I would like to know how to get the distance and bearing between 2 GPS points. I have researched on the haversine formula. Someone told me
Here's a numpy vectorized implementation of the Haversine Formula given by @Michael Dunn, gives a 10-50 times improvement over large vectors.
from numpy import radians, cos, sin, arcsin, sqrt
def haversine(lon1, lat1, lon2, lat2):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees)
"""
#Convert decimal degrees to Radians:
lon1 = np.radians(lon1.values)
lat1 = np.radians(lat1.values)
lon2 = np.radians(lon2.values)
lat2 = np.radians(lat2.values)
#Implementing Haversine Formula:
dlon = np.subtract(lon2, lon1)
dlat = np.subtract(lat2, lat1)
a = np.add(np.power(np.sin(np.divide(dlat, 2)), 2),
np.multiply(np.cos(lat1),
np.multiply(np.cos(lat2),
np.power(np.sin(np.divide(dlon, 2)), 2))))
c = np.multiply(2, np.arcsin(np.sqrt(a)))
r = 6371
return c*r