R中的函数返回网络中的祖先和孩子

Question

我想在R中创建一个函数“f”，它在条目中包含个人和个人之间的边缘data.frame（例如称为A2），并返回另一个只有A2的“祖先”和“孩子”以及祖先和孩子的祖先的数据框架！

为说明我的复杂的问题：

library(visNetwork) 
nodes <- data.frame(id = c(paste0("A",1:5),paste0("B",1:3)), 
       label = c(paste0("A",1:5),paste0("B",1:3))) 
edges <- data.frame(from = c("A1","A1","A2","A3","A4","B1","B2"), 
       to = c("A2","A3","A4","A4","A5","B3","B3")) 
visNetwork(nodes, edges) %>% 
    visNodes(font = list(size=45)) %>% 
    visHierarchicalLayout(direction = "LR", levelSeparation = 500) 

在这个例子中，包含data.frame 2个不同独立的网络：1个网络与 “A” S和其他与 “B” S 。

我想实现函数f（数据=边缘，逐张=“A2”），它返回其包含涉及的“A” S网络data.frame边缘的所有行一个data.frame：

F（边，“A2”）将返回该提取物data.frame边缘

head(f(edges,"A2")) 
# from to 
#1 A1 A2 
#2 A1 A3 
#3 A2 A4 
#4 A3 A4 
#5 A4 A5 

我希望这是很清楚的，你来帮我。

非常感谢！

Answer 1

我写了一个简单的算法来查找所有链接到个人的家庭（我相信它可以改进）。像@romles建议你可以用像igraph这样的一些R包来做同样的事情。然而，在这种情况下，我的函数看起来更像igraph选项。

edges <- data.frame(from = c("A1","A1","A2","A3","A4","B1","B2"), 
        to = c("A2","A3","A4","A4","A5","B3","B3"), 
        stringsAsFactors = FALSE) 
f <- function(data, indiv){ 
    children_ancestors <- function(indiv){ 
     # Find children and ancestors of an indiv 
     c(data[data[,"from"]==indiv,"to"],data[data[,"to"]==indiv,"from"]) 
    } 
    family <- indiv 
    new_people <- children_ancestors(indiv) # New people to inspect 
    while(length(diff_new_p <- setdiff(new_people,family)) > 0){ 
     # if the new people aren't yet in the family : 
     family <- c(family, diff_new_p) 
     new_people <- unlist(sapply(diff_new_p, children_ancestors)) 
     new_people <- unique(new_people) 
    } 
    data[(data[,1] %in% family) | (data[,2] %in% family),] 
} 

f(edges, "A2")给出了预期的结果。与igraph相比：

library(igraph) 
library(microbenchmark) 
edges2 <- graph_from_data_frame(edges, directed = FALSE) 
microbenchmark(simple_function = f(edges,"A2"), 
       igraph_option = as_data_frame(subgraph.edges(edges2, subcomponent(edges2, 'A2', 'in'))) 
       ) 
#Unit: microseconds 
#   expr  min  lq  mean median  uq  max neval 
# simple_function 874.411 968.323 1206.037 1123.515 1325.075 2957.931 100 
# igraph_option 1239.896 1451.364 1802.341 1721.227 1984.380 3907.089 100 

Answer 2

这个工作对我来说：

library(igraph) 
g <- graph_from_literal(A1--A2, A1--A3, A2--A4, A3--A4, A4--A5, B1--B3, B2--B3) 
sg_a2 <- subcomponent(g, 'A2', 'in') 
as_data_frame(subgraph.edges(g, sg_a2)) 

它提供：

# from to 
#1 A1 A2 
#2 A1 A3 
#3 A2 A4 
#4 A3 A4 
#5 A4 A5 

Answer 3

你可以尝试和过滤只有连接到A2的节点（即距离不等于Inf

library(tidygraph) 
edges <- data.frame(from = c("A1","A1","A2","A3","A4","B1","B2"), 
        to = c("A2","A3","A4","A4","A5","B3","B3")) 
as_tbl_graph(edges) %>% 
    filter(is.finite(node_distance_to(name=="A2", mode="all"))) 

哪给出

# A tbl_graph: 5 nodes and 5 edges 
# 
# A directed acyclic simple graph with 1 component 
# 
# Node Data: 5 x 1 (active) 
    name 
    <chr> 
1 A1 
2 A2 
3 A3 
4 A4 
5 A5 
# 
# Edge Data: 5 x 2 
    from to 
    <int> <int> 
1  1  2 
2  1  3 
3  2  4 
# ... with 2 more rows