Sometimes it is useful to work with a standard representation of a graph, like an adjacency matrix.

## Usage

``````as_adjacency_matrix(
graph,
type = c("both", "upper", "lower"),
attr = NULL,
edges = deprecated(),
names = TRUE,
sparse = igraph_opt("sparsematrices")
)

graph,
type = c("both", "upper", "lower"),
attr = NULL,
edges = deprecated(),
names = TRUE,
sparse = igraph_opt("sparsematrices")
)``````

## Arguments

graph

The graph to convert.

type

Gives how to create the adjacency matrix for undirected graphs. It is ignored for directed graphs. Possible values: `upper`: the upper right triangle of the matrix is used, `lower`: the lower left triangle of the matrix is used. `both`: the whole matrix is used, a symmetric matrix is returned.

attr

Either `NULL` or a character string giving an edge attribute name. If `NULL` a traditional adjacency matrix is returned. If not `NULL` then the values of the given edge attribute are included in the adjacency matrix. If the graph has multiple edges, the edge attribute of an arbitrarily chosen edge (for the multiple edges) is included. This argument is ignored if `edges` is `TRUE`.

Note that this works only for certain attribute types. If the `sparse` argumen is `TRUE`, then the attribute must be either logical or numeric. If the `sparse` argument is `FALSE`, then character is also allowed. The reason for the difference is that the `Matrix` package does not support character sparse matrices yet.

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 `name` vertex attribute is present in the graph.

sparse

Logical scalar, whether to create a sparse matrix. The ‘`Matrix`’ package must be installed for creating sparse matrices.

## Value

A `vcount(graph)` by `vcount(graph)` (usually) numeric matrix.

## Details

`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`.

`graph_from_adjacency_matrix()`, `read_graph()`

Other conversion: `as.directed()`, `as.matrix.igraph()`, `as_adj_list()`, `as_biadjacency_matrix()`, `as_data_frame()`, `as_edgelist()`, `as_graphnel()`, `as_long_data_frame()`, `graph_from_adj_list()`, `graph_from_graphnel()`

## Examples

``````
g <- sample_gnp(10, 2 / 10)
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#>
#>  [1,] . . . . . . . 1 1 .
#>  [2,] . . 1 . . . . . . .
#>  [3,] . 1 . . . . 1 1 . .
#>  [4,] . . . . . . . . . .
#>  [5,] . . . . . 1 . 1 . .
#>  [6,] . . . . 1 . 1 . . .
#>  [7,] . . 1 . . 1 . . . 1
#>  [8,] 1 . 1 . 1 . . . . 1
#>  [9,] 1 . . . . . . . . 1
#> [10,] . . . . . . 1 1 1 .
V(g)\$name <- letters[1:vcount(g)]
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#>   [[ suppressing 10 column names ‘a’, ‘b’, ‘c’ ... ]]
#>
#> a . . . . . . . 1 1 .
#> b . . 1 . . . . . . .
#> c . 1 . . . . 1 1 . .
#> d . . . . . . . . . .
#> e . . . . . 1 . 1 . .
#> f . . . . 1 . 1 . . .
#> g . . 1 . . 1 . . . 1
#> h 1 . 1 . 1 . . . . 1
#> i 1 . . . . . . . . 1
#> j . . . . . . 1 1 1 .
E(g)\$weight <- runif(ecount(g))
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#>   [[ suppressing 10 column names ‘a’, ‘b’, ‘c’ ... ]]
#>
#> a .         .         .         . .           .          .          0.125495772
#> b .         .         0.9695255 . .           .          .          .
#> c .         0.9695255 .         . .           .          0.14713281 0.514231354
#> d .         .         .         . .           .          .          .
#> e .         .         .         . .           0.00332753 .          0.003141262
#> f .         .         .         . 0.003327530 .          0.60409122 .
#> g .         .         0.1471328 . .           0.60409122 .          .
#> h 0.1254958 .         0.5142314 . 0.003141262 .          .          .
#> i 0.1863833 .         .         . .           .          .          .
#> j .         .         .         . .           .          0.02471268 0.330121691
#>
#> a 0.186383283 .
#> b .           .
#> c .           .
#> d .           .
#> e .           .
#> f .           .
#> g .           0.024712676
#> h .           0.330121691
#> i .           0.009822477
#> j 0.009822477 .
``````