1 / 21

graphical representation

graphical representation. plot_Risoe.BINfileData analyse_FadingMeasurement calc_FadingCorr ExampleData.Fading. 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 ))

ranieri
Download Presentation

graphical representation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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)

More Related