subgraph_isomorphic {igraph} | R Documentation

## Decide if a graph is subgraph isomorphic to another one

### Description

Decide if a graph is subgraph isomorphic to another one

### Usage

    subgraph_isomorphic(pattern, target, method = c("auto", "lad", "vf2"), ...)

    is_subgraph_isomorphic_to(pattern, target, method = c("auto", "lad", "vf2"),
      ...)

### Arguments

`pattern` | The smaller graph, it might be directed or undirected. Undirected graphs are treated as directed graphs with mutual edges.
`target` | The bigger graph, it might be directed or undirected. Undirected graphs are treated as directed graphs with mutual edges.
`method` | The method to use. Possible values: ‘auto’, ‘lad’, ‘vf2’. See their details below.
`...` | Additional arguments, passed to the various methods.

### Value

Logical scalar, `TRUE` if the `pattern` is isomorphic to a (possibly induced) subgraph of `target`.

### ‘auto’ method

This method currently selects ‘lad’, always, as it seems to be superior on most graphs.

### ‘lad’ method

This is the LAD algorithm by Solnon, see the reference below. It has the following extra arguments:

domains

  If not `NULL`, then it specifies matching restrictions. It must be a list of `target` vertex sets, given as numeric vertex ids or symbolic vertex names. The length of the list must be `vcount(pattern)` and for each vertex in `pattern` it gives the allowed matching vertices in `target`. Defaults to `NULL`.

induced

  Logical scalar, whether to search for an induced subgraph. It is `FALSE` by default.

time.limit

  The processor time limit for the computation, in seconds. It defaults to `Inf`, which means no limit.

### ‘vf2’ method

This method uses the VF2 algorithm by Cordella, Foggia et al., see references below. It supports vertex and edge colors and have the following extra arguments:

vertex.color1, vertex.color2

  Optional integer vectors giving the colors of the vertices for colored graph isomorphism. If they are not given, but the graph has a “color” vertex attribute, then it will be used. If you want to ignore these attributes, then supply `NULL` for both of these arguments. See also examples below.

edge.color1, edge.color2

  Optional integer vectors giving the colors of the edges for edge-colored (sub)graph isomorphism. If they are not given, but the graph has a “color” edge attribute, then it will be used. If you want to ignore these attributes, then supply `NULL` for both of these arguments.

### References

LP Cordella, P Foggia, C Sansone, and M Vento: An improved algorithm for matching large graphs, Proc. of the 3rd IAPR TC-15 Workshop on Graphbased Representations in Pattern Recognition, 149–159, 2001.

C. Solnon: AllDifferent-based Filtering for Subgraph Isomorphism, Artificial Intelligence 174(12-13):850–864, 2010.

### See Also

Other graph isomorphism: `count_isomorphisms`, `count_subgraph_isomorphisms`, `graph_from_isomorphism_class`, `isomorphic`, `isomorphism_class`, `isomorphisms`, `subgraph_isomorphisms`

### Examples

    # A LAD example
    pattern <- make_graph(~ 1:2:3:4:5,
                          1 - 2:5, 2 - 1:5:3, 3 - 2:4, 4 - 3:5, 5 - 4:2:1)
    target <- make_graph(~ 1:2:3:4:5:6:7:8:9,
                        1 - 2:5:7, 2 - 1:5:3, 3 - 2:4, 4 - 3:5:6:8:9,
                        5 - 1:2:4:6:7, 6 - 7:5:4:9, 7 - 1:5:6,
                        8 - 4:9, 9 - 6:4:8)
    domains <- list(`1` = c(1,3,9), `2` = c(5,6,7,8), `3` = c(2,4,6,7,8,9),
                    `4` = c(1,3,9), `5` = c(2,4,8,9))
    subgraph_isomorphisms(pattern, target)
    subgraph_isomorphisms(pattern, target, induced = TRUE)
    subgraph_isomorphisms(pattern, target, domains = domains)

    # Directed LAD example
    pattern <- make_graph(~ 1:2:3, 1 -+ 2:3)
    dring <- make_ring(10, directed = TRUE)
    subgraph_isomorphic(pattern, dring)

[Package igraph version 1.1.2 Index]