R ggplot2：使用stat_summary（均值）和对数比例 [英] R ggplot2: using stat_summary (mean) and logarithmic scale

问题描述

随着时间的推移，我有很多测量数据，我想在R中绘制它们。下面是我的数据样本。我对4个时间点中的每一个都有6次测量：

 值<-c（1012.0,1644.9,837.0,1200.9 ，1652.0,981.5，
 2236.9,1697.5,2087.7,1500.8，
 2789.3,1502.9,2051.3,3070.7,3105.4，
 2692.5，1488.5，1978.1,1925.4,1524.3，
 2772.0 （c（0,12,24,72），c（6,6,6）））
  
 
 $ b这些数据的规模是任意的，实际上我将对它进行规范化，以使t = 0的平均值为1。 
  norm < -  values / mean（values [time == 0]）
  
到目前为止这么好。使用 ggplot ，我绘制了各个点以及在每个时间点通过平均线的线。
  require（ggplot2）
p < -  ggplot（data = data.frame（time，norm），mapping = aes（x = time，y = norm））+ 
 stat_summary（fun.y = mean，geom =line，mapping = aes（group = 1））+ 
 geom_point（）
  
但是，现在我想要应用对数刻度，这就是我的麻烦开始的地方。当我这样做时：
 
 
  q < -  ggplot（data = data.frame（time，norm），mapping = aes（x = time，y = norm））+ 
 stat_summary（fun.y = mean，geom =line，mapping = aes（group = 1））+ 
 geom_point（）+ 
 scale_y_log2 （）
  
该行在t = 0时不会经过0，正如您所期望的那样，因为log 1）== 0.相反，这条线横穿y轴略低于0。显然， ggplot 会应用log变换后的平均值，它给出一个不同的结果。我希望它能够在日志转换之前使用 。    >首先应用平均值？有没有更好的方法来创建此图表？
解决方案
  scale_y_log2（）将首先进行转换，然后计算几何。
 
 
 
  coord_trans（）会做相反的处理：计算
 
 
所以你需要 coord_trans（ytrans =log2），而不是 scale_y_log2（） 
 
I have a bunch of measurements over time and I want to plot them in R. Here is a sample of my data. I've got 6 measurements for each of 4 time points:
values <- c (1012.0, 1644.9, 837.0, 1200.9, 1652.0, 981.5, 
    2236.9, 1697.5, 2087.7, 1500.8,
    2789.3, 1502.9, 2051.3, 3070.7, 3105.4, 
    2692.5, 1488.5, 1978.1, 1925.4, 1524.3,
    2772.0, 1355.3, 2632.4, 2600.1)
time <- factor (rep (c(0, 12, 24, 72), c(6, 6, 6, 6)))
The scale of these data is arbitrary, and in fact I'm going to normalize it so that the average of t=0 is 1.
norm <- values / mean (values[time == 0])
So far so good. Using ggplot, I plot both the individual points, as well as a line that goes through the average at each time point:
require (ggplot2)
p <- ggplot(data = data.frame(time, norm), mapping = aes (x = time, y = norm)) +
    stat_summary (fun.y = mean, geom="line", mapping = aes (group = 1)) +
    geom_point()
However, now I want to apply a logarithmic scale, and this is where my trouble starts. When I do:
q <- ggplot(data = data.frame(time, norm), mapping = aes (x = time, y = norm)) +
    stat_summary (fun.y = mean, geom="line", mapping = aes (group = 1)) +
    geom_point() + 
    scale_y_log2()
The line does NOT go through 0 at t=0, as you would expect because log (1) == 0. Instead the line crosses the y-axis slightly below 0. Apparently, ggplot applies the mean after log transformation, which gives a different result. I want it to take the mean before log transformation.

How can I tell ggplot to apply the mean first? Is there a better way to create this chart?
解决方案
scale_y_log2() will do the transformation first and then calculate the geoms.

coord_trans() will do the opposite: calculate the geoms first, and the transform the axis.

So you need coord_trans(ytrans = "log2") instead of scale_y_log2()

                        
这篇关于R ggplot2：使用stat_summary（均值）和对数比例的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！