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#' Extract spectral data from spectra files
#'
#' Finds and imports reflectance/transmittance/absorbance data from spectra
#' files in a given location.
#'
#' @inheritParams lr_parse_generic
#'
#' @param where Folder in which files are located (defaults to current working
#' directory).
#' @param ext File extension to be searched for, without the "." (defaults to
#' `txt`). You can also use a character vector to specify multiple file
#' extensions.
#' @param lim A vector with two numbers determining the wavelength limits to be
#' considered (defaults to `c(300, 700)`).
#' @param subdir Should subdirectories within the `where` folder be included in
#' the search? (defaults to `FALSE`).
#' @param subdir.names Should subdirectory path be included in the name of the
#' spectra? (defaults to `FALSE`).
#' @param ignore.case Should the extension search be case insensitive? (defaults
#' to `TRUE`)
#' @param interpolate Boolean indicated whether spectral data should be
#' interpolated and pruned at every nanometre. Note that this option can only
#' work if all input data samples the same wavelengths. Defaults to `TRUE`.
#'
#' @details
#' You can customise the type of parallel processing used by this function with
#' the [future::plan()] function. This works on all operating systems, as well
#' as high performance computing (HPC) environment. Similarly, you can customise
#' the way progress is shown with the [progressr::handlers()] functions
#' (progress bar, acoustic feedback, nothing, etc.)
#'
#' @return A data.frame, containing the wavelengths in the first column and
#' individual imported spectral files in the subsequent columns.
#'
#' @export
#'
#' @importFrom tools file_path_sans_ext
#' @importFrom stats approx
#' @importFrom future.apply future_lapply
#' @importFrom progressr with_progress progressor
#'
#' @seealso [pavo::getspec()]
#'
#' @examples
#' spcs <- lr_get_spec(system.file("testdata", package = "lightr"), ext = "jdx")
#' head(spcs)
#'
lr_get_spec <- function(where = getwd(), ext = "txt", lim = c(300, 700),
decimal = ".", sep = NULL, subdir = FALSE,
subdir.names = FALSE, ignore.case = TRUE,
interpolate = TRUE) {
extension <- paste0("\\.", ext, "$", collapse = "|")
file_names <- list.files(where,
pattern = extension, ignore.case = ignore.case,
recursive = subdir, include.dirs = subdir
)
# This step is needed to ensure reproducibility between locales and platforms
file_names <- sort(file_names, method = "radix")
nb_files <- length(file_names)
if (nb_files == 0) {
warning('No files found. Try a different value for argument "ext".',
call. = FALSE)
return(NULL)
}
files <- file.path(where, file_names)
if (!subdir.names) {
file_names <- basename(file_names)
}
specnames <- file_path_sans_ext(file_names)
range <- seq(lim[1], lim[2])
message(nb_files, " files found; importing spectra:")
if (!interpolate) {
gsp <- function(f) {
dispatch_parser(f, decimal = decimal, sep = sep)[[1]]
}
} else {
gsp <- function(f) {
df <- dispatch_parser(f, decimal = decimal, sep = sep)[[1]]
# Trim now because otherwise, approx() can fill the region of interest
# with bogus data (e.g., if the data is complete between 200-300nm and
# 800-1200nm and your region of interested if 300-700 nm).
bounds <- which(df$wl >= lim[1] & df$wl <= lim[2])
if (length(bounds) == 0) {
warning(f, " does not contain spectral data over the provided wl range",
call. = FALSE)
return(NULL)
}
df <- df[c(min(bounds) - 1, bounds, max(bounds) + 1), ]
approx(df[, "wl"], df[, "processed"],
xout = range, ties = "ordered")$y
}
}
with_progress({
p <- progressor(along = files)
tmp <- future_lapply(files, function(x) {
p()
tryCatch(
gsp(x),
error = function(e) {
warning(conditionMessage(e))
return(NULL)
}
)
})
})
whichfailed <- which(vapply(tmp, is.null, logical(1)))
if (length(whichfailed) == nb_files) {
warning("File import failed.\n",
"Check input files and function arguments.", call. = FALSE)
return(NULL)
} else if (length(whichfailed) > 0) {
warning("Could not import one or more files:\n",
paste0(files[whichfailed], collapse = "\n"),
call. = FALSE
)
specnames <- specnames[-whichfailed]
}
if (interpolate) {
# We convert to data.frame before adding the wl to preserve wl class (int or
# altrep)
tmp <- as.data.frame(do.call(cbind, tmp))
final <- cbind(range, tmp)
} else {
if (length(unique(lapply(tmp, function(x) x[, "wl"]))) != 1) {
stop("'interpolate = FALSE' can only work if all input files sample the ",
"same wavelengths.", call. = FALSE)
}
final <- as.data.frame(
do.call(cbind, lapply(tmp, function(x) x[, "processed"]))
)
final <- cbind(tmp[[1]][, "wl"], final)
# This steps needs to be only run when !interp because it breaks altrep
final <- final[final[, 1] <= lim[2] & final[, 1] >= lim[1], ]
}
colnames(final) <- c("wl", specnames)
# TODO: should uninterpolated spectra be marked as rspec objects?
class(final) <- c("rspec", "data.frame")
return(final)
}
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