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authorJake Vanderplas <jakevdp@yahoo.com>2012-06-11 14:07:47 -0700
committerJake Vanderplas <jakevdp@yahoo.com>2012-06-11 14:07:47 -0700
commit6cb02660163c107e2cf407c1483bad485fa5fd95 (patch)
tree826bae4b06ea92214dc2bfa4466718e5028804dd /numpy/lib/function_base.py
parenta0d1a961a9e3428d378e2189b8c337cc629a2fae (diff)
downloadnumpy-6cb02660163c107e2cf407c1483bad485fa5fd95.tar.gz
remove unused variables from histogramdd
Diffstat (limited to 'numpy/lib/function_base.py')
-rw-r--r--numpy/lib/function_base.py2
1 files changed, 0 insertions, 2 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 2de5c6193..9df44a477 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -350,7 +350,6 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None):
# Using digitize, values that fall on an edge are put in the right bin.
# For the rightmost bin, we want values equal to the right
# edge to be counted in the last bin, and not as an outlier.
- outliers = zeros(N, int)
for i in arange(D):
# Rounding precision
mindiff = dedges[i].min()
@@ -369,7 +368,6 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None):
# Compute the sample indices in the flattened histogram matrix.
ni = nbin.argsort()
- shape = []
xy = zeros(N, int)
for i in arange(0, D-1):
xy += Ncount[ni[i]] * nbin[ni[i+1:]].prod()