2008/8/6 Dag Sverre Seljebotn [EMAIL PROTECTED]:
cdef numpy.ndarray[numpy.int64, ndim=2]
I'd definitely prefer a comma between the two, and an (optional) ndim
keyword argument if possible.
I'm taking this as a vote in favor of this and against 2D and ?
The keyword is already present in
I made the following modification to the source code, I hope it is ready
to be included in scipy.
1. Added a BSD licence declaration.
2. Small optimisation.
3. The code is split into a cython back-end and a python
front-end.
All remarks are welcome,
Nadav.
On Tue,
I did about the same thing 9 year ago (in python of course). If I can recall
correctly, you need to double the arrays size (with padding of 0) in order to
avoid this artifact. I think that its origin is that the DFT is equivalent to
periodic boundary conditions.
Nadav.
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Hello,
If I use the -O switch then it seems getting some testcase failures,
and finally a windows message that python.exe has encountered a problem
and needs to close. We are sorry for the inconvenience..
Running the testsuite via jepp (jepp.sourceforge.net) gives the same
failures, plus 8
The Python standard random API allows me to define multiple independent
random streams, which I can control with their own seed, e.g.
import random
generator_1 = random.Random()
generator_2 = random.Random()
generator_1.seed(100)
generator_2.seed(100)
So now generator_1 and 2 will produce the
On Wed, Aug 6, 2008 at 04:30, Ludwig [EMAIL PROTECTED] wrote:
The Python standard random API allows me to define multiple independent
random streams, which I can control with their own seed, e.g.
import random
generator_1 = random.Random()
generator_2 = random.Random()
Exactly. Using FFT to do a convolution should be done after some
signal processing readings ;) (That's why I hate FFT to do signal
processing as well).
Matthieu
2008/8/6 Nadav Horesh [EMAIL PROTECTED]:
I did about the same thing 9 year ago (in python of course). If I can recall
correctly,
Hello list. I am confused about importing numpy.
When I do
from numpy import *
and I try the min function, I get the default Python min function.
On the other hand, when I do
import numpy as np
and use the np.min function, I get the numpy min function (which is
obviously what I want).
I
On Wed, Aug 6, 2008 at 05:00, mark [EMAIL PROTECTED] wrote:
Hello list. I am confused about importing numpy.
When I do
from numpy import *
and I try the min function, I get the default Python min function.
On the other hand, when I do
import numpy as np
and use the np.min function, I
2008/8/6 Matthieu Brucher [EMAIL PROTECTED]:
Exactly. Using FFT to do a convolution should be done after some
signal processing readings ;)
When you convolve two signals, of lengths N and M, you need to pad the
FFTs to length (N+M-1) before multiplication.
You can take a look at my linear
I guess that makes sense on a certain level, but boy it is cumbersome
to explain to a class.
It pretty much defeats the whole purpose of doing from numpy import *.
Mark
On Aug 6, 12:03 pm, Robert Kern [EMAIL PROTECTED] wrote:
On Wed, Aug 6, 2008 at 05:00, mark [EMAIL PROTECTED] wrote:
Hello
Anything that defeats the purpose of doing * imports is good in my book. :-)
Seriously, willy nilly import of any package into the base namespace
is just asking for trouble.
Tell your class to import numpy as np, then there will be no chance of
confusion.
Then later tell them about from numpy
Hi Greg,
Greg Novak wrote:
Argh. I could swear that yesterday I typed test cases just like the
one you provide, and it behaved correctly. Nevertheless, it clearly
fails in spite of my memory, so attached is a version which I believe
gives the correct behavior.
It looks ok now, although I
Hi,
due to popular demand, I have updated unique1d() to optionally return
both kinds of indices:
In [3]: b, i, j = nm.unique1d( a, return_index=True, return_inverse=True )
In [4]: a
Out[4]: array([1, 1, 8, 3, 3, 5, 4])
In [6]: b
Out[6]: array([1, 3, 4, 5, 8])
In [7]: a[i]
Out[7]: array([1,
Dear list.
I've got a feeling that what I'm trying to do *should* be easy but at the
moment I can't find a non-brute-force method.
I'm working with quite a high-rank matrix; 7 dimensions filled with chi**2
values. It's form is something like this:
chi2 = numpy.ones((3,4,5,6,7,8,9))
What I
Try using slice (python builtin) to create slice objects (what is
created implicitly by :5, 1:20, etc.). slice takes the same arguments
as range. A list of these (7 in your case) can then be passed to
A[...] as a tuple.
That's how I would do it, but maybe someone else has a better idea or
can
You can access nd_image by:
from numpy.numarray import nd_image
but as Zach noted, scipy.interpolate is what you are looking for.
Nadav.
-הודעה מקורית-
מאת: [EMAIL PROTECTED] בשם Zachary Pincus
נשלח: ד 06-אוגוסט-08 19:09
אל: Discussion of Numerical Python
נושא: Re: [Numpy-discussion]
hi list,
I am trying to find 1-D cubic spline function. Google search yields
that there is a function called spline_filter1d in numarray. But I am
not able to call it.
Would someone point me to 1-D cubic spline function either in numarray
or numpy?
I can find source codes and enter in Python.
Hi Shawn,
I am trying to find 1-D cubic spline function. But I am not able to call
it. Error message can’t find “ndimage”
Ndimage is a module in SciPy, so you'd need to install that first,
not just NumPy. I'm not really familar with the available 1-D cubic
spline functions, but I think you
Thank you both, Nadav and Zach.
Shawn
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Nadav Horesh
Sent: Wednesday, August 06, 2008 12:16 PM
To: Discussion of Numerical Python
Subject: RE: [Numpy-discussion] cubic spline function in numarray or numpy
Dag Sverre Seljebotn wrote:
cdef numpy.ndarray[numpy.int64, ndim=2]
+1 it's very clear what this means. I think the keyword should be required.
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR(206) 526-6959 voice
7600 Sand Point Way NE
mark wrote:
I guess that makes sense on a certain level, but boy it is cumbersome
to explain to a class.
It pretty much defeats the whole purpose of doing from numpy import *.
which is fine by me:
Namespaces are one honking great idea -- let's do more of those!
explain namespaces to your
You're best off using scipy.
Just Google search for scipy spline:
e.g.
http://www.scipy.org/Cookbook/Interpolation
http://xinqingpeng.blogspot.com/2007/07/scipy-spline-example.html
Gary R.
Gong, Shawn (Contractor) wrote:
hi list,
I am trying to find 1-D cubic spline function. But I am not
I think the square brackets are very confusing as a numpy user not
familiar with CPython.
On 8/6/08, Christopher Barker [EMAIL PROTECTED] wrote:
Dag Sverre Seljebotn wrote:
cdef numpy.ndarray[numpy.int64, ndim=2]
+1 it's very clear what this means. I think the keyword should be required.
Hello,
When you convolve two signals, of lengths N and M, you need to pad the
FFTs to length (N+M-1) before multiplication.
You can take a look at my linear position-invariant filtering code at:
http://mentat.za.net/hg/filter
I understand your comments that I need zero padding when doing
Hi all,
My machine: Mac dual G5, OSX 10.5.4, Python 2.5.2 (r252:60911, Feb 22
2008, 07:57:53), numpy 1.1.1
After considerable agony, I succeeded in building and installing scipy
from SVN, only to be told upon importing it:
Traceback (most recent call last):
File stdin, line 1, in module
On Wed, Aug 6, 2008 at 3:57 PM, Robert Pyle [EMAIL PROTECTED] wrote:
My machine: Mac dual G5, OSX 10.5.4, Python 2.5.2 (r252:60911, Feb 22
2008, 07:57:53), numpy 1.1.1
After considerable agony, I succeeded in building and installing scipy
from SVN, only to be told upon importing it:
On Aug 6, 2008, at 4:17 PM, Alan McIntyre wrote:
You will actually need to use NumPy from svn as well, since 1.1.1
didn't have NoseTester (SciPy 0.7 will require NumPy 1.2).
Thanks. I can now import scipy, but I'm puzzled by the following:
Python 2.5.2 (r252:60911, Feb 22 2008, 07:57:53)
Thanks for the encouragement to try to dive deeper into namespaces,
but also thanks for the amin, amax suggestions.
Mark
On Aug 6, 8:21 pm, Eric Firing [EMAIL PROTECTED] wrote:
mark wrote:
Hello list. I am confused about importing numpy.
When I do
from numpy import *
and I try the min
Tester is a class, not a module. Try from numpy.testing import Tester.
On 2008-08-06, Robert Pyle [EMAIL PROTECTED] wrote:
On Aug 6, 2008, at 4:17 PM, Alan McIntyre wrote:
You will actually need to use NumPy from svn as well, since 1.1.1
didn't have NoseTester (SciPy 0.7 will require NumPy
2008/8/6 Eric Firing [EMAIL PROTECTED]:
While I agree with the other posters that import * is not preferred,
if you want to use it, the solution is to use amin and amax, which are
provided precisely to avoid the conflict. Just as arange is a numpy
analog of range, amin and amax are numpy
Hello,
When you convolve two signals, of lengths N and M, you need to pad the
FFTs to length (N+M-1) before multiplication.
You can take a look at my linear position-invariant filtering code at:
http://mentat.za.net/hg/filter
I understand your comments that I need zero padding when doing
The 0 padding is easy in numpp/pylab as in octave/matlab, by just adding one
argument. In pylab it is the a keyword:
y = fft(x, n=2*len(x))
if n is not given then n=len(x) --- normal fft
if n len(x) then it pads x with 0.
Nadav.
-הודעה מקורית-
מאת: [EMAIL PROTECTED] בשם Matthias
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