On Fri, Jan 6, 2012 at 9:15 AM, Ralf Gommers
wrote:
>
>
> On Tue, Dec 20, 2011 at 9:28 PM, Ralf Gommers
> wrote:
>>
>>
>>
>> On Tue, Dec 20, 2011 at 3:18 PM, Charles R Harris
>> wrote:
>>>
>>> Hi Ralf,
>>>
>>> On Mon, Dec 5, 2011 at 12:43 PM, Ralf Gommers
>>> wrote:
Hi all,
>>>
>>> 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 Sat, Dec 24, 2011 at 3:11 AM, xantares 09
>> wrote:
>> >
On Tue, Dec 20, 2011 at 9:28 PM, Ralf Gommers
wrote:
>
>
> On Tue, Dec 20, 2011 at 3:18 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>> Hi Ralf,
>>
>> On Mon, Dec 5, 2011 at 12:43 PM, Ralf Gommers <
>> ralf.gomm...@googlemail.com> wrote:
>>
>>> Hi all,
>>>
>>> It's been a little ov
Dear numpy community,
I'm trying to create an array of type object.
A = empty(9, dtype=object)
A[ array(0,1,2) ] = MyObject(1)
A[ array(3,4,5) ] = MyObject(2)
A[ array(6,7,8) ] = MyObject(3)
This has worked well until MyObject has gotten an __getitem__ method. Now
python (as it is usually suppo
On Wed, 04 Jan 2012 12:29:36 +0100, Derek Homeier wrote:
> On 04.01.2012, at 5:10AM, questions anon wrote:
>
>> Thanks for your responses but I am still having difficuties with this
>> problem. Using argmax gives me one very large value and I am not sure
>> what it is.
it is the index in the fla
