sfnetworks: st_network_cost – R documentation

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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,
  Inf_as_NaN = FALSE,
  ...
)

Arguments

`x`	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.
`to`	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.
`Inf_as_NaN`	Should the cost values of unconnected nodes be stored as `NaN` instead of `Inf`? Defaults to `FALSE`.
`...`	Arguments passed on to `distances`.

Details

See the igraph documentation.

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.

Note

By default, distances calculates costs by by allowing to travel each edge in both directions, hence by assuming an undirected network. This is the default even when the input network is directed! For directed networks, the behaviour can be changed by setting mode = "out" to consider only outbound edges, or mode = "in" to consider only inbound edges.

Examples

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)

sfnetworks

Tidy Geospatial Networks

v0.5.1

Apache License (>= 2)

Authors

Lucas van der Meer [aut, cre] (<https://orcid.org/0000-0001-6336-8628>), Lorena Abad [aut] (<https://orcid.org/0000-0003-0554-734X>), Andrea Gilardi [aut] (<https://orcid.org/0000-0002-9424-7439>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>)

Initial release