On Tue, Jun 2, 2009 at 10:56 PM, Ryan May rma...@gmail.com wrote:
On Tue, Jun 2, 2009 at 5:59 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Robin wrote:
On Tue, Jun 2, 2009 at 11:36 AM, David Cournapeau courn...@gmail.com
wrote:
Done in r7031 - correlate/PyArray_Correlate
On Thu, Jun 4, 2009 at 5:14 AM, David Cournapeau courn...@gmail.com wrote:
On Tue, Jun 2, 2009 at 10:56 PM, Ryan May rma...@gmail.com wrote:
On Tue, Jun 2, 2009 at 5:59 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Robin wrote:
On Tue, Jun 2, 2009 at 11:36 AM, David
I wonder if xcorrelate would be a better name than acorrelate?
I think it would.
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion
On Tue, Jun 2, 2009 at 12:37 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Robert Kern wrote:
This does not solve the C function problem (PyArray_Correlate). The easy
solution would be to keep the current C version, deal with the problem
in python for acorrelate for the time being,
On Tue, Jun 2, 2009 at 11:36 AM, David Cournapeau courn...@gmail.com wrote:
Done in r7031 - correlate/PyArray_Correlate should be unchanged, and
acorrelate/PyArray_Acorrelate implement the conventional definitions,
I don't know if it's been discussed before but while people are
thinking
Robin wrote:
On Tue, Jun 2, 2009 at 11:36 AM, David Cournapeau courn...@gmail.com wrote:
Done in r7031 - correlate/PyArray_Correlate should be unchanged, and
acorrelate/PyArray_Acorrelate implement the conventional definitions,
I don't know if it's been discussed before but while
On Tue, Jun 2, 2009 at 5:59 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Robin wrote:
On Tue, Jun 2, 2009 at 11:36 AM, David Cournapeau courn...@gmail.com
wrote:
Done in r7031 - correlate/PyArray_Correlate should be unchanged, and
acorrelate/PyArray_Acorrelate implement the
I also think that the conjugate should be taken. I spent the last few weeks
using correlate to experiment with
signal processing and I got strange results until I realised that I had to
manually take the conjugate. It
would also be good if the function did it since applying the conjugate to
Charles R Harris wrote:
I also think that having weighting options would be good. I now
understand the complexities of the various
weightings that can be applied to the correlation i.e. biased vs
unbiased but I think that having correlate
include these options might
On Mon, Jun 1, 2009 at 00:05, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
I think we should just fix it to use conjugate - I will do this in the
branch, and I will integrate it in the trunk later unless someone stands
up vehemently against the change. I opened up a ticket to track
On Mon, Jun 1, 2009 at 11:48 AM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Mon, Jun 1, 2009 at 10:35 AM, Robert Kern robert.k...@gmail.comwrote:
On Mon, Jun 1, 2009 at 00:05, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
I think we should just fix it to use conjugate -
On Mon, Jun 1, 2009 at 13:44, Charles R Harris
charlesr.har...@gmail.com wrote:
On Mon, Jun 1, 2009 at 11:48 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Mon, Jun 1, 2009 at 10:35 AM, Robert Kern robert.k...@gmail.com
wrote:
On Mon, Jun 1, 2009 at 00:05, David Cournapeau
Charles R Harris wrote:
On Mon, Jun 1, 2009 at 11:48 AM, Charles R Harris
charlesr.har...@gmail.com mailto:charlesr.har...@gmail.com wrote:
On Mon, Jun 1, 2009 at 10:35 AM, Robert Kern
robert.k...@gmail.com mailto:robert.k...@gmail.com wrote:
On Mon, Jun 1, 2009 at
On Mon, Jun 1, 2009 at 22:33, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Charles R Harris wrote:
On Mon, Jun 1, 2009 at 11:48 AM, Charles R Harris
charlesr.har...@gmail.com mailto:charlesr.har...@gmail.com wrote:
On Mon, Jun 1, 2009 at 10:35 AM, Robert Kern
Hi,
After my previous email, I have opened a ticket #1117 (correlate not order
dependent)
I have found that the correlate function is defined in multiarraymodule.c and
that inputs are being swapped using the following code
n1 = ap1-dimensions[0];
n2 = ap2-dimensions[0];
if (n1 n2)
Charles R Harris wrote:
On Sun, May 31, 2009 at 11:54 AM, rob steed rjst...@talk21.com
mailto:rjst...@talk21.com wrote:
Hi,
After my previous email, I have opened a ticket #1117 (correlate
not order dependent)
I have found that the correlate function is defined in
On Sun, May 31, 2009 at 7:18 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Charles R Harris wrote:
On Sun, May 31, 2009 at 11:54 AM, rob steed rjst...@talk21.com
mailto:rjst...@talk21.com wrote:
Hi,
After my previous email, I have opened a ticket #1117
Charles R Harris wrote:
On Sun, May 31, 2009 at 7:18 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp mailto:da...@ar.media.kyoto-u.ac.jp
wrote:
Charles R Harris wrote:
On Sun, May 31, 2009 at 11:54 AM, rob steed rjst...@talk21.com
mailto:rjst...@talk21.com
On Sun, May 31, 2009 at 9:08 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Charles R Harris wrote:
On Sun, May 31, 2009 at 7:18 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp mailto:da...@ar.media.kyoto-u.ac.jp
wrote:
Charles R Harris wrote:
Charles R Harris wrote:
On Sun, May 31, 2009 at 9:08 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp mailto:da...@ar.media.kyoto-u.ac.jp
wrote:
Charles R Harris wrote:
On Sun, May 31, 2009 at 7:18 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp
Hi all,
I have been using numpy.correlate and was finding something weird. I now think
that there might be a bug.
Correlations should be order dependent eg. correlate(x,y) != correlate(y,x) in
general (whereas convolutions are symmetric)
import numpy as N
x = N.array([1,0,0])
y =
2009/5/18 rob steed rjst...@talk21.com:
This works fine. However, if the arrays have different lengths, we get a
problem.
y2=N.array([0,0,0,1])
N.correlate(x,y2,'full')
This looks like a bug to me.
In [54]: N.correlate([1, 0, 0, 0], [0, 0, 0, 1],'full')
Out[54]: array([1, 0, 0, 0, 0, 0,
2009/5/18 Stéfan van der Walt ste...@sun.ac.za:
2009/5/18 rob steed rjst...@talk21.com:
This works fine. However, if the arrays have different lengths, we get a
problem.
y2=N.array([0,0,0,1])
N.correlate(x,y2,'full')
This looks like a bug to me.
In [54]: N.correlate([1, 0, 0, 0], [0, 0,
Hi Stefan,
yes, indeed, that's what I thought. This result is odd. Has correlate
been changed since version 1.0.4, or should I submit this as a bug?
Best regards,
Hanno
Stéfan van der Walt [EMAIL PROTECTED] said:
--=_Part_25307_10322093.1219268954678
Content-Type: text/plain;
Hi Hanno
2008/8/22 Hanno Klemm [EMAIL PROTECTED]:
yes, indeed, that's what I thought. This result is odd. Has correlate
been changed since version 1.0.4, or should I submit this as a bug?
Is there any way that you could try out the latest release on your
machine and see if it solves your
Hi Stefan,
I checked it with numpy version 1.1.1 just now and the result is the same:
x = N.array([0.,0,1,0,0])
y1 = N.array([1.,0,0,0,0])
N.correlate(x,y1, mode='full')
array([ 0., 0., 0., 0., 0., 0., 1., 0., 0.])
y2 = N.array([1.,0,0,0,0,0,0])
N.correlate(x,y2, mode='full')
Hi All,
after the discussion on numpy.correlate some time ago, regarding
complex conjugation, etc. I today was pointed to yet another oddity,
which I hope somebody could explain to me, as to why that's a feature,
rather than a bug. I'm thoroughly confused by the following behaviour:
In [29]:
2008/8/20 Hanno Klemm [EMAIL PROTECTED]:
In [29]: x = array([0.,0.,1, 0, 0])
In [35]: y1 = array([1,0,0,0,0])
In [36]: correlate(x,y1,mode='full')
Out[36]: array([ 0., 0., 0., 0., 0., 0., 1., 0., 0.])
That doesn't look right. Under r5661:
In [60]: np.convolve([0, 0, 1, 0, 0], [1,
28 matches
Mail list logo
