/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package opennlp.tools.namefind;
import java.io.IOException;
import java.util.Collections;
import opennlp.tools.ml.model.AbstractModel;
import opennlp.tools.ml.model.Event;
import opennlp.tools.ml.model.Sequence;
import opennlp.tools.ml.model.SequenceStream;
import opennlp.tools.util.ObjectStream;
import opennlp.tools.util.SequenceCodec;
import opennlp.tools.util.featuregen.AdaptiveFeatureGenerator;
public class NameSampleSequenceStream implements SequenceStream {
private NameContextGenerator pcg;
private final boolean useOutcomes;
private ObjectStream<NameSample> psi;
private SequenceCodec<String> seqCodec;
public NameSampleSequenceStream(ObjectStream<NameSample> psi) throws IOException {
this(psi, new DefaultNameContextGenerator((AdaptiveFeatureGenerator) null), true);
}
public NameSampleSequenceStream(ObjectStream<NameSample> psi, AdaptiveFeatureGenerator featureGen)
throws IOException {
this(psi, new DefaultNameContextGenerator(featureGen), true);
}
public NameSampleSequenceStream(ObjectStream<NameSample> psi, AdaptiveFeatureGenerator featureGen, boolean useOutcomes)
throws IOException {
this(psi, new DefaultNameContextGenerator(featureGen), useOutcomes);
}
public NameSampleSequenceStream(ObjectStream<NameSample> psi, NameContextGenerator pcg)
throws IOException {
this(psi, pcg, true);
}
public NameSampleSequenceStream(ObjectStream<NameSample> psi, NameContextGenerator pcg, boolean useOutcomes)
throws IOException {
this(psi, pcg, useOutcomes, new BioCodec());
}
public NameSampleSequenceStream(ObjectStream<NameSample> psi, NameContextGenerator pcg, boolean useOutcomes,
SequenceCodec<String> seqCodec)
throws IOException {
this.psi = psi;
this.useOutcomes = useOutcomes;
this.pcg = pcg;
this.seqCodec = seqCodec;
}
@SuppressWarnings("unchecked")
public Event[] updateContext(Sequence sequence, AbstractModel model) {
Sequence<NameSample> pss = sequence;
TokenNameFinder tagger = new NameFinderME(new TokenNameFinderModel("x-unspecified", model, Collections.<String, Object>emptyMap(), null));
String[] sentence = pss.getSource().getSentence();
String[] tags = seqCodec.encode(tagger.find(sentence), sentence.length);
Event[] events = new Event[sentence.length];
NameFinderEventStream.generateEvents(sentence,tags,pcg).toArray(events);
return events;
}
@Override
public Sequence read() throws IOException {
NameSample sample = psi.read();
if (sample != null) {
String sentence[] = sample.getSentence();
String tags[] = seqCodec.encode(sample.getNames(), sentence.length);
Event[] events = new Event[sentence.length];
for (int i=0; i < sentence.length; i++) {
// it is safe to pass the tags as previous tags because
// the context generator does not look for non predicted tags
String[] context;
if (useOutcomes) {
context = pcg.getContext(i, sentence, tags, null);
}
else {
context = pcg.getContext(i, sentence, null, null);
}
events[i] = new Event(tags[i], context);
}
Sequence<NameSample> sequence = new Sequence<NameSample>(events,sample);
return sequence;
}
else {
return null;
}
}
@Override
public void reset() throws IOException, UnsupportedOperationException {
psi.reset();
}
@Override
public void close() throws IOException {
psi.close();
}
}