public void Experiment3()
{
Range range = new Range(-5, 5);
double[][] testPoints = generateRandom2DPoints(range, RANDOM_POINTS_COUNT);
IFunction function = FunctionsHelper.GetConcreteFunction(FunNumber.F3);
NeuroBackPropagation backPropagation = new NeuroBackPropagation(generateRandom2DPoints(range, RANDOM_POINTS_COUNT), function);
WriteResults(function, backPropagation, testPoints, "Function3");
}
public void testOneDimensionalFunction(IFunction function, Range range, String filename)
{
NeuroBackPropagation backPropagation = new NeuroBackPropagation(to2DArray(generateRandomPoints(range, RANDOM_POINTS_COUNT)), function);
double[][] testPoints = to2DArray(generateRandomPoints(range, RANDOM_POINTS_COUNT));
WriteResults(function, backPropagation, testPoints, filename);
}
private void WriteResults(IFunction function, NeuroBackPropagation backPropagation, double[][] testPoints, String filename)
{
StringBuilder expected = new StringBuilder();
StringBuilder result = new StringBuilder();
foreach (double[] xs in testPoints)
{
double output = backPropagation.getOutput(xs);
// Console.WriteLine(String.format("f(" + Arrays.toString(xs) + ") = %.2f, expected %.2f", output, function.evaluate(xs)));
expected.Append(StringUtils.Join(xs, " ") + " " + output + "\n");
result.Append(StringUtils.Join(xs, " ") + " " + function.evaluate(xs) + "\n");
}
// Save results to files.
FileManagement.WriteToFile(outputDirectory + "//neuro_" + filename + "_expected.dat", expected.ToString());
FileManagement.WriteToFile(outputDirectory + "//neuro_" + filename + "_result.dat", result.ToString());
// Print Error message.
double error = backPropagation.getError(testPoints);
Console.WriteLine("Error = " + error);
}
