tidygraph和igraph-从数据框差异构建图

Question

我可以从两个数据帧在igraph中构建图形对象，而不会出现问题。当我尝试在tidygraph中执行相同操作时，会出现错误。让我示范一下。首先，我加载源数据（来自留言板的数据）：

library(dplyr)
library(tidyr)
library(tidygraph)
library(lubridate)
library(iterpc)
library(igraph)

df <- data.frame(author_id = c(2,4,8,16,4,8,2,256,512,8),
             topic_id = c(101,101,101,101,301,301,501,501,501,501),
             time = as.POSIXct(c("2011-08-16 20:20:11", "2011-08-16 21:10:00", "2011-08-17 06:30:10",
                                 "2011-08-17 10:08:32", "2011-08-20 22:23:01","2011-08-20 23:03:03",
                                 "2011-08-25 17:05:01", "2011-08-25 19:15:10",  "2011-08-25 20:07:11",
                                 "2011-08-25 23:59:59")),
             vendor = as.logical(c("FALSE", "FALSE", "TRUE", "FALSE", "FALSE",
                                   "TRUE", "FALSE", "FALSE", "FALSE", "TRUE"))) 

接下来，我创建一个唯一的节点列表（将消息发布在留言板上的人）：

node <- df %>% distinct(author_id, vendor) %>% rename(id = author_id) %>% mutate(vendor = as.numeric(vendor))

然后，我的边缘列表（通过讨论线程（主题）联系的人）：

edge <- df %>% 
  group_by(topic_id) %>% 
  do(data.frame(getall(iterpc(table(.$author_id), 2, replace =TRUE)))) %>%
  filter(X1 != X2) %>% rename(from = X1, to = X2) %>% select(to, from, topic_id)

使用igraph我可以创建以下图形对象：

test_net <- graph_from_data_frame(d = edge, directed = F, vertices = node)
plot(test_net)

看起来不错 现在我尝试对tidygraph做同样的事情：

tidy_net <- tbl_graph(nodes = node, edges = edge, directed = F)
Error in add_vertices(gr, nrow(nodes) - gorder(gr)) : At type_indexededgelist.c:369 : cannot add negative number of vertices, Invalid value

kes！但是，当我将igraph对象导入tidygraph时：

tidy_net <- as_tbl_graph(test_net)
plot(tidy_net)

所有作品！到底是怎么回事？请帮忙。

Answer 1

我想是因为你的节点id和边缘to和from是数字，它假定应该有之间的每个整数节点min(node$id)（2）和max(node$id)（512）。您可以通过将其强制为字符来解决此问题。另外，您的iterpc命令对我来说无法正常工作，因此我将其转换tidyr为扩展数据的版本。

node <- 
  df %>% 
  distinct(author_id, vendor) %>% 
  rename(id = author_id) %>% 
  mutate(vendor = as.numeric(vendor)) %>% 
  mutate(id = as.character(id))

edge <- 
  df %>% 
  group_by(topic_id) %>% 
  expand(topic_id, from = author_id, to = author_id) %>% 
  filter(from < to) %>% 
  select(to, from, topic_id) %>% 
  mutate_at(vars(to, from), as.character)

tidy_net <- tbl_graph(nodes = node, edges = edge, directed = F)
plot(tidy_net)