"Johannes Nix|Johannes.Nix"@uni-oldenburg.de wrote:
Hi,
I have a tricky problem with Numeric. Some time ago, I have generated
a huge and complex data structure, and stored it using the cPickle
module. Now I want to evaluate it quickly again on a workstation
cluster with 64-Bit Opteron CPUs - I have no more than three days to
do this. Compiling Python and running Numeric has been no problem at
all. However, I get an error message when accessing the data pickled
before. (I can load it regularly on 32 bit computers, but it is a
quite complex data object, so I really don't want to store every
element as ASCII data). The problem seems to be with 64 Bit integers
(with 32-bit-floats, no problem was observed).
This looks like that (from the Unix command shell):
[EMAIL PROTECTED]:~> python ~/python/test_npickle.py -dump test.pck
[EMAIL PROTECTED]:~> python ~/python/test_npickle.py test.pck
[0 1 2 3 4 5 6 7 8 9]
[EMAIL PROTECTED]:~> ssh 64bithost python ~/python/test_npickle.py test.pck
Traceback (most recent call last):
File "/home/jnix/python/test_npickle.py", line 16, in ?
a = cPickle.load(file(filename))
File "/home/jnix/lib/python2.4/SuSE-9.0/x86_64/Numeric/Numeric.py", line 520,
in array_constructor
x.shape = shape
ValueError: ('total size of new array must be unchanged', <function
array_constructor at 0x2a960b0b18>, ((10,), 'l',
'\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\x06\x00\x00\x00\x07\x00\x00\x00\x08\x00\x00\x00\t\x00\x00\x00',
1))
also I get:
[EMAIL PROTECTED]:~> python -c "import Numeric; print
Numeric.arange(0).itemsize()"
4
[EMAIL PROTECTED]:~> python -c "import Numeric; print
Numeric.arange(0).itemsize()"
8
The script used to produce the example above is:
-------------------------------------------------------------------------
#/usr/bin/python
# -*- coding: latin1 -*-
import Numeric
import cPickle
import sys
if len(sys.argv) > 1 and sys.argv[1] == '-dump':
filename = sys.argv[2]
binary=1
a = Numeric.arange(10)
cPickle.dump(a, file(filename,'w',binary))
else:
filename = sys.argv[1]
a = cPickle.load(file(filename))
print a
---------------------------------------------------------------------
So what would you suggest ? Can I hack Numeric to assume non-native
32 bit integer numbers ?
Many thanks for any help,
Johannes
It might be worth posting to the Numeric mailing list, mirrored at
http://news.gmane.org/gmane.comp.python.numeric.general
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