public void Experiment3()
{
String filename = "Function3";
StringBuilder expected = new StringBuilder();
StringBuilder result = new StringBuilder();
int fuzzySetsCount = 10;
Range range = new Range(-5, 5);
IFunction function = FunctionsHelper.GetConcreteFunction(FunNumber.F3);
List<FuzzySet> fuzzySets = FuzzySet.coverRangeWithFuzzySets(range, fuzzySetsCount);
SimpleFuzzyRules3D fuzzyRules = new SimpleFuzzyRules3D(generateRandom2DPoints(range, RANDOM_POINTS_COUNT), function, fuzzySets);
double[][] testPoints = generateRandom2DPoints(range, RANDOM_POINTS_COUNT);
foreach (double[] xs in testPoints)
{
double output = fuzzyRules.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 + "//fuzzy_" + filename + "_expected.dat", expected.ToString());
FileManagement.WriteToFile(outputDirectory + "//fuzzy_" + filename + "_result.dat", result.ToString());
double error = fuzzyRules.getError(testPoints);
Console.WriteLine("Error = " + error);
}
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");
}
private double[][] generateRandom2DPoints(Range range, int randomPointsCount)
{
double[] xs = generateRandomPoints(range, randomPointsCount);
double[] ys = generateRandomPoints(range, randomPointsCount, false);
double[][] result = new double[randomPointsCount][];
for (int i = 0; i < xs.Length; i++)
{
result[i] = new double[] { xs[i], ys[i] };
}
return result;
}
public static List<FuzzySet> coverRangeWithFuzzySets(Range range, int fuzzySetsCount)
{
double halfFuzzySetWidth = range.getWidth() / (fuzzySetsCount - 1);
List<FuzzySet> fuzzySets = new List<FuzzySet>();
fuzzySets.Add(new FuzzySet(Double.NegativeInfinity, range.getBegin(), range.getBegin() + halfFuzzySetWidth));
for (double a = range.getBegin(); a + 2 * halfFuzzySetWidth <= range.getEnd();
a += halfFuzzySetWidth)
{
double b = a + halfFuzzySetWidth;
double c = b + halfFuzzySetWidth;
fuzzySets.Add(new FuzzySet(a, b, c));
}
fuzzySets.Add(new FuzzySet(range.getEnd() - halfFuzzySetWidth, range.getEnd(), Double.PositiveInfinity));
return fuzzySets;
}
private double[] generateRandomPoints(Range range, int randomPointsCount, bool sort)
{
double[] randomPoints = new double[randomPointsCount];
for (int i = 0; i < randomPoints.Length; i++)
{
randomPoints[i] = randomPoint(range);
}
if (sort)
{
Array.Sort(randomPoints);
}
return randomPoints;
}
private double[] generateRandomPoints(Range range, int randomPointsCount)
{
return generateRandomPoints(range, randomPointsCount, true);
}
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 double randomPoint(Range range)
{
return range.getBegin() + (random.NextDouble() * range.getWidth());
}
private void testOneDimensionalFunction(IFunction function, Range range, String filename)
{
double[][] testPoints = to2DArray(generateRandomPoints(range, RANDOM_POINTS_COUNT));
List<FuzzySet> fuzzySets = FuzzySet.coverRangeWithFuzzySets(range, FUZZY_SETS_COUNT);
SimpleFuzzyRules fuzzyRules = new SimpleFuzzyRules(to2DArray(generateRandomPoints(range, RANDOM_POINTS_COUNT)), function, fuzzySets);
WriteResults(function, fuzzyRules, testPoints, filename);
}