[Numpy-discussion] Bug in memmap/python allocation code?

Mike Ressler mike.ressler at gmail.com
Mon Jul 24 19:36:53 CDT 2006

I'm trying to work with memmaps on very large files, i.e. > 2 GB, up to 10
GB. The files are data cubes of images (my largest is
1290(x)x1024(y)x2011(z)) and my immediate task is to strip the data from
32-bits down to 16, and to rearrange some of the data on a per-xy-plane
basis. I'm running this on a Fedora Core 5 64-bit system, with
python-2.5b2(that I believe I compiled in 64-bit mode) and
numpy-1.0b1. The disk has 324 GB free space.

The log from a minimal case is as follows:

ressler > python2.5
Python 2.5b2 (r25b2:50512, Jul 18 2006, 12:58:29)
[GCC 4.1.1 20060525 (Red Hat 4.1.1-1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> data=np.memmap('temp_file',mode='w+',shape=(2011,1280,1032),dtype='h')
size = 2656450560
bytes = 5312901120
len(mm) = 5312901120
(2011, 1280, 1032) h 0 0
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.5/site-packages/numpy/core/memmap.py", line
75, in __new__
    offset=offset, order=order)
TypeError: buffer is too small for requested array

If I have a small number of frames (z=800 rather than 2011), this all works
fine. I've added a few lines to memmap.py to print some diagnostic
information - the error occurs on line 71 in the original memmap.py file,
not 75. The "size =" and "bytes =" lines show that memmap.py is calculating
the correct size for the buffer, and the len(mm) shows that the python
mmap.mmap call on line 67 is returning a buffer of the correct size. The
"(2011, 1280, 1032) h 0 0" bit is from a print statement that was left in
the source file by the authors, and indicates what the following "self =
ndarray.__new__" call is trying to do. However, it is the ndarray.__new__
call that is breaking down, and I don't really have enough skill to continue
chasing it down. I took a quick look at the C source, but I couldn't figure
out where the ndarray.__new__ is actually defined.

Any suggestions to help me past this? Thanks.


mike.ressler at alum.mit.edu
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