graph.adjacency {igraph} | R Documentation |

`graph.adjacency`

is a flexible function for creating
`igraph`

graphs from adjacency matrices.

graph.adjacency(adjmatrix, mode=c("directed", "undirected", "max", "min", "upper", "lower", "plus"), weighted=NULL, diag=TRUE, add.colnames=NULL, add.rownames=NA)

`adjmatrix` |
A square adjacency matrix. From igraph version 0.5.1
this can be a sparse matrix created with the |

`mode` |
Character scalar, specifies how igraph should interpret the supplied
matrix. See also the |

`weighted` |
This argument specifies whether to create a weighted
graph from an adjacency matrix. If it is |

`diag` |
Logical scalar, whether to include the diagonal of the
matrix in the calculation. If this is |

`add.colnames` |
Character scalar, whether to add the column names as
vertex attributes. If it is ‘ |

`add.rownames` |
Character scalar, whether to add the row names as
vertex attributes. Possible values the same as the previous
argument. By default row names are not added. If
‘ |

`graph.adjacency`

creates a graph from an adjacency matrix.

The order of the vertices are preserved, i.e. the vertex corresponding to the first row will be vertex 0 in the graph, etc.

`graph.adjacency`

operates in two main modes, depending on the
`weighted`

argument.

If this argument is `NULL`

then an unweighted graph is
created and an element of the adjacency matrix gives the number
of edges to create between the two corresponding vertices.
The details depend on the value of the `mode`

argument:

`directed`

The graph will be directed and a matrix element gives the number of edges between two vertices.

`undirected`

This is exactly the same as

`max`

, for convenience. Note that it is*not*checked whether the matrix is symmetric.`max`

An undirected graph will be created and

`max(A(i,j), A(j,i))`

gives the number of edges.`upper`

An undirected graph will be created, only the upper right triangle (including the diagonal) is used for the number of edges.

`lower`

An undirected graph will be created, only the lower left triangle (including the diagonal) is used for creating the edges.

`min`

undirected graph will be created with

`min(A(i,j), A(j,i))`

edges between vertex`i`

and`j`

.`plus`

undirected graph will be created with

`A(i,j)+A(j,i)`

edges between vertex`i`

and`j`

.

If the `weighted`

argument is not `NULL`

then the elements
of the matrix give the weights of the edges (if they are not zero).
The details depend on the value of the `mode`

argument:

`directed`

The graph will be directed and a matrix element gives the edge weights.

`undirected`

First we check that the matrix is symmetric. It is an error if not. Then only the upper triangle is used to create a weighted undirected graph.

`max`

An undirected graph will be created and

`max(A(i,j), A(j,i))`

gives the edge weights.`upper`

An undirected graph will be created, only the upper right triangle (including the diagonal) is used (for the edge weights).

`lower`

An undirected graph will be created, only the lower left triangle (including the diagonal) is used for creating the edges.

`min`

An undirected graph will be created,

`min(A(i,j), A(j,i))`

gives the edge weights.`plus`

An undirected graph will be created,

`A(i,j)+A(j,i)`

gives the edge weights.

An igraph graph object.

Gabor Csardi csardi.gabor@gmail.com

graph and `graph.formula`

for
other ways to create graphs.

adjm <- matrix(sample(0:1, 100, replace=TRUE, prob=c(0.9,0.1)), nc=10) g1 <- graph.adjacency( adjm ) adjm <- matrix(sample(0:5, 100, replace=TRUE, prob=c(0.9,0.02,0.02,0.02,0.02,0.02)), nc=10) g2 <- graph.adjacency(adjm, weighted=TRUE) E(g2)$weight ## various modes for weighted graphs, with some tests nzs <- function(x) sort(x [x!=0]) adjm <- matrix(runif(100), 10) adjm[ adjm<0.5 ] <- 0 g3 <- graph.adjacency((adjm + t(adjm))/2, weighted=TRUE, mode="undirected") g4 <- graph.adjacency(adjm, weighted=TRUE, mode="max") all(nzs(pmax(adjm, t(adjm))[upper.tri(adjm)]) == sort(E(g4)$weight)) g5 <- graph.adjacency(adjm, weighted=TRUE, mode="min") all(nzs(pmin(adjm, t(adjm))[upper.tri(adjm)]) == sort(E(g5)$weight)) g6 <- graph.adjacency(adjm, weighted=TRUE, mode="upper") all(nzs(adjm[upper.tri(adjm)]) == sort(E(g6)$weight)) g7 <- graph.adjacency(adjm, weighted=TRUE, mode="lower") all(nzs(adjm[lower.tri(adjm)]) == sort(E(g7)$weight)) g8 <- graph.adjacency(adjm, weighted=TRUE, mode="plus") d2 <- function(x) { diag(x) <- diag(x)/2; x } all(nzs((d2(adjm+t(adjm)))[lower.tri(adjm)]) == sort(E(g8)$weight)) g9 <- graph.adjacency(adjm, weighted=TRUE, mode="plus", diag=FALSE) d0 <- function(x) { diag(x) <- 0 } all(nzs((d0(adjm+t(adjm)))[lower.tri(adjm)]) == sort(E(g9)$weight)) ## row/column names rownames(adjm) <- sample(letters, nrow(adjm)) colnames(adjm) <- seq(ncol(adjm)) g10 <- graph.adjacency(adjm, weighted=TRUE, add.rownames="code") summary(g10)

[Package *igraph* version 0.6.5-1 Index]