public ProbabilityTable pointwiseProductPOS(ProbabilityTable multiplier, params IRandomVariable[] prodVarOrder)
{
ProbabilityTable product = new ProbabilityTable(prodVarOrder);
if (!product.randomVarInfo.GetKeys()
.SequenceEqual(
SetOps.union(CollectionFactory.CreateSet <IRandomVariable>(randomVarInfo.GetKeys()), CollectionFactory.CreateSet <IRandomVariable>(multiplier.randomVarInfo.GetKeys()))))
{
throw new IllegalArgumentException("Specified list deatailing order of mulitplier is inconsistent.");
}
// If no variables in the product
if (1 == product.getValues().Length)
{
product.getValues()[0] = getValues()[0] * multiplier.getValues()[0];
}
else
{
// Otherwise need to iterate through the product
// to calculate its values based on the terms.
object[] term1Values = new object[randomVarInfo.Size()];
object[] term2Values = new object[multiplier.randomVarInfo.Size()];
ProbabilityTableIterator di = new ProbabilityTablecIteratorImpl3(term1Values,
term2Values, product, multiplier, this);
product.iterateOverTable(di);
}
return(product);
}
public ProbabilityTable sumOut(params IRandomVariable[] vars)
{
ISet <IRandomVariable> soutVars = CollectionFactory.CreateSet <IRandomVariable>(this.randomVarInfo.GetKeys());
foreach (IRandomVariable rv in vars)
{
soutVars.Remove(rv);
}
ProbabilityTable summedOut = new ProbabilityTable(soutVars);
if (1 == summedOut.getValues().Length)
{
summedOut.getValues()[0] = getSum();
}
else
{
// Otherwise need to iterate through this distribution
// to calculate the summed out distribution.
object[] termValues = new object[summedOut.randomVarInfo.Size()];
ProbabilityTableIterator di = new ProbabilityTableIteratorImpl(summedOut, termValues);
iterateOverTable(di);
}
return(summedOut);
}
public ProbabilityTable divideBy(ProbabilityTable divisor)
{
if (!randomVarInfo.GetKeys().ContainsAll(divisor.randomVarInfo.GetKeys()))
{
throw new IllegalArgumentException("Divisor must be a subset of the dividend.");
}
ProbabilityTable quotient = new ProbabilityTable(randomVarInfo.GetKeys());
if (1 == divisor.getValues().Length)
{
double d = divisor.getValues()[0];
for (int i = 0; i < quotient.getValues().Length; ++i)
{
if (0 == d)
{
quotient.getValues()[i] = 0;
}
else
{
quotient.getValues()[i] = getValues()[i] / d;
}
}
}
else
{
ISet <IRandomVariable> dividendDivisorDiff = SetOps
.difference(
CollectionFactory.CreateSet <IRandomVariable>(this.randomVarInfo.GetKeys()),
CollectionFactory.CreateSet <IRandomVariable>(divisor.randomVarInfo.GetKeys()));
IMap <IRandomVariable, RVInfo> tdiff = null;
MixedRadixNumber tdMRN = null;
if (dividendDivisorDiff.Size() > 0)
{
tdiff = CollectionFactory.CreateInsertionOrderedMap <IRandomVariable, RVInfo>();
foreach (IRandomVariable rv in dividendDivisorDiff)
{
tdiff.Put(rv, new RVInfo(rv));
}
tdMRN = new MixedRadixNumber(0, createRadixs(tdiff));
}
IMap <IRandomVariable, RVInfo> diff = tdiff;
MixedRadixNumber dMRN = tdMRN;
int[] qRVs = new int[quotient.radices.Length];
MixedRadixNumber qMRN = new MixedRadixNumber(0, quotient.radices);
ProbabilityTableIterator divisorIterator = new ProbabilityTableIteratorImp2(quotient, qRVs, qMRN, dMRN, diff, this);
divisor.iterateOverTable(divisorIterator);
}
return(quotient);
}
//
//
private void updateQuotient(double probability)
{
int offset = (int)qMRN.GetCurrentValueFor(qRVs);
if (0 == probability)
{
quotient.getValues()[offset] = 0;
}
else
{
quotient.getValues()[offset] += probabilityTable.getValues()[offset] / probability;
}
}
public void iterate(IMap <IRandomVariable, object> possibleWorld, double probability)
{
int term1Idx = termIdx(term1Values, probabilityTable, possibleWorld);
int term2Idx = termIdx(term2Values, multiplier, possibleWorld);
product.getValues()[idx] = probabilityTable.getValues()[term1Idx] * multiplier.getValues()[term2Idx];
idx++;
}
public void iterate(IMap <IRandomVariable, object> possibleWorld, double probability)
{
int i = 0;
foreach (IRandomVariable rv in summedOut.randomVarInfo.GetKeys())
{
termValues[i] = possibleWorld.Get(rv);
++i;
}
summedOut.getValues()[summedOut.getIndex(termValues)] += probability;
}