
int tempDim2;
for (int i = 0; i < numMutations; i++)
{
tempDim1 = Prob.Next(dim1);
tempDim2 = Prob.Next(dim2);
output[tempDim1, tempDim2] += Prob.Gaussian(MutateSTD, 0.0);
}
// return mutated matrix
return(output);
}
