我目前使用scale_brewer()進行填充，這些顏色看起來非常漂亮（在屏幕上和通過彩色打印機），但在使用黑白打印機時可以相當均勻地以灰色打印。我搜索了在線ggplot2文檔，但沒有看到任何有關添加紋理來填充顏色的信息。有沒有官方ggplot2的方式來做到這一點，或有沒有人有他們使用的黑客？通過紋理我的意思是像黑色和白色打印時區分填充顏色的對角線條，反向對角線條，點圖案等。如何添加紋理來填充ggplot2中的顏色？
ggplot可以使用colorbrewer調色板。其中一些是「影印」友好的。所以瑪貝這樣的事情會對你有用嗎？
ggplot(diamonds, aes(x=cut, y=price, group=cut))+
geom_boxplot(aes(fill=cut))+scale_fill_brewer(palette="OrRd")
是在網頁在ColorBrewer發現的調色板：http://colorbrewer2.org/
影印友好：這表明 給定的顏色方案將 承受黑白影印 。發散計劃 不能成功複印。 亮度差異應該是 保留序列計劃。
目前不可能，因爲網格（ggplot2用於執行實際繪圖的圖形系統）不支持紋理。抱歉!
是否有計劃將gridextra作爲依賴添加以獲得此功能？ – russellpierce 2013-02-03 02:44:11
嘿人這裏有一個凌晨黑客工具，在一個非常基本的方式解決了質地問題：
ggplot2: make the border on one bar darker than the others using R
編輯：我終於找到時間給這個技巧，可以讓一個簡單的例子ggplot2中至少有3種基本模式。代碼：
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")
產生以下：
它不是超級靚，但它是我能想到的唯一解決方案。
可以看出我產生了一些非常基本的數據。爲了獲得垂直線，我只需創建一個數據框來包含我想要添加垂直線的變量，並多次重繪圖形邊框，從而每次減小寬度。
對於水平線也做了類似的事情，但是每次重繪都需要一個新的數據幀，我從與感興趣的變量相關的值中減去了一個值（在我的示例中爲'5'）。有效降低酒吧的高度。這很難實現，可能會有更簡化的方法，但這說明了如何實現。
網格模式是兩者的組合。首先繪製垂直線，然後將fill的水平線設置爲fill='transparent'，以確保垂直線不會被拉伸。
直到有一個模式更新，我希望你們有些人覺得這很有用。
編輯2：也可以添加
此外對角線圖案。我添加一個額外的變量，以該數據幀：
Example.Data[4,] <- c(20, 'Diagonal Pattern','Diagonal Pattern')
然後創建了一個新的數據幀，以保持座標爲對角線：
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"
)
從那裏我加入geom_paths到ggplot以上與每個一個調用不同的座標和在所期望的杆繪製線：
+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")
這導致以下：
因爲我沒有得到完美線條彎角投入太多的時間和間隔，但是這應該作爲一個概念證明這是一個有點草率。
顯然這些線可以傾斜相反的方向，並且還有對角線齧合的空間，就像水平和垂直齧合一樣。
我認爲這就是我可以在模式方面提供的所有東西。希望有人能找到它的用途。
編輯3：着名的遺言。我提出了另一種模式選項。這次使用geom_jitter。
我再次加入另外的變量數據幀：
Example.Data[5,] <- c(100, 'Bubble Pattern','Bubble Pattern')
我下令我希望如何呈現每個圖案：
Example.Data$Variable = Relevel(Example.Data$Variable, ref = c("Diagonal Pattern", "Bubble Pattern","Horizontal Pattern","Mesh Pattern","Vertical Pattern"))
接着我創建一列包含具有相關聯的數在x軸上的預期目標欄：
Example.Data$Bubbles <- 2
後面跟着要包含的列在上的「氣泡」的y軸上的位置：
Example.Data$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)
最後我添加geom_jitter S到ggplot以上使用新的列用於定位和重新使用「點」以改變的大小的'泡泡：
+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)
每個地塊運行抖動位置上的時間‘泡’不同，但這裏是更好的輸出，我有一個：
有時候，「氣泡」會在邊界外抖動。如果發生這種情況，可以重新運行或者直接以較大尺寸導出如果你願意，可以在y軸上的每個增量上繪製更多的氣泡，這將填充更多的空白空間。
最多可以構成7種模式（如果您包含可以在ggplot中進行攻擊的相反傾斜對角線和兩者的對角線網格）。
如果有人能想到一些，請隨時提出建議。
編輯4：我一直在使用包裝函數來自動化ggplot2中的陰影/圖案。我會發佈一個鏈接一旦我擴展功能，允許在facet_grid地塊等。這裏是一個與功能的輸入輸出的酒吧情節簡單作爲一個例子模式：
我會添加一個最後一次編輯，我有功能可以共享。
編輯5：Here's a link到函數EggHatch，我寫了使向geom_bar圖添加模式的過程更容易一些。
[底層網格問題的gridSVG解決方案]（http://stackoverflow.com/questions/26110160/how-to-apply-cross-hatching-to-a-polygon-using-the-grid-graphical-系統/ 26110400＃26110400） – baptiste 2014-10-06 10:59:19