Question

我以这种方式使用ggdendro创建树状图：

library(igraph)
library(RColorBrewer)
library(GGally)
library(ggplot2)
library(plotrix)
library(extrafont)
library(ggdendro)

# load dataset
net <- read.graph("./dataset/lesmiserables.gml", format = c("gml"))
deg <- igraph::degree(net, mode = "all")

# find communities
girvNew <- cluster_edge_betweenness(net)

girvNew_sizesComm <- sizes(girvNew)
girvNew_numComm <- length(girvNew_sizesComm)

# colors
colorsRainbow <- rainbow(max(membership(girvNew)), alpha = 0.6)

x11()
plot(net,
     vertex.size = plotrix::rescale(deg, c(5, 16)),
     vertex.color = colorsRainbow[membership(girvNew)],
     vertex.frame.color = NA,
     vertex.label = NA,
     vertex.size = 10,
     edge.color = "#d8d8d8",
     layout = layout.fruchterman.reingold,
     main = "Detected communities")

# find dendrogram
girvNew_den <- as.dendrogram(girvNew)

#convert cluster object to use with ggplot
girvNew_dendrogram <- dendro_data(girvNew_den, type = "rectangle") 

x11()
ggdendrogram(girvNew_dendrogram, 
             rotate = TRUE, 
             labels = TRUE,
             segments = TRUE,
             leaf_labels = TRUE, 
             theme_dendro = FALSE)

我得到：

我的网络是：

> dput(net)
structure(list(77, FALSE, c(1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 11, 
11, 11, 11, 12, 13, 14, 15, 17, 18, 18, 19, 19, 19, 20, 20, 20, 
20, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 
23, 23, 23, 23, 23, 24, 24, 25, 25, 25, 26, 26, 26, 26, 27, 27, 
27, 27, 27, 28, 28, 29, 29, 29, 30, 31, 31, 31, 31, 32, 33, 33, 
34, 34, 35, 35, 35, 36, 36, 36, 36, 37, 37, 37, 37, 37, 38, 38, 
38, 38, 38, 38, 39, 40, 41, 41, 42, 42, 42, 43, 43, 43, 44, 44, 
45, 47, 48, 48, 48, 48, 49, 49, 50, 50, 51, 51, 51, 52, 52, 53, 
54, 54, 54, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 56, 56, 57, 
57, 57, 58, 58, 58, 58, 58, 59, 59, 59, 59, 60, 60, 60, 61, 61, 
61, 61, 61, 61, 62, 62, 62, 62, 62, 62, 62, 62, 63, 63, 63, 63, 
63, 63, 63, 63, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 65, 65, 
65, 65, 65, 65, 65, 65, 65, 65, 66, 66, 66, 66, 66, 66, 66, 66, 
66, 67, 68, 68, 68, 68, 68, 68, 69, 69, 69, 69, 69, 69, 69, 70, 
70, 70, 70, 70, 70, 70, 70, 71, 71, 71, 71, 71, 71, 71, 71, 72, 
72, 72, 73, 74, 74, 75, 75, 75, 75, 75, 75, 75, 76, 76, 76, 76, 
76, 76, 76), c(0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 10, 3, 2, 0, 11, 
11, 11, 11, 16, 16, 17, 16, 17, 18, 16, 17, 18, 19, 16, 17, 18, 
19, 20, 16, 17, 18, 19, 20, 21, 16, 17, 18, 19, 20, 21, 22, 12, 
11, 23, 11, 24, 23, 11, 24, 11, 16, 25, 11, 23, 25, 24, 26, 11, 
27, 23, 27, 11, 23, 30, 11, 23, 27, 11, 11, 27, 11, 29, 11, 34, 
29, 34, 35, 11, 29, 34, 35, 36, 11, 29, 34, 35, 36, 37, 11, 29, 
25, 25, 24, 25, 41, 25, 24, 11, 26, 27, 28, 11, 28, 46, 47, 25, 
27, 11, 26, 11, 49, 24, 49, 26, 11, 51, 39, 51, 51, 49, 26, 51, 
49, 39, 54, 26, 11, 16, 25, 41, 48, 49, 55, 55, 41, 48, 55, 48, 
27, 57, 11, 58, 55, 48, 57, 48, 58, 59, 48, 58, 60, 59, 57, 55, 
55, 58, 59, 48, 57, 41, 61, 60, 59, 48, 62, 57, 58, 61, 60, 55, 
55, 62, 48, 63, 58, 61, 60, 59, 57, 11, 63, 64, 48, 62, 58, 61, 
60, 59, 57, 55, 64, 58, 59, 62, 65, 48, 63, 61, 60, 57, 25, 11, 
24, 27, 48, 41, 25, 68, 11, 24, 27, 48, 41, 25, 69, 68, 11, 24, 
27, 41, 58, 27, 69, 68, 70, 11, 48, 41, 25, 26, 27, 11, 48, 48, 
73, 69, 68, 25, 48, 41, 70, 71, 64, 65, 66, 63, 62, 48, 58), 
    c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 13, 12, 11, 10, 14, 15, 16, 
    17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 
    32, 33, 34, 35, 36, 37, 38, 47, 46, 39, 40, 41, 42, 43, 44, 
    45, 49, 48, 52, 51, 50, 54, 55, 53, 56, 57, 58, 60, 59, 61, 
    62, 63, 66, 64, 65, 67, 69, 70, 71, 68, 72, 73, 74, 75, 76, 
    77, 79, 78, 82, 83, 80, 81, 87, 88, 84, 85, 86, 93, 94, 89, 
    90, 91, 92, 95, 96, 97, 98, 101, 100, 99, 102, 103, 104, 
    106, 105, 107, 108, 112, 110, 111, 109, 114, 113, 116, 115, 
    119, 118, 117, 121, 120, 122, 125, 124, 123, 131, 132, 133, 
    130, 128, 134, 135, 127, 126, 129, 136, 137, 139, 140, 138, 
    145, 143, 142, 141, 144, 148, 147, 149, 146, 150, 151, 152, 
    153, 158, 157, 154, 156, 155, 164, 162, 159, 163, 160, 161, 
    166, 165, 168, 174, 170, 171, 167, 173, 172, 169, 184, 177, 
    175, 183, 179, 182, 181, 180, 176, 178, 187, 194, 193, 189, 
    192, 191, 190, 188, 185, 186, 200, 196, 197, 203, 202, 198, 
    201, 195, 199, 204, 206, 207, 205, 208, 210, 209, 213, 214, 
    211, 215, 217, 216, 212, 221, 222, 218, 223, 224, 225, 220, 
    219, 230, 233, 226, 232, 231, 228, 227, 229, 236, 234, 235, 
    237, 238, 239, 242, 244, 243, 241, 240, 245, 246, 252, 253, 
    251, 250, 247, 248, 249), c(0, 1, 2, 4, 5, 6, 7, 8, 9, 13, 
    3, 12, 11, 10, 14, 15, 16, 17, 47, 49, 52, 54, 57, 62, 66, 
    69, 72, 73, 75, 77, 82, 87, 93, 102, 106, 112, 114, 119, 
    131, 145, 184, 206, 213, 221, 230, 236, 46, 18, 19, 21, 24, 
    28, 33, 39, 55, 132, 20, 22, 25, 29, 34, 40, 23, 26, 30, 
    35, 41, 27, 31, 36, 42, 32, 37, 43, 38, 44, 45, 48, 51, 58, 
    64, 67, 70, 50, 53, 60, 97, 101, 116, 207, 214, 222, 56, 
    59, 95, 96, 98, 100, 110, 133, 205, 211, 218, 233, 242, 61, 
    103, 113, 118, 125, 130, 234, 63, 65, 71, 74, 104, 111, 143, 
    208, 215, 223, 226, 235, 105, 107, 76, 79, 83, 88, 94, 68, 
    78, 80, 84, 89, 81, 85, 90, 86, 91, 92, 121, 128, 99, 134, 
    139, 164, 210, 217, 224, 232, 244, 108, 109, 135, 140, 142, 
    148, 150, 153, 162, 168, 177, 187, 200, 209, 216, 231, 237, 
    238, 243, 252, 115, 117, 124, 127, 136, 120, 122, 123, 126, 
    129, 137, 138, 141, 147, 158, 159, 174, 175, 194, 144, 149, 
    157, 163, 170, 183, 193, 204, 146, 151, 154, 160, 171, 179, 
    189, 196, 225, 253, 152, 156, 161, 167, 182, 192, 197, 155, 
    166, 173, 181, 191, 203, 165, 172, 180, 190, 202, 169, 176, 
    188, 198, 251, 178, 185, 201, 250, 186, 195, 247, 199, 248, 
    249, 212, 220, 228, 241, 219, 227, 240, 229, 245, 246, 239
    ), c(0, 0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 10, 14, 15, 16, 17, 
    18, 18, 19, 21, 24, 28, 33, 39, 48, 50, 53, 57, 62, 64, 67, 
    68, 72, 73, 75, 77, 80, 84, 89, 95, 96, 97, 99, 102, 105, 
    107, 108, 108, 109, 113, 115, 117, 120, 122, 123, 126, 136, 
    138, 141, 146, 150, 153, 159, 167, 175, 185, 195, 204, 205, 
    211, 218, 226, 234, 237, 238, 240, 247, 254), c(0, 10, 10, 
    12, 13, 13, 13, 13, 13, 13, 13, 14, 46, 47, 47, 47, 47, 56, 
    62, 67, 71, 74, 76, 77, 83, 92, 105, 112, 124, 126, 131, 
    132, 132, 132, 132, 136, 139, 141, 142, 142, 144, 144, 153, 
    153, 153, 153, 153, 154, 155, 173, 178, 178, 182, 182, 182, 
    183, 192, 192, 200, 210, 217, 223, 228, 233, 237, 240, 242, 
    243, 243, 247, 250, 252, 253, 253, 254, 254, 254, 254), list(
        c(1, 0, 1), structure(list(), .Names = character(0)), 
        structure(list(id = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
        11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 
        25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 
        39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 
        53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 
        67, 68, 69, 70, 71, 72, 73, 74, 75, 76), label = c("Myriel", 
        "Napoleon", "MlleBaptistine", "MmeMagloire", "CountessDeLo", 
        "Geborand", "Champtercier", "Cravatte", "Count", "OldMan", 
        "Labarre", "Valjean", "Marguerite", "MmeDeR", "Isabeau", 
        "Gervais", "Tholomyes", "Listolier", "Fameuil", "Blacheville", 
        "Favourite", "Dahlia", "Zephine", "Fantine", "MmeThenardier", 
        "Thenardier", "Cosette", "Javert", "Fauchelevent", "Bamatabois", 
        "Perpetue", "Simplice", "Scaufflaire", "Woman1", "Judge", 
        "Champmathieu", "Brevet", "Chenildieu", "Cochepaille", 
        "Pontmercy", "Boulatruelle", "Eponine", "Anzelma", "Woman2", 
        "MotherInnocent", "Gribier", "Jondrette", "MmeBurgon", 
        "Gavroche", "Gillenormand", "Magnon", "MlleGillenormand", 
        "MmePontmercy", "MlleVaubois", "LtGillenormand", "Marius", 
        "BaronessT", "Mabeuf", "Enjolras", "Combeferre", "Prouvaire", 
        "Feuilly", "Courfeyrac", "Bahorel", "Bossuet", "Joly", 
        "Grantaire", "MotherPlutarch", "Gueulemer", "Babet", 
        "Claquesous", "Montparnasse", "Toussaint", "Child1", 
        "Child2", "Brujon", "MmeHucheloup"), maincharacter = c(0, 
        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0)), .Names = c("id", "label", "maincharacter"
        )), structure(list(value = c(1, 8, 10, 6, 1, 1, 1, 1, 
        2, 1, 1, 3, 3, 5, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 3, 3, 
        3, 4, 3, 3, 3, 3, 5, 3, 3, 3, 3, 4, 4, 3, 3, 3, 3, 4, 
        4, 4, 2, 9, 2, 7, 13, 1, 12, 4, 31, 1, 1, 17, 5, 5, 1, 
        1, 8, 1, 1, 1, 2, 1, 2, 3, 2, 1, 1, 2, 1, 3, 2, 3, 3, 
        2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 
        2, 3, 2, 2, 1, 3, 1, 1, 3, 1, 2, 1, 2, 1, 1, 1, 3, 2, 
        1, 1, 9, 2, 2, 1, 1, 1, 2, 1, 1, 6, 12, 1, 1, 21, 19, 
        1, 2, 5, 4, 1, 1, 1, 1, 1, 7, 7, 6, 1, 4, 15, 5, 6, 2, 
        1, 4, 2, 2, 6, 2, 5, 1, 1, 9, 17, 13, 7, 2, 1, 6, 3, 
        5, 5, 6, 2, 4, 3, 2, 1, 5, 12, 5, 4, 10, 6, 2, 9, 1, 
        1, 5, 7, 3, 5, 5, 5, 2, 5, 1, 2, 3, 3, 1, 2, 2, 1, 1, 
        1, 1, 3, 5, 1, 1, 1, 1, 1, 6, 6, 1, 1, 2, 1, 1, 4, 4, 
        4, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 
        2, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)), .Names = "value")), 
    <environment>), class = "igraph")

我希望垂直轴上有网络节点的名称，并且群集线与使用cluster_edge_betweenness函数计算的社区的颜色相同。

如果它们色彩丰富，那真的无关紧要：

节点（标签）或
群集线或
每个群集的背景。

重要的是，我可以根据颜色区分聚类，就像我在第一个图中所做的那样（使用圆形节点）。

我该怎么办？我搜索了互联网，但我无法解决。谢谢

我试图遵循这两条道路：

跟随this post
使用dendextend package

我从一开始就遇到了两个问题。

（1）在回复中，df是一个数据框，而我有一个列表（net），我不知道如何在数据框中正确转换我的网络，如示例中的那样。无论如何，如果我尝试（只是为了玩）rownames(df) <- V(net)$label我得到

row.names<-.data.frame（*tmp*，值=值）中的错误：长度＆＃39; row.names＆＃39;不可接受的

非常正确。但绘制的结果如下：

它不使用net网络节点的标签，而是df网络节点的标签。在我看来非常奇怪。

（2）这就是我所做的：

library(igraph)
library(GGally)
library(ggplot2)
library(ggdendro)
library(dendextend)
library(dendextendRcpp)
library(zoo)

# load dataset
net <- read.graph("./dataset/lesmiserables.gml", format = c("gml"))
deg <- igraph::degree(net, mode = "all")

comm <- fastgreedy.community(net)

comm_sizesComm <- sizes(comm) 
comm_numComm <- length(comm_sizesComm)
comm_modularity <- modularity(comm)

# plot communities
colorsRainbow <- rainbow(max(membership(comm)), alpha = 0.6)
pdf(file = "./output/prova_comm2.pdf")
plot(net,
     vertex.size = plotrix::rescale(deg, c(5, 16)),
     vertex.color = colorsRainbow[membership(comm)],
     vertex.frame.color = NA,
     vertex.label.color = "black",
     vertex.label.cex = 0.5,
     vertex.size = 10,
     edge.color = "#d8d8d8",
     layout = layout.fruchterman.reingold,
     edge.curved = FALSE)
dev.off()

# create dendrogram
dend <- as.dendrogram(comm)

cut <- comm_numComm

# change labels
dend <- dend %>% set("labels", V(net)$label) # change label
dend <- dend %>% set("labels_col", "black") # change color 
dend <- dend %>% set("labels_cex", .5) # change size

# color label based on communities
colorsRainbow <- rainbow(max(membership(comm)), alpha = 1)
dend <- dend %>% set("labels_col", value = colorsRainbow, k = cut) 

# plot dendrogram
pdf(file = "./output/prova_dend2.pdf")
plot(dend, 
     horiz = TRUE,
     main = "Dendrogram")
dev.off()

我成功地改变了标签并为它们着色。但两种图形之间的颜色不匹配。我不明白它是否是情节或树状结构的问题。

说明：在第一个图（带有由点表示的节点的图）中，我在蓝色社区中有节点{Perpetual，Fantine， Anzelma ，Simplice，...}。在黄色社区中有{ Woman2 ，Marius，Magnon，珂赛特，......}。

如果现在我去看第二个图（树形图），我看到 Woman2 和 Anzelma 节点位于两个不同的社区中。这似乎是个大问题，我不知道如何开始解决。

（3）我也试过了：

ggd1 <- as.ggdend(dend)
ggplot(ggd1)

问题与（2）相同：社区不匹配。

我创建了这个简单的图表：

> dput(net)
structure(list(16, FALSE, c(1, 2, 3, 2, 3, 3, 4, 5, 5, 7, 7, 
9, 8, 10, 9, 11, 11, 14, 15, 15, 15, 12, 14), c(0, 0, 0, 1, 2, 
1, 3, 3, 4, 3, 6, 6, 7, 8, 8, 8, 10, 11, 14, 13, 12, 3, 1), c(0, 
1, 3, 2, 5, 4, 6, 7, 8, 9, 10, 12, 11, 14, 13, 15, 16, 21, 22, 
17, 20, 19, 18), c(0, 1, 2, 3, 5, 22, 4, 6, 7, 9, 21, 8, 10, 
11, 12, 14, 13, 15, 16, 17, 20, 19, 18), c(0, 0, 1, 3, 6, 7, 
9, 9, 11, 12, 14, 15, 17, 18, 18, 20, 23), c(0, 3, 6, 7, 11, 
12, 12, 14, 15, 18, 18, 19, 20, 21, 22, 23, 23), list(c(1, 0, 
1), structure(list(), .Names = character(0)), structure(list(
    id = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
    15), label = c("A", "B", "C", "D", "E", "F", "G", "H", "I", 
    "L", "M", "N", "O", "P", "Q", "R")), .Names = c("id", "label"
)), list()), <environment>), class = "igraph")

然后我找到社区和树状图：

# calculate degree
deg <- igraph::degree(net, mode = "all")

# find communities
com <- cluster_edge_betweenness(net) 
## or use 
# com <- fastgreedy.community(net)

# details on communities
com_sizesCom <- sizes(com) 
com_numCom <- length(com_sizesCom)

# create dendrogram
dend <- as.dendrogram(com)
labels(dend) <- V(net)$label[order.dendrogram(dend)]

k <- max(membership(com))
colorsRainbow <- rainbow(k, alpha = 1)

set.seed(23420)
colorsRainbow <- rainbow(max(membership(com)))
colorsRainbow <- sample(colorsRainbow)
dend <- dend %>% set("labels_col", value = colorsRainbow, k = k)
dend <- dend %>% set("branches_k_color", value = colorsRainbow, k = k)
dend <- dend %>% set("labels_cex", 1)

我得到：

因此，颜色不正确。

整个更新代码。现在蓝色和绿色都会切换。

 library(igraph)
 library(dendextend)
 library(colorspace)

 net <- upgrade_graph(net)
 # dput(net)

 # calculate degree
 deg <- igraph::degree(net, mode = "all")

 # plot network
 x11()
 plot(net,
      vertex.size = plotrix::rescale(deg, c(8, 22)),
      vertex.color = "tomato",
      vertex.frame.color = NA,
      vertex.label.color = "black",
      vertex.size = 10,
      edge.color = "#d8d8d8",
      layout = layout.fruchterman.reingold,
      edge.curved = FALSE)

 # find communities
 com <- cluster_edge_betweenness(net) 

 # details on communities
 com_sizesCom <- sizes(com) 
 com_numCom <- length(com_sizesCom)
 print(com_numCom)

 # plot communities
 colorsRainbow <- rainbow(max(membership(com)), alpha = 0.6)
 x11()
 par(mar = c(1, 1, 1, 1))
 plot(net,
      vertex.size = plotrix::rescale(deg, c(8, 22)),
      vertex.color = colorsRainbow[membership(com)],
      vertex.frame.color = NA,
      edge.color = "#d8d8d8",
      vertex.label.color = "black",
      layout = layout.fruchterman.reingold,
      edge.curved = FALSE)

 # create dendrogram
 dend <- as.dendrogram(com)
 labels(dend) <- V(net)$label[order.dendrogram(dend)]

 k <- max(membership(com))
 colorsRainbow <- rainbow(k, alpha = 1)

 colorsRainbow <- rev(unique(colorsRainbow[membership(com)[order.dendrogram(dend)]]))
 dend <- dend %>% set("labels_col", value = colorsRainbow, k = k)
 dend <- dend %>% set("branches_k_color", value = colorsRainbow, k = k)
 dend <- dend %>% set("labels_cex", 1)

 # plot dendrogram
 x11()
 par(mar = c(3, 1, 1, 5))
 plot(dend, horiz = T)

Answer 1

我不确定我是否正确地获得了标签顺序（因为我不确定它们是如何从网络中提取出来的），但这是尝试一个可重现的例子：

library(igraph)

net <- structure(list(77, FALSE, c(1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 11, 
11, 11, 11, 12, 13, 14, 15, 17, 18, 18, 19, 19, 19, 20, 20, 20, 
20, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 
23, 23, 23, 23, 23, 24, 24, 25, 25, 25, 26, 26, 26, 26, 27, 27, 
27, 27, 27, 28, 28, 29, 29, 29, 30, 31, 31, 31, 31, 32, 33, 33, 
34, 34, 35, 35, 35, 36, 36, 36, 36, 37, 37, 37, 37, 37, 38, 38, 
38, 38, 38, 38, 39, 40, 41, 41, 42, 42, 42, 43, 43, 43, 44, 44, 
45, 47, 48, 48, 48, 48, 49, 49, 50, 50, 51, 51, 51, 52, 52, 53, 
54, 54, 54, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 56, 56, 57, 
57, 57, 58, 58, 58, 58, 58, 59, 59, 59, 59, 60, 60, 60, 61, 61, 
61, 61, 61, 61, 62, 62, 62, 62, 62, 62, 62, 62, 63, 63, 63, 63, 
63, 63, 63, 63, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 65, 65, 
65, 65, 65, 65, 65, 65, 65, 65, 66, 66, 66, 66, 66, 66, 66, 66, 
66, 67, 68, 68, 68, 68, 68, 68, 69, 69, 69, 69, 69, 69, 69, 70, 
70, 70, 70, 70, 70, 70, 70, 71, 71, 71, 71, 71, 71, 71, 71, 72, 
72, 72, 73, 74, 74, 75, 75, 75, 75, 75, 75, 75, 76, 76, 76, 76, 
76, 76, 76), c(0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 10, 3, 2, 0, 11, 
11, 11, 11, 16, 16, 17, 16, 17, 18, 16, 17, 18, 19, 16, 17, 18, 
19, 20, 16, 17, 18, 19, 20, 21, 16, 17, 18, 19, 20, 21, 22, 12, 
11, 23, 11, 24, 23, 11, 24, 11, 16, 25, 11, 23, 25, 24, 26, 11, 
27, 23, 27, 11, 23, 30, 11, 23, 27, 11, 11, 27, 11, 29, 11, 34, 
29, 34, 35, 11, 29, 34, 35, 36, 11, 29, 34, 35, 36, 37, 11, 29, 
25, 25, 24, 25, 41, 25, 24, 11, 26, 27, 28, 11, 28, 46, 47, 25, 
27, 11, 26, 11, 49, 24, 49, 26, 11, 51, 39, 51, 51, 49, 26, 51, 
49, 39, 54, 26, 11, 16, 25, 41, 48, 49, 55, 55, 41, 48, 55, 48, 
27, 57, 11, 58, 55, 48, 57, 48, 58, 59, 48, 58, 60, 59, 57, 55, 
55, 58, 59, 48, 57, 41, 61, 60, 59, 48, 62, 57, 58, 61, 60, 55, 
55, 62, 48, 63, 58, 61, 60, 59, 57, 11, 63, 64, 48, 62, 58, 61, 
60, 59, 57, 55, 64, 58, 59, 62, 65, 48, 63, 61, 60, 57, 25, 11, 
24, 27, 48, 41, 25, 68, 11, 24, 27, 48, 41, 25, 69, 68, 11, 24, 
27, 41, 58, 27, 69, 68, 70, 11, 48, 41, 25, 26, 27, 11, 48, 48, 
73, 69, 68, 25, 48, 41, 70, 71, 64, 65, 66, 63, 62, 48, 58), 
    c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 13, 12, 11, 10, 14, 15, 16, 
    17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 
    32, 33, 34, 35, 36, 37, 38, 47, 46, 39, 40, 41, 42, 43, 44, 
    45, 49, 48, 52, 51, 50, 54, 55, 53, 56, 57, 58, 60, 59, 61, 
    62, 63, 66, 64, 65, 67, 69, 70, 71, 68, 72, 73, 74, 75, 76, 
    77, 79, 78, 82, 83, 80, 81, 87, 88, 84, 85, 86, 93, 94, 89, 
    90, 91, 92, 95, 96, 97, 98, 101, 100, 99, 102, 103, 104, 
    106, 105, 107, 108, 112, 110, 111, 109, 114, 113, 116, 115, 
    119, 118, 117, 121, 120, 122, 125, 124, 123, 131, 132, 133, 
    130, 128, 134, 135, 127, 126, 129, 136, 137, 139, 140, 138, 
    145, 143, 142, 141, 144, 148, 147, 149, 146, 150, 151, 152, 
    153, 158, 157, 154, 156, 155, 164, 162, 159, 163, 160, 161, 
    166, 165, 168, 174, 170, 171, 167, 173, 172, 169, 184, 177, 
    175, 183, 179, 182, 181, 180, 176, 178, 187, 194, 193, 189, 
    192, 191, 190, 188, 185, 186, 200, 196, 197, 203, 202, 198, 
    201, 195, 199, 204, 206, 207, 205, 208, 210, 209, 213, 214, 
    211, 215, 217, 216, 212, 221, 222, 218, 223, 224, 225, 220, 
    219, 230, 233, 226, 232, 231, 228, 227, 229, 236, 234, 235, 
    237, 238, 239, 242, 244, 243, 241, 240, 245, 246, 252, 253, 
    251, 250, 247, 248, 249), c(0, 1, 2, 4, 5, 6, 7, 8, 9, 13, 
    3, 12, 11, 10, 14, 15, 16, 17, 47, 49, 52, 54, 57, 62, 66, 
    69, 72, 73, 75, 77, 82, 87, 93, 102, 106, 112, 114, 119, 
    131, 145, 184, 206, 213, 221, 230, 236, 46, 18, 19, 21, 24, 
    28, 33, 39, 55, 132, 20, 22, 25, 29, 34, 40, 23, 26, 30, 
    35, 41, 27, 31, 36, 42, 32, 37, 43, 38, 44, 45, 48, 51, 58, 
    64, 67, 70, 50, 53, 60, 97, 101, 116, 207, 214, 222, 56, 
    59, 95, 96, 98, 100, 110, 133, 205, 211, 218, 233, 242, 61, 
    103, 113, 118, 125, 130, 234, 63, 65, 71, 74, 104, 111, 143, 
    208, 215, 223, 226, 235, 105, 107, 76, 79, 83, 88, 94, 68, 
    78, 80, 84, 89, 81, 85, 90, 86, 91, 92, 121, 128, 99, 134, 
    139, 164, 210, 217, 224, 232, 244, 108, 109, 135, 140, 142, 
    148, 150, 153, 162, 168, 177, 187, 200, 209, 216, 231, 237, 
    238, 243, 252, 115, 117, 124, 127, 136, 120, 122, 123, 126, 
    129, 137, 138, 141, 147, 158, 159, 174, 175, 194, 144, 149, 
    157, 163, 170, 183, 193, 204, 146, 151, 154, 160, 171, 179, 
    189, 196, 225, 253, 152, 156, 161, 167, 182, 192, 197, 155, 
    166, 173, 181, 191, 203, 165, 172, 180, 190, 202, 169, 176, 
    188, 198, 251, 178, 185, 201, 250, 186, 195, 247, 199, 248, 
    249, 212, 220, 228, 241, 219, 227, 240, 229, 245, 246, 239
    ), c(0, 0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 10, 14, 15, 16, 17, 
    18, 18, 19, 21, 24, 28, 33, 39, 48, 50, 53, 57, 62, 64, 67, 
    68, 72, 73, 75, 77, 80, 84, 89, 95, 96, 97, 99, 102, 105, 
    107, 108, 108, 109, 113, 115, 117, 120, 122, 123, 126, 136, 
    138, 141, 146, 150, 153, 159, 167, 175, 185, 195, 204, 205, 
    211, 218, 226, 234, 237, 238, 240, 247, 254), c(0, 10, 10, 
    12, 13, 13, 13, 13, 13, 13, 13, 14, 46, 47, 47, 47, 47, 56, 
    62, 67, 71, 74, 76, 77, 83, 92, 105, 112, 124, 126, 131, 
    132, 132, 132, 132, 136, 139, 141, 142, 142, 144, 144, 153, 
    153, 153, 153, 153, 154, 155, 173, 178, 178, 182, 182, 182, 
    183, 192, 192, 200, 210, 217, 223, 228, 233, 237, 240, 242, 
    243, 243, 247, 250, 252, 253, 253, 254, 254, 254, 254), list(
        c(1, 0, 1), structure(list(), .Names = character(0)), 
        structure(list(id = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
        11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 
        25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 
        39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 
        53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 
        67, 68, 69, 70, 71, 72, 73, 74, 75, 76), label = c("Myriel", 
        "Napoleon", "MlleBaptistine", "MmeMagloire", "CountessDeLo", 
        "Geborand", "Champtercier", "Cravatte", "Count", "OldMan", 
        "Labarre", "Valjean", "Marguerite", "MmeDeR", "Isabeau", 
        "Gervais", "Tholomyes", "Listolier", "Fameuil", "Blacheville", 
        "Favourite", "Dahlia", "Zephine", "Fantine", "MmeThenardier", 
        "Thenardier", "Cosette", "Javert", "Fauchelevent", "Bamatabois", 
        "Perpetue", "Simplice", "Scaufflaire", "Woman1", "Judge", 
        "Champmathieu", "Brevet", "Chenildieu", "Cochepaille", 
        "Pontmercy", "Boulatruelle", "Eponine", "Anzelma", "Woman2", 
        "MotherInnocent", "Gribier", "Jondrette", "MmeBurgon", 
        "Gavroche", "Gillenormand", "Magnon", "MlleGillenormand", 
        "MmePontmercy", "MlleVaubois", "LtGillenormand", "Marius", 
        "BaronessT", "Mabeuf", "Enjolras", "Combeferre", "Prouvaire", 
        "Feuilly", "Courfeyrac", "Bahorel", "Bossuet", "Joly", 
        "Grantaire", "MotherPlutarch", "Gueulemer", "Babet", 
        "Claquesous", "Montparnasse", "Toussaint", "Child1", 
        "Child2", "Brujon", "MmeHucheloup"), maincharacter = c(0, 
        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0)), .Names = c("id", "label", "maincharacter"
        )), structure(list(value = c(1, 8, 10, 6, 1, 1, 1, 1, 
        2, 1, 1, 3, 3, 5, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 3, 3, 
        3, 4, 3, 3, 3, 3, 5, 3, 3, 3, 3, 4, 4, 3, 3, 3, 3, 4, 
        4, 4, 2, 9, 2, 7, 13, 1, 12, 4, 31, 1, 1, 17, 5, 5, 1, 
        1, 8, 1, 1, 1, 2, 1, 2, 3, 2, 1, 1, 2, 1, 3, 2, 3, 3, 
        2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 
        2, 3, 2, 2, 1, 3, 1, 1, 3, 1, 2, 1, 2, 1, 1, 1, 3, 2, 
        1, 1, 9, 2, 2, 1, 1, 1, 2, 1, 1, 6, 12, 1, 1, 21, 19, 
        1, 2, 5, 4, 1, 1, 1, 1, 1, 7, 7, 6, 1, 4, 15, 5, 6, 2, 
        1, 4, 2, 2, 6, 2, 5, 1, 1, 9, 17, 13, 7, 2, 1, 6, 3, 
        5, 5, 6, 2, 4, 3, 2, 1, 5, 12, 5, 4, 10, 6, 2, 9, 1, 
        1, 5, 7, 3, 5, 5, 5, 2, 5, 1, 2, 3, 3, 1, 2, 2, 1, 1, 
        1, 1, 3, 5, 1, 1, 1, 1, 1, 6, 6, 1, 1, 2, 1, 1, 4, 4, 
        4, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 
        2, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)), .Names = "value")), 
    "<environment>"), class = "igraph")

girvNew <- cluster_edge_betweenness(upgrade_graph(net))
dend <- as.dendrogram(girvNew )

library(dendextend)
# hopefully this is correct, but I'm not sure. It assumes that
# V(net)$label has the order of the original data
labels(dend) <- V(net)$label[order.dendrogram(dend)]

plot(dend)

library(colorspace)
k <- max(membership(girvNew))
colorsRainbow <- rainbow_hcl(k, alpha = 1) # [membership(girvNew)]

set.seed(23420)
colorsRainbow <- rainbow_hcl(max(membership(girvNew)))
colorsRainbow <- sample(colorsRainbow)
dend <- dend %>% set("labels_col", value = colorsRainbow, k = k) 
dend <- dend %>% set("branches_k_color", value = colorsRainbow, k = k) 

par(mar = c(3,1,1,5) )
plot(dend, horiz = T)

输出：

现在用ggplot2：

library(ggplot2)
ggplot(dend) # the same as: ggplot(as.ggdend(dend))
# more work is needed for fixing the margins etc.

更新的代码：

# dput(net)
net <- structure(list(16, FALSE, c(1, 2, 3, 2, 3, 3, 4, 5, 5, 7, 7, 
9, 8, 10, 9, 11, 11, 14, 15, 15, 15, 12, 14), c(0, 0, 0, 1, 2, 
1, 3, 3, 4, 3, 6, 6, 7, 8, 8, 8, 10, 11, 14, 13, 12, 3, 1), c(0, 
1, 3, 2, 5, 4, 6, 7, 8, 9, 10, 12, 11, 14, 13, 15, 16, 21, 22, 
17, 20, 19, 18), c(0, 1, 2, 3, 5, 22, 4, 6, 7, 9, 21, 8, 10, 
11, 12, 14, 13, 15, 16, 17, 20, 19, 18), c(0, 0, 1, 3, 6, 7, 
9, 9, 11, 12, 14, 15, 17, 18, 18, 20, 23), c(0, 3, 6, 7, 11, 
12, 12, 14, 15, 18, 18, 19, 20, 21, 22, 23, 23), list(c(1, 0, 
1), structure(list(), .Names = character(0)), structure(list(
    id = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
    15), label = c("A", "B", "C", "D", "E", "F", "G", "H", "I", 
    "L", "M", "N", "O", "P", "Q", "R")), .Names = c("id", "label"
)), list()), "<environment>"), class = "igraph")


library(igraph)
net <- upgrade_graph(net)
# calculate degree
deg <- degree(net, mode = "all")

# find communities
com <- cluster_edge_betweenness(net) 
## or use 
# com <- fastgreedy.community(net)

# details on communities
com_sizesCom <- sizes(com) 
com_numCom <- length(com_sizesCom)


# create dendrogram
dend <- as.dendrogram(com)
plot(dend)
library(dendextend)
labels(dend) <- V(net)$label[order.dendrogram(dend)]
plot(dend)

k <- max(membership(com))
colorsRainbow <- rainbow(k, alpha = 1)

# colorsRainbow <- sample(colorsRainbow)
# dend <- rotate(dend, order(membership(comm)))
colorsRainbow <- rev(unique(colorsRainbow[membership(comm)[order.dendrogram(dend)]]))
dend <- dend %>% set("labels_col", value = colorsRainbow, k = k)
dend <- dend %>% set("branches_k_col", value = colorsRainbow, k = k)
dend <- dend %>% set("labels_cex", 1)
plot(dend)

为树形图添加标签并为群集着色

1 个答案: