Installing colorblindr

devtools::install_github("wilkelab/cowplot")
install.packages("colorspace", repos = "http://R-Forge.R-project.org")
devtools::install_github("clauswilke/colorblindr")

Preliminaries

library(ggplot2)
library(ggthemes)
library(colorblindr)
library(colorspace)
library(wesanderson)
library(ggsci)

d <- mpg

Using Colors

  1. Aesthetics
  1. Colors that are attractive - large geoms (fills) - pale colors - small geoms(lines,points) - bright colors
  2. Colors that highlight elements - pale, grey to de-emphasize - bright or saturated colors to emphasize
  3. Colors that are visible to the color blind
  4. Colors that convert well to black and white
  1. Information content
  1. Discrete scale
  1. Continuous scale
  1. Use color information within and between graphs
  1. show color names, hex in base R
  2. show color schemes in colorbrewer

Color visualizations

my_cols <- c("thistle","tomato","cornsilk","cyan","chocolate")
demoplot(my_cols,"map")

demoplot(my_cols,"bar")

demoplot(my_cols,"scatter")

demoplot(my_cols,"heatmap")

demoplot(my_cols,"spine")

demoplot(my_cols,"perspective")

Working with black and white

# gray function versus gray colors

# built in greys (0 = black, 100 = white
my_greys <- c("grey20","grey50","grey80")
demoplot(my_greys,"bar")

my_greys2 <- grey(seq(from=0.1,to=0.9,length.out=10))         
demoplot(my_greys2,"heatmap")

# converting color plots to black and white
p1 <- ggplot(d,aes(x=as.factor(cyl),y=cty,fill=as.factor(cyl))) + geom_boxplot() 
plot(p1)

# default colors look identical in black white
p1_des<- colorblindr::edit_colors(p1, desaturate)
plot(p1_des)

# custom colors not pretty, but convert ok to bw
p2 <- p1 + scale_fill_manual(values=c("red","blue","green","yellow"))
plot(p2)

p2_des<- colorblindr::edit_colors(p2, desaturate)
plot(p2_des)

using alpha transparency for histograms

x1 <- rnorm(n=100,mean=0)
x2 <- rnorm(n=100,mean=2.7)
d_frame <- data.frame(v1=c(x1,x2))
lab <- rep(c("Control","Treatment"),each=100)
d_frame <- cbind(d_frame,lab)
str(d_frame)
## 'data.frame':    200 obs. of  2 variables:
##  $ v1 : num  -0.0306 1.4022 0.166 2.5987 -1.1781 ...
##  $ lab: chr  "Control" "Control" "Control" "Control" ...
h1 <- ggplot(d_frame) +
      aes(x=v1,fill=lab)
h1 + geom_histogram(position="identity",alpha=0.5,color="black")

Color customizations

d <- mpg
# --------- discrete classification
# scale_fill_manual for boxplots,bars
# scale_color_manual for points, lines

# boxplot no color
p_fil <- ggplot(d) +
         aes(x=as.factor(cyl),y=cty)
p_fil + geom_boxplot()

# boxplot default ggplot fill
p_fil <- ggplot(d) +
         aes(x=as.factor(cyl),y=cty,fill=as.factor(cyl)) + 
         geom_boxplot()
plot(p_fil)

# create custom color palette
my_cols <- c("red","brown","blue","orange")

# boxplot with custom colors for fill
p_fil + scale_fill_manual(values=my_cols)

# scatterplot with no color
p_col <- ggplot(d) +
         aes(x=displ,y=cty)
p_col + geom_point(size=3)

# scatterplot default ggplot colors
p_col <- ggplot(d) +
         aes(x=displ,y=cty,col=as.factor(cyl)) + 
         geom_point(size=3)
plot(p_col)

# scatterplot with custom colors for point color
p_col + scale_color_manual(values=my_cols)

# ------- continuous classification (color gradient)

# default color gradient
p_grad <- ggplot(d) + 
          aes(x=displ,y=cty,col=hwy) + 
          geom_point(size=3)
plot(p_grad)

# custom sequential gradient (2-colors)
p_grad + scale_color_gradient(low="green", high="red")

# custom diverging gradient (3-colors)
mid <- median(d$cty)
p_grad + scale_color_gradient2(midpoint=mid,
                               low="blue",
                               mid="white",
                               high="red")

# custom diverging gradient (n-colors
p_grad + scale_color_gradientn(colors=c("blue","green","yellow","purple","orange"))

Tour of color palettes

Wes Anderson palettes
library(wesanderson)
print(wes_palettes)
## $BottleRocket1
## [1] "#A42820" "#5F5647" "#9B110E" "#3F5151" "#4E2A1E" "#550307" "#0C1707"
## 
## $BottleRocket2
## [1] "#FAD510" "#CB2314" "#273046" "#354823" "#1E1E1E"
## 
## $Rushmore1
## [1] "#E1BD6D" "#EABE94" "#0B775E" "#35274A" "#F2300F"
## 
## $Rushmore
## [1] "#E1BD6D" "#EABE94" "#0B775E" "#35274A" "#F2300F"
## 
## $Royal1
## [1] "#899DA4" "#C93312" "#FAEFD1" "#DC863B"
## 
## $Royal2
## [1] "#9A8822" "#F5CDB4" "#F8AFA8" "#FDDDA0" "#74A089"
## 
## $Zissou1
## [1] "#3B9AB2" "#78B7C5" "#EBCC2A" "#E1AF00" "#F21A00"
## 
## $Zissou1Continuous
##  [1] "#3A9AB2" "#6FB2C1" "#91BAB6" "#A5C2A3" "#BDC881" "#DCCB4E" "#E3B710"
##  [8] "#E79805" "#EC7A05" "#EF5703" "#F11B00"
## 
## $Darjeeling1
## [1] "#FF0000" "#00A08A" "#F2AD00" "#F98400" "#5BBCD6"
## 
## $Darjeeling2
## [1] "#ECCBAE" "#046C9A" "#D69C4E" "#ABDDDE" "#000000"
## 
## $Chevalier1
## [1] "#446455" "#FDD262" "#D3DDDC" "#C7B19C"
## 
## $FantasticFox1
## [1] "#DD8D29" "#E2D200" "#46ACC8" "#E58601" "#B40F20"
## 
## $Moonrise1
## [1] "#F3DF6C" "#CEAB07" "#D5D5D3" "#24281A"
## 
## $Moonrise2
## [1] "#798E87" "#C27D38" "#CCC591" "#29211F"
## 
## $Moonrise3
## [1] "#85D4E3" "#F4B5BD" "#9C964A" "#CDC08C" "#FAD77B"
## 
## $Cavalcanti1
## [1] "#D8B70A" "#02401B" "#A2A475" "#81A88D" "#972D15"
## 
## $GrandBudapest1
## [1] "#F1BB7B" "#FD6467" "#5B1A18" "#D67236"
## 
## $GrandBudapest2
## [1] "#E6A0C4" "#C6CDF7" "#D8A499" "#7294D4"
## 
## $IsleofDogs1
## [1] "#9986A5" "#79402E" "#CCBA72" "#0F0D0E" "#D9D0D3" "#8D8680"
## 
## $IsleofDogs2
## [1] "#EAD3BF" "#AA9486" "#B6854D" "#39312F" "#1C1718"
## 
## $FrenchDispatch
## [1] "#90D4CC" "#BD3027" "#B0AFA2" "#7FC0C6" "#9D9C85"
## 
## $AsteroidCity1
## [1] "#0A9F9D" "#CEB175" "#E54E21" "#6C8645" "#C18748"
## 
## $AsteroidCity2
## [1] "#C52E19" "#AC9765" "#54D8B1" "#b67c3b" "#175149" "#AF4E24"
## 
## $AsteroidCity3
## [1] "#FBA72A" "#D3D4D8" "#CB7A5C" "#5785C1"
demoplot(wes_palettes$BottleRocket1,"pie")

demoplot(wes_palettes[[2]][1:3],"bar")

my_cols <- wes_palettes$GrandBudapest2[1:4]
p_fil + scale_fill_manual(values=my_cols)

Color Brewer palettes
library(RColorBrewer)
display.brewer.all()

display.brewer.all(colorblindFriendly=TRUE)

demoplot(brewer.pal(4,"Accent"),"bar")

demoplot(brewer.pal(11,"Spectral"),"heatmap")

my_cols <- c("grey75",brewer.pal(3,"Blues"))
p_fil + scale_fill_manual(values=my_cols)

# nice for seeing hex values!
library(scales)
show_col(my_cols)

Viridis palettes
#### Making a heat map
xVar <- 1:30
yVar <- 1:5
myData <- expand.grid(xVar=xVar,yVar=yVar)
head(myData)
##   xVar yVar
## 1    1    1
## 2    2    1
## 3    3    1
## 4    4    1
## 5    5    1
## 6    6    1
zVar <- myData$xVar + myData$yVar + 2*rnorm(n=150)
myData <- cbind(myData,zVar)
head(myData)
##   xVar yVar     zVar
## 1    1    1 1.930717
## 2    2    1 4.783829
## 3    3    1 4.301021
## 4    4    1 3.626993
## 5    5    1 6.506057
## 6    6    1 5.774694
# default gradient colors in ggplot
p4 <- ggplot(myData) +
      aes(x=xVar,y=yVar,fill=zVar) +
  geom_tile()
print(p4)

# user defined divergent palette
p4 + scale_fill_gradient2(midpoint=19,
                          low="brown",
                          mid=grey(0.8),
                          high="darkblue")

# viridis scale
p4  + scale_fill_viridis_c()

# options viridis, cividis, magma, inferno, plasma
p4 + scale_fill_viridis_c(option="inferno")

#desaturated viridis
p4 <- p4 + geom_tile() + scale_fill_viridis_c() 
p4des<-edit_colors(p4, desaturate)
plot(p4des)