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LimnoPalettes

Table of Contents

Code and general idea inspired by the “Wes Anderson Palettes” R-Package.

Citing package 

citation('LimnoPalettes')
## 
## To cite package 'LimnoPalettes' in publications use:
## 
##   Paul Julian (2020). LimnoPalettes: A Limnology Themed Palette
##   Generator. R package version 0.1.0.
##   https://github.com/SwampThingPaul/LimnoPalettes
## 
## A BibTeX entry for LaTeX users is
## 
##   @Manual{,
##     title = {LimnoPalettes: A Limnology Themed Palette Generator},
##     author = {Paul Julian},
##     year = {2020},
##     note = {R package version 0.1.0},
##     url = {https://github.com/SwampThingPaul/LimnoPalettes},
##   }

Installation 

install.packages("devtools");# if you do not have it installed on your PC
devtools::install_github("SwampThingPaul/LimnoPalettes")

Now Presenting…

Working Examples. 

set.seed(1)
dat = data.frame(Group=c(rep("A",10),rep("B",10),rep("C",10),rep("D",10)),
                  var1=rnorm(40),var2=runif(40,1,15),var3=rpois(40,3))

cols = limno_palette("SuperIce",4)
boxplot(var2~Group,dat, col=cols)

cols = limno_palette("IowaSummer",4,"continuous")
cols2 = cols[dat$Group]
plot(var2~var3,dat,pch=21,bg=cols2,cex=2)

cols = limno_palette("PeriFA",4,"continuous")
barplot(aggregate(dat$var3,list(dat$Group),mean)$x,names.arg=unique(dat$Group),ylim=c(0,4),col=cols)

While not a part of this package, for data visualization purposes it would be a good idea to see how these colors are perceived for people with color blindness.

library(colorBlindness)
mat = matrix(1:81, nrow = 9, ncol = 9)

library(ggplot2)
library(reshape2)
cols = limno_palette("IowaSummer")

mat1 = melt(t(mat[9:1, ]))
len = length(cols)-1
mat1$v2 = cut(mat1$value,
              breaks = seq(0,ceiling(81/len)*len, 
                           length.out = len+1))
ht = ggplot(mat1) + 
  geom_tile(aes(x=Var1, y=Var2, fill=v2)) + 
  scale_fill_manual(values=cols) + 
  theme_bw()

# check the plot by CVD simulator
cvdPlot(ht)

# Second Example
cols = limno_palette("Bloom2",10, "continuous")

mat1 = melt(t(mat[9:1, ]))
len = length(cols)-1
mat1$v2 = cut(mat1$value,
              breaks = seq(0,ceiling(81/len)*len, 
                           length.out = len+1))
ht = ggplot(mat1) + 
  geom_tile(aes(x=Var1, y=Var2, fill=v2)) + 
  scale_fill_manual(values=cols) + 
  theme_bw()

# check the plot by CVD simulator
cvdPlot(ht)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.