ENH support getting single element from CSR/CSC where duplicates are present
ENH: improve signal.convolve2d performance

Store indices in inner most loop and apply them in one typed loop one
level lower. This avoids expensive memcpy and function calls for very
cheap operations.
Improves performance by almost a factor 3 with relative small changes,
but there is still a lot of room for improvement.
MAINT: raise warnings for logm of some possibly nearly singular matrices
MAINT: fix a backwards incompatible change to stats.distributions.__all__
Merge pull request #3292 from argriffing/stats-distributions-all

MAINT: fix a backwards incompatible change to stats.distributions.__all__
MAINT: add 2d convolution benchmark
TST: sparse: accept Numpy dev versions in >= 1.9.0 version checks
TST: sparse: fix some issues in sparse non-canonical tests + mark new known failures
TST: sparse: fix dense-sparse in-place op tests

These tests previously assumed that ndarray.__imul__(sparse) would
correspond to elementwise product. This behavior in __numpy_ufunc__ was
changed in Numpy, so that "a *= b" corresponds to sparse.__rmul__
(similarly as "a = a*b").
TST: sparse: Py3 fix
Merge pull request #3269 from jnothman/get_single_duplicate

ENH: sparse: getting single element from CSR/CSC sparse matrix with duplicates
Merge pull request #3287 from argriffing/logm-singular-warning

ENH: linalg: raise warnings for logm of some possibly nearly singular matrices
Merge pull request #3295 from argriffing/conv2d-bench

TST: signal: add 2d convolution benchmark
Merge pull request #3277 from juliantaylor/sig-conv2d-improv

ENH: improve signal.convolve2d performance
ENH: sparse: implement fancy indexing in dok_matrix.__setitem__
TST: sparse: turn on DOK fancy indexing tests
BUG: sparse: fix bugs in DOK setitem for multidim index arrays
ENH: sparse: implement fancy indexing in DOK getitem
ENH: sparse: fast path for DOK scalar setitem
BUG: sparse: fix logic error in DOK getitem

Since i, j can be arbitrary, also for small NNZ one needs to look up
which index in i, j it corresponds to.