DOC: Mention all min/max functions from all others, clarify differences
DOC: Harmonize max and min docstrings with each other
DOC: update numpy.distutils documentation, remove info.py details.

Addresses https://github.com/scipy/scipy/issues/2492
Merge pull request #3340 from rgommers/distutils-doc

DOC: update numpy.distutils documentation, remove info.py details.
ENH: improved, faster algorithm for array padding

New padding method which scales much better with dimensionality.
This new implementation is fully vectorized, builds each abstracted
n-dimensional padding block in a single step, and takes advantage
of separability. The API is completely preserved, and the old
algorithm is used if a vector function is input for `mode`.

The new algorithm is faster for all tested combinations of inputs,
and scales much better with dimensionality. Execution time reductions
from ~25% for small rank 1 arrays to >99% for rank 4+ arrays observed.
Merge pull request #3329 from JDWarner/faster_arraypad

ENH: improved, faster algorithm for array padding
BLD: fix setuptools-specific easy_install issue.  Closes gh-3160.

An error is raised by setuptools when trying to write to /dev/null.  Was fixed
in distribute, but not in setuptools.

No multi-arch support with plain setuptools should be OK, because multi-arch is
Ubuntu specific (at least for now), and they ship distribute.
DOC: add fmax/fmin to ufuncs list and math routines list
Merge pull request #3339 from endolith/min_max_docstrings

DOC: Min max docstrings
Merge pull request #3342 from rgommers/easyinstall-issue

BLD: fix setuptools-specific easy_install issue.  Closes gh-3160.
MAINT: Remove msvc_on_amd64 function

This function is no longer required for building with msvc on AMD64
DOC: Remove confusing comment about warnings from top-level README.
Merge pull request #3350 from njsmith/tweak-README

DOC: Remove confusing comment about warnings from top-level README.
Merge pull request #3344 from cgohlke/patch-1

Remove the msvc_on_amd64 function
MAINT: Remove tools/osxbuild

These scripts have been broken for years (build.py errors out
immediately if not running from an *svn* checkout), so I'm sure
no-one's using them, and they only attract pointless maintenance fixes
(py3 changes, keeping the pointless extra copy of the top-level
README.txt up to date as in #3288). Let's just remove them.
ENH: vectorize sqrt ufunc using SSE2

specialize the sqrt ufunc for float and double and vectorize it using
SSE2.

improves performance by 4/2 for float/double if one is not memory bound
due to non-cached data.
performance is always better on all tested machines (amd phenom X2,
intel xeon 5xxx/7xxx, core2duo, corei7)

This version will not set errno on invalid input, but numpy only checks
the fpu flags so the behavior is the same.

In principle the compiler could autovectorize it when setting ffast-math
(for no errno) and specializing the loop for the vectorizable strides
and giving it some hints (restrict, __builtin_assume_aligned, etc.),
but its simpler and more reliable to simply vectorize it by hand.
MAINT: use sse header macros for einsum sse activation