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#'Save objects of class 's2dv_cube' to data in NetCDF format
#'
#'@author Perez-Zanon Nuria, \email{nuria.perez@bsc.es}
#'
#'@description This function allows to divide and save a object of class
#''s2dv_cube' into a NetCDF file, allowing to reload the saved data using
#'\code{CST_Start} or \code{CST_Load} functions. It also allows to save any
#''s2dv_cube' object that follows the NetCDF attributes conventions.
#'@param data An object of class \code{s2dv_cube}.
#'@param destination A character string containing the directory name in which
#' to save the data. NetCDF file for each starting date are saved into the
#' folder tree: 'destination/Dataset/variable/'. By default the function
#' saves the data into the working directory.
#'@param sdate_dim A character string indicating the name of the start date
#' dimension. By default, it is set to 'sdate'. It can be NULL if there is no
#' start date dimension.
#'@param ftime_dim A character string indicating the name of the forecast time
#' dimension. If 'Dates' are used, it can't be NULL. If there is no forecast
#' time dimension, 'Dates' will be set to NULL and will not be used. By
#' default, it is set to 'time'.
#'@param dat_dim A character string indicating the name of dataset dimension.
#' It can be NULL if there is no dataset dimension. By default, it is set to
#' 'dataset'.
#'@param var_dim A character string indicating the name of variable dimension.
#' It can be NULL if there is no variable dimension. By default, it is set to
#' 'var'.
#'@param memb_dim A character string indicating the name of the member
#' dimension. It can be NULL if there is no member dimension. By default, it is
#' set to 'member'.
#'@param startdates A vector of dates that will be used for the filenames
#' when saving the data in multiple files (single_file = FALSE). It must be a
#' vector of the same length as the start date dimension of data. It must be a
#' vector of class \code{Dates}, \code{'POSIXct'} or character with lenghts
#' between 1 and 10. If it is NULL, the coordinate corresponding the the start
#' date dimension or the first Date of each time step will be used as the name
#' of the files. It is NULL by default.
#'@param single_file A logical value indicating if all object is saved in a
#' single file (TRUE) or in multiple files (FALSE). When it is FALSE,
#' the array is separated for datasets, variable and start date. When there are
#' no specified time dimensions, the data will be saved in a single file by
#' default. The output file name when 'single_file' is TRUE is a character
#' string containing: '<var>_<first_sdate>_<last_sdate>.nc'; when it is FALSE,
#' it is '<var>_<sdate>.nc'. It is FALSE by default.
#'@param drop_dims (optional) A vector of character strings indicating the
#' dimension names of length 1 that need to be dropped in order that they don't
#' appear in the netCDF file. Only is allowed to drop dimensions that are not
#' used in the computation. The dimensions used in the computation are the ones
#' specified in: sdate_dim, ftime_dim, dat_dim, var_dim and memb_dim. It is
#' NULL by default.
#'@param extra_string (Optional) A character string to be included as part of
#' the file name, for instance, to identify member or realization. When
#' single_file is TRUE, the 'extra_string' will substitute all the default
#' file name; when single_file is FALSE, the 'extra_string' will be added
#' in the file name as: '<var>_<extra_string>_<sdate>.nc'. It is NULL by
#' default.
#'@param units_hours_since (Optional) A logical value only available for the
#' case: 'Dates' have forecast time and start date dimension, 'single_file' is
#' TRUE and 'time_bounds' are not used. When it is TRUE, it saves the forecast
#' time with units of 'hours since'; if it is FALSE, the time units will be a
#' number of time steps with its corresponding frequency (e.g. n days, n months
#' or n hours). It is FALSE by default.
#'@param global_attrs (Optional) A list with elements containing the global
#' attributes to be saved in the NetCDF.
#'@return Multiple or single NetCDF files containing the data array.\cr
#' All data is saved in a single file located in the specified destination
#' path with the following name (by default):
#' '<variable_name>_<first_sdate>_<last_sdate>.nc'. Multiple variables
#' are saved separately in the same file. The forecast time units
#' are calculated from each start date (if sdate_dim is not NULL) or from
#' the time step. If 'units_hours_since' is TRUE, the forecast time units
#' will be 'hours since <each start date>'. If 'units_hours_since' is FALSE,
#' the forecast time units are extracted from the frequency of the time steps
#' (hours, days, months); if no frequency is found, the units will be ’hours
#' since’. When the time units are 'hours since' the time ateps are assumed to
#' be equally spaced.
#' The data array is subset and stored into multiple files. Each file
#' contains the data subset for each start date, variable and dataset. Files
#' with different variables and datasets are stored in separated directories
#' within the following directory tree: 'destination/Dataset/variable/'.
#' The name of each file will be by default: '<variable_name>_<sdate>.nc'.
#' The forecast time units are calculated from each start date (if sdate_dim
#' is not NULL) or from the time step. The forecast time units will be 'hours
#' since <each start date>'.
#'
#'@seealso \code{\link[startR]{Start}}, \code{\link{as.s2dv_cube}} and
#'\code{\link{s2dv_cube}}
#'\dontrun{
#'CST_SaveExp(data = data, ftime_dim = 'ftime', var_dim = 'var',
#' dat_dim = 'dataset', sdate_dim = 'sdate')
#'}
CST_SaveExp <- function(data, destination = "./", startdates = NULL,
sdate_dim = 'sdate', ftime_dim = 'time',
memb_dim = 'member', dat_dim = 'dataset',
var_dim = 'var', drop_dims = NULL,
single_file = FALSE, extra_string = NULL,
global_attrs = NULL, units_hours_since = FALSE) {
stop("Parameter 'data' must be of the class 's2dv_cube'.")
# Check object structure
if (!all(c('data', 'attrs') %in% names(data))) {
stop("Parameter 'data' must have at least 'data' and 'attrs' elements ",
"within the 's2dv_cube' structure.")
}
if (!inherits(data$attrs, 'list')) {
stop("Level 'attrs' must be a list with at least 'Dates' element.")
}
# metadata
if (!is.null(data$attrs$Variable$metadata)) {
if (!inherits(data$attrs$Variable$metadata, 'list')) {
stop("Element metadata from Variable element in attrs must be a list.")
}
}
# Dates
if (is.null(data$attrs$Dates)) {
stop("Element 'Dates' from 'attrs' level cannot be NULL.")
}
if (is.null(dim(data$attrs$Dates))) {
stop("Element 'Dates' from 'attrs' level must have time dimensions.")
}
# sdate_dim
if (!is.null(sdate_dim)) {
if (!is.character(sdate_dim)) {
stop("Parameter 'sdate_dim' must be a character string.")
}
# startdates
if (is.null(startdates)) {
if (is.character(data$coords[[sdate_dim]])) {
startdates <- data$coords[[sdate_dim]]
}
destination = destination,
coords = data$coords,
Dates = data$attrs$Dates,
time_bounds = data$attrs$time_bounds,
startdates = startdates,
varname = data$attrs$Variable$varName,
metadata = data$attrs$Variable$metadata,
Datasets = data$attrs$Datasets,
sdate_dim = sdate_dim, ftime_dim = ftime_dim,
dat_dim = dat_dim, var_dim = var_dim,
drop_dims = drop_dims,
single_file = single_file,
global_attrs = global_attrs,
units_hours_since = units_hours_since)
}
#'Save a multidimensional array with metadata to data in NetCDF format
#'@description This function allows to save a data array with metadata into a
#'NetCDF file, allowing to reload the saved data using \code{Start} function
#'from StartR package. If the original 's2dv_cube' object has been created from
#'\code{CST_Load()}, then it can be reloaded with \code{Load()}.
#'
#'@author Perez-Zanon Nuria, \email{nuria.perez@bsc.es}
#'
#'@param data A multi-dimensional array with named dimensions.
#'@param destination A character string indicating the path where to store the
#' NetCDF files.
#'@param coords A named list with elements of the coordinates corresponding to
#' the dimensions of the data parameter. The names and length of each element
#' must correspond to the names of the dimensions. If any coordinate is not
#' provided, it is set as an index vector with the values from 1 to the length
#' of the corresponding dimension.
#'@param Dates A named array of dates with the corresponding sdate and forecast
#' time dimension. If there is no sdate_dim, you can set it to NULL.
#' It must have ftime_dim dimension.
#'@param time_bounds (Optional) A list of two arrays of dates containing
#' the lower (first array) and the upper (second array) time bounds
#' corresponding to Dates. Each array must have the same dimensions as Dates.
#' If 'Dates' parameter is NULL, 'time_bounds' are not used. It is NULL by
#' default.
#'@param startdates A vector of dates that will be used for the filenames
#' when saving the data in multiple files (single_file = FALSE). It must be a
#' vector of the same length as the start date dimension of data. It must be a
#' vector of class \code{Dates}, \code{'POSIXct'} or character with lenghts
#' between 1 and 10. If it is NULL, the coordinate corresponding the the start
#' date dimension or the first Date of each time step will be used as the name
#' of the files. It is NULL by default.
#'@param varname A character string indicating the name of the variable to be
#'@param metadata A named list where each element is a variable containing the
#' corresponding information. The information must be contained in a list of
#' lists for each variable.
#'@param Datasets A vector of character string indicating the names of the
#' datasets.
#'@param sdate_dim A character string indicating the name of the start date
#' dimension. By default, it is set to 'sdate'. It can be NULL if there is no
#' start date dimension.
#'@param ftime_dim A character string indicating the name of the forecast time
#' dimension. By default, it is set to 'time'. It can be NULL if there is no
#' forecast time dimension.
#'@param dat_dim A character string indicating the name of dataset dimension.
#' By default, it is set to 'dataset'. It can be NULL if there is no dataset
#' dimension.
#'@param var_dim A character string indicating the name of variable dimension.
#' By default, it is set to 'var'. It can be NULL if there is no variable
#' dimension.
#'@param memb_dim A character string indicating the name of the member
#' dimension. By default, it is set to 'member'. It can be NULL if there is no
#' member dimension.
#'@param drop_dims (optional) A vector of character strings indicating the
#' dimension names of length 1 that need to be dropped in order that they don't
#' appear in the netCDF file. Only is allowed to drop dimensions that are not
#' used in the computation. The dimensions used in the computation are the ones
#' specified in: sdate_dim, ftime_dim, dat_dim, var_dim and memb_dim. It is
#' NULL by default.
#'@param single_file A logical value indicating if all object is saved in a
#' single file (TRUE) or in multiple files (FALSE). When it is FALSE,
#' the array is separated for datasets, variable and start date. When there are
#' no specified time dimensions, the data will be saved in a single file by
#' default. The output file name when 'single_file' is TRUE is a character
#' string containing: '<var>_<first_sdate>_<last_sdate>.nc'; when it is FALSE,
#' it is '<var>_<sdate>.nc'. It is FALSE by default.
#'@param extra_string (Optional) A character string to be included as part of
#' the file name, for instance, to identify member or realization. When
#' single_file is TRUE, the 'extra_string' will substitute all the default
#' file name; when single_file is FALSE, the 'extra_string' will be added
#' in the file name as: '<var>_<extra_string>_<sdate>.nc'. It is NULL by
#' default.
#'@param global_attrs (Optional) A list with elements containing the global
#' attributes to be saved in the NetCDF.
#'@param units_hours_since (Optional) A logical value only available for the
#' case: Dates have forecast time and start date dimension, single_file is
#' TRUE and 'time_bounds' is NULL. When it is TRUE, it saves the forecast time
#' with units of 'hours since'; if it is FALSE, the time units will be a number
#' of time steps with its corresponding frequency (e.g. n days, n months or n
#' hours). It is FALSE by default.
#'@return Multiple or single NetCDF files containing the data array.\cr
#' All data is saved in a single file located in the specified destination
#' path with the following name (by default):
#' '<variable_name>_<first_sdate>_<last_sdate>.nc'. Multiple variables
#' are saved separately in the same file. The forecast time units
#' are calculated from each start date (if sdate_dim is not NULL) or from
#' the time step. If 'units_hours_since' is TRUE, the forecast time units
#' will be 'hours since <each start date>'. If 'units_hours_since' is FALSE,
#' the forecast time units are extracted from the frequency of the time steps
#' (hours, days, months); if no frequency is found, the units will be ’hours
#' since’. When the time units are 'hours since' the time ateps are assumed to
#' be equally spaced.
#'\item{\code{single_file is FALSE}}{
#' The data array is subset and stored into multiple files. Each file
#' contains the data subset for each start date, variable and dataset. Files
#' with different variables and datasets are stored in separated directories
#' within the following directory tree: 'destination/Dataset/variable/'.
#' The name of each file will be by default: '<variable_name>_<sdate>.nc'.
#' The forecast time units are calculated from each start date (if sdate_dim
#' is not NULL) or from the time step. The forecast time units will be 'hours
#' since <each start date>'.
#'\dontrun{
#'data <- lonlat_temp_st$exp$data
#'lon <- lonlat_temp_st$exp$coords$lon
#'lat <- lonlat_temp_st$exp$coords$lat
#'Datasets <- lonlat_temp_st$exp$attrs$Datasets
#'Dates <- lonlat_temp_st$exp$attrs$Dates
#'metadata <- lonlat_temp_st$exp$attrs$Variable$metadata
#'SaveExp(data = data, coords = coords, Datasets = Datasets, varname = varname,
#' Dates = Dates, metadata = metadata, single_file = TRUE,
#' ftime_dim = 'ftime', var_dim = 'var', dat_dim = 'dataset')
#'}
#'@importFrom s2dv Reorder
#'@import multiApply
#'@importFrom ClimProjDiags Subset
SaveExp <- function(data, destination = "./", coords = NULL,
Dates = NULL, time_bounds = NULL, startdates = NULL,
varname = NULL, metadata = NULL, Datasets = NULL,
sdate_dim = 'sdate', ftime_dim = 'time',
memb_dim = 'member', dat_dim = 'dataset', var_dim = 'var',
drop_dims = NULL, single_file = FALSE, extra_string = NULL,
global_attrs = NULL, units_hours_since = FALSE) {
## Initial checks
# data
if (is.null(data)) {
stop("Parameter 'data' cannot be NULL.")
}
dimnames <- names(dim(data))
if (is.null(dimnames)) {
stop("Parameter 'data' must be an array with named dimensions.")
}
if (!is.null(attributes(data)$dimensions)) {
attributes(data)$dimensions <- NULL
}
# destination
if (!is.character(destination) | length(destination) > 1) {
stop("Parameter 'destination' must be a character string of one element ",
"indicating the name of the file (including the folder if needed) ",
"where the data will be saved.")
}
Eva Rifà
committed
# drop_dims
if (!is.null(drop_dims)) {
if (!is.character(drop_dims) | any(!drop_dims %in% names(dim(data)))) {
warning("Parameter 'drop_dims' must be character string containing ",
"the data dimension names to be dropped. It will not be used.")
} else if (!all(dim(data)[drop_dims] %in% 1)) {
warning("Parameter 'drop_dims' can only contain dimension names ",
"that are of length 1. It will not be used.")
} else if (any(drop_dims %in% c(ftime_dim, sdate_dim, dat_dim, memb_dim, var_dim))) {
warning("Parameter 'drop_dims' contains dimensions used in the computation. ",
"It will not be used.")
drop_dims <- NULL
Eva Rifà
committed
} else {
data <- Subset(x = data, along = drop_dims,
indices = lapply(1:length(drop_dims), function(x) 1),
drop = 'selected')
dimnames <- names(dim(data))
}
}
if (!inherits(coords, 'list')) {
stop("Parameter 'coords' must be a named list of coordinates.")
}
if (is.null(names(coords))) {
stop("Parameter 'coords' must have names corresponding to coordinates.")
}
} else {
coords <- sapply(dimnames, function(x) 1:dim(data)[x])
}
# varname
if (is.null(varname)) {
varname <- 'X'
} else if (length(varname) > 1) {
multiple_vars <- TRUE
} else {
multiple_vars <- FALSE
}
if (!all(sapply(varname, is.character))) {
stop("Parameter 'varname' must be a character string with the ",
"variable names.")
}
# single_file
if (!inherits(single_file, 'logical')) {
warning("Parameter 'single_file' must be a logical value. It will be ",
"set as FALSE.")
single_file <- FALSE
if (!is.null(extra_string)) {
if (!is.character(extra_string)) {
stop("Parameter 'extra_string' must be a character string.")
}
}
# global_attrs
if (!is.null(global_attrs)) {
if (!inherits(global_attrs, 'list')) {
stop("Parameter 'global_attrs' must be a list.")
}
}
## Dimensions checks
# Spatial coordinates
if (!any(dimnames %in% .KnownLonNames()) |
!any(dimnames %in% .KnownLatNames())) {
lon_dim <- NULL
lat_dim <- NULL
} else {
lon_dim <- dimnames[which(dimnames %in% .KnownLonNames())]
lat_dim <- dimnames[which(dimnames %in% .KnownLatNames())]
}
# ftime_dim
if (!is.null(ftime_dim)) {
if (!is.character(ftime_dim)) {
stop("Parameter 'ftime_dim' must be a character string.")
}
if (!all(ftime_dim %in% dimnames)) {
stop("Parameter 'ftime_dim' is not found in 'data' dimension. Set it ",
"as NULL if there is no forecast time dimension.")
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}
}
# sdate_dim
if (!is.null(sdate_dim)) {
if (!is.character(sdate_dim)) {
stop("Parameter 'sdate_dim' must be a character string.")
}
if (!all(sdate_dim %in% dimnames)) {
stop("Parameter 'sdate_dim' is not found in 'data' dimension.")
}
}
# memb_dim
if (!is.null(memb_dim)) {
if (!is.character(memb_dim)) {
stop("Parameter 'memb_dim' must be a character string.")
}
if (!all(memb_dim %in% dimnames)) {
stop("Parameter 'memb_dim' is not found in 'data' dimension. Set it ",
"as NULL if there is no member dimension.")
}
}
# dat_dim
if (!is.null(dat_dim)) {
if (!is.character(dat_dim)) {
stop("Parameter 'dat_dim' must be a character string.")
}
if (!all(dat_dim %in% dimnames)) {
stop("Parameter 'dat_dim' is not found in 'data' dimension. Set it ",
"as NULL if there is no Datasets dimension.")
}
n_datasets <- dim(data)[dat_dim]
} else {
n_datasets <- 1
}
# var_dim
if (!is.null(var_dim)) {
if (!is.character(var_dim)) {
stop("Parameter 'var_dim' must be a character string.")
}
if (!all(var_dim %in% dimnames)) {
stop("Parameter 'var_dim' is not found in 'data' dimension. Set it ",
"as NULL if there is no variable dimension.")
}
n_vars <- dim(data)[var_dim]
} else {
n_vars <- 1
}
# minimum dimensions
if (all(dimnames %in% c(var_dim, dat_dim))) {
if (!single_file) {
warning("Parameter data has only ",
paste(c(var_dim, dat_dim), collapse = ' and '), " dimensions ",
"and it cannot be splitted in multiple files. All data will ",
"be saved in a single file.")
single_file <- TRUE
}
}
if (!any(inherits(Dates, "POSIXct"), inherits(Dates, "Date"))) {
stop("Parameter 'Dates' must be of 'POSIXct' or 'Dates' class.")
if (is.null(dim(Dates))) {
stop("Parameter 'Dates' must have dimension names.")
}
if (all(is.null(ftime_dim), is.null(sdate_dim))) {
warning("Parameters 'ftime_dim' and 'sdate_dim' can't both be NULL ",
"if 'Dates' are used. 'Dates' will not be used.")
Dates <- NULL
}
# sdate_dim in Dates
if (!is.null(sdate_dim)) {
if (!sdate_dim %in% names(dim(Dates))) {
warning("Parameter 'sdate_dim' is not found in 'Dates' dimension. ",
"Dates will not be used.")
Dates <- NULL
}
# ftime_dim in Dates
if (!is.null(ftime_dim)) {
if (!ftime_dim %in% names(dim(Dates))) {
warning("Parameter 'ftime_dim' is not found in 'Dates' dimension. ",
"Dates will not be used.")
Dates <- NULL
}
}
# time_bounds
if (!is.null(time_bounds)) {
if (!inherits(time_bounds, 'list')) {
stop("Parameter 'time_bounds' must be a list with two dates arrays.")
}
time_bounds_dims <- lapply(time_bounds, function(x) dim(x))
if (!identical(time_bounds_dims[[1]], time_bounds_dims[[2]])) {
stop("Parameter 'time_bounds' must have 2 arrays with same dimensions.")
}
if (is.null(Dates)) {
time_bounds <- NULL
} else {
name_tb <- sort(names(time_bounds_dims[[1]]))
name_dt <- sort(names(dim(Dates)))
if (!identical(dim(Dates)[name_dt], time_bounds_dims[[1]][name_tb])) {
stop(paste0("Parameter 'Dates' and 'time_bounds' must have same length ",
"of all dimensions."))
}
}
}
# Dates (2): Check dimensions
if (!is.null(Dates)) {
if (any(dim(Dates)[!names(dim(Dates)) %in% c(ftime_dim, sdate_dim)] != 1)) {
stop("Parameter 'Dates' can have only 'sdate_dim' and 'ftime_dim' ",
"dimensions of length greater than 1.")
}
# drop dimensions of length 1 different from sdate_dim and ftime_dim
dim(Dates) <- dim(Dates)[names(dim(Dates)) %in% c(ftime_dim, sdate_dim)]
# add ftime if needed
if (is.null(ftime_dim)) {
warning("A 'time' dimension of length 1 will be added to 'Dates'.")
dim(Dates) <- c(time = 1, dim(Dates))
dim(data) <- c(time = 1, dim(data))
dimnames <- names(dim(data))
ftime_dim <- 'time'
if (!is.null(time_bounds)) {
time_bounds <- lapply(time_bounds, function(x) {
dim(x) <- c(time = 1, dim(x))
return(x)
})
units_hours_since <- TRUE
}
# add sdate if needed
if (is.null(sdate_dim)) {
if (!single_file) {
dim(Dates) <- c(dim(Dates), sdate = 1)
dim(data) <- c(dim(data), sdate = 1)
dimnames <- names(dim(data))
sdate_dim <- 'sdate'
if (!is.null(time_bounds)) {
time_bounds <- lapply(time_bounds, function(x) {
dim(x) <- c(dim(x), sdate = 1)
return(x)
})
}
if (!is.null(startdates)) {
if (length(startdates) != 1) {
warning("Parameter 'startdates' must be of length 1 if 'sdate_dim' is NULL.",
"They won't be used.")
startdates <- NULL
}
}
units_hours_since <- TRUE
}
# startdates
if (!is.null(Dates)) {
# check startdates
if (is.null(startdates)) {
startdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected')
} else if (any(nchar(startdates) > 10, nchar(startdates) < 1)) {
warning("Parameter 'startdates' should be a character string containing ",
"the start dates in the format 'yyyy-mm-dd', 'yyyymmdd', 'yyyymm', ",
"'POSIXct' or 'Dates' class. Files will be named with Dates instead.")
startdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected')
}
} else if (!single_file) {
warning("Dates must be provided if 'data' must be saved in separated files. ",
"All data will be saved in a single file.")
single_file <- TRUE
}
# startdates
if (is.null(startdates)) {
if (is.null(sdate_dim)) {
startdates <- 'XXX'
} else {
startdates <- rep('XXX', dim(data)[sdate_dim])
}
} else {
if (any(inherits(startdates, "POSIXct"), inherits(startdates, "Date"))) {
startdates <- format(startdates, "%Y%m%d")
}
if (!is.null(sdate_dim)) {
if (dim(data)[sdate_dim] != length(startdates)) {
warning(paste0("Parameter 'startdates' doesn't have the same length ",
"as dimension '", sdate_dim,"', it will not be used."))
startdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected')
startdates <- format(startdates, "%Y%m%d")
}
}
# Datasets
if (is.null(Datasets)) {
Datasets <- rep('XXX', n_datasets )
if (inherits(Datasets, 'list')) {
Datasets <- names(Datasets)
if (n_datasets > length(Datasets)) {
warning("Dimension 'Datasets' in 'data' is greater than those listed in ",
"element 'Datasets' and the first element will be reused.")
Datasets <- c(Datasets, rep(Datasets[1], n_datasets - length(Datasets)))
} else if (n_datasets < length(Datasets)) {
warning("Dimension 'Datasets' in 'data' is smaller than those listed in ",
"element 'Datasets' and only the firsts elements will be used.")
Datasets <- Datasets[1:n_datasets]
## NetCDF dimensions definition
excluded_dims <- var_dim
if (!is.null(Dates)) {
excluded_dims <- c(excluded_dims, sdate_dim, ftime_dim)
}
if (!single_file) {
excluded_dims <- c(excluded_dims, dat_dim)
}
alldims <- c(dat_dim, var_dim, sdate_dim, lon_dim, lat_dim, ftime_dim, memb_dim)
if (!all(dimnames %in% alldims)) {
unknown_dims <- dimnames[which(!dimnames %in% alldims)]
memb_dim <- c(memb_dim, unknown_dims)
}
filedims <- c(dat_dim, var_dim, sdate_dim, lon_dim, lat_dim, ftime_dim, memb_dim)
filedims <- filedims[which(!filedims %in% excluded_dims)]
# Delete unneded coords
coords[c(names(coords)[!names(coords) %in% filedims])] <- NULL
out_coords <- NULL
if (i_coord %in% names(coords)) {
if (length(coords[[i_coord]]) != dim(data)[i_coord]) {
warning(paste0("Coordinate '", i_coord, "' has different lenght as ",
"its dimension and it will not be used."))
out_coords[[i_coord]] <- 1:dim(data)[i_coord]
} else if (is.numeric(coords[[i_coord]])) {
out_coords[[i_coord]] <- as.vector(coords[[i_coord]])
out_coords[[i_coord]] <- 1:dim(data)[i_coord]
out_coords[[i_coord]] <- 1:dim(data)[i_coord]
dim(out_coords[[i_coord]]) <- dim(data)[i_coord]
## metadata
if (i_coord %in% names(metadata)) {
if ('variables' %in% names(attributes(metadata[[i_coord]]))) {
# from Start: 'lon' or 'lat'
attrs <- attributes(metadata[[i_coord]])[['variables']]
attrs[[i_coord]]$dim <- NULL
attr(out_coords[[i_coord]], 'variables') <- attrs
} else if (inherits(metadata[[i_coord]], 'list')) {
# from Start and Load: main var
attr(out_coords[[i_coord]], 'variables') <- list(metadata[[i_coord]])
names(attributes(out_coords[[i_coord]])$variables) <- i_coord
} else if (!is.null(attributes(metadata[[i_coord]]))) {
# from Load
attrs <- attributes(metadata[[i_coord]])
# We remove because some attributes can't be saved
attrs <- NULL
attr(out_coords[[i_coord]], 'variables') <- list(attrs)
names(attributes(out_coords[[i_coord]])$variables) <- i_coord
if (!single_file) {
for (i in 1:n_datasets) {
path <- file.path(destination, Datasets[i], varname)
for (j in 1:n_vars) {
if (!dir.exists(path[j])) {
dir.create(path[j], recursive = TRUE)
}
startdates <- gsub("-", "", startdates)
dim(startdates) <- c(length(startdates))
names(dim(startdates)) <- sdate_dim
if (is.null(dat_dim) & is.null(var_dim)) {
data_subset <- data
} else if (is.null(dat_dim)) {
data_subset <- Subset(data, c(var_dim), list(j), drop = 'selected')
} else if (is.null(var_dim)) {
data_subset <- Subset(data, along = c(dat_dim), list(i), drop = 'selected')
} else {
data_subset <- Subset(data, c(dat_dim, var_dim), list(i, j), drop = 'selected')
}
target <- names(dim(data_subset))[which(!names(dim(data_subset)) %in% c(sdate_dim, ftime_dim))]
target_dims_data <- c(target, ftime_dim)
if (is.null(Dates)) {
input_data <- list(data_subset, startdates)
target_dims <- list(target_dims_data, NULL)
} else if (!is.null(time_bounds)) {
input_data <- list(data_subset, startdates, Dates,
time_bounds[[1]], time_bounds[[2]])
target_dims = list(target_dims_data, NULL,
} else {
input_data <- list(data_subset, startdates, Dates)
target_dims = list(target_dims_data, NULL, ftime_dim)
}
Apply(data = input_data,
target_dims = target_dims,
ftime_dim = ftime_dim,
varname = varname[j],
metadata_var = metadata[[varname[j]]],
extra_string = extra_string,
global_attrs = global_attrs)
# time_bnds
if (!is.null(time_bounds)) {
time_bnds <- c(time_bounds[[1]], time_bounds[[2]])
}
# Dates
remove_metadata_dim <- TRUE
if (is.null(sdate_dim)) {
sdates <- Dates[1]
# ftime definition
leadtimes <- as.numeric(difftime(Dates, sdates, units = "hours"))
# sdate definition
sdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected')
differ <- as.numeric(difftime(sdates, sdates[1], units = "hours"))
dim(differ) <- dim(data)[sdate_dim]
differ <- list(differ)
names(differ) <- sdate_dim
out_coords <- c(differ, out_coords)
attrs <- list(units = paste('hours since', sdates[1]),
calendar = 'proleptic_gregorian', longname = sdate_dim)
attr(out_coords[[sdate_dim]], 'variables')[[sdate_dim]] <- attrs
# ftime definition
Dates <- Reorder(Dates, c(ftime_dim, sdate_dim))
differ_ftime <- array(dim = dim(Dates))
for (i in 1:length(sdates)) {
differ_ftime[, i] <- as.numeric(difftime(Dates[, i], Dates[1, i],
units = "hours"))
}
dim(differ_ftime) <- dim(Dates)
leadtimes <- Subset(differ_ftime, along = sdate_dim, 1, drop = 'selected')
if (!all(apply(differ_ftime, 1, function(x){length(unique(x)) == 1}))) {
warning("Time steps are not equal for all start dates. Only ",
"forecast time values for the first start date will be saved ",
"correctly.")
}
if (all(!units_hours_since, is.null(time_bounds))) {
if (all(diff(leadtimes/24) == 1)) {
# daily values
units <- 'days'
leadtimes_vals <- round(leadtimes/24) + 1
} else if (all(diff(leadtimes/24) %in% c(28, 29, 30, 31))) {
# monthly values
units <- 'months'
leadtimes_vals <- round(leadtimes/(30.437*24)) + 1
} else {
# other frequency
units <- 'hours'
leadtimes_vals <- leadtimes + 1
}
} else {
units <- paste('hours since', paste(sdates, collapse = ', '))
leadtimes_vals <- leadtimes
# Add time_bnds
if (!is.null(time_bounds)) {
if (is.null(sdate_dim)) {
sdates <- Dates[1]
time_bnds <- c(time_bounds[[1]], time_bounds[[2]])
leadtimes_bnds <- as.numeric(difftime(time_bnds, sdates, units = "hours"))
dim(leadtimes_bnds) <- c(dim(Dates), bnds = 2)
} else {
# assuming they have sdate and ftime
time_bnds <- lapply(time_bounds, function(x) {
x <- Reorder(x, c(ftime_dim, sdate_dim))
return(x)
})
time_bnds <- c(time_bounds[[1]], time_bounds[[2]])
dim(time_bnds) <- c(dim(Dates), bnds = 2)
differ_bnds <- array(dim = c(dim(time_bnds)))
for (i in 1:length(sdates)) {
differ_bnds[, i, ] <- as.numeric(difftime(time_bnds[, i, ], Dates[1, i],
units = "hours"))
}
# NOTE (TODO): Add a warning when they are not equally spaced?
leadtimes_bnds <- Subset(differ_bnds, along = sdate_dim, 1, drop = 'selected')
}
# Add time_bnds
leadtimes_bnds <- Reorder(leadtimes_bnds, c('bnds', ftime_dim))
leadtimes_bnds <- list(leadtimes_bnds)
names(leadtimes_bnds) <- 'time_bnds'
out_coords <- c(leadtimes_bnds, out_coords)
attrs <- list(units = paste('hours since', paste(sdates, collapse = ', ')),
calendar = 'proleptic_gregorian',
long_name = 'time bounds', unlim = FALSE)
attr(out_coords[['time_bnds']], 'variables')$time_bnds <- attrs
# Add ftime var
dim(leadtimes_vals) <- dim(data)[ftime_dim]
leadtimes_vals <- list(leadtimes_vals)
names(leadtimes_vals) <- ftime_dim
out_coords <- c(leadtimes_vals, out_coords)
attrs <- list(units = units, calendar = 'proleptic_gregorian',
longname = ftime_dim,
dim = list(list(name = ftime_dim, unlim = TRUE)))
if (!is.null(time_bounds)) {
attrs$bounds = 'time_bnds'
}
attr(out_coords[[ftime_dim]], 'variables')[[ftime_dim]] <- attrs
for (j in 1:n_vars) {
remove_metadata_dim <- FALSE
metadata[[varname[j]]]$dim <- list(list(name = ftime_dim, unlim = TRUE))
}
# Reorder ftime_dim to last
if (length(dim(data)) != which(names(dim(data)) == ftime_dim)) {
order <- c(names(dim(data))[which(!names(dim(data)) %in% c(ftime_dim))], ftime_dim)
data <- Reorder(data, order)
}
}
# var definition
extra_info_var <- NULL
for (j in 1:n_vars) {
varname_j <- varname[j]
metadata_j <- metadata[[varname_j]]
if (is.null(var_dim)) {
out_coords[[varname_j]] <- data
out_coords[[varname_j]] <- Subset(data, var_dim, j, drop = 'selected')
if (remove_metadata_dim) metadata_j$dim <- NULL
attr(out_coords[[varname_j]], 'variables') <- list(metadata_j)
names(attributes(out_coords[[varname_j]])$variables) <- varname_j
# Add global attributes
if (!is.null(global_attrs)) {
attributes(out_coords[[varname_j]])$global_attrs <- global_attrs
first_sdate <- startdates[1]
last_sdate <- startdates[length(startdates)]
gsub("-", "", first_sdate)
file_name <- paste0(paste(c(varname,
gsub("-", "", first_sdate),
gsub("-", "", last_sdate)),
collapse = '_'), ".nc")
nc <- substr(extra_string, nchar(extra_string)-2, nchar(extra_string))
if (nc == ".nc") {
file_name <- extra_string
} else {
file_name <- paste0(extra_string, ".nc")
full_filename <- file.path(destination, file_name)
ArrayToNc(out_coords, full_filename)
.saveexp <- function(data, coords, destination = "./",
startdates = NULL, dates = NULL,
time_bnds1 = NULL, time_bnds2 = NULL,
ftime_dim = 'time', varname = 'var',
metadata_var = NULL, extra_string = NULL,
global_attrs = NULL) {
remove_metadata_dim <- TRUE
if (!any(is.null(time_bnds1), is.null(time_bnds2))) {
time_bnds <- c(time_bnds1, time_bnds2)
time_bnds <- as.numeric(difftime(time_bnds, dates[1], units = "hours"))
dim(time_bnds) <- c(dim(data)[ftime_dim], bnds = 2)
time_bnds <- Reorder(time_bnds, c('bnds', ftime_dim))
time_bnds <- list(time_bnds)
names(time_bnds) <- 'time_bnds'
coords <- c(time_bnds, coords)
attrs <- list(units = paste('hours since', dates[1]),
calendar = 'proleptic_gregorian',
longname = 'time bounds')
attr(coords[['time_bnds']], 'variables')$time_bnds <- attrs
}
# Add ftime_dim
differ <- as.numeric(difftime(dates, dates[1], units = "hours"))
dim(differ) <- dim(data)[ftime_dim]
differ <- list(differ)
names(differ) <- ftime_dim
coords <- c(differ, coords)
attrs <- list(units = paste('hours since', dates[1]),
calendar = 'proleptic_gregorian',
longname = ftime_dim,
dim = list(list(name = ftime_dim, unlim = TRUE)))
if (!is.null(time_bnds1)) {
attrs$bounds = 'time_bnds'
}
attr(coords[[ftime_dim]], 'variables')[[ftime_dim]] <- attrs
metadata_var$dim <- list(list(name = ftime_dim, unlim = TRUE))
remove_metadata_dim <- FALSE
}
# Add data
coords[[varname]] <- data
if (!is.null(metadata_var)) {
if (remove_metadata_dim) metadata_var$dim <- NULL
attr(coords[[varname]], 'variables') <- list(metadata_var)
names(attributes(coords[[varname]])$variables) <- varname
}
# Add global attributes
if (!is.null(global_attrs)) {
attributes(coords[[varname]])$global_attrs <- global_attrs
file_name <- paste0(varname, "_", startdates, ".nc")
file_name <- paste0(varname, "_", extra_string, "_", startdates, ".nc")
full_filename <- file.path(destination, file_name)