/**
* @return Returns a string representation of the classification structure. Of the form P(a|b,c,d)
*/
public String getClassificationStructure() {
StringBuilder result = new StringBuilder();
result.append("P(");
boolean first = true;
for (int i = 0; i < this.getEvents().size(); i++) {
BayesianEvent event = this.events.get(i);
EventState state = this.query.getEventState(event);
if (state.getEventType() == EventType.Outcome) {
if (!first) {
result.append(",");
}
result.append(event.getLabel());
first = false;
}
}
result.append("|");
first = true;
for (int i = 0; i < this.getEvents().size(); i++) {
BayesianEvent event = this.events.get(i);
if (this.query.getEventState(event).getEventType() == EventType.Evidence) {
if (!first) {
result.append(",");
}
result.append(event.getLabel());
first = false;
}
}
result.append(")");
return result.toString();
}
/**
* Create, or register, the specified event with this bayesian network.
*
* @param event The event to add.
*/
public void createEvent(BayesianEvent event) {
if (eventExists(event.getLabel())) {
throw new BayesianError("The label \"" + event.getLabel() + "\" has already been defined.");
}
this.eventMap.put(event.getLabel(), event);
this.events.add(event);
}
/**
* Remove the specified event.
*
* @param event The event to remove.
*/
private void removeEvent(BayesianEvent event) {
for (BayesianEvent e : event.getParents()) {
e.getChildren().remove(event);
}
this.eventMap.remove(event.getLabel());
this.events.remove(event);
}
/** {@inheritDoc} */
@Override
public final void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final BayesianNetwork b = (BayesianNetwork) obj;
out.addSection("BAYES-NETWORK");
out.addSubSection("BAYES-PARAM");
String queryType = "";
String queryStr = b.getClassificationStructure();
if (b.getQuery() != null) {
queryType = b.getQuery().getClass().getSimpleName();
}
out.writeProperty("queryType", queryType);
out.writeProperty("query", queryStr);
out.writeProperty("contents", b.getContents());
out.addSubSection("BAYES-PROPERTIES");
out.addProperties(b.getProperties());
out.addSubSection("BAYES-TABLE");
for (BayesianEvent event : b.getEvents()) {
for (TableLine line : event.getTable().getLines()) {
if (line == null) continue;
StringBuilder str = new StringBuilder();
str.append("P(");
str.append(BayesianEvent.formatEventName(event, line.getResult()));
if (event.getParents().size() > 0) {
str.append("|");
}
int index = 0;
boolean first = true;
for (BayesianEvent parentEvent : event.getParents()) {
if (!first) {
str.append(",");
}
first = false;
int arg = line.getArguments()[index++];
if (parentEvent.isBoolean()) {
if (arg == 0) {
str.append("+");
} else {
str.append("-");
}
}
str.append(parentEvent.getLabel());
if (!parentEvent.isBoolean()) {
str.append("=");
if (arg >= parentEvent.getChoices().size()) {
throw new BayesianError(
"Argument value " + arg + " is out of range for event " + parentEvent.toString());
}
str.append(parentEvent.getChoice(arg));
}
}
str.append(")=");
str.append(line.getProbability());
str.append("\n");
out.write(str.toString());
}
}
out.flush();
}
/**
* 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();
}
}
