I have a graph
of vertices and edges which I'd like to plot using a fruchtermanreingold
layout.
Here's the graph
edges matrix:
edge.mat <- matrix(as.numeric(strsplit("3651,0,0,1,0,0,0,0,2,0,11,2,0,0,0,300,0,1,0,0,66,0,78,9,0,0,0,0,0,0,11690,0,1,0,0,0,0,0,0,0,0,493,1,1,0,4288,5,0,0,36,0,9,7,3,0,6,1,0,1,7,490,0,0,0,6,0,0,628,6,12,0,0,0,0,0,641,0,0,4,0,0,0,0,0,0,66,0,0,0,0,3165,0,281,0,0,0,0,0,0,0,0,45,1,0,0,35248,0,1698,2,0,1,0,2,99,0,0,6,29,286,0,31987,0,1,10,0,8,0,16,0,21,1,0,0,1718,0,51234,0,0,17,3,12,0,0,7,0,0,0,1,0,2,16736,0,0,0,3,0,0,4,630,0,0,0,9,0,0,29495,53,6,0,0,0,0,5,0,0,0,0,3,0,19,186,0,0,0,482,8,12,0,1,0,7,1,0,6,0,26338",
split = ",")[[1]]),
nrow = 14,
dimnames = list(LETTERS[1:14], LETTERS[1:14]))
I then create an igraph
object from that using:
gr <- igraph::graph_from_adjacency_matrix(edge.mat, mode="undirected", weighted=T, diag=F)
And then use ggnetwork
to convert gr
to a data.frame
, with specified vertex colors:
set.seed(1)
gr.df <- ggnetwork::ggnetwork(gr,
layout="fruchtermanreingold",
weights="weight",
niter=50000,
arrow.gap=0)
And then I plot it using ggplot2
and ggnetwork
:
vertex.colors <- strsplit("#00BE6B,#DC2D00,#F57962,#EE8044,#A6A400,#62B200,#FF6C91,#F77769,#EA8332,#DA8E00,#C59900,#00ACFC,#C49A00,#DC8D00",
split=",")[[1]]
library(ggplot2)
library(ggnetwork)
ggplot(gr.df, aes(x = x, y = y, xend = xend, yend = yend)) +
geom_edges(color = "gray", aes(size = weight)) +
geom_nodes(color = "black")+
geom_nodelabel(aes(label = vertex.names),
color = vertex.colors, fontface = "bold")+
theme_minimal() +
theme(axis.text=element_blank(),
axis.title=element_blank(),
legend.position="none")
In my case each vertex actually represents many points, where each vertex has a different number of points. Adding that information to gr.df
:
gr.df$n <- NA
gr.df$n[which(is.na(gr.df$weight))] <- as.integer(runif(length(which(is.na(gr.df$weight))), 100, 500))
What I'd like to do is add to the plot gr.df$n
radially jittered points around each vertex (i.e., with its corresponding n
), with the same vertex.colors
coding. Any idea how to do that?
I think sampling and then plotting with geom_point
is a reasonable strategy. (otherwise you could create your own geom).
Here is some rough code, starting from the relevant bit of your question
gr.df$n <- 1
gr.df$n[which(is.na(gr.df$weight))] <- as.integer(runif(length(which(is.na(gr.df$weight))), 100, 500))
# function to sample
# https://stackoverflow.com/questions/5837572/generate-a-random-point-within-a-circle-uniformly
circSamp <- function(x, y, R=0.1){
n <- length(x)
A <- a <- runif(n,0,1)
b <- runif(n,0,1)
ind <- b < a
a[ind] <- b[ind]
b[ind] <- A[ind]
xn = x+b*R*cos(2*pi*a/b)
yn = y+b*R*sin(2*pi*a/b)
cbind(x=xn, y=yn)
}
# sample
d <- with(gr.df, data.frame(vertex.names=rep(vertex.names, n),
circSamp(rep(x,n), rep(y,n))))
# p is your plot
p + geom_point(data=d, aes(x, y, color = vertex.names),
alpha=0.1, inherit.aes = FALSE) +
scale_color_manual(values = vertex.colors)
Giving