Hi all,
I have the following problem:
Given a array with dimension Nx3, where N is generally greater than
1.000.000, for each item in this array I have to calculate its density,
Where its density is the number of items from the same array with
distance less than a given r. The items are the
On Saturday, January 14, 2012, Thiago Franco de Moraes
totonixs...@gmail.com wrote:
Hi all,
I have the following problem:
Given a array with dimension Nx3, where N is generally greater than
1.000.000, for each item in this array I have to calculate its density,
Where its density is the
Den 14.01.2012 21:52, skrev Thiago Franco de Moraes:
Is there a better and faster way of doing that? Is there something in my
Cython implementation I can do to perform better?
You need to use a kd-tree to make the computation run in O(n log n) time
instead of O(n**2).
scipy.spatial.cKDTree
This sort of makes sense, but is it the 'correct' behavior?
In [20]: zeros(2, 'S')
Out[20]:
array(['', ''],
dtype='|S1')
It might be more consistent to return '0' instead, as in
In [3]: zeros(2, int).astype('S')
Out[3]:
array(['0', '0'],
dtype='|S24')
Chuck
On Sat, Jan 14, 2012 at 4:12 PM, Charles R Harris charlesr.har...@gmail.com
wrote:
This sort of makes sense, but is it the 'correct' behavior?
In [20]: zeros(2, 'S')
Out[20]:
array(['', ''],
dtype='|S1')
It might be more consistent to return '0' instead, as in
In [3]: zeros(2,
On Sat, Jan 14, 2012 at 4:16 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:12 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
This sort of makes sense, but is it the 'correct' behavior?
In [20]: zeros(2, 'S')
Out[20]:
array(['', ''],
dtype='|S1')
It
I've put up a pull request for a fix to ticket #1973. Currently the fix
simply propagates the maskna flag when the *.astype method is called. A
more complicated option would be to add a maskna keyword to specify whether
the output is masked or not or propagates the type of the source, but that
Hi,
I am finding it less than useful to have the negative index wrapping on
nd-arrays. Here is a short example:
import numpy as np
a = np.zeros((3, 3))
a[:,2] = 1000
print a[0,-1]
print a[0,-1]
print a[-1,-1]
In all cases 1000 is printed out.
What I am after is a way to say please don't wrap
On Sat, Jan 14, 2012 at 5:25 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:16 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:12 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
This sort of makes sense, but is it the 'correct' behavior?
In
On Thu, Dec 29, 2011 at 2:36 PM, Ralf Gommers
ralf.gomm...@googlemail.comwrote:
On Thu, Dec 29, 2011 at 9:50 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I thought I'd raise this topic just to get some ideas out there. At the
moment I see two areas that I'd like to see
No dia Sábado, 14 de Janeiro de 2012, Benjamin rootben.r...@ou.edu escreveu:
On Saturday, January 14, 2012, Thiago Franco de Moraes
totonixs...@gmail.com wrote:
Hi all,
I have the following problem:
Given a array with dimension Nx3, where N is generally greater than
1.000.000, for each
On Sat, Jan 14, 2012 at 5:21 PM, josef.p...@gmail.com wrote:
On Sat, Jan 14, 2012 at 5:25 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:16 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:12 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On 15. jan. 2012, at 01:21, josef.p...@gmail.com wrote:
On Sat, Jan 14, 2012 at 5:25 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:16 PM, Benjamin Root ben.r...@ou.edu wrote:
On Sat, Jan 14, 2012 at 4:12 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
This
13 matches
Mail list logo
