Fast Haversine distance with NumPY

haversine.py

def haversine_np(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points
    on the earth (specified in decimal degrees)

    Reference:
        https://stackoverflow.com/a/29546836/7657658
    """
    lon1, lat1, lon2, lat2 = map(np.radians, [lon1, lat1, lon2, lat2])

    dlon = lon2 - lon1
    dlat = lat2 - lat1

    a = np.sin(
        dlat / 2.0)**2 + np.cos(lat1) * np.cos(lat2) * np.sin(dlon / 2.0)**2

    c = 2 * np.arcsin(np.sqrt(a))
    km = 6371 * c
    return km

FYI Something is wrong with the formula I think. below matches an implementation I have used before and verified on https://www.movable-type.co.uk/scripts/latlong.html

https://stackoverflow.com/a/51722117

def distance(s_lat, s_lng, e_lat, e_lng):

approximate radius of earth in km

R = 6373.0

s_lat = s_lat*np.pi/180.0
s_lng = np.deg2rad(s_lng)
e_lat = np.deg2rad(e_lat)
e_lng = np.deg2rad(e_lng)

d = np.sin((e_lat - s_lat)/2)**2 + np.cos(s_lat)*np.cos(e_lat) * np.sin((e_lng - s_lng)/2)**2

return 2 * R * np.arcsin(np.sqrt(d))

distance(-33.786955,150.951098,-33.799938,150.947311)