seaweed_1.R

library(ambient)
library(dplyr)

seaweed <- function(seed) {
  
  set.seed(seed)
  
  output <- here::here("images", paste0("seaweed_", seed, ".png"))
  
  # generate a random palette
  palette_name <- sample(scico::scico_palette_names(), 1)
  palette <- scico::scico(1000, palette = palette_name)
  
  
  # construct the transformed space
  grid <- long_grid(
    x = seq(-10, 10, length.out = 1000), 
    y = seq(-20, 0, length.out = 1000)
  )
  f <- runif(1, min = .3, max = .5)
  curl <- curl_noise(
    generator = gen_simplex, 
    x = grid$x, 
    y = grid$y, 
    seed = sample(1000, 1), 
    frequency = f
  )
  g <- runif(1, min = .1, max = .4)
  c <- runif(1, min = .1, max = .4)
  curl$x <- g * grid$x + c * curl$x 
  curl$y <- g * grid$y + c * curl$y 
  
  
  # frequency of waves (in transformed space) mixing the 
  # two noise components
  f <- runif(1, min = .1, max = 1)
  grid$mix <- gen_spheres(
    x = curl$x, 
    y = curl$y, 
    frequency = f
  )
  grid$mix <- normalise(grid$mix)

  
  # "a" governs the shading in the "high" regions
  grid$a <- fracture(
    noise = gen_worley,
    fractal = fbm,
    value = "distance",
    octaves = 8,
    x = curl$x,
    y = curl$y,
    seed = sample(1000, 1),
    frequency = runif(1, min = .1, max = .9)
  ) %>% normalise()

  
  # "b" governs the noise in the "low" regions
  grid$b <- fracture(
    noise = gen_worley,
    fractal = fbm,
    value = "distance",
    octaves = 8,
    x = curl$x,
    y = curl$y,
    seed = sample(1000, 1),
    frequency = runif(1, min = 1, max = 2)
  ) %>% normalise()
  
  # mix, normalise and shade the grid
  grid$pattern <- normalise(
    x = with(grid, (a * mix + (1-mix) * b)),
    to = c(.00001, 1)
  )
  grid$pattern <- ceiling(grid$pattern * 1000)
  grid$shade <- palette[grid$pattern]
  
  
  # render and save the image file
  png(output, 5000, 5000)
  op <- par(mar = c(0,0,0,0))
  rast <- as.raster(grid, value = shade)
  plot(rast)
  dev.off()
  par(op)
  
}