参数化 ggplot2 直方图/密度 aes 函数找不到对象

Question

我创建了一个直方图/密度图函数，我希望 y 轴为 count 而不是密度，但在参数化其 binwidth 时遇到问题。

我使用基于http://docs.ggplot2.org/current/geom_histogram.html 的示例来说明我的尝试。

这是成功的 plotMovies1 函数。我按照引用的url 使 y 轴 ..count.. 而不是 ..density.. 请注意，它在两个地方使用了硬编码的 .5 binwidth ，这就是我要参数化的...

# I want y axis as count, rather than density, and followed
# https://stat.ethz.ch/pipermail/r-help/2011-June/280588.html
plotMovies1 <- function() {
  m <- ggplot(movies, aes(x = rating))
  m <- m + geom_histogram(binwidth = .5)
  m <- m + geom_density(aes(y = .5 * ..count..))
}

我第一次失败天真地尝试在 plotMovies2 中的本地 bw 中参数化 binwidth ...

# Failed first attempt to parameterize binwidth
plotMovies2 <- function() {
  bw <- .5
  m <- ggplot(movies, aes(x = rating))
  m <- m + geom_histogram(binwidth = bw)
# Error in eval(expr, envir, enclos) : object 'bw' not found 
  m <- m + geom_density(aes(y = bw * ..count..))
}
> print(plotMovies2())
Error in eval(expr, envir, enclos) : object 'bw' not found

我在https://github.com/hadley/ggplot2/issues/743 看到关于将本地环境传递给 ggplot 中的 aes 的讨论，但 plotMovies3 也以同样的方式失败，未能找到 bw 对象。 ..

# Failed second attempt to parameterize binwidth, even after establishing
# aes environment, per https://github.com/hadley/ggplot2/issues/743
plotMovies3 <- function() {
  bw <- .5
  m <- ggplot(movies, aes(x = rating), environment = environment())
  m <- m + geom_histogram(binwidth = bw)
# Error in eval(expr, envir, enclos) : object 'bw' not found 
  m <- m + geom_density(aes(y = bw * ..count..))
}
> print(plotMovies3())
Error in eval(expr, envir, enclos) : object 'bw' not found

我终于尝试设置一个全局，但它仍然未能找到对象...

# Failed third attempt using global binwidth
global_bw <<- .5
plotMovies4 <- function() {
  m <- ggplot(movies, aes(x = rating), environment = environment())
  m <- m + geom_histogram(binwidth = global_bw)
# Error in eval(expr, envir, enclos) : object 'global_bw' not found 
  m <- m + geom_density(aes(y = global_bw * ..count..))
}
> print(plotMovies4())
Error in eval(expr, envir, enclos) : object 'global_bw' not found

鉴于 plotMovies3 和 plotMovies4，我猜这不是一个简单的环境问题。谁能阐明我如何解决这个问题？同样，我的目标是能够创建一个直方图/密度图函数，其中

1. 它的 y 轴是计数而不是密度，并且
2. 它的 binwidth 可以参数化（例如，用于操作）

Answer 1

这是对 mts 的跟进。它旨在作为一个长评论：首先，数据集是通过加载library("ggplot2movies") 获得的。其次，循环遍历binw 的多个值以生成一系列要一起使用的数字可能是有意义的，例如动画。所以下面的代码所做的只是为了这个目的将mts的代码放入一个循环中。确实是微不足道的贡献。

    ### Data
    library("ggplot2movies")

    ### Histograms
    ggplotMovieHistogram <- function(binw = 0.5) {
        require('ggplot2movies')
        p <- ggplot(movies, aes(x = rating)) + 
            geom_histogram(binwidth = binw)
        wa <- density(x = movies$rating, bw = binw)
        wa <- as.data.frame(cbind(xvals = wa$x, yvals = wa$y * wa$n * binw))
        p <- p + geom_point(data = wa, aes(x = xvals, y = yvals))
        return(p)
    }

    ggsaveMovieHistogram <- function(binw = 0.5, file = 'test.pdf') {
        pdf(file, width = 8, height = 8)
            print(ggplotMovieHistogram(binw = binw))
        dev.off()
    }

    for(i in seq(0.2, 0.8, by = 0.2)) {
        ggsaveMovieHistogram(binw = i, 
                    file = paste0('ggplot-barchart-loop-histogram-', 
                                  format(i, decimal.mark = '-'), 
                                  '.pdf'))
    }


    ### Densities
    library("ggplot2movies")
    ggplotMovieDensity <- function(binw = 0.5) {
        require('ggplot2movies')
        p <- ggplot(movies, aes(x = rating)) + 
            geom_density(aes(y = 0.5 * ..count..))
        wa <- density(x = movies$rating, bw = binw)
        wa <- as.data.frame(cbind(xvals = wa$x, yvals = wa$y * wa$n * binw))
        p <- p + geom_point(data = wa, aes(x = xvals, y = yvals))
        return(p)
    }

    ggsaveMovieDensity <- function(binw = 0.5, file = 'test.pdf') {
        pdf(file, width = 8, height = 8)
            print(ggplotMovieDensity(binw = binw))
        dev.off()
    }

    for(i in seq(0.2, 0.8, by = 0.2)) {
        ggsaveMovieDensity(binw = i, 
                    file = paste0('ggplot-barchart-loop-density-', 
                                  format(i, decimal.mark = '-'), 
                                  '.pdf'))
    }

Answer 2

另一种方法是使用带有 aes_string 的预定义 bin。然后可以通过具有可变 binwidth 的循环创建直方图：

bins <<- list()
bins[["Variable1"]] <- 2
bins[["Variable2"]] <- 0.5
bins[["Variable3"]] <- 1
print(ggplot(movies, aes(x = rating))+
aes_string(x = "rating", y=paste("..density..*",bins[[i]],sep="")), na.rm=TRUE, position='dodge', binwidth=bins[[i]])

Answer 3

绝不漂亮，但如果您需要解决方法，您可以使用常规的density 函数

plotMovies5 <- function(binw=0.5) {
  m <- ggplot(movies, aes(x = rating))
  m <- m + geom_histogram(binwidth = binw)
  wa <- density(x=movies$rating, bw = binw)
  wa <- as.data.frame(cbind(xvals = wa$x, yvals = wa$y * wa$n * binw))
  m <- m + geom_point(data = wa, aes(x = xvals, y = yvals))
}
print(plotMovies5(binw=0.25))

请注意，您仍然需要对变量进行一些修改，因为密度估计值并不完全相等，如下所示：

binw = 0.5
m <- ggplot(movies, aes(x = rating))
m <- m + geom_density(aes(y = 0.5 * ..count..))
wa <- density(x=movies$rating, bw = binw)
wa <- as.data.frame(cbind(xvals = wa$x, yvals = wa$y * wa$n * binw))
m <- m + geom_point(data = wa, aes(x = xvals, y = yvals))
m