peartree is a library for converting GTFS feed schedules into a representative directed network graph. The tool uses Partridge to convert the target operator schedule data into Pandas dataframes and then NetworkX to hold the manipulated schedule data as a directed multigraph.
Above, an example of multiple Bay Area transit operators being incrementally loaded into peartree.
pip install peartreeSee a full notebook at this gist to see a simple, step-by-step iPython Notebook pulling in an AC Transit GTFS feed and converting it to a NetworkX graph.
import peartree as pt
path = 'path/to/actransit_gtfs.zip'
# Automatically identify the busiest day and
# read that in as a Partidge feed
feed = pt.get_representative_feed(path)
# Set a target time period to
# use to summarize impedance
start = 7*60*60 # 7:00 AM
end = 10*60*60 # 10:00 AM
# Converts feed subset into a directed
# network multigraph
G = pt.load_feed_as_graph(feed, start, end)I've yet to produce a full how-to guide for this library, but will begin to populate this section with any blog posts or notebooks that I or others produce, that include workflows using peartree.
Calculating betweeness centrality with Brooklyn bus network
Combining a peartree transit network and an OpenStreetMap walk network
Generating comparative acyclic route graphs
Coalescing transit network graphs and spectral clustering methods
Exploratory graph analysis with betweenness and load centrality