private void undoPriorInfluence(Map<String, Double> probabilites) {
if (probabilites != null && probabilites.size() > 0) {
model.priorDenominator--;
for (Map.Entry<String, Double> e : model.categoryPriors.entrySet()) {
e.setValue(e.getValue() - probabilites.get(e.getKey()));
}
}
}
private void makePriorInfluence(Map<String, Double> probabilites) {
if (probabilites != null) {
model.priorDenominator++;
for (Map.Entry<String, Double> e : model.categoryPriors.entrySet()) {
e.setValue(e.getValue() + probabilites.get(e.getKey()));
}
}
}
@Override
public void newAssign(AssignedLabel<String> assign) {
DatumResult dr = results.getOrCreateDatumResult(assign.getLobject());
Map<String, Double> oldProbabilites = dr.getCategoryProbabilites();
// update object class probabilites
Map<String, Double> probabilities =
getObjectClassProbabilities(assign.getLobject(), assign.getWorker());
dr.setCategoryProbabilites(probabilities);
results.addDatumResult(assign.getLobject(), dr);
// update priors
if (!data.arePriorsFixed()) {
undoPriorInfluence(oldProbabilites);
makePriorInfluence(probabilities);
}
// rebuild worker confusion matrices for all workers who assigned this object
if (probabilities != null)
for (AssignedLabel<String> al : data.getAssignsForObject(assign.getLobject())) {
WorkerResult wr = results.getOrCreateWorkerResult(al.getWorker());
for (Map.Entry<String, Double> e : probabilities.entrySet()) {
wr.addError(e.getKey(), al.getLabel(), e.getValue());
}
results.addWorkerResult(al.getWorker(), wr);
}
}
