dfellis / h3-py

Python bindings for H3, a hierarchical hexagonal geospatial indexing system

Home Page:https://uber.github.io/h3/

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H3-Python

Build Status H3 Version License

This library provides Python bindings for the H3 Core Library. For API reference, please see the H3 Documentation.

Installing

You need to have cc, make, and cmake in your $PATH when installing this package:

which cc
/usr/bin/cc
which make
/usr/bin/make
which cmake
/usr/bin/cmake
pip install h3

Development

git clone https://github.com/uber/h3-py.git && cd h3-py
virtualenv env
source env/bin/activate
pip install -r requirements-dev.txt
fab bootstrap

Usage

The following visualizations are achieved with folium.

from h3 import h3

Convert lat/lng to hexagon address

h3_address = h3.geo_to_h3(37.3615593, -122.0553238, 5) # lat, lng, hex resolution
hex_center_coordinates = h3.h3_to_geo(h3_address) # array of [lat, lng]
hex_boundary = h3.h3_to_geo_boundary(h3_address) # array of arrays of [lat, lng]

docs/source/Hexagon.png

Get KRings of hexagon

h3.k_ring_distances(h3_address, 4) # array of 4 rings with size [1, 6, 12, 18]
h3.k_ring(h3_address, 4) # a collection of hexagons within kring sizes from 0 to 3

docs/source/KRings.png

Polyfill a Geo Json with hexagons

geoJson = {'type': 'Polygon',
 'coordinates': [[[37.813318999983238, -122.4089866999972145],
 [ 37.7866302000007224, -122.3805436999997056 ],
 [37.7198061999978478, -122.3544736999993603],
 [ 37.7076131999975672, -122.5123436999983966 ],
 [37.7835871999971715, -122.5247187000021967],
 [37.8151571999998453, -122.4798767000009008]]] }
hexagons = list(h3.polyfill(geoJson, 8)) # resolution 8

docs/source/Polyfill.png

For more API reference, please see the H3 Documentation.

About

Python bindings for H3, a hierarchical hexagonal geospatial indexing system

https://uber.github.io/h3/

License:Apache License 2.0


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