/**
* Write a Bayesian network to an output stream in BIF format.
*
* @param os The output stream to write to.
* @param network The network to write.
*/
public static void writeBIF(OutputStream os, BayesianNetwork network) {
WriteXML xml = new WriteXML(os);
xml.beginDocument();
xml.addAttribute("VERSION", "0.3");
xml.beginTag("BIF");
xml.beginTag("NETWORK");
xml.addProperty("NAME", "Bayes Network, Generated by Encog");
// write variables
for (BayesianEvent event : network.getEvents()) {
xml.addAttribute("TYPE", "nature");
xml.beginTag("VARIABLE");
xml.addProperty("NAME", event.getLabel());
for (BayesianChoice str : event.getChoices()) {
xml.addProperty("OUTCOME", str.getLabel());
}
xml.endTag();
}
// write relations
for (BayesianEvent event : network.getEvents()) {
xml.beginTag("DEFINITION");
xml.addProperty("FOR", event.getLabel());
for (BayesianEvent parentEvent : event.getParents()) {
xml.addProperty("GIVEN", parentEvent.getLabel());
}
xml.addAttribute("TABLE", generateTable(event));
xml.endTag();
}
xml.endTag();
xml.endTag();
xml.endDocument();
}
/** {@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 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();
}