[Ironpython-users] IronPython, Daily Digest 12/27/2011

[no_reply at codeplex.com]

Hi ironpython,

Here's your Daily Digest of new issues for project "IronPython".

In today's digest:ISSUES

1. [New issue] Pickling Numpy arrays
2. [New comment] Pickling Numpy arrays
3. [New comment] Pickling Numpy arrays
4. [New comment] Pickling Numpy arrays

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ISSUES

1. [New issue] Pickling Numpy arrays
http://ironpython.codeplex.com/workitem/32007
User Hyang02116 has proposed the issue:

"When I pickle large Numpy arrays using IronPython [e.g. arrays that have 1 million elements], >99% of the numbers are recovered exactly when using Unpickle, but <1% of the entries  are quite different after loading the pickled value, and the differences seem larger than can be accounted for by simple floating point precision errors, e.g. -0.0241330987517 becomes -0.448629580028. I wonder if anyone else has experienced this."-----------------

2. [New comment] Pickling Numpy arrays
http://ironpython.codeplex.com/workitem/32007
User slide_o_mix has commented on the issue:

"Can you please add a simple test case so this can be reproduced and debugged."-----------------

3. [New comment] Pickling Numpy arrays
http://ironpython.codeplex.com/workitem/32007
User Hyang02116 has commented on the issue:

"import numpy, pickle

fname = "H:\\testfile"
fobj = open(fname, 'w')
old = numpy.zeros((1, 1))

old[0][0] = -0.0241330987517
pickle.dump(["h","a","y", old], fobj)
fobj.close()    

fobj = open(fname)
new = pickle.Unpickler(fobj).load() 
new = new[3]
fobj.close()

for i in range(1):
  if old[i][0] != new[i][0]:
    print str(i) + " " + str(old[i][0]) + " " + str(new[i][0])
    
"-----------------

4. [New comment] Pickling Numpy arrays
http://ironpython.codeplex.com/workitem/32007
User Hyang02116 has commented on the issue:

"Doing that, I get an old value of -0.02413309877517 and a new value of -0.448629580027"
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