eat writes:
> Nikolaus Rath rath.org> writes:
>
> [snip]
>> Not quite, because I'm interested in the n largest values over all
>> elements, not the largest element in each row or column. But Keith's
>> solution seems to work fine, even though I'm still struggling to
>> understand what's going on
2010/4/16 Charles سمير Doutriaux
> Thx Ralf,
>
> I was able to get the 64bit version going. But as I mentioned earlier this
> doesn't help me since I have other externals dying...
>
> I'll try the 32bit one again with these hints.
>
>
The dmg installer on sourceforge is 32-bit, so unless you're a
Antoine,
You want a python function with two python array arguments, therefore
you are dealing with two different typemaps, each of which requires
its own %apply directive:
%apply (double* IN_ARRAY1, int DIM1) {(double* vec , int m)};
%apply (double* ARGOUT_ARRAY1, int DIM1) {(double* vec
Thx Ralf,
I was able to get the 64bit version going. But as I mentioned earlier this
doesn't help me since I have other externals dying...
I'll try the 32bit one again with these hints.
Thanks again,
C.
On Apr 15, 2010, at 4:53 PM, Ralf Gommers wrote:
>
> 2010/4/16 Charles سمير Doutriaux
>
On Thu, Apr 15, 2010 at 1:48 PM, Keith Goodman wrote:
> On Thu, Apr 15, 2010 at 12:41 PM, Nikolaus Rath wrote:
>> Keith Goodman writes:
>>> On Wed, Apr 14, 2010 at 12:39 PM, Nikolaus Rath wrote:
Keith Goodman writes:
> On Wed, Apr 14, 2010 at 8:49 AM, Keith Goodman
> wrote:
2010/4/16 Charles سمير Doutriaux
> Hi There,
>
> 1.4.1rc2
> gcc 4.2.1
>
> And yes I'm trying to build a 32bit python because a lot of externals seem
> to be breaking with the 64bit stuff...
>
> But I'm giving it another shot building 64bit
>
For 64-bit the command is:
$ LDFLAGS="-arch x86_64" FF
Dear Numpy and SWIG users,
I am currently trying to use SWIG and Numpy to launch C++ codes from
python.
My C++ code takes an array as an input (as well as integers, but this
will be my next problem...) and returns a different array (with
different dimensions).
I have managed to make ve
Nikolaus Rath rath.org> writes:
[snip]
> Not quite, because I'm interested in the n largest values over all
> elements, not the largest element in each row or column. But Keith's
> solution seems to work fine, even though I'm still struggling to
> understand what's going on there .
My bad. I jus
On Thu, Apr 15, 2010 at 12:41 PM, Nikolaus Rath wrote:
> Keith Goodman writes:
>> On Wed, Apr 14, 2010 at 12:39 PM, Nikolaus Rath wrote:
>>> Keith Goodman writes:
On Wed, Apr 14, 2010 at 8:49 AM, Keith Goodman wrote:
> On Wed, Apr 14, 2010 at 8:16 AM, Nikolaus Rath wrote:
>> Hell
Keith Goodman writes:
> On Wed, Apr 14, 2010 at 12:39 PM, Nikolaus Rath wrote:
>> Keith Goodman writes:
>>> On Wed, Apr 14, 2010 at 8:49 AM, Keith Goodman wrote:
On Wed, Apr 14, 2010 at 8:16 AM, Nikolaus Rath wrote:
> Hello,
>
> How do I best find out the indices of the larges
eat writes:
>> How do I best find out the indices of the largest x elements in an
>> array?
>
> Just
> a= np.asarray([[1, 8, 2], [2, 1, 3]])
> print np.where((a.T== a.max(axis= 1)).T)
>
> However, if any row contains more than 1 max entity, above will fail. Please
> let me to know if that's relev
On Thu, Apr 15, 2010 at 13:42, Neal Becker wrote:
> Is there a simple way to create a rectangular grid, like this loopy code:
> (This is for a QAM256 constellation, btw):
>
> import numpy as np
>
> u = np.arange (-7.5, 8)
>
> const = np.empty ((16,16), dtype=complex)
>
> for ix in range (16):
>
On Thu, Apr 15, 2010 at 2:42 PM, Neal Becker wrote:
> Is there a simple way to create a rectangular grid, like this loopy code:
> (This is for a QAM256 constellation, btw):
>
> import numpy as np
>
> u = np.arange (-7.5, 8)
>
> const = np.empty ((16,16), dtype=complex)
>
> for ix in range (16):
>
Is there a simple way to create a rectangular grid, like this loopy code:
(This is for a QAM256 constellation, btw):
import numpy as np
u = np.arange (-7.5, 8)
const = np.empty ((16,16), dtype=complex)
for ix in range (16):
for iy in range (16):
const[ix, iy] = u[ix] + 1j*u[iy]
__
Hi There,
1.4.1rc2
gcc 4.2.1
And yes I'm trying to build a 32bit python because a lot of externals seem to
be breaking with the 64bit stuff...
But I'm giving it another shot building 64bit
C.
On Apr 14, 2010, at 5:48 PM, Ralf Gommers wrote:
>
>
> 2010/4/15 Charles سمير Doutriaux
> Just
On Wed, Apr 14, 2010 at 9:32 PM, James Bergstra
wrote:
> On Tue, Apr 6, 2010 at 10:08 AM, David Cournapeau wrote:
>> could be put out of multiarray proper. Also, exposing an API for
>> things like fancy indexing would be very useful, but I don't know if
>> it even makes sense - I think a pure pyth
Yes. I am really sorry about that.
> From: seb.ha...@gmail.com
> Date: Thu, 15 Apr 2010 13:24:10 +0200
> To: numpy-discussion@scipy.org
> Subject: Re: [Numpy-discussion] use of %extend
>
> did you mean to send this to the SWIG list !?
> -S.
>
>
> On Thu, Apr 15, 2010 at 11:53 AM, Michel Du
did you mean to send this to the SWIG list !?
-S.
On Thu, Apr 15, 2010 at 11:53 AM, Michel Dupront
wrote:
> Hello,
>
> With the following example, given in the documentation:
>
> struct Vector {
> double x,y,z;
> };
> %extend Vector {
> Vector __add__(Vector *other) {
> Vector v;
Hello,
With the following example, given in the documentation:
struct Vector {
double x,y,z;
};
%extend Vector {
Vector __add__(Vector *other) {
Vector v;
v.x = $self->x + other->x;
v.y = $self->y + other->y;
v.z = $self->z + other->z;
retu
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