public void testSampling3() {
BayesianNetwork network = new BayesianNetwork();
BayesianEvent a = network.createEvent("a");
BayesianEvent x1 = network.createEvent("x1");
BayesianEvent x2 = network.createEvent("x2");
BayesianEvent x3 = network.createEvent("x3");
network.createDependancy(a, x1, x2, x3);
network.finalizeStructure();
a.getTable().addLine(0.5, true); // P(A) = 0.5
x1.getTable().addLine(0.2, true, true); // p(x1|a) = 0.2
x1.getTable().addLine(0.6, true, false); // p(x1|~a) = 0.6
x2.getTable().addLine(0.2, true, true); // p(x2|a) = 0.2
x2.getTable().addLine(0.6, true, false); // p(x2|~a) = 0.6
x3.getTable().addLine(0.2, true, true); // p(x3|a) = 0.2
x3.getTable().addLine(0.6, true, false); // p(x3|~a) = 0.6
network.validate();
SamplingQuery query = new SamplingQuery(network);
query.defineEventType(x1, EventType.Evidence);
query.defineEventType(x3, EventType.Outcome);
query.setEventValue(x1, true);
query.setEventValue(x3, true);
query.execute();
testPercent(query.getProbability(), 50);
}
/** {@inheritDoc} */
@Override
public final Object read(final InputStream is) {
final BayesianNetwork result = new BayesianNetwork();
final EncogReadHelper in = new EncogReadHelper(is);
EncogFileSection section;
String queryType = "";
String queryStr = "";
String contentsStr = "";
while ((section = in.readNextSection()) != null) {
if (section.getSectionName().equals("BAYES-NETWORK")
&& section.getSubSectionName().equals("BAYES-PARAM")) {
final Map<String, String> params = section.parseParams();
queryType = params.get("queryType");
queryStr = params.get("query");
contentsStr = params.get("contents");
}
if (section.getSectionName().equals("BAYES-NETWORK")
&& section.getSubSectionName().equals("BAYES-TABLE")) {
result.setContents(contentsStr);
// first, define relationships (1st pass)
for (String line : section.getLines()) {
result.defineRelationship(line);
}
result.finalizeStructure();
// now define the probabilities (2nd pass)
for (String line : section.getLines()) {
result.defineProbability(line);
}
}
if (section.getSectionName().equals("BAYES-NETWORK")
&& section.getSubSectionName().equals("BAYES-PROPERTIES")) {
final Map<String, String> params = section.parseParams();
result.getProperties().putAll(params);
}
}
// define query, if it exists
if (queryType.length() > 0) {
BayesianQuery query = null;
if (queryType.equals("EnumerationQuery")) {
query = new EnumerationQuery(result);
} else {
query = new SamplingQuery(result);
}
if (query != null && queryStr.length() > 0) {
result.setQuery(query);
result.defineClassificationStructure(queryStr);
}
}
return result;
}
public void testSampling1() {
BayesianNetwork network = new BayesianNetwork();
BayesianEvent a = network.createEvent("a");
BayesianEvent b = network.createEvent("b");
network.createDependancy(a, b);
network.finalizeStructure();
a.getTable().addLine(0.5, true); // P(A) = 0.5
b.getTable().addLine(0.2, true, true); // p(b|a) = 0.2
b.getTable().addLine(0.8, true, false); // p(b|~a) = 0.8
network.validate();
SamplingQuery query = new SamplingQuery(network);
query.defineEventType(a, EventType.Evidence);
query.defineEventType(b, EventType.Outcome);
query.setEventValue(b, true);
query.setEventValue(a, true);
query.execute();
testPercent(query.getProbability(), 20);
}
/**
* Define the structure of the Bayesian network as a string.
*
* @param line The string to define events and relations.
*/
public void setContents(String line) {
List<ParsedProbability> list = ParseProbability.parseProbabilityList(this, line);
List<String> labelList = new ArrayList<String>();
// ensure that all events are there
for (ParsedProbability prob : list) {
ParsedEvent parsedEvent = prob.getChildEvent();
String eventLabel = parsedEvent.getLabel();
labelList.add(eventLabel);
// create event, if not already here
BayesianEvent e = getEvent(eventLabel);
if (e == null) {
List<BayesianChoice> cl = new ArrayList<BayesianChoice>();
for (ParsedChoice c : parsedEvent.getList()) {
cl.add(new BayesianChoice(c.getLabel(), c.getMin(), c.getMax()));
}
createEvent(eventLabel, cl);
}
}
// now remove all events that were not covered
for (int i = 0; i < events.size(); i++) {
BayesianEvent event = this.events.get(i);
if (!labelList.contains(event.getLabel())) {
removeEvent(event);
}
}
// handle dependencies
for (ParsedProbability prob : list) {
ParsedEvent parsedEvent = prob.getChildEvent();
String eventLabel = parsedEvent.getLabel();
BayesianEvent event = requireEvent(eventLabel);
// ensure that all "givens" are present
List<String> givenList = new ArrayList<String>();
for (ParsedEvent given : prob.getGivenEvents()) {
if (!event.hasGiven(given.getLabel())) {
BayesianEvent givenEvent = requireEvent(given.getLabel());
this.createDependency(givenEvent, event);
}
givenList.add(given.getLabel());
}
// now remove givens that were not covered
for (int i = 0; i < event.getParents().size(); i++) {
BayesianEvent event2 = event.getParents().get(i);
if (!givenList.contains(event2.getLabel())) {
removeDependency(event2, event);
}
}
}
// finalize the structure
finalizeStructure();
if (this.query != null) {
this.query.finalizeStructure();
}
}