st_network_cost: Compute a cost matrix of a spatial network

Description

Wrapper around distances to calculate costs of pairwise shortest paths between points in a spatial network. It allows to provide any set of geospatial point as from and to arguments. If such a geospatial point is not equal to a node in the network, it will be snapped to its nearest node before calculating costs.

Usage

st_network_cost(x, from = igraph::V(x), to = igraph::V(x), weights = NULL, ...)

Arguments

An object of class sfnetwork.

from

The (set of) geospatial point(s) from which the shortest paths will be calculated. Can be an object of class sf or sfc. Alternatively it can be a numeric vector containing the indices of the nodes from which the shortest paths will be calculated, or a character vector containing the names of the nodes from which the shortest paths will be calculated. By default, all nodes in the network are included.

The (set of) geospatial point(s) to which the shortest paths will be calculated. Can be an object of class sf or sfc. Alternatively it can be a numeric vector containing the indices of the nodes to which the shortest paths will be calculated, or a character vector containing the names of the nodes to which the shortest paths will be calculated. By default, all nodes in the network are included.

weights

The edge weights to be used in the shortest path calculation. Can be a numeric vector giving edge weights, or a column name referring to an attribute column in the edges table containing those weights. If set to NULL, the values of a column named weight in the edges table will be used automatically, as long as this column is present. If not, the geographic edge lengths will be calculated internally and used as weights. If set to NA, no weights are used, even if the edges have a weight column.

...

Arguments passed on to distances.

Value

An n times m numeric matrix where n is the length of the from argument, and m is the length of the to argument.

Details

See the igraph documentation.

Examples

Run this code

# NOT RUN {
library(sf, quietly = TRUE)
library(tidygraph, quietly = TRUE)

# Create a network with edge lenghts as weights.
# These weights will be used automatically in shortest paths calculation.
net = as_sfnetwork(roxel, directed = FALSE) %>%
  st_transform(3035) %>%
  activate("edges") %>%
  mutate(weight = edge_length())

# Providing node indices.
st_network_cost(net, from = c(495, 121), to = c(495, 121))

# Providing nodes as spatial points.
# Points that don't equal a node will be snapped to their nearest node.
p1 = st_geometry(net, "nodes")[495] + st_sfc(st_point(c(50, -50)))
st_crs(p1) = st_crs(net)
p2 = st_geometry(net, "nodes")[121] + st_sfc(st_point(c(-10, 100)))
st_crs(p2) = st_crs(net)

st_network_cost(net, from = c(p1, p2), to = c(p1, p2))

# Using another column for weights.
net %>%
  activate("edges") %>%
  mutate(foo = runif(n(), min = 0, max = 1)) %>%
  st_network_cost(c(p1, p2), c(p1, p2), weights = "foo")

# Not providing any from or to points includes all nodes by default.
with_graph(net, graph_order()) # Our network has 701 nodes.
cost_matrix = st_network_cost(net)
dim(cost_matrix)

# }