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我可以告诉 ggpairs 使用对数刻度吗？

发布于 2024-11-27 22:48:38 字数 60 浏览 0 评论 0原文

我可以向 GGally 包中的 ggpairs 函数提供一个参数，以便对某些而不是全部变量使用对数刻度吗？

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一念一轮回 2024-12-04 22:48:38

您无法提供这样的参数（原因是创建散点图的函数是在没有比例的情况下预定义的，请参阅ggally_points），但您可以随后使用getPlot更改比例代码>和putPlot。例如：

custom_scale <- ggpairs(data.frame(x=exp(rnorm(1000)), y=rnorm(1000)),
upper=list(continuous='points'), lower=list(continuous='points'))
subplot <- getPlot(custom_scale, 1, 2) # retrieve the top left chart
subplotNew <- subplot + scale_y_log10() # change the scale to log
subplotNew$type <- 'logcontinuous' # otherwise ggpairs comes back to a fixed scale
subplotNew$subType <- 'logpoints'
custom_scale <- putPlot(custom_fill, subplotNew, 1, 2)

You can't provide the parameter as such (a reason is that the function creating the scatter plots is predefined without scale, see ggally_points), but you can change the scale afterward using getPlot and putPlot. For instance:

custom_scale <- ggpairs(data.frame(x=exp(rnorm(1000)), y=rnorm(1000)),
upper=list(continuous='points'), lower=list(continuous='points'))
subplot <- getPlot(custom_scale, 1, 2) # retrieve the top left chart
subplotNew <- subplot + scale_y_log10() # change the scale to log
subplotNew$type <- 'logcontinuous' # otherwise ggpairs comes back to a fixed scale
subplotNew$subType <- 'logpoints'
custom_scale <- putPlot(custom_fill, subplotNew, 1, 2)

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半﹌身腐败 2024-12-04 22:48:38

这本质上与 Jean-Robert 的答案相同，但看起来更简单（平易近人）。我不知道这是否是一个新功能，但看起来您不再需要使用 getPlot 或 putPlot 。

custom_scale[1,2]<-custom_scale[1,2] + scale_y_log10() + scale_x_log10()

这是一个将其应用于大矩阵的函数。提供绘图中的行数和绘图名称。

scalelog2<-function(x=2,g){  #for below diagonal
 for (i in 2:x){ 
    for (j in 1:(i-1)) { 
      g[i,(j)]<-g[i,(j)] + scale_x_continuous(trans='log2') +
scale_y_continuous(trans='log2')
                        } } 
 for (i in 1:x){  #for the bottom row 
      g[(x+1),i]<-g[(x+1),i] + scale_y_continuous(trans='log2') 
                       } 
 for (i in 1:x){ #for the diagonal
      g[i,i]<-g[i,i]+ scale_x_continuous(trans='log2')  } 
  return(g) }

This is essentially the same answer as Jean-Robert but looks much more simple (approachable). I don't know if it is a new feature but it doesn't look like you need to use getPlot or putPlot anymore.

custom_scale[1,2]<-custom_scale[1,2] + scale_y_log10() + scale_x_log10()

Here is a function to apply it across a big matrix. Supply the number of rows in the plot and the name of the plot.

scalelog2<-function(x=2,g){  #for below diagonal
 for (i in 2:x){ 
    for (j in 1:(i-1)) { 
      g[i,(j)]<-g[i,(j)] + scale_x_continuous(trans='log2') +
scale_y_continuous(trans='log2')
                        } } 
 for (i in 1:x){  #for the bottom row 
      g[(x+1),i]<-g[(x+1),i] + scale_y_continuous(trans='log2') 
                       } 
 for (i in 1:x){ #for the diagonal
      g[i,i]<-g[i,i]+ scale_x_continuous(trans='log2')  } 
  return(g) }

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数理化全能战士 2024-12-04 22:48:38

在将它们提供给 ggpairs 之前，最好适当使用线性标度和对数变换变量，因为这可以避免相关系数计算方式的歧义（在对数变换之前或之后）。
这可以很容易地实现，例如：

library(tidyverse)

log10_vars <- vars(ends_with(".Length"))             # define variables to be transformed

iris %>%                                             # use standard R example dataframe
  mutate_at(log10_vars, log10) %>%                   # log10 transform selected columns
  rename_at(log10_vars, sprintf, fmt="log10 %s") %>% # rename variables accordingly
  GGally::ggpairs(aes(color=Species))

It's probably better use a linear scale and log transform variables as appropriate before supplying them to ggpairs because this avoids ambiguity in how the correlation coefficients have been computed (before or after log-transform).
This can be easily achieved e.g. like this:

library(tidyverse)

log10_vars <- vars(ends_with(".Length"))             # define variables to be transformed

iris %>%                                             # use standard R example dataframe
  mutate_at(log10_vars, log10) %>%                   # log10 transform selected columns
  rename_at(log10_vars, sprintf, fmt="log10 %s") %>% # rename variables accordingly
  GGally::ggpairs(aes(color=Species))