Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/11119#discussion_r78690235
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---
@@ -139,16 +146,72 @@ class KMeansSuite extends SparkFunSuite with
MLlibTestSparkContext with DefaultR
val kmeans = new KMeans()
testEstimatorAndModelReadWrite(kmeans, dataset,
KMeansSuite.allParamSettings, checkModelData)
}
+
+ test("Initialize using given cluster centers") {
+ val kmeans = new KMeans().setK(k).setSeed(1).setMaxIter(1)
+ val oneIterModel = kmeans.fit(dataset)
+ val twoIterModel = kmeans.copy(ParamMap(ParamPair(kmeans.maxIter,
2))).fit(dataset)
+ val oneMoreIterModel =
kmeans.setInitialModel(oneIterModel).fit(dataset)
+
+ twoIterModel.clusterCenters.zip(oneMoreIterModel.clusterCenters)
+ .foreach { case (center1, center2) => assert(center1 ~== center2
absTol 1E-8) }
+ }
+
+ test("Initialize using wrong model") {
+ val kmeans = new KMeans().setK(k).setSeed(1).setMaxIter(10)
+ val wrongTypeModel = new KMeansSuite.MockModel()
+
+ withClue("The type of an initial model should only be a KMeansModel.")
{
+ intercept[IllegalArgumentException] {
+ kmeans.setInitialModel(wrongTypeModel).fit(dataset)
+ }
+ }
+
+ val wrongKModel = KMeansSuite.generateRandomKMeansModel(3, k + 1)
+ withClue("The number of clusters set in the given model should be the
same with the one set" +
+ " in the KMeans estimator.") {
+ intercept[IllegalArgumentException] {
+ kmeans.setInitialModel(wrongKModel).fit(dataset)
+ }
+ }
+
+ val wrongDimModel = KMeansSuite.generateRandomKMeansModel(4, k)
+ withClue("The dimension of points in the model should be the same with
the dimension of the" +
--- End diff --
`withClue` just prepends the provided message to the error message when the
exception is not thrown as expected. I think we should check that the correct
exception is thrown:
````scala
val thrown = intercept[IllegalArgumentException] {
...
}
assert(thrown.getMessage.contains("mismatched dimension"))
````
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