Andreas Klöckner wrote:
>> [snip]
>> a += 3 is really equivalent to a = a+3.
>
> Except when it isn't.
right -- it isn't the same. In fact, if I were king (or BDFL), you
wouldn't be able to use += with immutable types, but I'm not ;-)
One of the reasons the augmented assignment operators where
On Dienstag 25 März 2008, Nadav Horesh wrote:
> scalars are immutable objects in python. Thus the += (and alike) are "fake":
Again, thanks for the explanation. IMHO, whether or not they are fake is an
implementation detail. You shouldn't have to know Python's guts to be able to
use Numpy success
-הודעה מקורית-
מאת: [EMAIL PROTECTED] בשם Andreas Kl?ckner
נשלח: ג 25-מרץ-08 06:42
אל: Discussion of Numerical Python
נושא: Re: [Numpy-discussion] __iadd__(ndarray, ndarray)
On Montag 24 M?rz 2008, St?fan van der Walt wrote:
> > I think this is highly undesirable and should be
On Dienstag 25 März 2008, Travis E. Oliphant wrote:
> > Question: If it's a known trap, why not change it?
>
> It also has useful applications. Also, it can only happen at with a
> bump in version number to 1.1
I'm not trying to make the functionality go away. I'm arguing that
int_array += downc
Andreas Klöckner wrote:
> On Montag 24 März 2008, Stéfan van der Walt wrote:
>
>>> I think this is highly undesirable and should be fixed, or at least
>>> warned about. Opinions?
>>>
>> I know the result is surprising, but it follows logically. You have
>> created two integers in memory
On Montag 24 März 2008, Stéfan van der Walt wrote:
> > I think this is highly undesirable and should be fixed, or at least
> > warned about. Opinions?
>
> I know the result is surprising, but it follows logically. You have
> created two integers in memory, and now you add 0.2 and 0.1 to both --
>
Hi Andreas
On Mon, Mar 24, 2008 at 7:28 PM, Andreas Klöckner
<[EMAIL PROTECTED]> wrote:
> I just got tripped up by this behavior in Numpy 1.0.4:
>
> >>> u = numpy.array([1,3])
> >>> v = numpy.array([0.2,0.1])
> >>> u+=v
> >>> u
> array([1, 3])
> >>>
>
> I think this is highly undesirable a
Hi all,
I just got tripped up by this behavior in Numpy 1.0.4:
>>> u = numpy.array([1,3])
>>> v = numpy.array([0.2,0.1])
>>> u+=v
>>> u
array([1, 3])
>>>
I think this is highly undesirable and should be fixed, or at least warned
about. Opinions?
Andreas
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