R語(yǔ)言可視化學(xué)習(xí)筆記之ggridges包繪制山巒圖
作者：嚴(yán)濤 浙江大學(xué)作物遺傳育種在讀研究生（生物信息學(xué)方向）偽碼農(nóng)，R語(yǔ)言愛(ài)好者，愛(ài)開(kāi)源。
嚴(yán)濤老師的繪圖教程還有：
gganimate |諾獎(jiǎng)文章里面的動(dòng)圖繪制教程來(lái)了?。?/a>
ggplot2高效實(shí)用指南 (可視化腳本、工具、套路、配色)
簡(jiǎn)介
ggridges包主要用來(lái)繪制山巒圖。尤其是針對(duì)時(shí)間或者空間分布可視化具有十分好的效果。ggridges主要提供兩個(gè)幾何圖像函數(shù)：
geom_ridgeline(): 主要繪制山脊線圖
geom_density_ridges()：主要繪制密度山脊線圖
具體用法可以參考官方文檔：
https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html
geom_ridgeline()
library(ggridges)
library(tidyverse)
# grid.arrange來(lái)自于gridExtra包，可以同時(shí)拼圖多個(gè)ggplot2對(duì)象
library(gridExtra)
my_data <- data.frame(x=1:5, y=rep(1,5), height=c(0,1,-1,3,2))
plot_base <- ggplot(my_data, aes(x, y, height=height))
# 默認(rèn)負(fù)值不顯示，除非指定min_height參數(shù)
grid.arrange(plot_base+geom_ridgeline(),
? ? ? ? ? ? plot_base+geom_ridgeline(min_height=-2), ncol=2)
geom_density_ridges()
geom_density_ridges()函數(shù)首先會(huì)根據(jù)數(shù)據(jù)計(jì)算密度然后繪圖，此時(shí)美學(xué)映射height沒(méi)有必要寫(xiě)入函數(shù)中。下面使用lincoln_weather數(shù)據(jù)集。
# creates a vector of n equally spaced colors along the
# Matplolib 'viridis' color map
# also designed to be perceived by readers with the most common form of color blindness
# ?scale_fill_viridis函數(shù)來(lái)源于此包，
# 其參數(shù) option用于設(shè)置顏色 "magma" (or "A"), "inferno" (or "B"), "plasma" (or "C"),
and "viridis" (or "D", the default option).
# ?viridis可以查看其具體含義
library(viridis)
head(lincoln_weather[ ,1:4])
## # A tibble: 6 x 4
## ? CST ? ? ?`Max Temperature [F]` `Mean Temperature [F]` `Min Temperature ~
## ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
## 1 2016-1-1 ? ? ? ? ? ? ? ? ? ?37 ? ? ? ? ? ? ? ? ? ? 24 ? ? ? ? ? ? ? ? 11
## 2 2016-1-2 ? ? ? ? ? ? ? ? ? ?41 ? ? ? ? ? ? ? ? ? ? 23 ? ? ? ? ? ? ? ? ?5
## 3 2016-1-3 ? ? ? ? ? ? ? ? ? ?37 ? ? ? ? ? ? ? ? ? ? 23 ? ? ? ? ? ? ? ? ?8
## 4 2016-1-4 ? ? ? ? ? ? ? ? ? ?30 ? ? ? ? ? ? ? ? ? ? 17 ? ? ? ? ? ? ? ? ?4
## 5 2016-1-5 ? ? ? ? ? ? ? ? ? ?38 ? ? ? ? ? ? ? ? ? ? 29 ? ? ? ? ? ? ? ? 19
## 6 2016-1-6 ? ? ? ? ? ? ? ? ? ?34 ? ? ? ? ? ? ? ? ? ? 33 ? ? ? ? ? ? ? ? 32
# x后的值用 ` (反引號(hào))括起，是因?yàn)榱忻种写嬖诳崭窈吞厥庾址?，需要特殊?duì)待
# fill = ..x..， double dots是ggplot2的一種特殊識(shí)別符，用來(lái)區(qū)分定義的和計(jì)算的美學(xué)參數(shù)
# 這里指用橫軸的數(shù)據(jù)著色
ggplot(lincoln_weather, aes(x=`Mean Temperature [F]`, y=`Month`, fill=..x..))+
?geom_density_ridges_gradient(scale=3, rel_min_height=0.01, gradient_lwd = 1.)+
?scale_x_continuous(expand = c(0.01, 0))+ # 擴(kuò)展下橫軸和縱軸
?scale_y_discrete(expand = c(0.01,0))+
?scale_fill_viridis(name="Temp. [F]", option = "C")+
?labs(title="Temperature in Lincoln NE",
? ? ? subtitle="Mean temperature (Fahrenheit) by month for 2016\nData:Orogin CSV from the Weather Underground ")+
?theme_ridges(font_size = 13, grid = FALSE)+
?theme(axis.title.y = element_blank()) 
cyclinal scales
為了使得ggridges繪制的圖形可視化效果最好，同時(shí)為了減少用戶對(duì)顏色設(shè)置的困難，作者提供了cyclinal scales用于顏色輪轉(zhuǎn)映射。
ggplot(diamonds, aes(x=price, y=cut, fill=cut))+
?geom_density_ridges(scale=4)+
?scale_fill_cyclical(values = c("blue", "green"))+
?theme_ridges(grid = FALSE)
默認(rèn)的，cyclinal scales為了防止誤解是不繪制圖例的，但是可以通過(guò)選項(xiàng)guide="legend"添加圖例。
ggplot(diamonds, aes(x=price, y=cut, fill=cut))+
?geom_density_ridges(scale=4)+
?scale_fill_cyclical(values = c("blue", "green"), guide="legend")+
?theme_ridges(grid = FALSE)
跟ggplot2一樣，圖例是可以修改的,其他參數(shù)比如大小、透明度、形狀等都是可以通過(guò)cyclinal scales修改。
ggplot(diamonds, aes(x=price, y=cut, fill=cut))+
?geom_density_ridges(scale=4)+
?scale_fill_cyclical(values = c("blue", "green"), guide="legend",
? ? ? ? ? ? ? ? ? ? ?labels=c("Fair"="blue", "Good"="green"),
? ? ? ? ? ? ? ? ? ? ?name="Fill colors")+
?theme_ridges(grid = FALSE)
再來(lái)2個(gè)示例
不做解釋了，如果想重現(xiàn)就把代碼拆解開(kāi)，按需修改。一句句話單獨(dú)拆開(kāi)運(yùn)行，理解其操作內(nèi)容。
library(dplyr)
library(forcats)
Catalan_elections %>%
?mutate(YearFct = fct_rev(as.factor(Year))) %>%
?ggplot(aes(y = YearFct)) +
?geom_density_ridges(
? ?aes(x = Percent, fill = paste(YearFct, Option)),
? ?alpha = .8, color = "white", from = 0, to = 100
?) +
?labs(
? ?x = "Vote (%)",
? ?y = "Election Year",
? ?title = "Indy vs Unionist vote in Catalan elections",
? ?subtitle = "Analysis unit: municipalities (n = 949)",
? ?caption = "Marc Belzunces (@marcbeldata) | Source: Idescat"
?) +
?scale_y_discrete(expand = c(0.01, 0)) +
?scale_x_continuous(expand = c(0.01, 0)) +
?scale_fill_cyclical(
? ?breaks = c("1980 Indy", "1980 Unionist"),
? ?labels = c(`1980 Indy` = "Indy", `1980 Unionist` = "Unionist"),
? ?values = c("#ff0000", "#0000ff", "#ff8080", "#8080ff"),
? ?name = "Option", guide = "legend"
?) +
?theme_ridges(grid = FALSE)
library(DAAG) # for ais dataset
ais$sport <- factor(
?ais$sport,
?levels = c("B_Ball", "Field", "Gym", "Netball", "Row", "Swim", "T_400m", "T_Sprnt", "Tennis", "W_Polo"),
?labels = c("Basketball", "Field", "Gym", "Netball", "Row", "Swim", "Track 400m", "Track Sprint", "Tennis", "Water Polo")
)
ggplot(ais, aes(x=ht, y=sport, color=sex, point_color=sex, fill=sex)) +
?geom_density_ridges(
? ?jittered_points=TRUE, scale = .95, rel_min_height = .01,
? ?point_shape = "|", point_size = 3, size = 0.25,
? ?position = position_points_jitter(height = 0)
?) +
?scale_y_discrete(expand = c(.01, 0)) +
?scale_x_continuous(expand = c(0, 0), name = "height [cm]") +
?scale_fill_manual(values = c("#D55E0050", "#0072B250"), labels = c("female", "male")) +
?scale_color_manual(values = c("#D55E00", "#0072B2"), guide = "none") +
?scale_discrete_manual("point_color", values = c("#D55E00", "#0072B2"), guide = "none") +
?guides(fill = guide_legend(
? ?override.aes = list(
? ? ?fill = c("#D55E00A0", "#0072B2A0"),
? ? ?color = NA, point_color = NA))
?) +
?ggtitle("Height in Australian athletes") +
?theme_ridges(center = TRUE)
還有很多用法有興趣的可以查看官方文檔https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html和https://cran.r-project.org/web/packages/ggridges/vignettes/gallery.html）繼續(xù)學(xué)習(xí)。
R統(tǒng)計(jì)和作圖
一文學(xué)會(huì)網(wǎng)絡(luò)分析——Co-occurrence網(wǎng)絡(luò)圖在R中的實(shí)現(xiàn)
一個(gè)函數(shù)抓取代謝組學(xué)權(quán)威數(shù)據(jù)庫(kù)HMDB的所有表格數(shù)據(jù)
編程模板-R語(yǔ)言腳本寫(xiě)作：最簡(jiǎn)單的統(tǒng)計(jì)與繪圖，包安裝、命令行參數(shù)解析、文件讀取、表格和矢量圖輸出
R語(yǔ)言統(tǒng)計(jì)入門(mén)課程推薦——生物科學(xué)中的數(shù)據(jù)分析Data Analysis for the Life Sciences
隨機(jī)森林randomForest?分類Classification?回歸Regression
隨機(jī)森林randomForest?分類Classification?回歸Regression
R語(yǔ)言可視化學(xué)習(xí)筆記之ggridges包
萬(wàn)能轉(zhuǎn)換：R圖和統(tǒng)計(jì)表轉(zhuǎn)成發(fā)表級(jí)的Word、PPT、Excel、HTML、Latex、矢量圖等
那天空飄過(guò)的梅花月餅，是今年中秋最好的禮物
高顏值免費(fèi)在線繪圖
往期精品
心得體會(huì)?TCGA數(shù)據(jù)庫(kù)?Linux?Python?
高通量分析?免費(fèi)在線畫(huà)圖?測(cè)序歷史?超級(jí)增強(qiáng)子
生信學(xué)習(xí)視頻?PPT?EXCEL?文章寫(xiě)作?ggplot2
自學(xué)生信?2019影響因子?GSEA?單細(xì)胞?
后臺(tái)回復(fù)“生信寶典福利第一波”獲取教程合集