Question

我有这个data file有足够的数据点供我在三元图中绘制“热图”。（它不是真正的热图，只是具有足够数据点的散点图）

library(ggtern)
library(reshape2)

N=90
trans.prob = as.matrix(read.table("./N90_p_0.350_eta_90_W12.dat",fill=TRUE))
colnames(trans.prob) = NULL

# flatten trans.prob for ternary plot
flattened.tb = melt(trans.prob,varnames = c("x","y"),value.name = "W12")
# delete rows with NA
flattened.tb = flattened.tb[complete.cases(flattened.tb),]
flattened.tb$x = (flattened.tb$x-1)/N
flattened.tb$y = (flattened.tb$y-1)/N
flattened.tb$z = 1 - flattened.tb$x - flattened.tb$y

ggtern(data = flattened.tb, aes(x=x,y=y,z=z)) +
  geom_point(size=1, aes(color=W12)) +
  theme_bw() +
  scale_color_gradient2(low = "green", mid = "yellow", high = "red")

这是我得到的：

我希望使用ggtern获得类似以下内容：

我的问题是：如何使用ggtern获得第二个数字？

编辑1 ：抱歉文件名中有拼写错误。我修改了文件名。数据文件包含太多数据点，我可以直接将它们粘贴到这里。

第二个数字是由第三方Matlab软件包ternplot生成的。我想要一个三元等高线图，它在我的第一个图中有离散线而不是热图。更具体地说，我想指定一个轮廓线列表，例如W12=0.05,0.1,0.15,...。我和geom_density_tern和geom_interpolate_tern玩了好几个小时，但仍然不知道如何得到我想要的东西。

MATLAB代码是：

[HCl, Hha, cax] = terncontour(X,Y,1-X-Y,data,[0.01,0.1,0.2,0.3,0.4,0.5]);

其中X,Y,1-X-Y指定绘图上的坐标，data存储值，矢量指定轮廓的值。

Answer 1

这看起来并不像你的例子那么漂亮，但希望它能让你更接近你想要的地方：

flattened.tb$a <- 0
flattened.tb$a[flattened.tb$W12 > 0.04 & flattened.tb$W12 < .05] <- 1

flattened.tb$b <- 0
flattened.tb$b[flattened.tb$W12 > 0.05 & flattened.tb$W12 < .06] <- 1

flattened.tb$c <- 0
flattened.tb$c[flattened.tb$W12 > 0.07 & flattened.tb$W12 < .08] <- 1

flattened.tb$d <- 0
flattened.tb$d[flattened.tb$W12 > 0.09 & flattened.tb$W12 < .1] <- 1


options("tern.discard.external" = F)   
ggtern(data = flattened.tb, aes(x, y, z)) +
  geom_line(aes(a),color="red",linetype=1) + 
  geom_line(aes(b),color="blue",linetype=1) +
  geom_line(aes(c),color="yellow",linetype=1) +
  geom_line(aes(d),color="green",linetype=1) +
  theme_bw()

情节只是需要一个漂亮的。我不能说哪些数据区域最适合绘图。

Answer 2

WDG，我对ggtern进行了一些小改动，以便更好地处理这种刚刚提交给CRAN的建模类型，因此应该在第二天左右提供。在此期间，您可以从我的BitBucket帐户下载源代码：https://bitbucket.org/nicholasehamilton/ggtern

无论如何，这是源代码，它将在ggtern版本2.1.2中起作用。

我已经包含了下面的点（具有温和的alpha值），因此可以观察插值几何的代表性：

library(ggtern)
library(reshape2)

N=90
trans.prob = as.matrix(read.table("~/Downloads/N90_p_0.350_eta_90_W12.dat",fill=TRUE))
colnames(trans.prob) = NULL

# flatten trans.prob for ternary plot
flattened.tb = melt(trans.prob,varnames = c("x","y"),value.name = "W12")
# delete rows with NA
flattened.tb   = flattened.tb[complete.cases(flattened.tb),]
flattened.tb$x = (flattened.tb$x-1)/N
flattened.tb$y = (flattened.tb$y-1)/N
flattened.tb$z = 1 - flattened.tb$x - flattened.tb$y

############### MODIFIED CODE BELOW ###############

#Remove the (trivially) Negative Concentrations
flattened.tb = subset(flattened.tb,z >= 0)

#Plot a series of plots in increasing polynomial degree
plots = lapply(seq(3,18,by=3),function(x){
  degree = x
  breaks = seq(0.025,0.575,length.out = 10)
  base   = ggtern(data = flattened.tb, aes(x=x,y=y,z=z)) +
    geom_point(size=1, aes(color=W12),alpha=0.05) +
    geom_interpolate_tern(aes(value=W12,color=..level..),
                          base = 'identity',method = glm,
                          formula = value ~ polym(x,y,degree = degree,raw=T),
                          n = 150, breaks = breaks) + 
    theme_bw() +
    theme_legend_position('topleft') + 
    scale_color_gradient2(low = "green", mid = "yellow", high = "red",
                          midpoint = mean(range(flattened.tb$W12)))+
    labs(title=sprintf("Polynomial Degree %s",degree))
  base
})

#Arrange the plots using grid.arrange
png("~/Desktop/output.png",width=700,height=900)
  grid.arrange(grobs = plots,ncol=2)
garbage <- dev.off()

这会产生以下输出：

为了生成更接近颜色和方向的图表作为样本matlab等高线图，请尝试以下方法：

plots = lapply(seq(3,18,by=3),function(x){
  degree = x
  breaks = seq(0.025,0.575,length.out = 10)
  base   = ggtern(data = flattened.tb, aes(x=z,y=y,z=x)) +
    geom_point(size=1, aes(color=W12),alpha=0.05) +
    geom_interpolate_tern(aes(value=W12,color=..level..),
                          base = 'identity',method = glm,
                          formula = value ~ polym(x,y,degree = degree,raw=T),
                          n = 150, breaks = breaks) + 
    theme_bw() +
    theme_legend_position('topleft') + 
    scale_color_gradient2(low = "darkblue", mid = "green", high = "darkred",
                          midpoint = mean(range(flattened.tb$W12)))+
    labs(title=sprintf("Polynomial Degree %s",degree))
  base
})
png("~/Desktop/output2.png",width=700,height=900)
  grid.arrange(grobs = plots,ncol=2)
garbage <- dev.off()

这会产生以下输出：

R

2 个答案: