spatial-enum

Enumerations for spatial data with support for vectorized spatial operations via pygeos.

from enum_spatial import BoundsEnum
from shapely.geometry import Point

class MyEnum(BoundsEnum):
    bbox1 = [-118, 34, -117, 35]
    bbox2 = [-81, 30, -80, 31]

print(MyEnum.bbox1)
>>> POLYGON ((-118 34, -118 35, -117 35, -117 34, -118 34))

print(MyEnum.intersects(Point([-117.5, 34.5]))
>>> bbox1

Supported enum types:

• BoundsEnum
• PointEnum
• LineStringEnum
• PolygonEnum
• MultiPointEnum
• MultiLineStringEnum
• MultiPolygonEnum

Support spatial operations:

• intersects
• contains
• overlaps
• touches
• disjoint
• crosses

Installation

pip install shapely --no-binary shapely
pip install git+https://github.com/geospatial-jeff/enum-spatial.git

World Cities Example

Download the dataset:

curl https://raw.githubusercontent.com/datasets/geo-countries/master/data/countries.geojson -o countries.geojson

Load into the enum through the enum.Enum functional API:

import json
from enum_spatial import MultiPolygonEnum
from shapely.geometry import shape

data = json.load(open('countries.geojson', 'r'))
enum_members = []
for feat in data['features']:
    geom = shape(feat['geometry'])
    country_name = feat['properties']['ADMIN']
    if geom.is_valid:
        enum_members.append((country_name, geom))

world_countries = MultiPolygonEnum('WorldCountries', enum_members)

Find a country which contains a given point:

print(world_countries.intersects(Point([-54, 15])))
>>> Brazil

Find neighboring countries:

print(world_countries.intersects(world_countries.Paraguay))
>>> ['Argentina', 'Bolivia', 'Brazil', 'Paraguay']