Use this if you are using igraph from R

Query and manipulate a graph as it were an adjacency matrix

## 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]

`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` |
A numeric or character vector giving vertex ids or
names. Together with the |

`sparse` |
Logical scalar, whether to return sparse matrices. |

`edges` |
Logical scalar, whether to return edge ids. |

`drop` |
Ignored. |

`attr` |
If not |

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

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.

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.

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)]

.

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.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.

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.

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.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 ‘`[[`

’.

A scalar or matrix. See details below.

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 1.2.3 Index]