使用R igraph和dplyr（purrr）有條件地在列表列圖中設置邊屬性

Question

我有一個數據框，其中包含一系列列列格式的igraph對象。 我想有條件地設置邊緣顏色屬性。

我已經包含了dput包含三個圖形的實際數據幀（非常大，數千個圖形）的示例版本的dput輸出。 它仍然很長，因此我將其放在本文的底部，我將解釋到目前為止我嘗試過的一些想法。

首先嘗試使用purrr包對mutate和map進行多次使用。

sampleColored <- sampleGraphs %>% mutate(map(graph, function(x) 
E(x)[weights == 0]$color = "blue")) %>% mutate(map(graph, function(x)
    E(x)[weights < 0]$color = "red"))  %>% mutate(map(graph, function(x)
    E(x)[weights > 0]$color = "green"))

沒有錯誤信息，但是命令

 shortPlots <- sampleColored %>%
 mutate(plots = map(graph, function(x) plot(x, layout=layout.circle,
     vertex.size=20,                                                          
     edge.curved=TRUE)))

產生了漂亮的圖形，所有邊緣均為灰色。

同樣，在第二次嘗試中，我創建了edgeColor函數並使用了單個map調用。

edgecolor <- function(x) {
E(x)[weights == 0]$color <- "blue"
E(x)[weights < 0]$color <- "red"
E(x)[weights > 0]$color <- "green"
return(E(x))
}
sampleColored <- sampleGraphs %>% mutate(map(graph, function(x) edgecolor(x)))

沒有錯誤和灰色邊緣。 刪除mutate命令會產生錯誤消息：

Error in as.numeric(n): cannot coerce type 'closure' to vector of type 'double'

我相信這是可能的，而且我只是不了解要使用正確的語法。 任何建議將不勝感激。 感謝您的光臨。

這是sampleGraph dput ：

sampleGraphs <- structure(list(ID = 997:1000, graph = list(structure(list(5, 
TRUE, c(0, 1, 2, 0, 3, 4, 1, 2, 4, 3, 0, 4, 2, 3, 0, 1, 3, 
1, 4, 2), c(1, 0, 0, 4, 1, 1, 4, 3, 0, 2, 3, 2, 1, 4, 2, 
3, 0, 2, 3, 4), c(0, 14, 10, 3, 1, 17, 15, 6, 2, 12, 7, 19, 
16, 4, 9, 13, 8, 5, 11, 18), c(1, 2, 16, 8, 0, 12, 4, 5, 
14, 17, 9, 11, 10, 15, 7, 18, 3, 6, 19, 13), c(0, 4, 8, 12, 
16, 20), c(0, 4, 8, 12, 16, 20), list(c(1, 0, 1), structure(list(), .Names = character(0)), 
    structure(list(name = c("3", "0", "2", "4", "1")), .Names = "name"), 
    structure(list(weights = c(3L, -4L, 4L, -3L, 43L, 8L, 
    4L, 14L, 1L, 55L, 2L, 22L, 26L, 64L, 9L, 2L, 13L, -12L, 
    25L, 16L)), .Names = "weights")), <environment>), class = "igraph"), 
structure(list(5, TRUE, c(0, 1, 2, 2, 1, 3, 1, 3, 4, 3, 3, 
0, 4, 0, 4, 4, 2, 1, 2, 0), c(3, 3, 4, 0, 2, 1, 4, 2, 0, 
4, 0, 2, 1, 4, 2, 3, 3, 0, 1, 1), c(19, 11, 0, 13, 17, 4, 
1, 6, 3, 18, 16, 2, 10, 5, 7, 9, 8, 12, 14, 15), c(17, 3, 
10, 8, 19, 18, 5, 12, 11, 4, 7, 14, 0, 1, 16, 15, 13, 6, 
2, 9), c(0, 4, 8, 12, 16, 20), c(0, 4, 8, 12, 16, 20), list(
    c(1, 0, 1), structure(list(), .Names = character(0)), 
    structure(list(name = c("2", "0", "1", "3", "4")), .Names = "name"), 
    structure(list(weights = c(4L, -4L, 25L, 22L, 4L, 3L, 
    2L, -3L, 55L, 2L, 9L, 16L, 43L, 14L, 64L, 13L, 1L, -12L, 
    8L, 26L)), .Names = "weights")), <environment>), class = "igraph"), 
structure(list(5, TRUE, c(0, 1, 2, 3, 4, 0, 1, 2, 1, 3, 1, 
3, 2, 4, 2, 4, 0, 0, 3, 4), c(1, 4, 3, 4, 0, 4, 2, 0, 0, 
2, 3, 1, 4, 1, 1, 2, 3, 2, 0, 3), c(0, 17, 16, 5, 8, 6, 10, 
1, 7, 14, 2, 12, 18, 11, 9, 3, 4, 13, 15, 19), c(8, 7, 18, 
4, 0, 14, 11, 13, 17, 6, 9, 15, 16, 10, 2, 19, 5, 1, 12, 
3), c(0, 4, 8, 12, 16, 20), c(0, 4, 8, 12, 16, 20), list(
    c(1, 0, 1), structure(list(), .Names = character(0)), 
    structure(list(name = c("4", "0", "3", "2", "1")), .Names = "name"), 
    structure(list(weights = c(43L, 4L, 9L, 16L, 25L, 64L, 
    -4L, 2L, 2L, 4L, -11L, 26L, -3L, 8L, 3L, 1L, 55L, 13L, 
    14L, 22L)), .Names = "weights")), <environment>), class = "igraph"), 
structure(list(5, TRUE, c(0, 1, 2, 3, 4, 1, 3, 2, 4, 0, 1, 
3, 2, 4, 0, 0, 2, 4, 1, 3), c(4, 4, 4, 1, 2, 0, 2, 3, 0, 
3, 2, 0, 1, 1, 2, 1, 0, 3, 3, 4), c(15, 14, 9, 0, 5, 10, 
18, 1, 16, 12, 7, 2, 11, 3, 6, 19, 8, 13, 4, 17), c(5, 16, 
11, 8, 15, 12, 3, 13, 14, 10, 6, 4, 9, 18, 7, 17, 0, 1, 2, 
19), c(0, 4, 8, 12, 16, 20), c(0, 4, 8, 12, 16, 20), list(
    c(1, 0, 1), structure(list(), .Names = character(0)), 
    structure(list(name = c("1", "4", "0", "2", "3")), .Names = "name"), 
    structure(list(weights = c(1L, 13L, -4L, 14L, 3L, 64L, 
    26L, -11L, -3L, 22L, 43L, 16L, 2L, 2L, 8L, 25L, 4L, 8L, 
    55L, 4L)), .Names = "weights")), <environment>), class = "igraph"))),     class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -4L), .Names = c("ID", 
"graph"))

Answer 1

使用set_edge_attr而不是igraph的慣用E()邊緣函數會set_edge_attr幫助。 我不得不將sampleGraph列表修改為一個簡單的圖形列表，將其升級到igraph的較新版本，但這igraph ：

graphs <- sampleGraphs$graph
graphs <- lapply(graphs, function(x) upgrade_graph(x)) #making a simple list of graphs

edgecolor <- function(x) {
  E(x)[weights == 0]$color <- "blue"
  E(x)[weights < 0]$color <- "red"
  E(x)[weights > 0]$color <- "green"
  return(E(x)$color)
} #The function now returns a list of colors conditional on statements

#Pass the function to the "values" argument of "set_edge_attr"

graphs_colored <- graphs %>% map(., function(x) set_edge_attr(x, "color", value = edgecolor(x)))

par(mfrow = c(2,2), mar = c(0,0,0,0))
shortPlots <- graphs_colored %>%
 map(., function(x) plot(x, 
                         layout=layout.circle,
                         vertex.size=20,                                                          
                         edge.curved=TRUE,
                         edge.arrow.size = 0.5))

Answer 2

得到它了！ 感謝@paqmo的建議。 我需要使用mutate重新定義graph list-column變量。

edgecolor <- function(x) {
  E(x)[weights == 0]$color <- "#FF000000"
  E(x)[weights < 0]$color <- "red"
  E(x)[weights > 0]$color <- "green"
  return(E(x)$color)
}
sampleColored <- sampleGraphs %>% mutate(graph = map(graph, function(x) 
  set_edge_attr(x, "color", value = edgecolor(x))))

par(mfrow = c(2,2), mar = c(0,0,0,0))
samplePlots <- sampleColored %>%
     mutate(plots = map(graph, function(x) plot(x, layout=layout.circle,
       vertex.size=20,                                                          
       edge.curved=TRUE)))

生成與@paqmo相同的圖像。