基于R语言绘制Network几种方式

2022-03-10 本文已影响0人凯凯何_Boy

平时对于网络图的绘制，一般我们都会在R中生成边和点列表后导入到Cytoscape和Gephi等的本地工具软件当中，而R语言中也自带有不少优秀的包也可精美的可视化我们的数据，所有函数也比较简单，有时间的不妨学习一下~~

加载R包

## 安装加载数据
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/navdata")
install.packages(
  c("tidyverse", "igraph", "tidygraph", "ggraph")
)

library(pacman)
p_load("navdata","tidyverse", "igraph", "tidygraph", "ggraph")

navdata:需要用到此包中的示例数据集phone.call
tidyverse：数据进行操作转换
igraph，tidygraph和ggraph：用于网络可视化

查看示例数据

文件包含三列数据：来源地、目的地、及call数量

library("navdata")
data("phone.call")
head(phone.call, 3)
## # A tibble: 3 x 3
##    source destination n.call
##              
## 1  France     Germany      9
## 2 Belgium      France      4
## 3  France       Spain      3

我们都知道可视化网络，需要准备两个数据文件：

点列表：包含点标签和其它的点属性
边列表：包含点与点之间的关系，及其它属性

接下来基于此数据集准备点和边列表文件

点列表

去重source 和 destination列，然后将向量合并一列命名为label，添加索引值

#  来源地去重
sources <- phone.call %>%
  distinct(source) %>%
  rename(label = source)
  
#目的地去重
destinations <- phone.call %>%
  distinct(destination) %>%
  rename(label = destination)
  
## 合并数据并添加一列索引
nodes <- full_join(sources, destinations, by = "label") 
nodes <- nodes %>%
  mutate(id = 1:nrow(nodes)) %>%
  select(id, everything())
head(nodes, 3)

## # A tibble: 3 x 2
##      id   label
##      
## 1     1  France
## 2     2 Belgium
## 3     3 Germany

创建边列表

其实原始数据已具备边列表的格式，重命名 n.call为weight，然后通过left_join函数将点列表中id数据和边列表中进行合并

# Rename the n.call column to weight
phone.call <- phone.call %>%
  rename(weight = n.call)
  
# (a) Join nodes id for source column
edges <- phone.call %>% 
  left_join(nodes, by = c("source" = "label")) %>% 
  rename(from = id)
  
# (b) Join nodes id for destination column
edges <- edges %>% 
  left_join(nodes, by = c("destination" = "label")) %>% 
  rename(to = id)
  
# (c) Select/keep only the columns from and to
edges <- select(edges, from, to, weight)
head(edges, 3)

## # A tibble: 3 x 3
##    from    to weight
##      
## 1     1     3      9
## 2     2     1      4
## 3     1     8      3

可视化网络

至此，简单的边和点列表已经准备好了，我们接下来通过几个R包来可视化下

igraph

这是R中绘制网络图的一个基本R包，这里主要用到graph_from_data_fram()函数。更多关于此包绘图的细节可参考这个帖子Network Analysis and Visualization with R and igraph (kateto.net)，介绍的十分详细。

library(igraph)
net.igraph <- graph_from_data_frame(
  d = edges, vertices = nodes, 
  directed = TRUE
  )
  ## d 边列表，vertices 点列表，directer：有向或者无向
  
  ## network
  set.seed(123)
plot(net.igraph, edge.arrow.size = 0.2,
     layout = layout_with_graphopt)

image-20220308151413493

tidygraph和ggraph

这两个R包目前相对比较流行，可以对network数据进行操作和可视化

首先用tidygraph创建networ对象

library(tidygraph)
net.tidy <- tbl_graph(
  nodes = nodes, edges = edges, directed = TRUE
  )

使用ggraph可视化网络

library(ggraph)
ggraph(net.tidy, layout = "graphopt") + 
  geom_node_point(col = 'gold',size = 2) + # 点信息
  geom_edge_link(aes(width = weight), alpha = 0.8) +  # 边信息
  scale_edge_width(range = c(0.2, 2)) + # 控制粗细
  geom_node_text(aes(label = label), repel = TRUE) + # 增加节点的标签，reple避免节点重叠
  labs(edge_width = "phone.call") + # 图例标签
  theme_graph()

image-20220308152100483

visNetwor和network3D

这两款R包都是基于浏览器的JavaScript可视化库，用于交互式的展示图形，这里我们还用到刚才的示例数据来展示。

加载数据

library(tidyverse)
library("navdata")
data("phone.call2")
nodes <- phone.call2$nodes
edges <- phone.call2$edges
## 刚才数据集是phone.call，phone.call2可以直接提取点和边列表

##注意：该包中节点和边缘列表中的ID应该是从0开始的数字值。我们直接减1 即可
nodes_d3 <- mutate(nodes, id = id - 1)
edges_d3 <- mutate(edges, from = from - 1, to = to - 1)

network3D

常用来快速创建交互式桑基图、和其它种类的网络图等，核心的函数即forceNetwork()

library(networkD3)
forceNetwork(
  Links = edges_d3, Nodes = nodes_d3,bounded = T,
  Source = "from", Target = "to",      # so the network is directed.
  NodeID = "label", Group = "id", Value = "weight", 
  width = 700, height=500,legend = T,
  colourScale = JS("d3.scaleOrdinal(d3.schemeCategory10);"), ## 颜色模板
  opacity = 1, fontSize = 18, zoom = TRUE, opacityNoHover = 1  ## 显示标签信息
)

## 如果想自定义颜色新修改，直接括号中改为16进制颜色即可
 colourScale = JS("d3.scaleOrdinal([`#383867`, `#584c77`, `#e1eff7`,`#dd2c29`]);"),

image-20220308160944163

制作桑基图

sankeyNetwork(
  Links = edges_d3, Nodes = nodes_d3, 
  Source = "from", Target = "to", 
  NodeID = "label", Value = "weight", 
  fontSize = 16, unit = "Letter(s)")

image-20220308161022262

visNetwork

该包绘制更加方便，

library(visNetwork)
visNetwork(nodes, edges) %>%
  visLayout(randomSeed = 12)

image-20220308161618459

我们也可以为网络中的边添加方向,用到 layout_with_fr 方式

visNetwork(nodes, edges) %>% 
  visIgraphLayout(layout = "layout_with_fr") %>% 
  visEdges(arrows = "middle") %>%
  visLayout(randomSeed = 1234)

image-20220308161805871