[NumPy-Tickets] [NumPy] #1411: Array reshape bug

[NumPy Trac]

#1411: Array reshape bug
---------------------------------------------------+------------------------
 Reporter:  Han                                    |       Owner:  somebody
     Type:  defect                                 |      Status:  new     
 Priority:  normal                                 |   Milestone:          
Component:  numpy.core                             |     Version:  1.3.0   
 Keywords:  reshape, overflow, unpropagated error  |  
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 (See also: http://bugs.python.org/issue6562 -- might be related?)

 When reshaping a flat ndarray with a (mistaken) 64-bits long, an
 OverflowError will be generated in the C layer, but not propagated
 to the Python layer. This error can then be caught later on, in a totally
 unrelated piece of code.

 {{{
 >>> from __future__ import with_statement
 >>> import sys; sys.version
 '2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310 32 bit  Intel)]'
 >>> import threading
 >>> import numpy as np
 >>> # needing this to reproduce the error, but it can
 ... # also be reproduced in other ways
 ... lock = threading.RLock()
 >>> # creating a flat array
 ... arr = np.arange(10)
 >>> # reshaping the array, but mistakenly using a 64-bit integer
 ... arr_shaped = arr.reshape(1<<63)
 >>> # all seems to go well up to this point..
 ... with lock:
 ...     print "done!"
 ...
 C:\Python25\lib\threading.py:697: RuntimeWarning: tp_compare didn't return
 -1 or
  -2 for exception
 Traceback (most recent call last):
   File "<stdin>", line 2, in <module>
   File "c:\python25\lib\threading.py", line 94, in acquire
     me = currentThread()
   File "c:\python25\lib\threading.py", line 697, in currentThread
     return _active[_get_ident()]
 OverflowError: long int too large to convert to int
 }}}

 Other ways to reproduce the OverflowError after creating arr_shaped:

 {{{
 >>> print arr_shaped
 >>> import <anything>
 >>> arr_shaped + 10 # or other operations
 }}}

 I also tested it on Python 2.6, with similar results.

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1411>
NumPy <http://projects.scipy.org/numpy>
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