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Introduction

The fishualize package provides color scales for plotting in R based on nature’s most stunning and colorful organisms: teleost fishes (with a few chondrichthyan cameos). #TeamFish in its colorful glory.

Installation

install.packages("fishualize")
library(fishualize)

or for the latest development version:

library(devtools)
devtools::install_github("nschiett/fishualize", force = TRUE)
library(fishualize)

The color scales

The package contains one scale per species, defined by five dominant colors. The number of fishualized species will expand over time. For a list of fish species that are currently available, run fish_palettes().
A visual overview of the color scales can be found here.

To visualize a fish color palette, you can run fishualize() and specify your choice.

fishualize()
<img src="README_files/figure-markdown_github/tldr_vis-1.png" width="672" /> 
fishualize(n = 8, option = "Hypsypops_rubicundus", end = 0.9)
<img src="README_files/figure-markdown_github/tldr_vis-2.png" width="672" />

Usage

The fish() function produces the fish color scale based on your favorite species, which can be specified using ‘option’ = “Your_favorite” or fish_palettes()[] with the number of your species specified.

For base R plots, use the fish() function to generate a palette:

pal <- fish(256, option = "Trimma_lantana")
image(volcano, col = pal)
<img src="README_files/figure-markdown_github/tldr_base-1.png" width="672" /> 
pal <- fish(10, option = "Ostracion_cubicus")
image(volcano, col = pal)
<img src="README_files/figure-markdown_github/tldr_base-2.png" width="672" />

ggplot2

The package also contains color scale functions for ggplot2 plots: scale_color_fish() and scale_fill_fish().

library(ggplot2)
library(rfishbase)

# load data for plotting 
# 1. Create list of species names currently featured in fishualize
spp <- fishualize::fish_palettes()
# 2. Get data on the included species from FishBase using the rfishbase package
dt <- rfishbase::species(gsub("_"," ", spp))

## Warning: `data_frame()` is deprecated as of tibble 1.1.0.
## Please use `tibble()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.

dt$Importance = factor(dt$Importance, levels = c("highly commercial", "commercial", "minor commercial", "subsistence fisheries", "of no interest"))

# plot bars with discrete colors using color scheme provided by Scarus quoyi
ggplot(dt[!is.na(dt$Importance),]) +
  geom_bar(aes(x = Importance, fill = Importance)) +
  scale_fill_fish_d(option = "Scarus_quoyi") +
  theme_bw() +
  theme(axis.text.x= element_blank() )
<img src="README_files/figure-markdown_github/tldr_ggplot-1.png" width="672" /> 
# plot points with continuous colors provided by Hypsypops rubicundus
ggplot(dt) +
  geom_point(aes(x = Length, y = Vulnerability, color = Vulnerability), size = 3) +
  scale_color_fish(option = "Hypsypops_rubicundus", direction = -1) +
  theme_bw()

## Warning: Removed 12 rows containing missing values (geom_point).
<img src="README_files/figure-markdown_github/tldr_ggplot-2.png" width="672" /> 
# get ecological information from FishBase
data <- rfishbase::ecology(gsub("_"," ", spp), c("SpecCode","FeedingType", "DietTroph")) %>% 
  dplyr::left_join( rfishbase::species(gsub("_"," ", spp)))

# plot boxplots of length across feeding groups using discrete colors provided by Cirrilabrus solorensis
ggplot(data[!is.na(data$FeedingType),]) +
  geom_boxplot(aes(x = FeedingType, y = log(Length), fill = FeedingType )) +
  scale_fill_fish_d(option = "Cirrhilabrus_solorensis", labels = c("invertivore", "herbivore", "carnivore", "planktivore", "omnivore")) +
  theme_bw() +
  theme(axis.text.x= element_blank() )
<img src="README_files/figure-markdown_github/tldr_ggplot-3.png" width="672" /> 
# examine relationships between size and trophic level with vulnerability as a continuous color scheme provided by Lepomis megalotis
ggplot(data) +
  geom_point(aes(x = Length, y = DietTroph, color = Vulnerability), size = 6, alpha = 0.9) +
  scale_color_fish(option = "Lepomis_megalotis", direction = -1) +
  theme_bw()

## Warning: Removed 192 rows containing missing values (geom_point).
<img src="README_files/figure-markdown_github/tldr_ggplot-4.png" width="672" />

Colors can also be used with maps. Here are several examples of discrete and continuous color schemes on a world-map.

library(ggplot2)

#get dataset of the world's countries
world <- rnaturalearth::ne_countries(scale = "medium", returnclass = "sf")

#plot worldmap with each country's estimated population as a continuous colors scale based on the reverse colors of Whitley's Boxfish Ostracion whitleyi
ggplot(data = world) +
  geom_sf(aes(fill = pop_est)) +
  scale_fill_fish(option = "Ostracion_whitleyi", direction = -1) +
  theme_bw() +
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-1.png" width="672" /> 
#plot worldmap with each country's estimated gdp based on the colors of the Sailfin Tang Zebrasoma velifer
ggplot(data = world) +
  geom_sf(aes(fill = gdp_md_est)) +
  scale_fill_fish(option = "Zebrasoma_velifer", trans = "sqrt") +
  theme_bw()+
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-2.png" width="672" /> 
#same example as above but starting at a lighter point of the color scale
ggplot(data = world) +
  geom_sf(aes(fill = gdp_md_est)) +
  scale_fill_fish(option = "Zebrasoma_velifer", trans = "sqrt", begin = 0.3, end = 1) +
  theme_bw()+
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-3.png" width="672" /> 
#plot worldmap again, this time with countries colored by their respective regional affiliation using the colors of the Clown coris *Coris gaimard* and 'discrete = TRUE'
ggplot(data = world) +
  geom_sf(aes(fill = region_wb)) +
  scale_fill_fish(option = "Coris_gaimard", discrete = TRUE) +
  theme_bw()+
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-4.png" width="672" /> 
##same map with colors reversed
ggplot(data = world) +
  geom_sf(aes(fill = region_wb)) +
  scale_fill_fish(option = "Coris_gaimard", discrete = TRUE, direction = -1) +
  theme_bw()+
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-5.png" width="672" /> 
#another map with countries colored by economic status using the colors of the Mandarinfish *Synchiropus splendidus*
ggplot(data = world) +
  geom_sf(aes(fill = income_grp)) +
  scale_fill_fish(option = "Synchiropus_splendidus", discrete = T, alpha = 0.8) +
  theme_bw()+
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-6.png" width="672" /> 
#same map as above but with a narrower color palette in discrete values
ggplot(data = world) +
  geom_sf(aes(fill = income_grp)) +
  scale_fill_fish(option = "Synchiropus_splendidus", discrete = T, alpha = 0.8, begin = 0.3, end = 1) +
  theme_bw()+
  theme(legend.position = "top")
<img src="README_files/figure-markdown_github/ggplot2-7.png" width="672" />

Fish shapes

fishualize 2.0 enables you to add fish silhouettes to a ggplot object with the function add_fishape(). To get an overview of all available silhouettes, run fishapes().

# Default shape
ggplot() + add_fishape() +
  theme_void()
<img src="README_files/figure-markdown_github/shapes-1.png" width="672" /> 
# Species are specified with family and option
# The color and transparency of the shape is chosen with fill and alpha
# xmin, xmax, ymin, and ymax indicate the position of the fish silhouette
 ggplot(diamonds)+
   geom_bar(aes(cut, fill = cut)) +
   scale_fill_fish_d(option = "Naso_lituratus") +
   add_fishape(family = "Acanthuridae",
               option = "Naso_unicornis",
               xmin = 1, xmax = 3, ymin = 15000, ymax = 20000,
               fill = fish(option = "Naso_lituratus", n = 4)[2],
               alpha = 0.8) +
   theme_bw()
<img src="README_files/figure-markdown_github/shapes-2.png" width="672" />

Alternatively, you can specify the coordinates according to a relative scale (between 0 and 1; with scaled = TRUE). In this case, parameters xlim and ylim indicate the x and y limits of x and y. This is useful to keep the fish silhouette positioned identically across graphs with different scales.

 ggplot(diamonds)+
   geom_bar(aes(cut, fill = cut)) +
   scale_fill_fish_d(option = "Naso_lituratus") +
   add_fishape(family = "Acanthuridae",
               option = "Naso_unicornis",
               xmin = 0.3, xmax = 0.7, ymin = 0.8, ymax = 1,
               scaled = TRUE,
               xlim = c(0.5, 5.5), ylim = c(0, 21000) ,
               fill = fish(option = "Naso_lituratus", n = 5)[3],
               alpha = 1) +
   theme_bw()
<img src="README_files/figure-markdown_github/shapes relative-1.png" width="672" />

Contribute

Love it? Missing your favorite species? Check out how you can contribute to this package here

Citation

To cite package fishualize in publications use:

Nina Schiettekatte, Simon Brandl and Jordan Casey (2019). fishualize: Color Palettes Based on Fish Species. R package version 0.1.0. https://CRAN.R-project.org/package=fishualize

A BibTeX entry for LaTeX users is

@Manual{, title = {fishualize: Color Palettes Based on Fish Species}, author = {Nina Schiettekatte and Simon Brandl and Jordan Casey}, year = {2019}, note = {R package version 0.1.0}, url = {https://CRAN.R-project.org/package=fishualize}, }

Contributions

JMC, SJB, and NMDS created the color palettes, SJB drew the fish silhouettes, which are freely available here. NMDS wrote the functions. SJB, JMC, and NMDS wrote the documentation. A big thanks to everyone that submitted additional color palettes via GitHub: Jindra Lacko, Andrew Steinkruger, Adam Smit, pomboal, anhsmith, Kent Sorgon, Jean-Pierre Rossi, jdittrich, amedelin, Leonardo Donato Nunes, tesaucier, Thais Araújo, Áthila Bertoncini Andrade

Credits

The initial structure of this package was inspired by the harrypotter package by Alejandro Jiménez: https://github.com/aljrico/harrypotter