DOC: Add NEP and documentation for ufunc overrides.
ENH: Add ufunc override API.
STY: Make numpy/polynomial/tests/*.py PEP8 compliant.

Run autopep8 on the tests and fixup the results.
ENH: Add ufunc override functionality to ufuncs and dots.
TST: Add ufunc override tests.
BLD: Added ufunc_override.h to setup.py.
BLD TRAVIS: Added libatlas to travis build so it can test BLAS stuff.

sudo apt-get install -qq libatlas-dev libatlas-base-dev
DOC: Update release notes.
Merge pull request #3524 from cowlicks/ufunc-override

Ufunc Overrides
Merge pull request #3676 from charris/pep8-polynomial-tests

STY: Make numpy/polynomial/tests/*.py PEP8 compliant.
BUG: fix windows fpu flag check for mixed x87 and sse instructions

windows enables sse intrinsics also on 32 bit by default so we need to
check both the x87 and sse fpu flags.
closes #3680
Merge pull request #3691 from juliantaylor/windows-fpu-fix

BUG: fix windows fpu flag check for mixed x87 and sse instructions
BUG: fix test_rational PyNumberMethods for python3

wrong structure makes VC9 fail to compile under python3
Merge pull request #3694 from juliantaylor/test-rational-fix

BUG: fix test_rational PyNumberMethods for python3
ENH: Improve accuracy of numpy.gradient at edges

* numpy.gradient has been enhanced to use a second order accurate
  one-sided finite difference stencil at boundary elements of the
  array. Second order accurate central difference are still used for
  the interior elements. The result is a fully second order accurate
  approximation of the gradient over the full domain.

* The one-sided stencil uses 3 elements each with a different weight. A
  forward difference is used for the first element,
     dy/dx ~ -(3.0*y[0] - 4.0*y[1] + y[2]) / (2.0*dx)
  and backwards difference is used for the last element,
     dy/dx ~ (3.0*y[-1] - 4.0*y[-2] + y[-3]) / (2.0*dx)

* Because the datetime64 datatype cannot be multiplied a view is taken
  of datetime64 arrays and cast to int64. The gradient algorithm is
  then applied to the view rather than the input array.

* Previously no dimension checks were performed on the input array. Now
  if the array size along the differentiation axis is less than 2, a
  ValueError is raised which explains that more elements are needed. If
  the size is exactly two the function falls back to using a 2 point
  stencil (the old behaviour). If the size is 3 and above then the
  higher accuracy methods are used.

* A new test has been added which validates the higher accuracy. Old
  tests have been updated to pass. Note, this should be expected
  because the boundary elements now return different (more accurate)
  values.
Merge branch 'gradient'

* gradient:
  ENH: Improve accuracy of numpy.gradient at edges
BUG: Fix UFUNC_CHECK_STATUS to work on both 32 and 64 bit Windows.

Patch is due to Christolph Gohlke.
Merge pull request #3697 from charris/fix-simd-for-windows

BUG: Fix UFUNC_CHECK_STATUS to work on both 32 and 64 bit Windows.