On Wed, Jul 27, 2011 at 2:49 AM, Mark Dickinson <[email protected]>wrote:
> In NumPy 1.6.0, I get the following behaviour: > > > Python 2.7.2 |EPD 7.1-1 (32-bit)| (default, Jul 3 2011, 15:40:35) > [GCC 4.0.1 (Apple Inc. build 5493)] on darwin > Type "packages", "demo" or "enthought" for more information. > >>> import numpy > >>> numpy.nanmin(numpy.ma.masked_array([1,2,3,4])) > Traceback (most recent call last): > File "<stdin>", line 1, in <module> > File > "/Library/Frameworks/Python.framework/Versions/7.1/lib/python2.7/site-packages/numpy/lib/function_base.py", > line 1507, in nanmin > return np.fmin.reduce(a.flat) > TypeError: cannot reduce on a scalar > >>> numpy.__version__ > '1.6.0' > > > In NumPy version 1.5.1: > > Python 2.7.2 |EPD 7.1-1 (32-bit)| (default, Jul 3 2011, 15:40:35) > [GCC 4.0.1 (Apple Inc. build 5493)] on darwin > Type "packages", "demo" or "enthought" for more information. > >>> import numpy > >>> numpy.nanmin(numpy.ma.masked_array([1,2,3,4])) > 1 > >>> numpy.__version__ > '1.5.1' > > > Was this change intentional? > > No, it comes from this In [2]: a = numpy.ma.masked_array([1,2,3,4]) In [3]: array(a.flat) Out[3]: array(<numpy.ma.core.MaskedIterator object at 0x1fd1f90>, dtype='object') i.e., the a.flat iterator is turned into an object array with one element. I'm not sure what the correct fix for this would be. Please open a ticket. Chuck
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