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我刚刚执行了一个代码来使用 igraph 和 tidygraph 获得一致的图形。在我的示例中，A 和 C 之间的权重仅为 1。因此 igraph 包中的网络图将权重适当地反映为距离。

在此处输入图像描述

但是，我认为 tidygraph 未能将重量作为距离。例如，尽管权重很大，但 B 和 E 没有联系。

在此处输入图像描述

如何将重量反映为距离？

   source target weight
1       A      B      4
2       A      B      7
3       A      C      1
4       A      D      2
5       A      J     11
6       J      A     14
7       B      E     18
8       B      F     19
9       C      G      1
10      C      H     10
11      D      I     14
12      I      I     10


# https://www.r-graph-gallery.com/249-igraph-network-map-a-color.html

# library
library(igraph)
set.seed(1)

# Create data
links <- data.frame(
  source = c("A","A", "A", "A", "A","J", "B", "B", "C", "C", "D","I"),
  target = c("B","B", "C", "D", "J","A","E", "F", "G", "H", "I","I"),
  weight = sample(1:20, 12, replace = T)
)

# Print out weights
links$weight

nodes <- data.frame(
  name=LETTERS[1:10],
  carac = c(rep("young", 3), rep("adult", 2), rep("old", 5))
)

# Turn it into igraph object
network <- graph_from_data_frame(d = links, vertices = nodes, directed = F) 

# Make a palette of 3 colors
library(RColorBrewer)
coul <- brewer.pal(3, "Set1") 

# Create a vector of color
my_color <- coul[as.numeric(as.factor(V(network)$carac))]

# Make the plot
plot(network, vertex.color = my_color)

# See colors
as.factor(nodes$carac)

library(ggraph)
library(tidygraph)
#
g <- tbl_graph(nodes, links, directed = FALSE)
g %>% mutate(degree = centrality_degree(),
         community = carac)%>%
  ggraph(layout = "lgl") +
  geom_edge_link(aes(width = 1),
                 alpha = 0.8,
                 colour = "lightgray") +
  scale_edge_width(range = c(0.1, 1)) +geom_node_point(aes(colour = community, size = degree)) +
  geom_node_text(aes(label = name), repel = TRUE) +
  theme_graph()
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1 回答 1

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似乎设计者tidygraph更喜欢使用边缘连接的索引。因此，在函数中，tbl_graph()对您的数据进行了一些假设以构建网络对象。

因此，我认为解决此问题的最简单方法是将igraph您创建的对象传递as_tbl_graph()给以确保连接正确。

# Library
library(igraph)
#> Attaching package: 'igraph'
#> The following objects are masked from 'package:stats':
#> 
#>     decompose, spectrum
#> The following object is masked from 'package:base':
#> 
#>     union
library(tidygraph)
#> Attaching package: 'tidygraph'
#> The following object is masked from 'package:igraph':
#> 
#>     groups
#> The following object is masked from 'package:stats':
#> 
#>     filter
library(ggraph)
#> Loading required package: ggplot2

set.seed(1)

# Create data
links <- data.frame(
  source = c("A","A", "A", "A", "A","J", "B", "B", "C", "C", "D","I"),
  target = c("B","B", "C", "D", "J","A","E", "F", "G", "H", "I","I"),
  weight = sample(1:20, 12, replace = T)
)
nodes <- data.frame(
  name = LETTERS[1:10],
  carac = c(rep("young", 3), rep("adult", 2), rep("old", 5))
)
network <- graph_from_data_frame(d = links, vertices = nodes, directed = F) 

g <- as_tbl_graph(network)
g %>% mutate(degree = centrality_degree(),
             community = carac)%>%
  ggraph(layout = "lgl") +
  geom_edge_link(aes(width = 1),
                 alpha = 0.8,
                 colour = "lightgray") +
  scale_edge_width(range = c(0.1, 1)) +
  geom_node_point(aes(colour = community, size = degree)) +
  geom_node_text(aes(label = name), repel = TRUE) +
  theme_graph()

由reprex 包（v0.3.0）于 2020-07-03 创建

编辑：经过进一步检查，问题的根源在于tbl_graph()不喜欢因素并将其删除。然后，这会根据显示的节点顺序创建映射。所以这就是为什么我们看到一个奇怪的网络。所以在下面，我stringsAsFactors = FALSE在创建links数据框时添加了。

# Library
library(igraph)
#> Attaching package: 'igraph'
#> The following objects are masked from 'package:stats':
#> 
#>     decompose, spectrum
#> The following object is masked from 'package:base':
#> 
#>     union
library(tidygraph)
#> Attaching package: 'tidygraph'
#> The following object is masked from 'package:igraph':
#> 
#>     groups
#> The following object is masked from 'package:stats':
#> 
#>     filter
library(ggraph)
#> Loading required package: ggplot2

set.seed(1)

# Create data
links <- data.frame(
  source = c("A","A", "A", "A", "A","J", "B", "B", "C", "C", "D","I"),
  target = c("B","B", "C", "D", "J","A","E", "F", "G", "H", "I","I"),
  weight = sample(1:20, 12, replace = T),
  stringsAsFactors = FALSE
)
nodes <- data.frame(
  name = LETTERS[1:10],
  carac = c(rep("young", 3), rep("adult", 2), rep("old", 5))
)

# Create network
g <- tbl_graph(nodes, links, directed = FALSE)
g %>% mutate(degree = centrality_degree(),
             community = carac)%>%
  ggraph(layout = "lgl") +
  geom_edge_link(aes(width = 1),
                 alpha = 0.8,
                 colour = "lightgray") +
  scale_edge_width(range = c(0.1, 1)) +
  geom_node_point(aes(colour = community, size = degree)) +
  geom_node_text(aes(label = name), repel = TRUE) +
  theme_graph()

由reprex 包（v0.3.0）于 2020-07-03 创建

于 2020-07-03T21:37:20.133 回答