public static ConditionalProbabilityTable multiplyAll(List<ConditionalProbabilityTable> cpts) {
ConditionalProbabilityTable product = null;
if (cpts.size() > 0) {
product = cpts.get(0);
for (int i = 1; i < cpts.size(); i++) {
product = product.multiply(cpts.get(i));
}
}
return product;
}
public static List<ConditionalProbabilityTable> getAllCptsContaining(
List<ConditionalProbabilityTable> factorization, Variable variable) {
List<ConditionalProbabilityTable> relevantCpts = new ArrayList<>();
for (ConditionalProbabilityTable cpt : factorization) {
if (cpt.contains(variable)) {
relevantCpts.add(cpt);
}
}
return relevantCpts;
}
public static List<ConditionalProbabilityTable> sumOut(
List<ConditionalProbabilityTable> factorization, List<Variable> varsToSumOut) {
List<ConditionalProbabilityTable> newFactorization = new ArrayList<>(factorization);
for (Variable varToSumOut : varsToSumOut) {
// Multiply all together
List<ConditionalProbabilityTable> relevantCpts =
Inference.getAllCptsContaining(newFactorization, varToSumOut);
ConditionalProbabilityTable product = Inference.multiplyAll(relevantCpts);
// Marginalize out the variable
ConditionalProbabilityTable marginal = product.marginalize(varToSumOut);
newFactorization.removeAll(relevantCpts);
newFactorization.add(marginal);
}
return newFactorization;
}
@Test
public void sumOut() {
XmlBif xmlBif;
try {
xmlBif =
new XmlBif(
new FileInputStream(
new File("/Users/jhonatanoliveira/Insync/uregina/research/dataset/asia.xml")));
BayesianNetwork bn = xmlBif.getBn();
List<Variable> varsToSumOut = bn.getAllVariables();
varsToSumOut.remove(bn.getVariable("dysp"));
List<ConditionalProbabilityTable> newFactorization =
Inference.sumOut(bn.getAllCpts(), varsToSumOut);
ConditionalProbabilityTable finalCpt = Inference.multiplyAll(newFactorization);
System.out.println(finalCpt);
System.out.println(finalCpt.getValues());
} catch (ParserConfigurationException | SAXException | IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
