/*
 * 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.formats.convert;

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

import opennlp.tools.sentdetect.SentenceSample;
import opennlp.tools.tokenize.Detokenizer;
import opennlp.tools.util.FilterObjectStream;
import opennlp.tools.util.ObjectStream;

public abstract class AbstractToSentenceSampleStream<T> extends
    FilterObjectStream<T, SentenceSample> {

  private final Detokenizer detokenizer;

  private final int chunkSize;

  AbstractToSentenceSampleStream(Detokenizer detokenizer,
      ObjectStream<T> samples, int chunkSize) {
    super(samples);

    this.detokenizer = Objects.requireNonNull(detokenizer, "detokenizer must not be null");

    if (chunkSize < 0) {
      throw new IllegalArgumentException("chunkSize must be zero or larger but was " + chunkSize + "!");
    }

    if (chunkSize > 0) {
      this.chunkSize = chunkSize;
    }
    else {
      this.chunkSize = Integer.MAX_VALUE;
    }
  }

  protected abstract String[] toSentence(T sample);

  public SentenceSample read() throws IOException {
    List<String[]> sentences = new ArrayList<>();

    T posSample;
    int chunks = 0;
    while ((posSample = samples.read()) != null && chunks < chunkSize) {
      sentences.add(toSentence(posSample));
      chunks++;
    }

    if (sentences.size() > 0) {
      return new SentenceSample(detokenizer,
          sentences.toArray(new String[sentences.size()][]));
    }
    else if (posSample != null) {
      return read(); // filter out empty line
    }

    return null; // last sample was read
  }
}