从动物身上学习颜色

2020-03-20 10:01:26 浏览数 (1)

介绍

"fishualize"软件包提供基于自然界最令人惊叹和最丰富多彩的生物：各自美丽的鱼的颜色，以便在R中进行绘制。

下载

  • 通过install.packages下载稳定版本的
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install.packages("fishualize")
library(fishualize)
  • 下载最新版本的
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library(devtools)
devtools::install_github("nschiett/fishualize", force = TRUE)
library(fishualize)

展示

为了调取可视化鱼的调色板，可以运行fishualize（）并指定选择。

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fishualize()

这几个颜色倒是给人某个国家国旗的感觉。

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fishualize(n = 8, option = "Hypsypops_rubicundus", end = 0.9)

用法

fish（）函数根据您喜欢的物种产生可供选择的色彩，可以使用指定物种数的'option'=“ Your_favorite”或fish_palettes（）进行指定。对于基本R图，请使用fish（）函数生成一个调色板：

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pal <- fish(256, option = "Trimma_lantana")
image(volcano, col = pal)
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pal <- fish(10, option = "Ostracion_cubicus")
image(volcano, col = pal)

该软件包还包含用于ggplot2 **绘图的色阶函数：scale_color_fish（）和scale_fill_fish（）。

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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))

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() )
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# 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()
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## Warning: Removed 1 rows containing missing values (geom_point).
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# 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() )
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# 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()
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## Warning: Removed 48 rows containing missing values (geom_point).

颜色也可以与地图一起使用。 这是世界地图上离散和连续配色方案的几个示例。

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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")
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#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")
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#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")
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#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")
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##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")
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#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")
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#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")
ggplot2 scale 配色

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