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Fading Measurement Analysis Tools for Luminescence Dating Research

Utilize tools for analyzing fading measurements, calculating fading correction, and plotting graphical representations from BIN file data for luminescence dating research.

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Fading Measurement Analysis Tools for Luminescence Dating Research

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  1. graphical representation

  2. plot_Risoe.BINfileData • analyse_FadingMeasurement • calc_FadingCorr • ExampleData.Fading

  3. subset IRSL 50°C, 225°C, 290°C bin_De <- choose.files(default=paste0(getwd(), "/*.*"), caption = "De",) # 515 - KF - Fading.binx setwd(dirname(bin_De)) # ## Calculate the De of the IR50 signal bin_De <- read_BIN2R(bin_De) bin_De_IRSL_50 <- subset(bin_De, LTYPE == "IRSL" & TEMPERATURE == 50) bin_De_IRSL_225 <- subset(bin_De, LTYPE == "IRSL" & TEMPERATURE == 225) bin_De_IRSL_290 <- subset(bin_De, LTYPE == "IRSL" & TEMPERATURE == 290)

  4. analyse_SAR.CWOSL • Analyse SAR CW-OSL measurements analyse_SAR.CWOSL(object, signal.integral.min, signal.integral.max, background.integral.min, background.integral.max, rejection.criteria = NULL, dose.points = NULL, mtext.outer, plot = TRUE, plot.single = FALSE, onlyLxTxTable = FALSE, ...)

  5. analyse_SAR.CWOSL bin_De <- choose.files(default=paste0(getwd(), "/*.*"), caption = "De",) # 515 - KF - Fading.binx setwd(dirname(bin_De)) Aliquot <- 3 # ## Calculate the De of the IR50 signal bin_De <- read_BIN2R(bin_De) bin_De_IRSL <- subset(bin_De, LTYPE == "IRSL") # say, you would like to only see the OSL curves Rlum_IR50_De <- Risoe.BINfileData2RLum.Analysis(bin_De_IRSL, pos=Aliquot) # ## Calculate the De of the IR50 signal IR50_De <- analyse_SAR.CWOSL( object = Rlum_IR50_De, signal.integral.min = 1, signal.integral.max = 5, background.integral.min = 81, background.integral.max = 100, fit.method = "EXP", ) ## Extract the calculated De and its error IR50_De.res <- get_RLum(IR50_De) De <- c(IR50_De.res$De, IR50_De.res$De.Error)

  6. analyse_FadingMeasurement • Analyse fading measurements and returns the fading rate per decade (g-value) • density of recombination centres (rho’) is estimated after Kars et al. 2008. analyse_FadingMeasurement(object, structure = c("Lx", "Tx"), signal.integral, background.integral, t_star = "half", n.MC = 100, verbose = TRUE, plot = TRUE, plot.single = FALSE, ...)

  7. analyse_FadingMeasurement analyse_FadingMeasurement(object, structure = c("Lx", "Tx"), signal.integral, background.integral) object: RLum.Analysis or a data.frame structure: character (with default): sets the structure of the measurement data. Allowed are 'Lx' or c('Lx','Tx’) signal.integral: vector (required) background.integral: vector (required)

  8. analyse_FadingMeasurement • current limitations • object: RLum.Analysis • TIMESINCEIRR: required to calculate the time values

  9. analyse_FadingMeasurement: Rlum, 1 aliquot MyFileName <- choose.files(default=paste0(getwd(), "/*.*")) # 433 - KF - Fading.binx setwd(dirname(MyFileName)) bin <- read_BIN2R(MyFileName) # say, you would like to only see the OSL curves bin_IRSL <- subset(bin, LTYPE == "IRSL") Aliquot <- 25 fading_data <- Risoe.BINfileData2RLum.Analysis(bin_IRSL, pos=Aliquot) g_value <- analyse_FadingMeasurement( fading_data, plot = TRUE, verbose = TRUE, n.MC = 10, structure = c("Lx", "Tx"), signal.integral = c(6:10), background.integral = c(80:100)) # results, printed to the console g_value@data[["fading_results"]][["G_VALUE_2DAYS"]] g_value@data[["fading_results"]][["G_VALUE_2DAYS.ERROR"]]

  10. analyse_FadingMeasurement: Rlum, all aliquots MyFileName <- choose.files(default=paste0(getwd(), "/*.*")) # 515 - KF - Fading.binx setwd(dirname(MyFileName)) bin <- read_BIN2R(MyFileName) # say, you would like to only see the IRSL curves # bin_IRSL <- subset(bin, LTYPE == "IRSL") # 1.3 SELECT aliquot.position ------------------------------------------------- # ... all positions aliquot.position <- unique(bin@METADATA[, "POSITION"]) for(i in aliquot.position) { fading_data <- Risoe.BINfileData2RLum.Analysis(bin_IRSL, pos=i) g_value <- analyse_FadingMeasurement( fading_data, plot = TRUE, verbose = TRUE, n.MC = 10, structure = c("Lx", "Tx"), signal.integral = c(6:10), background.integral = c(80:100)) }

  11. analyse_FadingMeasurement • collect info from many aliquot, then pass to fading corr

  12. calc_FadingCorr • Apply a fading correction according to Huntley & Lamothe (2001) calc_FadingCorr(age.faded, g_value, tc = NULL, tc.g_value = tc, n.MC = 10000, seed = NULL, interval = c(0.01, 500), txtProgressBar = TRUE, verbose = TRUE) age.faded: numeric vector (required): uncorrected age with error in ka g_value: vector (required): g-value and error obtained from separate fading measurements (see example). Alternatively an RLum.Results object can be provided produced by the function analyse_FadingMeasurement, in this case tc is set automatically tc: numeric (required): time in seconds between irradiation and the prompt measurement (cf. Huntley & Lamothe 2001). Argument will be ignored if g_value was an RLum.Results object

  13. calc_FadingCorr ##run the examples given in the appendix of Huntley and Lamothe, 2001 ##(3) faded age: 10.0 ka results <- calc_FadingCorr( age.faded = c(10,0), g_value = c(5.0, 1.0), tc = 2592000, tc.g_value = 172800, n.MC = 100) ##access the last output get_RLum(results) # detailed console output

  14. calc_FadingCorr (an example, 1 aliquot) bin_fading <- choose.files(default=paste0(getwd(), "/*.*"), caption = "fading",) # 515 - KF - Fading.binx setwd(dirname(bin_fading)) bin_De <- choose.files(default=paste0(getwd(), "/*.*"), caption = "De",) # 515 - KF - De - 1.binx bin <- read_BIN2R(bin_fading) # say, you would like to only see the OSL curves bin_IRSL <- subset(bin, LTYPE == "IRSL") Aliquot <- 3 fading_data <- Risoe.BINfileData2RLum.Analysis(bin_IRSL, pos=Aliquot) g_value <- analyse_FadingMeasurement( fading_data, plot = TRUE, verbose = TRUE, n.MC = 10, structure = c("Lx", "Tx"), signal.integral = c(1:5), background.integral = c(81:100))

  15. calc_FadingCorr (an example, 1 aliquot, continued) # ## Calculate the De of the IR50 signal bin_De <- read_BIN2R(bin_De) bin_De_IRSL <- subset(bin_De, LTYPE == "IRSL") # say, you would like to only see the OSL curves Rlum_IR50_De <- Risoe.BINfileData2RLum.Analysis(bin_De_IRSL, pos=Aliquot) # ## Calculate the De of the IR50 signal IR50_De <- analyse_SAR.CWOSL( object = Rlum_IR50_De, signal.integral.min = 1, signal.integral.max = 5, background.integral.min = 81, background.integral.max = 100, fit.method = "EXP") ## Extract the calculated De and its error IR50_De.res <- get_RLum(IR50_De) De <- c(IR50_De.res$De, IR50_De.res$De.Error) ## Apply fading correction (age conversion greatly simplified) IR50_Age <- De / 2 * 0.13 # De (s) / (environment) dose rate (Gy/ka) * beta dose rate (Gy/s) IR50_Age.corr <- calc_FadingCorr(IR50_Age, g_value = g_value)

  16. calc_FadingCorr (an example, many aliquots) bin_fading <- choose.files(default=paste0(getwd(), "/*.binx"), caption = "fading",) # 515 - KF - Fading.binx setwd(dirname(bin_fading)) bin_De <- choose.files(default=paste0(getwd(), "/*.binx"), caption = "De",) # 515 - KF - De - 1.binx bin <- read_BIN2R(bin_fading) # say, you would like to only see the OSL curves bin_IRSL <- subset(bin, LTYPE == "IRSL") # 1.3 SELECT aliquot.position ------------------------------------------------- # ... all positions aliquot.position <- unique(bin@METADATA[, "POSITION"]) for(i in aliquot.position) { fading_data <- Risoe.BINfileData2RLum.Analysis(bin_IRSL, pos=i) g_value <- analyse_FadingMeasurement( fading_data, plot = TRUE, verbose = TRUE, n.MC = 10, structure = c("Lx", "Tx"), signal.integral = c(1:5), background.integral = c(81:100))

  17. calc_FadingCorr (an example, many aliquots, continued) # ## Calculate the De of the IR50 signal bin_De <- read_BIN2R(bin_De) bin_De_IRSL <- subset(bin_De, LTYPE == "IRSL") # say, you would like to only see the OSL curves Rlum_IR50_De <- Risoe.BINfileData2RLum.Analysis(bin_De_IRSL, pos=i) # ## Calculate the De of the IR50 signal IR50_De <- analyse_SAR.CWOSL( object = Rlum_IR50_De, signal.integral.min = 1, signal.integral.max = 5, background.integral.min = 81, background.integral.max = 100, fit.method = "EXP") ## Extract the calculated De and its error IR50_De.res <- get_RLum(IR50_De) De <- c(IR50_De.res$De, IR50_De.res$De.Error) ## Apply fading correction (age conversion greatly simplified) IR50_Age <- De / 2 * 0.13 # De (s) / (environment) dose rate (Gy/ka) * beta dose rate (Gy/s) IR50_Age.corr <- calc_FadingCorr(IR50_Age, g_value = g_value) }

  18. analyse_FadingMeasurement ## load example data (sample UNIL/NB123, see ?ExampleData.Fading) data("ExampleData.Fading", envir = environment()) ##(1) get fading measurement data (here a three column data.frame) fading_data <- ExampleData.Fading$fading.data$IR50 ##(2) run analysis g_value <- analyse_FadingMeasurement( fading_data, plot = TRUE, verbose = TRUE, n.MC = 10) ##(3) this can be further used in the function to correct the age according to Huntley & Lamothe, 2001 results <- calc_FadingCorr( age.faded = c(100,2), g_value = g_value, n.MC = 10)

  19. ?ExampleData.Fading ## Load example data data("ExampleData.Fading", envir = environment()) ## Get fading measurement data of the IR50 signal IR50_fading <- ExampleData.Fading$fading.data$IR50 head(IR50_fading) ## Determine g-value and rho' for the IR50 signal IR50_fading.res <- analyse_FadingMeasurement(IR50_fading) ## Show g-value and rho' results gval <- get_RLum(IR50_fading.res) rhop <- get_RLum(IR50_fading.res, "rho_prime") gval rhop ## Get LxTx values of the IR50 DE measurement IR50_De.LxTx <- ExampleData.Fading$equivalentDose.data$IR50 ## Calculate the De of the IR50 signal IR50_De <- plot_GrowthCurve(IR50_De.LxTx, mode = "interpolation", fit.method = "EXP") ## Extract the calculated De and its error IR50_De.res <- get_RLum(IR50_De) De <- c(IR50_De.res$De, IR50_De.res$De.Error) ## Apply fading correction (age conversion greatly simplified) IR50_Age <- De / 7.00 IR50_Age.corr <- calc_FadingCorr(IR50_Age, g_value = IR50_fading.res)

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