Find the closest latitude and longitude

Question

I\'m writing a small program and to improve efficiency, I need to be able to find the closest latitude and longitude in my array.

Assume you have the following code:

Answer 1

Also u can simple do:

import mpu
def distance(point1, point2):
    return mpu.haversine_distance(point1, point2)

def closest(data, this_point):
    return min(data, key=lambda x: distance(this_point, x))

Answer 2

For a correct calculation of the distance between points on the globe, you need something like the Haversine formula. Using the Python implementation offered in this answer, you could code it like this:

from math import cos, asin, sqrt

def distance(lat1, lon1, lat2, lon2):
    p = 0.017453292519943295
    a = 0.5 - cos((lat2-lat1)*p)/2 + cos(lat1*p)*cos(lat2*p) * (1-cos((lon2-lon1)*p)) / 2
    return 12742 * asin(sqrt(a))

def closest(data, v):
    return min(data, key=lambda p: distance(v['lat'],v['lon'],p['lat'],p['lon']))

tempDataList = [{'lat': 39.7612992, 'lon': -86.1519681}, 
                {'lat': 39.762241,  'lon': -86.158436 }, 
                {'lat': 39.7622292, 'lon': -86.1578917}]

v = {'lat': 39.7622290, 'lon': -86.1519750}
print(closest(tempDataList, v))

Answer 3

if earth is plane,

from itertools import combinations
from math import sqrt

coords = [{'lat': 39.7612992 , 'lon': -86.1519681}, 
                {"lat": 39.762241, "lon": -86.158436}, 
                {"lat": 39.7622292, "lon": -86.1578917}]


def euclidean(l1, l2):
    return ((l1[0]**2)-(l2[0]**2)) + ((l1[1]**2)-(l2[1]**2)) 

pairs = [j for j in combinations([i.values() for i in coords], 2)]
pairs.sort(key= lambda x: euclidean(*x))
print pairs[-1]