implement untested variance calculation for RandomVariables

tools.descartes.dml.mm.applicationlevel/src/tools/descartes/dml/mm/applicationlevel/functions/util/RandomVariableHelper.java

@@ -16,6 +16,7 @@ import tools.descartes.dml.mm.applicationlevel.functions.IntSampleList;
 import tools.descartes.dml.mm.applicationlevel.functions.NormalDistribution;
 import tools.descartes.dml.mm.applicationlevel.functions.ProbabilityFunction;
 import tools.descartes.dml.mm.applicationlevel.functions.ProbabilityMassFunction;
+import tools.descartes.dml.mm.applicationlevel.functions.ReplayFile;
 import tools.descartes.dml.mm.applicationlevel.functions.SampleList;
 
 /**
@@ -45,11 +46,125 @@ public class RandomVariableHelper {
 			return _getNumericalMean((BoxedPDF) probfn);
 		if (probfn instanceof ProbabilityMassFunction)
 			return _getNumericalMean((ProbabilityMassFunction) probfn);
+		if (probfn instanceof ReplayFile)
+			return _getNumericalMean((ReplayFile) probfn);
 		return _getNumericalMean(probfn);
 	}
 
+	public static Double getNumericalVariance(ProbabilityFunction probfn) {
+		if (probfn instanceof IntLiteral)
+			return _getNumericalVariance((IntLiteral) probfn);
+		if (probfn instanceof DoubleLiteral)
+			return _getNumericalVariance((DoubleLiteral) probfn);
+		if (probfn instanceof BooleanLiteral)
+			return _getNumericalVariance((BooleanLiteral) probfn);
+		if (probfn instanceof ExponentialDistribution)
+			return _getNumericalVariance((ExponentialDistribution) probfn);
+		if (probfn instanceof NormalDistribution)
+			return _getNumericalVariance((NormalDistribution) probfn);
+		if (probfn instanceof BoxedPDF)
+			return _getNumericalVariance((BoxedPDF) probfn);
+		if (probfn instanceof ProbabilityMassFunction)
+			return _getNumericalVariance((ProbabilityMassFunction) probfn);
+		if (probfn instanceof ReplayFile)
+			return _getNumericalVariance((ReplayFile) probfn);
+		return _getNumericalVariance(probfn);
+	}
+
+	private static Double _getNumericalVariance(EnumSampleList enumSl) {
+		throw new UnsupportedOperationException("Enums do not have a numerical variance.");
+	}
+
+	private static Double _getNumericalVariance(DoubleSampleList doubleSl) {
+		double[] singletons = new double[doubleSl.getItems().size()];
+		double[] probabilities = new double[doubleSl.getItems().size()];
+		for (int i = 0; i < doubleSl.getItems().size(); i++) {
+			singletons[i] = doubleSl.getItems().get(i).getValue().doubleValue();
+			probabilities[i] = doubleSl.getItems().get(i).getProbability().doubleValue();
+		}
+		EnumeratedRealDistribution dist = new EnumeratedRealDistribution(singletons, probabilities);
+		return dist.getNumericalVariance();
+	}
+
+	private static Double _getNumericalVariance(BoolSampleList boolSl) {
+		throw new UnsupportedOperationException("Booleans do not have a numerical variance.");
+
+	}
+
+	private static Double _getNumericalVariance(IntSampleList intSl) {
+		int[] singletons = new int[intSl.getItems().size()];
+		double[] probabilities = new double[intSl.getItems().size()];
+		for (int i = 0; i < intSl.getItems().size(); i++) {
+			singletons[i] = intSl.getItems().get(i).getValue().intValue();
+			probabilities[i] = intSl.getItems().get(i).getProbability().doubleValue();
+		}
+		EnumeratedIntegerDistribution dist = new EnumeratedIntegerDistribution(singletons, probabilities);
+		return dist.getNumericalVariance();
+	}
+
+	private static Double _getNumericalVariance(SampleList sl) {
+		if (sl instanceof IntSampleList)
+			return _getNumericalVariance((IntSampleList) sl);
+		else if (sl instanceof BoolSampleList)
+			return _getNumericalVariance((BoolSampleList) sl);
+		else if (sl instanceof DoubleSampleList)
+			return _getNumericalVariance((DoubleSampleList) sl);
+		else if (sl instanceof EnumSampleList)
+			return _getNumericalVariance((EnumSampleList) sl);
+		throw new IllegalStateException("Unknown type of SampleList: " + sl.getClass().getName());
+	}
+
+	private static Double _getNumericalVariance(ProbabilityMassFunction pmf) {
+		return _getNumericalVariance(pmf.getSamples());
+	}
+
+	private static Double _getNumericalVariance(BoxedPDF bpdf) {
+		double lastValue = 0;
+		double meanSquaredSamples = 0.0;
+		double numericalMean = _getNumericalMean(bpdf);
+		for (ContinuousSample cs : bpdf.getSample()) {
+			meanSquaredSamples += cs.getProbability().doubleValue()
+					* Math.pow((lastValue + (cs.getValue().doubleValue() - lastValue) / 2), 2);
+			lastValue = cs.getValue().doubleValue();
+		}
+		return meanSquaredSamples - Math.pow(numericalMean, 2);
+	}
+
+	private static Double _getNumericalVariance(NormalDistribution nd) {
+		return Math.pow(nd.getSigma().doubleValue(), 2);
+	}
+
+	private static Double _getNumericalVariance(ExponentialDistribution expd) {
+		double rate = expd.getRate().doubleValue();
+		if (rate > 0) {
+			return 1 / Math.pow(rate, 2);
+		}
+		throw new IllegalArgumentException("ExponentialDistribution rate must be greater than 0.");
+	}
+
+	private static Double _getNumericalVariance(BooleanLiteral l) {
+		return 0.0;
+	}
+
+	private static Double _getNumericalVariance(DoubleLiteral l) {
+		return 0.0;
+	}
+
+	private static Double _getNumericalVariance(IntLiteral l) {
+		return 0.0;
+	}
+
+	private static Double _getNumericalVariance(ProbabilityFunction probfn) {
+		throw new IllegalStateException("Unknown type of ProbabilityFunction: " + probfn.getClass().getName());
+	}
+
+	private static Double _getNumericalMean(ReplayFile replay) {
+		double sum = 0;
+		throw new UnsupportedOperationException("File Path: " + replay.getFilepath());
+	}
+
 	private static Double _getNumericalMean(ProbabilityMassFunction pmf) {
-		return RandomVariableHelper._getNumericalMean(pmf.getSamples());
+		return _getNumericalMean(pmf.getSamples());
 	}
 
 	private static Double _getNumericalMean(IntSampleList intsl) {