我有以下图表:
library(tidyverse)
library(igraph)
library(visNetwork)
set.seed(123)
n=15
data = data.frame(tibble(d = paste(1:n)))
relations = data.frame(tibble(
from = sample(data$d),
to = lead(from, default=from[1]),
))
data$name = c("new york", "chicago", "los angeles", "orlando", "houston", "seattle", "washington", "baltimore", "atlanta", "las vegas", "oakland", "phoenix", "kansas", "miami", "newark" )
graph = graph_from_data_frame(relations, directed=T, vertices = data)
V(graph)$color <- ifelse(data$d == relations$from[1], "red", "orange")
plot(graph, layout=layout.circle, edge.arrow.size = 0.2)
我尝试使用“visNetwork”库制作完全相同的图表,但该图表现在显示为“圆形”而不是“随机”:
visIgraph(graph)
我尝试研究是否可以使用“visNetwork”库生成“随机排序”图而不是圆形图。例如:
visIgraph(graph) %>%
visLayout(randomSeed = 123)
但这仍然会产生圆形图。
我意外地发现这段代码可以正常工作( https://www.rdocumentation.org/packages/visNetwork/versions/2.1.0/topics/visIgraphLayout ):
visIgraph(graph) %>%
visIgraphLayout(layout = "layout_in_circle") %>%
visOptions(highlightNearest = list(enabled = T, hover = T),
nodesIdSelection = T)
为什么“随机种子”选项仍然会产生圆形图,但上述选项会产生所需的结果?有没有解释一下?
谢谢!
最佳答案
不确定完全理解您在寻找什么,但是:
如果您希望顶点随机放置而不是在圆上,则只需使用参数
layout = "layout_randomly"
里面visIgraph()
功能。如果您希望顶点随机放置在圆上,则需要使用
permute()
函数,然后只需添加参数layout = "layout_circle"
里面visIgraph()
功能。
请在下面找到一个代表。
Reprex
- 您的数据
library(dplyr)
library(igraph)
library(visNetwork)
set.seed(123)
n=15
data = data.frame(tibble(d = paste(1:n)))
relations = data.frame(tibble(
from = sample(data$d),
to = lead(from, default=from[1]),
))
# data$name = c("new york", "chicago", "los angeles", "orlando", "houston", "seattle", "washington", "baltimore", "atlanta", "las vegas", "oakland", "phoenix", "kansas", "miami", "newark" )
graph = graph_from_data_frame(relations, directed=T, vertices = data)
V(graph)$color <- ifelse(data$d == relations$from[1], "red", "orange")
建议的代码
1。随机顶点放置
visIgraph(graph, layout='layout_randomly')
2。圆上的随机顶点放置
permute(graph, permutation = sample(vcount(graph))) %>%
visIgraph(layout='layout_in_circle')
由 reprex package 于 2022 年 2 月 25 日创建(v2.0.1)
关于r - 调整图表布局,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/71261431/