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# rochacbruno/haversine.py

Created June 6, 2012 17:43
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Calculate distance between latitude longitude pairs with Python
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 #!/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

### joaovs12 commented Sep 4, 2019

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

### zuzhaoye commented Dec 14, 2019

Thank you! @MalyutinS

### manikyalarao16 commented Feb 11, 2020

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]
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 = 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!

### vivek1240 commented Jul 29, 2020

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