On Tue, Sep 9, 2014 at 8:52 PM, Charles R Harris
wrote:
> Hi All,
>
> I'm in the midst of implementing the '@' operator (PEP 465), and there are
> some behaviors that are unspecified by the PEP.
>
> Should the operator accept array_like for one of the arguments?
I would be mildly disappointed if
Hi All,
I'm in the midst of implementing the '@' operator (PEP 465), and there are
some behaviors that are unspecified by the PEP.
1. Should the operator accept array_like for one of the arguments?
2. Does it need to handle __numpy_ufunc__, or will __array_priority__
serve?
3. Do we
On 09/09/14 20:08, Nathaniel Smith wrote:
> There's also another reason why generator decisions should be part of
> the RandomState object itself: we may want to change the distribution
> methods themselves over time (e.g., people have been complaining for a
> while that we use a suboptimal method
On 8 Sep 2014 14:43, "Robert Kern" wrote:
>
> On Mon, Sep 8, 2014 at 6:05 PM, Pierre-Andre Noel
> wrote:
> > > I think we could add new generators to NumPy though,
> > > perhaps with a keyword to control the algorithm (defaulting to the
> > current
> > > Mersenne Twister).
> >
> > Why not do s
Hi!
I want to use the OPT/FOPT environment viariables to set compiler flags
when compiling numpy. However it seems that they get ignored under
python3. Using Ubuntu 14.04 and numpy 1.9.0, I did the following:
>export OPT="-march=native"
>export FOPT = "-march=native"
> python setup.py build
On Tue, Sep 9, 2014 at 8:30 AM, wrote:
>
>
>
> On Tue, Sep 9, 2014 at 5:42 AM, Stefan Otte wrote:
>
>> Hey,
>>
>> @Josef, I wasn't aware of `bmat` and `np.asarray(np.bmat())` does
>> basically what I want and what I'm already using.
>>
>
> I never needed any tetris or anything similar except
On Tue, Sep 9, 2014 at 5:42 AM, Stefan Otte wrote:
> Hey,
>
> @Josef, I wasn't aware of `bmat` and `np.asarray(np.bmat())` does
> basically what I want and what I'm already using.
>
I never needed any tetris or anything similar except for the matched block
version.
Just to point out two mor
Hey,
@Josef, I wasn't aware of `bmat` and `np.asarray(np.bmat())` does
basically what I want and what I'm already using.
Regarding the Tetris problem: that never happened to me, but stack, as
Josef pointed out, can handle that already :)
I like the idea of removing the redundant square brack
