Generate weighted edge list from an edge list with multiedges.

The attribute reporting the aggregated weight of the multiedges is computed according to the expression specified in `aggr_expression`. When no expression is specified, the 'attr' column returns the multiedge multiplicity.

multi2weight(edge.list, select_cols = NULL, aggr_expression = NULL)

Arguments

edge.list	dataframe containing a (weighted) edgelist.
select_cols	optional vector of 2 elements specifying which columns are the source,target for the edges from which building the weighted edge list. Otherwise column 1 is assumed to be the source and column 2 the target.
aggr_expression	string, the expression used to compute the aggregated value in the adjacency matrix in the presence of multiedges. It defaults to 'dplyr::n()'. If `edge.list` contains other columns such as `weight`, examples of `aggr_expression` could be `"mean(weight)"` to report the average of the `weight` column of the multiedges, `"min(weight)"` to report the minimum of the `weight` column of the multiedges.

Value

a tibble with 3 columns: source, target, and attr, where attr has been computed according to `aggr_expression`.

Examples

el <- data.frame(from= c('a','b','b','c','d','d','d','d'),
             to  = c('b','c','d','a','b','a','a','a'),
             attr= c( 1,  1,  1 , 1 , 1 , 1,  2 , 3 ),
            attr2= c( TRUE,  FALSE,  TRUE , TRUE , FALSE , TRUE,  TRUE , FALSE ))
# edgelist with multiedge multiplicities
multi2weight(el)
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target  attr
#>   <chr>  <chr>  <int>
#> 1 a      b          1
#> 2 b      c          1
#> 3 b      d          1
#> 4 c      a          1
#> 5 d      a          3
#> 6 d      b          1

# edgelist with sum of attr
multi2weight(el, aggr_expression='sum(attr)')
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target  attr
#>   <chr>  <chr>  <dbl>
#> 1 a      b          1
#> 2 b      c          1
#> 3 b      d          1
#> 4 c      a          1
#> 5 d      a          6
#> 6 d      b          1

# edgelist with mean of attr
multi2weight(el, aggr_expression='mean(attr)')
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target  attr
#>   <chr>  <chr>  <dbl>
#> 1 a      b          1
#> 2 b      c          1
#> 3 b      d          1
#> 4 c      a          1
#> 5 d      a          2
#> 6 d      b          1

# edgelist with min of attr
multi2weight(el, aggr_expression='min(attr)')
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target  attr
#>   <chr>  <chr>  <dbl>
#> 1 a      b          1
#> 2 b      c          1
#> 3 b      d          1
#> 4 c      a          1
#> 5 d      a          1
#> 6 d      b          1

# edgelist with max of attr
multi2weight(el, aggr_expression='max(attr)')
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target  attr
#>   <chr>  <chr>  <dbl>
#> 1 a      b          1
#> 2 b      c          1
#> 3 b      d          1
#> 4 c      a          1
#> 5 d      a          3
#> 6 d      b          1

# edgelist with any() of attr2
multi2weight(el, aggr_expression='any(attr2)')
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target attr 
#>   <chr>  <chr>  <lgl>
#> 1 a      b      TRUE 
#> 2 b      c      FALSE
#> 3 b      d      TRUE 
#> 4 c      a      TRUE 
#> 5 d      a      TRUE 
#> 6 d      b      FALSE

# edgelist with all() of attr2
multi2weight(el, aggr_expression='all(attr2)')
#> # A tibble: 6 x 3
#> # Groups:   source [4]
#>   source target attr 
#>   <chr>  <chr>  <lgl>
#> 1 a      b      TRUE 
#> 2 b      c      FALSE
#> 3 b      d      TRUE 
#> 4 c      a      TRUE 
#> 5 d      a      FALSE
#> 6 d      b      FALSE