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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
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  package org.apache.spark.ml.feature;
  
  import java.util.Arrays;
  import java.util.List;
  
  import org.junit.Assert;
  import org.junit.Test;
  
  import org.apache.spark.SharedSparkSession;
  import org.apache.spark.ml.linalg.Vector;
  import org.apache.spark.ml.linalg.VectorUDT;
  import org.apache.spark.ml.linalg.Vectors;
  import org.apache.spark.sql.Dataset;
  import org.apache.spark.sql.Row;
  import org.apache.spark.sql.RowFactory;
  import org.apache.spark.sql.types.Metadata;
  import org.apache.spark.sql.types.StructField;
  import org.apache.spark.sql.types.StructType;
  
  public class JavaPolynomialExpansionSuite extends SharedSparkSession {
  
    @Test
    public void polynomialExpansionTest() {
      PolynomialExpansion polyExpansion = new PolynomialExpansion()
        .setInputCol("features")
        .setOutputCol("polyFeatures")
        .setDegree(3);
  
      List<Row> data = Arrays.asList(
        RowFactory.create(
          Vectors.dense(-2.0, 2.3),
          Vectors.dense(-2.0, 4.0, -8.0, 2.3, -4.6, 9.2, 5.29, -10.58, 12.17)
        ),
        RowFactory.create(Vectors.dense(0.0, 0.0), Vectors.dense(new double[9])),
        RowFactory.create(
          Vectors.dense(0.6, -1.1),
          Vectors.dense(0.6, 0.36, 0.216, -1.1, -0.66, -0.396, 1.21, 0.726, -1.331)
        )
      );
  
      StructType schema = new StructType(new StructField[]{
        new StructField("features", new VectorUDT(), false, Metadata.empty()),
        new StructField("expected", new VectorUDT(), false, Metadata.empty())
      });
  
      Dataset<Row> dataset = spark.createDataFrame(data, schema);
  
      List<Row> pairs = polyExpansion.transform(dataset)
        .select("polyFeatures", "expected")
        .collectAsList();
  
      for (Row r : pairs) {
        double[] polyFeatures = ((Vector) r.get(0)).toArray();
        double[] expected = ((Vector) r.get(1)).toArray();
        Assert.assertArrayEquals(polyFeatures, expected, 1e-1);
      }
    }
  }
  