[.igraph {igraph} | R Documentation

## Query and manipulate a graph as it were an adjacency matrix

### Description

Query and manipulate a graph as it were an adjacency matrix

### Usage

    ## S3 method for class 'igraph'
    x[i, j, ..., from, to,
      sparse = igraph_opt("sparsematrices"), edges = FALSE, drop = TRUE,
      attr = if (is_weighted(x)) "weight" else NULL]

### Arguments

`x` | The graph.
`i` | Index. Vertex ids or names or logical vectors. See details below.
`j` | Index. Vertex ids or names or logical vectors. See details below.
`...` | Currently ignored.
`from` | A numeric or character vector giving vertex ids or names. Together with the `to` argument, it can be used to query/set a sequence of edges. See details below. This argument cannot be present together with any of the `i` and `j` arguments and if it is present, then the `to` argument must be present as well.
`to` | A numeric or character vector giving vertex ids or names. Together with the `from` argument, it can be used to query/set a sequence of edges. See details below. This argument cannot be present together with any of the `i` and `j` arguments and if it is present, then the `from` argument must be present as well.
`sparse` | Logical scalar, whether to return sparse matrices.
`edges` | Logical scalar, whether to return edge ids.
`drop` | Ignored.
`attr` | If not `NULL`, then it should be the name of an edge attribute. This attribute is queried and returned.

### Details

The single bracket indexes the (possibly weighted) adjacency matrix of the graph. Here is what you can do with it:

1. Check whether there is an edge between two vertices (v and w) in the graph:

         graph[v, w]

   A numeric scalar is returned, one if the edge exists, zero otherwise.

2. Extract the (sparse) adjacency matrix of the graph, or part of it:

         graph[]
       graph[1:3,5:6]
       graph[c(1,3,5),]

   The first variants returns the full adjacency matrix, the other two return part of it.

3. The `from` and `to` arguments can be used to check the existence of many edges. In this case, both `from` and `to` must be present and they must have the same length. They must contain vertex ids or names. A numeric vector is returned, of the same length as `from` and `to`, it contains ones for existing edges edges and zeros for non-existing ones. Example:

         graph[from=1:3, to=c(2,3,5)]

   .

4. For weighted graphs, the `[` operator returns the edge weights. For non-esistent edges zero weights are returned. Other edge attributes can be queried as well, by giving the `attr` argument.

5. Querying edge ids instead of the existance of edges or edge attributes. E.g.

         graph[1, 2, edges=TRUE]

   returns the id of the edge between vertices 1 and 2, or zero if there is no such edge.

6. Adding one or more edges to a graph. For this the element(s) of the imaginary adjacency matrix must be set to a non-zero numeric value (or `TRUE`):

         graph[1, 2] <- 1
       graph[1:3,1] <- 1
       graph[from=1:3, to=c(2,3,5)] <- TRUE

   This does not affect edges that are already present in the graph, i.e. no multiple edges are created.

7. Adding weighted edges to a graph. The `attr` argument contains the name of the edge attribute to set, so it does not have to be ‘weight’:

         graph[1, 2, attr="weight"]<- 5
       graph[from=1:3, to=c(2,3,5)] <- c(1,-1,4)

   If an edge is already present in the network, then only its weights or other attribute are updated. If the graph is already weighted, then the `attr="weight"` setting is implicit, and one does not need to give it explicitly.

8. Deleting edges. The replacement syntax allow the deletion of edges, by specifying `FALSE` or `NULL` as the replacement value:

         graph[v, w] <- FALSE

   removes the edge from vertex v to vertex w. As this can be used to delete edges between two sets of vertices, either pairwise:

         graph[from=v, to=w] <- FALSE

   or not:

         graph[v, w] <- FALSE

   if v and w are vectors of edge ids or names.

‘`[`’ allows logical indices and negative indices as well, with the usual R semantics. E.g.

      graph[degree(graph)==0, 1] <- 1

adds an edge from every isolate vertex to vertex one, and

      G <- make_empty_graph(10)
    G[-1,1] <- TRUE

creates a star graph.

Of course, the indexing operators support vertex names, so instead of a numeric vertex id a vertex can also be given to ‘`[`’ and ‘`[[`’.

### Value

A scalar or matrix. See details below.

### See Also

Other structural queries: `[[.igraph`, `adjacent_vertices`, `are_adjacent`, `ends`, `get.edge.ids`, `gorder`, `gsize`, `head_of`, `incident_edges`, `incident`, `is_directed`, `neighbors`, `tail_of`

[Package igraph version 1.1.2 Index]