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
You can solve the negative bearing problem by adding 360°. Unfortunately, this might result in bearings larger than 360° for positive bearings. This is a good candidate for the modulo operator, so all in all you should add the line
Bearing = (Bearing + 360) % 360
at the end of your method.
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
Here's a Python version:
from math import radians, cos, sin, asin, 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, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
# haversine formula
dlon = lon2 - lon1
dlat = lat2 - lat1
a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
c = 2 * asin(sqrt(a))
r = 6371 # Radius of earth in kilometers. Use 3956 for miles
return c * r
You can try the following:
from haversine import haversine
haversine((45.7597, 4.8422),(48.8567, 2.3508), unit='mi')
243.71209416020253