>>> Yep, that'd be a good idea. Want to write a patch? :-)
>>
>> https://github.com/numpy/numpy/pull/440
>
> Thinking about the other thread, and the 'number of elements' check, I
> noticed this:
>
> In [51]: np.__version__
> Out[51]: '1.6.1'
>
> In [52]: r4 = range(4)
>
> In [53]: r3 = range(
Hi,
On Thu, Sep 13, 2012 at 11:31 AM, Matthew Brett wrote:
> On Wed, Sep 12, 2012 at 4:19 PM, Nathaniel Smith wrote:
>> On Wed, Sep 12, 2012 at 2:46 PM, Matthew Brett
>> wrote:
>>> Hi,
>>>
>>> I just noticed that this works for numpy 1.6.1:
>>>
>>> In [36]: np.concatenate(([2, 3], [1]), 1)
>>>
>>
>>
>> This is expected behavior. It's how the concatenate Python function
>> manages to handle axis=None to flatten the arrays before concatenation.
>> This has been in NumPy since 1.0 and should not be changed without
>> deprecation warnings which I am -0 on.
>>
>> Now, it is true th
Hi,
On Thu, Sep 13, 2012 at 3:01 PM, Travis Oliphant wrote:
>
> On Sep 13, 2012, at 8:40 AM, Nathaniel Smith wrote:
>
>> On Thu, Sep 13, 2012 at 11:12 AM, Matthew Brett
>> wrote:
>>> Hi,
>>>
>>> While writing some tests for np.concatenate, I ran foul of this code:
>>>
>>>if (axis >= NPY_MAX
On Thu, Sep 13, 2012 at 6:39 PM, Warren Weckesser
wrote:
> I would expect an error, consistent with the behavior when 1 < axis < 32.
In that case, you are hitting the dimension limit.
np.concatenate((a,b), axis=31)
ValueError: bad axis1 argument to swapaxes
Where axis=32, axis=3500, axis=None a
On Sep 13, 2012, at 11:39 AM, Warren Weckesser wrote:
>
>
> On Thu, Sep 13, 2012 at 9:01 AM, Travis Oliphant wrote:
>
> On Sep 13, 2012, at 8:40 AM, Nathaniel Smith wrote:
>
> > On Thu, Sep 13, 2012 at 11:12 AM, Matthew Brett
> > wrote:
> >> Hi,
> >>
> >> While writing some tests for np.co
On Thu, Sep 13, 2012 at 9:01 AM, Travis Oliphant wrote:
>
> On Sep 13, 2012, at 8:40 AM, Nathaniel Smith wrote:
>
> > On Thu, Sep 13, 2012 at 11:12 AM, Matthew Brett
> wrote:
> >> Hi,
> >>
> >> While writing some tests for np.concatenate, I ran foul of this code:
> >>
> >>if (axis >= NPY_MAXD
On Sep 13, 2012, at 8:40 AM, Nathaniel Smith wrote:
> On Thu, Sep 13, 2012 at 11:12 AM, Matthew Brett
> wrote:
>> Hi,
>>
>> While writing some tests for np.concatenate, I ran foul of this code:
>>
>>if (axis >= NPY_MAXDIMS) {
>>ret = PyArray_ConcatenateFlattenedArrays(narrays, arr
On Thu, Sep 13, 2012 at 11:12 AM, Matthew Brett wrote:
> Hi,
>
> While writing some tests for np.concatenate, I ran foul of this code:
>
> if (axis >= NPY_MAXDIMS) {
> ret = PyArray_ConcatenateFlattenedArrays(narrays, arrays, NPY_CORDER);
> }
> else {
> ret = PyArray_Co
Hi,
On Wed, Sep 12, 2012 at 10:24 PM, Ondřej Čertík wrote:
> Hi Matt,
>
> On Wed, Sep 12, 2012 at 1:27 PM, Travis Oliphant wrote:
>
> Is this intended? Is there a performance reason to keep the same
> strides in 1.7.0?
I believe that this could be because in 1.7.0, NumPy w
On Wed, Sep 12, 2012 at 4:19 PM, Nathaniel Smith wrote:
> On Wed, Sep 12, 2012 at 2:46 PM, Matthew Brett
> wrote:
>> Hi,
>>
>> I just noticed that this works for numpy 1.6.1:
>>
>> In [36]: np.concatenate(([2, 3], [1]), 1)
>> Out[36]: array([2, 3, 1])
>>
>> but the beta release branch:
>>
>> In
Hi,
While writing some tests for np.concatenate, I ran foul of this code:
if (axis >= NPY_MAXDIMS) {
ret = PyArray_ConcatenateFlattenedArrays(narrays, arrays, NPY_CORDER);
}
else {
ret = PyArray_ConcatenateArrays(narrays, arrays, axis);
}
in multiarraymodule.c
So
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