private void addObjects(Type newObjType, Collection newObjs) {
if (newObjs.isEmpty()) {
return;
}
List objs = (List) objectsByType.get(newObjType);
if (objs != null) { // if type serves as an argument to some basic RV
// Add function app vars with these objects as argument
for (Iterator fIter = model.getFunctions().iterator(); fIter.hasNext(); ) {
Function f = (Function) fIter.next();
if (f instanceof RandomFunction) {
RandomFunction rf = (RandomFunction) f;
if (Arrays.asList(f.getArgTypes()).contains(newObjType)) {
addFuncAppVars(rf, newObjType, newObjs);
}
}
}
// Add number vars with these object as arguments
for (Iterator typeIter = model.getTypes().iterator(); typeIter.hasNext(); ) {
Type generatedType = (Type) typeIter.next();
for (Iterator popIter = generatedType.getPOPs().iterator(); popIter.hasNext(); ) {
POP pop = (POP) popIter.next();
if (Arrays.asList(pop.getArgTypes()).contains(newObjType)) {
addNumberVars(pop, newObjType, newObjs);
}
}
}
// Don't need to worry about skolem constant vars because
// they don't have arguments
objs.addAll(newObjs);
}
}
/**
* compute the feasible region based on the evidence, the method will only use the v2 if 1. v1 is
* a direct parent of v2, or 2. v1 and v2 are the same, i.e. corresponding to evidence variable
*
* @param v1 the variable to sample
* @param v2 the variable corresponding to evidence
* @return
*/
private Region computeRegionFromEvidence(BayesNetVar v1, BayesNetVar v2) {
if (v1.equals(v2)) {
// the variable is in the evidence, it should be directly set to evidence
// value
return new SingletonRegion(evidence.getObservedValue(v2));
}
if (v2 instanceof DerivedVar) {
ArgSpec as = ((DerivedVar) v2).getArgSpec();
if (as instanceof CardinalitySpec) {
// child is cardinality of a set
ImplicitSetSpec iss = ((CardinalitySpec) as).getSetSpec();
Type childType = iss.getType();
if (v1 instanceof NumberVar) {
// parent is number variable, potential match
NumberVar numv1 = (NumberVar) v1;
POP parentPOP = numv1.pop();
Type parentType = parentPOP.type();
if (!parentType.equals(childType)) {
return null;
} else {
// potential match, if
Object[] objs = numv1.args(); // generating objects for parent
// variable
if (objs.length == 0) {
// no any constraint
return Region.FULL_REGION;
} else {
// v1 is parent of v2
Formula cond = iss.getCond();
if (cond.isDetermined(this) && cond.isTrue(this)) {
int value = ((Number) evidence.getObservedValue(v2)).intValue();
// get all previously satisfied var
Set<BayesNetVar> pvars = getAlreadySampledParentVars(v2);
for (BayesNetVar pv : pvars) {
// eliminate the already sampled ones
int a = ((Number) this.getValue(pv)).intValue();
value -= a;
}
// v1 is parent of v2, and will be sampled immediately
pvars.add(v1);
if ((value > 0) && anyMoreNumberVar(childType, cond)) {
return new IntRegion(0, value);
} else {
return new SingletonRegion(value);
}
}
}
}
} /* TODO check other cases of v1 that can be potential parent of this */
} else {
// other cases of argspec in v1
}
} else {
// other variables
// might be parent
// TODO check whether the condition has v1 as parent
}
return null;
}
/** add all random variables without parents into the uninstantiated variables */
protected void init() {
// added number variables for those number statement without origin
// functions
for (Type generatedType : model.getTypes()) {
Collection<POP> pops = generatedType.getPOPs();
// set initial size of unused number statements for each type
restPOPs.put(generatedType, new HashSet<POP>(pops));
for (POP pop : pops) {
for (int i = 0; i < pop.getArgTypes().length; ++i) {
objectsByType.put(pop.getArgTypes()[i], new ArrayList());
}
if (pop.getArgTypes().length == 0) {
addNumberVar(new NumberVar(pop, Collections.EMPTY_LIST));
}
}
}
// Determine what types serve as arguments to basic RVs. Initialize
// their object lists to be empty. As we're doing this, add any
// random variables with empty arg lists to the list of uninstantiated
// RVs.
for (Function f : model.getFunctions()) {
if (f instanceof RandomFunction) {
for (int i = 0; i < f.getArgTypes().length; ++i) {
objectsByType.put(f.getArgTypes()[i], new ArrayList());
}
if (f.getArgTypes().length == 0) {
uninstVars.add(new RandFuncAppVar((RandomFunction) f, Collections.EMPTY_LIST));
}
}
}
// add skolem constants defined in symbol evidence
// already added in step 1
// for (SkolemConstant c : evidence.getSkolemConstants()) {
// uninstVars.add(new RandFuncAppVar(c, Collections.EMPTY_LIST));
// }
// Create initial object lists for those types. While doing so,
// add uninstantiated variables that have these objects as arguments.
for (Type type : objectsByType.keySet()) {
if (type.isSubtypeOf(BuiltInTypes.INTEGER)) {
addObjects(type, Collections.singleton(new Integer(0)));
intsAreArgs = true;
} else if (type == BuiltInTypes.BOOLEAN) {
addObjects(type, type.getGuaranteedObjects());
} else if (type.isBuiltIn()) {
Util.fatalError("Illegal argument type for random function: " + type, false);
} else {
// user-defined type
addObjects(type, type.getGuaranteedObjects());
}
}
// set the iterator
lastIter = uninstVars.iterator();
}