Last year, inspired by a tweet from Ilya Kashnitsky, I wrote a snow animation which you can read all about here.

Now, this year, the old code no longer worked due to an update to the gganimate API. Hence, I was about to only refactor the code, but decided to give the whole thing a minor update. Below, you find the 2.0 version of my R snow animation.

# PACKAGES ####

pkg <- c("here", "tidyverse", "gganimate", "animation")

sapply(pkg, function(x){

if (!x %in% installed.packages()){install.packages(x)}

library(x, character.only = TRUE)

})



# CUSTOM FUNCTIONS ####

map_to_range <- function(x, from, to) {

# Shifting the vector so that min(x) == 0

x <- x - min(x)

# Scaling to the range of [0, 1]

x <- x / max(x)

# Scaling to the needed amplitude

x <- x * (to - from)

# Shifting to the needed level

x + from

}



# CONSTANTS ####

N <- 500 # number of flakes

TIMES <- 100 # number of loops

XPOS_DELTA <- 0.01

YSPEED_MIN = 0.005

YSPEED_MAX = 0.03

FLAKE_SIZE_COINFLIP = 5

FLAKE_SIZE_COINFLIP_PROB = 0.1

FLAKE_SIZE_MIN = 4

FLAKE_SIZE_MAX = 20



# INITIALIZE DATA ####

set.seed(1)



size <- runif(N) + rbinom(N, FLAKE_SIZE_COINFLIP, FLAKE_SIZE_COINFLIP_PROB) # random flake size

yspeed <- map_to_range(size, YSPEED_MIN, YSPEED_MAX)



# create storage vectors

xpos <- rep(NA, N * TIMES)

ypos <- rep(NA, N * TIMES)



# loop through simulations

for(i in seq(TIMES)){

if(i == 1){

# initiate values

xpos[1:N] <- runif(N, min = -0.1, max = 1.1)

ypos[1:N] <- runif(N, min = 1.1, max = 2)

} else {

# specify datapoints to update

first_obs <- (N * i - N + 1)

last_obs <- (N * i)

# update x position

# random shift

xpos[first_obs:last_obs] <- xpos[(first_obs-N):(last_obs-N)] - runif(N, min = -XPOS_DELTA, max = XPOS_DELTA)

# update y position

# lower by yspeed

ypos[first_obs:last_obs] <- ypos[(first_obs-N):(last_obs-N)] - yspeed

# reset if passed bottom screen

xpos <- ifelse(ypos < -0.1, runif(N), xpos) # restart at random x

ypos <- ifelse(ypos < -0.1, 1.1, ypos) # restart just above top

}

}





# VISUALIZE DATA ####

cbind.data.frame(ID = rep(1:N, TIMES)

,x = xpos

,y = ypos

,s = size

,t = rep(1:TIMES, each = N)) %>%

# create animation

ggplot() +

geom_point(aes(x, y, size = s, alpha = s), color = "white", pch = 42) +

scale_size_continuous(range = c(FLAKE_SIZE_MIN, FLAKE_SIZE_MAX)) +

scale_alpha_continuous(range = c(0.2, 0.8)) +

coord_cartesian(c(0, 1), c(0, 1)) +

theme_void() +

theme(legend.position = "none",

panel.background = element_rect("black")) +

transition_time(t) +

ease_aes('linear') ->

snow_plot



snow_anim <- animate(snow_plot, nframes = TIMES, width = 600, height = 600)

If you want to see some spin-offs of last years code: