//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: protected void initWithDefaultTransitions(org.maltparser.parser.history.GuideUserHistory history) throws org.maltparser.core.exception.MaltChainedException
protected internal override void initWithDefaultTransitions(GuideUserHistory history)
{
GuideUserAction currentAction = new ComplexDecisionAction(history);
transActionContainer.Action = SHIFT;
for (int i = 0; i < arcLabelActionContainers.Length; i++)
{
arcLabelActionContainers[i].Action = -1;
}
currentAction.addAction(actionContainers);
}
//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: protected void initWithDefaultTransitions(org.maltparser.parser.history.GuideUserHistory history) throws org.maltparser.core.exception.MaltChainedException
protected internal override void initWithDefaultTransitions(GuideUserHistory history)
{
GuideUserAction currentAction = new ComplexDecisionAction(history);
transActionContainer.Action = SHIFT;
transActionContainer.Action = REDUCE;
transActionContainer.Action = SWITCH; //TODO it seems like a good idea to do this, but I don't know what it actually does
transActionContainer.Action = REDUCEBOTH; //TODO same as above
for (int i = 0; i < arcLabelActionContainers.Length; i++)
{
arcLabelActionContainers[i].Action = -1;
}
currentAction.addAction(actionContainers);
}
//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: public boolean predictFromKBestList(org.maltparser.core.feature.FeatureModel featureModel, org.maltparser.parser.history.action.ComplexDecisionAction decision) throws org.maltparser.core.exception.MaltChainedException
public bool predictFromKBestList(FeatureModel featureModel, ComplexDecisionAction decision)
{
predict(featureModel, decision, false);
if (decision.numberOfDecisions() == 1)
{
return(decision.getSingleDecision(0).updateFromKBestList());
}
else if (decision.numberOfDecisions() > 2)
{
throw new MaltChainedException("Number of decisions is greater than two, which is unsupported in the light-weight parser (lw.parser)");
}
bool success = false;
if (decision.getSingleDecision(0).continueWithNextDecision())
{
success = decision.getSingleDecision(1).updateFromKBestList();
}
return(success);
}
//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: public LWDeterministicParser(LWSingleMalt lwSingleMalt, org.maltparser.core.symbol.SymbolTableHandler symbolTableHandler) throws org.maltparser.core.exception.MaltChainedException
public LWDeterministicParser(LWSingleMalt lwSingleMalt, SymbolTableHandler symbolTableHandler)
{
manager = lwSingleMalt;
registry = new ParserRegistry();
registry.SymbolTableHandler = symbolTableHandler;
registry.DataFormatInstance = manager.DataFormatInstance;
registry.setAbstractParserFeatureFactory(manager.ParserFactory);
registry.Algorithm = this;
transitionSystem = manager.ParserFactory.makeTransitionSystem();
transitionSystem.initTableHandlers(lwSingleMalt.DecisionSettings, symbolTableHandler);
tableHandlers = transitionSystem.TableHandlers;
kBestSize = lwSingleMalt.getkBestSize();
decisionTables = new List <TableContainer>();
actionTables = new List <TableContainer>();
initDecisionSettings(lwSingleMalt.DecisionSettings, lwSingleMalt.Classitem_separator);
transitionSystem.initTransitionSystem(this);
config = manager.ParserFactory.makeParserConfiguration();
featureModel = manager.FeatureModelManager.getFeatureModel(lwSingleMalt.FeatureModelURL, 0, registry, manager.DataSplitColumn, manager.DataSplitStructure);
currentAction = new ComplexDecisionAction(this);
}
//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: public boolean predict(org.maltparser.core.feature.FeatureModel featureModel, org.maltparser.parser.history.action.ComplexDecisionAction decision, boolean one_prediction) throws org.maltparser.core.exception.MaltChainedException
public bool predict(FeatureModel featureModel, ComplexDecisionAction decision, bool one_prediction)
{
if (decision.numberOfDecisions() > 2)
{
throw new MaltChainedException("Number of decisions is greater than two, which is unsupported in the light-weight parser (lw.parser)");
}
featureModel.update();
bool success = true;
for (int i = 0; i < decision.numberOfDecisions(); i++)
{
LWClassifier classifier = null;
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final org.maltparser.parser.history.action.SingleDecision singleDecision = decision.getSingleDecision(i);
SingleDecision singleDecision = decision.getSingleDecision(i);
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final StringBuilder classifierString = new StringBuilder();
StringBuilder classifierString = new StringBuilder();
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final StringBuilder decisionModelString = new StringBuilder();
StringBuilder decisionModelString = new StringBuilder();
if (singleDecision.RelationToNextDecision == RelationToNextDecision.BRANCHED)
{
decisionModelString.Append("bdm");
}
else if (singleDecision.RelationToNextDecision == RelationToNextDecision.SEQUANTIAL)
{
decisionModelString.Append("sdm");
}
else
{
decisionModelString.Append("odm");
}
decisionModelString.Append(i);
string decisionSymbol = "";
if (i == 1 && singleDecision.RelationToNextDecision == RelationToNextDecision.BRANCHED)
{
decisionSymbol = singleDecision.DecisionSymbol;
decisionModelString.Append(decisionSymbol);
}
decisionModelString.Append('.');
FeatureVector featureVector = featureModel.getFeatureVector(decisionSymbol, singleDecision.TableContainer.TableContainerName);
if (featureModel.hasDivideFeatureFunction())
{
SingleFeatureValue featureValue = (SingleFeatureValue)featureModel.DivideFeatureFunction.FeatureValue;
classifierString.Append(decisionModelString);
classifierString.Append(string.Format("{0:D3}", featureValue.IndexCode));
classifierString.Append('.');
classifierString.Append(classifierName);
classifier = classifiers[classifierString.ToString()];
if (classifier != null)
{
FeatureVector dividefeatureVector = featureModel.getFeatureVector("/" + featureVector.SpecSubModel.SubModelName);
success = classifier.predict(dividefeatureVector, singleDecision, one_prediction) && success;
continue;
}
classifierString.Length = 0;
}
classifierString.Append(decisionModelString);
classifierString.Append(classifierName);
classifier = classifiers[classifierString.ToString()];
if (classifier != null)
{
success = classifier.predict(featureVector, singleDecision, one_prediction) && success;
}
else
{
singleDecision.addDecision(1);
}
if (!singleDecision.continueWithNextDecision())
{
break;
}
}
return(success);
}