ユーザーの皆さん、三角プロット（ "vcd"）のヒントをいくつか教えてください。
私はこのデータフレームを持っています：
a <- c(0.1, 0.5, 0.5, 0.6, 0.2, 0, 0, 0.004166667, 0.45)
b <- c(0.75,0.5,0,0.1,0.2,0.951612903,0.918103448,0.7875,0.45)
c <- c(0.15,0,0.5,0.3,0.6,0.048387097,0.081896552,0.208333333,0.1)
d <- c(500,2324.90,2551.44,1244.50, 551.22,-644.20,-377.17,-100, 2493.04)
df <- data.frame(a, b, c, d)
そして私は三角プロットを構築しています：
ternaryplot(df[,1:3], df$d)
d連続変数をマッピングして、これと同様の結果を得るにはどうすればよいですか？
同様の問題を解決する必要がありました。これは、三角グラフのggplot2の拡張としてパッケージを作成するための触媒でした。パッケージはCRANで入手できます。
この問題の出力：
上記を構築するためのコード
#Orignal Data as per Question
a <- c(0.1, 0.5,0.5, 0.6, 0.2, 0 , 0 , 0.004166667, 0.45)
b <- c(0.75,0.5,0 , 0.1, 0.2, 0.951612903,0.918103448, 0.7875 , 0.45)
c <- c(0.15,0 ,0.5, 0.3, 0.6, 0.048387097,0.081896552, 0.208333333, 0.10)
d <- c(500,2324.90,2551.44,1244.50, 551.22,-644.20,-377.17,-100, 2493.04)
df <- data.frame(a, b, c, d)
#For labelling each point.
df$id <- 1:nrow(df)
#Build Plot
ggtern(data=df,aes(x=c,y=a,z=b),aes(x,y,z)) +
stat_density2d(geom="polygon",
n=400,
aes(fill=..level..,
weight=d,
alpha=abs(..level..)),
binwidth=100) +
geom_density2d(aes(weight=d,color=..level..),
n=400,
binwidth=100) +
geom_point(aes(fill=d),color="black",size=5,shape=21) +
geom_text(aes(label=id),size=3) +
scale_fill_gradient(low="yellow",high="red") +
scale_color_gradient(low="yellow",high="red") +
theme_tern_rgbw() +
theme(legend.justification=c(0,1), legend.position=c(0,1)) +
guides(fill = guide_colorbar(order=1),
alpha= guide_legend(order=2),
color="none") +
labs( title= "Ternary Plot and Filled Contour",
fill = "Value, V",alpha="|V - 0|")
#Save Plot
ggsave("TernFilled.png")
これはおそらくこれを行うための最もエレガントな方法ではありませんが、機能します（最初から使用せternaryplotずに：それを行う方法を理解できませんでした）。
a<- c (0.1, 0.5, 0.5, 0.6, 0.2, 0, 0, 0.004166667, 0.45)
b<- c (0.75,0.5,0,0.1,0.2,0.951612903,0.918103448,0.7875,0.45)
c<- c (0.15,0,0.5,0.3,0.6,0.048387097,0.081896552,0.208333333,0.1)
d<- c (500,2324.90,2551.44,1244.50, 551.22,-644.20,-377.17,-100, 2493.04)
df<- data.frame (a, b, c)
# First create the limit of the ternary plot:
plot(NA,NA,xlim=c(0,1),ylim=c(0,sqrt(3)/2),asp=1,bty="n",axes=F,xlab="",ylab="")
segments(0,0,0.5,sqrt(3)/2)
segments(0.5,sqrt(3)/2,1,0)
segments(1,0,0,0)
text(0.5,(sqrt(3)/2),"c", pos=3)
text(0,0,"a", pos=1)
text(1,0,"b", pos=1)
# The biggest difficulty in the making of a ternary plot is to transform triangular coordinates into cartesian coordinates, here is a small function to do so:
tern2cart <- function(coord){
coord[1]->x
coord[2]->y
coord[3]->z
x+y+z -> tot
x/tot -> x # First normalize the values of x, y and z
y/tot -> y
z/tot -> z
(2*y + z)/(2*(x+y+z)) -> x1 # Then transform into cartesian coordinates
sqrt(3)*z/(2*(x+y+z)) -> y1
return(c(x1,y1))
}
# Apply this equation to each set of coordinates
t(apply(df,1,tern2cart)) -> tern
# Intrapolate the value to create the contour plot
resolution <- 0.001
require(akima)
interp(tern[,1],tern[,2],z=d, xo=seq(0,1,by=resolution), yo=seq(0,1,by=resolution)) -> tern.grid
# And then plot:
image(tern.grid,breaks=c(-1000,0,500,1000,1500,2000,3000),col=rev(heat.colors(6)),add=T)
contour(tern.grid,levels=c(-1000,0,500,1000,1500,2000,3000),add=T)
points(tern,pch=19)
私の以前の答えは密度推定を使用しました。これは線形回帰を使用したものです。
df <- data.frame(a, b, c, d)
ggtern(df,aes(a,c,b)) +
geom_interpolate_tern(aes(value=d,fill=..level..),
binwidth=500,
colour="white") +
geom_point(aes(fill=d),color="black",shape=21,size=3) +
scale_fill_gradient(low="yellow",high="red") +
theme(legend.position=c(0,1),legend.justification=c(0,1)) +
labs(fill="Value, d")
ヒントをありがとうございます。これが私の最終結果です。
#Rename header
names(SI) [6] <- "WATER%"
names(SI) [7] <- "VEGETATION%"
names(SI) [8] <- "SOIL%"
#pdf(file="prova_ternary12.pdf", width = 5, height =5)
##++++++++++++++++++++++++++++++
install.packages("colourschemes", repos="http://R-Forge.R-project.org")
library(colourschemes)
rs = rampInterpolate ( limits =c(-0.8 , 0.8),
ramp = c("red4", "red", "orangered", "orange", "darkgoldenrod1", "white",
"cyan2", "blue", "darkblue", "blueviolet", "purple3") )
rs(-0.8)
rs(-0.6000)
rs(-0.4)
rs(-0.2)
rs(0)
rs(0.2)
rs(0.4)
rs(0.6000)
rs(0.8000)
#++++++++++++++++++++++++++++++
#TERNARYPLOT (vcd)
library(vcd)
png(file="ternary.png", width=800, height=800)
ternaryplot(
SI[,6:8],
bg = "lightgray",
grid_color = "black",
labels_color = "black",
dimnames_position = c("corner"),
#dimnames = 10,
newpage = T,
#dimnames_color = "green",
border = "black",
pop=T,
#SI$MEAN_b2b6.tm,
col=rs(SI$MEAN_b2b6.TM_V2),
#col = ifelse(SI$MEAN_b1b6.tm > 0, "blue", "#cd000020"),
pch=13, cex=.4, prop_size = F,
labels = c("outside"),
#size=SI$MEAN_b1b6.tm,
main="b4b6 -TM data-")
