karpfen / dodgr

Distances on Directed Graphs in R

dodgr: Distances on Directed Graphs in R

R package for calculating pairwise distances on dual-weighted directed graphs using Priority Queue Shortest Paths. Dual-weighted directed graphs are directed graphs with two sets of weights so that weight1(A->B) != weight1(B->A)---the directed property---and weight2(A->B) != weight1(A->B)---the dual property. dodgr calculates shortest paths according to one weight, while distances along paths are calculating using the other weight. A canonical example of a dual-weighted directed graph is a street network to be used for routing. Routes are usually calculated by weighting different kinds of streets or ways according to a particular mode of transport, while the desired output is a direct, unweighted distance.

The shortest path algorithm relies on priority queue code adapted from original code by Shane Saunders available here http://www.cosc.canterbury.ac.nz/tad.takaoka/alg/spalgs/spalgs.html

Installation

You can install dodgr from github with:

# install.packages("devtools")
devtools::install_github("gmost/dodgr")

Usage

The primary function,

d <- dodgr_dists (graph = graph, from = pts, to = pts)

produces a square matrix of distances between all points listed in pts and routed along the dual-weighted directed network given in graph. An even simpler usage allows calculation of pair-wise distances between a set of geographical coordinates (here, for a sizey chunk of New York City):

xlim <- c (-74.12931, -73.99214)
ylim <- c (40.70347, 40.75354)
npts <- 1000
pts <- data.frame (x = xlim [1] + runif (npts) * diff (xlim),
                   y = ylim [1] + runif (npts) * diff (ylim))
st <- Sys.time ()
d <- dodgr_dists (from = pts)
Sys.time () - st
#> Time difference of 9.473597 secs
range (d, na.rm = TRUE)
#> [1]  0.00000 16.64285

This will automatically download the street network (using osmdata), and even then calculating distances between 1,000 points can be done in around 10 seconds.

A graph or network in dodgr is represented as a flat table (data.frame, tibble, data.table, whatever) of minimally four columns: from, to, weight, and distance. The first two can be of arbitrary form (numeric or character); weight is used to evaluate the shortest paths, and the desired distances are evaluated by summing the values of distance along those paths. For a street network example, weight will generally be the actual distance multiplied by a priority weighting for a given mode of transport and type of way, while distance will be the pysical distance.

For more detail, see the main package vignette, along with a second vignette detailing benchmark timings, showing that under many circumstances, dodgr performs considerably faster than equivalent routines from the igraph package.