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/*
 * 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 chalk.tools.tokenize;

import java.io.IOException;

import chalk.tools.dictionary.Dictionary;
import chalk.tools.util.ObjectStream;
import chalk.tools.util.TrainingParameters;
import chalk.tools.util.eval.CrossValidationPartitioner;
import chalk.tools.util.eval.FMeasure;
import chalk.tools.util.model.ModelUtil;


public class TokenizerCrossValidator {
  
  private final TrainingParameters params;
  
  private FMeasure fmeasure = new FMeasure();
  private TokenizerEvaluationMonitor[] listeners;
  private final TokenizerFactory factory;
  
  public TokenizerCrossValidator(TrainingParameters params,
      TokenizerFactory factory, TokenizerEvaluationMonitor... listeners) {
    this.params = params;
    this.listeners = listeners;
    this.factory = factory;
  }

  /**
   * @deprecated use
   *             {@link #TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...)}
   *             instead and pass in a {@link TokenizerFactory}
   */
  public TokenizerCrossValidator(String language, Dictionary abbreviations,
      boolean alphaNumericOptimization, TrainingParameters params,
      TokenizerEvaluationMonitor ... listeners) {
    this(params, new TokenizerFactory(language, abbreviations,
        alphaNumericOptimization, null), listeners);
  }
  
  /**
   * @deprecated use
   *             {@link #TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...)}
   *             instead and pass in a {@link TokenizerFactory}
   */
  public TokenizerCrossValidator(String language, boolean alphaNumericOptimization, int cutoff, int iterations) {
    this(language, alphaNumericOptimization, ModelUtil.createTrainingParameters(iterations, cutoff));
  }
  
  /**
   * @deprecated use
   *             {@link #TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...)}
   *             instead and pass in a {@link TokenizerFactory}
   */
  public TokenizerCrossValidator(String language, boolean alphaNumericOptimization) {
    this(language, alphaNumericOptimization, ModelUtil.createTrainingParameters(100, 5));
  }
  
  /**
   * @deprecated use
   *             {@link #TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...)}
   *             instead and pass in a {@link TokenizerFactory}
   */
  public TokenizerCrossValidator(String language,
      boolean alphaNumericOptimization, TrainingParameters params,
      TokenizerEvaluationMonitor ... listeners) {
    this(language, null, alphaNumericOptimization, params, listeners);
  }


  /**
   * Starts the evaluation.
   * 
   * @param samples
   *          the data to train and test
   * @param nFolds
   *          number of folds
   * 
   * @throws IOException
   */
  public void evaluate(ObjectStream samples, int nFolds) throws IOException {
    
    CrossValidationPartitioner partitioner = 
      new CrossValidationPartitioner(samples, nFolds);
  
     while (partitioner.hasNext()) {
       
       CrossValidationPartitioner.TrainingSampleStream trainingSampleStream =
         partitioner.next();
       
       // Maybe throws IOException if temporary file handling fails ...
       TokenizerModel model;
       
      model = TokenizerME.train(trainingSampleStream, this.factory, params);
       
       TokenizerEvaluator evaluator = new TokenizerEvaluator(new TokenizerME(model), listeners);
       
       evaluator.evaluate(trainingSampleStream.getTestSampleStream());
       fmeasure.mergeInto(evaluator.getFMeasure());
     }
  }
  
  public FMeasure getFMeasure() {
    return fmeasure;
  }
}