content: /*
   * 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.spark.mllib.regression;
  
  import java.util.ArrayList;
  import java.util.Arrays;
  import java.util.List;
  
  import scala.Tuple3;
  
  import org.junit.Assert;
  import org.junit.Test;
  
  import org.apache.spark.SharedSparkSession;
  import org.apache.spark.api.java.JavaDoubleRDD;
  import org.apache.spark.api.java.JavaRDD;
  
  public class JavaIsotonicRegressionSuite extends SharedSparkSession {
  
    private static List<Tuple3<Double, Double, Double>> generateIsotonicInput(double[] labels) {
      List<Tuple3<Double, Double, Double>> input = new ArrayList<>(labels.length);
  
      for (int i = 1; i <= labels.length; i++) {
        input.add(new Tuple3<>(labels[i - 1], (double) i, 1.0));
      }
  
      return input;
    }
  
    private IsotonicRegressionModel runIsotonicRegression(double[] labels) {
      JavaRDD<Tuple3<Double, Double, Double>> trainRDD =
        jsc.parallelize(generateIsotonicInput(labels), 2).cache();
  
      return new IsotonicRegression().run(trainRDD);
    }
  
    @Test
    public void testIsotonicRegressionJavaRDD() {
      IsotonicRegressionModel model =
        runIsotonicRegression(new double[]{1, 2, 3, 3, 1, 6, 7, 8, 11, 9, 10, 12});
  
      Assert.assertArrayEquals(
        new double[]{1, 2, 7.0 / 3, 7.0 / 3, 6, 7, 8, 10, 10, 12}, model.predictions(), 1.0e-14);
    }
  
    @Test
    public void testIsotonicRegressionPredictionsJavaRDD() {
      IsotonicRegressionModel model =
        runIsotonicRegression(new double[]{1, 2, 3, 3, 1, 6, 7, 8, 11, 9, 10, 12});
  
      JavaDoubleRDD testRDD = jsc.parallelizeDoubles(Arrays.asList(0.0, 1.0, 9.5, 12.0, 13.0));
      List<Double> predictions = model.predict(testRDD).collect();
  
      Assert.assertEquals(1.0, predictions.get(0).doubleValue(), 1.0e-14);
      Assert.assertEquals(1.0, predictions.get(1).doubleValue(), 1.0e-14);
      Assert.assertEquals(10.0, predictions.get(2).doubleValue(), 1.0e-14);
      Assert.assertEquals(12.0, predictions.get(3).doubleValue(), 1.0e-14);
      Assert.assertEquals(12.0, predictions.get(4).doubleValue(), 1.0e-14);
    }
  }
  