@Override
public void nextSample() {
WorldWithBlock curWorld = (WorldWithBlock) getBaseWorld();
if (curWorld == null) {
curWorld = new WorldWithBlock(model, evidence, intBound, depthBound);
Util.debug("Creating initial possible world");
}
this.curWorld = curWorld;
double logWeight = Double.NEGATIVE_INFINITY;
latestSampleLogWeight = 0;
while (!isCurWorldSufficient(curWorld)) {
VarWithDistrib var = curWorld.getNextUninstVar();
if (var != null) {
if (var.canSample(curWorld)) {
logWeight = sampleAndComputeLogWeight(var, curWorld);
} else {
curWorld.putBackVarWithDistrib(var);
}
} else {
System.out.println(
"World is not complete, but no basic random "
+ "variable is supported. Please check for "
+ "a possible cycle in your model.");
}
latestSampleLogWeight += logWeight;
}
if (!evidence.isTrue(curWorld)) latestSampleLogWeight = Double.NEGATIVE_INFINITY;
BLOGUtil.ensureDetAndSupported(queryVars, curWorld);
// FIXME: remove duplication with LWSampler
++totalNumSamples;
++numSamplesThisTrial;
if (latestSampleLogWeight > NEGLIGIBLE_LOG_WEIGHT) {
++totalNumConsistent;
++numConsistentThisTrial;
}
logSumWeightsThisTrial = Util.logSum(logSumWeightsThisTrial, latestSampleLogWeight);
}
private double sampleAndComputeLogWeight(VarWithDistrib var, WorldWithBlock curWorld) {
DependencyModel.Distrib distrib =
var.getDistrib(new BlockInstantiatingEvalContextImpl(curWorld));
Util.debug("Instantiating: ", var);
Type varType = var.getType();
CondProbDistrib cpd = distrib.getCPD();
cpd.setParams(distrib.getArgValues());
Region r = curWorld.getSatisfyingRegion(var);
double logWeight = Double.NEGATIVE_INFINITY;
if (r.isEmpty()) return -1;
Object value = null;
if (r.isSingleton()) {
value = r.getOneValue();
logWeight = java.lang.Math.log(cpd.getProb(value));
} else {
do {
value = cpd.sampleVal();
} while (!r.contains(value));
logWeight = java.lang.Math.log(computeCPD(cpd, r));
}
curWorld.setValue(var, value);
return logWeight;
}