| as_adjacency_matrix {igraph} | R Documentation |
Sometimes it is useful to work with a standard representation of a graph, like an adjacency matrix.
as_adjacency_matrix(
graph,
type = c("both", "upper", "lower"),
attr = NULL,
edges = FALSE,
names = TRUE,
sparse = igraph_opt("sparsematrices")
)
as_adj(
graph,
type = c("both", "upper", "lower"),
attr = NULL,
edges = FALSE,
names = TRUE,
sparse = igraph_opt("sparsematrices")
)
graph |
The graph to convert. |
type |
Gives how to create the adjacency matrix for undirected graphs.
It is ignored for directed graphs. Possible values: |
attr |
Either Note that this works only for certain attribute types. If the |
edges |
Logical scalar, whether to return the edge ids in the matrix. For non-existant edges zero is returned. |
names |
Logical constant, whether to assign row and column names
to the matrix. These are only assigned if the |
sparse |
Logical scalar, whether to create a sparse matrix. The
‘ |
as_adjacency_matrix() returns the adjacency matrix of a graph, a
regular matrix if sparse is FALSE, or a sparse matrix, as
defined in the ‘Matrix’ package, if sparse if
TRUE.
A vcount(graph) by vcount(graph) (usually) numeric
matrix.
graph_from_adjacency_matrix(), read_graph()
Other conversion:
as.directed(),
as.matrix.igraph(),
as_adj_list(),
as_data_frame(),
as_edgelist(),
as_graphnel(),
as_incidence_matrix(),
as_long_data_frame(),
graph_from_adj_list(),
graph_from_graphnel()
Other conversion:
as.directed(),
as.matrix.igraph(),
as_adj_list(),
as_data_frame(),
as_edgelist(),
as_graphnel(),
as_incidence_matrix(),
as_long_data_frame(),
graph_from_adj_list(),
graph_from_graphnel()
g <- sample_gnp(10, 2 / 10)
as_adjacency_matrix(g)
V(g)$name <- letters[1:vcount(g)]
as_adjacency_matrix(g)
E(g)$weight <- runif(ecount(g))
as_adjacency_matrix(g, attr = "weight")