From 0f1dc3a73d6687f0027a68eb9a4a13a7c7848205 Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Wed, 11 Jun 2014 00:22:40 -0700
Subject: [PATCH] [SPARK-2091][MLLIB] use numpy.dot instead of ndarray.dot
`ndarray.dot` is not available in numpy 1.4. This PR makes pyspark/mllib compatible with numpy 1.4.
Author: Xiangrui Meng <meng@databricks.com>
Closes #1035 from mengxr/numpy-1.4 and squashes the following commits:
7ad2f0c [Xiangrui Meng] use numpy.dot instead of ndarray.dot
---
python/pyspark/mllib/_common.py | 8 +++++---
1 file changed, 5 insertions(+), 3 deletions(-)
diff --git a/python/pyspark/mllib/_common.py b/python/pyspark/mllib/_common.py
index a411a5d591..e609b60a0f 100644
--- a/python/pyspark/mllib/_common.py
+++ b/python/pyspark/mllib/_common.py
@@ -454,7 +454,7 @@ def _squared_distance(v1, v2):
v2 = _convert_vector(v2)
if type(v1) == ndarray and type(v2) == ndarray:
diff = v1 - v2
- return diff.dot(diff)
+ return numpy.dot(diff, diff)
elif type(v1) == ndarray:
return v2.squared_distance(v1)
else:
@@ -469,10 +469,12 @@ def _dot(vec, target):
calling numpy.dot of the two vectors, but for SciPy ones, we
have to transpose them because they're column vectors.
"""
- if type(vec) == ndarray or type(vec) == SparseVector:
+ if type(vec) == ndarray:
+ return numpy.dot(vec, target)
+ elif type(vec) == SparseVector:
return vec.dot(target)
elif type(vec) == list:
- return _convert_vector(vec).dot(target)
+ return numpy.dot(_convert_vector(vec), target)
else:
return vec.transpose().dot(target)[0]
--
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