(S)hapefile (2) Graph/network converter in Python
When we process GIS data, a non-trivial problem is the conversion from shape lines to graph or network data structure. The latter may benefit from these out-of-box graphical libraries such as networkx and igraph. But the conversion is a headache to components open communities. This mostly urges me to finish this tiny but useful library.
Requirements: Python 2.7+ or Python 3.3+
sudo apt-get install python python-pip libgeos-dev
Install s2g
,
sudo pip install s2g
Extra utilities to run unittests,
sudo apt-get install python-tk
sudo pip install matplotlib
You have two alternative ways to construct the graph. One is reading from a raw shapefiles with LineString
objects.
(Under the hood, I involve fiona to read geometries and
shapely to analyze the data.).
Currently, this tool only supports conversion to undirected graph.
from s2g import ShapeGraph
import networkx as nx
sg = ShapeGraph(shapefile='path/to/roads.shp', to_graph=True)
assert isinstance(sg.graph, nx.Graph)
The other way is designed for programmable usage or time-consuming process where intermediate data could be sniffed or saved. Here is an example to read lines with [fiona]:
from s2g import ShapeGraph
import fiona
from shapely.geometry import shape, LineString
shp = 'path/to/shapefile.shp'
with fiona.open(shp) as source:
geoms = []
for r in source:
s = shape(r['geometry'])
if isinstance(s, LineString):
geoms.append(s)
# create ShapeGraph object from a list of lines
sg = ShapeGraph(geoms, to_graph=False)
# detect major components
mc = sg.gen_major_components()
# major components are mc[2]
# convert the largest component to networkx Graph
graph = sg.to_networkx() # equivalently sg.graph
Dive into source doc to discover other functionalities.
read_shp
function? (Issue)I endeavored to avoid reinventing the wheel at the beginning. It has several limitations to meet common road network processing: