Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/15777#discussion_r88261887
--- Diff: python/pyspark/ml/tests.py ---
@@ -1097,6 +1097,44 @@ def test_logistic_regression_summary(self):
sameSummary = model.evaluate(df)
self.assertAlmostEqual(sameSummary.areaUnderROC, s.areaUnderROC)
+ def test_gaussian_mixture_summary(self):
+ data = [(Vectors.dense(1.0),), (Vectors.dense(5.0),),
(Vectors.dense(10.0),),
+ (Vectors.sparse(1, [], []),)]
+ df = self.spark.createDataFrame(data, ["features"])
+ gmm = GaussianMixture(k=2)
+ model = gmm.fit(df)
+ self.assertTrue(model.hasSummary)
+ s = model.summary
+ self.assertTrue(isinstance(s.predictions, DataFrame))
+ self.assertEqual(s.probabilityCol, "probability")
+ self.assertTrue(isinstance(s.probability, DataFrame))
+ self.assertEqual(s.featuresCol, "features")
+ self.assertEqual(s.predictionCol, "prediction")
+ self.assertTrue(isinstance(s.cluster, DataFrame))
+ self.assertEqual(len(s.clusterSizes), 2)
+ self.assertEqual(s.k, 2)
+
+ model._call_java("setSummary", None)
--- End diff --
Why we test this? Actually ```setSummary``` is private and it should not
generate a model w/o summary in ordinary case. I think we should only test the
public API for Python. Further more, if we want to test model w/o summary, we
need to write a dummy Scala model w/o summary, and check ```hasSummary```
directly at Python side. I think if the Scala function is not public, we may
not confirm Scala/Python compatibility, so testing is also not very make sense.
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