/* (non-Javadoc)
* @see com.joliciel.talismane.maxent.MaxentObserver#onAnalyse(java.util.List, java.util.Collection)
*/
@Override
public void onAnalyse(
Object event, List<FeatureResult<?>> featureResults, Collection<Decision<T>> decisions) {
try {
Map<String, Double> outcomeTotals = new TreeMap<String, Double>();
for (String outcome : modelParams.getOutcomes()) outcomeTotals.put(outcome, 0.0);
writer.append("####### Event: " + event.toString() + "\n");
writer.append("### Feature results:\n");
for (FeatureResult<?> featureResult : featureResults) {
if (featureResult.getOutcome() instanceof List) {
@SuppressWarnings("unchecked")
FeatureResult<List<WeightedOutcome<String>>> stringCollectionResult =
(FeatureResult<List<WeightedOutcome<String>>>) featureResult;
for (WeightedOutcome<String> stringOutcome : stringCollectionResult.getOutcome()) {
String featureName =
featureResult.getTrainingName()
+ "|"
+ featureResult.getTrainingOutcome(stringOutcome.getOutcome());
String featureOutcome = stringOutcome.getOutcome();
double value = stringOutcome.getWeight();
this.writeFeatureResult(featureName, featureOutcome, value, outcomeTotals);
}
} else {
double value = 1.0;
if (featureResult.getFeature() instanceof DoubleFeature) {
value = (Double) featureResult.getOutcome();
}
this.writeFeatureResult(
featureResult.getTrainingName(),
featureResult.getOutcome().toString(),
value,
outcomeTotals);
}
}
List<Integer> featureIndexList = new ArrayList<Integer>();
List<Double> featureValueList = new ArrayList<Double>();
modelParams.prepareData(featureResults, featureIndexList, featureValueList);
double[] results = decisionMaker.predict(featureIndexList, featureValueList);
writer.append("### Outcome totals:\n");
writer.append(
String.format("%1$-30s", "outcome")
+ String.format("%1$#15s", "total")
+ String.format("%1$#15s", "normalised")
+ "\n");
int j = 0;
for (String outcome : modelParams.getOutcomes()) {
double total = outcomeTotals.get(outcome);
double normalised = results[j++];
writer.append(
String.format("%1$-30s", outcome)
+ String.format("%1$#15s", decFormat.format(total))
+ String.format("%1$#15s", decFormat.format(normalised))
+ "\n");
}
writer.append("\n");
Map<String, Double> outcomeWeights = new TreeMap<String, Double>();
for (Decision<T> decision : decisions) {
outcomeWeights.put(decision.getCode(), decision.getProbability());
}
writer.append("### Outcome list:\n");
Set<WeightedOutcome<String>> weightedOutcomes = new TreeSet<WeightedOutcome<String>>();
for (String outcome : modelParams.getOutcomes()) {
Double weightObj = outcomeWeights.get(outcome);
double weight = (weightObj == null ? 0.0 : weightObj.doubleValue());
WeightedOutcome<String> weightedOutcome = new WeightedOutcome<String>(outcome, weight);
weightedOutcomes.add(weightedOutcome);
}
for (WeightedOutcome<String> weightedOutcome : weightedOutcomes) {
writer.append(
String.format("%1$-30s", weightedOutcome.getOutcome())
+ String.format("%1$#15s", decFormat.format(weightedOutcome.getWeight()))
+ "\n");
}
writer.append("\n");
writer.flush();
} catch (IOException ioe) {
throw new RuntimeException(ioe);
}
}
@Test
public void testGetTokenSequence(@NonStrict final Sentence sentence) {
new NonStrictExpectations() {
{
sentence.getText();
returns("Je n'ai pas encore l'ourang-outan.");
}
};
TokeniserOutcome[] tokeniserOutcomeArray =
new TokeniserOutcome[] {
TokeniserOutcome.SEPARATE, // Je
TokeniserOutcome.SEPARATE, // _
TokeniserOutcome.SEPARATE, // n
TokeniserOutcome.JOIN, // '
TokeniserOutcome.SEPARATE, // ai
TokeniserOutcome.SEPARATE, // _
TokeniserOutcome.SEPARATE, // pas
TokeniserOutcome.JOIN, // _
TokeniserOutcome.JOIN, // encore
TokeniserOutcome.SEPARATE, // _
TokeniserOutcome.SEPARATE, // l
TokeniserOutcome.JOIN, // '
TokeniserOutcome.SEPARATE, // ourang
TokeniserOutcome.JOIN, // -
TokeniserOutcome.JOIN, // outan
TokeniserOutcome.SEPARATE // .
};
final TalismaneSession talismaneSession = TalismaneSession.getInstance("");
TokenisedAtomicTokenSequence atomicTokenSequence =
new TokenisedAtomicTokenSequence(sentence, talismaneSession);
TokenSequence tokenSequence =
new TokenSequence(sentence, Tokeniser.SEPARATORS, talismaneSession);
int i = 0;
for (Token token : tokenSequence.listWithWhiteSpace()) {
Decision decision = new Decision(tokeniserOutcomeArray[i++].name());
TaggedToken<TokeniserOutcome> taggedToken =
new TaggedToken<>(token, decision, TokeniserOutcome.valueOf(decision.getOutcome()));
atomicTokenSequence.add(taggedToken);
}
TokenSequence newTokenSequence = atomicTokenSequence.inferTokenSequence();
LOG.debug(newTokenSequence.toString());
i = 0;
for (Token token : newTokenSequence) {
if (i == 0) {
assertEquals("Je", token.getText());
} else if (i == 1) {
assertEquals("n'", token.getText());
} else if (i == 2) {
assertEquals("ai", token.getText());
} else if (i == 3) {
assertEquals("pas encore", token.getText());
} else if (i == 4) {
assertEquals("l'", token.getText());
} else if (i == 5) {
assertEquals("ourang-outan", token.getText());
} else if (i == 6) {
assertEquals(".", token.getText());
}
i++;
}
assertEquals(7, newTokenSequence.size());
}
