/*
 * 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.disambiguator;

import static org.junit.Assert.*;

import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

import opennlp.tools.util.ObjectStream;
import org.junit.BeforeClass;
import org.junit.Test;

import opennlp.tools.disambiguator.datareader.SemcorReaderExtended;
import opennlp.tools.util.Span;
import opennlp.tools.util.TrainingParameters;

/**
 * This is the test class for {@link WSDisambiguatorME}.
 * <p/>
 * The scope of this test is to make sure that the WSDisambiguatorME code can be
 * executed. This test can not detect mistakes which lead to incorrect feature
 * generation or other mistakes which decrease the disambiguation performance of
 * the disambiguator.
 * <p/>
 * In this test the {@link WSDisambiguatorME} is trained with Semcor
 * and then the computed model is used to predict sentences
 * from the training sentences.
 */

public class WSDTester {
  // TODO write more tests
  // TODO modify when we fix the parameter model

  static String modelsDir = "src/test/resources/models/";
  static String trainingDataDirectory = "src/test/resources/supervised/models/";

  static WSDDefaultParameters params;
  static WSDisambiguatorME wsdME;
  static WSDModel model;

  static String test = "please.v";
  static File outFile;

  static String test1 = "We need to discuss an important topic, please write to me soon.";
  static String test2 = "The component was highly radioactive to the point that"
    + " it has been activated the second it touched water";
  static String test3 = "The summer is almost over and I did not go to the beach even once";

  static String[] sentence1;
  static String[] sentence2;
  static String[] sentence3;

  static String[] tags1;
  static String[] tags2;
  static String[] tags3;

  static String[] lemmas1;
  static String[] lemmas2;
  static String[] lemmas3;

  /*
   * Setup the testing variables
   */
  @BeforeClass public static void setUpAndTraining() {
    WSDHelper.loadTokenizer(modelsDir + "en-token.bin");
    WSDHelper.loadLemmatizer(modelsDir + "en-lemmatizer.dict");
    WSDHelper.loadTagger(modelsDir + "en-pos-maxent.bin");

    sentence1 = WSDHelper.getTokenizer().tokenize(test1);
    sentence2 = WSDHelper.getTokenizer().tokenize(test2);
    sentence3 = WSDHelper.getTokenizer().tokenize(test3);

    tags1 = WSDHelper.getTagger().tag(sentence1);
    tags2 = WSDHelper.getTagger().tag(sentence2);
    tags3 = WSDHelper.getTagger().tag(sentence3);

    List<String> tempLemmas1 = new ArrayList<String>();
    for (int i = 0; i < sentence1.length; i++) {
      tempLemmas1
        .add(WSDHelper.getLemmatizer().lemmatize(sentence1[i], tags1[i]));
    }
    lemmas1 = tempLemmas1.toArray(new String[tempLemmas1.size()]);

    List<String> tempLemmas2 = new ArrayList<String>();
    for (int i = 0; i < sentence2.length; i++) {
      tempLemmas2
        .add(WSDHelper.getLemmatizer().lemmatize(sentence2[i], tags2[i]));
    }
    lemmas2 = tempLemmas2.toArray(new String[tempLemmas2.size()]);

    List<String> tempLemmas3 = new ArrayList<String>();
    for (int i = 0; i < sentence3.length; i++) {
      tempLemmas3
        .add(WSDHelper.getLemmatizer().lemmatize(sentence3[i], tags3[i]));
    }
    lemmas3 = tempLemmas3.toArray(new String[tempLemmas3.size()]);

    params = new WSDDefaultParameters("");
    params.setTrainingDataDirectory(trainingDataDirectory);
    TrainingParameters trainingParams = new TrainingParameters();
    SemcorReaderExtended sr = new SemcorReaderExtended();
    ObjectStream<WSDSample> sampleStream = sr.getSemcorDataStream(test);

    WSDModel writeModel = null;
    /*
     * Tests training the disambiguator We test both writing and reading a model
     * file trained by semcor
     */

    try {
      writeModel = WSDisambiguatorME
        .train("en", sampleStream, trainingParams, params);
      assertNotNull("Checking the model to be written", writeModel);
      writeModel.writeModel(params.getTrainingDataDirectory() + test);
      outFile = new File(
        params.getTrainingDataDirectory() + test + ".wsd.model");
      model = new WSDModel(outFile);
      assertNotNull("Checking the read model", model);
      wsdME = new WSDisambiguatorME(model, params);
      assertNotNull("Checking the disambiguator", wsdME);
    } catch (IOException e1) {
      e1.printStackTrace();
      fail("Exception in training");
    }
  }

  /*
   * Tests disambiguating only one word : The ambiguous word "please"
   */
  @Test public void testOneWordDisambiguation() {
    String sense = wsdME.disambiguate(sentence1, tags1, lemmas1, 8);
    assertEquals("Check 'please' sense ID", "WORDNET please%2:37:00::", sense);
  }

  /*
   * Tests disambiguating a word Span In this case we test a mix of monosemous
   * and polysemous words as well as words that do not need disambiguation such
   * as determiners
   */
  @Test public void testWordSpanDisambiguation() {
    Span span = new Span(3, 7);
    List<String> senses = wsdME.disambiguate(sentence2, tags2, lemmas2, span);

    assertEquals("Check number of returned words", 5, senses.size());
    assertEquals("Check 'highly' sense ID", "WORDNET highly%4:02:01::",
      senses.get(0));
    assertEquals("Check 'radioactive' sense ID",
      "WORDNET radioactive%3:00:00::", senses.get(1));
    assertEquals("Check preposition", "WSDHELPER to", senses.get(2));
    assertEquals("Check determiner", "WSDHELPER determiner", senses.get(3));
  }

  /*
   * Tests disambiguating all the words
   */
  @Test public void testAllWordsDisambiguation() {
    List<String> senses = wsdME.disambiguate(sentence3, tags3, lemmas3);

    assertEquals("Check number of returned words", 15, senses.size());
    assertEquals("Check preposition", "WSDHELPER personal pronoun",
      senses.get(6));
  }

}