opennlp.tools.chunker.ChunkerEventStream Maven / Gradle / Ivy
/*
* 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.chunker;
import java.io.IOException;
import opennlp.model.Event;
import opennlp.tools.util.ObjectStream;
/**
* Class for creating an event stream out of data files for training a chunker.
*/
public class ChunkerEventStream extends opennlp.model.AbstractEventStream {
private ChunkerContextGenerator cg;
private ObjectStream data;
private Event[] events;
private int ei;
/**
* Creates a new event stream based on the specified data stream using the specified context generator.
* @param d The data stream for this event stream.
* @param cg The context generator which should be used in the creation of events for this event stream.
*/
public ChunkerEventStream(ObjectStream d, ChunkerContextGenerator cg) {
this.cg = cg;
data = d;
ei = 0;
addNewEvents();
}
/**
* Creates a new event stream based on the specified data stream.
* @param d The data stream for this event stream.
*/
public ChunkerEventStream(ObjectStream d) {
this(d, new DefaultChunkerContextGenerator());
}
public Event next() {
hasNext();
return events[ei++];
}
public boolean hasNext() {
if (ei == events.length) {
addNewEvents();
ei = 0;
}
return ei < events.length;
}
private void addNewEvents() {
ChunkSample sample;
try {
sample = data.read();
} catch (IOException e) {
throw new RuntimeException(e);
}
if (sample != null) {
events = new Event[sample.getSentence().length];
String[] toksArray = sample.getSentence();
String[] tagsArray = sample.getTags();
String[] predsArray = sample.getPreds();
for (int ei = 0, el = events.length; ei < el; ei++) {
events[ei] = new Event(predsArray[ei], cg.getContext(ei,toksArray,tagsArray,predsArray));
}
}
else {
events = new Event[0];
}
}
}