Add note to scipy.optimize.brute_force about the datatype of the evalution.
ENH: scipy.special information theory functions
TST: remove negative inputs
BUG: cluster.linkage array conversion to double dtype
BUG: sparse: fix operator overloading with custom types

See issue #3580.
ENH: sparse: inplace ops should fall back to x = x op y if not implemented
MAINT: remove most references to symeig and move lobpcg benchmarks out of the test directory
MAINT: remove the rest of the symeig references
DOC: move docs from __init__.py to the lobpcg docstring
BUG: sparse: itruediv should be allowed on sparse matrix
BENCH: lobpcg vs. eigh mikota pair benchmark now works
BENCH: let the preconditioner do mat-mat explicitly, not just mat-vec
BENCH: resurrect another lobpcg benchmark
MAINT: remove unused imports
MAINT: change variable names that used incorrect terminology
MAINT: remove the '__main__' section and the X.txt file from lobpcg
TST: the '__main__' lobpcg.py code is now a real test
Sort netcdf variables in a Python-3 compatible way

The previous implementation ran into issues with comparing different
types (tuples and bools).

Also simplified the sorting, since Python 2.3 support is no longer an
issue.
Add test for zero dimensional netCDF variables
Ensure isrec always returns a boolean