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);
}
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);
}
/** {@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();
}
