Find the closest match of a list in a list containing lists

Question

I have a list with two elements like this:

list_a = [27.666521, 85.437447]

and another list like this:

big_list = [[27.666519,          


        

Answer 1

From your question, it's hard to tell how you want to measure the distance, so I simply assume you mean Euclidean distance.

You can use the key parameter to min():

from functools import partial

def distance_squared(x, y):
    return (x[0] - y[0])**2 + (x[1] - y[1])**2

print min(big_list, key=partial(distance_squared, list_a))

Answer 2

Assumptions:

• You intend to make this type query more than once on the same list of lists
• Both the query list and the lists in your list of lists represent points in a n-dimensional euclidean space (here: a 2-dimensional space, unlike GPS positions that come from a spherical space).

This reads like a nearest neighbor search. Probably you should take into consideration a library dedicated for this, like scikits.ann.

Example:

import scikits.ann as ann
import numpy as np
k = ann.kdtree(np.array(big_list))
indices, distances = k.knn(list_a, 1)

This uses euclidean distance internally. You should make sure, that the distance measure you apply complies your idea of proximity.

You might also want to have a look on Quadtree, which is another data structure that you could apply to avoid the brute force minimum search through your entire list of lists.