battlefield/optimCORR_battle.R

In samuel-rosa/spsann: Optimization of Spatial Samples via Simulated Annealing

# Initial settings
rm(list = ls())
gc()
sapply(list.files("R", full.names = TRUE, pattern = ".R$"), source)
sapply(list.files("src", full.names = TRUE, pattern = ".cpp$"), Rcpp::sourceCpp)

# 0) DEFAULT EXAMPLE ##########################################################################################
data(meuse.grid, package = "sp")
candi <- meuse.grid[1:1000, 1:2]
covars <- meuse.grid[1:1000, 5]
schedule <- scheduleSPSANN(
  initial.temperature = 5, chains = 1, x.max = 1540, y.max = 2060, 
  x.min = 0, y.min = 0, cellsize = 40)
set.seed(2001)
res <- optimCORR(
  points = 10, candi = candi, covars = covars, use.coords = TRUE, 
  schedule = schedule)
objSPSANN(res) - objCORR(
  points = res, candi = candi, covars = covars, use.coords = TRUE)

# 1) FACTOR COVARIATES WITH THE COORDINATES ###################################################################
rm(list = ls())
gc()
sapply(list.files("R", full.names = TRUE, pattern = ".R$"), source)
sapply(list.files("src", full.names = TRUE, pattern = ".cpp$"), Rcpp::sourceCpp)
data(meuse.grid)
candi <- meuse.grid[, 1:2]
covars <- meuse.grid[, 6:7]
schedule <- scheduleSPSANN(initial.temperature = 0.5, chains = 10)
set.seed(2001)
res <- optimCORR(
  points = 100, candi = candi, covars = covars, use.coords = TRUE, schedule = schedule, plotit = TRUE)
objSPSANN(res)
objCORR(points = res, candi = candi, covars = covars, use.coords = TRUE)

# 2) ADD TEN POINTS TO AN EXISTING SAMPLE CONFIGURATION #######################################################
rm(list = ls())
gc()
sapply(list.files("R", full.names = TRUE, pattern = ".R$"), source)
sapply(list.files("src", full.names = TRUE, pattern = ".cpp$"), Rcpp::sourceCpp)
data(meuse.grid)
candi <- meuse.grid[, 1:2]
covars <- meuse.grid[, 6:7]
schedule <- scheduleSPSANN(initial.temperature = 0.5)
free <- 10
set.seed(1500)
id <- sample(1:nrow(candi), 40)
fixed <- cbind(id, candi[id, ])
objCORR(points = fixed, candi = candi, covars = covars, use.coords = TRUE)
set.seed(2001)
res <- optimCORR(
  points = list(free = free, fixed = fixed), candi = candi, covars = covars, use.coords = TRUE, 
  schedule = schedule, plotit = TRUE)
objSPSANN(res)
objCORR(points = res, candi = candi, covars = covars, use.coords = TRUE)
plot(res)