public ProbabilityTable pointwiseProductPOS(
ProbabilityTable multiplier, params RandomVariable[] prodVarOrder)
{
ProbabilityTable product = new ProbabilityTable(prodVarOrder);
if (!product.randomVarInfo.keySet().Equals(
SetOps.union(new List <RandomVariable>(randomVarInfo.keySet()),
new List <RandomVariable>(multiplier.randomVarInfo
.keySet()))))
{
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()];
//ProbabilityTable.Iterator di = new ProbabilityTable.Iterator() {
// private int idx = 0;
// public void iterate(Map<RandomVariable, Object> possibleWorld,
// double probability) {
// int term1Idx = termIdx(term1Values, ProbabilityTable.this,
// possibleWorld);
// int term2Idx = termIdx(term2Values, multiplier,
// possibleWorld);
// product.getValues()[idx] = getValues()[term1Idx]
// * multiplier.getValues()[term2Idx];
// idx++;
// }
// private int termIdx(Object[] termValues, ProbabilityTable d,
// Map<RandomVariable, Object> possibleWorld) {
// if (0 == termValues.Length) {
// // The term has no variables so always position 0.
// return 0;
// }
// int i = 0;
// for (RandomVariable rv : d.randomVarInfo.keySet()) {
// termValues[i] = possibleWorld.get(rv);
// i++;
// }
// return d.getIndex(termValues);
// }
//};
//product.iterateOverTable(di);
// TODO
}
}
return(product);
}
public ProbabilityTable sumOut(params RandomVariable[] vars)
{
Set <RandomVariable> soutVars = new Set <RandomVariable>(
this.randomVarInfo.keySet());
foreach (RandomVariable 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()];
//ProbabilityTable.Iterator di = new ProbabilityTable.Iterator() {
// public void iterate(Map<RandomVariable, Object> possibleWorld,
// double probability) {
// int i = 0;
// foreach (RandomVariable rv in summedOut.randomVarInfo.keySet()) {
// termValues[i] = possibleWorld.get(rv);
// i++;
// }
// summedOut.getValues()[summedOut.getIndex(termValues)] += probability;
// }
//};
//iterateOverTable(di);
//TODO:
}
return(summedOut);
}
public ProbabilityTable divideBy(ProbabilityTable divisor)
{
if (!randomVarInfo.keySet().containsAll(divisor.randomVarInfo.keySet()))
{
throw new IllegalArgumentException(
"Divisor must be a subset of the dividend.");
}
ProbabilityTable quotient = new ProbabilityTable(new List <RandomVariable>(randomVarInfo.Keys));
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
{
Set <RandomVariable> dividendDivisorDiff = SetOps
.difference(new List <RVInfo>(randomVarInfo.keySet()),
new List <RVInfo>(randomVarInfo.keySet()));
Map <RandomVariable, RVInfo> tdiff = null;
MixedRadixNumber tdMRN = null;
if (dividendDivisorDiff.size() > 0)
{
tdiff = new LinkedHashMap <RandomVariable, RVInfo>();
foreach (RandomVariable rv in dividendDivisorDiff)
{
tdiff.put(rv, new RVInfo(rv));
}
tdMRN = new MixedRadixNumber(0, createRadixs(tdiff));
}
Map <RandomVariable, RVInfo> diff = tdiff;
MixedRadixNumber dMRN = tdMRN;
int[] qRVs = new int[quotient.radices.Length];
MixedRadixNumber qMRN = new MixedRadixNumber(0,
quotient.radices);
//ProbabilityTable.Iterator divisorIterator = new ProbabilityTable.Iterator() {
// public void iterate(Map<RandomVariable, Object> possibleWorld,
// double probability) {
// foreach (RandomVariable rv in possibleWorld.keySet()) {
// RVInfo rvInfo = quotient.randomVarInfo.get(rv);
// qRVs[rvInfo.getRadixIdx()] = rvInfo
// .getIdxForDomain(possibleWorld.get(rv));
// }
// if (null != diff) {
// // Start from 0 off the diff
// dMRN.setCurrentValueFor(new int[diff.size()]);
// do {
// for (RandomVariable rv : diff.keySet()) {
// RVInfo drvInfo = diff.get(rv);
// RVInfo qrvInfo = quotient.randomVarInfo.get(rv);
// qRVs[qrvInfo.getRadixIdx()] = dMRN
// .getCurrentNumeralValue(drvInfo
// .getRadixIdx());
// }
// updateQuotient(probability);
// } while (dMRN.increment());
// } else {
// updateQuotient(probability);
// }
// }
// //
//
//private void updateQuotient(double probability) {
// int offset = (int) qMRN.getCurrentValueFor(qRVs);
// if (0 == probability) {
// quotient.getValues()[offset] = 0;
// } else {
// quotient.getValues()[offset] += getValues()[offset]
// / probability;
// }
//}
////// };
// divisor.iterateOverTable(divisorIterator);
// TODO
}
return(quotient);
}
public ProbabilityTable pointwiseProductPOS(
ProbabilityTable multiplier, params RandomVariable[] prodVarOrder)
{
ProbabilityTable product = new ProbabilityTable(prodVarOrder);
if (!product.randomVarInfo.keySet().Equals(
SetOps.union(new List<RandomVariable>(randomVarInfo.keySet()),
new List<RandomVariable>(multiplier.randomVarInfo
.keySet()))))
{
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()];
//ProbabilityTable.Iterator di = new ProbabilityTable.Iterator() {
// private int idx = 0;
// public void iterate(Map<RandomVariable, Object> possibleWorld,
// double probability) {
// int term1Idx = termIdx(term1Values, ProbabilityTable.this,
// possibleWorld);
// int term2Idx = termIdx(term2Values, multiplier,
// possibleWorld);
// product.getValues()[idx] = getValues()[term1Idx]
// * multiplier.getValues()[term2Idx];
// idx++;
// }
// private int termIdx(Object[] termValues, ProbabilityTable d,
// Map<RandomVariable, Object> possibleWorld) {
// if (0 == termValues.Length) {
// // The term has no variables so always position 0.
// return 0;
// }
// int i = 0;
// for (RandomVariable rv : d.randomVarInfo.keySet()) {
// termValues[i] = possibleWorld.get(rv);
// i++;
// }
// return d.getIndex(termValues);
// }
//};
//product.iterateOverTable(di);
// TODO
}
}
return product;
}
public ProbabilityTable divideBy(ProbabilityTable divisor)
{
if (!randomVarInfo.keySet().containsAll(divisor.randomVarInfo.keySet()))
{
throw new IllegalArgumentException(
"Divisor must be a subset of the dividend.");
}
ProbabilityTable quotient = new ProbabilityTable(new List<RandomVariable>(randomVarInfo.Keys));
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
{
Set<RandomVariable> dividendDivisorDiff = SetOps
.difference(new List<RVInfo>(randomVarInfo.keySet()),
new List<RVInfo>(randomVarInfo.keySet()));
Map<RandomVariable, RVInfo> tdiff = null;
MixedRadixNumber tdMRN = null;
if (dividendDivisorDiff.size() > 0)
{
tdiff = new LinkedHashMap<RandomVariable, RVInfo>();
foreach (RandomVariable rv in dividendDivisorDiff)
{
tdiff.put(rv, new RVInfo(rv));
}
tdMRN = new MixedRadixNumber(0, createRadixs(tdiff));
}
Map<RandomVariable, RVInfo> diff = tdiff;
MixedRadixNumber dMRN = tdMRN;
int[] qRVs = new int[quotient.radices.Length];
MixedRadixNumber qMRN = new MixedRadixNumber(0,
quotient.radices);
//ProbabilityTable.Iterator divisorIterator = new ProbabilityTable.Iterator() {
// public void iterate(Map<RandomVariable, Object> possibleWorld,
// double probability) {
// foreach (RandomVariable rv in possibleWorld.keySet()) {
// RVInfo rvInfo = quotient.randomVarInfo.get(rv);
// qRVs[rvInfo.getRadixIdx()] = rvInfo
// .getIdxForDomain(possibleWorld.get(rv));
// }
// if (null != diff) {
// // Start from 0 off the diff
// dMRN.setCurrentValueFor(new int[diff.size()]);
// do {
// for (RandomVariable rv : diff.keySet()) {
// RVInfo drvInfo = diff.get(rv);
// RVInfo qrvInfo = quotient.randomVarInfo.get(rv);
// qRVs[qrvInfo.getRadixIdx()] = dMRN
// .getCurrentNumeralValue(drvInfo
// .getRadixIdx());
// }
// updateQuotient(probability);
// } while (dMRN.increment());
// } else {
// updateQuotient(probability);
// }
// }
// //
//
//private void updateQuotient(double probability) {
// int offset = (int) qMRN.getCurrentValueFor(qRVs);
// if (0 == probability) {
// quotient.getValues()[offset] = 0;
// } else {
// quotient.getValues()[offset] += getValues()[offset]
// / probability;
// }
//}
////// };
// divisor.iterateOverTable(divisorIterator);
// TODO
}
return quotient;
}
public ProbabilityTable sumOut(params RandomVariable[] vars)
{
Set<RandomVariable> soutVars = new Set<RandomVariable>(
this.randomVarInfo.keySet());
foreach (RandomVariable 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()];
//ProbabilityTable.Iterator di = new ProbabilityTable.Iterator() {
// public void iterate(Map<RandomVariable, Object> possibleWorld,
// double probability) {
// int i = 0;
// foreach (RandomVariable rv in summedOut.randomVarInfo.keySet()) {
// termValues[i] = possibleWorld.get(rv);
// i++;
// }
// summedOut.getValues()[summedOut.getIndex(termValues)] += probability;
// }
//};
//iterateOverTable(di);
//TODO:
}
return summedOut;
}
