On Mon, Apr 29, 2013 at 2:10 PM, Andrew Giessel <
andrew_gies...@hms.harvard.edu> wrote:
> Matthew: Thanks for the link to array order discussion.
>
> Any more thoughts on Phil's slice() function?
>
>
>
I rather like Phil's solution. Just some caveats. Will it always return
views or copies? It
Matthew: Thanks for the link to array order discussion.
Any more thoughts on Phil's slice() function?
On Fri, Apr 26, 2013 at 4:50 PM, Gael Varoquaux <
gael.varoqu...@normalesup.org> wrote:
> On Thu, Apr 25, 2013 at 08:10:32PM +0100, Robert Kern wrote:
> > In my opinion, duplicating functional
On Thu, Apr 25, 2013 at 08:10:32PM +0100, Robert Kern wrote:
> In my opinion, duplicating functionality under different aliases just
> so people can supposedly find things without reading the documentation
> is not a viable strategy for building out an API.
+1. It's been my experience over and ove
Hi,
On Fri, Apr 26, 2013 at 10:02 AM, Andrew Giessel
wrote:
> I like this, thank you Phil.
>
> From what I can see, the ordering of the returned slices when you use more
> than one axis (ie: slices(a, [1,2]), increments the last axis fastest. Does
> this makes sense based on the default ordering
I like this, thank you Phil.
>From what I can see, the ordering of the returned slices when you use more
than one axis (ie: slices(a, [1,2]), increments the last axis fastest.
Does this makes sense based on the default ordering of, say, nditer()? I
know that C-order (row major) and Fortran order
I didn't find the rollaxis solution particularly obvious and also had to
think about what rollaxis did before understanding its usefulness for
iteration.
Now that I've understood it, I'm +1 for the statement that, as it stands,
the proposed iteraxis method doesn't add enough to warrant its inclusio
the "new" documentation
http://stackoverflow.com/questions/1589706/iterating-over-arbitrary-dimension-of-numpy-array
second answer, 1st answer is what I usually use
search term "[numpy] iterate over axis"
Josef
On Fri, Apr 26, 2013 at 9:37 AM, Jason Grout
wrote:
> On 4/26/13 6:33 AM, Robert K
On 4/26/13 6:33 AM, Robert Kern wrote:
> In any case, whether you put the documentation in the rollaxis()
> docstring or in one of the indexing/iteration sections, or
> (preferably) both, I strongly encourage you to do that first and see
> how it goes before adding a new alias.
+1 (for what it's w
On Fri, Apr 26, 2013 at 12:26 PM, Andrew Giessel
wrote:
> I agree with Charles that rollaxis() isn't immediately intuitive.
>
> It seems to me that documentation like this doesn't belong in rollaxis() but
> instead wherever people talk about indexing and/or iterating over an array.
> Nothing about
I agree with Charles that rollaxis() isn't immediately intuitive.
It seems to me that documentation like this doesn't belong in rollaxis()
but instead wherever people talk about indexing and/or iterating over an
array. Nothing about the iteration depends on rollaxis(), rollaxis is
just giving yo
On Thu, Apr 25, 2013 at 9:04 PM, Charles R Harris
wrote:
> After thinking about it, I'm in favor of this small function. Rollaxis takes
> a bit of thought and document reading to figure out how to use it, whereas
> this function covers a common use with an easy to understand API.
It seems to me
On Thu, 2013-04-25 at 14:04 -0600, Charles R Harris wrote:
>
>
> On Thu, Apr 25, 2013 at 1:51 PM, wrote:
> On Thu, Apr 25, 2013 at 3:40 PM, Robert Kern
> wrote:
> > On Thu, Apr 25, 2013 at 8:21 PM, Andrew Giessel
> > wrote:
> >> I respect this opinion.
On Thu, Apr 25, 2013 at 1:51 PM, wrote:
> On Thu, Apr 25, 2013 at 3:40 PM, Robert Kern
> wrote:
> > On Thu, Apr 25, 2013 at 8:21 PM, Andrew Giessel
> > wrote:
> >> I respect this opinion. However (and maybe this is legacy), while
> reading
> >> through the numeric.py source file, I was surpris
On Thu, Apr 25, 2013 at 3:40 PM, Robert Kern wrote:
> On Thu, Apr 25, 2013 at 8:21 PM, Andrew Giessel
> wrote:
>> I respect this opinion. However (and maybe this is legacy), while reading
>> through the numeric.py source file, I was surprised at how short many of the
>> functions are, generally.
On Thu, Apr 25, 2013 at 8:21 PM, Andrew Giessel
wrote:
> I respect this opinion. However (and maybe this is legacy), while reading
> through the numeric.py source file, I was surprised at how short many of the
> functions are, generally. Functions like ones() and zeros() are pretty
> simple wrap
I respect this opinion. However (and maybe this is legacy), while reading
through the numeric.py source file, I was surprised at how short many of
the functions are, generally. Functions like ones() and zeros() are pretty
simple wrappers which call empty() and then copy over values.
FWIW, I had
On Thu, Apr 25, 2013 at 6:54 PM, Matthew Brett wrote:
> Hi,
>
> On Thu, Apr 25, 2013 at 10:42 AM, Robert Kern wrote:
>> On Thu, Apr 25, 2013 at 6:30 PM, Matthew Brett
>> wrote:
>>> So the decision has to be based on some estimate of:
>>>
>>> 1) Cost for adding a new function to the namespace
>
Hi,
On Thu, Apr 25, 2013 at 10:42 AM, Robert Kern wrote:
> On Thu, Apr 25, 2013 at 6:30 PM, Matthew Brett
> wrote:
>> Hi,
>>
>> On Thu, Apr 25, 2013 at 10:14 AM, Robert Kern wrote:
>>> On Wed, Apr 24, 2013 at 10:37 PM, andrew giessel
>>> wrote:
Hello all-
A while back I emailed
On Thu, Apr 25, 2013 at 6:30 PM, Matthew Brett wrote:
> Hi,
>
> On Thu, Apr 25, 2013 at 10:14 AM, Robert Kern wrote:
>> On Wed, Apr 24, 2013 at 10:37 PM, andrew giessel
>> wrote:
>>> Hello all-
>>>
>>> A while back I emailed the list about function for the numpy namespace,
>>> iteraxis(), which
Hi,
On Thu, Apr 25, 2013 at 10:14 AM, Robert Kern wrote:
> On Wed, Apr 24, 2013 at 10:37 PM, andrew giessel
> wrote:
>> Hello all-
>>
>> A while back I emailed the list about function for the numpy namespace,
>> iteraxis(), which allows you to generalize the default iteration behavior of
>> nump
On Wed, Apr 24, 2013 at 10:37 PM, andrew giessel
wrote:
> Hello all-
>
> A while back I emailed the list about function for the numpy namespace,
> iteraxis(), which allows you to generalize the default iteration behavior of
> numpy arrays over any axis.
>
> I've implemented this function more clea
Hello all-
A while back I emailed the list about function for the numpy namespace,
iteraxis(), which allows you to generalize the default iteration behavior
of numpy arrays over any axis.
I've implemented this function more cleanly and the pull request is here:
https://github.com/numpy/numpy/pull
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