Calculates the resistance distance between points.

commuteDistance(x, coords)

Arguments

x

object of class TransitionLayer

coords

point locations coordinates (of SpatialPoints, matrix or numeric class)

Value

distance matrix (S3 class dist or matrix)

Details

This function calculates the expected random-walk commute time between nodes in a graph. It is defined as the effective distance (resistance distance) between the selected nodes multiplied by the volume of the graph, which is the sum of the conductance weights of all the edges in the graph (Chandra et al. 1997). The result represents the average number of steps that is needed to commute between the nodes during a random walk.

The function implements the algorithm given by Fouss et al. (2007).

Before calculating commute-time distances from a TransitionLayer object, see if you need to apply the function geoCorrection

References

Chandra, A.K., Raghavan, P., Ruzzo, W.L., Smolensy, R. & Tiwari, P. 1996. The electrical resistance of a graph captures its commute and cover times. Computational Complexity, 6(4), 312-340.

Fouss, F., Pirotte, A., Renders, J.-M. & Saerens, M. 2007. Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation. IEEE Transactions on Knowledge and Data Engineering, 19(3), 355-369.

McRae, B.H. 2006. Isolation by resistance. Evolution 60(8), 1551-1561. https://circuitscape.org/

See also

Author

Jacob van Etten

Examples

library("raster")
# Create a new raster and set all its values to unity.
r <- raster(nrows=18, ncols=36)
r <- setValues(r,rep(1,ncell(raster)))

#Create a Transition object from the raster
tr <- transition(r, function(x) 1/mean(x),4)
#> The extent and CRS indicate this raster is a global lat/lon raster. This means that transitions going off of the East or West edges will 'wrap' to the opposite edge.
#> Global lat/lon rasters are not supported under new optimizations for 4 and 8 directions with custom transition functions. Falling back to old method.

# Create two sets of coordinates
library("sp")
sP1 <- SpatialPoints(cbind(c(65,5,-65),c(55,35,-35)))
sP2 <- SpatialPoints(cbind(c(50,15,-40),c(80,20,-5)))

#Calculate the resistance distance between the points
commuteDistance(tr, sP1)
#>          1        2
#> 2 2882.026         
#> 3 3704.695 3256.071