On Thu, Apr 2, 2015 at 11:30 PM, Nathaniel Smith wrote:
> On Thu, Apr 2, 2015 at 6:35 PM, wrote:
>> (I thought about this because I was looking at accessing off-diagonal
>> elements, m2[np.arange(4), np.arange(4) + 1] )
>
> Psst: np.diagonal(m2, offset=1)
It was just an example (banded or toep
On Thu, Apr 2, 2015 at 6:35 PM, wrote:
> (I thought about this because I was looking at accessing off-diagonal
> elements, m2[np.arange(4), np.arange(4) + 1] )
Psst: np.diagonal(m2, offset=1)
--
Nathaniel J. Smith -- http://vorpus.org
___
NumPy-Discu
Hi,
On Thu, Apr 2, 2015 at 8:20 PM, Jaime Fernández del Río
wrote:
> On Thu, Apr 2, 2015 at 7:30 PM, Matthew Brett
> wrote:
>>
>> Hi,
>>
>> On Thu, Apr 2, 2015 at 6:09 PM, wrote:
>> > On Thu, Apr 2, 2015 at 8:02 PM, Eric Firing wrote:
>> >> On 2015/04/02 1:14 PM, Hanno Klemm wrote:
>> >>> Wel
On Thu, Apr 2, 2015 at 7:30 PM, Matthew Brett
wrote:
> Hi,
>
> On Thu, Apr 2, 2015 at 6:09 PM, wrote:
> > On Thu, Apr 2, 2015 at 8:02 PM, Eric Firing wrote:
> >> On 2015/04/02 1:14 PM, Hanno Klemm wrote:
> >>> Well, I have written quite a bit of code that relies on fancy
> >>> indexing, and I
On Thu, Apr 2, 2015 at 10:30 PM, Matthew Brett wrote:
> Hi,
>
> On Thu, Apr 2, 2015 at 6:09 PM, wrote:
>> On Thu, Apr 2, 2015 at 8:02 PM, Eric Firing wrote:
>>> On 2015/04/02 1:14 PM, Hanno Klemm wrote:
Well, I have written quite a bit of code that relies on fancy
indexing, and I thin
Hi,
On Thu, Apr 2, 2015 at 6:09 PM, wrote:
> On Thu, Apr 2, 2015 at 8:02 PM, Eric Firing wrote:
>> On 2015/04/02 1:14 PM, Hanno Klemm wrote:
>>> Well, I have written quite a bit of code that relies on fancy
>>> indexing, and I think the question, if the behaviour of the []
>>> operator should b
On Thu, Apr 2, 2015 at 9:09 PM, wrote:
> On Thu, Apr 2, 2015 at 8:02 PM, Eric Firing wrote:
>> On 2015/04/02 1:14 PM, Hanno Klemm wrote:
>>> Well, I have written quite a bit of code that relies on fancy
>>> indexing, and I think the question, if the behaviour of the []
>>> operator should be cha
On Thu, Apr 2, 2015 at 8:02 PM, Eric Firing wrote:
> On 2015/04/02 1:14 PM, Hanno Klemm wrote:
>> Well, I have written quite a bit of code that relies on fancy
>> indexing, and I think the question, if the behaviour of the []
>> operator should be changed has sailed with numpy now at version 1.9.
On 2015/04/02 1:14 PM, Hanno Klemm wrote:
> Well, I have written quite a bit of code that relies on fancy
> indexing, and I think the question, if the behaviour of the []
> operator should be changed has sailed with numpy now at version 1.9.
> Given the amount packages that rely on numpy, changing
---
**LAST CALL FOR SCIPY 2015 TALK AND POSTER SUBMISSIONS - EXTENSION TO 4/10*
---
> On 03 Apr 2015, at 00:04, Colin J. Williams wrote:
>
>
>
> On 02-Apr-15 4:35 PM, Eric Firing wrote:
>> On 2015/04/02 10:22 AM, josef.p...@gmail.com wrote:
>>> Swapping the axis when slices are mixed with fancy indexing was a
>>> design mistake, IMO. But not fancy indexing itself.
>> I'm not
On Thu, Apr 2, 2015 at 7:46 AM, David Cournapeau wrote:
>
>
> On Wed, Apr 1, 2015 at 7:43 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Wed, Apr 1, 2015 at 11:55 AM, Sturla Molden
>> wrote:
>>
>>> Charles R Harris wrote:
>>>
>>> > I'd be
>>> > interested in informatio
On 02-Apr-15 4:35 PM, Eric Firing wrote:
> On 2015/04/02 10:22 AM, josef.p...@gmail.com wrote:
>> Swapping the axis when slices are mixed with fancy indexing was a
>> design mistake, IMO. But not fancy indexing itself.
> I'm not saying there should be no fancy indexing capability; I am saying
> t
On 2015/04/02 10:22 AM, josef.p...@gmail.com wrote:
> Swapping the axis when slices are mixed with fancy indexing was a
> design mistake, IMO. But not fancy indexing itself.
I'm not saying there should be no fancy indexing capability; I am saying
that it should be available through a function or
On Thu, Apr 2, 2015 at 2:03 PM, Eric Firing wrote:
> On 2015/04/02 4:15 AM, Jaime Fernández del Río wrote:
>> We probably need more traction on the "should this be done?" discussion
>> than on the "can this be done?" one, the need for a reordering of the
>> axes swings me slightly in favor, but I
The distinction that boolean indexing has over the other 2 methods of
indexing is that it can guarantee that it references a position at most
once. Slicing and scalar indexes are also this way, hence why these methods
allow for in-place assignments. I don't see boolean indexing as an
extension of o
On Thu, Apr 2, 2015 at 11:03 AM, Eric Firing wrote:
> Fancy indexing is a horrible design mistake--a case of cleverness run
> amok. As you can read in the Numpy documentation, it is hard to
> explain, hard to understand, hard to remember.
Well put!
I also failed to correct predict your exampl
On 2015/04/02 4:15 AM, Jaime Fernández del Río wrote:
> We probably need more traction on the "should this be done?" discussion
> than on the "can this be done?" one, the need for a reordering of the
> axes swings me slightly in favor, but I mostly don't see it yet.
As a long-time user of numpy, a
On Thu, Apr 2, 2015 at 1:29 AM, Stephan Hoyer wrote:
> On Wed, Apr 1, 2015 at 7:06 AM, Jaime Fernández del Río <
> jaime.f...@gmail.com> wrote:
>
>> Is there any other package implementing non-orthogonal indexing aside
>> from numpy?
>>
>
> I think we can safely say that NumPy's implementation of
On Wed, Apr 1, 2015 at 7:43 PM, Charles R Harris
wrote:
>
>
> On Wed, Apr 1, 2015 at 11:55 AM, Sturla Molden
> wrote:
>
>> Charles R Harris wrote:
>>
>> > I'd be
>> > interested in information from anyone with experience in using such an
>> IDE
>> > and ideas of how Numpy might make using some
On Do, 2015-04-02 at 01:29 -0700, Stephan Hoyer wrote:
> On Wed, Apr 1, 2015 at 7:06 AM, Jaime Fernández del Río
> wrote:
> Is there any other package implementing non-orthogonal
> indexing aside from numpy?
>
>
> I think we can safely say that NumPy's implementation of broadcast
On Wed, Apr 1, 2015 at 7:06 AM, Jaime Fernández del Río <
jaime.f...@gmail.com> wrote:
> Is there any other package implementing non-orthogonal indexing aside from
> numpy?
>
I think we can safely say that NumPy's implementation of broadcasting
indexing is unique :).
The issue is that many other
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