R海拾遗-sci配色

火星娃统计

发布于 2020-09-15 15:38:14

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发布于 2020-09-15 15:38:14

文章被收录于专栏：火星娃统计

sci配色

sunqi

2020/7/19

概述

使用到的包ggsci

ggsci提供了一系列高质量的调色板，其灵感来自于科学期刊、数据可视化图书馆、科幻电影和电视节目中使用的色彩。ggsci中的调色板可以对ggplot2使用，目前支持JAMA、Lancet等杂志的配色

包的安装及使用

library("ggsci")
library("ggplot2")
library("gridExtra")
library(ggpubr)
data("diamonds")

# 离散数据的绘图

p1 = ggplot(subset(diamonds, carat >= 2.2),
       aes(x = table, y = price, colour = cut)) +
  geom_point(alpha = 0.7) +
  geom_smooth(method = "loess", alpha = 0.05, size = 1, span = 1) +
  theme_bw()

p2 = ggplot(subset(diamonds, carat > 2.2 & depth > 55 & depth < 70),
       aes(x = depth, fill = cut)) +
  geom_histogram(colour = "black", binwidth = 1, position = "dodge") +
  theme_bw()

# Nature Publishing Group主题色

p1_npg = p1 + scale_color_npg()
p2_npg = p2 + scale_fill_npg()
# A和B是原始配色，C和D为新配色
ggarrange(p1,p2,p1_npg,p2_npg,ncol=2,nrow=2,labels=c("A","B","C","D"))

# American Association for the Advancement of Science
p1_aaas = p1 + scale_color_aaas()
p2_aaas = p2 + scale_fill_aaas()
# A和B是原始配色，C和D为新配色
ggarrange(p1,p2,p1_aaas,p2_aaas,ncol=2,nrow=2,labels=c("A","B","C","D"))

# The New England Journal of Medicine

p1_nejm = p1 + scale_color_nejm()
p2_nejm = p2 + scale_fill_nejm()
# A和B是原始配色，C和D为新配色
ggarrange(p1,p2,p1_nejm,p2_nejm,ncol=2,nrow=2,labels=c("A","B","C","D"))

# Rick and Morty 配色，嘿嘿嘿
p1_rickandmorty = p1 + scale_color_rickandmorty()
p2_rickandmorty = p2 + scale_fill_rickandmorty()
# A和B是原始配色，C和D为Rick and Morty配色
ggarrange(p1,p2,p1_rickandmorty,p2_rickandmorty,ncol=2,nrow=2,labels=c("A","B","C","D"))

ggsci支持的配色方法有很多

Name	Scales	Palette Types	Palette Generator
NPG	scale_color_npg() scale_fill_npg()	“nrc”	pal_npg()
AAAS	scale_color_aaas() scale_fill_aaas()	“default”	pal_aaas()
NEJM	scale_color_nejm() scale_fill_nejm()	“default”	pal_nejm()
Lancet	scale_color_lancet() scale_fill_lancet()	“lanonc”	pal_lancet()
JAMA	scale_color_jama() scale_fill_jama()	“default”	pal_jama()
JCO	scale_color_jco() scale_fill_jco()	“default”	pal_jco()
UCSCGB	scale_color_ucscgb() scale_fill_ucscgb()	“default”	pal_ucscgb()
D3	scale_color_d3() scale_fill_d3()	“category10” “category20” “category20b” “category20c”	pal_d3()
LocusZoom	scale_color_locuszoom() scale_fill_locuszoom()	“default”	pal_locuszoom()
IGV	scale_color_igv() scale_fill_igv()	“default” “alternating”	pal_igv()
UChicago	scale_color_uchicago() scale_fill_uchicago()	“default” “light” “dark”	pal_uchicago()
Star Trek	scale_color_startrek() scale_fill_startrek()	“uniform”	pal_startrek()
Tron Legacy	scale_color_tron() scale_fill_tron()	“legacy” pal_tron()
Futurama	scale_color_futurama() scale_fill_futurama()	“planetexpress”	pal_futurama()
Rick and Morty	scale_color_rickandmorty() scale_fill_rickandmorty()	“schwifty”	pal_rickandmorty()
The Simpsons	scale_color_simpsons() scale_fill_simpsons()	“springfield”	pal_simpsons()
GSEA	scale_color_gsea() scale_fill_gsea()	“default”	pal_gsea()
Material Design	scale_color_material() scale_fill_material()	“red” “pink” “purple” “deep-purple” “indigo” “blue” “light-blue” “cyan” “teal” “green” “light-green” “lime” “yellow” “amber” “orange” “deep-orange” “brown” “grey” “blue-grey”	pal_material()

对于连续数据的配色

library("reshape2")

data("mtcars")
cor = cor(unname(cbind(mtcars, mtcars, mtcars, mtcars)))
cor_melt = melt(cor)

p3 = ggplot(cor_melt,
            aes(x = Var1, y = Var2, fill = value)) +
  geom_tile(colour = "black", size = 0.3) +
  theme_bw() +
  theme(axis.title.x = element_blank(),
        axis.title.y = element_blank())
# 使用GSEA主题
p3_gsea     = p3 + scale_fill_gsea()
p3_gsea_inv = p3 + scale_fill_gsea(reverse = TRUE)
grid.arrange(p3_gsea, p3_gsea_inv, ncol = 2)