On 6/19/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Go for it.
Done, thanks.
Cheers,
f
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Fernando Perez wrote:
> Question
>
>
> any objection if I commit this? Since I don't really touch the
> codebase often, I'd rather ask the real core people. I also don't
> know if it's really the right thing to do, I just tabbed into the
> object and picked what seemed to be the most r
Bug
===
In [8]: N.info(N.ones(3))
class: ndarray
shape: (3,)
strides: (8,)
itemsize: 8
aligned: True
contiguous: True
fortran: True
---
TypeError Traceback (most recent call last)
/home/
On 6/19/07, Jon Wright <[EMAIL PROTECTED]> wrote:
Dear numpy experts,
I see from the docs that there seem to be 3 sorting algorithms for array
data (quicksort, mergesort and heapsort). After hearing a rumour about
radix sorts and floats I google'd and now I'm wondering about a radix
sort for nu
Dear numpy experts,
I see from the docs that there seem to be 3 sorting algorithms for array
data (quicksort, mergesort and heapsort). After hearing a rumour about
radix sorts and floats I google'd and now I'm wondering about a radix
sort for numpy (and Numeric) scalars? See:
http://www.stereo
Stefan van der Walt schrieb:
> http://buildbot.scipy.org
>
> If your platform is not currently on the list, please consider
> volunteering a machine as a build slave. This machine will be
> required to run the buildbot client, and to build a new version of
> numpy whenever changes are made to the
Sturla Molden schrieb:
>
> >>> x = numpy.arange(100).reshape((1,10,10))
>
> >>> x[0,:,numpy.arange(5)].shape
> (5, 10)
>
> >>> x[:,:,numpy.arange(5)].shape
> (1, 10, 5)
>
>
> It looks like a bug that needs to be squashed.
>
> S.M.
And you already had me convinced ;-)
I'm still curious wh
>>> x = numpy.arange(100).reshape((1,10,10))
>>> x[0,:,numpy.arange(5)].shape
(5, 10)
>>> x[:,:,numpy.arange(5)].shape
(1, 10, 5)
It looks like a bug that needs to be squashed.
S.M.
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ht
On 6/19/2007 1:28 PM, Stefan van der Walt wrote:
>
> x = N.arange(100).reshape((10,10))
> x[:,N.arange(5)].shape
>
> should be (5, 10), while in reality it is (10, 5).
>>> y = numpy.arange(100).reshape((10,10))
>>> y[:,numpy.arange(5)].shape
(10,5)
>>> x = numpy.arange(100).reshape((1,10,10
On Tue, Jun 19, 2007 at 12:35:05PM +0200, Sturla Molden wrote:
> On 6/19/2007 12:14 PM, Sturla Molden wrote:
>
> > h[0,:,numpy.arange(14)] is a case of "sdvanced indexing". You can also
> > see that
> >
> > >>> h[0,:,[0,1,2,3,4,5,6,7,8,9,10,11,12,13]].shape
> > (14, 4)
>
> Another way to expla
On 6/19/2007 12:14 PM, Sturla Molden wrote:
> h[0,:,numpy.arange(14)] is a case of "sdvanced indexing". You can also
> see that
>
> >>> h[0,:,[0,1,2,3,4,5,6,7,8,9,10,11,12,13]].shape
> (14, 4)
Another way to explain this is that numpy.arange(14) and
[0,1,2,3,4,5,6,7,8,9,10,11,12,13] is a sequ
On 6/19/2007 12:19 PM, Sven Schreiber wrote:
> To be more specific, I would expect shape==(4,14).
>>> h = numpy.zeros((1,4,14))
>>> h[0,:,numpy.arange(14)].shape
(14, 4)
>>> h[0,:,:].shape
(4, 14)
>>>
h[0,:,numpy.arange(14)] is a case of "sdvanced indexing". You can also
see that
>>> h[
Sven Schreiber schrieb:
> Tom K. schrieb:
> h = zeros((1, 4, 100))
> h[0,:,arange(14)].shape
>> (14, 4)
>>
>
> After reading section 3.4.2.1 of the numpy book, I also still don't
> expect this result. So if it's not a bug, I'd be glad if some expert
> could explain why not.
>
To be more
On Tue, Jun 19, 2007 at 05:06:42PM +0900, David Cournapeau wrote:
> Robert Kern wrote:
> > Stefan van der Walt wrote:
> >> On Fri, Jun 15, 2007 at 03:44:37PM -0400, David M. Cooke wrote:
> I meet a problem when I installed numpy. I installed numpy by the command
> "python setup.py install
Robert Kern wrote:
> Stefan van der Walt wrote:
>> On Fri, Jun 15, 2007 at 03:44:37PM -0400, David M. Cooke wrote:
I meet a problem when I installed numpy. I installed numpy by the command
"python setup.py install". Then I tested it by "python -c 'import numpy;
numpy.test()'". But it
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