# clusters

From igraph v0.6.5-2
by Gabor Csardi

##### Connected components of a graph

Calculate the maximal (weakly or strongly) connected components of a graph

- Keywords
- graphs

##### Usage

```
is.connected(graph, mode=c("weak", "strong"))
clusters(graph, mode=c("weak", "strong"))
no.clusters(graph, mode=c("weak", "strong"))
cluster.distribution(graph, cumulative = FALSE, mul.size = FALSE, ...)
```

##### Arguments

- graph
- The graph to analyze.
- mode
- Character string, either
weak orstrong . For directed graphsweak implies weakly,strong strongly connected components to search. It is ignored for undirected graphs. - cumulative
- Logical, if TRUE the cumulative distirubution (relative frequency) is calculated.
- mul.size
- Logical. If TRUE the relative frequencies will be multiplied by the cluster sizes.
- ...
- Additional attributes to pass to
`cluster`

, right now only`mode`

makes sense.

##### Details

`is.connected`

decides whether the graph is weakly or strongly
connected.

`clusters`

finds the maximal (weakly or strongly) connected
components of a graph.

`no.clusters`

does almost the same as `clusters`

but returns
only the number of clusters found instead of returning the actual
clusters.

`cluster.distribution`

creates a histogram for the maximal
connected component sizes.

The weakly connected components are found by a simple breadth-first search. The strongly connected components are implemented by two consecutive depth-first searches.

##### Value

- For
`is.connected`

a logical constant.For

`clusters`

a named list with three components: membership numeric vector giving the cluster id to which each vertex belongs. csize numeric vector giving the sizes of the clusters. no numeric constant, the number of clusters. - For
`no.clusters`

an integer constant is returned. For`cluster.distribution`

a numeric vector with the relative frequencies. The length of the vector is the size of the largest component plus one. Note that (for currently unknown reasons) the first element of the vector is the number of clusters of size zero, so this is always zero.

##### concept

- Connectedness
- Graph component

##### See Also

##### Examples

```
g <- erdos.renyi.game(20, 1/20)
clusters(g)
```

*Documentation reproduced from package igraph, version 0.6.5-2, License: GPL (>= 2)*

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