Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/9838#discussion_r45350947
--- Diff: mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala
---
@@ -65,4 +65,24 @@ class PCASuite extends SparkFunSuite with
MLlibTestSparkContext {
assert(x ~== y absTol 1e-5, "Transformed vector is different with
expected vector.")
}
}
+
+ test("read/write") {
+
+ def checkModelData(model1: PCAModel, model2: PCAModel): Unit = {
+ assert(model1.pc === model2.pc)
+ }
+ val allParams: Map[String, Any] = Map(
+ "k" -> 3,
+ "inputCol" -> "features",
+ "outputCol" -> "pca_features"
+ )
+ val data = Seq(
+ (0.0, Vectors.sparse(5, Seq((1, 1.0), (3, 7.0)))),
+ (1.0, Vectors.dense(2.0, 0.0, 3.0, 4.0, 5.0)),
+ (2.0, Vectors.dense(4.0, 0.0, 0.0, 6.0, 7.0))
+ )
+ val df = sqlContext.createDataFrame(data).toDF("id", "features")
+ val pca = new PCA().setK(3)
+ testEstimatorAndModelReadWrite(pca, df, allParams, checkModelData)
+ }
}
--- End diff --
The same as
[StandardScalerModel](https://github.com/apache/spark/pull/9839/files#diff-7ae15fe7b1bc41e6a876c2424380d764R132),
we can not construct PCAModel directly by specifying the variable ```k```, so
test estimator and model in one case with ```testEstimatorAndModelReadWrite```.
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