geom_raster插值与对数刻度 [英] geom_raster interpolation with log scale

问题描述

我有点卡住了一个日志规模的栅格。例如：

  ggplot（faithfuld，aes（waiting，eruptions））+ 
 geom_raster（aes（ fill = density））
  

但是如何在这个几何图形中使用对数刻度？

  ggplot（faithfuld，aes（waiting，log10（eruptions）））+ 
 geom_raster（aes（fill = density））
  

我可以做些什么来消除光栅中的空白？

请注意，这个问题与这两个相关：

• 
  
  

  如果您真的想将y转换为日志范围并生成密度图，则必须使用忠实的 geom_density_2d 。

   ＃使用geom_density_2d 
   ggplot（ aes（fill = .. density，）aes（x = waiting，y = log（eruptions）））+ 
   geom_density_2d（）+ 
   stat_density_2d（geom =raster $ b contour = FALSE）
    

  
  
  

  更新：使用 geom_rect 并提供自定义xmin，xmax，ymin，ymax值以适合日志比例的空格。由于 geom_raster 使用相同大小的图块，因此您可能必须使用<$ c>
  $ c> geom_tile 或 geom_rect 来创建绘图。我的想法是计算每个图块的大小（宽度），并将每个图块的 xmin 和 xmax 调整为填补差距。
  
  

    dat < -  data.frame（x = rep（1:10，10），
  y = unlist lapply（1:10，function（i）rep（i，10））），
  z = faithfuld $ density [1：100]）
   library（ggplot2）
   library（gridExtra）
   
  g < -  ggplot（dat，aes（x = log（x），y​​ = y，fill = z））+ 
   geom_raster（）
   
  ＃替换（独特的（dat $ x）））/ 2 
   upper < - （唯一的（dat $ x））+ c（距离，距离[长度（距离）]）
   lower < - （unique（dat $ x）） -  c（distance [1]，distance）
   
  ＃创建xmin，xmax，ymin，ymax 
   dat $ xmin < -  dat $ x  -  0.5＃geom_raster的默认值是0.5 
   dat $ xmax <-dat $ x + 0.5 
   dat $ ymin < -  unlist（lapply（lower，function， （i）rep（i，rle（dat $ y）$ lengths [1]）））
   dat $ ymax < -  unlist（lapply（upper，function（i）rep（i，rle（dat $ y ）$ length [1]）））
   
  ＃您也可以使用geom_tile和width参数
   g2 < -  ggplot（dat，aes（x = log（x），y​​ = y，xmin = xmin，xmax = xm ax，ymin = ymin，ymax = ymax，fill = z））+ 
   geom_rect（）
   
  ＃显示地块
   grid.arrange（g，g2，ncol = 2 ）
    

  
  

  I'm a bit stuck plotting a raster with a log scale. Consider this plot for example:

  ggplot(faithfuld, aes(waiting, eruptions)) +
   geom_raster(aes(fill = density))
  

  But how to use a log scale with this geom? None of the usual methods are very satisfying:

   ggplot(faithfuld, aes(waiting, log10(eruptions))) +
     geom_raster(aes(fill = density))
  

   ggplot(faithfuld, aes(waiting, (eruptions))) +
     geom_raster(aes(fill = density)) + 
     scale_y_log10()
  

  and this doesn't work at all:

   ggplot(faithfuld, aes(waiting, (eruptions))) +
     geom_raster(aes(fill = density)) + 
     coord_trans(x="log10")
  

  Error: geom_raster only works with Cartesian coordinates

  Are there any options for using a log scale with a raster?

  To be precise, I have three columns of data. The z value is the one I want to use to colour the raster, and it is not computed from the x and y values. So I need to supply all three columns to the ggplot function. For example:

  dat <- data.frame(x = rep(1:10, 10), 
                    y = unlist(lapply(1:10, function(i) rep(i, 10))), 
                    z = faithfuld$density[1:100])
  
  ggplot(dat, aes(x = log(x), y = y, fill = z)) +
    geom_raster()
  

  What can I do to get rid of those gaps in the raster?

  Note that this question is related to these two:

  • geom_raster interpolation with log scale
  • Use R to recreate contour plot made in Igor

  I have been keeping an updated gist of R code that combines details from the answers to these questions (example output included in the gist). That gist is here: https://gist.github.com/benmarwick/9a54cbd325149a8ff405

  解决方案

  The dataset faithfuld already have a column for density which is the estimates of the 2D density for waiting and eruptions. You can find that the eruptions and waiting in the dataset are points in a grid. When you use geom_raster, it doesn't compute the density for you. Instead, it plots the density according to the x, y coordinates, in this case, is the grid. Hence, if you just apply the log transformation on y, it will distort the difference between y (originally they are equally spaced) and this is why you see the space in your plot. I used points to visualize the effects:

  library(ggplot2)
  library(gridExtra)
  
  # Use point to visualize the effect of log on the dataset
  g1 <- ggplot(faithfuld, aes(x=waiting, y=eruptions)) +
    geom_point(size=0.5)    
  
  g2 <- ggplot(faithfuld, aes(x=waiting, y=log(eruptions))) +
    geom_point(size=0.5)    
  
  grid.arrange(g1, g2, ncol=2)    
  

  If you really want to transform y to log scale and produce the density plot, you have to use the faithful dataset with geom_density_2d.

  # Use geom_density_2d
  ggplot(faithful, aes(x=waiting, y=log(eruptions))) +
    geom_density_2d() +
    stat_density_2d(geom="raster", aes(fill=..density..),
                    contour=FALSE)
  

  Update: Use geom_rect and supply custom xmin, xmax, ymin, ymax values to fit the spaces of the log scale.

  Since the geom_raster use the same size of tiles, you probably have to use geom_tile or geom_rect to create the plot. My idea is to calculate how large (width) each tile should be and adjust the xmin and xmax for each tile to fill up the gap.

   dat <- data.frame(x = rep(1:10, 10), 
                    y = unlist(lapply(1:10, function(i) rep(i, 10))), 
                    z = faithfuld$density[1:100])
  library(ggplot2)
  library(gridExtra)   
  
  g <- ggplot(dat, aes(x = log(x), y = y, fill = z)) +
    geom_raster()   
  
  # Replace the ymin and ymax
  distance <- diff((unique(dat$x)))/2
  upper <- (unique(dat$x)) + c(distance, distance[length(distance)])
  lower <- (unique(dat$x)) - c(distance[1], distance) 
  
  # Create xmin, xmax, ymin, ymax
  dat$xmin <- dat$x - 0.5 # default of geom_raster is 0.5
  dat$xmax <- dat$x + 0.5
  dat$ymin <- unlist(lapply(lower, function(i) rep(i, rle(dat$y)$lengths[1])))
  dat$ymax <- unlist(lapply(upper, function(i) rep(i, rle(dat$y)$lengths[1])))        
  
  # You can also use geom_tile with the width argument
  g2 <- ggplot(dat, aes(x=log(x), y=y, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, fill=z)) +
    geom_rect() 
  
  # show the plots     
  grid.arrange(g, g2, ncol=2)
  

  这篇关于geom_raster插值与对数刻度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！