/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreemnets. 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.postag;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import opennlp.model.AbstractModel;
import opennlp.model.Event;
import opennlp.model.Sequence;
import opennlp.model.SequenceStream;
import opennlp.tools.util.ObjectStream;
public class POSSampleSequenceStream implements SequenceStream {
private POSContextGenerator pcg;
private List<POSSample> samples;
public POSSampleSequenceStream(ObjectStream<POSSample> psi) throws IOException {
this(psi, new DefaultPOSContextGenerator(null));
}
public POSSampleSequenceStream(ObjectStream<POSSample> psi, POSContextGenerator pcg)
throws IOException {
samples = new ArrayList<POSSample>();
POSSample sample;
while((sample = psi.read()) != null) {
samples.add(sample);
}
System.err.println("Got "+samples.size()+" sequences");
this.pcg = pcg;
}
@SuppressWarnings("unchecked")
public Event[] updateContext(Sequence sequence, AbstractModel model) {
Sequence<POSSample> pss = sequence;
POSTagger tagger = new POSTaggerME(new POSModel("x-unspecified", model, null, null));
String[] sentence = pss.getSource().getSentence();
String[] tags = tagger.tag(pss.getSource().getSentence());
Event[] events = new Event[sentence.length];
POSSampleEventStream.generateEvents(sentence,tags,pcg).toArray(events);
return events;
}
@SuppressWarnings("unchecked")
public Iterator<Sequence> iterator() {
return new POSSampleSequenceIterator(samples.iterator());
}
}
class POSSampleSequenceIterator implements Iterator<Sequence> {
private Iterator<POSSample> psi;
private POSContextGenerator cg;
public POSSampleSequenceIterator(Iterator<POSSample> psi) {
this.psi = psi;
cg = new DefaultPOSContextGenerator(null);
}
public boolean hasNext() {
return psi.hasNext();
}
public Sequence<POSSample> next() {
POSSample sample = psi.next();
String sentence[] = sample.getSentence();
String tags[] = sample.getTags();
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 = cg.getContext(i, sentence, tags, null);
events[i] = new Event(tags[i], context);
}
Sequence<POSSample> sequence = new Sequence<POSSample>(events,sample);
return sequence;
}
public void remove() {
throw new UnsupportedOperationException();
}
}