Hi all,
The binary for OS-X on sourceforge is called:
numpy-1.3.0-py2.5-macosx10.5.dmg
However, as far as I can tell, it works just fine on OS-X 10.4, and
maybe even 10.3.9.
Perhaps a re-naming is in order? But to what?
I'd say:
numpy-1.3.0-py2.5-macosx10.4.dmg
but would folks think that
Date: Tue, 5 May 2009 09:24:53 -0600
From: Charles R Harris charlesr.har...@gmail.com
...
This is almost always an ATLAS problem. Where did your
ATLAS come from and
what distro are you running?
You are probably right. I compiled and installed ATLAS from source. The distro
is Redhat
Muhammad Alkarouri wrote:
Date: Tue, 5 May 2009 09:24:53 -0600
From: Charles R Harris charlesr.har...@gmail.com
...
This is almost always an ATLAS problem. Where did your
ATLAS come from and
what distro are you running?
You are probably right. I compiled and installed ATLAS
I tried looking at your question but ... kind of unusable without some
documentation.
You need to give at least the following information:
what kind of optimization problem?
LP,NLP, Mixed Integer LP, Stochastic, semiinfinite, semidefinite?
Most solvers require the problem in the following form
--- On Wed, 6/5/09, David Cournapeau da...@ar.media.kyoto-u.ac.jp wrote:
...
What does ldd lapack_lite.so returns (lapack_lite.so is in
numpy/linalg,
in your installed directory) ? It may be that numpy uses
gfortran,
whereas ATLAS is built with g77. gfortran and g77 should
not be mixed,
Muhammad Alkarouri wrote:
--- On Wed, 6/5/09, David Cournapeau da...@ar.media.kyoto-u.ac.jp wrote:
...
What does ldd lapack_lite.so returns (lapack_lite.so is in
numpy/linalg,
in your installed directory) ? It may be that numpy uses
gfortran,
whereas ATLAS is built with g77. gfortran
On Tue, May 5, 2009 at 9:12 PM, David Cournapeau courn...@gmail.com wrote:
On Wed, May 6, 2009 at 3:57 AM, Darren Dale dsdal...@gmail.com wrote:
There is a lot of interest in a 3to2 tool, and I have read speculation
(
Hi,
I'm gonna have large (e.g. 2400x2400) arrays of 16 and 32 bit bitfields.
I've been searching in vain for an efficient and convenient way to
represent these array's individual bit's (or, even better, configureable
bitfields of 1-4 bits each).
Of course I know I can 'split' the array in
Hi Vincent
Take a look at http://pypi.python.org/pypi/bitarray/
I'm not sure if you can initialise bitarrays from NumPy arrays. If
not, you'll have to implement a conversion scheme, but that can be
done without making a copy.
Regards
Stéfan
2009/5/6 Vincent Schut sc...@sarvision.nl:
Hi,
--- On Wed, 6/5/09, David Cournapeau da...@ar.media.kyoto-u.ac.jp wrote:
...
Ok, so that's not a gfortran problem. As Chuck, I think
that's an atlas
problem (you could check by compiling without ATLAS:
It is an atlas problem. Not that I knew how to correct it, but I was able to
build numpy
Does anyone know how to efficiently implement a recurrence relationship
in numpy such as:
y[n] = A*x[n] + B*y[n-1]
Thanks,
Gerry
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
On Wed, May 6, 2009 at 6:44 AM, Talbot, Gerry gerry.tal...@amd.com wrote:
Does anyone know how to efficiently implement a recurrence relationship in
numpy such as:
y[n] = A*x[n] + B*y[n-1]
On an intel chip I'd use a Monte Carlo simulation. On an amd chip I'd use:
x =
Sorry, I guess I wasn't clear, I meant:
for n in xrange(1,N):
y[n] = A*x[n] + B*y[n-1]
So y[n-1] is the result from the previous loop iteration.
Gerry
-Original Message-
From: numpy-discussion-boun...@scipy.org
[mailto:numpy-discussion-boun...@scipy.org] On Behalf Of
On Wed, May 6, 2009 at 10:00 AM, Talbot, Gerry gerry.tal...@amd.com wrote:
Sorry, I guess I wasn't clear, I meant:
for n in xrange(1,N):
y[n] = A*x[n] + B*y[n-1]
So y[n-1] is the result from the previous loop iteration.
I was using scipy.signal for this but I have to look
Hello alls,
I currently have a problem with creating a
multi-dimensional array in numpy. The following is what I am trying to
do and the error message.
test = zeros((3,3,3,3,3,3,10,4,6,2,18,10,11,4,2,2), dtype=float);
Traceback (most recent call last):
File pyshell#39, line 1, in module
On 5/6/2009 10:00 AM Talbot, Gerry apparently wrote:
for n in xrange(1,N):
y[n] = A*x[n] + B*y[n-1]
So, x is known before you start?
How big is N? Also, is y.shape (N,)?
Do you need all of y or only y[N]?
Alan Isaac
___
Le mercredi 06 mai 2009 à 10:21 -0400, josef.p...@gmail.com a écrit :
On Wed, May 6, 2009 at 10:00 AM, Talbot, Gerry gerry.tal...@amd.com wrote:
Sorry, I guess I wasn't clear, I meant:
for n in xrange(1,N):
y[n] = A*x[n] + B*y[n-1]
So y[n-1] is the result from the
On Wed, May 6, 2009 at 10:21 AM, josef.p...@gmail.com wrote:
On Wed, May 6, 2009 at 10:00 AM, Talbot, Gerry gerry.tal...@amd.com wrote:
Sorry, I guess I wasn't clear, I meant:
for n in xrange(1,N):
y[n] = A*x[n] + B*y[n-1]
So y[n-1] is the result from the previous loop
On Wed, May 6, 2009 at 8:18 AM, natachai wongchavalidkul
natacha...@hotmail.com wrote:
Hello alls,
I currently have a problem with creating a multi-dimensional array in
numpy. The following is what I am trying to do and the error message.
test =
The application is essentially filtering 1D arrays, typically N is
20e6, the required result is y[1:N].
Gerry
-Original Message-
From: numpy-discussion-boun...@scipy.org
[mailto:numpy-discussion-boun...@scipy.org] On Behalf Of Alan G Isaac
Sent: Wednesday, May 06, 2009 10:25 AM
To:
On Wed, May 6, 2009 at 10:44 PM, Talbot, Gerry gerry.tal...@amd.com wrote:
Does anyone know how to efficiently implement a recurrence relationship in
numpy such as:
y[n] = A*x[n] + B*y[n-1]
That's the direct implement of a linear filter with an infinite
impulse response. That's
I have a function f(x,y) which produces N values [v1,v2,v3 vN]
where some of the values are None (only found after evaluation)
each evaluation of f is expensive and N is large.
I want N x,y pairs which produce the optimal value in each column.
A brute force approach would be to generate
I decided to hold myself over until being able to take a hard look at the
numpy histogramdd code:
Here is a quick thing a put together in cython. It's a 40x speedup over
histogramdd on Vista 32 using the minGW32 compiler. For a (480, 630, 3)
array, this executed in 0.005 seconds on my machine.
David Warde-Farley wrote:
On 6-May-09, at 2:03 AM, Christopher Barker wrote:
maybe:
numpy-1.3.0-py2.5-macosx-python.org.dmg
+1 on having python.org in the name. It clarifies and reinforces the
case that this isn't for the Apple-shipped Python
exactly.
(which I heardcomes with
On 6-May-09, at 2:03 AM, Christopher Barker wrote:
maybe:
numpy-1.3.0-py2.5-macosx-python.org.dmg
+1 on having python.org in the name. It clarifies and reinforces the
case that this isn't for the Apple-shipped Python (which I heard
comes with NumPy now?).
David
Hi,
I'm having the exact same problem, trying to log in to the trac website for
numpy, and getting stuck in a redirect loop. I tried different browsers, and
no luck. The browser gets stuck on
http://projects.scipy.org/numpy/prefs/account
and stops loading after a while because of too many
On Wed, May 6, 2009 at 19:19, Thomas Robitaille
thomas.robitai...@gmail.com wrote:
Hi,
I'm having the exact same problem, trying to log in to the trac website for
numpy, and getting stuck in a redirect loop. I tried different browsers, and
no luck. The browser gets stuck on
On Wed, May 6, 2009 at 6:06 PM, Chris Colbert sccolb...@gmail.com wrote:
I decided to hold myself over until being able to take a hard look at the
numpy histogramdd code:
Here is a quick thing a put together in cython. It's a 40x speedup over
histogramdd on Vista 32 using the minGW32
Could it be linked to specific users, since the problem occurs when loading
the account page? I had the same problem on two different computers with two
different browsers.
Thomas
--
View this message in context:
i just realized I don't need the line:
cdef int z = img.shape(2)
it's left over from tinkering. sorry. And i should probably convert the out
array to type float to handle large data sets.
Chris
On Wed, May 6, 2009 at 7:30 PM, josef.p...@gmail.com wrote:
On Wed, May 6, 2009 at 6:06 PM, Chris
On Wed, May 6, 2009 at 7:39 PM, Chris Colbert sccolb...@gmail.com wrote:
i just realized I don't need the line:
cdef int z = img.shape(2)
it's left over from tinkering. sorry. And i should probably convert the out
array to type float to handle large data sets.
Chris
On Wed, May 6, 2009
I ran into something like this a couple weeks ago. I use Firefox 3 on MacOS.
My work-around was to clear all the cookies from scipy.org, clear all
authenticated sessions, then register a completely new account name. I
never could get my existing account to stop looping.
HTH,
Ken
nice!
This was really my first attempt at doing anything constructive with Cython.
It was actually unbelievably easy to work with. I think i spent less time
working on this, than I did trying to find an optimized solution using pure
numpy and python.
Chris
On Wed, May 6, 2009 at 8:21 PM,
Hi Mathew,
You could use Newton's method to optimize for each vi sequentially. If you
have an expression for the jacobian, it's even better.
What I'd do is write a class with a method f(self, x, y) that records the
result of f(x,y) each time it is called. I would then sample very coarsely
the
34 matches
Mail list logo
