On Thu, Apr 29, 2010 at 1:30 PM, Pauli Virtanen wrote:
> Wed, 28 Apr 2010 14:12:07 -0400, Alan G Isaac wrote:
> [clip]
> > Here is a related ticket that proposes a more explicit alternative:
> > adding a ``dot`` method to ndarray.
> > http://projects.scipy.org/numpy/ticket/1456
>
> I kind of like
On Thu, Apr 29, 2010 at 9:56 AM, Charles R Harris
wrote:
> It looks like the consensus is that zero should be returned. This is a
> change from current behaviour and that bothers me a bit. Here are some other
> oddities
>
> In [6]: nanmax([nan])
> Out[6]: nan
>
> In [7]: nanargmax([nan])
> Out[7]:
On Thu, Apr 29, 2010 at 12:56 PM, Charles R Harris
wrote:
>
>
> On Wed, Apr 28, 2010 at 11:56 AM, T J wrote:
>>
>> On Mon, Apr 26, 2010 at 10:03 AM, Charles R Harris
>> wrote:
>> >
>> >
>> > On Mon, Apr 26, 2010 at 10:55 AM, Charles R Harris
>> > wrote:
>> >>
>> >> Hi All,
>> >>
>> >> We need t
On Apr 29, 2010, at 2:30 PM, Pauli Virtanen wrote:
Wed, 28 Apr 2010 14:12:07 -0400, Alan G Isaac wrote:
[clip]
Here is a related ticket that proposes a more explicit alternative:
adding a ``dot`` method to ndarray.
http://projects.scipy.org/numpy/ticket/1456
I kind of like this idea. Simple,
Hi,
> I kind of like this idea. Simple, obvious, and leads
> to clear code:
>
> a.dot(b).dot(c)
>
> or in another multiplication order,
>
> a.dot(b.dot(c))
>
> And here's an implementation:
>
>
> http://github.com/pv/numpy-work/commit/414429ce0bb0c4b7e780c4078c5ff71c113050b6
On Thu, Apr 29, 2010 at 1:52 AM, Sebastian Haase wrote:
> Thanks for those replies.
> But isn't npy_intp about pointers ?
>
At one point perhaps, but how it is used is to get 32 bits on 32 OS's and 64
bits on 64 bit OS's, For the common architectures int will always be 32 bits
regardless, it i
Hi,
I have a few questions:
1)
I downloaded numpy1.3.0 and installed it in a directory using the command
*python setup.py install --prefix=$HOME/src/numpy
*and I see that numpy files have been generated in that directory.
Now when I tried to install matplotlib, it complained that my numpy versio
Wed, 28 Apr 2010 14:12:07 -0400, Alan G Isaac wrote:
[clip]
> Here is a related ticket that proposes a more explicit alternative:
> adding a ``dot`` method to ndarray.
> http://projects.scipy.org/numpy/ticket/1456
I kind of like this idea. Simple, obvious, and leads
to clear code:
a.dot(b
On Wed, Apr 28, 2010 at 11:56 AM, T J wrote:
> On Mon, Apr 26, 2010 at 10:03 AM, Charles R Harris
> wrote:
> >
> >
> > On Mon, Apr 26, 2010 at 10:55 AM, Charles R Harris
> > wrote:
> >>
> >> Hi All,
> >>
> >> We need to make a decision for ticket #1123 regarding what nansum should
> >> return w
On Thu, Apr 29, 2010 at 03:28, Jon Wright wrote:
> Hello everyone,
>
> Is there a 'numpy' efficient way to do the following loop:
>
> for i, v in indices, values:
> total[ i ] += v
>
>
> The behaviour is like numpy.put, but instead of overwriting the array
> element, it is incremented. Current
Hello everyone,
Is there a 'numpy' efficient way to do the following loop:
for i, v in indices, values:
total[ i ] += v
The behaviour is like numpy.put, but instead of overwriting the array
element, it is incremented. Currently I have a little C extension which
does the job, but I'm lazy
Alan G Isaac wrote:
> On 4/28/2010 12:08 PM, Dag Sverre Seljebotn wrote:
>
>> it would be good to deprecate the matrix class
>> from NumPy
>>
>
>
> Please let us not have this discussion all over again.
>
> The matrix class is very useful for teaching.
> In economics for example, the use
Thanks for those replies.
But isn't npy_intp about pointers ?
I would need something likenpy_int32 .
But does that exist ? Where is the list of types that numpy.i supports ?
Also, BTW, is there code duplication if numpy.i supports (let's say)
both npy_int and npy_int32 on a machine, where
On 4/28/2010 5:46 PM, David Warde-Farley wrote:
> Would it be acceptable to retain the matrix class but not have it
> imported in the default namespace, and have to import e.g.
> numpy.matlib to get at them?
If we can have A * M undefined, then I do not think this is
a needed addition. But I do n
> Alan wrote:
>> There is one change I would not mind: let
>> A * M be undefined if A is an ndarray and
>> M is a NumPy matrix.
On 4/28/2010 5:46 PM, David Warde-Farley wrote:
> What about the other binary ops? I would say, matrix goes with matrix,
> array with array, never the two shall meet unl
On Apr 28, 2010, at 4:46 PM, David Warde-Farley wrote:
On 2010-04-28, at 2:30 PM, Alan G Isaac wrote:
Please let us not have this discussion all over again.
Agreed. See my preface to this discussion.
My main objection is that it's not easy to explain to a newcomer
what the difference pre
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