Well, thanks everybody for such a quick help!! I just couldn't imagine what could arise this difference.
1e-15 is enough precision for what I will be doing, but was just curious. Anyway, this 'deepcopy' really surprised me. I have now looked for it and I think I get an idea of it, though I wouldn't expect this difference in behavior to happen. From "my logical" point of view a copy is a copy, and if I find a method called copy() I can only expect it to...copy (whether I am copying compound or "simple" objects!!). This comment is only for the shake of curiosity. I guess maybe it is just my lack of knowledge in programming in general and this is such a needed difference in copy behavior. On Mon, Apr 20, 2009 at 7:21 PM, John Gleeson <jdglee...@mac.com> wrote: > > On 2009-04-20, at 10:04 AM, David Cournapeau wrote: > > > > > Yes, it is legitimate and healthy to worry about the difference - but > > the surprising thing really is the list behavior when you are used to > > numerical computation :) And I maintain that the algorithms are not > > the same in both operations. > It's not? Would you please mind commenting this a little bit? > For once, the operation of using arrays > > on the data do not give the same data in both cases, you can see right > > away that m and ml are not the same, e.g. > I don't get what you mean > > > > > print ml - morig > > > > shows that the internal representation is not exactly the same. > > > > David > > The discrepancy David found in ml - morig vanishes if you change line > 118 > > morigl = ml[:] Sorry for this mistake :S > to > > import copy > morigl = copy.deepcopy(ml) > > There is still an issue with disagreement in minimum diff, but I'd bet > it is not a floating point precision problem. > > John > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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