R中的ggtern有什么替代品吗？

Question

Its looks like that ggtern has not been synchronised with new version of ggplot2. Therefore we can not use ggtern.

library(ggtern)
set.seed(1)
plot <- ggtern(data = data.frame(x = runif(100),
                                 y = runif(100),
                                 z = runif(100)),
               aes(x, y, z))
plot + stat_density_tern(geom = 'polygon',
                         n         = 200,
                         aes(fill  = ..level..,
                             alpha = ..level..)) +
  geom_point() +
  theme_rgbw() +
  labs(title = "Example Density/Contour Plot")    +
  scale_fill_gradient(low = "blue",high = "red")  +
  guides(color = "none", fill = "none", alpha = "none")

Error: geom_point requires the following missing aesthetics: x and y

Does anyone have in find other options for ternary diagrams apart from ggtern in R?

Answer 1

Manually, you could plot the points with a function: (I used the formulas at https://en.wikipedia.org/wiki/Ternary_plot )

I'm not familiar with the output of stat_density_tern so I'm not sure what is expected from that part.

library(tidyverse)
tern <- function(df) {
  df %>% mutate(x_pos = 0.5 * (2*y + z) / (x+y+z),
                y_pos = sqrt(3) / 2 * z / (x+y+z)) 
}

tern(plot) %>%
  ggplot(aes(x_pos, y_pos)) +
  geom_point() +
  annotate("path", x = c(0, 0.5, 1, 0), y = c(0,sqrt(3)/2,0,0)) +
  coord_equal()

Answer 2

this worked for me! Uninstall ggtern and ggplot2 then

install_version("ggplot2", version = "3.3.0", repos = "http://cran.us.r-project.org")

install.packages("ggtern")

library(ggtern)

Answer 3

I use the following script which also supports making diagrams with 4 or more corners. It also divides the points into colored clusters by cutting a hierarchical clustering at the height where it has 32 subtrees, and it draws a line from each point to its two nearest neighbors.

library(tidyverse)
library(ggforce)
library(colorspace)

t=as.matrix(read.csv("https://pastebin.com/raw/1EDJJtHU",row.names=1,check.names=F))/100

fst=as.matrix(read.csv("https://pastebin.com/raw/6JmN2hRY",row.names=1))
mult=t%*%cmdscale(fst,ncol(fst)-1)

# t=cbind(t[,2]+t[,1],t[,8]+t[,9],rowSums(t[,-c(1,2,8,9)]))
# colnames(t)=c("Baltic + North_Atlantic","Siberian + East_Asian","Other")

# t=cbind(t[,2],t[,1],t[,8]+t[,9],rowSums(t[,-c(1,2,8,9)]))
# colnames(t)=c("Baltic","North_Atlantic","Siberian + East_Asian","Other")

ncorn=ncol(t)
start=ifelse(ncorn==4,.25,0)
corners=sapply(c(sin,cos),\(x)x((start+seq(0,2,,ncorn+1)[-(ncorn+1)])*pi))
corners=corners*min(2/diff(apply(corners,2,range)))
corners[,2]=corners[,2]-mean(range(corners[,2]))

xy=t%*%corners

grid=if(ncorn==3)do.call(rbind.data.frame,apply(simplify=F,rbind(c(1,2,3,2),c(1,3,2,3),c(2,1,3,1)),1,\(x)cbind(
  seq(corners[x[1],1],corners[x[2],1],,11),
  seq(corners[x[1],2],corners[x[2],2],,11),
  seq(corners[x[3],1],corners[x[4],1],,11),
  seq(corners[x[3],2],corners[x[4],2],,11)
)))else if(ncorn==4)do.call(rbind.data.frame,apply(simplify=F,rbind(c(1,2,4,3),c(1,4,2,3)),1,\(x)cbind(
  seq(corners[x[1],1],corners[x[2],1],,11),
  seq(corners[x[1],2],corners[x[2],2],,11),
  seq(corners[x[3],1],corners[x[4],1],,11),
  seq(corners[x[3],2],corners[x[4],2],,11)
)))else rbind.data.frame(cbind(corners,rbind(corners[-1,],corners[1,])),cbind(corners,matrix(colMeans(corners),ncorn,2,T)))

seg=as.data.frame(cbind(xy[rep(1:nrow(xy),each=2),],xy[apply(as.matrix(dist(mult)),1,\(x)order(x)[2:3]),]))
k=as.factor(cutree(hclust(dist(mult)),32))

set.seed(0)
hue=seq(0,360,,nlevels(k)+1)%>%head(-1)%>%sample()
pal1=hex(colorspace::HSV(hue,.6,1))
pal2=hex(colorspace::HSV(hue,.3,1))

angle=head(seq(360,0,length.out=ncorn+1),-1)
angle=ifelse(angle>90&angle<=270,angle+180,angle)

ggplot(as.data.frame(xy),aes(x=V1,y=V2))+
geom_polygon(data=as.data.frame(corners),fill="gray25")+
(if(ncorn>=5)geom_text(data=as.data.frame(corners),aes(x=1.04*V1,y=1.04*V2),label=colnames(t),size=3.2,angle=angle,color="gray85") # use rotated labels
else geom_text(data=as.data.frame(corners),aes(x=V1,y=1.03*V2),vjust=(1-corners[,2])/2,hjust=(1+corners[,1])/2,label=colnames(t),size=3.2,color="gray85"))+ # don't rotate labels
geom_segment(data=grid,aes(x=V1,y=V2,xend=V3,yend=V4),color="gray30",size=.4)+
ggforce::geom_mark_hull(aes(group=!!k,color=!!k,fill=!!k),concavity=1000,radius=unit(.15,"cm"),expand=unit(.15,"cm"),alpha=.15,size=.1)+
geom_segment(data=seg,aes(x=V1,y=V2,xend=V3,yend=V4),color="gray10",size=.25)+
geom_point(aes(color=k),size=.5)+
geom_text(aes(label=rownames(xy),color=!!k),size=2.2,vjust=-.6)+
coord_fixed(xlim=c(-1,1),ylim=c(-1,1))+
scale_fill_manual(values=pal1)+
scale_color_manual(values=pal2)+
theme(
  axis.text=element_blank(),
  axis.ticks=element_blank(),
  axis.title=element_blank(),
  legend.position="none",
  panel.background=element_rect(fill="gray20"),
  panel.grid=element_blank(),
  plot.background=element_rect(fill="gray20",color=NA,size=0),
  plot.margin=margin(0,0,0,0)
)

ggsave("1.png",width=7,height=7)

Or here's another version that uses Voronoi tesselation to plot the points ( https://ggforce.data-imaginist.com/reference/geom_delvor.html ):

t=read.table("https://pastebin.com/raw/CeLAEiAq")
t=distinct(t[,-1]) # geom_voronoi_tile doesn't handle a large number of overlapping points
pop=t[,1]
t=as.matrix(t[,-1])

ncorn=ncol(t)
start=ifelse(ncorn==4,.25,0)
corners=sapply(c(sin,cos),\(x)x((start+seq(0,2,,ncorn+1)[-(ncorn+1)])*pi))
corners=corners*min(2/diff(apply(corners,2,range))) # resize so bigger one of width and height is 2
corners[,2]=corners[,2]-mean(range(corners[,2])) # center vertically

xy=as.data.frame(t%*%corners)

# # use a simple grid with line from each corner to center for a plot with more than 3 corners
# grid=rbind.data.frame(cbind(corners,rbind(corners[-1,],corners[1,])),cbind(corners,matrix(colMeans(corners),ncorn,2,T)))

# use a grid with 10 subdivisions per side for a triangle plot
grid=do.call(rbind.data.frame,apply(simplify=F,rbind(c(1,2,3,2),c(1,3,2,3),c(2,1,3,1)),1,\(x)cbind(
  seq(corners[x[1],1],corners[x[2],1],,11),
  seq(corners[x[1],2],corners[x[2],2],,11),
  seq(corners[x[3],1],corners[x[4],1],,11),
  seq(corners[x[3],2],corners[x[4],2],,11)
)))

centers=data.frame(aggregate(xy,list(pop),mean),row.names=1)

set.seed(0)
color=as.factor(sample(length(unique(pop))))
cl=rbind(c(60,80),c(25,95),c(30,70),c(70,50),c(60,100),c(20,50),c(15,40))
hues=max(ceiling(length(color)/nrow(cl)),8)
pal1=as.vector(apply(cl,1,\(x)hcl(seq(15,375,,hues+1)[-(hues+1)],x[1],x[2])))
pal2=as.vector(apply(cl,1,\(x)hcl(seq(15,375,,hues+1)[-(hues+1)],if(x[2]>=60).5*x[1]else .1*x[1],if(x[2]>=60).2*x[2]else 95)))

xy=xy+runif(nrow(xy)*2)/1e3 # add a small random factor to prevent errors because of overlapping points

ggplot(xy,aes(V1,V2))+
geom_segment(data=grid,aes(V1,V2,xend=V3,yend=V4),color="gray85",size=.3)+
ggforce::geom_voronoi_tile(aes(group=0,fill=color[as.factor(pop)],color=color[as.factor(pop)]),size=.07,max.radius=.055)+ # `group=0` is just an arbitrary constant
# ggrepel::geom_label_repel(data=centers,aes(V1,V2,color=color,fill=color),label=rownames(centers),max.overlaps=Inf,point.size=0,size=2.3,alpha=.8,label.r=unit(.1,"lines"),label.padding=unit(.1,"lines"),label.size=.1,box.padding=0,segment.size=.3)+
geom_label(data=centers,aes(V1,V2,color=color,fill=color),label=rownames(centers),size=2.3,alpha=.8,label.r=unit(.1,"lines"),label.padding=unit(.1,"lines"),label.size=.1)+
coord_fixed(xlim=c(-1.08,1.08),ylim=c(-1.08,1.08),expand=F)+
scale_fill_manual(values=pal1)+
scale_color_manual(values=pal2)+
theme(
  axis.text=element_blank(),
  axis.ticks=element_blank(),
  axis.title=element_blank(),
  legend.position="none",
  panel.background=element_rect(fill="white")
)

ggsave("1.png",width=7,height=7)