Extract one of more ego network from an input graph
extract_egonet(x, vertices = NULL, order = 1, type = c("all", "out", "in"))input graph of class igraph or network
if NULL the egonetworks for each vertex in the graph
are returned. If vertices is a single vertex or a vector, the ego networks
for these specific vertices are returned. This is generally what you want.
the order of the resulting graph
Character constant, it specifies how to use the direction of the
edges if a directed graph is analyzed. For ‘out’ only the outgoing edges are
followed, so all vertices reachable from the source vertex in at most
order steps are counted. For ‘"in"’ all vertices from which the
source vertex is reachable in at most order steps are counted.
‘"all"’ ignores the direction of the edges. This argument is ignored for undirected graphs.
a list of graphs of the same class as the input graph
For each vertex in vertices, the ego network is returned. This includes
the vertices that can be reached in order number of steps.
The type argument determines whether edges should be followed as
incoming, outgoing, or undirected (and are considered undirected anyway for
an undirected graph.)
The output is a list of egonetworks, one for each ego vertex.
g <- igraph::graph_from_literal(One --+ Two +-+ Three +-- Four --+ Five +-- Six +-- Seven +-+ Eight +-+ One +-+ Five)
snafun::to_matrix(g)
#> One Two Three Four Five Six Seven Eight
#> One 0 1 0 0 1 0 0 1
#> Two 0 0 1 0 0 0 0 0
#> Three 0 1 0 0 0 0 0 0
#> Four 0 0 1 0 1 0 0 0
#> Five 1 0 0 0 0 0 0 0
#> Six 0 0 0 0 1 0 0 0
#> Seven 0 0 0 0 0 1 0 1
#> Eight 1 0 0 0 0 0 1 0
extract_egonet(g, vertices = 1, order = 1, type = "in")[[1]] |> snafun::to_matrix()
#> One Five Eight
#> One 0 1 1
#> Five 1 0 0
#> Eight 1 0 0
extract_egonet(g, vertices = 1, order = 1, type = "out")[[1]] |> snafun::to_matrix()
#> One Two Five Eight
#> One 0 1 1 1
#> Two 0 0 0 0
#> Five 1 0 0 0
#> Eight 1 0 0 0
extract_egonet(g, vertices = 1, order = 1, type = "all")[[1]] |> snafun::to_matrix()
#> One Two Five Eight
#> One 0 1 1 1
#> Two 0 0 0 0
#> Five 1 0 0 0
#> Eight 1 0 0 0
extract_egonet(g, vertices = 1, order = 2, type = "in")[[1]] |> snafun::to_matrix()
#> One Four Five Six Seven Eight
#> One 0 0 1 0 0 1
#> Four 0 0 1 0 0 0
#> Five 1 0 0 0 0 0
#> Six 0 0 1 0 0 0
#> Seven 0 0 0 1 0 1
#> Eight 1 0 0 0 1 0
extract_egonet(g, vertices = 1, order = 2, type = "out")[[1]] |> snafun::to_matrix()
#> One Two Three Five Seven Eight
#> One 0 1 0 1 0 1
#> Two 0 0 1 0 0 0
#> Three 0 1 0 0 0 0
#> Five 1 0 0 0 0 0
#> Seven 0 0 0 0 0 1
#> Eight 1 0 0 0 1 0
extract_egonet(g, vertices = 1, order = 2, type = "all")[[1]] |> snafun::to_matrix()
#> One Two Three Four Five Six Seven Eight
#> One 0 1 0 0 1 0 0 1
#> Two 0 0 1 0 0 0 0 0
#> Three 0 1 0 0 0 0 0 0
#> Four 0 0 1 0 1 0 0 0
#> Five 1 0 0 0 0 0 0 0
#> Six 0 0 0 0 1 0 0 0
#> Seven 0 0 0 0 0 1 0 1
#> Eight 1 0 0 0 0 0 1 0
extract_egonet(g, vertices = c("One"), order = 2, type = "in")[[1]] |> snafun::to_matrix()
#> One Four Five Six Seven Eight
#> One 0 0 1 0 0 1
#> Four 0 0 1 0 0 0
#> Five 1 0 0 0 0 0
#> Six 0 0 1 0 0 0
#> Seven 0 0 0 1 0 1
#> Eight 1 0 0 0 1 0
extract_egonet(g, vertices = c("One", "Three"), order = 2, type = "in")
#> [[1]]
#> IGRAPH cce60c6 DN-- 6 9 --
#> + attr: name (v/c)
#> + edges from cce60c6 (vertex names):
#> [1] One ->Five One ->Eight Four ->Five Five ->One Six ->Five
#> [6] Seven->Six Seven->Eight Eight->One Eight->Seven
#>
#> [[2]]
#> IGRAPH cce6104 DN-- 4 4 --
#> + attr: name (v/c)
#> + edges from cce6104 (vertex names):
#> [1] One ->Two Two ->Three Three->Two Four ->Three
#>
g_n <- snafun::to_network(g)
extract_egonet(g_n, vertices = 1, order = 1, type = "in")[[1]] |> snafun::to_matrix()
#> One Five Eight
#> One 0 1 1
#> Five 1 0 0
#> Eight 1 0 0
extract_egonet(g_n, vertices = 1, order = 1, type = "out")[[1]] |> snafun::to_matrix()
#> One Two Five Eight
#> One 0 1 1 1
#> Two 0 0 0 0
#> Five 1 0 0 0
#> Eight 1 0 0 0
extract_egonet(g_n, vertices = 1, order = 1, type = "all")[[1]] |> snafun::to_matrix()
#> One Two Five Eight
#> One 0 1 1 1
#> Two 0 0 0 0
#> Five 1 0 0 0
#> Eight 1 0 0 0
extract_egonet(g_n, vertices = 1, order = 2, type = "in")[[1]] |> snafun::to_matrix()
#> One Four Five Six Seven Eight
#> One 0 0 1 0 0 1
#> Four 0 0 1 0 0 0
#> Five 1 0 0 0 0 0
#> Six 0 0 1 0 0 0
#> Seven 0 0 0 1 0 1
#> Eight 1 0 0 0 1 0
extract_egonet(g_n, vertices = 1, order = 2, type = "out")[[1]] |> snafun::to_matrix()
#> One Two Three Five Seven Eight
#> One 0 1 0 1 0 1
#> Two 0 0 1 0 0 0
#> Three 0 1 0 0 0 0
#> Five 1 0 0 0 0 0
#> Seven 0 0 0 0 0 1
#> Eight 1 0 0 0 1 0
extract_egonet(g_n, vertices = 1, order = 2, type = "all")[[1]] |> snafun::to_matrix()
#> One Two Three Four Five Six Seven Eight
#> One 0 1 0 0 1 0 0 1
#> Two 0 0 1 0 0 0 0 0
#> Three 0 1 0 0 0 0 0 0
#> Four 0 0 1 0 1 0 0 0
#> Five 1 0 0 0 0 0 0 0
#> Six 0 0 0 0 1 0 0 0
#> Seven 0 0 0 0 0 1 0 1
#> Eight 1 0 0 0 0 0 1 0
extract_egonet(g_n, vertices = c("One"), order = 2, type = "in")[[1]] |> snafun::to_matrix()
#> One Four Five Six Seven Eight
#> One 0 0 1 0 0 1
#> Four 0 0 1 0 0 0
#> Five 1 0 0 0 0 0
#> Six 0 0 1 0 0 0
#> Seven 0 0 0 1 0 1
#> Eight 1 0 0 0 1 0
extract_egonet(g_n, vertices = c("One", "Three"), order = 2, type = "in")
#> $`1`
#> Network attributes:
#> vertices = 6
#> directed = TRUE
#> hyper = FALSE
#> loops = FALSE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 9
#> missing edges= 0
#> non-missing edges= 9
#>
#> Vertex attribute names:
#> vertex.names
#>
#> No edge attributes
#>
#> $`3`
#> Network attributes:
#> vertices = 4
#> directed = TRUE
#> hyper = FALSE
#> loops = FALSE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 4
#> missing edges= 0
#> non-missing edges= 4
#>
#> Vertex attribute names:
#> vertex.names
#>
#> No edge attributes
#>