Compute a cost matrix of a spatial network

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.

st_network_cost(
  x,
  from = igraph::V(x),
  to = igraph::V(x),
  weights = NULL,
  direction = "out",
  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. 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.
direction: The direction of travel. Defaults to 'out', meaning that the direction given by the network is followed and costs are calculated from the points given as argument from. May be set to 'in', meaning that the opposite direction is followed an costs are calculated towards the points given as argument from. May also be set to 'all', meaning that the network is considered to be undirected. This argument is ignored for undirected networks.
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. Argument mode is ignored. Use direction instead.

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

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.

Examples

library(sf, quietly = TRUE)
library(tidygraph, quietly = TRUE)

# Create a network with edge lengths 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))
#> Units: [m]
#>          [,1]     [,2]
#> [1,]    0.000 2094.555
#> [2,] 2094.555    0.000

# 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))
#> Units: [m]
#>          [,1]     [,2]
#> [1,]    0.000 2094.555
#> [2,] 2094.555    0.000

# 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")
#>          [,1]     [,2]
#> [1,]  0.00000 10.29983
#> [2,] 10.29983  0.00000

# Not providing any from or to points includes all nodes by default.
with_graph(net, graph_order()) # Our network has 701 nodes.
#> [1] 701
cost_matrix = st_network_cost(net)
dim(cost_matrix)
#> [1] 701 701

Arguments

Value

Details

See also

Examples