Commute-time distance Calculates the resistance distance between points.
Commute-time distance
Calculates the resistance distance between points.
commuteDistance(x, coords)
x |
object of class |
coords |
point locations coordinates (of SpatialPoints, matrix or numeric class) |
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
distance matrix (S3 class dist or matrix)
Jacob van Etten
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.
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)
# 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.