Skip to contents

Aggregate flows dispersed from each point in a network.

Source: R/flows.R
dodgr_flows_disperse.Rd

Disperse flows throughout a network based on a input vectors of origin points and associated densities

Usage

dodgr_flows_disperse(
  graph,
  from,
  dens,
  k = 500,
  contract = TRUE,
  heap = "BHeap",
  tol = 0.000000000001,
  quiet = TRUE
)

Arguments

graph

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

from

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

dens

Vectors of densities corresponding to the from points

k

Width coefficient of exponential diffusion function defined as exp(-d/k), in units of distance column of graph (metres by default). Can also be a vector with same length as from, giving dispersal coefficients from each point. If value of k<0 is given, a standard logistic polynomial will be used.

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 dispersal is considered to have finished. This parameter can generally be ignored; if in doubt, its effect can be removed by setting tol = 0.

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.

See also

Other distances: dodgr_distances(), dodgr_dists(), dodgr_dists_categorical(), dodgr_dists_nearest(), dodgr_flows_aggregate(), 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)
dens <- rep (1, length (from)) # Uniform densities
graph <- dodgr_flows_disperse (graph, from = from, dens = dens)
# 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)