Dyad level indices

Source: R/d.R

Dyad level indices

d_distance(x, mode = c("all", "out", "in"))

Arguments

x

graph object

mode

Character constant, gives whether the shortest paths to or from the given vertices should be calculated for directed graphs. If out then the shortest paths from the vertex, if in then to it will be considered. If all, the default, then the corresponding undirected graph will be used, ie. not directed paths are searched. This argument is ignored for undirected graphs.

Details

Calculate several dyad level indices.

Functions

  • d_distance(): Distance between each pair of vertices in the graph. Weights are discarded. The output of this function is a matrix. Use distances or geodist if edge weights are to be used or specific options are needed.

Examples

# 
# distance
g <- igraph::make_ring(10)
igraph::distances(g)
#>       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#>  [1,]    0    1    2    3    4    5    4    3    2     1
#>  [2,]    1    0    1    2    3    4    5    4    3     2
#>  [3,]    2    1    0    1    2    3    4    5    4     3
#>  [4,]    3    2    1    0    1    2    3    4    5     4
#>  [5,]    4    3    2    1    0    1    2    3    4     5
#>  [6,]    5    4    3    2    1    0    1    2    3     4
#>  [7,]    4    5    4    3    2    1    0    1    2     3
#>  [8,]    3    4    5    4    3    2    1    0    1     2
#>  [9,]    2    3    4    5    4    3    2    1    0     1
#> [10,]    1    2    3    4    5    4    3    2    1     0
d_distance(g)
#>       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#>  [1,]    0    1    2    3    4    5    4    3    2     1
#>  [2,]    1    0    1    2    3    4    5    4    3     2
#>  [3,]    2    1    0    1    2    3    4    5    4     3
#>  [4,]    3    2    1    0    1    2    3    4    5     4
#>  [5,]    4    3    2    1    0    1    2    3    4     5
#>  [6,]    5    4    3    2    1    0    1    2    3     4
#>  [7,]    4    5    4    3    2    1    0    1    2     3
#>  [8,]    3    4    5    4    3    2    1    0    1     2
#>  [9,]    2    3    4    5    4    3    2    1    0     1
#> [10,]    1    2    3    4    5    4    3    2    1     0
d_distance(snafun::to_network(g))
#>    1 2 3 4 5 6 7 8 9 10
#> 1  0 1 2 3 4 5 4 3 2  1
#> 2  1 0 1 2 3 4 5 4 3  2
#> 3  2 1 0 1 2 3 4 5 4  3
#> 4  3 2 1 0 1 2 3 4 5  4
#> 5  4 3 2 1 0 1 2 3 4  5
#> 6  5 4 3 2 1 0 1 2 3  4
#> 7  4 5 4 3 2 1 0 1 2  3
#> 8  3 4 5 4 3 2 1 0 1  2
#> 9  2 3 4 5 4 3 2 1 0  1
#> 10 1 2 3 4 5 4 3 2 1  0
igraph::V(g)$name <- LETTERS[1:10]
igraph::distances(g)
#>   A B C D E F G H I J
#> A 0 1 2 3 4 5 4 3 2 1
#> B 1 0 1 2 3 4 5 4 3 2
#> C 2 1 0 1 2 3 4 5 4 3
#> D 3 2 1 0 1 2 3 4 5 4
#> E 4 3 2 1 0 1 2 3 4 5
#> F 5 4 3 2 1 0 1 2 3 4
#> G 4 5 4 3 2 1 0 1 2 3
#> H 3 4 5 4 3 2 1 0 1 2
#> I 2 3 4 5 4 3 2 1 0 1
#> J 1 2 3 4 5 4 3 2 1 0
d_distance(g)
#>   A B C D E F G H I J
#> A 0 1 2 3 4 5 4 3 2 1
#> B 1 0 1 2 3 4 5 4 3 2
#> C 2 1 0 1 2 3 4 5 4 3
#> D 3 2 1 0 1 2 3 4 5 4
#> E 4 3 2 1 0 1 2 3 4 5
#> F 5 4 3 2 1 0 1 2 3 4
#> G 4 5 4 3 2 1 0 1 2 3
#> H 3 4 5 4 3 2 1 0 1 2
#> I 2 3 4 5 4 3 2 1 0 1
#> J 1 2 3 4 5 4 3 2 1 0
d_distance(snafun::to_network(g))
#>   A B C D E F G H I J
#> A 0 1 2 3 4 5 4 3 2 1
#> B 1 0 1 2 3 4 5 4 3 2
#> C 2 1 0 1 2 3 4 5 4 3
#> D 3 2 1 0 1 2 3 4 5 4
#> E 4 3 2 1 0 1 2 3 4 5
#> F 5 4 3 2 1 0 1 2 3 4
#> G 4 5 4 3 2 1 0 1 2 3
#> H 3 4 5 4 3 2 1 0 1 2
#> I 2 3 4 5 4 3 2 1 0 1
#> J 1 2 3 4 5 4 3 2 1 0