It looks like you encountered a fundamental short come of numpy (or in fact any
similar system like octave, matlab etc...): The dependence on values calculated
in previous iteration can not vectorize easily. If you have an access to C
compiler, I urge you to write (at least) the inner loop with
Travis Oliphant ee.byu.edu> writes:
> You can submit a patch as a ticket on the Trac pages. The trend is to
> put this kind of stuff into SciPy instead of NumPy. I think we are
> trying to trim NumPy in the long term.
I'll look into this.
> As far as I'm concerned just placing a link t
On 2/16/07, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On 2/15/07, Sebastian Haase <[EMAIL PROTECTED]> wrote:
> > On 2/15/07, Keith Goodman <[EMAIL PROTECTED]> wrote:
> > > On 2/15/07, Keith Goodman <[EMAIL PROTECTED]> wrote:
> > > > I built a new computer: Core 2 Duo 32-bit Debian etch with numpy
OK, I looked at the varin, varout descriptions in the online manual,
and they specifically mention global variables, but WOW is that
documentation minimal. I would suggest asking Swig-
[EMAIL PROTECTED] for some assistance.
On Feb 16, 2007, at 1:10 PM, Bill Spotz wrote:
> Andrea,
>
> It is
Andrea,
It is my understanding that swig typemaps only apply to function
arguments. Since what you are talking about is a global variable, I
don't believe typemaps will help you. I would try
%{
#include "header-that-contains-vec.h"
npy_intp vec_dims[ ] = { (npy_intp) length_of_vec };
%}
%re
Alec Mihailovs wrote:
>I saw somewhere a comparison between numpy and Matlab/Octave. One of the
>Matlab/Octave commands that is missing in Numpy is magic(n) for producing n-by-
>n magic squares.
>
>Yesterday I posted a magic_square module in the CheeseShop, containing this
>missing magic(n) comm
Brian, thanks for your answer!
I removed and completely reinstalled the Developer Tools. The issue with gcc
seems to be resolved now. My python binary is indeed the one of python.org, but
nevertheless I also reinstalled Python 2.5.
To install numpy I started all over again with svn. The results
I saw somewhere a comparison between numpy and Matlab/Octave. One of the
Matlab/Octave commands that is missing in Numpy is magic(n) for producing n-by-
n magic squares.
Yesterday I posted a magic_square module in the CheeseShop, containing this
missing magic(n) command together with 2 others, i
Il giorno 15/feb/07, alle ore 22:26, Bill Spotz ha scritto:
> It seems to me you would need to %ignore vec, so that it is not
> wrapped as a raw pointer to a double, and then in your interface
> file create a PyArrayObject whose data buffer points to vec (the
> most efficient way to do this
Keir Mierle wrote:
> On 2/15/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
>> On 2/12/07, LUK ShunTim <[EMAIL PROTECTED]> wrote:
>>> David Cournapeau wrote:
Keith Goodman wrote:
> On 2/11/07, David Cournapeau <[EMAIL PROTECTED]> wrote:
>> My impression is that binary distribution of
Hi Nadav,
The code is attached at the end. There is probably still bugs in there
but it does not prevent me from showing the difficulity.
If you look at the inner loop below, you will see that vector v is
updated element by element. The new value of v[i] depends on the new
value of v[i-1] and the
In fact I am not looking for an implementation but a method to update a
vector iteratively when the value of an item of the vector depend partly
on the already updated items and partly depend on the old items.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf
Hi Nadav,
The code is attached at the end. There is probably still bugs in there
but it does not prevent me from showing the difficulity.
If you look at the inner loop below, you will see that vector v is
updated element by element. The new value of v[i] depends on the new
value of v[i-1] and the
Numpy should install fine on your system. If there was no gcc in
/usr/bin, then something significant went wrong with your
DeveloperTools install. I would do a full reinstall of that. Also,
gcc 4.0.1 is the default so there is no reason to use gcc_select.
Where did you get your python. I would
Nadav Horesh wrote:
> At first glance it doesn't look hard to, at least, avoid looping over i, by
> replacing [i] by [:-2], [i+1] by [1:-1] and [i+2] by [2:]. But I might be
> wrong. Can you submit the piece of code with at least the most internal loop?
>
>Nadav.
>
I guess he is looking fo
At first glance it doesn't look hard to, at least, avoid looping over i, by
replacing [i] by [:-2], [i+1] by [1:-1] and [i+2] by [2:]. But I might be
wrong. Can you submit the piece of code with at least the most internal loop?
Nadav.
-Original Message-
From: [EMAIL PROTECTED] on b
On 2/15/07, Sebastian Haase <[EMAIL PROTECTED]> wrote:
> On 2/15/07, Keith Goodman <[EMAIL PROTECTED]> wrote:
> > On 2/15/07, Keith Goodman <[EMAIL PROTECTED]> wrote:
> > > I built a new computer: Core 2 Duo 32-bit Debian etch with numpy
> > > 1.0.2.dev3546. The repeatability test still fails. In o
Hi,
I'm trying to install numpy 1.0.2 (trunk) on my intel mac with Tiger 10.4.8,
but I experience some problems, which I think may be compiler problems. From
the
beginning:
I installed MacPython 2.5:
Python 2.5 (r25:51918, Sep 19 2006, 08:49:13)
[GCC 4.0.1 (Apple Computer, Inc. build 5341)] on d
On Feb 11, 2007, at 22:51 , Satrajit Ghosh wrote:
> Hi,
>
> I'm also not quite clear whether the optimized FFTW and UMFPACK
> libraries
> are being used or required in numpy at all as show_config() doesn't
> report
> it.
>
> I see that fftw and umfpack are being used for scipy.
>
> I have atta
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