r - 如何在ggplot2中添加纹理以填充颜色

Question

我目前正在使用 scale_brewer()用于填充，这些颜色看起来很漂亮(在屏幕上和通过彩色打印机)，但在使用黑白打印机时打印出相对均匀的灰色。我在网上搜了ggplot2文档，但没有看到任何有关添加纹理以填充颜色的信息。有没有官方ggplot2方法来做到这一点还是有人有他们使用的黑客？我所说的纹理是指对角线、反向对角线、圆点图案等，当以黑白打印时可以区分填充颜色。

Answer 1

嘿伙计们，这是一个以非常基本的方式解决纹理问题的小技巧:
Make the border on one bar darker than the others
编辑:我终于有时间给出这个 hack 的简短示例，它允许 ggplot2 中至少有 3 种类型的基本模式。编码:

Example.Data<- data.frame(matrix(vector(), 0, 3, dimnames=list(c(), c("Value", "Variable", "Fill"))), stringsAsFactors=F)

Example.Data[1, ] <- c(45, 'Horizontal Pattern','Horizontal Pattern' )
Example.Data[2, ] <- c(65, 'Vertical Pattern','Vertical Pattern' )
Example.Data[3, ] <- c(89, 'Mesh Pattern','Mesh Pattern' )


HighlightDataVert<-Example.Data[2, ]
HighlightHorizontal<-Example.Data[1, ]
HighlightMesh<-Example.Data[3, ]
HighlightHorizontal$Value<-as.numeric(HighlightHorizontal$Value)
Example.Data$Value<-as.numeric(Example.Data$Value)

HighlightDataVert$Value<-as.numeric(HighlightDataVert$Value)
HighlightMesh$Value<-as.numeric(HighlightMesh$Value)
HighlightHorizontal$Value<-HighlightHorizontal$Value-5
HighlightHorizontal2<-HighlightHorizontal
HighlightHorizontal2$Value<-HighlightHorizontal$Value-5
HighlightHorizontal3<-HighlightHorizontal2
HighlightHorizontal3$Value<-HighlightHorizontal2$Value-5
HighlightHorizontal4<-HighlightHorizontal3
HighlightHorizontal4$Value<-HighlightHorizontal3$Value-5
HighlightHorizontal5<-HighlightHorizontal4
HighlightHorizontal5$Value<-HighlightHorizontal4$Value-5
HighlightHorizontal6<-HighlightHorizontal5
HighlightHorizontal6$Value<-HighlightHorizontal5$Value-5
HighlightHorizontal7<-HighlightHorizontal6
HighlightHorizontal7$Value<-HighlightHorizontal6$Value-5
HighlightHorizontal8<-HighlightHorizontal7
HighlightHorizontal8$Value<-HighlightHorizontal7$Value-5

HighlightMeshHoriz<-HighlightMesh
HighlightMeshHoriz$Value<-HighlightMeshHoriz$Value-5
HighlightMeshHoriz2<-HighlightMeshHoriz
HighlightMeshHoriz2$Value<-HighlightMeshHoriz2$Value-5
HighlightMeshHoriz3<-HighlightMeshHoriz2
HighlightMeshHoriz3$Value<-HighlightMeshHoriz3$Value-5
HighlightMeshHoriz4<-HighlightMeshHoriz3
HighlightMeshHoriz4$Value<-HighlightMeshHoriz4$Value-5
HighlightMeshHoriz5<-HighlightMeshHoriz4
HighlightMeshHoriz5$Value<-HighlightMeshHoriz5$Value-5
HighlightMeshHoriz6<-HighlightMeshHoriz5
HighlightMeshHoriz6$Value<-HighlightMeshHoriz6$Value-5
HighlightMeshHoriz7<-HighlightMeshHoriz6
HighlightMeshHoriz7$Value<-HighlightMeshHoriz7$Value-5
HighlightMeshHoriz8<-HighlightMeshHoriz7
HighlightMeshHoriz8$Value<-HighlightMeshHoriz8$Value-5
HighlightMeshHoriz9<-HighlightMeshHoriz8
HighlightMeshHoriz9$Value<-HighlightMeshHoriz9$Value-5
HighlightMeshHoriz10<-HighlightMeshHoriz9
HighlightMeshHoriz10$Value<-HighlightMeshHoriz10$Value-5
HighlightMeshHoriz11<-HighlightMeshHoriz10
HighlightMeshHoriz11$Value<-HighlightMeshHoriz11$Value-5
HighlightMeshHoriz12<-HighlightMeshHoriz11
HighlightMeshHoriz12$Value<-HighlightMeshHoriz12$Value-5
HighlightMeshHoriz13<-HighlightMeshHoriz12
HighlightMeshHoriz13$Value<-HighlightMeshHoriz13$Value-5
HighlightMeshHoriz14<-HighlightMeshHoriz13
HighlightMeshHoriz14$Value<-HighlightMeshHoriz14$Value-5
HighlightMeshHoriz15<-HighlightMeshHoriz14
HighlightMeshHoriz15$Value<-HighlightMeshHoriz15$Value-5
HighlightMeshHoriz16<-HighlightMeshHoriz15
HighlightMeshHoriz16$Value<-HighlightMeshHoriz16$Value-5
HighlightMeshHoriz17<-HighlightMeshHoriz16
HighlightMeshHoriz17$Value<-HighlightMeshHoriz17$Value-5

ggplot(Example.Data, aes(x=Variable, y=Value, fill=Fill)) + theme_bw() + #facet_wrap(~Product, nrow=1)+ #Ensure theme_bw are there to create borders
  theme(legend.position = "none")+
  scale_fill_grey(start=.4)+
  #scale_y_continuous(limits = c(0, 100), breaks = (seq(0,100,by = 10)))+
  geom_bar(position=position_dodge(.9), stat="identity", colour="black", legend = FALSE)+
  geom_bar(data=HighlightDataVert, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.80)+
geom_bar(data=HighlightDataVert, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.60)+  
  geom_bar(data=HighlightDataVert, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.40)+
  geom_bar(data=HighlightDataVert, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.20)+
  geom_bar(data=HighlightDataVert, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.0) +
  geom_bar(data=HighlightHorizontal, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal2, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal3, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal4, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal5, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal6, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal7, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightHorizontal8, position=position_dodge(.9), stat="identity", colour="black", size=.5)+
  geom_bar(data=HighlightMesh, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.80)+
 geom_bar(data=HighlightMesh, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.60)+
  geom_bar(data=HighlightMesh, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.40)+
  geom_bar(data=HighlightMesh, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.20)+
  geom_bar(data=HighlightMesh, position=position_dodge(.9), stat="identity", colour="black", size=.5, width=0.0)+
  geom_bar(data=HighlightMeshHoriz, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
geom_bar(data=HighlightMeshHoriz2, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz3, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz4, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz5, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz6, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz7, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz8, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz9, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz10, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz11, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz12, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz13, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz14, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz15, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz16, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  geom_bar(data=HighlightMeshHoriz17, position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")

产生这个:

它不是 super 漂亮，但它是我能想到的唯一解决方案。
可以看出，我生成了一些非常基本的数据。为了获得垂直线，我只需创建一个数据框来包含我想要添加垂直线的变量，并多次重新绘制图形边框以减少宽度。
对水平线进行了类似的操作，但每次重绘都需要一个新的数据框，其中我从与感兴趣的变量关联的值中减去了一个值(在我的示例中为“5”)。有效降低杆的高度。这很难实现，可能有更精简的方法，但这说明了如何实现。
网格图案是两者的结合。首先绘制垂直线，然后添加水平线设置 fill如 fill='transparent'以确保垂直线不被绘制。
在有模式更新之前，我希望你们中的一些人觉得这很有用。
编辑2:
此外，还可以添加对角线图案。我在数据框中添加了一个额外的变量:

Example.Data[4,] <- c(20, 'Diagonal Pattern','Diagonal Pattern' )

然后我创建了一个新的数据框来保存对角线的坐标:

Diag <- data.frame(
  x = c(1,1,1.45,1.45), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y = c(0,0,20,20),
  x2 = c(1.2,1.2,1.45,1.45), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y2 = c(0,0,11.5,11.5),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  x3 = c(1.38,1.38,1.45,1.45), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y3 = c(0,0,3.5,3.5),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  x4 = c(.8,.8,1.26,1.26), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y4 = c(0,0,20,20),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  x5 = c(.6,.6,1.07,1.07), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y5 = c(0,0,20,20),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  x6 = c(.555,.555,.88,.88), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y6 = c(6,6,20,20),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  x7 = c(.555,.555,.72,.72), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y7 = c(13,13,20,20),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  x8 = c(.8,.8,1.26,1.26), # 1st 2 values dictate starting point of line. 2nd 2 dictate width. Each whole = one background grid
  y8 = c(0,0,20,20),# inner 2 values dictate height of horizontal line. Outer: vertical edge lines.
  #Variable = "Diagonal Pattern",
  Fill = "Diagonal Pattern"
  )

从那里我将 geom_paths 添加到上面的 ggplot ，每个调用不同的坐标并在所需的条上绘制线条:

+geom_path(data=Diag, aes(x=x, y=y),colour = "black")+  # calls co-or for sig. line & draws
  geom_path(data=Diag, aes(x=x2, y=y2),colour = "black")+  # calls co-or for sig. line & draws
  geom_path(data=Diag, aes(x=x3, y=y3),colour = "black")+
  geom_path(data=Diag, aes(x=x4, y=y4),colour = "black")+
  geom_path(data=Diag, aes(x=x5, y=y5),colour = "black")+
  geom_path(data=Diag, aes(x=x6, y=y6),colour = "black")+
  geom_path(data=Diag, aes(x=x7, y=y7),colour = "black")

这导致以下结果:

这有点草率，因为我没有花太多时间让线条完美地倾斜和间隔开，但这应该作为概念的证明。
显然，线条可以向相反的方向倾斜，并且也有像水平和垂直网格一样的对角网格划分的空间。
我认为这就是我在模式方面所能提供的。希望有人能找到它的用途。
编辑 3:著名的遗言。我想出了另一个模式选项。这次使用 geom_jitter .
我再次向数据框中添加了另一个变量:

Example.Data[5,] <- c(100, 'Bubble Pattern','Bubble Pattern' )

我订购了我希望每个图案呈现的方式:

Example.Data$Variable = Relevel(Example.Data$Variable, ref = c("Diagonal Pattern", "Bubble Pattern","Horizontal Pattern","Mesh Pattern","Vertical Pattern"))

接下来，我创建了一个列来包含与 x 轴上的预期目标条相关联的数字:

Example.Data$Bubbles <- 2

后跟列以包含“气泡”在 y 轴上的位置:

Example.Data$Points <- c(5, 10, 15, 20, 25)
Example.Data$Points2 <- c(30, 35, 40, 45, 50)
Example.Data$Points3 <- c(55, 60, 65, 70, 75)
Example.Data$Points4 <- c(80, 85, 90, 95, 7)
Example.Data$Points5 <- c(14, 21, 28, 35, 42)
Example.Data$Points6 <- c(49, 56, 63, 71, 78)
Example.Data$Points7 <- c(84, 91, 98, 6, 12)

最后我加了 geom_jitter s 到上面的 ggplot 使用新列进行定位并重新使用“点”来改变“气泡”的大小:

+geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points3, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points4, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points3, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points4, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points5, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points5, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points6, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points6, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points7, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points7, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points3, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points4, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points3, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points4, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points2, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points5, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points5, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points6, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points6, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points7, size=Points), alpha=.5)+
  geom_jitter(data=Example.Data,aes(x=Bubbles, y=Points7, size=Points), alpha=.5)

每次运行绘图时，抖动都会以不同的方式定位“气泡”，但这是我拥有的更好的输出之一:

有时，“气泡”会在边界外抖动。如果发生这种情况，请重新运行或简单地以更大的尺寸导出。可以在 y 轴上的每个增量上绘制更多气泡，如果您愿意，这将填充更多空白空间。
这构成了多达 7 个可以在 ggplot 中破解的模式(如果您包括相反的倾斜对角线和两者的对角网格)。
如果有人能想到一些，请随时提出更多建议。
编辑 4:我一直在研究包装函数来自动化 ggplot2 中的孵化/模式。一旦我扩展了函数以允许 facet_grid 图等中的模式，我将发布一个链接。 以下是一个带有简单条形图的函数输入的输出作为示例:

一旦我准备好共享该功能，我将添加最后一个编辑。
编辑 5: Here's a link我编写的函数 EggHatch 使向 geom_bar 绘图添加模式的过程更容易一些。
编辑 6:我想我会分享这个解决方案的一个简单变体，为阴影图添加一些颜色。
使用与上面相同的 df 运行此代码:

bar_width = 0.8
xaxislabs <- c("Purple", "Blue", "Green")

ggplot(Example.Data, aes(x=Variable, y=Value, fill=Fill)) +
  theme(legend.position = "none")+
  geom_bar(position=position_dodge(.9), stat="identity", colour="black", legend = FALSE,  width=bar_width, fill="#15a742")+
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7)*5, fill="#FFFFFF")+  
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="#15a742", width=(bar_width/7)*3, fill="#15a742")+
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7), fill="#FFFFFF")+
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="black", width=bar_width, fill="transparent")+
  
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="black", width=bar_width, fill="#8b2fbb")+
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7)*5, fill="#FFFFFF")+
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="#8b2fbb", width=(bar_width/7)*3, fill="#8b2fbb")+
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7), fill="#FFFFFF")+
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="black", width=bar_width, fill="transparent")+
  
  
  geom_bar(data=Example.Data[3, ], position=position_dodge(.9), stat="identity", colour="#59a5db", width=bar_width, fill="#59a5db")+
  geom_bar(data=Example.Data[3, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7)*5, fill="#FFFFFF")+  
  geom_bar(data=Example.Data[3, ], position=position_dodge(.9), stat="identity", colour="#59a5db", width=(bar_width/7)*3, fill="#59a5db")+
  geom_bar(data=Example.Data[3, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7), fill="#FFFFFF")+
  geom_bar(data=Example.Data[3, ], position=position_dodge(.9), stat="identity", colour="black", width=bar_width, fill="transparent")+
  
  scale_x_discrete(labels= xaxislabs)

结果在这个情节:

这段代码，再次使用上面的 dfs:

bar_width = 0.8
xaxislabs <- c("Purple", "Blue", "Green")


ggplot(Example.Data, aes(x=Variable, y=Value, fill=Fill)) +
  theme(legend.position = "none")+
  geom_bar(position=position_dodge(.9), stat="identity", colour="black", legend = FALSE,  width=bar_width, fill="#15a742")+
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7)*5, fill="#FFFFFF")+  
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="#15a742", width=(bar_width/7)*3, fill="#15a742")+
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="#FFFFFF", width=(bar_width/7), fill="#FFFFFF")+
  geom_bar(data=Example.Data[2, ], position=position_dodge(.9), stat="identity", colour="black", width=bar_width, fill="transparent")+
  
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="#8b2fbb", size=.5, fill = "#8b2fbb")+
  geom_bar(data=HighlightHorizontal, position=position_dodge(.9), stat="identity", colour="#FFFFFF", size=.5, fill = "#FFFFFF")+
  geom_bar(data=HighlightHorizontal2, position=position_dodge(.9), stat="identity", colour="#8b2fbb", size=.5, fill="#8b2fbb")+
  geom_bar(data=HighlightHorizontal3, position=position_dodge(.9), stat="identity", colour="#FFFFFF", size=.5, fill = "#FFFFFF")+
  geom_bar(data=HighlightHorizontal4, position=position_dodge(.9), stat="identity", colour="#8b2fbb", size=.5, fill="#8b2fbb")+
  geom_bar(data=HighlightHorizontal5, position=position_dodge(.9), stat="identity", colour="#FFFFFF", size=.5, fill = "#FFFFFF")+
  geom_bar(data=HighlightHorizontal6, position=position_dodge(.9), stat="identity", colour="#8b2fbb", size=.5, fill="#8b2fbb")+
  geom_bar(data=HighlightHorizontal7, position=position_dodge(.9), stat="identity", colour="#FFFFFF", size=.5, fill = "#FFFFFF")+
  geom_bar(data=HighlightHorizontal8, position=position_dodge(.9), stat="identity", colour="#8b2fbb", size=.5, fill="#8b2fbb")+
  geom_bar(data=Example.Data[1, ], position=position_dodge(.9), stat="identity", colour="black", size=.5, fill = "transparent")+
  
  geom_bar(data=Example.Data[3, ], position=position_dodge(.9), stat="identity", colour="black", width=bar_width, fill="#59a5db")+
  
  scale_x_discrete(labels= xaxislabs)

结果如下: