发散尺寸比例尺ggplot2

问题描述

我试图在空间位置映射模型/观测差异。我有颜色映射到差异，但我也想映射大小差异。我目前将尺寸映射到abs（差异），但它产生了两个不同的传说，我想合并。将大小映射到差异会为负值创建小点，为正值创建大点，但我真的只希望为过度/欠量预测显示幅度。如果它有所作为，我还希望尺度是离散的。
谢谢

一些测试数据：

  so。 df = data.frame（lat = runif（50,33,43），long = runif（50，-112，-104），diff = runif（50，-2,2））
 ggplot（）+ 
 geom_point（data = so.df，aes（x = long，y = lat，color = diff，size = abs（diff）），alpha = 0.8）+ 
 scale_color_gradient2（low ='red' ，mid ='white'，high ='blue'，limits = c（-0.6,0.6），breaks = c（-0.6，-0.4，-0.2，-0.1,0,0.1,0.2,0.6））+ 
 guides（color = guide_legend（'SWE Differences（m）'），size = guide_legend（'SWE Difference \Magnitudes（m）'））+ 
 coord_cartesian（xlim = c（-112.5，-104.25 ），ylim = c（33,44））+ 
 theme_bw（）
  

编辑：
使用离散色标我使用以下内容（对建议开放）

  so.df $ cut = cut_interval（so.df $ diff，length = 0.15）
 ggplot（）+ 
 geom_path（data = states，aes（x = long，y = lat，group = group），color ='grey10 '）+ 
 geom_point（data = so.df，aes（x = long，y = lat，color = cuts，size = abs（diff）），alpha = 0.8）+ 
 coord_cartesian（xlim = c（-112.5，-104.25），ylim = c（33,44））+ 
 scale_colour_brewer（type ='div'，palette ='RdYlBu'）+ 
 guides（color = guide_legend（'SWE Differences（m）'），size = guide_legend（'SWE Difference \Magnitudes（m））+ 
 theme_bw（）
  
 
 
  ggplot（）+ geom_point（data = so.df，aes（x = long，y = lat，size =剪切，颜色=剪切））
 + scale_size_manual（值= 
c（8,6,4,2,1,2,4,6,8），guide =legend）+ 
 coord_cartesian（xlim = c（-112.5，-104.25），ylim = c（33,44））+ 
 scale_colour_brewer（type ='div'，palette ='RdBu'）
  
 
I am trying to map model/obs differences at locations in space. I have color mapped to the diff but I would also like to map size to diff.  i'm currently mapping size to abs(diff) but it produces two different legends that I would like to combine. mapping size to diff creates small points for negative values and large points for positive values but I really only want the magnitude represented for over/under predictions. In case it makes a difference, I would also like the scales to be discrete.Thanks
Some test data:
so.df=data.frame(lat=runif(50,33,43),long=runif(50,-112,-104),diff=runif(50,-2,2))
    ggplot()+
        geom_point(data=so.df,aes(x=long,y=lat,color=diff,size=abs(diff)),alpha=0.8)+
scale_color_gradient2(low='red',mid='white',high='blue',limits=c(-0.6,0.6),breaks=c(-0.6,-0.4,-0.2,-0.1,0,0.1,0.2,0.6))+
        guides(color=guide_legend('SWE Differences (m)'),size=guide_legend('SWE Difference\nMagnitudes (m)'))+
        coord_cartesian(xlim=c(-112.5,-104.25),ylim=c(33,44))+
        theme_bw()
EDIT:to use a discrete color scale I'm using the following (open to suggestions)
so.df$cuts=cut_interval(so.df$diff,length=0.15)
ggplot()+
    geom_path(data=states,aes(x=long,y=lat,group=group),color='grey10')+
    geom_point(data=so.df,aes(x=long,y=lat,color=cuts,size=abs(diff)),alpha=0.8)+
    coord_cartesian(xlim=c(-112.5,-104.25),ylim=c(33,44))+
    scale_colour_brewer(type='div',palette='RdYlBu')+
    guides(color=guide_legend('SWE Differences (m)'),size=guide_legend('SWE Difference\nMagnitudes (m))+
    theme_bw()
 解决方案 
If you map your sizes to your cuts column and use scale_size_manual you can get the diverging size scale you want.
ggplot() + geom_point(data=so.df,aes(x=long,y=lat,size=cuts,color=cuts))
+ scale_size_manual(values =
c(8,6,4,2,1,2,4,6,8),guide="legend") +
coord_cartesian(xlim=c(-112.5,-104.25),ylim=c(33,44)) +
scale_colour_brewer(type='div',palette='RdBu')
                        
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