Skip to contents

Aggregate flows throughout a network.

Source: R/flows.R
dodgr_flows_aggregate.Rd

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,
  pairwise = FALSE,
  contract = TRUE,
  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 route distances are to be calculated, specified as one of the following:

  • Single character vector precisely matching node numbers or names given in graph$from or graph$to.

  • Single vector of integer-ish values, in which case these will be presumed to specify indices into dodgr_vertices, and NOT to correspond to values in the 'from' or 'to' columns of the graph. See the example below for a demonstration.

  • Matrix or equivalent of longitude and latitude coordinates, in which case these will be matched on to the nearest coordinates of 'from' and 'to' points in the graph.

to

Vector or matrix of points to which route distances are to be calculated. If to is NULL, pairwise distances will be calculated from all from points to all other nodes in graph. If both from and to are NULL, pairwise distances are calculated between all nodes in graph.

flows

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

pairwise

If TRUE, aggregate flows only only paths connecting the ordered pairs of from and to. In this case, both from and to must be of the same length, and flows must be either a vector of the same length, or a matrix with only one column and same number of rows. flows then quantifies the flows between each pair of from and to points.

contract

If TRUE (default), calculate flows on contracted graph before mapping them back on to the original full graph (recommended as this will generally be much faster). FALSE should only be used if the graph has already been contracted.

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 additional flow column added.

Note

Spatial Interaction models are often fitted through trialling a range of values of 'k'. The specification above allows fitting multiple values of 'k' to be done with a single call, in a way that is far more efficient than making multiple calls. A matrix of 'k' values may be entered, with each column holding a different vector of values, one for each 'from' point. For a matrix of 'k' values having 'n' columns, the return object will be a modified version in the input 'graph', with an additional 'n' columns, named 'flow1', 'flow2', ... up to 'n'. These columns must be subsequently matched by the user back on to the corresponding columns of the matrix of 'k' values.

The norm_sums parameter should be used whenever densities at origins and destinations are absolute values, and ensures that the sum of resultant flow values throughout the entire network equals the sum of densities at all origins. For example, with norm_sums = TRUE (the default), a flow from a single origin with density one to a single destination along two edges will allocate flows of one half to each of those edges, such that the sum of flows across the network will equal one, or the sum of densities from all origins. The norm_sums = TRUE option is appropriate where densities are relative values, and ensures that each edge maintains relative proportions. In the above example, flows along each of two edges would equal one, for a network sum of two, or greater than the sum of densities.

Flows are calculated by default using parallel computation with the maximal number of available cores or threads. This number can be reduced by specifying a value via RcppParallel::setThreadOptions (numThreads = <desired_number>).

See also

Other distances: dodgr_distances(), dodgr_dists(), dodgr_dists_categorical(), dodgr_dists_nearest(), dodgr_flows_disperse(), dodgr_flows_si(), dodgr_isochrones(), dodgr_isodists(), dodgr_isoverts(), dodgr_paths(), dodgr_times()

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_graph (graph)
# This graph will only include those edges having non-zero flows, and so:
nrow (graph)
#> [1] 6813
nrow (graph_undir) # the latter is much smaller
#> [1] 756

# The following code can be used to convert the resultant graph to an `sf`
# object suitable for plotting
if (FALSE) { # \dontrun{
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)
} # }

# 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.
if (FALSE) { # \dontrun{
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"])
} # }