This post describes how to add labels on a
hierarchical edge bundling
chart. It explains how to proceed, with reproducible
R
code, using the ggraph
package.
Previous post of the hierarchical edge bundling section explained:
Let’s remind how to prepare the data for the
ggraph
library.
# Libraries
library(ggraph)
library(igraph)
library(tidyverse)
library(RColorBrewer)
# create a data frame giving the hierarchical structure of your individuals
set.seed(1234)
d1 <- data.frame(from="origin", to=paste("group", seq(1,10), sep=""))
d2 <- data.frame(from=rep(d1$to, each=10), to=paste("subgroup", seq(1,100), sep="_"))
edges <- rbind(d1, d2)
# create a dataframe with connection between leaves (individuals)
all_leaves <- paste("subgroup", seq(1,100), sep="_")
connect <- rbind(
data.frame( from=sample(all_leaves, 100, replace=T) , to=sample(all_leaves, 100, replace=T)),
data.frame( from=sample(head(all_leaves), 30, replace=T) , to=sample( tail(all_leaves), 30, replace=T)),
data.frame( from=sample(all_leaves[25:30], 30, replace=T) , to=sample( all_leaves[55:60], 30, replace=T)),
data.frame( from=sample(all_leaves[75:80], 30, replace=T) , to=sample( all_leaves[55:60], 30, replace=T)) )
connect$value <- runif(nrow(connect))
# create a vertices data.frame. One line per object of our hierarchy
vertices <- data.frame(
name = unique(c(as.character(edges$from), as.character(edges$to))) ,
value = runif(111)
)
# Let's add a column with the group of each name. It will be useful later to color points
vertices$group <- edges$from[ match( vertices$name, edges$to ) ]
Next step: computing the label features that will be displayed all around the circle, next to the nodes:
Those information are computed and added to the
vertices
data frame.
#Let's add information concerning the label we are going to add: angle, horizontal adjustement and potential flip
#calculate the ANGLE of the labels
vertices$id <- NA
myleaves <- which(is.na( match(vertices$name, edges$from) ))
nleaves <- length(myleaves)
vertices$id[ myleaves ] <- seq(1:nleaves)
vertices$angle <- 90 - 360 * vertices$id / nleaves
# calculate the alignment of labels: right or left
# If I am on the left part of the plot, my labels have currently an angle < -90
vertices$hjust <- ifelse( vertices$angle < -90, 1, 0)
# flip angle BY to make them readable
vertices$angle <- ifelse(vertices$angle < -90, vertices$angle+180, vertices$angle)
Now that label features have been computed, we just need to display
it on the chart using the geom_node_text()
function.
# Create a graph object
mygraph <- igraph::graph_from_data_frame( edges, vertices=vertices )
# The connection object must refer to the ids of the leaves:
from <- match( connect$from, vertices$name)
to <- match( connect$to, vertices$name)
# Basic usual argument
ggraph(mygraph, layout = 'dendrogram', circular = TRUE) +
geom_node_point(aes(filter = leaf, x = x*1.05, y=y*1.05)) +
geom_conn_bundle(data = get_con(from = from, to = to), alpha=0.2, colour="skyblue", width=0.9) +
geom_node_text(aes(x = x*1.1, y=y*1.1, filter = leaf, label=name, angle = angle, hjust=hjust), size=1.5, alpha=1) +
theme_void() +
theme(
legend.position="none",
plot.margin=unit(c(0,0,0,0),"cm"),
) +
expand_limits(x = c(-1.2, 1.2), y = c(-1.2, 1.2))
To get the final figure, it is necessary to add customization described in graph #310:
ggraph(mygraph, layout = 'dendrogram', circular = TRUE) +
geom_conn_bundle(data = get_con(from = from, to = to), alpha=0.2, width=0.9, aes(colour=..index..)) +
scale_edge_colour_distiller(palette = "RdPu") +
geom_node_text(aes(x = x*1.15, y=y*1.15, filter = leaf, label=name, angle = angle, hjust=hjust, colour=group), size=2, alpha=1) +
geom_node_point(aes(filter = leaf, x = x*1.07, y=y*1.07, colour=group, size=value, alpha=0.2)) +
scale_colour_manual(values= rep( brewer.pal(9,"Paired") , 30)) +
scale_size_continuous( range = c(0.1,10) ) +
theme_void() +
theme(
legend.position="none",
plot.margin=unit(c(0,0,0,0),"cm"),
) +
expand_limits(x = c(-1.3, 1.3), y = c(-1.3, 1.3))
👋 After crafting hundreds of R charts over 12 years, I've distilled my top 10 tips and tricks. Receive them via email! One insight per day for the next 10 days! 🔥