Recursively looping through neighbors with an igraph object

Question

Appreciate any pointers to the below output that want. I know I need to do some form of recursion but sure how to do that exactly.

I have the following code

>> start of code
# BOM data
library("dplyr")
library(igraph)

text1 <- ("
          matnr,comp
          FG1,SA1
          FG1,SA2
          SA1,SA3
          SA1,SA4
          SA1,SA5
          SA5,SA6
          FG2,SA1
          FG2,SA8
          SA8,SA9
          SA9,SA10
          SA9,SA11")

df1 <- read.table(textConnection(text1),  header = TRUE, stringsAsFactors=FALSE, strip.white = TRUE, sep=",")
head(df1)
net <- graph_from_data_frame(df1)
net
neighbors_FG1 <- neighbors(net, v=c("FG1"), mode=c("out"))
neighbors_FG1

neighbors_FG2 <- neighbors(net, v=c("FG2"), mode=c("out"))
neighbors_FG2            

neighbors_SA1 <- neighbors(net, v=c("SA1"), mode=c("out"))
neighbors_SA1

>> end of code

I want to be able to produce a data frame like below. I would think that this will need some sort of recursion and I would like to get help with this. If you can even help me with how I can get to the output below, that will be great.

FG,level,material,Comp  
FG1,1,FG1,SA1  
FG1,1,FG1,SA2  
FG1,2,SA1,SA3  
FG1,2,SA1,SA4  
FG1,2,SA1,SA5  
FG1,3,SA5,SA6  
FG2,1,FG2,SA1  
FG2,1,FG2,SA8  
FG2,2,SA8,SA9  

Answer 1

Here is an igraph option

lst <- lapply(
  names(V(net))[degree(net, mode = "in") == 0],
  function(x) {
    d <- Filter(
      is.finite,
      setNames(
        c(distances(net, x, mode = "out") + 1),
        names(V(net))
      )
    )
    cbind(
      FG = x,
      merge(
        setNames(get.data.frame(
          induced_subgraph(
            net,
            names(d)
          )
        ), c("matnr", "comp")),
        setNames(
          rev(stack(d)),
          c("matnr", "lvl")
        )
      )
    )
  }
)

res <- `row.names<-`(
  subset(
    do.call(rbind, lst),
    ave(seq_along(matnr), matnr, comp, lvl, FUN = seq_along) == 1
  ), NULL
)

which gives

> res
    FG matnr comp lvl
1  FG1   FG1  SA1   1
2  FG1   FG1  SA2   1
3  FG1   SA1  SA3   2
4  FG1   SA1  SA4   2
5  FG1   SA1  SA5   2
6  FG1   SA5  SA6   3
7  FG2   FG2  SA1   1
8  FG2   FG2  SA8   1
9  FG2   SA8  SA9   2
10 FG2   SA9 SA10   3
11 FG2   SA9 SA11   3

Answer 2

I use tidyverse, igraph and tidygraph to solve this question:

1. Converts the type of net so that it can be manipulated by the TidyGraph package

gr <- as_tbl_graph(net)

2. Get a vector that contains the correspondence between nodes' names and their order.

name_vector <- gr %>%
  activate(nodes) %>% 
  as_tibble() %>%
  as_vector()

3. Define the node to strat the search

start_node = 1 # The first node is FG1

4. Generate the variables you want:

temp <- gr %>%
  activate(nodes) %>%
  mutate(
    # Get the nodes from which each node is visited in a breath first search
    material = bfs_parent(root = start_node), 
    # Get the succession in which the nodes are visited in a depth first search
    level = bfs_dist(root = start_node)) %>%
  as_tibble() %>%
  drop_na() %>%
  rename(Comp = name)

5. Replace the order with a name

temp <- temp %>%
  mutate(FG = name_vector[start_node],
         material = name_vector[material])

And that's the result:

> temp %>% arrange(level)
# A tibble: 6 x 4
  Comp  material level FG   
  <chr> <chr>    <int> <chr>
1 SA1   FG1          1 FG1  
2 SA2   FG1          1 FG1  
3 SA5   SA1          2 FG1  
4 SA3   SA1          2 FG1  
5 SA4   SA1          2 FG1  
6 SA6   SA5          3 FG1    

Based on the code above, We found all the cases where start_node = 1.
You can use loops to redefine the start_node and combine these results together.