Alias for dodgr_dists
dodgr_distances(
graph,
from = NULL,
to = NULL,
shortest = TRUE,
pairwise = FALSE,
heap = "BHeap",
parallel = TRUE,
quiet = TRUE
)data.frame or equivalent object representing the network
graph (see Notes)
Vector or matrix of points from which route distances are to be calculated (see Notes)
Vector or matrix of points to which route distances are to be calculated (see Notes)
If FALSE, calculate distances along the fastest
rather than shortest routes (see Notes).
If TRUE, calculate distances only between the ordered
pairs of from and to.
Type of heap to use in priority queue. Options include
Fibonacci Heap (default; FHeap), Binary Heap (BHeap),
Trinomial Heap (TriHeap), Extended Trinomial Heap (TriHeapExt, and 2-3 Heap (Heap23`).
If TRUE, perform routing calculation in parallel (see
details)
If FALSE, display progress messages on screen.
square matrix of distances between nodes
graph must minimally contain three columns of from,
to, dist. If an additional column named weight or
wt is present, shortest paths are calculated according to values
specified in that column; otherwise according to dist values. Either
way, final distances between from and to points are calculated
by default according to values of dist. That is, paths between any pair of
points will be calculated according to the minimal total sum of weight
values (if present), while reported distances will be total sums of dist
values.
For street networks produced with weight_streetnet, distances may also
be calculated along the fastest routes with the shortest = FALSE
option. Graphs must in this case have columns of time and time_weighted.
Note that the fastest routes will only be approximate when derived from
sf-format data generated with the osmdata function
osmdata_sf(), and will be much more accurate when derived from sc-format
data generated with osmdata_sc(). See weight_streetnet for details.
The from and to columns of graph may be either single
columns of numeric or character values specifying the numbers or names of
graph vertices, or combinations to two columns specifying geographical
(longitude and latitude) coordinates. In the latter case, almost any sensible
combination of names will be accepted (for example, fromx, fromy,
from_x, from_y, or fr_lat, fr_lon.)
from and to values can be either two-column matrices of
equivalent of longitude and latitude coordinates, or else single columns
precisely matching node numbers or names given in graph$from or
graph$to. If to is NULL, pairwise distances are calculated
between all points specified in from. If both from and to are NULL,
pairwise distances are calculated between all nodes in graph.
Calculations in parallel (parallel = TRUE) ought very generally be
advantageous. For small graphs, calculating distances in parallel is likely
to offer relatively little gain in speed, but increases from parallel
computation will generally markedly increase with increasing graph sizes.
By default, parallel computation uses the maximal number of available cores
or threads. This number can be reduced by specifying a value via
RcppParallel::setThreadOptions (numThreads = <desired_number>). Parallel
calculations are, however, not able to be interrupted (for example, by
Ctrl-C), and can only be stopped by killing the R process.
Other distances:
dodgr_dists_categorical(),
dodgr_dists(),
dodgr_flows_aggregate(),
dodgr_flows_disperse(),
dodgr_flows_si(),
dodgr_isochrones(),
dodgr_isodists(),
dodgr_isoverts(),
dodgr_paths(),
dodgr_times()
# A simple graph
graph <- data.frame (
from = c ("A", "B", "B", "B", "C", "C", "D", "D"),
to = c ("B", "A", "C", "D", "B", "D", "C", "A"),
d = c (1, 2, 1, 3, 2, 1, 2, 1)
)
dodgr_dists (graph)
#> A B C D
#> A 0 1 2 3
#> B 2 0 1 2
#> C 2 2 0 1
#> D 1 2 2 0
# A larger example from the included [hampi()] data.
graph <- weight_streetnet (hampi)
from <- sample (graph$from_id, size = 100)
to <- sample (graph$to_id, size = 50)
d <- dodgr_dists (graph, from = from, to = to)
# d is a 100-by-50 matrix of distances between `from` and `to`
if (FALSE) {
# a more complex street network example, thanks to @chrijo; see
# https://github.com/ATFutures/dodgr/issues/47
xy <- rbind (
c (7.005994, 51.45774), # limbeckerplatz 1 essen germany
c (7.012874, 51.45041)
) # hauptbahnhof essen germany
xy <- data.frame (lon = xy [, 1], lat = xy [, 2])
essen <- dodgr_streetnet (pts = xy, expand = 0.2, quiet = FALSE)
graph <- weight_streetnet (essen, wt_profile = "foot")
d <- dodgr_dists (graph, from = xy, to = xy)
# First reason why this does not work is because the graph has multiple,
# disconnected components.
table (graph$component)
# reduce to largest connected component, which is always number 1
graph <- graph [which (graph$component == 1), ]
d <- dodgr_dists (graph, from = xy, to = xy)
# should work, but even then note that
table (essen$level)
# There are parts of the network on different building levels (because of
# shopping malls and the like). These may or may not be connected, so it may
# be necessary to filter out particular levels
index <- which (!(essen$level == "-1" | essen$level == "1")) # for example
library (sf) # needed for following sub-select operation
essen <- essen [index, ]
graph <- weight_streetnet (essen, wt_profile = "foot")
graph <- graph [which (graph$component == 1), ]
d <- dodgr_dists (graph, from = xy, to = xy)
}