2009/11/16 Christopher Barker chris.bar...@noaa.gov:
Anne Archibald wrote:
2009/11/13 Christopher Barker chris.bar...@noaa.gov:
Wow! great -- you sounded interested, but I had no idea you'd run out
and do it! thanks! we'll check it out.
well, it turns out the Python version is unacceptably
Anne Archibald wrote:
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
This is now implemented in SVN.
Wow! great -- you sounded
2009/11/13 Christopher Barker chris.bar...@noaa.gov:
Anne Archibald wrote:
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
This
Peter Schmidtke wrote:
On Tue, 10 Nov 2009 16:07:32 -0800, Christopher Barker
chris.bar...@noaa.gov wrote:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
How big is your set
David Cournapeau wrote:
I would love having a core C library of containers -
I'm all for that. However, I think that a very, very common need is
simply for a growable numpy array.
It seems this would actually be pretty darn easy (again, for someone
familiar with the code!).
IIUC, it would
On Thu, Nov 12, 2009 at 10:01 AM, Christopher Barker
chris.bar...@noaa.govwrote:
Peter Schmidtke wrote:
On Tue, 10 Nov 2009 16:07:32 -0800, Christopher Barker
chris.bar...@noaa.gov wrote:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a
Lou Pecora wrote:
Maybe I'm missing something simple, but if your array of 2D points is
static,
well, not quite.
a KD tree for 2D nearest neighbor seems like over kill. You
might want to try the simple approach of using boxes of points to
narrow things down by sorting on the first
On Thu, Nov 12, 2009 at 10:32 AM, Christopher Barker
chris.bar...@noaa.govwrote:
David Cournapeau wrote:
I would love having a core C library of containers -
I'm all for that. However, I think that a very, very common need is
simply for a growable numpy array.
It seems this would
On Thu, Nov 12, 2009 at 11:39, Charles R Harris
charlesr.har...@gmail.com wrote:
On Thu, Nov 12, 2009 at 10:32 AM, Christopher Barker chris.bar...@noaa.gov
wrote:
David Cournapeau wrote:
I would love having a core C library of containers -
I'm all for that. However, I think that a very,
- Original Message
From: Christopher Barker chris.bar...@noaa.gov
To: Discussion of Numerical Python numpy-discussion@scipy.org
Sent: Thu, November 12, 2009 12:37:37 PM
Subject: Re: [Numpy-discussion] finding close together points.
Lou Pecora wrote:
a KD tree for 2D nearest neighbor
2009/11/12 Lou Pecora lou_boog2...@yahoo.com:
- Original Message
From: Christopher Barker chris.bar...@noaa.gov
To: Discussion of Numerical Python numpy-discussion@scipy.org
Sent: Thu, November 12, 2009 12:37:37 PM
Subject: Re: [Numpy-discussion] finding close together points
Robert Kern wrote:
Didn't we already do this?
http://www.mail-archive.com/numpy-discussion@scipy.org/msg21010.html
Indeed we did. What I posted then ( and have improved a bit now). Is a
Python version. Written in Python, it has an advantage of using less
memory for a big array, but is
On Thu, Nov 12, 2009 at 12:52 PM, Christopher Barker
chris.bar...@noaa.govwrote:
Robert Kern wrote:
Didn't we already do this?
http://www.mail-archive.com/numpy-discussion@scipy.org/msg21010.html
Indeed we did. What I posted then ( and have improved a bit now). Is a
Python version.
On Thu, Nov 12, 2009 at 3:30 PM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Thu, Nov 12, 2009 at 12:52 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
Robert Kern wrote:
Didn't we already do this?
http://www.mail-archive.com/numpy-discussion@scipy.org/msg21010.html
Charles R Harris wrote:
So what you buy
with an array implementation is the space/time efficiency of not having
to allocate python types to put on the list. But you probably need to go
through a python type at some point anyway,
When writing Python, yes (though maybe not if you are
Charles R Harris wrote:
And here is a pep http://www.python.org/dev/peps/pep-3128/%20
That link was broken, try this one:
http://www.python.org/dev/peps/pep-3128/
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR(206) 526-6959 voice
2009/11/11 Christopher Barker chris.bar...@noaa.gov:
Anne Archibald wrote:
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
- Original Message
From: Christopher Barker chris.bar...@noaa.gov
To: Discussion of Numerical Python numpy-discussion@scipy.org
Sent: Tue, November 10, 2009 7:07:32 PM
Subject: [Numpy-discussion] finding close together points.
Hi all,
I have a bunch of points in 2-d space, and I need
On Tue, Nov 10, 2009 at 11:15 PM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Charles R Harris wrote:
I think Python lists are basically just expanding arrays and pointers
are cheap. Where you might lose is in creating python objects to put
in the list and not having ufuncs and
Hi all,
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
scipy.spatial.KDTree.query_ball_tree() seems like it's built for this.
However, I'm a bit confused. The first argument is a
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
Hi all,
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
This is an eminently reasonable thing to want, and KDTree should
support
On Tue, Nov 10, 2009 at 7:07 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
Hi all,
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
scipy.spatial.KDTree.query_ball_tree()
James Bergstra wrote:
In some cases a brute-force approach is also good.
true.
If r is a matrix of shape Nx2:
(r*r).sum(axis=1) -2 * numpy.dot(r, r.T) +
(r*r).sum(axis=1).reshape((r.shape[0], 1)) thresh**2
It's brute force, but it takes advantage of fast matrix multiplication.
I'm
On Tue, Nov 10, 2009 at 8:17 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
James Bergstra wrote:
In some cases a brute-force approach is also good.
true.
If r is a matrix of shape Nx2:
(r*r).sum(axis=1) -2 * numpy.dot(r, r.T) +
(r*r).sum(axis=1).reshape((r.shape[0], 1)) thresh**2
Also, is it not returning distances between points and themselves? Or am I
misinterpreting it?
DG
On Tue, Nov 10, 2009 at 5:17 PM, Christopher Barker
chris.bar...@noaa.govwrote:
James Bergstra wrote:
In some cases a brute-force approach is also good.
true.
If r is a matrix of shape
On Tue, Nov 10, 2009 at 7:48 PM, Anne Archibald
peridot.face...@gmail.com wrote:
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
Hi all,
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old
Anne Archibald wrote:
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
This is an eminently reasonable thing to want, and
On Tue, Nov 10, 2009 at 10:51 PM, Christopher Barker
chris.bar...@noaa.govwrote:
Anne Archibald wrote:
2009/11/10 Christopher Barker chris.bar...@noaa.gov:
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another
Charles R Harris wrote:
I think Python lists are basically just expanding arrays and pointers
are cheap. Where you might lose is in creating python objects to put
in the list and not having ufuncs and the rest of the numpy machinery.
If you don't need the machinery, lists are probably not a
On Wed, Nov 11, 2009 at 01:15, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
- The Apple Core Foundation (I have to check the Apple license is
ok).
No. The APSL is not DFSG-free.
It is more complex, but is designed with objective-C in mind,
meaning integration with the C python
Robert Kern wrote:
No. The APSL is not DFSG-free.
It was too good to be true, I guess.
http://c-algorithms.sourceforge.net/
Thanks for the link,
David
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On Tue, 10 Nov 2009 16:07:32 -0800, Christopher Barker
chris.bar...@noaa.gov wrote:
Hi all,
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
How big is your set of points?
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