ENH: Add a 1D Savitzky-Golay filter
DOC: signal: fixed the last example in the docstring for savgol_coeffs
DOC: signal: fixed a typo in the savgol_filter docstring
DOC: signal: fix typo in _fit_edge docstring
BUG: signal: in savgol_filter, properly handle dtypes that are not 32 or 64 bit floating point
ENH: use partition for faster trim_mean

partition available in numpy 1.8 partially sorts array around the cut
positions. Scales linear instead of the linearithmic scaling of sort.
Detect over-long compressed sequences, test mat file data integrity checks
ENH: scipy.spatial.distance: use BLAS and waste less memory

This module was using np.linalg.norm instead of the SciPy version,
which switches to BLAS when appropriate.

The change to sqeuclidean makes it four times faster for length-1e5
random vectors using NumPy 1.6.2 linked against ATLAS 3.8.4:

>>> %timeit ((u - v) ** 2).sum()
1000 loops, best of 3: 2.01 ms per loop
>>> %timeit u_v = u - v; np.dot(u_v, u_v)
1000 loops, best of 3: 552 us per loop
BUG: Remove bug where __div__ & __truediv__ didn't upcast dtype.
ENH: Sparse compatibility with NumPy dot, multiply, add, div, subtract.
TST: Tests for compatibility with NumPy ufuncs and dot.

Note that these tests only run if NumPy version is greater than 1.9.
BUG: sparse: enable right division in numpy_ufunc
TST: sparse: test __numpy_ufunc__ also for mixed dense/sparse operations
DOC: sparse: add a clarifying comment why rdiv is not inverse
TST: sparse: test __numpy_ufunc__ for right division and throw scalars into the mix
BUG: sparse: don't abort program with SIGFPE on integer divide by zero
BUG: sparse: fix elementwise division by sparse matrix to produce correct results
TST: sparse: fix up __numpy_ufunc__ tests, and throw complex scalars into the mix
BUG: sparse: fix elementwise division of int matrix by int scalar
TST: sparse: deal with precision issues in division tests, and check int division