ml/feature/JavaPolynomialExpansionSuite.java

0001 /*
0002  * Licensed to the Apache Software Foundation (ASF) under one or more
0003  * contributor license agreements.  See the NOTICE file distributed with
0004  * this work for additional information regarding copyright ownership.
0005  * The ASF licenses this file to You under the Apache License, Version 2.0
0006  * (the "License"); you may not use this file except in compliance with
0007  * the License.  You may obtain a copy of the License at
0008  *
0009  *    http://www.apache.org/licenses/LICENSE-2.0
0010  *
0011  * Unless required by applicable law or agreed to in writing, software
0012  * distributed under the License is distributed on an "AS IS" BASIS,
0013  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014  * See the License for the specific language governing permissions and
0015  * limitations under the License.
0016  */
0017
0018 package org.apache.spark.ml.feature;
0019
0020 import java.util.Arrays;
0021 import java.util.List;
0022
0023 import org.junit.Assert;
0024 import org.junit.Test;
0025
0026 import org.apache.spark.SharedSparkSession;
0027 import org.apache.spark.ml.linalg.Vector;
0028 import org.apache.spark.ml.linalg.VectorUDT;
0029 import org.apache.spark.ml.linalg.Vectors;
0030 import org.apache.spark.sql.Dataset;
0031 import org.apache.spark.sql.Row;
0032 import org.apache.spark.sql.RowFactory;
0033 import org.apache.spark.sql.types.Metadata;
0034 import org.apache.spark.sql.types.StructField;
0035 import org.apache.spark.sql.types.StructType;
0036
0037 public class JavaPolynomialExpansionSuite extends SharedSparkSession {
0038
0039   @Test
0040   public void polynomialExpansionTest() {
0041     PolynomialExpansion polyExpansion = new PolynomialExpansion()
0042       .setInputCol("features")
0043       .setOutputCol("polyFeatures")
0044       .setDegree(3);
0045
0046     List<Row> data = Arrays.asList(
0047       RowFactory.create(
0048         Vectors.dense(-2.0, 2.3),
0049         Vectors.dense(-2.0, 4.0, -8.0, 2.3, -4.6, 9.2, 5.29, -10.58, 12.17)
0050       ),
0051       RowFactory.create(Vectors.dense(0.0, 0.0), Vectors.dense(new double[9])),
0052       RowFactory.create(
0053         Vectors.dense(0.6, -1.1),
0054         Vectors.dense(0.6, 0.36, 0.216, -1.1, -0.66, -0.396, 1.21, 0.726, -1.331)
0055       )
0056     );
0057
0058     StructType schema = new StructType(new StructField[]{
0059       new StructField("features", new VectorUDT(), false, Metadata.empty()),
0060       new StructField("expected", new VectorUDT(), false, Metadata.empty())
0061     });
0062
0063     Dataset<Row> dataset = spark.createDataFrame(data, schema);
0064
0065     List<Row> pairs = polyExpansion.transform(dataset)
0066       .select("polyFeatures", "expected")
0067       .collectAsList();
0068
0069     for (Row r : pairs) {
0070       double[] polyFeatures = ((Vector) r.get(0)).toArray();
0071       double[] expected = ((Vector) r.get(1)).toArray();
0072       Assert.assertArrayEquals(polyFeatures, expected, 1e-1);
0073     }
0074   }
0075 }