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