如何在R中使用ggplot绘制绘图区域的“外部"?

编程入门行业动态更新时间:2024-10-26 23:32:26

本文介绍了如何在R中使用ggplot绘制绘图区域的“外部"?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！问题描述

我最近问了

但是，我试图找到一种一致的方式来绘制类似这样的东西(我很快在photoshop中制作了):

主要问题是能够操纵绘图区域外部"的新比例尺的坐标.有没有办法移动外面的瓷砖，以便我可以将它们放置在有意义的区域?

解决方案

在绘图区域外进行绘图时，总是有两个经典选项:

使用 coord _...(剪辑="off")注释/绘图
制作不同的情节并将它们组合起来.

在我的拙见中，后一种选择通常可以提供更大的灵活性，并且可以减少头痛.

库(色彩空间)图书馆(tidyverse)图书馆(拼凑而成)asd<-expand_grid(paste0("a"，1:9)，paste0("b"，1:9))df<-data.frame(a = asd $`paste0("a"，1:9)`，b = asd $`paste0("b"，1:9)`，c =样本(20，81，替换= T))#从离散到连续df $ a<-匹配(df $ a，sort(unique(df $ a)))df $ b<-匹配(df $ b，sort(unique(df $ b)))z<-sample(10，18，T)#设置调色板pal<-rev(diverging_hcl(palette ="Blue-Red"，n = 11))palEdge<-rev(sequential_hcl(palette ="Plasma"，n = 11))# 阴谋p_main<-ggplot(df，aes(a，b))+geom_tile(aes(fill = c))+scale_fill_gradientn("C"，颜色= pal，guide = guide_colorbar(frame.colour ="black"，ticks.colour =黑色"))+theme_classic()+labs(x ="A轴"，y ="B轴")p_bottom<-ggplot()+geom_tile(data = tibble(a = 1:9，z = z [1:9])，aes(x = a，y = 0，填充= z，高度= 0.3))+theme_void()+scale_fill_gradientn("Z"，限制= c(0,10)，颜色= palEdge，指南= guide_colorbar(frame.colour ="black"，ticks.colour ="black"))p_left<-ggplot()+theme_void()+geom_tile(data = tibble(b = 1:9，z = z [10:18])，aes(x = 0，y = b，填充= z，宽度= 0.3))+scale_fill_gradientn("Z"，限制= c(0,10)，颜色= palEdge，guide = guide_colorbar(frame.colour ="black"，ticks.colour ="black"))p_left + p_main + plot_spacer()+ p_bottom +plot_layout(guides ="collect"，高度= c(1，.1)，宽度= c(.1，1))

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I recently asked this question. However, I am asking a separate question now as the scope of my new question falls outside the range of the last question.

I am trying to create a heatmap in ggplot... however, outside of the axis I am trying to plot geom_tile. The issue is I cannot find a consistent way to get it to work. For example, the code I am using to plot is:

library(colorspace) library(ggplot2) library(ggnewscale) library(tidyverse) asd <- expand_grid(paste0("a", 1:9), paste0("b", 1:9)) df <- data.frame( a = asd$`paste0("a", 1:9)`, b = asd$`paste0("b", 1:9)`, c = sample(20, 81, replace = T) ) # From discrete to continuous df$a <- match(df$a, sort(unique(df$a))) df$b <- match(df$b, sort(unique(df$b))) z <- sample(10, 18, T) # set color palettes pal <- rev(diverging_hcl(palette = "Blue-Red", n = 11)) palEdge <- rev(sequential_hcl(palette = "Plasma", n = 11)) # plot ggplot(df, aes(a, b)) + geom_tile(aes(fill = c)) + scale_fill_gradientn( colors = pal, guide = guide_colorbar( frame.colour = "black", ticks.colour = "black" ), name = "C" ) + theme_classic() + labs(x = "A axis", y = "B axis") + new_scale_fill() + geom_tile(data = tibble(a = 1:9, z = z[1:9]), aes(x = a, y = 0, fill = z, height = 0.3)) + geom_tile(data = tibble(b = 1:9, z = z[10:18]), aes(x = 0, y = b, fill = z, width = 0.3)) + scale_fill_gradientn( colors = palEdge, guide = guide_colorbar( frame.colour = "black", ticks.colour = "black" ), name = "Z" )+ coord_cartesian(clip = "off", xlim = c(0.5, NA), ylim = c(0.5, NA)) + theme(aspect.ratio = 1, plot.margin = margin(10, 15.5, 25, 25, "pt") )

This produces something like this:

However, I am trying to find a consistent way to plot something more like this (which I quickly made in photoshop):

The main issue im having is being able to manipulate the coordinates of the new scale 'outside' of the plotting area. Is there a way to move the tiles that are outside so I can position them in an area that makes sense?

解决方案

There are always the two classic options when plotting outside the plot area:

annotate/ plot with coord_...(clip = "off")
make different plots and combine them.

The latter option usually gives much more flexibility and way less headaches, in my humble opinion.

library(colorspace) library(tidyverse) library(patchwork) asd <- expand_grid(paste0("a", 1:9), paste0("b", 1:9)) df <- data.frame( a = asd$`paste0("a", 1:9)`, b = asd$`paste0("b", 1:9)`, c = sample(20, 81, replace = T) ) # From discrete to continuous df$a <- match(df$a, sort(unique(df$a))) df$b <- match(df$b, sort(unique(df$b))) z <- sample(10, 18, T) # set color palettes pal <- rev(diverging_hcl(palette = "Blue-Red", n = 11)) palEdge <- rev(sequential_hcl(palette = "Plasma", n = 11)) # plot p_main <- ggplot(df, aes(a, b)) + geom_tile(aes(fill = c)) + scale_fill_gradientn("C",colors = pal, guide = guide_colorbar(frame.colour = "black", ticks.colour = "black")) + theme_classic() + labs(x = "A axis", y = "B axis") p_bottom <- ggplot() + geom_tile(data = tibble(a = 1:9, z = z[1:9]), aes(x = a, y = 0, fill = z, height = 0.3)) + theme_void() + scale_fill_gradientn("Z",limits = c(0,10), colors = palEdge, guide = guide_colorbar( frame.colour = "black", ticks.colour = "black")) p_left <- ggplot() + theme_void()+ geom_tile(data = tibble(b = 1:9, z = z[10:18]), aes(x = 0, y = b, fill = z, width = 0.3)) + scale_fill_gradientn("Z",limits = c(0,10), colors = palEdge, guide = guide_colorbar( frame.colour = "black", ticks.colour = "black")) p_left + p_main +plot_spacer()+ p_bottom + plot_layout(guides = "collect", heights = c(1, .1), widths = c(.1, 1))