[Numpy-discussion] nanmin(<masked array>) fails with 'TypeError: cannot reduce a scalar'. Numpy 1.6.0 regression?

[Mark Dickinson]

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?

-- 
Mark