Bottleneck 1.1.0 released

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Keith Goodman

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Jun 22, 2016, 4:30:52 PM6/22/16
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Bottleneck 1.1.0

*Release date: 2016-06-22*

This release makes Bottleneck more robust, releases GIL, adds new functions.

**More Robust**

- move_median can now handle NaNs and `min_count` parameter
- move_std is slower but numerically more stable
- Bottleneck no longer crashes on byte-swapped input arrays

**Faster**

- All Bottleneck functions release the GIL
- median is faster if the input array contains NaN
- move_median is faster for input arrays that contain lots of NaNs
- No speed penalty for median, nanmedian, nanargmin, nanargmax for Fortran
  ordered input arrays when axis is None
- Function call overhead cut in half for reduction along all axes (axis=None)
  if the input array satisfies at least one of the following properties: 1d,
  C contiguous, F contiguous
- Reduction along all axes (axis=None) is more than twice as fast for long,
  narrow input arrays such as a (1000000, 2) C contiguous array and a
  (2, 1000000) F contiguous array

**New Functions**

- move_var
- move_argmin
- move_argmax
- move_rank
- push

**Beware**

- median now returns NaN for a slice that contains one or more NaNs
- Instead of using the distutils default, the '-O2' C compiler flag is forced
- move_std output changed when mean is large compared to standard deviation
- Fixed: Non-accelerated moving window functions used min_count incorrectly
- move_median is a bit slower for float input arrays that do not contain NaN

**Thanks**

Alphabeticaly by last name

- Alessandro Amici worked on setup.py
- Pietro Battiston modernized bottleneck installation
- Moritz E. Beber set up continuous integration with Travis CI
- Jaime Frio improved the numerical stability of move_std
- Christoph Gohlke revived Windows compatibility
- Jennifer Olsen added NaN support to move_median
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