Depth First Search

Description

This function implements algorithm 4.2.1 of Gross and Yellen. The input is a graph and a node to start from. It returns a standard vertex labeling of graph. This is a vector with elements corresponding to the nodes of graph and with values that correspond to point in the depth first search the node is visited.

Usage

DFS(object, node, checkConn=TRUE)

Arguments

Details

This function implements algorithm 4.2.1 of Gross and Yellen. Specific details are given there.

It requires that the graph be connected. By default, this is checked, but since the checking can be expensive it is optional.

A faster and mostly likely better implementation of depth first searching is given by dfs in the RBGL package.

Value

A vector with names given by the nodes of graph whose values are 0 to one less than the number of nodes. These indices indicate the point at which the node will be visited.

Author(s)

R. Gentleman

References

Graph Theory and its Applications, J. Gross and J. Yellen.

See Also

boundary

Examples

  RNGkind("Mersenne-Twister")
  set.seed(123)
  g1 <- randomGraph(letters[1:10], 1:4, p=.3)
  RNGkind()
  DFS(g1, "a")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(graph)
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/graph/DFS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: DFS
> ### Title: Depth First Search
> ### Aliases: DFS DFS,graph,character-method
> ### Keywords: manip
> 
> ### ** Examples
> 
>   RNGkind("Mersenne-Twister")
>   set.seed(123)
>   g1 <- randomGraph(letters[1:10], 1:4, p=.3)
>   RNGkind()
[1] "Mersenne-Twister" "Inversion"       
>   DFS(g1, "a")
a b c d e f g h i j 
0 1 6 2 3 4 8 5 9 7 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>