On Tue, Apr 30, 2013 at 8:08 PM, Yaroslav Halchenko wrote:
> could anyone on 32bit system with fresh numpy (1.7.1) test following:
>
> > wget -nc http://www.onerussian.com/tmp/data.npy ; python -c 'import
> numpy as np; data1 = np.load("/tmp/data.npy"); print
> np.sum(data1[1,:,0,1]) - np.sum(dat
Hi,
On Tue, Apr 30, 2013 at 9:16 PM, Matthew Brett wrote:
> Hi,
>
> On Tue, Apr 30, 2013 at 8:08 PM, Yaroslav Halchenko
> wrote:
>> could anyone on 32bit system with fresh numpy (1.7.1) test following:
>>
>>> wget -nc http://www.onerussian.com/tmp/data.npy ; python -c 'import numpy
>>> as np; d
On Apr 30, 2013, at 6:37 PM, Benjamin Root wrote:
> I can not think of any reason not to include these functions in v1.8.
+1
> Of course, the documentation for discussed before: np.minmax(). My thinking
> is that it would return a 2xN array
How about a tuple: (min, max)?
-Chris
Hi,
On Tue, Apr 30, 2013 at 8:08 PM, Yaroslav Halchenko
wrote:
> could anyone on 32bit system with fresh numpy (1.7.1) test following:
>
>> wget -nc http://www.onerussian.com/tmp/data.npy ; python -c 'import numpy as
>> np; data1 = np.load("/tmp/data.npy"); print np.sum(data1[1,:,0,1]) -
>> np
could anyone on 32bit system with fresh numpy (1.7.1) test following:
> wget -nc http://www.onerussian.com/tmp/data.npy ; python -c 'import numpy as
> np; data1 = np.load("/tmp/data.npy"); print np.sum(data1[1,:,0,1]) -
> np.sum(data1, axis=1)[1,0,1]'
0.0
because unfortunately it seems on fr
On 1 May 2013 03:36, Benjamin Root wrote:
> There is one other non-trivial function that have been discussed before:
> np.minmax(). My thinking is that it would return a 2xN array (where N is
> whatever size of the result that would be returned if just np.min() was
> used). This would allow one
Hi all!
I have written my application[1] for *Performance parity between numpy
arrays and Python scalars[2]. *It would be a great help if you view it.
Does it look achievable and deliverable according to the project.
[1]
http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/arinkverma
Currently, I am in the process of migrating some co-workers from Matlab and
IDL, and the number one complaint I get is that numpy has nansum() but no
nanmean() and nanstd(). While we do have an alternative in the form of
masked arrays, most of these people are busy enough trying to port their
exis
On Tue, Apr 30, 2013 at 4:02 PM, Pauli Virtanen wrote:
> 30.04.2013 22:37, Nathaniel Smith kirjoitti:
> [clip]
>> How do you plan to go about this? The obvious option of just calling
>> scipy.sparse.issparse() on ufunc entry raises some problems, since
>> numpy can't depend on or even import scipy
Hi,
On Sat, Apr 6, 2013 at 3:15 PM, Matthew Brett wrote:
> Hi,
>
> On Sat, Apr 6, 2013 at 1:35 PM, Ralf Gommers wrote:
>>
>>
>>
>> On Sat, Apr 6, 2013 at 7:22 PM, Matthew Brett
>> wrote:
>>>
>>> Hi,
>>>
>>> On Sat, Apr 6, 2013 at 1:51 AM, Ralf Gommers
>>> wrote:
>>> >
>>> >
>>> >
>>> > On Sat,
30.04.2013 22:37, Nathaniel Smith kirjoitti:
[clip]
> How do you plan to go about this? The obvious option of just calling
> scipy.sparse.issparse() on ufunc entry raises some problems, since
> numpy can't depend on or even import scipy, and we might be reluctant
> to add such a special case for wh
On Tue, Apr 30, 2013 at 1:37 PM, Nathaniel Smith wrote:
> On Tue, Apr 30, 2013 at 3:19 PM, Blake Griffith
> wrote:
> > Hello, I'm writing a GSoC proposal, mostly concerning SciPy, but it
> involves
> > a few changes to NumPy.
> > The proposal is titled: Improvements to the sparse package of Scip
On Tue, Apr 30, 2013 at 3:19 PM, Blake Griffith
wrote:
> Hello, I'm writing a GSoC proposal, mostly concerning SciPy, but it involves
> a few changes to NumPy.
> The proposal is titled: Improvements to the sparse package of Scipy: support
> for bool dtype and better interaction with NumPy
> and ca
Hello, I'm writing a GSoC proposal, mostly concerning SciPy, but it
involves a few changes to NumPy.
The proposal is titled: Improvements to the sparse package of Scipy:
support for bool dtype and better interaction with NumPy
and can be found on my GitHub:
https://github.com/cowlicks/GSoC-proposal
hmm -- I suppose one of us should post an issue on github -- then ask for
it ti be fixed before 1.8 ;-)
I'll try to get to the issue if no one beats me to it -- got to run now...
-Chris
On Tue, Apr 30, 2013 at 5:35 AM, Richard Hattersley
wrote:
> +1 for getting rid of this inconsistency
>
>
+1 for getting rid of this inconsistency
We've hit this with Iris (a met/ocean analysis package - see github), and
have had to add several workarounds.
On 19 April 2013 16:55, Chris Barker - NOAA Federal
wrote:
> Hi folks,
>
> In [264]: np.__version__
> Out[264]: '1.7.0'
>
> I just noticed that
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