| st_network_cost {sfnetworks} | R 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,
direction = "out",
Inf_as_NaN = FALSE,
...
)
Arguments
x |
An object of class |
from |
The (set of) geospatial point(s) from which the shortest paths
will be calculated. Can be an object of class |
to |
The (set of) geospatial point(s) to which the shortest paths will
be calculated. Can be an object of class |
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
|
direction |
The direction of travel. Defaults to |
Inf_as_NaN |
Should the cost values of unconnected nodes be stored as
|
... |
Arguments passed on to |
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 the to argument.
See Also
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))
# 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)