geodesy.haversine_distance

Attributes

AXIS_A
AXIS_B
RADIUS

Functions

haversine_distance(→ float)

Calculate great circle distance between two points in a sphere,

Module Contents

geodesy.haversine_distance.haversine_distance(lat1: float, lon1: float, lat2: float, lon2: float) → float

Calculate great circle distance between two points in a sphere, given longitudes and latitudes https://en.wikipedia.org/wiki/Haversine_formula

We know that the globe is “sort of” spherical, so a path between two points isn’t exactly a straight line. We need to account for the Earth’s curvature when calculating distance from point A to B. This effect is negligible for small distances but adds up as distance increases. The Haversine method treats the earth as a sphere which allows us to “project” the two points A and B onto the surface of that sphere and approximate the spherical distance between them. Since the Earth is not a perfect sphere, other methods which model the Earth’s ellipsoidal nature are more accurate but a quick and modifiable computation like Haversine can be handy for shorter range distances.

Args:

lat1, lon1: latitude and longitude of coordinate 1 lat2, lon2: latitude and longitude of coordinate 2

Returns:

geographical distance between two points in metres

>>> from collections import namedtuple
>>> point_2d = namedtuple("point_2d", "lat lon")
>>> SAN_FRANCISCO = point_2d(37.774856, -122.424227)
>>> YOSEMITE = point_2d(37.864742, -119.537521)
>>> f"{haversine_distance(*SAN_FRANCISCO, *YOSEMITE):0,.0f} meters"
'254,352 meters'

geodesy.haversine_distance.AXIS_A = 6378137.0

geodesy.haversine_distance.AXIS_B = 6356752.314245

geodesy.haversine_distance.RADIUS = 6378137