BUG: Fix generalized ufunc so repeating labels in one input/output is ok
BUG: Missed case of broadcasting onto core dimensions in gufunc
BUG: Make sure the nditer doesn't complain when 0 broadcast dims
TST: Add test for gufunc scalar case
BUG: Fix bug in gufunc scalar case
TST: Test for a generalized ufunc bug, for zero-sized inputs
BUG: Fix for generalized ufunc zero-sized input case
compile fix on linux/mac
BUG: npy-pkg-config ini files were missing after Bento build.
BUG: gh-2790, fix column scaling in polynomial package least squares.

The columns should be scaled using their 2-norm, but in the complex case
that was being incorrectly computed as the square root of the sum of the
squared elements rather than as the square root of the  sum of their squared
real and imaginary parts.
TST: Add Test for column scaling in the polynomial package fits.

The test uses the complex set of sample points [1, 1j, -1, -1j] whose
squared sum is exactly zero. This would fail before the column scaling
was fixed.
MAINT: Use a better method to detect complex arrays.

Instead of

    if lhs.dtype.char in np.typecodes['Complex']:

use

    if issubclass(lhs.dtype.type, np.complexfloating):
BUG: Fix strides of trailing 1s when reshaping

When adding ones to the shape for non contiguous arrays reshapes
(i.e. either the first array is not contiguous or the the reshape
order does not match it). The strides of trailing ones were not
set. For example reshape of (6,) to (6,1,1). Previously this occured
rarely because of removed special handleing when only ones were
added or removed.
DOC/FIX: fix example in ctypeslib module documentation

Fix some inconsistencies in the example. The library is loaded as '_lib' not
'lib' in the rest of the example. Also, the function is called 'foo_func' not
'foo'
Merge pull request #2960 from esc/doc/fix/ctypeslib

DOC/FIX: fix example in ctypeslib module documentation
Merge pull request #2947 from charris/fix-complex-polynomial-fit

Fix complex polynomial fit
DOC -- add another paragraph note to ndarray.view docs

Since most numpy operations are not sensitive to underlying data
structure (C-ordered arrays vs fortran-ordered arrays, versus slices or
transposes of arrays, etc.), but structured-array views ARE sensitive to
that, it is worth saying it explicitly in the documentation.
DOC -- add another paragraph note to ndarray.view docs (cont'd)

More detail: Views are only sensitive to under-the-hood storage when
the dtype storage size has changed.
DOC: Add example showing how a view of a slice can misbehave
DOC: update 1.7.0-notes.rst from release branch

There were some changes in the release branch that were not put into master.
After this commit, the file 1.7.0-notes.rst is synchronised with the release
branch.