opennlp-ml/src/test/java/org/apache/opennlp/ml/PrepAttachDataUtil.java

/*
 * 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 org.apache.opennlp.ml;

import static org.junit.Assert.assertEquals;

import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.List;

import org.apache.opennlp.ml.model.AbstractModel;
import org.apache.opennlp.ml.model.Event;
import org.apache.opennlp.ml.model.EventStream;
import org.apache.opennlp.ml.model.ListEventStream;
import org.apache.opennlp.ml.perceptron.PerceptronPrepAttachTest;


public class PrepAttachDataUtil {

  private static List<Event> readPpaFile(String filename) throws IOException {

    List<Event> events = new ArrayList<Event>();

    InputStream in = PerceptronPrepAttachTest.class.getResourceAsStream("/data/ppa/" +
        filename);
    
    try {
      BufferedReader reader = new BufferedReader(new InputStreamReader(in, "UTF-8"));
      String line;
      while ((line = reader.readLine()) != null) {
        String[] items = line.split("\\s+");
        String label = items[5];
        String[] context = { "verb=" + items[1], "noun=" + items[2],
            "prep=" + items[3], "prep_obj=" + items[4] };
        events.add(new Event(label, context));
      }
    }
    finally {
      in.close();
    }
    
    return events;
  }
  
  public static EventStream createTrainingStream() throws IOException {
    List<Event> trainingEvents = readPpaFile("training");

    EventStream trainingStream = new ListEventStream(trainingEvents);
    
    return trainingStream;
  }
  
  public static void testModel(AbstractModel model, double expecedAccuracy) throws IOException {

    List<Event> devEvents = readPpaFile("devset");

    int total = 0;
    int correct = 0;
    for (Event ev: devEvents) {
      String targetLabel = ev.getOutcome();
      double[] ocs = model.eval(ev.getContext());

      int best = 0;
      for (int i=1; i<ocs.length; i++)
        if (ocs[i] > ocs[best])
          best = i;

      String predictedLabel = model.getOutcome(best);

      if (targetLabel.equals(predictedLabel))
        correct++;
      total++;
    }

    double accuracy = correct/(double)total;
    System.out.println("Accuracy on PPA devset: (" + correct + "/" + total + ") " + accuracy);

    assertEquals(expecedAccuracy, accuracy, .00001);
  }
}