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Perform a breadth-first search on a graph and convert it into a tree or forest by replicating vertices that were found more than once.

## Usage

unfold_tree(graph, mode = c("all", "out", "in", "total"), roots)

## Arguments

graph

The input graph, it can be either directed or undirected.

mode

Character string, defined the types of the paths used for the breadth-first search. “out” follows the outgoing, “in” the incoming edges, “all” and “total” both of them. This argument is ignored for undirected graphs.

roots

A vector giving the vertices from which the breadth-first search is performed. Typically it contains one vertex per component.

## Value

A list with two components:

tree

The result, an igraph object, a tree or a forest.

vertex_index

A numeric vector, it gives a mapping from the vertices of the new graph to the vertices of the old graph.

## Details

A forest is a graph, whose components are trees.

The roots vector can be calculated by simply doing a topological sort in all components of the graph, see the examples below.

## See also

Other structural.properties: bfs(), component_distribution(), connect(), constraint(), coreness(), degree(), dfs(), distance_table(), edge_density(), feedback_arc_set(), girth(), is_acyclic(), is_dag(), is_matching(), k_shortest_paths(), knn(), reciprocity(), subcomponent(), subgraph(), topo_sort(), transitivity(), which_multiple(), which_mutual()

## Author

Gabor Csardi csardi.gabor@gmail.com

## Examples


g <- make_tree(10) %du% make_tree(10)
V(g)$id <- seq_len(vcount(g)) - 1 roots <- sapply(decompose(g), function(x) { V(x)$id[topo_sort(x)[1] + 1]
})
tree <- unfold_tree(g, roots = roots)