[SPARK-7328] [MLLIB] [PYSPARK] Pyspark.mllib.linalg.Vectors: Missing items

Add
1. Class methods squared_dist
3. parse
4. norm
5. numNonzeros
6. copy

I made a few vectorizations wrt squared_dist and dot as well. I have added support for SparseMatrix serialization in a separate PR (https://github.com/apache/spark/pull/5775) and plan to complete support for Matrices in another PR.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #5872 from MechCoder/local_linalg_api and squashes the following commits:

a8ff1e0 [MechCoder] minor
ce3e53e [MechCoder] Add error message for parser
1bd3c04 [MechCoder] Robust parser and removed unnecessary methods
f779561 [MechCoder] [SPARK-7328] Pyspark.mllib.linalg.Vectors: Missing items

1 files changed, 24 insertions, 1 deletions

diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index d05cfe2af0..36a4c7a540 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -24,7 +24,7 @@ import sys
 import tempfile
 import array as pyarray
 
-from numpy import array, array_equal, zeros
+from numpy import array, array_equal, zeros, inf
 from py4j.protocol import Py4JJavaError
 
 if sys.version_info[:2] <= (2, 6):
@@ -220,6 +220,29 @@ class VectorTests(MLlibTestCase):
         self.assertTrue(array_equal(sm.colPtrs, [0, 2, 5]))
         self.assertTrue(array_equal(sm.values, [1, 3, 4, 6, 9]))
 
+    def test_parse_vector(self):
+        a = DenseVector([3, 4, 6, 7])
+        self.assertTrue(str(a), '[3.0,4.0,6.0,7.0]')
+        self.assertTrue(Vectors.parse(str(a)), a)
+        a = SparseVector(4, [0, 2], [3, 4])
+        self.assertTrue(str(a), '(4,[0,2],[3.0,4.0])')
+        self.assertTrue(Vectors.parse(str(a)), a)
+        a = SparseVector(10, [0, 1], [4, 5])
+        self.assertTrue(SparseVector.parse(' (10, [0,1 ],[ 4.0,5.0] )'), a)
+
+    def test_norms(self):
+        a = DenseVector([0, 2, 3, -1])
+        self.assertAlmostEqual(a.norm(2), 3.742, 3)
+        self.assertTrue(a.norm(1), 6)
+        self.assertTrue(a.norm(inf), 3)
+        a = SparseVector(4, [0, 2], [3, -4])
+        self.assertAlmostEqual(a.norm(2), 5)
+        self.assertTrue(a.norm(1), 7)
+        self.assertTrue(a.norm(inf), 4)
+
+        tmp = SparseVector(4, [0, 2], [3, 0])
+        self.assertEqual(tmp.numNonzeros(), 1)
+
 
 class ListTests(MLlibTestCase):