diff options
author | Jake Vanderplas <jakevdp@yahoo.com> | 2012-06-11 14:07:47 -0700 |
---|---|---|
committer | Jake Vanderplas <jakevdp@yahoo.com> | 2012-06-11 14:07:47 -0700 |
commit | 6cb02660163c107e2cf407c1483bad485fa5fd95 (patch) | |
tree | 826bae4b06ea92214dc2bfa4466718e5028804dd /numpy/lib/function_base.py | |
parent | a0d1a961a9e3428d378e2189b8c337cc629a2fae (diff) | |
download | numpy-6cb02660163c107e2cf407c1483bad485fa5fd95.tar.gz |
remove unused variables from histogramdd
Diffstat (limited to 'numpy/lib/function_base.py')
-rw-r--r-- | numpy/lib/function_base.py | 2 |
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() |