bottleneck 1.0.0 released

[Keith Goodman]

I am happy to announce the release of bottleneck 1.0.0.

Download: https://pypi.python.org/pypi/Bottleneck/1.0.0

This release is a complete rewrite of Bottleneck.

**Faster**

- "python setup.py build" is 18.7 times faster
- Function-call overhead cut in half---a big speed up for small input arrays
- Arbitrary ndim input arrays accelerated; previously only 1d, 2d, and 3d
- bn.nanrankdata is twice as fast for float input arrays
- bn.move_max, bn.move_min are faster for int input arrays
- No speed penalty for reducing along all axes when input is Fortran ordered

**Smaller**

- Compiled binaries 14.1 times smaller
- Source tarball 4.7 times smaller
- 9.8 times less C code
- 4.3 times less Cython code
- 3.7 times less Python code

**Beware**

- Requires numpy 1.9.1
- Single API, e.g.: bn.nansum instead of bn.nansum and nansum_2d_float64_axis0
- On 64-bit systems bn.nansum(int32) returns int32 instead of int64
- bn.nansum now returns 0 for all NaN slices (as does numpy 1.9.1)
- Reducing over all axes returns, e.g., 6.0; previously np.float64(6.0)
- bn.ss() now has default axis=None instead of axis=0
- bn.nn() is no longer in bottleneck

**min_count**

- Previous releases had moving window function pairs: move_sum, move_nansum
- This release only has half of the pairs: move_sum
- Instead a new input parameter, min_count, has been added
- min_count=None same as old move_sum; min_count=1 same as old move_nansum
- If # non-NaN values in window < min_count, then NaN assigned to the window
- Exception: move_median does not take min_count as input

**Bug Fixes**

- Can now install bottleneck with pip even if numpy is not already installed
- bn.move_max, bn.move_min now return float32 for float32 input

[Stephan Hoyer]

This is awesome. Congrats Keith!

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