>>>
>>> No. All of the PyTypeObject objects for the NumPy array scalars are
>>> explicitly part of the NumPy C API so you have no choice but to depend
>>> on that (to get the best performance). If you want to ONLY check for
>>> int64 at the C API level, I did a bit of digging and the relevant type
On Wed, Jan 4, 2012 at 5:22 AM, xantares 09 wrote:
>
>
>> From: wesmck...@gmail.com
>> Date: Sat, 24 Dec 2011 19:51:06 -0500
>
>> To: numpy-discussion@scipy.org
>> Subject: Re: [Numpy-discussion] PyInt and Numpy's int64 conversion
>>
>> On S
> From: wesmck...@gmail.com
> Date: Sat, 24 Dec 2011 19:51:06 -0500
> To: numpy-discussion@scipy.org
> Subject: Re: [Numpy-discussion] PyInt and Numpy's int64 conversion
>
> On Sat, Dec 24, 2011 at 3:11 AM, xantares 09 wrote:
> >
> >
> >> From: wes
On Sat, Dec 24, 2011 at 3:11 AM, xantares 09 wrote:
>
>
>> From: wesmck...@gmail.com
>> Date: Fri, 23 Dec 2011 12:31:45 -0500
>> To: numpy-discussion@scipy.org
>> Subject: Re: [Numpy-discussion] PyInt and Numpy's int64 conversion
>
>>
>> On F
> From: wesmck...@gmail.com
> Date: Fri, 23 Dec 2011 12:31:45 -0500
> To: numpy-discussion@scipy.org
> Subject: Re: [Numpy-discussion] PyInt and Numpy's int64 conversion
>
> On Fri, Dec 23, 2011 at 4:37 AM, xantares 09 wrote:
> > Hi,
> >
> > I'
On Fri, Dec 23, 2011 at 4:37 AM, xantares 09 wrote:
> Hi,
>
> I'm using Numpy from the C python api side while tweaking my SWIG interface
> to work with numpy array types.
> I want to convert a numpy array of integers (whose elements are numpy's
> 'int64')
> The problem is that it this int64 type
Hi,
I'm using Numpy from the C python api side while tweaking my SWIG interface to
work with numpy array types.
I want to convert a numpy array of integers (whose elements are numpy's 'int64')
The problem is that it this int64 type is not compatible with the standard
python integer type:
I cann
