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我有一个关于tidygraph::和ggraph::包的问题。我正在尝试创建一个食物网网络图（下面的代码和图表），但是，我想使用带有定义 y 轴的 kk 布局，在我的例子中是来自 nodes_df 的 TL 列。

我创建了模拟数据以作为示例显示。如果有人对如何改进这个情节有任何想法，那将有很大帮助。

library(tidyverse)
#> Warning: package 'ggplot2' was built under R version 4.1.2
#> Warning: package 'tibble' was built under R version 4.1.2
#> Warning: package 'readr' was built under R version 4.1.2
#> Warning: package 'purrr' was built under R version 4.1.2
#> Warning: package 'dplyr' was built under R version 4.1.2
#> Warning: package 'stringr' was built under R version 4.1.2
library(tidygraph)
#> Warning: package 'tidygraph' was built under R version 4.1.2
#> 
#> Attaching package: 'tidygraph'
#> The following object is masked from 'package:stats':
#> 
#>     filter
library(ggraph)
#> Warning: package 'ggraph' was built under R version 4.1.2
library(igraph)
#> Warning: package 'igraph' was built under R version 4.1.2
#> 
#> Attaching package: 'igraph'
#> The following object is masked from 'package:tidygraph':
#> 
#>     groups
#> The following objects are masked from 'package:dplyr':
#> 
#>     as_data_frame, groups, union
#> The following objects are masked from 'package:purrr':
#> 
#>     compose, simplify
#> The following object is masked from 'package:tidyr':
#> 
#>     crossing
#> The following object is masked from 'package:tibble':
#> 
#>     as_data_frame
#> The following objects are masked from 'package:stats':
#> 
#>     decompose, spectrum
#> The following object is masked from 'package:base':
#> 
#>     union
library(ggpubr)
#> Warning: package 'ggpubr' was built under R version 4.1.2

set.seed(16)


label <- c("Transient_orca",
           "Salmon_sharks",
           "Resident_orca",
           "Sleeper_sharks",    
           "Halibut",
           "Pinnipeds",
           "Porpoise",  
           "Lingcod",
           "Arrowtooth_L",  
           "Salmon_L",  
           "Pacific_cod",   
           "Sablefish", 
           "Arrowtooth_S",  
           "Spiny_dogfish", 
           "Avian_raptors",
           "Octopods",  
           "Seabirds",
           "Deep_demersals",    
           "Pollock_L",
           "Rockfish",
           "Baleen_whales", 
           "Salmon_fry_S",
           "Nshore_demersal",
           "Squids",    
           "Eulachon",  
           "Sea_otters",    
           "Deep_epibenthos",   
           "Capelin",
           "Herring_L", 
           "Pollock_S",
           "Invert_eat_seaduck",    
           "Oystercatchers",
           "Sandlance",
           "Sunflower_stars",   
           "Pisaster_Evasterias",   
           "Leather_stars",
           "Sea_cucumbers",
           "Urchins",
           "Helmet_crab",   
           "Herring_S",
           "Jellies",
           "Deep_infauna_S",    
           "Zoopl_near_onmiv",  
           "Zoop_omniv",
           "Shallow_infauna_S", 
           "Meiofauna",
           "Deep_infauna_L",    
           "Snail_crust_S",
           "Mussels",
           "Barnacles", 
           "Shallow_infauna_clams", 
           "Zoopl_near_herb",
           "Zoopl_herb",
           "Phyto_near",
           "Phyto_off",
           "Fucus",
           "Subtidal_kelps",    
           "Macroalgae_other",  
           "Eelgrass",
           "Nekton_falls",  
           "Inshore_detritus",  
           "Offshore_detritus", 
           "Salmon_seine","Salmon_gillnets",
           "Herring_seine","Shrimp_pot_trawl","Pollock_trawl" ,"Demersal_longline" ,
           "Other_commercial","Rec_anglers","Rec_charters", "Subsistence_take")
TL <- rnorm(72, 3.155, 1)
B <- abs(rnorm(72, 0.7789, 10))


nodes_df <-data.frame(label,TL, B)


from <- rep(c("Lingcod",
          "Arrowtooth_L",   
          "Salmon_L",   
          "Pacific_cod",    
          "Sablefish",  
          "Arrowtooth_S",   
          "Spiny_dogfish",  
          "Avian_raptors",
          "Octopods",   
          "Seabirds",
          "Deep_demersals", 
          "Pollock_L",
          "Rockfish",
          "Baleen_whales",  
          "Salmon_fry_S",
          "Nshore_demersal",
          "Squids", 
          "Eulachon",   
          "Sea_otters", 
          "Deep_epibenthos",    
          "Capelin",
          "Herring_L",  
          "Pollock_S",
          "Invert_eat_seaduck", 
          "Oystercatchers",
          "Sandlance",
          "Sunflower_stars",    
          "Pisaster_Evasterias",    
          "Leather_stars",
          "Sea_cucumbers",
          "Urchins",
          "Helmet_crab",    
          "Herring_S",
          "Jellies",
          "Deep_infauna_S", 
          "Zoopl_near_onmiv",   
          "Zoop_omniv",
          "Shallow_infauna_S",  
          "Meiofauna",
          "Deep_infauna_L", 
          "Snail_crust_S",
          "Mussels",
          "Barnacles",  
          "Shallow_infauna_clams",  
          "Zoopl_near_herb",
          "Zoopl_herb",
          "Phyto_near",
          "Phyto_off",
          "Fucus",
          "Subtidal_kelps", 
          "Macroalgae_other",   
          "Eelgrass",
          "Nekton_falls",   
          "Inshore_detritus",   
          "Offshore_detritus"), times= 3)

to <- sample(label, size = 165, replace = TRUE)
width <- abs(rnorm(165, 0.258370, 10))

edge_df <- as_tibble(data.frame(from, to,width))

netgraph_df <- graph_from_data_frame(d=edge_df, vertices = nodes_df, directed=T)



graph <- as_tbl_graph(netgraph_df)

# plot using ggraph
ggraph(graph, layout = 'kk') + 
  geom_edge_link(aes(edge_width = width, color=stat(index)), lineend="round")+
  scale_edge_colour_gradient(high = "#e96d50", low = "#4b84a6") + 
  scale_edge_width(range = c(0.5, 5)) + 
  geom_edge_loop(aes(edge_width = width, color=stat(index)), lineend="round")+ 
  geom_node_point(aes(col= nodes_df$TL, size = nodes_df$B)) + 
  geom_node_text(aes(label = label), size=3,color="black", repel = TRUE) +
  theme_transparent()+
  theme(legend.position = "none")

由reprex 包创建于 2022-02-03 (v2.0.1)

4

1 回答 1

1

您可以预先计算布局并将y列设置为某个指标。

# Same prep as in question
graph <- as_tbl_graph(netgraph_df)

lay <- create_layout(graph, "kk")
lay$y <- lay$TL

# plot using ggraph
ggraph(graph = lay) + 
  geom_edge_link(aes(edge_width = width, color=stat(index)), lineend="round")+
  scale_edge_colour_gradient(high = "#e96d50", low = "#4b84a6") + 
  scale_edge_width(range = c(0.5, 5)) + 
  geom_edge_loop(aes(edge_width = width, color=stat(index)), lineend="round")+ 
  geom_node_point(aes(col= nodes_df$TL, size = nodes_df$B)) + 
  geom_node_text(aes(label = label), size=3,color="black", repel = TRUE) +
  theme_transparent()+
  theme(legend.position = "none")

于 2022-02-03T19:56:28.673 回答