Function to aggregate positions defined via indirect relations to construct centrality scores.

aggregate_positions(tau_x, type = "sum")

## Arguments

tau_x Numeric matrix containing indirect relations calculated with indirect_relations. String indicating the type of aggregation to be used. See Details for options.

## Value

Scores for the index defined by the indirect relation tau_x and the used aggregation type.

## Details

The predefined functions are mainly wrappers around base R functions. type='sum', for instance, is equivalent to rowSums(). A non-base functions is type='invsum' which calculates the inverse of type='sum'. type='self' is mostly useful for walk based relations, e.g. to count closed walks. Other self explanatory options are type='mean', type='min', type='max' and type='prod'.

## Examples

library(igraph)#>
#> Attaching package: ‘igraph’#> The following object is masked from ‘package:testthat’:
#>
#>     compare#> The following objects are masked from ‘package:stats’:
#>
#>     decompose, spectrum#> The following object is masked from ‘package:base’:
#>
#>     unionlibrary(magrittr)#>
#> Attaching package: ‘magrittr’#> The following objects are masked from ‘package:testthat’:
#>
#>     equals, is_less_than, not
g <- graph.empty(n=11,directed = FALSE)
6,10,6,11,7,9,7,10,7,11,8,9,8,10,9,10))
#degree
g %>% indirect_relations(type='identity') %>%
aggregate_positions(type='sum')#> Warning: type="identity" is deprecated. Using "adjacency" instead.#>  [1] 1 1 2 2 3 4 4 4 4 4 5
#closeness centrality
g %>% indirect_relations(type='dist_sp') %>%
aggregate_positions(type='invsum')#>  [1] 0.03704 0.02941 0.04000 0.04000 0.05000 0.05882 0.05263 0.05556 0.05556
#> [10] 0.05263 0.05556
#betweenness centrality
g %>% indirect_relations(type='depend_sp') %>%
aggregate_positions(type='sum')#>  [1]  0.000  0.000  0.000 18.000  7.667 19.667  5.333 32.667 14.667  2.667
#> [11] 29.333
#eigenvector centrality
g %>% indirect_relations(type='walks',FUN=walks_limit_prop) %>%
aggregate_positions(type='sum')#>  [1] 0.27516 0.07864 0.46106 0.29410 0.69521 1.19904 1.21772 1.02121 1.10978
#> [10] 1.21608 1.02901
#subgraph centrality
g %>% indirect_relations(type='walks',FUN=walks_exp) %>%
aggregate_positions(type='self')#>  [1] 1.825 1.595 3.149 2.423 4.387 7.807 7.939 6.673 7.033 8.242 7.390