=(np.array([1]*1 + [1e4], dtype=np.float32))
np.sum(x*x)
1.0001e+08
You can sort x from small numbers to bigger numbers before you call sum.
-Kibeom Kim
On Sat, Mar 5, 2011 at 6:27 PM, Xavier Gnata xavier.gn...@gmail.com
mailto:xavier.gn...@gmail.com wrote:
Hi,
I got this problem
Hi,
I got this problem in a real life code and it took me some time to
figure out that np.linalg.norm has a terrible numerical behavior.
The problem is nicely described here
http://fseoane.net/blog/2011/computing-the-vector-norm/
numpy/linalg/linalg.py claims to be a high-level Python
Let (Xi,Yi) be the positions of your stars on the sky. i in the 1 to N
range.
Let (Xj,Yj) be the positions of your stars images (PSF) on your picture.
i in the 1 to N range.
You can parametrize the distortion this way:
Xj_param = Px(Xi,Yi)
Yj_param = Py(Xi,Yi)
where Px and Py are the two
Hi,
Do you plan to make some noise about that when numpy2.0 will be release?
IMHO you should.
Do you for instance plan to have a clear announcement on the scipy web site?
Xavier
Hi,
The test suite passes now on Pythons 2.4 - 3.1. Further testing is very
welcome -- also on Python 2.x. Please
On 02/28/2010 08:17 PM, josef.p...@gmail.com wrote:
On Sun, Feb 28, 2010 at 1:51 PM, Xavier Gnata xavier.gn...@gmail.com wrote:
Hi,
I'm sure I reinventing the wheel with the following code:
from numpy import *
from scipy import polyfit,stats
def f(x,y,z):
return x+y+z
M
New try new error:
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-x86_64-3.1/numpy/core/src/multiarray/multiarraymodule_onefile.o
-Lbuild/temp.linux-x86_64-3.1 -lnpymath -lm -o
build/lib.linux-x86_64-3.1/numpy/core/multiarray.so
/usr/bin/ld:
On 02/13/2010 09:28 PM, Pauli Virtanen wrote:
We will most likely have experimental py3 support in 2.0.
If you, or someone else wishes to help bringing 2.0 to fully work with Py3,
now is a very good time to step up.
How to give a hand:
1. Get my latest py3 branch from
/core/src/multiarray/multiarraymodule_onefile.o
failed with exit status 1
BTW, is there a better place to discuss these python3 only related issues?
Xavier
Xavier Gnata xavier.gnata at gmail.com writes:
Well I ran git clone git://github.com/pv/numpy-work.git an hour ago (in
an empty directory
On 02/13/2010 07:31 PM, Charles R Harris wrote:
On Sat, Feb 13, 2010 at 11:23 AM, Joe Harrington j...@physics.ucf.edu
mailto:j...@physics.ucf.edu wrote:
Chuck Harris writes (on numpy-discussion):
Since there has been talk of deprecating the numarray and numeric
compatibility
IMHO 2.0 should support python3.
That would be a major step and a good reason to call it 2.0.
Xavier
This is exactly what I was worried about with calling the next release
2.0.
This is not the time to change all the things we wish were done
differently.
The release is scheduled for 3
On 02/13/2010 09:28 PM, Pauli Virtanen wrote:
We will most likely have experimental py3 support in 2.0.
If you, or someone else wishes to help bringing 2.0 to fully work with Py3,
now is a very good time to step up.
How to give a hand:
1. Get my latest py3 branch from
On 02/13/2010 10:15 PM, Charles R Harris wrote:
On Sat, Feb 13, 2010 at 2:07 PM, Xavier Gnata xavier.gn...@gmail.com
mailto:xavier.gn...@gmail.com wrote:
On 02/13/2010 09:28 PM, Pauli Virtanen wrote:
We will most likely have experimental py3 support in 2.0.
If you
Hi,
I have compiled numpy 1.5.0.dev8039 both on a 32 and a 64bits ubuntu
machine.
On the 64bits one, everything is fine:
numpy.test get a perfect score:
nose.result.TextTestResult run=2504 errors=0 failures=0
On the 32bits ubuntu, the story is not that nice:
nose.result.TextTestResult run=2504
On Wed, Jan 6, 2010 at 6:48 AM, Xavier Gnata xavier.gn...@gmail.com wrote:
Hi,
I have compiled numpy 1.5.0.dev8039 both on a 32 and a 64bits ubuntu
machine.
On the 64bits one, everything is fine:
numpy.test get a perfect score:
nose.result.TextTestResult run=2504 errors=0 failures=0
Hi,
Is there a way to help to port numpy to python3?
I don't thing I have time to rewrite some code but I can test whatever
has to be tested.
Is there an official web page showing the status of this port? Same
question from scipy?
It is already nice to see that the last numpy version is
René Dudfield wrote:
On Mon, Sep 21, 2009 at 8:12 PM, David Warde-Farley d...@cs.toronto.edu
wrote:
On 21-Sep-09, at 2:55 PM, Xavier Gnata wrote:
Should I read that to learn you cython and numpy interact?
Or is there another best documentation (with examples...)?
You
David Cournapeau wrote:
Xavier Gnata wrote:
Hi,
I have a large 2D numpy array as input and a 1D array as output.
In between, I would like to use C code.
C is requirement because it has to be fast and because the algorithm
cannot be written in a numpy oriented way :( (no way...really
Hi,
I have a large 2D numpy array as input and a 1D array as output.
In between, I would like to use C code.
C is requirement because it has to be fast and because the algorithm
cannot be written in a numpy oriented way :( (no way...really).
Which tool should I use to achieve that?
Hi,
Let us consider one kN x kM array.
What is the fastest way to sum each k x k square block of A and to put
all these results into a NxM array B?
For instance:
If A =
[112233
112233
223311
223311]
then B =
[4 8 12
4 12 4]
No sanity checks on the arrays shapes are requiered. Only speed
Well it is the best pitch for numpy versus matlab I have read so far :)
(and I 100% agree)
Xavier
On 1/7/2009 4:16 PM, David Cournapeau wrote:
I think on recent versions of matlab, there is nothing you can do
without modifying the code: matlab has some JIT compilation for loops,
which is
Suppose I have a toeplitz matrix, A. There is a well known algorithm
for computing the matrix vector product Ax, in NlogN operations. An
exact reference escapes me, but it may be in Golub van Loan's book.
My question is, how could I best take advantage of this algorithm
within
Alok Singhal wrote:
On 14/08/08: 10:20, Keith Goodman wrote:
A unit test is attached. It contains three tests:
In test1, I construct matrices x and y and then repeatedly calculate z
= calc(x,y). The result z is the same every time. So this test passes.
In test2, I construct matrices x
Christopher Barker wrote:
Xavier Gnata wrote:
Here it is :)
Thanks, that's helpful. Am I reading it right? Are you running the
python process embedded in your C++ app? (rather than extending?)
Yes! The point is this way I'm able to debug my C++ code plotting the
array using
-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-discussion
--
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CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: [EMAIL
Christopher Barker wrote:
Xavier Gnata wrote:
I'm using the numpy C API (PyArray_SimpleNewFromData) to perform the
conversion but my code is written by hands.
I'd like to see that. How are you getting the pointer to pass in to
PyArray_SimpleNewFromData? It looks like you can do
...)
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: [EMAIL PROTECTED]
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CRAL - Observatoire de Lyon
9, avenue Charles André
ones working
properly for a long time.
David
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CRAL
Pearu Peterson wrote:
Xavier Gnata wrote:
I just would like to be able to tell numpy to use liblapack.so instead
of this non free libmkl_lapack32.so
For that set the following environment variable when building numpy/scipy:
export MKL=None
Hth,
Pearu
ok it works
Xavier Gnata wrote:
Hi,
I'm trying to update numpy by compiling the up to date svn:
I get this error :
gcc: numpy/linalg/lapack_litemodule.c
gcc -pthread -shared
build/temp.linux-i686-2.4/numpy/linalg/lapack_litemodule.o
-lmkl_lapack32 -lmkl_lapack64 -lmkl -lvml -lguide -lpthread -o
on this i386 machine.
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: [EMAIL PROTECTED
if it is a bug on my side.
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: [EMAIL PROTECTED
to
match the boost++ way of thinking.
Comments?
Xavier
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: [EMAIL PROTECTED
to report in case of errors. It is also
pretty hard to avoid nasty infinite recursions playing with to be
evaluated objects.
I'm going to have a look to this scipy sandbox module.
Xavier
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
can read things like
# !! This is actually (unexpectedly) zero in
/usr/lib/python2.4/site-packages/numpy/lib/tests/test_type_check.py
Xavier.
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4
but it is
always almost the same :)
--
Xavier Gnata
CRAL - Observatoire de Lyon
9, avenue Charles André
69561 Saint Genis Laval cedex
Phone: +33 4 78 86 85 28
Fax: +33 4 78 86 83 86
E-mail: [EMAIL PROTECTED
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