Neil Crighton wrote:
Robert Kern robert.kern at gmail.com writes:
Do you mind if we just add you to the THANKS.txt file, and consider
you as a NumPy Developer per the LICENSE.txt as having released that
code under the numpy license? If we're dotting our i's and crossing
our t's legally,
Robert Cimrman wrote:
Neil Crighton wrote:
Robert Kern robert.kern at gmail.com writes:
Do you mind if we just add you to the THANKS.txt file, and consider
you as a NumPy Developer per the LICENSE.txt as having released that
code under the numpy license? If we're dotting our i's and crossing
Jonathan Taylor wrote:
Sorry.. obviously having some copy and paste trouble here. The
message should be as follows:
Hi,
I am doing optimization on a vector of rotation angles tx,ty and tz
using scipy.optimize.fmin. Unfortunately the function that I am
optimizing needs the rotation
On Wed, Mar 4, 2009 at 1:27 AM, Robert Cimrman cimrm...@ntc.zcu.cz wrote:
Jonathan Taylor wrote:
Sorry.. obviously having some copy and paste trouble here. The
message should be as follows:
Hi,
I am doing optimization on a vector of rotation angles tx,ty and tz
using
Wes McKinney wrote:
This still doesn't explain why the buffer interface was slow.
I finally remembered to look at this; there seems to be a problem in
your code:
def reindexObject(ndarray[object, ndim=1] index,
ndarray[object, ndim=1] arr,
dict idxMap):
On 2/11/2009 6:40 AM, A B wrote:
Hi,
How do I write a loadtxt command to read in the following file and
store each data point as the appropriate data type:
12|h|34.5|44.5
14552|bbb|34.5|42.5
dt = {'names': ('gender','age','weight','bal'), 'formats': ('i4',
'S4','f4', 'f4')}
Does this
On 3/4/2009 12:57 PM, Sturla Molden wrote:
Does this work for you?
Never mind, it seems my e-mail got messed up. I ought to keep them
sorted by date...
S.M.
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On 3/4/2009 7:50 AM, Hoyt Koepke wrote:
In cython, the above would be (something like):
It also helps to turn off bounds checks:
from numpy cimport ndarray
cdef extern from math.h:
double cos(double)
double sin(double)
@cython.boundscheck(False)
cpdef ndarray[double,
First, do a profile. That will tell you how much time you are spending in each
function and where the bottlenecks are. Easy to do in iPython.
Second, (I am guessing here -- the profile will tell you) that the bottleneck
is the call back to the rotation matrix function from the optimizer.
Hi,
I re-enabled umath tests (to test generalized ufuncs), to fix
remaining issues, but I think there is something fundamentally wrong
with it: it assumes cblas is available, which is not true. It happens to
work on (some) Linux and mac os X only because those platforms provide
cblas and blas
Hi all,
sorry for the spam, but in case any of you are coming to the SIAM
Conference on Computational Science and Engineering (CSE09) in Miami:
http://www.siam.org/meetings/cse09/
you might be interested in stopping by the Python sessions on Thursday:
Dear all,
I've written a wrapper enabling to run python code from within octave
(and vice versa). To this end I am embedding python in octave. So I am
calling
Py_Initialize();
_import_array();
do something with numpy
Py_Finalize();
multiple times. While things work nicely on the first run, I am
Is commit to NumPy SVN still turned off? How do I get a working SVN
again?
-Travis
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Travis E. Oliphant wrote:
Is commit to NumPy SVN still turned off? How do I get a working SVN
again?
It is on - I could commit a few things 1-2 hours ago. If you still get
an administrative error message (repo is read only ...), it means you
are on the old repo.
cheers,
David
On Mar 4, 2009, at 8:37 AM, David Cournapeau wrote:
Travis E. Oliphant wrote:
Is commit to NumPy SVN still turned off? How do I get a working SVN
again?
It is on - I could commit a few things 1-2 hours ago. If you still get
an administrative error message (repo is read only ...), it
On Thu, Mar 5, 2009 at 12:06 AM, Scott Sinclair
scott.sinclair...@gmail.com wrote:
I had to do a fresh checkout from http://svn.scipy.org/svn/numpy/
(note changed URL).
I did not know we could access svn from scipy.org. I have alway used
svn.scipy.org - in which case you don't need to do
Whoops. I see you have profiled your code. Sorry to re-suggest that.
But I agree with those who suggest a C speed up using ctypes or cthyon.
However, thanks for posting your question. It caused a LOT of very useful
responses that I didn't know about. Thanks to all who replied.
-- Lou
David Cournapeau wrote:
On Thu, Mar 5, 2009 at 12:06 AM, Scott Sinclair
scott.sinclair...@gmail.com wrote:
I had to do a fresh checkout from http://svn.scipy.org/svn/numpy/
(note changed URL).
I did not know we could access svn from scipy.org. I have alway used
svn.scipy.org - in
On Thu, Mar 5, 2009 at 1:33 AM, Bruce Southey bsout...@gmail.com wrote:
David Cournapeau wrote:
On Thu, Mar 5, 2009 at 12:06 AM, Scott Sinclair
scott.sinclair...@gmail.com wrote:
I had to do a fresh checkout from http://svn.scipy.org/svn/numpy/
(note changed URL).
I did not know we could
Sweet!
I found that *M*b.reshape(1,1)* will also do the trick. Any guess which
method is faster?
On Tue, Mar 3, 2009 at 9:11 PM, josef.p...@gmail.com wrote:
On Tue, Mar 3, 2009 at 8:53 PM, Jose Borreguero borregu...@gmail.com
wrote:
I guess there has to be an easy way for this. I have:
Hi David,
It isn't clear to me that trac is mailing out the ticket reponses, so I'm
posting to the list.
#913: max is bogus if nan is in the array
+---
Reporter: cdavid |Owner: somebody
Type: defect |
2009/3/4 Charles R Harris charlesr.har...@gmail.com:
It isn't clear to me that trac is mailing out the ticket reponses, so I'm
posting to the list.
It should work now.
Cheers
Stéfan
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On Wed, Mar 4, 2009 at 1:57 PM, Pauli Virtanen p...@iki.fi wrote:
Wed, 04 Mar 2009 13:18:55 -0700, Charles R Harris wrote:
[clip]
There are python max/min and their behaviour depends on the scalar type.
I haven't looked at the numpy scalars to see precisely what they do.
Numpy max/min
I found a nice module for these transforms at
http://www.lfd.uci.edu/~gohlke/code/transformations.py.html . I've
been using an older version for some time and thought it might make a
good addition to numpy/scipy. I made some simple mods to the older
version to add a couple of functions I needed
This is NOT yet discussed on the Cython list; I wanted to check with
more numerical users to see if the issue should even be brought up there.
The idea behind the current syntax was to keep things as close as
possible to Python/NumPy, and only provide some hints to Cython for
optimization. My
Just for other peoples reference I eventually went with a cython
version that goes about twice as fast as my old post. Here it is:
import numpy as np
cimport numpy as np
cdef extern from math.h:
double cos(double)
double sin(double)
def rotation(np.ndarray[double] theta):
cdef
Hi,
Please can someone suggest resources for learning how to use the
'repeat' macros in numpy C code to avoid repeating sections of
type-specific code for each data type? Ideally there would be two types
of resources: (i) a description of how the repeat macros are meant to be
used/compiled;
On Wed, Mar 4, 2009 at 5:54 PM, Stephen Simmons m...@stevesimmons.comwrote:
Hi,
Please can someone suggest resources for learning how to use the
'repeat' macros in numpy C code to avoid repeating sections of
type-specific code for each data type? Ideally there would be two types
of
Looks cool but a lot of this should be done in an extension module to
make it fast. Perhaps starting this process off as a separate entity
until stability is acheived. I would be tempted to do some of this
using cython. I just wrote found that generating a rotation matrix
from euler angles is
Charles R Harris wrote:
On Wed, Mar 4, 2009 at 1:57 PM, Pauli Virtanen p...@iki.fi
mailto:p...@iki.fi wrote:
Wed, 04 Mar 2009 13:18:55 -0700, Charles R Harris wrote:
[clip]
There are python max/min and their behaviour depends on the
scalar type.
I haven't looked at
On Wed, Mar 4, 2009 at 23:32, Charles R Harris
charlesr.har...@gmail.com wrote:
One thing that still bothers me a bit is the return value of fmax/fmin when
comparing two complex nan values. A complex number is a nan whenever the
real or imaginary part is nan, and currently the functions return
Robert Kern wrote:
On Wed, Mar 4, 2009 at 23:32, Charles R Harris
charlesr.har...@gmail.com wrote:
One thing that still bothers me a bit is the return value of fmax/fmin when
comparing two complex nan values. A complex number is a nan whenever the
real or imaginary part is nan, and
Hi Gareth
2009/3/5 Gareth Elston gareth.elston.fl...@googlemail.com:
I seem to remember that there was a first draft of a guide for
developers being written. Are there any links available?
Sorry, I should have posted that already. We are still setting up
Trac to support a proper work-flow,
Robert Kern wrote:
On Wed, Mar 4, 2009 at 23:32, Charles R Harris
charlesr.har...@gmail.com wrote:
One thing that still bothers me a bit is the return value of fmax/fmin when
comparing two complex nan values. A complex number is a nan whenever the
real or imaginary part is nan, and
On Thu, Mar 5, 2009 at 00:28, Charles R Harris
charlesr.har...@gmail.com wrote:
Heh, it's somehow comforting to know Matlab finds it a bit confusing too. I
suppose what bothers me is that fmax/fmin return the first argument when
both are nans. For reals, that is simply a nan, no problem, but
In general, using complex extension modules like numpy between
matching pairs of Py_Initialize()/Py_Finalize() is tricky...
Extension modules have to be VERY carefully written as to permit such
usage pattern... It is too easy to forget the init/cleanup/finalize
steps... I was able to manage this
Stéfan van der Walt wrote:
Hi Dag
2009/3/5 Dag Sverre Seljebotn da...@student.matnat.uio.no:
More details: http://wiki.cython.org/enhancements/buffersyntax
Interesting proposal! Am I correct in thinking that you'd have to
re-implement a lot of NumPy yourself to get this working? Or are
Sturla Molden wrote:
arr = np.zeros(..)
cdef int[:,:] buf = arr # 2D buffer
Here, buf would be something else than arr; it is a seperate view to the
array for low-level purposes.
I like your proposal. The reason we use Fortran for numerical computing is
that Fortran makes it easy to
Andrew Straw wrote:
Dag Sverre Seljebotn wrote:
This is NOT yet discussed on the Cython list; I wanted to check with
more numerical users to see if the issue should even be brought up there.
The idea behind the current syntax was to keep things as close as
possible to Python/NumPy, and
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