>
>
> --
>
> Message: 6
> Date: Thu, 3 May 2012 10:00:11 -0700
> From: Keith Goodman
> Subject: Re: [Numpy-discussion] record arrays initialization
> To: Discussion of Numerical Python
> Message-ID:
>
> Content-Type: te
On Wed, May 2, 2012 at 4:46 PM, Kevin Jacobs
wrote:
> The cKDTree implementation is more than 4 times faster than the brute-force
> approach:
>
> T = scipy.spatial.cKDTree(targets)
>
> In [11]: %timeit foo1(element, targets) # Brute force
> 1000 loops, best of 3: 385 us per loop
>
> In [12]: %
On Wed, May 2, 2012 at 6:46 PM, Kevin Jacobs
wrote:
> On Wed, May 2, 2012 at 7:25 PM, Aronne Merrelli
> wrote:
>>
>> In general this is a good suggestion - I was going to mention it
>> earlier - but I think for this particular problem it is not better
>> than the "brute force" and argmin() NumPy
On Wednesday, May 2, 2012, Stéfan van der Walt wrote:
> On Wed, May 2, 2012 at 4:46 PM, Kevin Jacobs
>
> >
> > wrote:
> > A FLANN implementation should be even faster--perhaps by as much as
> another
> > factor of two.
>
> I guess it depends on whether you care about the "Approximate" in
> "Fast
On Wed, May 2, 2012 at 4:46 PM, Kevin Jacobs
wrote:
> A FLANN implementation should be even faster--perhaps by as much as another
> factor of two.
I guess it depends on whether you care about the "Approximate" in
"Fast Library for Approximate Nearest Neighbors".
Stéfan
_
On Wed, May 2, 2012 at 4:26 PM, Moroney, Catherine M (388D)
wrote:
> Using structured arrays is making my code complex when I try to call the
> vectorized function. If I stick to the original record arrays, what's the
> best way of initializing b from a without doing an row-by-row copy?
What doe
On Wed, May 2, 2012 at 7:25 PM, Aronne Merrelli
wrote:
> In general this is a good suggestion - I was going to mention it
> earlier - but I think for this particular problem it is not better
> than the "brute force" and argmin() NumPy approach. On my laptop, the
> KDTree query is about a factor of
On May 2, 2012, at 3:23 PM,
wrote:
>> A) ?How do I most efficiently construct a record array from a single array?
>> I want to do the following, but it segfaults on me when i try to print b.
>>
>> vtype = [("x", numpy.ndarray)]
>> a = numpy.arange(0, 16).reshape(4,4)
>> b = numpy.recarray((4)
On Wed, May 2, 2012 at 5:27 PM, Kevin Jacobs
wrote:
> On Wed, May 2, 2012 at 5:45 PM, Moroney, Catherine M (388D)
> wrote:
>>
>> Thanks to Perry for some very useful off-list conversation. I realize
>> that
>> I wasn't being clear at all in my earlier description of the problem so
>> here it i
On Wed, May 2, 2012 at 5:45 PM, Moroney, Catherine M (388D) <
catherine.m.moro...@jpl.nasa.gov> wrote:
> Thanks to Perry for some very useful off-list conversation. I realize
> that
> I wasn't being clear at all in my earlier description of the problem so
> here it is
> in a nutshell:
>
> Find t
On Wed, May 2, 2012 at 2:45 PM, Moroney, Catherine M (388D)
wrote:
> Find the best match in an array t(5000, 7) for a single vector e(7). Now
> scale
> it up so e is (128, 512, 7) and I want to return a (128, 512) array of the
> t-identifiers
> that are the best match for e. "Best match" is de
Thanks to Perry for some very useful off-list conversation. I realize that
I wasn't being clear at all in my earlier description of the problem so here it
is
in a nutshell:
Find the best match in an array t(5000, 7) for a single vector e(7). Now scale
it up so e is (128, 512, 7) and I want to
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