Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/15770#discussion_r178992899
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/clustering/PowerIterationClusteringSuite.scala
---
@@ -0,0 +1,171 @@
+/*
+ * 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.ml.clustering
+
+import scala.collection.mutable
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
+import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.mllib.util.MLlibTestSparkContext
+import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession}
+
+class PowerIterationClusteringSuite extends SparkFunSuite
+ with MLlibTestSparkContext with DefaultReadWriteTest {
+
+ @transient var data: Dataset[_] = _
+ @transient var malData: Dataset[_] = _
+ final val r1 = 1.0
+ final val n1 = 10
+ final val r2 = 4.0
+ final val n2 = 40
+
+ override def beforeAll(): Unit = {
+ super.beforeAll()
+
+ data = PowerIterationClusteringSuite.generatePICData(spark, r1, r2,
n1, n2)
+ }
+
+ test("default parameters") {
+ val pic = new PowerIterationClustering()
+
+ assert(pic.getK === 2)
+ assert(pic.getMaxIter === 20)
+ assert(pic.getInitMode === "random")
+ assert(pic.getFeaturesCol === "features")
+ assert(pic.getPredictionCol === "prediction")
+ assert(pic.getIdCol === "id")
+ assert(pic.getWeightCol === "weight")
+ assert(pic.getNeighborCol === "neighbor")
+ }
+
+ test("set parameters") {
+ val pic = new PowerIterationClustering()
+ .setK(9)
+ .setMaxIter(33)
+ .setInitMode("degree")
+ .setFeaturesCol("test_feature")
+ .setPredictionCol("test_prediction")
+ .setIdCol("test_id")
+ .setWeightCol("test_weight")
+ .setNeighborCol("test_neighbor")
+
+ assert(pic.getK === 9)
+ assert(pic.getMaxIter === 33)
+ assert(pic.getInitMode === "degree")
+ assert(pic.getFeaturesCol === "test_feature")
+ assert(pic.getPredictionCol === "test_prediction")
+ assert(pic.getIdCol === "test_id")
+ assert(pic.getWeightCol === "test_weight")
+ assert(pic.getNeighborCol === "test_neighbor")
+ }
+
+ test("parameters validation") {
+ intercept[IllegalArgumentException] {
+ new PowerIterationClustering().setK(1)
+ }
+ intercept[IllegalArgumentException] {
+ new PowerIterationClustering().setInitMode("no_such_a_mode")
+ }
+ }
+
+ test("power iteration clustering") {
+ val n = n1 + n2
+
+ val model = new PowerIterationClustering()
+ .setK(2)
+ .setMaxIter(40)
+ val result = model.transform(data)
+
+ val predictions = Array.fill(2)(mutable.Set.empty[Long])
+ result.select("id", "prediction").collect().foreach {
+ case Row(id: Long, cluster: Integer) => predictions(cluster) += id
+ }
+ assert(predictions.toSet == Set((1 until n1).toSet, (n1 until
n).toSet))
+
+ val result2 = new PowerIterationClustering()
+ .setK(2)
+ .setMaxIter(10)
+ .setInitMode("degree")
+ .transform(data)
+ val predictions2 = Array.fill(2)(mutable.Set.empty[Long])
+ result2.select("id", "prediction").collect().foreach {
+ case Row(id: Long, cluster: Integer) => predictions2(cluster) += id
+ }
+ assert(predictions2.toSet == Set((1 until n1).toSet, (n1 until
n).toSet))
+
+ val expectedColumns = Array("id", "prediction")
--- End diff --
No need to check this since it's already checks above by result2.select(...)
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