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s2g

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(S)hapefile to(2) (G)raph/network converter in Python

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# python-s2g

(S)hapefile (2) Graph/network converter in Python

[![Build Status](https://travis-ci.org/caesar0301/s2g.svg?branch=master)](https://travis-ci.org/caesar0301/s2g)

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](http://networkx.github.io/)
and [igraph](http://igraph.org/python/). But the conversion is a headache to components open communities.
This mostly urges me to finish this tiny but useful library.

# Install

Requirements: Python 2.7+ or Python 3.3+

```
sudo apt-get install python python-pip libgeos-dev
```

Install `s2g`,

```$xslt
sudo pip install s2g
```

Extra utilities to run unittests,

```
sudo apt-get install python-tk
sudo pip install matplotlib
```

# Usage

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](https://pypi.python.org/pypi/Fiona/) to read geometries and
[shapely](https://pypi.python.org/pypi/Shapely) to analyze the data.).
Currently, this tool only supports conversion to *undirected graph*.

```python
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]:

```python
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](https://github.com/caesar0301/python-s2g/blob/master/s2g/shapegraph.py) to discover other functionalities.

## QA

* Why not NetworkX's `read_shp` function? ([Issue](https://github.com/caesar0301/s2g/issues/4))

I endeavored to avoid reinventing the wheel at the beginning. It has several limitations to meet common road network processing:
1. It is not able to detect the major components when the shapefile has disconneted parts
2. It has no buffer mechsnisms to determine the connectivities of line-line, line-point or point-point pairs
3. It does not support parameter controlled sampling of road lines when we convert geometry lines into edges
4. It has no pesudo edges to fix the disconnectivity of geometry elements

## References

* [shp2graph](https://cran.r-project.org/web/packages/shp2graph/index.html) in R by Binbin Lu, as well as [his talk](http://web.warwick.ac.uk/statsdept/user2011/TalkSlides/Contributed/17Aug_1600_FocusIV_2-Geospatial_1-Lu.pdf) on useR! 2011
* [A Tutorial on Topology Correction of Shapefiles Using GRASS](http://xiaming.me/posts/2015/08/29/a-tutorial-on-topology-correction-of-shapefiles-using-grass/)
* [Why do I make s2g](http://xiaming.me/posts/2016/12/18/process-gis-shapefile-with-graph-tools/)

s2g

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