gganimate动画

library(gganimate)
library(gapminder)
library(tidyverse)

#sudo apt install cargo
#install.packages("gifski")
data("gapminder")
glimpse(gapminder)

gapminder %>%
  select(country, pop, year, continent) %>%
  group_by(year) %>% # for each year we assign a rank
  arrange(year, -pop) %>%
  mutate(rank = 1:n()) %>% # assign ranking
  filter(rank <= 10) ->
  ranked_by_year

my_theme <- theme_classic(base_family = "Times") +
  theme(axis.text.y = element_blank()) +
  theme(axis.ticks.y = element_blank()) +
  theme(axis.line.y = element_blank()) +
  theme(legend.background = element_rect(fill = "linen")) +
  theme(plot.background = element_rect(fill = "linen")) +
  theme(panel.background = element_rect(fill = "linen"))

ggplot(data = ranked_by_year) +
  aes(group = country, fill = continent) +
  aes(xmin = 0 ,
      xmax = pop / 1000000) +
  aes(ymin = rank - .45,
      ymax = rank + .45) +
  scale_y_reverse() +
  scale_x_continuous(
    limits = c(-300, 1400),
    breaks = c(0, 400, 800, 1200),
    labels = c(0, 400, 800, 1200)) +
  labs(fill = "") +
  geom_rect(alpha = .7) +
  labs(x = 'Population (millions)') +
  aes(label = country, y = rank) +
  geom_text(col = "gray13",
            hjust = "right",
            x = -50) +
  labs(y = "") +
  scale_fill_viridis_d(option = "magma",
                       direction = -1) +
  geom_text(x = 1000 , y = -10,
            family = "Times",
            aes(label = as.character(year)),
            size = 30, col = "grey18") +
  my_theme ->
  g

g + gganimate::transition_time(year)


# transition_*(): 定义动画是根据哪个变量进行”动”.
# view_*(): 定义标尺的位置.
# shadow_*(): 影子?定义点相继出现的方式.
# enter_*()/exit_*(): 定义新数据产生和旧数据删除的方式.
# ease_aes(): 美观定义(如何让整个动画看起来更舒适).


ggplot(mtcars, aes(factor(cyl), mpg)) +
  geom_boxplot() +
  # Here comes the gganimate code
  transition_states(
    gear,
    transition_length = 2,state_length = 1) +
  enter_fade() +
  exit_shrink() +
  ease_aes('sine-in-out')

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')

ggplot(mtcars) +
  geom_boxplot(aes(factor(cyl), mpg)) +
  transition_manual(gear)

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

theme_set(theme_bw(base_size=16))
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() +
  # Here comes the gganimate code
  labs(title = '{previous_state}', x = 'GDP per capita', y = 'life expectancy') +
  transition_states(
    continent,
    transition_length = 2,
    state_length = 1
  )

#动画保存
anim_save(filename = "test.gif", animation = last_animation())
anim_save(filename = "test.mp4", animation = last_animation())


#传染病动画
library(gapminder)
library(rgdal)
GD<- readOGR("Data/guangdong.shp")
data10 <- read.csv("Data/animation.csv",header = T)

p = ggplot(GD)+
  geom_point(data= data10, aes(x = long, y = lat, colour=as.factor(type)), size=2) +
  geom_polygon( aes(x = long, y = lat, group =group), size=0.4,
                colour = "BLACK", fill = "transparent") +
  coord_map(project="conic", lat0 = 30) +
  theme_bw(base_size = 15) +
  # Here comes the gganimate specific bits
  lab(title = 'Disease in Guangdong Province in: {frame_time}', x = '', y = '') +
  transition_time(onset_date) +
  ease_aes('linear')