dodgr (version 0.2.8)

dodgr_flows_aggregate: dodgr_flows_aggregate

Description

Aggregate flows throughout a network based on an input matrix of flows between all pairs of from and to points.

Usage

dodgr_flows_aggregate(
  graph,
  from,
  to,
  flows,
  contract = FALSE,
  heap = "BHeap",
  tol = 0.000000000001,
  norm_sums = TRUE,
  quiet = TRUE
)

Arguments

graph

data.frame or equivalent object representing the network graph (see Details)

from

Vector or matrix of points from which aggregate flows are to be calculated (see Details)

to

Vector or matrix of points to which aggregate flows are to be calculated (see Details)

flows

Matrix of flows with nrow(flows)==length(from) and ncol(flows)==length(to).

contract

If TRUE, calculate flows on contracted graph before mapping them back on to the original full graph (recommended as this will generally be much faster).

heap

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).

tol

Relative tolerance below which flows towards to vertices are not considered. This will generally have no effect, but can provide speed gains when flow matrices represent spatial interaction models, in which case this parameter effectively reduces the radius from each from point over which flows are aggregated. To remove any such effect, set tol = 0.

norm_sums

Standardise sums from all origin points, so sum of flows throughout entire network equals sum of densities from all origins (see Note).

quiet

If FALSE, display progress messages on screen.

Value

Modified version of graph with additonal flow column added.

Examples

# NOT RUN {
graph <- weight_streetnet (hampi)
from <- sample (graph$from_id, size = 10)
to <- sample (graph$to_id, size = 5)
to <- to [!to %in% from]
flows <- matrix (10 * runif (length (from) * length (to)),
                 nrow = length (from))
graph <- dodgr_flows_aggregate (graph, from = from, to = to, flows = flows)
# graph then has an additonal 'flows' column of aggregate flows along all
# edges. These flows are directed, and can be aggregated to equivalent
# undirected flows on an equivalent undirected graph with:
graph_undir <- merge_directed_graph (graph)
# This graph will only include those edges having non-zero flows, and so:
nrow (graph); nrow (graph_undir) # the latter is much smaller

# The following code can be used to convert the resultant graph to an `sf`
# object suitable for plotting
# }
# NOT RUN {
gsf <- dodgr_to_sf (graph_undir)

# example of plotting with the 'mapview' package
library (mapview)
flow <- gsf$flow / max (gsf$flow)
ncols <- 30
cols <- c ("lawngreen", "red")
colranmp <- colorRampPalette (cols) (ncols) [ceiling (ncols * flow)]
mapview (gsf, color = colranmp, lwd = 10 * flow)
# }
# NOT RUN {
# An example of flow aggregation across a generic (non-OSM) highway,
# represented as the `routes_fast` object of the \pkg{stplanr} package,
# which is a SpatialLinesDataFrame containing commuter densities along
# components of a street network.
# }
# NOT RUN {
library (stplanr)
# merge all of the 'routes_fast' lines into a single network
r <- overline (routes_fast, attrib = "length", buff_dist = 1)
r <- sf::st_as_sf (r)
# then extract the start and end points of each of the original 'routes_fast'
# lines and use these for routing with `dodgr`
l <- lapply (routes_fast@lines, function (i)
             c (sp::coordinates (i) [[1]] [1, ],
                tail (sp::coordinates (i) [[1]], 1)))
l <- do.call (rbind, l)
xy_start <- l [, 1:2]
xy_end <- l [, 3:4]
# Then just specify a generic OD matrix with uniform values of 1:
flows <- matrix (1, nrow = nrow (l), ncol = nrow (l))
# We need to specify both a `type` and `id` column for the
# \link{weight_streetnet} function.
r$type <- 1
r$id <- seq (nrow (r))
graph <- weight_streetnet (r, type_col = "type", id_col = "id",
                           wt_profile = 1)
f <- dodgr_flows_aggregate (graph, from = xy_start, to = xy_end,
                            flows = flows)
# Then merge directed flows and convert to \pkg{sf} for plotting as before:
f <- merge_directed_graph (f)
geoms <- dodgr_to_sfc (f)
gc <- dodgr_contract_graph (f)
gsf <- sf::st_sf (geoms)
gsf$flow <- gc$flow
# sf plot:
plot (gsf ["flow"])
# }