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seasx_wrapper <- function(op, var, infile, outfile, nc34, overwrite, verbose, nc = NULL) {
calc_time_start <- Sys.time()
check_variable(var)
if (is.null(nc)) check_infile(infile)
check_outfile(outfile)
outfile <- correct_filename(outfile)
check_overwrite(outfile, overwrite)
check_nc_version(nc34)
##### extract data from file #####
file_data <- read_file(infile, var, nc = nc)
file_data$variable$prec <- "float"
date_time <- get_date_time(file_data$dimension_data$t, file_data$time_info$units)
months_all <- date_time$months
months_unique <- sort(unique(months_all))
years_all <- date_time$years
years_unique <- sort(unique(years_all))
# Use placeholder for result so that it can be calculated later without the
# need to have all input data in memory concurrently.
data_placeholder <- array(
file_data$variable$attributes$missing_value,
dim = c(length(file_data$dimension_data$x),
length(file_data$dimension_data$y),
1)
)
time_bnds <- get_time_bounds_1(
file_data$dimension_data$t
)
vars_data <- list(result = data_placeholder, time_bounds = time_bnds)
nc_format <- get_nc_version(nc34)
cmsaf_info <- switch(
op,
paste0("cmsafops::seasmean for variable ", file_data$variable$name),
paste0("cmsafops::seassum for variable ", file_data$variable$name),
paste0("cmsafops::seassd for variable ", file_data$variable$name),
paste0("cmsafops::seasvar for variable ", file_data$variable$name)
)
##### prepare output #####
global_att_list <- names(file_data$global_att)
global_att_list <- global_att_list[toupper(global_att_list) %in% toupper(GLOBAL_ATT_DEFAULT)]
global_attributes <- file_data$global_att[global_att_list]
dims <- define_dims(file_data$grid$is_regular,
file_data$dimension_data$x,
file_data$dimension_data$y,
time_data = 0,
NB2,
file_data$time_info$units)
vars <- define_vars(file_data$variable, dims, nc_format$compression)
write_output_file(
outfile,
nc_format$force_v4,
vars,
vars_data,
file_data$variable$name,
file_data$grid$vars, file_data$grid$vars_data,
cmsaf_info,
file_data$time_info$calendar,
file_data$variable$attributes,
global_attributes
)
##### calculate and write result #####
if (!is.null(nc)) nc_in <- nc
else nc_in <- nc_open(infile)
nc_out <- nc_open(outfile, write = TRUE)
dummy_vec <- seq_along(months_all)
count <- 1
for (i in seq_along(years_unique)) {
for (j in 1:4) {
dum <- NA
switch(j,
{
win <- which(years_all == years_unique[i] & months_all %in% c(1:2) | years_all == years_unique[i] - 1 & months_all == 12)
if (length(win) >= 3) {
dum <- win
}
},
{
spr <- which(years_all == years_unique[i] & months_all %in% c(3:5))
if (length(spr) >= 3) {
dum <- spr
}
},
{
sum <- which(years_all == years_unique[i] & months_all %in% c(6:8))
if (length(sum) >= 3) {
dum <- sum
}
},
{
aut <- which(years_all == years_unique[i] & months_all %in% c(9:11))
if (length(aut) >= 3) {
dum <- aut
}
}
)
if (all(is.na(dum))) {
if (verbose) message("Not enough data to calculate a seasonal maximum!")
next()
}
dum_dat <- array(NA, dim = c(length(file_data$dimension_data$x), length(file_data$dimension_data$y), length(dum)))
for (k in seq_along(dum)) {
if (!is.na(dum[k])) {
dum_dat[, , k] <- ncvar_get(nc_in, file_data$variable$name, start = c(1, 1, dum[k]), count = c(-1, -1, 1), collapse_degen = FALSE)
}
}
if (!(length(dum) == 3 | length(dum) > 85)) {
if (verbose) message("Not enough data to calculate a seasonal maximum!")
next()
}
switch(op,
{
if (verbose) message(paste0("apply seasonal mean ", count, " of ", 4 * length(years_unique)))
data <- rowMeans(dum_dat, dims = 2, na.rm = TRUE)
},
{
if (verbose) message(paste0("apply seasonal sum ", count, " of ", 4 * length(years_unique)))
data <- rowSums(dum_dat, dims = 2, na.rm = TRUE) * ifelse(rowSums(is.na(dum_dat), dims = 2) == dim(dum_dat)[3], NA, 1)
},
{
if (verbose) message(paste0("apply seasonal standard deviation ", count, " of ", 4 * length(years_unique)))
data <- apply(dum_dat, c(1, 2), stats::sd, na.rm = TRUE)
},
{
if (verbose) message(paste0("apply seasonal variance ", count, " of ", 4 * length(years_unique)))
data <- apply(dum_dat, c(1, 2), stats::var, na.rm = TRUE)
}
)
data[is.na(data)] <- file_data$variable$attributes$missing_value
tdum <- min(file_data$dimension_data$t[dum], na.rm = TRUE)
time_bnds[1, 1] <- min(file_data$dimension_data$t[dum], na.rm = TRUE)
time_bnds[2, 1] <- max(file_data$dimension_data$t[dum], na.rm = TRUE)
ncvar_put(nc_out, vars[[1]], data, start = c(1, 1, count), count = c(-1, -1, 1))
ncvar_put(nc_out, dims$t, tdum, start = count, count = 1)
ncvar_put(nc_out, vars[[2]], time_bnds, start = c(1, count), count = c(-1, 1))
count <- count + 1
}
}
nc_close(nc_out)
if (is.null(nc)) nc_close(nc_in)
calc_time_end <- Sys.time()
if (verbose) message(get_processing_time_string(calc_time_start, calc_time_end))
}
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