On Mon, Apr 27, 2009 at 1:12 PM, Whitcomb, Mr. Tim <
tim.whitc...@nrlmry.navy.mil> wrote:
> I'm trying to install NumPy 1.3.0 on an IBM Power6. I can build and
> install successfully, but when I try to execute the unit test suite it
> crashes with a MemoryError (with no additional information on the error
> - just the traceback). The failure occurs in test_roundtrip in
> numpy/lib/tests/test_format.py and the following snippet reproduces the
> error:
>
> ----------------------------------
> import numpy as np
> from cStringIO import StringIO
> from numpy.lib import format
>
> f = StringIO()
> a = np.array([], dtype='object')
> format.write_array(f, a)
> f2 = StringIO(f.getvalue())
> a2 = format.read_array(f2)
>
> print('%s %s' % (a, a2))
> -----------------------------------
>
> On the AIX/PPC install, this crashes with:
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "crash_numpy.py", line 10, in <module>
> a2 = format.read_array(f2)
> File
> "$HOME/.local/python/lib/python2.5/site-packages/numpy/lib/format.py",
> line 362, in read_array
> array = cPickle.load(fp)
> MemoryError
>
I think this means out of memory, which is probably not correct. What
happens if you simply pickle and object array? Something like
In [1]: import cPickle
In [2]: a = np.array([], dtype='object')
In [3]: cPickle.dump(a,open('foo.pkl','w'))
In [4]: b = cPickle.load(open('foo.pkl','r'))
In [5]: b
Out[5]: array([], dtype=object)
If that fails, try it using pickle instead of cPickle, then with a non-empty
object array like a = np.array([None,None], dtype='object')
Chuck
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