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

dodgr_flows_aggregate(graph, from, to, flows, wt_profile = "bicycle",
contract = FALSE, heap = "BHeap", quiet = TRUE)

## Arguments

graph data.frame or equivalent object representing the network graph (see Details) Vector or matrix of points from which aggregate flows are to be calculated (see Details) Vector or matrix of points to which aggregate flows are to be calculated (see Details) Matrix of flows with nrow(flows)==length(from) and ncol(flows)==length(to). Name of weighting profile for street networks (one of foot, horse, wheelchair, bicycle, moped, motorcycle, motorcar, goods, hgv, psv; only used if graph is not provided, in which case a street network is downloaded and correspondingly weighted). 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). Type of heap to use in priority queue. Options include Fibonacci Heap (default; FHeap), Binary Heap (BHeap), Radix, Trinomial Heap (TriHeap), Extended Trinomial Heap (TriHeapExt, and 2-3 Heap (Heap23). If FALSE, display progress messages on screen.

## Value

Modified version of graph with additonal flow column added.

## Examples

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_flows (graph)
# This graph will only include those edges having non-zero flows, and so:
nrow (graph); nrow (graph_undir) # the latter is much smaller#> [1] 5845#> [1] 759
# The following code can be used to convert the resultant graph to an sf
# object suitable for plotting
# NOT RUN {
geoms <- dodgr_to_sfc (graph_undir)
gc <- dodgr_contract_graph (graph_undir)
gsf <- sf::st_sf (geoms)
gsf$flow <- gc$graph$flow # example of plotting with the 'mapview' package library (mapview) flow <- gsf$flow / max (gsf$flow) ncols <- 30 cols <- colorRampPalette (c ("lawngreen", "red")) (ncols) [ceiling (ncols * flow)] mapview (gsf, color = cols, lwd = 10 * flow) # } # An example of flow aggregation across a generic (non-OSM) highway, # represented as the routes_fast object of the \pkg{stplanr} package, # which is a SpatialLinesDataFrame containing commuter densities along # components of a street network. # NOT RUN { library (stplanr) # merge all of the 'routes_fast' lines into a single network r <- overline (routes_fast, attrib = "length", buff_dist = 1) r <- sf::st_as_sf (r) # then extract the start and end points of each of the original 'routes_fast' # lines and use these for routing with dodgr l <- lapply (routes_fast@lines, function (i) c (sp::coordinates (i) [[1]] [1, ], tail (sp::coordinates (i) [[1]], 1))) l <- do.call (rbind, l) xy_start <- l [, 1:2] xy_end <- l [, 3:4] # Then just specify a generic OD matrix with uniform values of 1: flows <- matrix (1, nrow = nrow (l), ncol = nrow (l)) # We need to specify both a type and id column for the # \link{weight_streetnet} function. r$type <- 1
r$id <- seq (nrow (r)) graph <- weight_streetnet (r, type_col = "type", id_col = "id", wt_profile = 1) f <- dodgr_flows_aggregate (graph, from = xy_start, to = xy_end, flows = flows) # Then merge directed flows and convert to \pkg{sf} for plotting as before: f <- merge_directed_flows (f) geoms <- dodgr_to_sfc (f) gc <- dodgr_contract_graph (f) gsf <- sf::st_sf (geoms) gsf$flow <- gc$graph$flow
# sf plot:
plot (gsf ["flow"])
# }`