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Haversine Build Status

Calculate the distance (in various units) between two points on Earth using their latitude and longitude.

Installation

$ pip install haversine

Usage

Calculate the distance between Lyon and Paris

from haversine import haversine, Unit

lyon = (45.7597, 4.8422) # (lat, lon)
paris = (48.8567, 2.3508)

haversine(lyon, paris)
>> 392.2172595594006  # in kilometers

haversine(lyon, paris, unit=Unit.MILES)
>> 243.71201856934454  # in miles

# you can also use the string abbreviation for units:
haversine(lyon, paris, unit='mi')
>> 243.71201856934454  # in miles

haversine(lyon, paris, unit=Unit.NAUTICAL_MILES)
>> 211.78037755311516  # in nautical miles

The haversine.Unit enum contains all supported units:

import haversine

print(tuple(haversine.Unit))

outputs

(<Unit.FEET: 'ft'>, <Unit.INCHES: 'in'>, <Unit.KILOMETERS: 'km'>,
 <Unit.METERS: 'm'>, <Unit.MILES: 'mi'>, <Unit.NAUTICAL_MILES: 'nmi'>)

Performance optimisation for distances between all points in two vectors

You will need to add numpy in order to gain performance with vectors.

You can then do this:

from haversine import haversine_vector, Unit

lyon = (45.7597, 4.8422) # (lat, lon)
paris = (48.8567, 2.3508)
new_york = (40.7033962, -74.2351462)

haversine_vector([lyon, lyon], [paris, new_york], Unit.KILOMETERS)

>> array([ 392.21725956, 6163.43638211])

It is generally slower to use haversine_vector to get distance between two points, but can be really fast to compare distances between two vectors.

Combine matrix

You can generate a matrix of all combinations between coordinates in different vectors by setting comb parameter as True.

from haversine import haversine_vector, Unit

lyon = (45.7597, 4.8422) # (lat, lon)
london = (51.509865, -0.118092)
paris = (48.8567, 2.3508)
new_york = (40.7033962, -74.2351462)

haversine_vector([lyon, london], [paris, new_york], Unit.KILOMETERS, comb=True)

>> array([[ 392.21725956,  343.37455271],
 	  [6163.43638211, 5586.48447423]])

The output array from the example above returns the following table:

Paris New York
Lyon Lyon <-> Paris Lyon <-> New York
London London <-> Paris London <-> New York

By definition, if you have a vector a with n elements, and a vector b with m elements. The result matrix M would be $n x m$ and a element M[i,j] from the matrix would be the distance between the ith coordinate from vector a and jth coordinate with vector b.

Contributing

Clone the project.

Install pipenv.

Run pipenv install --dev

Launch test with pipenv run pytest


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