Great circle calculations with numpy

In this very short post I want to point you to some code for calculating the centroid and distance to that centroid for a set of points in numpy. As bonus I also included some profiling. Note that I already blogged about the centroid function in a previous post.

from math import atan2, sqrt, degrees
import numpy as np
from math import radians, sin, cos

RADIUS = 6371.009


def get_centroid(points):
    xy = np.asarray(points)
    xy = np.radians(xy)
    lon, lat = xy[:, 0], xy[:, 1]
    avg_x = np.sum(np.cos(lat) * np.cos(lon)) / xy.shape[0]
    avg_y = np.sum(np.cos(lat) * np.sin(lon)) / xy.shape[0]
    avg_z = np.sum(np.sin(lat)) / xy.shape[0]
    center_lon = atan2(avg_y, avg_x)
    hyp = sqrt(avg_x * avg_x + avg_y * avg_y)
    center_lat = atan2(avg_z, hyp)
    return degrees(center_lon), degrees(center_lat)


def gc_distance_points(a, points):
    b = np.asarray(points)
    lat1, lng1 = radians(a[1]), radians(a[0])
    lat2, lng2 = np.radians(b[:, 1]), np.radians(b[:, 0])

    sin_lat1, cos_lat1 = sin(lat1), cos(lat1)
    sin_lat2, cos_lat2 = np.sin(lat2), np.cos(lat2)

    delta_lng = np.subtract(lng2, lng1)
    cos_delta_lng, sin_delta_lng = np.cos(delta_lng), np.sin(delta_lng)

    d = np.arctan2(np.sqrt((cos_lat2 * sin_delta_lng) ** 2 +
                 (cos_lat1 * sin_lat2 -
                  sin_lat1 * cos_lat2 * cos_delta_lng) ** 2),
                 sin_lat1 * sin_lat2 + cos_lat1 * cos_lat2 * cos_delta_lng)

    return RADIUS * d


def gc_dist(a, b):
        from math import radians, sin, cos, sqrt, atan2
        lat1, lng1 = radians(a[1]), radians(a[0])
        lat2, lng2 = radians(b[1]), radians(b[0])

        sin_lat1, cos_lat1 = sin(lat1), cos(lat1)
        sin_lat2, cos_lat2 = sin(lat2), cos(lat2)

        delta_lng = lng2 - lng1
        cos_delta_lng, sin_delta_lng = cos(delta_lng), sin(delta_lng)

        d = atan2(sqrt((cos_lat2 * sin_delta_lng) ** 2 +
                       (cos_lat1 * sin_lat2 -
                        sin_lat1 * cos_lat2 * cos_delta_lng) ** 2),
                  sin_lat1 * sin_lat2 + cos_lat1 * cos_lat2 * cos_delta_lng)

        return RADIUS * d


if __name__ == '__main__':

    import random
    random.seed(42)
    pts = [(random.uniform(-180, 180), random.uniform(-90, 90)) for _ in range(1000000)]
    
    centr = get_centroid(pts)

    import cProfile

    cProfile.runctx('gc_distance_points(centr, pts)', globals(), locals())
    cProfile.runctx('dists = [gc_dist(centr, b) for b in pts]', globals(), locals())

All code is also available at Github. Feel free to post a comment or email in case you have any questions.