st_network_cost: Compute a cost matrix of a spatial network

View source: R/paths.R

st_network_costR Documentation

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. Features with duplicated nearest node indices will be removed before calculating the cost matrix. 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. Duplicated values will be removed before calculating the cost matrix. 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

Spatial features provided to the from and/or to argument don't necessarily have to be points. Internally, the nearest node to each feature is found by calling st_nearest_feature, so any feature with a geometry type that is accepted by that function can be provided as from and/or to argument.

When directly providing integer node indices or character node names to the from and/or to argument, keep the following in mind. A node index should correspond to a row-number of the nodes table of the network. A node name should correspond to a value of a column in the nodes table named name. This column should contain character values without duplicates.

For more details on the wrapped function from igraph see the distances documentation page.

Value

An n times m numeric matrix where n is the length of the from argument, and m is the length of unique values in the to argument. When the to argument contains spatial features that have the same nearest node, these features are considered duplicates.

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.

Furthermore, distances does not allow duplicated values in the to argument. This also means that when providing spatial features, sets of multiple features that happen to have the same nearest node will be reduced to one by selecting only the first of these features.

See Also

st_network_paths

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 documentation built on March 18, 2022, 7:49 p.m.