/*
 * 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.utils;

import java.util.ArrayList;
import java.util.Collection;
import java.util.Random;
import org.junit.Ignore;

/**
 * Utility class for tests
 */
@Ignore
public class TestUtils {

  private static Random r = new Random();

  public static void fillTrainingSet(TrainingSet trainingSet, int size, int dimension) {
    for (int i = 0; i < size; i++) {
      double[] inputs = new double[dimension];
      for (int j = 0; j < dimension; j++) {
        inputs[j] = Math.random();
      }
      double out = Math.random();
      trainingSet.add(new TrainingExample(inputs, out));
    }
  }

  public static Collection<String[]> generateRandomVocabulary() {
    int size = r.nextInt(1000);
    Collection<String[]> vocabulary = new ArrayList<String[]>(size);
    for (int i = 0; i < size; i++) {
      String[] sentence = generateRandomSentence();
      vocabulary.add(sentence);
    }
    return vocabulary;
  }

  public static String[] generateRandomSentence() {
    int dimension = r.nextInt(10);
    String[] sentence = new String[dimension];
    for (int j = 0; j < dimension; j++) {
      char c = (char) r.nextInt(10);
      sentence[j] = c + "-" + c + "-" + c;
    }
    return sentence;
  }
}