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 x,
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, wrote:
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
Thoma
On Wed, May 6, 2009 at 7:39 PM, Chris Colbert 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 at 7:30 PM,
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, wrote:
> On Wed, May 6, 2009 at 6:06 PM, Chris Colbert wrote:
> >
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:
http://www.nabble.com/Numpy-Trac-site-redirecting-in-a-loop--tp23067410p23417595.h
On Wed, May 6, 2009 at 6:06 PM, Chris Colbert 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 compiler. For a (480, 6
On Wed, May 6, 2009 at 19:19, Thomas Robitaille
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
>
> http://projects.scipy.org/numpy/pre
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 red
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 heardcom
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.
Th
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
_
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
[
On Wed, May 6, 2009 at 10:44 PM, Talbot, Gerry 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 exactly what s
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: Discu
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 = zeros((3,3,3,3,3,3,10,4,6,2,18,
On Wed, May 6, 2009 at 10:21 AM, wrote:
> On Wed, May 6, 2009 at 10:00 AM, Talbot, Gerry 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 sc
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 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 loo
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
___
Numpy-discu
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 "", line 1, in
test = zer
On Wed, May 6, 2009 at 10:00 AM, Talbot, Gerry 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 up what I did
e
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 6:44 AM, Talbot, Gerry 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 = np.array([1,2,3])
>>
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
http://mail.scipy.org/mailman/listinfo/
--- On Wed, 6/5/09, David Cournapeau 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 with a standard package bla
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 :
> Hi,
>
> I'm gonna have lar
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 its
On Tue, May 5, 2009 at 9:12 PM, David Cournapeau wrote:
> On Wed, May 6, 2009 at 3:57 AM, Darren Dale wrote:
>
> >
> > There is a lot of interest in a 3to2 tool, and I have read speculation
> > (
> http://sayspy.blogspot.com/2009/04/pycon-2009-recap-best-pycon-ever.html)
> > that going from 3 to
Muhammad Alkarouri wrote:
> --- On Wed, 6/5/09, David Cournapeau 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
>>
--- On Wed, 6/5/09, David Cournapeau 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,
Thanks David. I went ther
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
Muhammad Alkarouri wrote:
>> Date: Tue, 5 May 2009 09:24:53 -0600
>> From: Charles R Harris
>>
> ...
>
>> 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 so
> Date: Tue, 5 May 2009 09:24:53 -0600
> From: Charles R Harris
...
> 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 Enterprise Linux 4. I had to
33 matches
Mail list logo
