8000 BUG: Fixes for ma.median and nanpercentile. by juliantaylor · Pull Request #8372 · numpy/numpy · GitHub
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BUG: Fixes for ma.median and nanpercentile. #8372

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Merged
merged 5 commits into from
Dec 13, 2016
Merged

BUG: Fixes for ma.median and nanpercentile. #8372

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2e79af2
BUG: fix nanpercentile not returning scalar with axis argument
juliantaylor Dec 11, 2016
52336fc
BUG: handle unmasked NaN in ma.median like normal median
juliantaylor Dec 5, 2016
0ee6af6
MAINT: make regex strings raw
juliantaylor Dec 11, 2016
1e3ec9f
ENH: update the small nanmedian threshold
juliantaylor Dec 12, 2016
4c63449
DOC: add ma.median nan change to release notes
juliantaylor Dec 12, 2016
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ENH: update the small nanmedian threshold 
The apply_along_axis path is significantly more expensive than currently
accounted for in the check. Increase the minimum axis size from 400 to
1000 elements.
Either apply_along_axis got more expensive over time or the original
benchmarking was flawed.
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@juliantaylor
juliantaylor committed Dec 12, 2016
commit 1e3ec9fd3b4261c5222b2383589d170e98b7ecc3
2 changes: 1 addition & 1 deletion numpy/lib/nanfunctions.py
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Expand Up @@ -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:
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