How to manage parallel processing with animated ggplot2-plot?

Question

I\'m trying to build an animated barplot with ggplot2 and magick that\'s growing on a \"day per day\" base. Unfortunately, I\'ve got tenthousands o

Answer 1

I would do

library(tidyverse)
library(gganimate)
x %>% 
  as.tibble() %>% 
  arrange(date) %>%  
  group_by(category) %>% 
  mutate(Sum=cumsum(value)) %>% 
  ggplot(aes(category, Sum, fill = category)) +
  geom_col(position = 'identity') + 
  ggtitle("{frame_time}") +
  transition_time(date) +
  ease_aes('linear') 
anim_save("GIF.gif")  

If it's to much data I recommend to increase the transition time to months instead of days.

Answer 2

So, my solution:

• split dates in ncores periods

• get the plot for each period and save it as a GIF

• read back all GIF and combine them

---

########################################################################
# setup
########################################################################

# creating some sample data for one year
# 4 categories; each category has a specific value per day
set.seed(1)
x <- data.frame(
  rep(as.Date((Sys.Date()-364):Sys.Date(), origin="1970-01-01"),4),
  c(rep("cat01",length.out=365),
    rep("cat02",length.out=365),
    rep("cat03",length.out=365),
    rep("cat04",length.out=365)),
  sample(0:50,365*4, replace=TRUE)
)
colnames(x) <- c("date", "category", "value")

# creating a cumulative measure making the graphs appear "growing"
library(dplyr)
x <- x %>%
  as_tibble() %>%
  arrange(date) %>%
  mutate(date = as.character(date)) %>%
  group_by(category) %>%
  mutate(cumsum = cumsum(value))

y_max <- max(x$cumsum) + 500

library(doParallel)

all_dates <- unique(x$date)
ncores <- detectCores() - 1
ind_cluster <- sort(rep_len(1:ncores, length(all_dates)))
date_cluster <- split(all_dates, ind_cluster)
registerDoParallel(cl <- makeCluster(ncores))

tmp <- tempfile()

files <- foreach(ic = 1:ncores, .packages = c("tidyverse", "magick")) %dopar% {

  img <- image_graph(1000, 700, res = 96)

  x %>%
    filter(date %in% date_cluster[[ic]]) %>%
    group_by(date) %>%
    do(
      plot = ggplot(.) +
        geom_col(aes(category, cumsum)) +
        scale_y_continuous(expand = c(0, 0), 
                           breaks = seq(0, y_max, 500), 
                           limits = c(0, y_max))
    ) %>%
  pmap(function(date, plot) {
    print(plot + ggtitle(date))
    NULL
  })

  dev.off()

  image_write(image_animate(img, fps = 5), paste0(tmp, ic, ".gif"))
}
stopCluster(cl)

test <- do.call(c, lapply(files, magick::image_read))
test