dodgr_dists_categorical | R Documentation |
Cumulative distances along different edge categories
dodgr_dists_categorical(
graph,
from = NULL,
to = NULL,
proportions_only = FALSE,
pairwise = FALSE,
dlimit = NULL,
heap = "BHeap",
quiet = TRUE
)
graph |
|
from |
Vector or matrix of points from which route distances are to be calculated (see Notes) |
to |
Vector or matrix of points to which route distances are to be calculated (see Notes) |
proportions_only |
If |
pairwise |
If |
dlimit |
If no value to |
heap |
Type of heap to use in priority queue. Options include
Fibonacci Heap (default; |
quiet |
If |
If to
is specified, a list of distance matrices of equal dimensions
(length(from), length(to)), the first of which ("distance") holds the final
distances, while the rest are one matrix for each unique value of
"edge_type", holding the distances traversed along those types of edges only.
Otherwise, a single matrix of total distances along all ways from each point
out to the specified value of dlimit
, along with distances along each of
the different kinds of ways specified in the "edge_type" column of the input
graph.
The "edge_type" column in the graph can contain any kind of discrete or
categorical values, although integer values of 0 are not permissible. NA
values are ignored. The function requires one full distance
matrix to be stored for each category of "edge_type" (unless
proportions_only = TRUE
). It is wise to keep numbers of discrete types as
low as possible, especially for large distance matrices.
Setting the proportions_only
flag to TRUE
may be advantageous for
large jobs, because this avoids construction of the full matrices. This may
speed up calculations, but perhaps more importantly it may make possible
calculations which would otherwise require distance matrices too large to be
directly stored.
Calculations are not able to be interrupted (for example, by Ctrl-C
),
and can only be stopped by killing the R process.
Other distances:
dodgr_distances()
,
dodgr_dists()
,
dodgr_dists_nearest()
,
dodgr_flows_aggregate()
,
dodgr_flows_disperse()
,
dodgr_flows_si()
,
dodgr_isochrones()
,
dodgr_isodists()
,
dodgr_isoverts()
,
dodgr_paths()
,
dodgr_times()
# Prepare a graph for categorical routing by including an "edge_type" column
graph <- weight_streetnet (hampi, wt_profile = "foot")
graph <- graph [graph$component == 1, ]
graph$edge_type <- graph$highway
# Define start and end points for categorical distances; using all vertices
# here.
length (unique (graph$edge_type)) # Number of categories
v <- dodgr_vertices (graph)
from <- to <- v$id [1:100]
d <- dodgr_dists_categorical (graph, from, to)
class (d)
length (d)
sapply (d, dim)
# 9 distance matrices, all of same dimensions, first of which is standard
# distance matrix
s <- summary (d) # print summary as proportions along each "edge_type"
# or directly calculate proportions only
dodgr_dists_categorical (graph, from, to,
proportions_only = TRUE
)
# Pairwise distances return single matrix with number of rows equal to 'from'
# / 'to', and number of columns equal to number of edge types plus one for
# total distances.
d <- dodgr_dists_categorical (graph, from, to, pairwise = TRUE)
class (d)
dim (d)
# The 'dlimit' parameter can be used to calculate total distances along each
# category of edges from a set of points out to specified threshold:
dlimit <- 2000 # in metres
d <- dodgr_dists_categorical (graph, from, dlimit = dlimit)
dim (d) # length(from), length(unique(edge_type)) + 1
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