ggplot2直方图中每个方面的不同断点

一个 ggplot2 挑战的 latticist 需要帮助：在直方图中请求变量每面中断的语法是什么？

library(ggplot2)
d = data.frame(x=c(rnorm(100,10,0.1),rnorm(100,20,0.1)),par=rep(letters[1:2],each=100))
# Note: breaks have different length by par
breaks = list(a=seq(9,11,by=0.1),b=seq(19,21,by=0.2))
ggplot(d, aes(x=x) ) + 
  geom_histogram() + ### Here the ~breaks should be added
  facet_wrap(~ par,  scales="free")

正如所指出的jucor https://github.com/xfim/ggmcmc/pull/17#issuecomment-19899183, here https://groups.google.com/forum/#!topic/ggplot2/rhPWQEFMx6A更多解决方案。

根据特殊要求，并展示为什么我不是 ggplot 的忠实粉丝，lattice version

library(lattice)
d = data.frame(x=c(rnorm(100,10,0.1),rnorm(100,20,0.1)),par=rep(letters[1:2],each=100))
# Note: breaks have different length by par
myBreaks = list(a=seq(8,12,by=0.1),b=seq(18,22,by=0.2))
histogram(~x|par,data=d,
          panel = function(x,breaks,...){
            # I don't know of a generic way to get the 
            # grouping variable with histogram, so 
            # this is not very generic
            par = levels(d$par)[which.packet()]
            breaks = myBreaks[[par]]
            panel.histogram(x,breaks=breaks,...)
          },
          breaks=NULL, # important to force per-panel compute
          scales=list(x=list(relation="free")))

这是一种替代方案：

hls <- mapply(function(x, b) geom_histogram(data = x, breaks = b), 
              dlply(d, .(par)), myBreaks)
ggplot(d, aes(x=x)) + hls + facet_wrap(~par, scales = "free_x")

如果需要缩小x的范围，那么

hls <- mapply(function(x, b) {
  rng <- range(x$x)
  bb <- c(rng[1], b[rng[1] <= b & b <= rng[2]], rng[2])
  geom_histogram(data = x, breaks = bb, colour = "white")
}, dlply(d, .(par)), myBreaks)

ggplot(d, aes(x=x)) + hls + facet_wrap(~par, scales = "free_x")