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| author | Charles Harris <charlesr.harris@gmail.com> | 2016-12-12 18:10:12 -0500 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2016-12-12 18:10:12 -0500 |
| commit | aab7993af0f6f3b9ac0d76952933b19163d65496 (patch) | |
| tree | c29a3865d6cb645aa8a381f19d36e176de2fe560 /numpy/lib/nanfunctions.py | |
| parent | 74abcfc5431836825800550fd354f32bcc93a89d (diff) | |
| parent | 3b31fa130959bbc5544e7b5fa5226076466d6d88 (diff) | |
| download | numpy-aab7993af0f6f3b9ac0d76952933b19163d65496.tar.gz | |
Merge pull request #8364 from juliantaylor/masked-median-nan
BUG: handle unmasked NaN in ma.median like normal median
Diffstat (limited to 'numpy/lib/nanfunctions.py')
| -rw-r--r-- | numpy/lib/nanfunctions.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py index 24472dfcd..812b9bcb3 100644 --- a/numpy/lib/nanfunctions.py +++ b/numpy/lib/nanfunctions.py @@ -869,7 +869,7 @@ def _nanmedian(a, axis=None, out=None, overwrite_input=False): else: # for small medians use sort + indexing which is still faster than # apply_along_axis - if a.shape[axis] < 400: + if a.shape[axis] < 1000: return _nanmedian_small(a, axis, out, overwrite_input) result = np.apply_along_axis(_nanmedian1d, axis, a, overwrite_input) if out is not None: |