Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/5374#discussion_r27808046
--- Diff: python/pyspark/mllib/tests.py ---
@@ -363,6 +363,13 @@ def test_col_norms(self):
self.assertEqual(10, len(summary.normL1()))
self.assertEqual(10, len(summary.normL2()))
+ data2 = self.sc.parallelize(xrange(10)).map(lambda x:
Vectors.dense(x))
+ summary2 = Statistics.colStats(data2)
+ self.assertEqual(array([45.0]), summary2.normL1())
+ # Confirm normL2 is among this span because it is a float value.
+ self.assertTrue(summary2.normL2()[0] > 16.5)
--- End diff --
The bounds are too loose. We should reach machine precision for this.
~~~
import math
expectedNormL2 = math.sqrt(sum(map(lambda x: x*x, xrange(10))))
self.assertTrue(math.abs(summary2.normL2()[0] - expectedNormL2) < 1e-14)
~~~
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