☁️🎲💻

cloudy_day.R

# generate some relaxing cloudy sky squares
#
# David Lawrence Miller (2019)

library(INLA)
library(ggplot2)

## function to simulate spatial fields
simdat <- function(n, seed, prior.range = c(5, .05),
                   prior.sigma = c(.05, .05)){
  sigma.u <- .1
  kappa <- 1
  range <- sqrt(8*1.5) / kappa

  fake.locations <- as.matrix(expand.grid(seq(0, 10, length.out=n),
                                         seq(0, 10, length.out=n)))
  mesh.sim <- inla.mesh.2d(loc = fake.locations, max.n=500)
  spde <- inla.spde2.pcmatern(mesh.sim,
                              prior.range=prior.range,
                              prior.sigma=prior.sigma)
  Qu <- inla.spde.precision(spde, theta=c(log(range), log(sigma.u)))
  u <- inla.qsample(n=1, Q=Qu, seed=seed)
  u <- u[ ,1]

  # project mesh to locations
  A <- inla.spde.make.A(mesh=mesh.sim, fake.locations)
  u <- drop(A %*% u)

  # make a data object
  dat <- data.frame(x=fake.locations[,1],
                    y=fake.locations[,2],
                    u=u)
  return(dat)
}

cloudy_boi <- function(seed=runif(1)*1000){
  ggplot(simdat(200, seed)) + geom_tile(aes(x=x,y=y,fill=u)) +
    theme_void() + coord_equal() + theme(legend.position="none") +
    scale_fill_gradient(high = "#ffffff", low = "#56B1F7")
}  
  
  

p114 <- cloudy_boi(114)
p213 <- cloudy_boi(213)
p4144 <- cloudy_boi(4144)
p8912 <- cloudy_boi(8912)

library(gridExtra)
grid.arrange(p114, p213, p4144, p8912, ncol=2)