Hello again,
The best way so far that's come to my attention is to use:
numpy.ma.masked_object
The problem with this is that it's looking for a specific instance of an
object. So if the user had some elements of their array that were, for
example, randomString , then it would not be picked up
On Tue, Nov 10, 2009 at 12:09 PM, Darryl Wallace
darryl.wall...@prosensus.ca wrote:
Hello again,
The best way so far that's come to my attention is to use:
numpy.ma.masked_object
The problem with this is that it's looking for a specific instance of an
object. So if the user had some elements
Hello,
On Tue, Nov 10, 2009 at 1:32 PM, Gökhan Sever gokhanse...@gmail.com wrote:
On Tue, Nov 10, 2009 at 12:09 PM, Darryl Wallace
darryl.wall...@prosensus.ca wrote:
Hello again,
The best way so far that's come to my attention is to use:
numpy.ma.masked_object
The problem with this is
On Tue, Nov 10, 2009 at 11:14 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Nov 10, 2009 at 10:53 AM, Darryl Wallace
darryl.wall...@prosensus.ca wrote:
I currently do as you suggested. But when the dataset size becomes large,
it gets to be quite slow due to the overhead of python
On Tue, Nov 10, 2009 at 11:28 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Nov 10, 2009 at 11:14 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Nov 10, 2009 at 10:53 AM, Darryl Wallace
darryl.wall...@prosensus.ca wrote:
I currently do as you suggested. But when the dataset size
Thanks for the help,
I'll test out this simple example.
On Tue, Nov 10, 2009 at 2:28 PM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Nov 10, 2009 at 11:14 AM, Keith Goodman kwgood...@gmail.com
wrote:
On Tue, Nov 10, 2009 at 10:53 AM, Darryl Wallace
darryl.wall...@prosensus.ca wrote:
On Nov 10, 2009, at 1:09 PM, Darryl Wallace wrote:
Hello again,
The best way so far that's come to my attention is to use:
numpy.ma.masked_object
Will only work for masking one specific string, as you've noticed.
Can anyone help me so that all strings are found in the array without
I don't know if your 'long double' detection code is complete yet, but I
thought I'd share the current build output on one of our Solaris
machines. It looks like it may just be a typo difference between
'IEEE_QUAD_BE' in long_double_representation() and 'IEEE_QUAD_16B_BE' in
setup.py, but I
Hello!
On Tue, Nov 10, 2009 at 2:23 PM, Pierre GM pgmdevl...@gmail.com wrote:
On Nov 10, 2009, at 1:09 PM, Darryl Wallace wrote:
Hello again,
The best way so far that's come to my attention is to use:
numpy.ma.masked_object
Will only work for masking one specific string, as you've
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
I am building Numpy on OSX 10.6 using a recent update
from SVN (r7726). Though I was able to build the package
successfully, the resulting package generates an ImportError:
import umath
ImportError: dlopen(/Library/Python/2.6/site-packages/
numpy-1.4.0.dev7726-py2.6-macosx-10.6-
Chris wrote:
I am building Numpy on OSX 10.6 using a recent update
from SVN (r7726). Though I was able to build the package
successfully, the resulting package generates an ImportError:
import umath
ImportError: dlopen(/Library/Python/2.6/site-packages/
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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