DOC: Note nanpercentile in 1.9.0 release notes.
Fix minor error in "squeeze" docstring
Merge pull request #4764 from KillaW0lf04/master

Fix minor error in "squeeze" docstring
Optimization for pickling random states

-- Addresses https://github.com/numpy/numpy/issues/4763
DOC: add versionadded tags to meshgrid arguments

[ci skip]
Merge pull request #4769 from juliantaylor/mesh-doc

DOC: add versionadded tags to meshgrid arguments
Merge pull request #4757 from charris/update-1.9.0-release-notes

DOC: Note nanpercentile in 1.9.0 release notes.
Merge pull request #4768 from depristo/master

ENH: Optimization for pickling random states

the constructor intended for pickling initializes its state via reading /dev/urandom which can be expensive on virtual machines. as the pickle constructor just needs to create any state which will later be initialized these urandom reads are unnecessary.
ENH: use sparse meshgrid instead of indices().tolist()

tolist() converts numpy integers to python integers which are converted
back to numpy integers by the indexing.
meshgrid(indexing='ij') returns the indices wanted here as the right type.
triples performance of sorting a size=(200, 200, 50) array along axis 2
and reduces memory usage by almost 40%.
ENH: rewrite ma.median to improve poor performance for multiple dimensions

many masked median along a small dimension is extremely slow due to the
usage of apply_along_axis which iterates fully in python. The unmasked
median is about 1000x faster.

Work around this issue by using indexing to select the median element
instead of apply_along_axis.

Further improvements are possible, e.g. using the current np.nanmedian
approach for masked medians along large dimensions so partition is used
instead of sort or to extend partition to allow broadcasting over
multiple elements.

Closes gh-4683.
ENH: use masked median for small multidimensional nanmedians