View source: R/get_distance_mat.R
get_distance_matrix | R Documentation |
Compute all shortest distance between origin and destination nodes.
get_distance_matrix( Graph, from, to, algorithm = "phast", aggregate_aux = FALSE, allcores = FALSE )
Graph |
An object generated by makegraph, cpp_simplify or cpp_contract function. |
from |
A vector of one or more vertices from which distances are calculated (origin). |
to |
A vector of one or more vertices (destination). |
algorithm |
Character. Only for contracted graph, |
aggregate_aux |
Logical. If |
allcores |
Logical (deprecated). If |
If graph is not contracted, get_distance_matrix()
recursively perform Dijkstra algorithm for each from
nodes.
If graph is contracted, the user has the choice between :
many to many contraction hierarchies (mch
) : optimal for square matrix.
PHAST (phast
) : outperform mch on rectangular matrix
Shortest path is always computed according to the main edge weights, corresponding to the 3rd column of df
argument in makegraph()
function.
If aggregate_aux
argument is TRUE
, the values returned are the sum of auxiliary weights along shortest paths.
All algorithms are multithreaded. allcores
argument is deprecated, please use RcppParallel::setThreadOptions()
to set the number of threads.
See details in package website : https://github.com/vlarmet/cppRouting/blob/master/README.md
Matrix of shortest distances.
It is not possible to aggregate auxiliary weights on a Graph object coming from cpp_simplify function.
get_distance_pair, get_multi_paths
#Choose number of cores used by cppRouting RcppParallel::setThreadOptions(numThreads = 1) #Data describing edges of the graph edges <- data.frame(from_vertex = c(0,0,1,1,2,2,3,4,4), to_vertex = c(1,3,2,4,4,5,1,3,5), time = c(9,2,11,3,5,12,4,1,6), dist = c(5,3,4,7,5,5,5,8,7)) #Construct directed graph with travel time as principal weight, and distance as secondary weight graph <- makegraph(edges[,1:3], directed=TRUE, aux = edges$dist) #Get all nodes IDs nodes <- graph$dict$ref # Get matrix of shortest times between all nodes : the result are in time unit time_mat <- get_distance_matrix(graph, from = nodes, to = nodes) # Get matrix of distance according shortest times : the result are in distance unit dist_mat <- get_distance_matrix(graph, from = nodes, to = nodes, aggregate_aux = TRUE) print(time_mat) print(dist_mat)
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