Luminescence (version 0.9.23)

apply_EfficiencyCorrection: Function to apply spectral efficiency correction to RLum.Data.Spectrum S4 class objects

Description

The function allows spectral efficiency corrections for RLum.Data.Spectrum S4 class objects

Usage

apply_EfficiencyCorrection(object, spectral.efficiency)

Value

Returns same object as provided as input

Arguments

object

RLum.Data.Spectrum or RLum.Analysis (required): S4 object of class RLum.Data.Spectrum, RLum.Analysisor a list of such objects. Other objects in the list are skipped.

spectral.efficiency

data.frame (required): Data set containing wavelengths (x-column) and relative spectral response values (y-column) (values between 0 and 1). The provided data will be used to correct all spectra if object is a list

Function version

0.2.0

Author

Sebastian Kreutzer, IRAMAT-CRP2A, UMR 5060, CNRS-Université Bordeaux Montaigne (France)
Johannes Friedrich, University of Bayreuth (Germany) , RLum Developer Team

How to cite

Kreutzer, S., Friedrich, J., 2023. apply_EfficiencyCorrection(): Function to apply spectral efficiency correction to RLum.Data.Spectrum S4 class objects. Function version 0.2.0. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Philippe, A., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., Galharret, J., 2023. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.23. https://CRAN.R-project.org/package=Luminescence

Details

The efficiency correction is based on a spectral response dataset provided by the user. Usually the data set for the quantum efficiency is of lower resolution and values are interpolated for the required spectral resolution using the function stats::approx

If the energy calibration differs for both data set NA values are produces that will be removed from the matrix.

See Also

RLum.Data.Spectrum, RLum.Analysis

Examples

Run this code

##(1) - use with your own data (uncomment for usage)
## spectral.efficiency <- read.csv("your data")
##
## your.spectrum <- apply_EfficiencyCorrection(your.spectrum, )

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