Calculate distance between latitude longitude pairs with Python

haversine.py

#!/usr/bin/env python

# Haversine formula example in Python
# Author: Wayne Dyck

import math

def distance(origin, destination):
    lat1, lon1 = origin
    lat2, lon2 = destination
    radius = 6371 # km

    dlat = math.radians(lat2-lat1)
    dlon = math.radians(lon2-lon1)
    a = math.sin(dlat/2) * math.sin(dlat/2) + math.cos(math.radians(lat1)) \
        * math.cos(math.radians(lat2)) * math.sin(dlon/2) * math.sin(dlon/2)
    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
    d = radius * c

    return d

Cool, tnx!

My question may be very basic or even silly. If I have lat1=40.5, lat2=42, long1=-90 and long2=-93.
Where do I put these values in the above script?

Is the script written in the IDLE window?
Thanks and sorry for this basic, maybe stupid inquiry.
thanks
PHos

@osph, you could use the function with those values by adding code like this to the end:

lat1 = 40.5; lat2 = 42; long1 = -90; long2 = -93
print( distance((lat1, long1), (lat2, long2)) )

However it would be better to save the original script in a file namedhaversine.pyand then create separate scripts that use the function defined in it. This makes it a module which could be used with something like the following in these other scripts:

import haversine

lat1 = 40.5; lat2 = 42; long1 = -90; long2 = -93
print( haversine.distance((lat1, long1), (lat2, long2)) )

The script may have been written in IDLE, or any one of several other programming tools, including just a plain text editor -- it doesn't really matter.

If i want use with miles? radius can be 3959?

Thank you! you just made some Ecologist very happy :)

@marioidival The units of the equation are determined by the units of 'radius'. Which corresponds to the spherical radius of the Earth.

3959 # radius of the great circle in miles...some algorithms use 3956
6371 # radius in kilometers...some algorithms use 6367
3959 * 5280 # radius in feet
6371 * 1000 # radius in meters

Can this be modded to work with ALOT of longtitudes and latitudes?

Thank you very much. I study atmospheric science. Your program is useful for me.

Vector implementation (you can pass 4 numpy arrays instead of scalar values):

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)) 

Thanks so much! Just what I needed.

Great! Thanks!

Hello, thank you very much for this masterpiece. But my concern is how to do so when you have an excel file, I have bunch of cities and finding the distance from those cities to one reference point (which is also a city). Thanks

Thanks much , this helped a machine learning engineer.

Hi
I need to find the distance between two gps trajectories, from US 101 dataset, which covers totally 2000ft distance.

"Vehicle ID","Frame ID","Total Frames","Global Time","Local X","Local Y","Global X","Global Y","V_Len","V_Width","V_Class","V_Vel","V_Acc","Lane_ID","Pre_Veh","Fol_Veh","Spacing","Headway"

2,13,437,1118846980200,16.467,35.381,6451137.641,1873344.962,14.5,4.9,2,40.00,0.00,2,0,0,0.00,0.00
2,14,437,1118846980300,16.447,39.381,6451140.329,1873342.000,14.5,4.9,2,40.00,0.00,2,0,0,0.00,0.00
2,15,437,1118846980400,16.426,43.381,6451143.018,1873339.038,14.5,4.9,2,40.00,0.00,2,0,0,0.00,0.00
2,16,437,1118846980500,16.405,47.380,6451145.706,1873336.077,14.5,4.9,2,40.00,0.00,2,0,0,0.00,0.00
2,17,437,1118846980600,16.385,51.381,6451148.395,1873333.115,14.5,4.9,2,40.00,0.00,2,0,0,0.00,0.00

But when I am trying to find the distance between two adjacent points of the same vehicle, Its giving

in more than 20 kms..

Can any you help me to find the distance between two adjacent trajectories
I need to segregate the dataset into subsections covering 200ft distance each..

Hello, I have a list with 700 cities and I want to find the city where the sum of distances will be minimun
I defined a function that will give me that sum, but what I should do to find the lat,long where the sum of distances will be minimum? tks

Thank you! @MalyutinS

Hello i have two co-ordinates values sources and destination ,my source co-ordinates values are changing when i move robot , for that i have to calculate distance for each positional values pls help me how to write python code for that

Hello i have two co-ordinates values sources and destination ,my source co-ordinates values are changing when i move robot , for that i have to calculate the distance for each positional values pls help me how to write python code for that

#I am adding the code to calculate the distance between two coordinates, you can call this function inside a for loop to get the distance between source and destination as soon as your bot makes a displacement.

def distance(source , destination): 
    lat1, lon1 = source [0],source [1]
    lat2, lon2 = destination[0],destination[1]
    radius = 6371 # km
    dlat = math.radians(lat2-lat1)
    dlon = math.radians(lon2-lon1)
    a = math.sin(dlat/2) * math.sin(dlat/2) + math.cos(math.radians(lat1)) \
        * math.cos(math.radians(lat2)) * math.sin(dlon/2) * math.sin(dlon/2)
    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
    d = radius * c
    d = d*1000  #Converting distance to Metre as bot will make small displacements
    return d

#CALLING THE FUNCTION

source = [lat1, lon1] #Coordinates for the initial position of the robot
distance_measured = 0 #initially total distance covered by bot is 0.
Loop:
   new_latitude = GPS.latitude #  get current latitude of bot
   new_longitude = GPS.longitude # get current longitude bot
   destination = [new_latitude , new_longitude ]
   if (distance(source, destination) != 0):
         distance_measured = distance_measured + distance(source, destination)
         last_latitude = new_latitude  
	 last_longitude = new_longitude
         source =[last_latitude,last_longitude] 

Hope this helps!!

Hello, thank you very much for this masterpiece. But my concern is how to do so when you have an excel file, I have bunch of cities and finding the distance from those cities to one reference point (which is also a city). Thanks

Hello @Zagroz, did you able to find the distances from an excel file using this code? I am also stuck in similar kind of situation. Thank you!

Hello, thank you very much for this masterpiece. But my concern is how to do so when you have an excel file, I have a bunch of cities and finding the distance from those cities to one reference point (which is also a city). Thanks

Hello @Zagroz, did you able to find the distances from an excel file using this code? I am also stuck in a similar kind of situation. Thank you!

Hello, I have implemented something similar to what you are trying to do. You can visit my repo which involves what you desire. The link is here:

https://github.com/vivek1240/k-means-clustering-via-haversine-distance-/blob/master/clustering_stores_via_haversine_distance_kmeans.ipynb

Please inform if this solves your problem.
All the Best!!

Thanks for the eloquent and easily understandable code!

Thanks for this, can anyone explain what are 'a' and 'c' assignments , can we have better names for these variables ?