R中的ggtern等高线图[关闭]

我有这个数据文件 https://www.dropbox.com/s/xk8zyu9f0rw77eu/N90_p_0.350_eta_90_W12.dat?dl=0有足够的数据点让我在三元图中绘制“热图”。 （这并不是真正的热图，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：

我想使用以下方法得到类似的东西ggtern:

我的问题是：我怎样才能得到类似第二个数字的东西ggtern?

Edit 1: 抱歉，文件名有误。我修复了文件名。 数据文件包含太多数据点，我无法直接将它们粘贴到此处。

第二张图是由第三方Matlab包生成的ternplot。我想要一个具有离散线的三元等高线图，而不是我的第一个图中的热图。更具体地说，我想指定等高线列表，例如W12=0.05,0.1,0.15,...。我玩过geom_density_tern and geom_interpolate_tern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]); 

where X,Y,1-X-Y指定绘图上的坐标，data存储值，向量指定轮廓的值。

WDG，我对 ggtern 做了一些小的更改，以便更好地处理此类建模，该模型刚刚提交给 CRAN，因此应该在第二天左右可用。在此期间，您可以从我的 BitBucket 帐户中下载源代码：https://bitbucket.org/nicholasehamilton/ggtern https://bitbucket.org/nicholasehamilton/ggtern

不管怎样，这是源代码，它可以从 ggtern 版本 2.1.2 开始工作。

我已经包含了下面的点（具有温和的 alpha 值），以便人们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示例 matlab 等高线图，请尝试以下操作：

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：