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#' Script for data pretreatment
#'
#' This script opens a .binx file and creates a \linkS4class{TLum.Analysis} object from it.
#' It just requires the name of the file with the TL curves and the relative error on the measurements.
#' It extracts the TL curves and updates the data types.
#'
#' @param file.name
#' \link{character} (\bold{required}): Name of the file containing the luminescence data.
#' @param k
#' \link{numeric} (with default): Corrective factor for estimating the uncertainties using a poisson distribution.
#' @param protocol
#' \link{character} (\bold{required}): Measurment protocol used.
#' @param file.parameters
#' \link{list} (with default): list containing the file parameters. See details.
#' @param plotting.parameters
#' \link{list} (with default): list containing the plotting parameters. See details.
#'
#' @details
#' \bold{Plotting parameters} \cr
#' The plotting parameters are: \cr
#' \describe{
#' \item{\code{plot.Tmin}}{
#' \link{numeric}: Lowest temperature plotted.}
#' \item{\code{plot.Tmax}}{
#' \link{numeric}: Highest temperature plotted.}
#' \item{\code{no.plot}}{
#' \link{logical}: If \code{TRUE}, the results will not be plotted.}
#' }
#' See also \link{plot_extract.TL}. \cr
#'
#' \bold{File parameters} \cr
#' The file parameters are: \cr
#' \describe{
#' \item{\code{file.extension}}{
#' \link{character} (with default): extension of the file containing the luminescence data (.bin or .binx)}
#' \item{\code{folder.in}}{
#' \link{character} (with default): Folder containing the file with the luminescene data.}
#' }
#'
#' @return
#' This function returns a \code{\linkS4class{TLum.Analysis}} object.
#'
#' @seealso
#' \link{read_BIN2R},
#' \link{Risoe.BINfileData2TLum.BIN.File},
#' \link{TLum.BIN.File2TLum.Analysis},
#' \link{mod_extract.TL},
#' \link{mod_update.dType}.
#'
#' @author David Strebler, University of Cologne (Germany).
#'
#' @export script_TL.import
script_TL.import <- function(
file.name,
k = 1,
protocol = "Unknown",
file.parameters=list(file.extension =".binx",
folder.in = "./"),
plotting.parameters=list(plot.Tmin=0,
plot.Tmax=NA,
no.plot=FALSE)
){
# ------------------------------------------------------------------------------
# Integrity Check
# ------------------------------------------------------------------------------
if(missing(file.name)){
stop("[script_TL.import] Error: Input 'file.name' is missing.")
}else if(!is.character(file.name)){
stop("[script_TL.import] Error: Input 'file.name' is not of type 'character'.")
}
if(!is.character(protocol)){
stop("[script_TL.import] Error: Input 'protocol' is not of type 'character'.")
}
if(!is.numeric(k)){
stop("[script_TL.import] Error: Input 'k' is not of type 'numeric'.")
}
if(!is.list(file.parameters)){
stop("[script_TL.import] Error: Input 'file.parameters' is not of type 'list'.")
}
if(!is.list(plotting.parameters)){
stop("[script_TL.import] Error: Input 'plotting.parameters' is not of type 'list'.")
}
# ------------------------------------------------------------------------------
file.extension <- file.parameters$file.extension
folder.in <- file.parameters$folder.in
# ------------------------------------------------------------------------------
# Value check
if(k < 0){
k <- abs(k)
warning("[script_TL.import] Warning: Input 'k' < 0.")
}
if(!is.character(file.extension)){
stop("[script_TL.import] Error: Input 'file.extension' is not of type 'character'.")
}else if(file.extension != ".bin" && file.extension != ".binx"){
stop("[script_TL.import] Error: Input 'file.extension' is not of '.bin' or '.binx'.")
file.extension <- ".binx"
}
if(!is.character(folder.in)){
warning("[script_TL.import] Error: Input 'folder.in' is not of type 'character'.")
folder.in = "./"
}
# ------------------------------------------------------------------------------
path.in <- paste(folder.in,file.name, file.extension,sep="")
# Read file
data.in <- read_BIN2R(path.in)
data <- Risoe.BINfileData2TLum.BIN.File(object = data.in,
k = k)
data <- TLum.BIN.File2TLum.Analysis(object = data, protocol = protocol)
#TL curve selection
data <- mod_extract.TL(object = data, plotting.parameters = plotting.parameters)
print("TL signals selected")
#Identification of Preheat and Testdose
data <- mod_update.dType(object = data)
print("Preheat and tesdose identify")
# Update error using a poisson distribution
data <- mod_update.error(object = data, method = "poisson")
print("Uncertainties base on a poisson distribution")
return(data)
}
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