gganimate：让ggplot2图 随时而动。

常用参数

transition_*() defines how the data should be spread out and how it relates to itself across time.
view_*() defines how the positional scales should change along the animation.
shadow_*() defines how data from other points in time should be presented in the given point in time.
enter_*()/exit_*() defines how new data should appear and how old data should disappear during the course of the animation.
ease_aes() defines how different aesthetics should be eased during transitions.

实践的真知

R包安装

install.package("gganimate")
install.packages("gifski")

Preliminaries: Load gganimate & datas

rm(list = ls())  # Clear the environment
options(warn=-1) # Turn off warning message globally
library(ggplot2)
library(gganimate)

先赏为敬

ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +
  # Here comes the gganimate specific bits
  labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('linear')

庖丁解牛

library(gapminder)
theme_set(theme_bw())
head(gapminder)

ggplot(gapminder, aes(gdpPercap, lifeExp, size=pop, color=continent,frame=year)) +
  geom_point() +
  scale_x_log10() +
  transition_time(year)+
  shadow_wake(wake_length = 0.05)

图按照年份变化

ggplot(gapminder, aes(gdpPercap, lifeExp, size=pop))+
  geom_point()+
  geom_point(aes(colour = factor(year)))+
  scale_x_log10() +
  labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year)

一般来说我们都是将时间映射给frame，这也符合我们的直觉，但是这并不意味着我们只能将时间映射给frame，我们可以将任何想要的变量映射给frame。

ggplot(gapminder, aes(gdpPercap, lifeExp, size=pop, frame=continent))+
  geom_point(color="blue")+
  scale_x_log10() +
  transition_states(continent)

有一篇介绍本R包的比较好的一篇文章，大家可以自行比对学习脚本： 使用gganimate制作数据可视化gif动图

生物的坑

以下内容copy自如何让你的基因放烟花。
注：此部分内容仅觉得好玩，我还没有想到这些处理怎么展示会比较好，主要是学习以下代码。

load("fireworks.Rdata")
class(test)

>class(test)
[1] "data.frame"

ggplot(test,aes(x=subgroup,y=expression,fill=subgroup))+
  geom_boxplot()+
  geom_jitter()+
  theme_bw()

分面，表示不同基因的表达量

p <- ggplot(test,aes(x=subgroup,y=expression,fill=subgroup))+
  geom_boxplot()+
  geom_jitter()+
  theme_bw()
p +facet_grid(.~gene)

transition_*()选择分面并动态显示，transition_time()专指时间。

p <- ggplot(test,aes(x=subgroup,y=expression,fill=subgroup))+
  geom_boxplot()+
  geom_jitter()+
  theme_bw()
p +transition_states(gene,
                     state_length = 0)+
  labs(title = "{closest_state} expression(TPM)")

基因在不同分组中的动态数据展示

p <- ggplot(test,aes(x=gene,y=expression))+
  geom_boxplot(aes(color=gene),size=2)+
  geom_jitter()+
  theme_bw()
p +transition_states(subgroup,
                     transition_length = 0.1,
                     state_length = 0)+
  labs(title = "{closest_state}")

去除边界，放飞变量

p <- ggplot(test,aes(x=gene,y=expression,color=gene))+
  #geom_boxplot()+
  geom_jitter()+
  theme_bw()
p +transition_states(subgroup,
                     transition_length = 0.1,
                     state_length = 0)+
  labs(title = "{closest_state}")

巨人的肩膀

gganimate: A Grammar of Animated Graphics
Reference manual
使用gganimate制作数据可视化gif动图
如何让你的基因放烟花

生物的坑数据 提取码: a55g