File python-numpy-doc.changes of Package python-numpy

Tue Feb  4 00:51:36 UTC 2014 -

- add numpy-double-double-le.patch for ppc64le 

Thu Oct 31 10:17:25 UTC 2013 -

- Update to 1.8.0
  * New, no 2to3, Python 2 and Python 3 are supported by a common code base. 
  * New, gufuncs for linear algebra, enabling operations on stacked arrays. 
  * New, inplace fancy indexing for ufuncs with the ``.at`` method. 
  * New, ``partition`` function, partial sorting via selection for fast median. 
  * New, ``nanmean``, ``nanvar``, and ``nanstd`` functions skipping NaNs. 
  * New, ``full`` and ``full_like`` functions to create value initialized arrays. 
  * New, ``PyUFunc_RegisterLoopForDescr``, better ufunc support for user dtypes. 
  * Numerous performance improvements in many areas.
- Add a new flag to easily enable/disable atlas support for if it
  ever gets fixed in the future
- Rebase numpy-buildfix.patch

Thu Aug  1 11:52:47 UTC 2013 -

- The *.egg-info is a file, not a directory

Fri May  3 22:27:24 UTC 2013 -

- Update to 1.7.1
  * Bugfixes

Tue Mar 12 06:21:52 UTC 2013 -

- update to 1.7.0
 * This release includes several new features as well as numerous
 bug fixes and refactorings
  - ``where=`` parameter to ufuncs (allows the use of boolean
  arrays to choose where a computation should be done)
  - ``vectorize`` improvements (added 'excluded' and 'cache'
  keyword, general cleanup and bug fixes)
  - ``numpy.random.choice`` (random sample generating function)

  New Features:
  - Reduction UFuncs Generalize axis= Parameter
  - Reduction UFuncs New keepdims= Parameter
  - Datetime support
  - Custom formatter for printing arrays
  - New function numpy.random.choice
  - New function isclose
  - Preliminary multi-dimensional support in the polynomial package
  - Ability to pad rank-n arrays
  - New argument to searchsorted
  - Added experimental support for the AArch64 architecture.
 * For additional details check release notes at
- numpy-aarch64.diff: removed, now upstream

Fri Jun  1 12:08:16 UTC 2012 -

- Remove blas/lapack tests since these build successfully on all
  targets now
- Add documentation packages
  These are separate packages because a lot of packages depend on
  numpy, so building the documentation inside the base spec file
  would slow down the build process for the entire project