bootstrap_n_hypervolumes <- function(name, hv, n = 10, points_per_resample = 'sample_size', cores = 1, verbose = TRUE, seed = NULL) {
# check if hv is an object of class Hypervolume
# if yes, transform it to a list
if(inherits(hv, "Hypervolume")){
hv <- hypervolume_join(hv)
}
# get random state from global environment
old_state <- get0(".Random.seed", envir = .GlobalEnv, inherits = FALSE)
if(!is.null(seed)){
set.seed(seed)
}
on.exit({
# restore random state
if (!is.null(old_state)) {
assign(".Random.seed", old_state, envir = .GlobalEnv, inherits = FALSE)
}
}, add = TRUE)
# Check if cluster registered to doparallel backend exists
exists_cluster = TRUE
if(cores > 1 & getDoParWorkers() == 1) {
# If no cluster is registered, create a new one based on use input
cl = makeCluster(cores)
clusterEvalQ(cl, {
library(hypervolume)
})
registerDoParallel(cl)
exists_cluster = FALSE
}
on.exit({
# If a cluster was created for this specific function call, close cluster and register sequential backend
if(!exists_cluster) {
stopCluster(cl)
registerDoSEQ()
}
}, add = TRUE)
# Create folder to store bootstrapped hypervolumes
dir.create(file.path('./Objects', name), recursive = TRUE, showWarnings = FALSE)
# check if names are equal, if yes, add a number to make them unique
hv_names <- unlist(lapply(hv@HVList, function(x) x@Name))
if(length(unique(hv_names)) != length(hv@HVList)){
hv_names <- paste(hv_names, 1:length(hv@HVList), sep = "_")
}
# write the original order of hypervolumes, needed to avoid poor alignment when using
# hypervolume_n_occupancy
write.table(hv_names, file = file.path('./Objects', name, "log.txt"), row.names = FALSE)
if(verbose){
Fun <- function(...) progress_bar_foreach(iterator = n, fun = function (a, ...)c(a, list(...)), clear = FALSE)
} else {
Fun <- function(...) function (a, ...)c(a, list(...))
}
for(j in 1:length(hv@HVList)){
# Construct n hypervolumes from points_per_sample points sampled with replacement from original data
path_j <- file.path('./Objects', name, hv_names[j])
name_j <- dir.create(path_j, showWarnings = FALSE)
hv_j <- hv@HVList[[j]]
if(verbose){
cat("\n Permuting hypervolume", hv_names[j], "...\n")
}
foreach(i = 1:n, .combine = Fun()) %dopar% {
if(points_per_resample == 'sample_size') {
sample_dat = hv_j@Data[sample(1:nrow(hv_j@Data), nrow(hv_j@Data), replace = TRUE),]
} else {
sample_dat = hv_j@Data[sample(1:nrow(hv_j@Data), points_per_resample, replace = TRUE),]
}
h = suppressMessages(copy_param_hypervolume(hv_j, sample_dat, name = paste("resample", as.character(i))))
path = paste0(h@Name, '.rds')
saveRDS(h, file.path(path_j, path))
}
}
# Absolute path to hypervolume objects
return(file.path(getwd(), 'Objects', name))
}
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