On Tue, Jun 5, 2012 at 12:15 PM, Thouis Jones wrote:
> On Mon, Jun 4, 2012 at 11:49 PM, Nathaniel Smith wrote:
>> On Mon, Jun 4, 2012 at 10:00 PM, Thouis (Ray) Jones wrote:
>>> On Mon, Jun 4, 2012 at 4:27 PM, Thouis (Ray) Jones wrote:
>>>> I could look into this.
On Mon, Jun 4, 2012 at 11:49 PM, Nathaniel Smith wrote:
> On Mon, Jun 4, 2012 at 10:00 PM, Thouis (Ray) Jones wrote:
>> On Mon, Jun 4, 2012 at 4:27 PM, Thouis (Ray) Jones wrote:
>>> I could look into this. There are only ~10 places the code generates
>>> this error, so it should be a pretty min
On Fri, May 25, 2012 at 2:07 PM, Thouis Jones wrote:
> I don't seem to be able to reproduce with just a.max(0) or
> np.array(a.max(0), np.float), but since it seems to be very unstable
> to other changes in the code, I'll keep trying to find out if I can
> make those simpl
On Fri, May 25, 2012 at 1:52 PM, Nathaniel Smith wrote:
> On Fri, May 25, 2012 at 12:46 PM, Thouis (Ray) Jones wrote:
>> I'm seeing some strange behavior from .max() on a reshaped array in
>> the current master, and wanted to raise it here to make sure it's not
>> something uniquely broken in my
I recently had need of tracing numpy data allocation/deallocation. I
was unable to find a simple way to do so, and so ended up putting the
code below into ndarraytypes.h to allow me to trace allocations. A
key part is that this jumps back into python, so I can inspect the
stack and find out where
On Fri, Dec 2, 2011 at 18:53, Charles R Harris
wrote:
> After sleeping on this, I think an object array in this situation would be
> the better choice and wouldn't result in lost information. This might change
> the behavior of
> some functions though, so would need testing.
I tried to come up w
On Thu, Dec 1, 2011 at 16:29, Benjamin Root wrote:
> Does the same problem occur if -345 comes after "ABC"?
Yes.
>>> np.array(list(reversed([-345,4,2,'ABC'])))
array(['ABC', '2', '4', '-34'],
dtype='|S3')
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On Thu, Dec 1, 2011 at 15:47, Pierre Haessig wrote:
> Le 01/12/2011 14:52, Thouis (Ray) Jones a écrit :
>> Is this expected behavior?
>>
> np.array([-345,4,2,'ABC'])
>> array(['-34', '4', '2', 'ABC'], dtype='|S3')
>>
>>
> With my numpy 1.5.1, I got indeed a different result:
>
> In [1]: np.arr
