Numpy for Windows full changelog
Numpy for Windows 1.11.2
released Oct 4, 2016 (New Release)
Numpy 1.11.2 supports Python 2.6 - 2.7 and 3.2 - 3.5. It fixes bugs and regressions found in Numpy 1.11.1 and includes several build related improvements. Wheels for Linux, Windows, and OS X can be found on PyPI.
Numpy for Windows 1.6.2
released Aug 25, 2012 (New Release)
New features:
· Reduction UFuncs Generalize axis= Parameter
· Any ufunc.reduce function call, as well as other reductions like sum, prod, any, all, max and min support the ability to choose a subset of the axes to reduce over. Previously, one could say axis=None to mean all the axes or axis=# to pick a single axis. Now, one can also say axis=(#,#) to pick a list of axes for reduction.
Reduction UFuncs New keepdims= Parameter :
· There is a new keepdims= parameter, which if set to True, doesn't throw away the reduction axes but instead sets them to have size one. When this option is set, the reduction result will broadcast correctly to the original operand which was reduced.
Datetime support:
.. note:: The datetime API is *experimental* in 1.7.0, and may undergo changes in future versions of NumPy. There have been a lot of fixes and enhancements to datetime64 compared to NumPy 1.6:
· the parser is quite strict about only accepting ISO 8601 dates, with a few convenience extensions
· Reduction UFuncs Generalize axis= Parameter
· Any ufunc.reduce function call, as well as other reductions like sum, prod, any, all, max and min support the ability to choose a subset of the axes to reduce over. Previously, one could say axis=None to mean all the axes or axis=# to pick a single axis. Now, one can also say axis=(#,#) to pick a list of axes for reduction.
Reduction UFuncs New keepdims= Parameter :
· There is a new keepdims= parameter, which if set to True, doesn't throw away the reduction axes but instead sets them to have size one. When this option is set, the reduction result will broadcast correctly to the original operand which was reduced.
Datetime support:
.. note:: The datetime API is *experimental* in 1.7.0, and may undergo changes in future versions of NumPy. There have been a lot of fixes and enhancements to datetime64 compared to NumPy 1.6:
· the parser is quite strict about only accepting ISO 8601 dates, with a few convenience extensions
Numpy for Windows 1.6.1
released Jul 21, 2011 (New Release)
· BUG: Fix regression in printing polynomials.
· BUG: defer numpy.distutils import in ctypeslib.
· BUG: defer numpy.distutils import in ctypeslib.
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