使用stat_summary_hex以离散色阶显示最常见的值

问题描述

我有一个10k行和3列的数据框：xpos，ypos和cluster（cluster是一个从0到9的数字）：

我想根据最频繁的颜色显示六边形的六角形图

到目前为止，我得到了：

  library（ggplot2）
 library（hexbin）
 ggplot（clusters，aes（x = xpos，y = ypos，z = cluster））+ stat_summary_hex（fun.x = mode）
  

我想给我的是我想要的东西（即填充每个六边形的颜色从0到9），但色彩比例连续出现，我无法弄清楚如何使用离散色彩。

对于额外的上下文，这里是数据的底层混乱视图，我试图平滑通过使用六边形：

  qplot（data = clusters，xpos，ypos，color = factor（cluster））
  

stat_summary_hex（fun.x = mode）在做什么，但我是很确定这不是你的想法（ mode 给出对象的存储模式，而不是统计模式， fun.x 不匹配 stat_summary_hex 的任何正式参数）。尝试这个。它列出了每个箱中的观察值，并且拉出了最大值的标签。

  ggplot（clusters，aes（x = xpos，y = ypos，z = cluster））+ stat_summary_hex（fun = function（x）{
 tab<  -  table（x）
 names（tab）[which.max（tab）] 
}）
  

I have a data frame with 10k rows and 3 columns: xpos, ypos and cluster (cluster is a number from 0 to 9) here: http://pastebin.com/NyQw29tb

I would like to show a hex plot with each hexagon colored according to the most-frequent cluster within that hexagon.

So far I've got:

 library(ggplot2)
 library(hexbin)
 ggplot(clusters, aes(x=xpos, y=ypos, z=cluster)) + stat_summary_hex(fun.x=mode)

Which I think is giving me what I want (i.e. is filling in every hexagon with a color from 0 to 9), but the color scale appears continuous, and I can't figure out how to make it use a discrete one.

For extra context, here's the underlying, messier view of the data, which I'm trying to smooth out by using hexagons:

 qplot(data=clusters, xpos, ypos, color=factor(cluster))

解决方案

I don't knw what your stat_summary_hex(fun.x=mode) is doing, but I'm pretty sure it's not what you think (mode gives the storage mode of an object, not the statistical mode, and fun.x doesn't match any formal argument of stat_summary_hex). Try this. It tabulates the observations in each bin, and pulls out the label of the maximum count.

ggplot(clusters, aes(x=xpos, y=ypos, z=cluster)) + stat_summary_hex(fun = function(x) {
    tab <- table(x)
    names(tab)[which.max(tab)]
})

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