[scikit-learn] Nearest neighbor search with 2 distance measures

Rohin Kumar yrohinkumar at gmail.com
Tue Aug 1 09:15:56 EDT 2017

Since you seem to be from Astrophysics/Cosmology background (I am assuming
you are jakevdp - the creator of astroML - if you are - I am lucky!), I can
explain my application scenario. I am trying to calculate the anisotropic
two-point correlation function something like done in rp_pi_tpcf
 or s_mu_tpcf
using pairs (DD,DR,RR) calculated from BallTree.two_point_correlation

In halotools (
it is implemented using rectangular grids. I could calculate 2pcf with
custom metrics using one variable with BallTree as done in astroML. I
intend to find the anisotropic counter part.

Thanks & Regards,

Y.Rohin Kumar,

On Tue, Aug 1, 2017 at 5:18 PM, Rohin Kumar <yrohinkumar at gmail.com> wrote:

> Dear Jake,
> Thanks for your response. I meant to group/count pairs in boxes (using two
> arrays simultaneously-hence needing 2 metrics) instead of one distance
> array as the binning parameter. I don't know if the algorithm supports such
> a thing. For now, I am proceeding with your suggestion of two ball trees at
> huge computational cost. I hope I am able to frame my question properly.
> Thanks & Regards,
> Rohin.
> On Mon, Jul 31, 2017 at 8:16 PM, Jacob Vanderplas <
> jakevdp at cs.washington.edu> wrote:
>> On Sun, Jul 30, 2017 at 11:18 AM, Rohin Kumar <yrohinkumar at gmail.com>
>> wrote:
>>> *update*
>>> May be it doesn't have to be done at the tree creation level. It could
>>> be using loops and creating two different balltrees. Something like
>>> tree1=BallTree(X,metric='metric1') #for x-z plane
>>> tree2=BallTree(X,metric='metric2') #for y-z plane
>>> And then calculate correlation functions in a loop to get tpcf(X,r1,r2)
>>>  using tree1.two_point_correlation(X,r1) and
>>> tree2.two_point_correlation(X,r2)
>> Hi Rohin,
>> It's not exactly clear to me what you wish the tree to do with the two
>> different metrics, but in any case the ball tree only supports one metric
>> at a time. If you can construct your desired result from two ball trees
>> each with its own metric, then that's probably the best way to proceed,
>>    Jake
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