private void display()
{
double[] input = new double[SineWave.INPUT_SIZE];
double[] output = new double[SineWave.OUTPUT_SIZE];
for (int i = SineWave.INPUT_SIZE; i < SineWave.ACTUAL_SIZE; i++)
{
this.actual.getInputData(i - SineWave.INPUT_SIZE, input);
this.actual.getOutputData(i - SineWave.INPUT_SIZE, output);
StringBuilder str = new StringBuilder();
str.Append(i);
str.Append(":Actual=");
for (int j = 0; j < output.Length; j++)
{
if (j > 0)
{
str.Append(',');
}
str.Append(output[j]);
}
double[] predict = this.network.ComputeOutputs(input);
str.Append(":Predicted=");
for (int j = 0; j < output.Length; j++)
{
if (j > 0)
{
str.Append(',');
}
str.Append(predict[j]);
}
str.Append(":Difference=");
ErrorCalculation error = new ErrorCalculation();
error.UpdateError(predict, output);
str.Append(error.CalculateRMS().ToString("N2"));
Console.WriteLine(str.ToString());
}
}
/// <summary>
/// Calculate the error for this neural network. The error is calculated
/// using root-mean-square(RMS).
/// </summary>
/// <param name="input">Input patterns.</param>
/// <param name="ideal">Ideal patterns.</param>
/// <returns>The error percentage.</returns>
public double CalculateError(double[][] input, double[][] ideal)
{
ErrorCalculation errorCalculation = new ErrorCalculation();
for (int i = 0; i < ideal.Length; i++)
{
ComputeOutputs(input[i]);
errorCalculation.UpdateError(this.outputLayer.Fire,
ideal[i]);
}
return (errorCalculation.CalculateRMS());
}
public void display()
{
double[] present = new double[INPUT_SIZE * 2];
double[] predict = new double[OUTPUT_SIZE];
double[] actualOutput = new double[OUTPUT_SIZE];
int index = 0;
foreach (FinancialSample sample in this.actual.getSamples())
{
if (sample.getDate().CompareTo(this.PREDICT_FROM) > 0)
{
StringBuilder str = new StringBuilder();
str.Append(ReadCSV.DisplayDate(sample.getDate()));
str.Append(":Start=");
str.Append(sample.getAmount());
this.actual.getInputData(index - INPUT_SIZE, present);
this.actual.getOutputData(index - INPUT_SIZE, actualOutput);
predict = this.network.ComputeOutputs(present);
str.Append(",Actual % Change=");
str.Append(actualOutput[0].ToString("N2"));
str.Append(",Predicted % Change= ");
str.Append(predict[0].ToString("N2"));
str.Append(":Difference=");
ErrorCalculation error = new ErrorCalculation();
error.UpdateError(predict, actualOutput);
str.Append(error.CalculateRMS().ToString("N2"));
//
Console.WriteLine(str.ToString());
}
index++;
}
}