Calculate all topological indexes of a network

Add topological indexes for a network

net_par(
  go,
  mode = c("v", "e", "n", "all"),
  fast = TRUE,
  remove_negative = FALSE
)

c_net_index(go, force = FALSE)

Arguments

go

igraph or metanet

mode

calculate what? c("v", "e", "n", "all")

fast

less indexes for faster calculate ?

remove_negative

remove negative edge or not? default: FALSE

force

replace existed net_par

Value

a 3-elements list

n_index

indexs of the whole network

v_index

indexs of each vertex

e_index

indexs of each edge

Examples

igraph::make_graph("Walther") %>% net_par()
#> $n_index
#>      name Node_number Edge_number Edge_density Negative_percentage
#> 1 Walther          25          31    0.1033333                  NA
#>   Average_path_length Global_efficiency Average_degree Average_weighted_degree
#> 1            3.586667         0.3679762           2.48                    2.48
#>   Diameter Clustering_coefficient Centralized_betweenness Natural_connectivity
#> 1        8                      0               0.1436084             1.029526
#> 
#> $v_index
#>    name Degree Clustering_coefficient Betweenness Eccentricity   Closeness
#> 1     1      1                      0     0.00000            8 0.009009009
#> 2     2      3                      0    30.79762            7 0.011363636
#> 3     3      3                      0    36.63810            6 0.012345679
#> 4     4      3                      0    41.54286            7 0.012195122
#> 5     5      2                      0    30.84762            6 0.012048193
#> 6     6      3                      0    44.26905            5 0.012820513
#> 7     7      3                      0    62.25714            6 0.012987013
#> 8     8      2                      0    23.00000            7 0.010204082
#> 9     9      3                      0    42.82143            6 0.012658228
#> 10   10      3                      0    49.73810            5 0.013157895
#> 11   11      3                      0    66.67857            6 0.013333333
#> 12   12      2                      0    23.00000            7 0.010416667
#> 13   13      1                      0     0.00000            8 0.008403361
#> 14   14      3                      0    32.05476            7 0.012820513
#> 15   15      3                      0    38.00714            6 0.012987013
#> 16   16      3                      0    26.13333            7 0.011627907
#> 17   17      2                      0    10.82619            8 0.010989011
#> 18   18      2                      0    12.88810            6 0.011494253
#> 19   19      3                      0    29.44286            7 0.012195122
#> 20   20      2                      0    11.57619            6 0.011494253
#> 21   21      3                      0    69.09048            5 0.014285714
#> 22   22      1                      0     0.00000            8 0.008264463
#> 23   23      2                      0    10.40476            6 0.012048193
#> 24   24      3                      0    36.93095            5 0.013513514
#> 25   25      3                      0    47.05476            6 0.013698630
#>     Hub_score
#> 1  0.26099995
#> 2  0.76475258
#> 3  0.82459888
#> 4  0.65139399
#> 5  0.38805188
#> 6  0.48563182
#> 7  0.48420351
#> 8  0.21792635
#> 9  0.87458019
#> 10 0.79784358
#> 11 0.61009457
#> 12 0.27458636
#> 13 0.09371269
#> 14 1.00000000
#> 15 0.86397541
#> 16 0.68757575
#> 17 0.45697267
#> 18 0.44141478
#> 19 0.60580804
#> 20 0.37249399
#> 21 0.71520031
#> 22 0.07437538
#> 23 0.56032158
#> 24 0.84394749
#> 25 0.73887080
#> 
#> $e_index
#>    id from to
#> 1   1    1  2
#> 2   2    2  3
#> 3   3    2  9
#> 4   4    3  4
#> 5   5    3 14
#> 6   6    4  5
#> 7   7    4 17
#> 8   8    5  6
#> 9   9    6  7
#> 10 10    6 20
#> 11 11    7  8
#> 12 12    7 21
#> 13 13    8 22
#> 14 14    9 10
#> 15 15    9 14
#> 16 16   10 11
#> 17 17   10 23
#> 18 18   11 12
#> 19 19   11 21
#> 20 20   12 13
#> 21 21   14 15
#> 22 22   15 16
#> 23 23   15 24
#> 24 24   16 17
#> 25 25   16 18
#> 26 26   18 19
#> 27 27   19 20
#> 28 28   19 25
#> 29 29   21 25
#> 30 30   23 24
#> 31 31   24 25
#> 
c_net_index(co_net) -> co_net_with_par