R 如何在ggplot2中添加纹理以填充颜色

我目前正在使用

scale\u brewer（）

填充，它们的颜色看起来很漂亮（在屏幕上和通过彩色打印机），但在使用黑白打印机时，它们的灰色打印相对一致。我搜索了在线

ggplot2

文档，但没有看到任何关于添加纹理以填充颜色的内容。是否有官方的

ggplot2

方法来实现这一点，或者是否有人使用过黑客？所谓纹理，我指的是像对角线、反向对角线、点图案等，当以黑白打印时会区分填充颜色。

目前不可能，因为网格（ggplot2用于实际绘制的图形系统）不支持纹理。对不起

ggplot可以使用colorbrewer调色板。其中一些是“复印”友好的。这样的东西对你有用吗

ggplot(diamonds, aes(x=cut, y=price, group=cut))+
geom_boxplot(aes(fill=cut))+scale_fill_brewer(palette="OrRd")

在这种情况下，OrRd是colorbrewer网页上的调色板：

便于复印：这表明 一个给定的配色方案 白纸黑字 影印。发散方案可以 无法成功复印。 应注意亮度的差异 用顺序方案保存

---

嘿，伙计们，这里有一个小技巧，它以一种非常基本的方式解决了纹理问题：

编辑：我终于有时间给出一个简单的例子，说明这种黑客在ggplot2中至少可以使用3种基本模式。守则：

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")

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"
  )

其结果如下：

这是一个有点马虎，因为我没有投入太多的时间，使线完美的角度和间隔，但这应该作为一个概念证明

很明显，直线可以朝相反的方向倾斜，也有对角线啮合的空间，就像水平和垂直啮合一样

我想这就是我能提供的所有图案。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择。这次使用

geom\u抖动

我再次向数据框添加了另一个变量：

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

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

接下来，我创建了一列，其中包含与x轴上的目标条关联的编号：

Example.Data$Bubbles <- 2

每次运行绘图时，抖动都会对“气泡”进行不同的定位，但这里有一个更好的输出：

有时“泡沫”会在边界外抖动。如果发生这种情况，请重新运行或以更大的维度导出。更多的气泡可以绘制在y轴上的每个增量上，如果你愿意的话，会填充更多的空白空间。

这就构成了7种模式（如果你包括了斜对角线和斜网格的话），它们可以在ggplot中被破解

如果有人能考虑一些问题，请随时提出更多建议

编辑4：我一直在开发一个包装器函数，以便在ggplot2中自动填充图案。一旦我扩展了函数以允许在facet_网格图等中使用模式，我将发布一个链接。以下是一个简单条形图的函数输入输出示例：

我将添加一个最后的编辑，一旦我有了功能准备好共享

编辑5：我编写了一个函数egghtch，它使向几何图形添加图案的过程变得更简单

编辑6：我想我应该分享这个解决方案的一个简单变体，为阴影区添加一些颜色

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)

bar\u宽度=0.8
xaxislabs我认为这项工作很棒，但现在我突然在谷歌上搜索了一个特别的软件包--。没有看到内部代码，但vignette似乎很有用。
创建一个虚拟数据帧，其轮廓对应于“纹理”，然后使用geom_轮廓可能会很有用。以下是我的例子：

library(ggplot2)

eg = expand.grid(R1 = seq(0,1,by=0.01), R2 = seq(0,1,by=0.01))
     eg$importance = (eg$R1+eg$R2)/2

  ggplot(eg , aes(x = R1, y = R2)) +
  geom_raster(aes(fill = importance), interpolate=TRUE) +
  scale_fill_gradient2(low="white", high="gray20", limits=c(0,1)) +
  theme_classic()+
  geom_contour(bins=5,aes(z=importance), color="black", size=0.6)+
  coord_fixed(ratio = 1, xlim=c(0,1),ylim=c(0,1))

结果如下：

（线条应平滑）
您可以使用package by使用
ggplot2
绘制纹理矩形和条形图

# Image/pattern randomly selected from README
path_image <- "http://www.hypergridbusiness.com/wp-content/uploads/2012/12/rocks2-256.jpg"

library(ggplot2)
# devtools::install_github("clauswilke/ggtextures")
ggplot(mtcars, aes(cyl, mpg)) + 
  ggtextures::geom_textured_bar(stat = "identity", image = path_image)

#从自述文件中随机选择的图像/模式
path_image
ggrough
可能会引起人们的兴趣：
我刚刚发现了一个名为
ggpattern
（）的包，它似乎是解决此问题的很好的解决方案，并与ggplot2工作流很好地集成。虽然使用纹理的解决方案可能适用于对角线，但它们不会生成矢量图形，因此不是最佳解决方案

下面是一个直接取自ggpattern的github存储库的示例：

install.packages("remotes")
remotes::install_github("coolbutuseless/ggpattern")

library(ggplot2)
library(ggpattern)

df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))

ggplot(df) +
  geom_col_pattern(
    aes(level, outcome, pattern_fill = level), 
    pattern = 'stripe',
    fill    = 'white',
    colour  = 'black'
  ) +
  theme_bw(18) +
  theme(legend.position = 'none') + 
  labs(
    title    = "ggpattern::geom_pattern_col()",
    subtitle = "pattern = 'stripe'"
  ) +
  coord_fixed(ratio = 1/2)


install.packages（“remotes”）
remotes:：install_github（“coolbutuntible/ggpattern”）
图书馆（GG2）
图书馆（GG模式）
df是否计划添加gridextra作为依赖项以获得此功能？有相关消息吗？这可能在不久的将来发生变化。看，在这个基础上再接再厉。干得好！然而，这个解决方案似乎只适用于条形图，或者说？@Giovanni Azua我只在条形图上试过是的。当我有时间时，我会尝试调整堆叠图等的链接功能。这并没有回答OP的问题。我来这里是因为我坚持使用某些颜色。此接受的“答案”不建议如何应用纹理。@msbernds它不回答您的问题。可以肯定的是，绿色的复选标记表示它已经回答了这个问题！不要被复选标记愚弄。问题是如何应用纹理-这还没有回答。提供了一个开箱即用的想法，是的，但不是问题的答案。感谢您将答案移动到@PoGibas。我打赌它会在这里得到更多（当之无愧）的关注！欢迎在这里查看可下载的模式：现在我只需要了解如何在R中更改它们的透明度。。哈希也是。
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)

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)

library(ggplot2)

eg = expand.grid(R1 = seq(0,1,by=0.01), R2 = seq(0,1,by=0.01))
     eg$importance = (eg$R1+eg$R2)/2

  ggplot(eg , aes(x = R1, y = R2)) +
  geom_raster(aes(fill = importance), interpolate=TRUE) +
  scale_fill_gradient2(low="white", high="gray20", limits=c(0,1)) +
  theme_classic()+
  geom_contour(bins=5,aes(z=importance), color="black", size=0.6)+
  coord_fixed(ratio = 1, xlim=c(0,1),ylim=c(0,1))

# Image/pattern randomly selected from README
path_image <- "http://www.hypergridbusiness.com/wp-content/uploads/2012/12/rocks2-256.jpg"

library(ggplot2)
# devtools::install_github("clauswilke/ggtextures")
ggplot(mtcars, aes(cyl, mpg)) + 
  ggtextures::geom_textured_bar(stat = "identity", image = path_image)

data_raw <- data.frame(x = round(rbinom(1000, 50, 0.1)))
ggplot(data_raw, aes(x)) +
  geom_textured_bar(
    aes(y = ..prop..), image = path_image
  ) +
  geom_density()

install.packages("remotes")
remotes::install_github("coolbutuseless/ggpattern")

library(ggplot2)
library(ggpattern)

df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))

ggplot(df) +
  geom_col_pattern(
    aes(level, outcome, pattern_fill = level), 
    pattern = 'stripe',
    fill    = 'white',
    colour  = 'black'
  ) +
  theme_bw(18) +
  theme(legend.position = 'none') + 
  labs(
    title    = "ggpattern::geom_pattern_col()",
    subtitle = "pattern = 'stripe'"
  ) +
  coord_fixed(ratio = 1/2)