Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/5872#discussion_r29811164
--- Diff: python/pyspark/mllib/linalg.py ---
@@ -208,9 +209,55 @@ def __init__(self, ar):
ar = ar.astype(np.float64)
self.array = ar
+ def toString(self):
+ """
+ Convert DenseVector to string representation.
+
+ >>> a = DenseVector([0, 1, 2, 3])
+ >>> a.toString()
+ '[0.0,1.0,2.0,3.0]'
+ """
+ return str(self)
+
+ def copy(self):
+ return DenseVector(np.copy(self.array))
+
+ @staticmethod
+ def parse(vectorString):
+ """
+ Parse string representation back into the DenseVector.
+
+ >>> DenseVector.parse('[0.0,1.0,2.0,3.0]')
+ DenseVector([0.0, 1.0, 2.0, 3.0])
+ """
+ vectorString = vectorString[1:-1]
--- End diff --
I think the Scala version is a bit more robust since it uses Java's
StringTokenizer for splitting
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