Github user vectorijk commented on a diff in the pull request:
https://github.com/apache/spark/pull/12464#discussion_r61491169
--- Diff: python/pyspark/ml/tests.py ---
@@ -461,6 +461,31 @@ def _fit(self, dataset):
class CrossValidatorTests(PySparkTestCase):
+ def test_copy(self):
+ sqlContext = SQLContext(self.sc)
+ dataset = sqlContext.createDataFrame([
+ (10, 10.0),
+ (50, 50.0),
+ (100, 100.0),
+ (500, 500.0)] * 10,
+ ["feature", "label"])
+
+ iee = InducedErrorEstimator()
+ evaluator = RegressionEvaluator(metricName="rmse")
+
+ grid = (ParamGridBuilder()
+ .addGrid(iee.inducedError, [100.0, 0.0, 10000.0])
+ .build())
+ cv = CrossValidator(estimator=iee, estimatorParamMaps=grid,
evaluator=evaluator)
+ cvCopied = cv.copy()
+ self.assertEqual(cv.getEstimator().uid,
cvCopied.getEstimator().uid)
+
+ cvModel = cv.fit(dataset)
+ cvModelCopied = cvModel.copy()
+ for index in range(len(cvModel.avgMetrics)):
+ self.assertTrue(abs(cvModel.avgMetrics[index] -
cvModelCopied.avgMetrics[index])
--- End diff --
I have tried `assertEqual` before. This test case causes loss of precision
under python2 if we use `assertEqual`. But under python3, it passes.
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