Count the number of vertices/edges/slices in a graph
nvertices(graph)
nnodes(graph)
nedges(graph)
nlinks(graph)
nslices(graph)Any class of accepted graph format (see netdiffuseR-graphs).
For nvertices and nslices, an integer scalar equal to the number
of vertices and slices in the graph. Otherwise, from nedges, either a list
of size \(t\) with the counts of edges (non-zero elements in the adjacency matrices) at
each time period, or, when graph is static, a single scalar with
such number.
nnodes and nlinks are just aliases for nvertices and
nedges respectively.
# Creating a dynamic graph (we will use this for all the classes) -----------
set.seed(13133)
diffnet <- rdiffnet(100, 4)
#> Warning: The option -copy.first- is set to TRUE. In this case, the first graph will be treated as a baseline, and thus, networks after T=1 will be replaced with T-1.
# Lets use the first time period as a static graph
graph_mat <- diffnet$graph[[1]]
graph_dgCMatrix <- methods::as(graph_mat, "dgCMatrix")
# Now lets generate the other dynamic graphs
graph_list <- diffnet$graph
graph_array <- as.array(diffnet) # using the as.array method for diffnet objects
# Now we can compare vertices counts
nvertices(diffnet)
#> [1] 100
nvertices(graph_list)
#> [1] 100
nvertices(graph_array)
#> [1] 100
nvertices(graph_mat)
#> [1] 100
nvertices(graph_dgCMatrix)
#> [1] 100
# ... and edges count
nedges(diffnet)
#> $`1`
#> [1] 100
#>
#> $`2`
#> [1] 100
#>
#> $`3`
#> [1] 100
#>
#> $`4`
#> [1] 100
#>
nedges(graph_list)
#> $`1`
#> [1] 100
#>
#> $`2`
#> [1] 100
#>
#> $`3`
#> [1] 100
#>
#> $`4`
#> [1] 100
#>
nedges(graph_array)
#> $`1`
#> [1] 100
#>
#> $`2`
#> [1] 100
#>
#> $`3`
#> [1] 100
#>
#> $`4`
#> [1] 100
#>
nedges(graph_mat)
#> [1] 100
nedges(graph_dgCMatrix)
#> [1] 100