[Numpy-discussion] Numpy float precision vs Python list float issue
Mon Apr 20 14:50:09 CDT 2009
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 <firstname.lastname@example.org> 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
> morigl = ml[:]
Sorry for this mistake :S
> 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.
> Numpy-discussion mailing list
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