Hello, I posted this a while back and didn't get any replies. I'm running in to this issue again from a different aspect, and today I've been trying to figure out which method of ndarray needs to be overloaded for memmap so that the the ._mmap attribute gets handled appropriately. But, I have not been able to figure out what methods of ndarray are getting used in code such as this:
import numpy amemmap = numpy.memmap( '/tmp/afile', dtype=numpy.float32, shape=(4,5), mode='w+' ) b = amemmap[2:3] b Exception exceptions.AttributeError: "'memmap' object has no attribute '_mmap'" in <bound method memmap.__del__ of memmap([ 0., 0., 0., 0., 0.], dtype=float32)> ignored memmap([[ 0., 0., 0., 0., 0.]], dtype=float32)
Furthermore, can anyone enlighten me as to why an AttributeError exception would be ignored? Am I using numpy.memmap instances appropriately? Thank you, Glen Mabey On Thu, Jun 07, 2007 at 04:46:20PM -0500, Glen W. Mabey wrote:
Hello,
When assigning a variable that is the transpose() of a memmap array, the ._mmap member doesn't get copied, I guess:
In [1]:import numpy
In [2]:amemmap = numpy.memmap( '/tmp/afile', dtype=numpy.float32, shape=(4,5), mode='w+' )
In [3]:bmemmap = amemmap.transpose()
In [4]:bmemmap.close() --------------------------------------------------------------------------- <type 'exceptions.AttributeError'> Traceback (most recent call last)
/home/gmabey/src/R9619_dev_acqlibweb/Projects/R9619_NChannelDetection/NED/<ipython console> in <module>()
/usr/local/stow/numpy-20070605_svn-py2.5/lib/python2.5/site-packages/numpy/core/memmap.py in close(self) 86 87 def close(self): ---> 88 self._mmap.close() 89 90 def __del__(self):
<type 'exceptions.AttributeError'>: 'NoneType' object has no attribute 'close'
/usr/local/stow/numpy-20070605_svn-py2.5/lib/python2.5/site-packages/numpy/core/memmap.py(88)close() 87 def close(self): ---> 88 self._mmap.close() 89
This is an issue when the data is accessed in an order that is different from how it is stored on disk, as:
bmemmap = numpy.memmap( '/tmp/afile', dtype=numpy.float32, shape=(4,5), mode='w+' ).transpose()
So the object that was originally produced not accessible. I imagine there is some better way to indicate order of dimensions, but regardless, doing
In [4]:bmemmap._mmap = amemmap._mmap
is a hack workaround.
Best regards, Glen Mabey _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion