Merge pull request #2 from mengxr/isotonic-fix-java

fix java tests

Author: zapletal-martin

mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala

@@ -75,7 +75,7 @@ class IsotonicRegressionModel (
    * @return Predicted labels.
    */
   def predict(testData: JavaDoubleRDD): JavaDoubleRDD = {
-    JavaDoubleRDD.fromRDD(predict(testData.rdd.asInstanceOf[RDD[Double]]))
+    JavaDoubleRDD.fromRDD(predict(testData.rdd.retag.asInstanceOf[RDD[Double]]))
   }
 
   /**
@@ -194,7 +194,7 @@ class IsotonicRegression private (private var isotonic: Boolean) extends Seriali
    * @return Isotonic regression model.
    */
   def run(input: JavaRDD[(JDouble, JDouble, JDouble)]): IsotonicRegressionModel = {
-    run(input.rdd.asInstanceOf[RDD[(Double, Double, Double)]])
+    run(input.rdd.retag.asInstanceOf[RDD[(Double, Double, Double)]])
   }
 
   /**

mllib/src/test/java/org/apache/spark/mllib/regression/JavaIsotonicRegressionSuite.java

@@ -18,48 +18,36 @@
 package org.apache.spark.mllib.regression;
 
 import java.io.Serializable;
-import java.util.ArrayList;
-import java.util.Arrays;
 import java.util.List;
 
-import org.apache.spark.api.java.JavaDoubleRDD;
 import scala.Tuple3;
 
+import com.google.common.collect.Lists;
 import org.junit.After;
 import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
+import org.apache.spark.api.java.JavaDoubleRDD;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 
 public class JavaIsotonicRegressionSuite implements Serializable {
   private transient JavaSparkContext sc;
 
   private List<Tuple3<Double, Double, Double>> generateIsotonicInput(double[] labels) {
-    List<Tuple3<Double, Double, Double>> input = new ArrayList<>();
+    List<Tuple3<Double, Double, Double>> input = Lists.newArrayList();
 
-    for(int i = 1; i <= labels.length; i++) {
-      input.add(new Tuple3(labels[i-1], (double)i, 1d));
+    for (int i = 1; i <= labels.length; i++) {
+      input.add(new Tuple3<Double, Double, Double>(labels[i-1], (double) i, 1d));
     }
 
     return input;
   }
 
-  private double difference(List<Tuple3<Double, Double, Double>> expected, IsotonicRegressionModel model) {
-    double diff = 0;
-
-    for(int i = 0; i < model.predictions().length; i++) {
-      Tuple3<Double, Double, Double> exp = expected.get(i);
-      diff += Math.abs(model.predict(exp._2()) - exp._1());
-    }
-
-    return diff;
-  }
-
   private IsotonicRegressionModel runIsotonicRegression(double[] labels) {
     JavaRDD<Tuple3<Double, Double, Double>> trainRDD =
-      sc.parallelize(generateIsotonicInput(labels)).cache();
+      sc.parallelize(generateIsotonicInput(labels), 2).cache();
 
     return new IsotonicRegression().run(trainRDD);
   }
@@ -80,20 +68,16 @@ public void testIsotonicRegressionJavaRDD() {
     IsotonicRegressionModel model =
       runIsotonicRegression(new double[]{1, 2, 3, 3, 1, 6, 7, 8, 11, 9, 10, 12});
 
-    List<Tuple3<Double, Double, Double>> expected =
-      generateIsotonicInput(new double[] {1, 2, 7d/3, 7d/3, 7d/3, 6, 7, 8, 10, 10, 10, 12});
-
-    Assert.assertTrue(difference(expected, model) == 0);
+    Assert.assertArrayEquals(
+      new double[] {1, 2, 7d/3, 7d/3, 6, 7, 8, 10, 10, 12}, model.predictions(), 1e-14);
   }
 
   @Test
   public void testIsotonicRegressionPredictionsJavaRDD() {
     IsotonicRegressionModel model =
       runIsotonicRegression(new double[]{1, 2, 3, 3, 1, 6, 7, 8, 11, 9, 10, 12});
 
-    JavaDoubleRDD testRDD =
-      sc.parallelizeDoubles(Arrays.asList(new Double[] {0.0, 1.0, 9.5, 12.0, 13.0}));
-
+    JavaDoubleRDD testRDD = sc.parallelizeDoubles(Lists.newArrayList(0.0, 1.0, 9.5, 12.0, 13.0));
     List<Double> predictions = model.predict(testRDD).collect();
 
     Assert.assertTrue(predictions.get(0) == 1d);
@@ -102,4 +86,4 @@ public void testIsotonicRegressionPredictionsJavaRDD() {
     Assert.assertTrue(predictions.get(3) == 12d);
     Assert.assertTrue(predictions.get(4) == 12d);
   }
-}
+}