Hi,
numpy.var on a memory mapped array returns a 0-d memmap object instead of a
scalar (like with numpy arrays):
>>> import numpy as np
>>> fp = np.memmap('test.mm', dtype='float32', mode='w+', shape=(10,))
>>> fp[:] = np.random.rand(10)
>>> fp_var= np.var(fp)
>>> print type(fp_var)
<class 'numpy.core.memmap.memmap'>
>>> print fp_var.ndim
0
Moreover, the obtained object is missing 'filename' attribute, so that it can
not be reused in further calculations:
>>> fp_std = np.sqrt(fp_var)
...
AttributeError: 'memmap' object has no attribute 'filename'
I can produce this bug in numpy 1.5.1 with python2.6 (from macports).
Cheers,
Bartosz
Institute for Theoretical Biology
Humboldt University of Berlin
Germany
http://neuroscience.telenczuk.pl
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