Set friction in a gGraph object

The function setCosts defines costs for the edges of a gGraph object according to a node attribute and cost rules defined in @meta$costs. Each node has a value for the chosen attribute which is associated to a cost. The cost of an edge is computed as a function of the costs of its two nodes.

Usage

setCosts(
  x,
  attr.name = NULL,
  node.values = NULL,
  cost.rules = NULL,
  method = c("mean", "product", "function"),
  FUN = NULL,
  ...
)

Arguments

x

a gGraph object with at least one node attribute and a @meta$costs component (see worldgraph.10k for an example).

attr.name

the name of the node attribute used to compute costs.

node.values

a numeric vector of costs for the nodes. If provided, overrides attr.name.

cost.rules

a two-column data.frame to update x@meta$costs before computing edge costs. If NULL, existing x@meta$costs is used.

method

how edge costs are computed from node costs: "mean", "product", or "function" (requires FUN).

FUN

a function to compute edge cost from two node costs. Required when method = "function".

...

additional arguments passed to FUN.

Value

A gGraph object with the newly defined edge costs.

Details

Costs are inversely proportional to connectivity: the larger the cost of an edge, the lower the connectivity between its two nodes. Costs in geoGraph are equivalent to weights in the graph and RBGL packages.

See also

dropDeadEdges, getCosts, hasCosts

Other cost_functions: combineCosts(), dropCosts(), getCosts(), hasCosts(), setDistCosts()

Examples

## get and modify cost rules then set costs in one call
cost.rules <- getCosts(worldgraph.10k, res.type = "rules")
cost.rules
#>            habitat cost
#> 1              sea  100
#> 2             land    1
#> 3         mountain   10
#> 4       landbridge    5
#> 5 oceanic crossing   20
#> 6  deselected land  100

## make sea travel cheaper
cost.rules$cost[cost.rules$habitat == "sea"] <- 50

## update rules and set costs in one call
x <- setCosts(worldgraph.10k, attr.name = "habitat", cost.rules = cost.rules, method = "mean")