==1390668== Memcheck, a memory error detector ==1390668== Copyright (C) 2002-2024, and GNU GPL'd, by Julian Seward et al. ==1390668== Using Valgrind-3.24.0 and LibVEX; rerun with -h for copyright info ==1390668== Command: /data/blackswan/ripley/R/R-devel-vg/bin/exec/R --vanilla --encoding=UTF-8 ==1390668== R Under development (unstable) (2026-03-12 r89608) -- "Unsuffered Consequences" Copyright (C) 2026 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > pkgname <- "Luminescence" > source(file.path(R.home("share"), "R", "examples-header.R")) > options(warn = 1) > library('Luminescence') Welcome to the R package Luminescence version 1.2.0 [Built: 2026-03-12 23:27:41 UTC] An aliquot disc: 'The answer [...] is: 48' > > base::assign(".oldSearch", base::search(), pos = 'CheckExEnv') > base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv') > cleanEx() > nameEx("BaseDataSet.CosmicDoseRate") > ### * BaseDataSet.CosmicDoseRate > > flush(stderr()); flush(stdout()) > > ### Name: BaseDataSet.CosmicDoseRate > ### Title: Base data set for cosmic dose rate calculation > ### Aliases: BaseDataSet.CosmicDoseRate values.cosmic.Softcomp > ### values.factor.Altitude values.par.FJH > ### Keywords: datasets internal > > ### ** Examples > > > ##load data > data(BaseDataSet.CosmicDoseRate) > > > > > cleanEx() > nameEx("BaseDataSet") > ### * BaseDataSet > > flush(stderr()); flush(stdout()) > > ### Name: BaseDataSet > ### Title: Base datasets > ### Aliases: BaseDataSet BaseDataSet.ConversionFactors > ### BaseDataSet.GrainSizeAttenuation BaseDataSet.FractionalGammaDose > ### Keywords: datasets > > ### ** Examples > > ## conversion factors > data("BaseDataSet.ConversionFactors", envir = environment()) > > ## grain size attenuation > data("BaseDataSet.GrainSizeAttenuation", envir = environment()) > > ## fractional gamma dose > data("BaseDataSet.FractionalGammaDose", envir = environment()) > > > > > cleanEx() > nameEx("ExampleData.Al2O3C") > ### * ExampleData.Al2O3C > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.Al2O3C > ### Title: Example Al2O3:C Measurement Data > ### Aliases: ExampleData.Al2O3C data_CrossTalk data_ITC > ### Keywords: datasets internal > > ### ** Examples > > > ##(1) curves > data(ExampleData.Al2O3C, envir = environment()) > plot_RLum(data_ITC[1:2]) > > > > > cleanEx() > nameEx("ExampleData.BINfileData") > ### * ExampleData.BINfileData > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.BINfileData > ### Title: Example data from a SAR OSL and SAR TL measurement for the > ### package Luminescence > ### Aliases: ExampleData.BINfileData CWOSL.SAR.Data TL.SAR.Data > ### Keywords: datasets internal > > ### ** Examples > > > ## show first 5 elements of the METADATA and DATA elements in the terminal > data(ExampleData.BINfileData, envir = environment()) > CWOSL.SAR.Data@METADATA[1:5,] ID SEL VERSION LENGTH PREVIOUS NPOINTS LTYPE LOW HIGH RATE TEMPERATURE 1 1 TRUE 03 1272 0 250 TL 0 221 5 0 2 2 TRUE 03 1272 1272 250 TL 0 221 5 0 3 3 TRUE 03 1272 1272 250 TL 0 221 5 0 4 4 TRUE 03 1272 1272 250 TL 0 221 5 0 5 5 TRUE 03 1272 1272 250 TL 0 221 5 0 XCOORD YCOORD TOLDELAY TOLON TOLOFF POSITION RUN TIME DATE SEQUENCE 1 0 0 0 0 0 1 1 19:14:32 060920 20100906 2 0 0 0 0 0 2 1 19:16:11 060920 20100906 3 0 0 0 0 0 3 1 19:17:50 060920 20100906 4 0 0 0 0 0 4 1 19:19:30 060920 20100906 5 0 0 0 0 0 5 1 19:21:09 060920 20100906 USER DTYPE IRR_TIME IRR_TYPE IRR_UNIT BL_TIME BL_UNIT AN_TEMP AN_TIME 1 Default Natural 0 0 0 0 0 220 10 2 Default Natural 0 0 0 0 0 220 10 3 Default Natural 0 0 0 0 0 220 10 4 Default Natural 0 0 0 0 0 220 10 5 Default Natural 0 0 0 0 0 220 10 NORM1 NORM2 NORM3 BG SHIFT SAMPLE COMMENT 1 0 0 0 0 0 BT 607 Main Measurement Middle Grain SachsenLoesse 2 0 0 0 0 0 BT 607 Main Measurement Middle Grain SachsenLoesse 3 0 0 0 0 0 BT 607 Main Measurement Middle Grain SachsenLoesse 4 0 0 0 0 0 BT 607 Main Measurement Middle Grain SachsenLoesse 5 0 0 0 0 0 BT 607 Main Measurement Middle Grain SachsenLoesse LIGHTSOURCE SET TAG GRAIN LPOWER SYSTEMID FNAME 1 None 2 0 0 0 0 ExampleData.BINfileData 2 None 2 0 0 0 0 ExampleData.BINfileData 3 None 2 0 0 0 0 ExampleData.BINfileData 4 None 2 0 0 0 0 ExampleData.BINfileData 5 None 2 0 0 0 0 ExampleData.BINfileData > CWOSL.SAR.Data@DATA[1:5] [[1]] [1] 2 0 13 1 1 5 6 12 12 0 2 4 2 4 6 6 4 8 [19] 6 8 3 2 8 1 4 3 6 8 3 1 3 1 1 1 12 5 [37] 1 10 0 0 2 2 2 1 12 1 3 4 2 6 4 1 3 6 [55] 6 5 5 0 0 5 2 2 0 2 2 3 15 4 0 7 4 4 [73] 0 3 14 4 7 7 4 4 2 4 1 8 3 1 3 2 5 2 [91] 17 12 5 4 3 3 18 3 12 2 4 5 7 4 4 2 8 7 [109] 1 9 5 9 5 13 0 10 1 1 1 2 6 6 9 4 12 8 [127] 1 8 2 7 6 7 1 2 5 1 6 0 11 5 1 3 13 11 [145] 1 3 5 6 5 2 5 0 16 5 10 1 3 17 4 7 10 10 [163] 4 6 3 8 4 9 5 7 6 5 8 10 8 3 7 11 4 21 [181] 14 3 4 20 9 11 8 11 14 13 12 11 25 7 9 10 18 9 [199] 15 11 19 24 29 18 27 26 25 21 17 24 32 22 25 29 35 25 [217] 27 45 43 43 44 53 51 42 56 40 49 45 85 66 72 67 83 88 [235] 90 78 81 74 108 87 110 99 123 127 144 108 120 129 131 72 [[2]] [1] 4 2 3 0 20 4 4 2 3 12 3 6 6 15 8 3 1 5 [19] 5 8 1 6 8 6 5 20 12 4 4 8 2 5 11 3 5 6 [37] 1 4 11 5 9 5 4 6 5 5 1 1 4 7 1 12 6 4 [55] 1 0 2 5 5 10 11 4 3 9 3 2 7 2 7 11 8 2 [73] 0 6 6 8 0 8 2 8 8 5 10 4 1 24 7 4 7 5 [91] 6 5 17 1 3 1 2 4 5 6 26 4 7 8 11 5 6 2 [109] 6 6 5 14 3 10 2 18 2 0 2 1 10 10 2 11 7 0 [127] 2 16 0 13 6 10 0 3 6 6 15 3 2 10 4 3 6 2 [145] 11 5 2 7 3 6 2 1 6 4 0 1 3 5 4 8 7 6 [163] 10 6 2 7 3 7 3 4 10 7 4 12 6 6 16 11 6 6 [181] 1 8 8 11 5 10 6 17 3 6 10 8 11 10 8 15 14 11 [199] 14 10 9 12 11 12 8 19 16 41 13 22 20 39 15 27 27 24 [217] 25 32 26 20 30 27 37 38 29 31 35 42 49 41 36 60 51 43 [235] 41 48 49 55 75 53 76 67 59 61 88 76 95 85 101 41 [[3]] [1] 11 0 3 5 2 1 8 21 2 10 10 5 5 4 2 2 6 2 [19] 3 14 3 0 2 4 4 2 0 6 2 9 2 1 12 1 10 5 [37] 8 1 10 3 6 9 12 4 3 3 4 1 2 4 0 5 0 6 [55] 5 5 5 7 2 3 0 12 3 0 5 2 7 0 3 9 4 6 [73] 2 4 5 0 10 4 6 3 4 4 11 5 6 6 5 6 2 5 [91] 9 2 3 6 1 5 7 2 1 45 5 0 0 4 11 3 3 2 [109] 1 0 1 11 9 10 8 7 9 11 9 7 8 8 7 1 13 3 [127] 5 11 2 8 0 9 2 7 6 17 1 5 3 6 2 14 5 1 [145] 1 3 2 3 4 3 15 5 1 13 11 5 6 1 4 2 62 5 [163] 5 3 9 4 8 3 10 6 17 11 3 5 9 5 4 5 3 2 [181] 5 4 10 6 4 8 17 3 10 10 6 4 11 6 15 7 14 15 [199] 12 9 16 16 21 9 6 17 11 18 15 18 13 15 18 23 20 22 [217] 33 32 22 26 27 23 34 33 26 29 29 32 30 51 36 31 44 56 [235] 77 47 76 43 77 57 68 80 82 90 86 57 109 95 95 55 [[4]] [1] 17 1 0 5 1 5 2 2 8 0 1 4 10 5 0 5 6 3 3 2 8 3 1 47 13 [26] 0 3 2 0 4 12 9 7 1 4 6 4 2 6 0 6 6 8 10 3 8 1 7 13 3 [51] 5 12 8 4 7 4 7 8 8 2 3 4 10 6 12 12 2 1 8 0 3 23 6 13 1 [76] 2 16 2 7 3 9 4 10 12 8 8 5 3 3 10 10 5 1 2 2 4 4 11 3 6 [101] 2 4 2 7 2 6 8 16 6 1 8 6 5 9 15 4 13 2 5 5 20 2 3 7 5 [126] 6 7 1 4 11 9 3 6 1 7 9 0 3 3 9 0 1 4 10 2 7 2 1 0 1 [151] 3 4 4 5 0 6 4 3 5 0 3 3 3 2 5 1 5 18 4 1 8 9 3 20 12 [176] 1 0 2 1 1 8 5 9 8 1 5 6 5 12 8 8 17 5 6 4 12 2 8 5 4 [201] 4 7 12 3 7 10 10 5 5 4 7 3 7 15 6 11 12 5 6 18 5 18 18 8 13 [226] 13 15 11 13 14 11 15 16 12 19 23 24 12 14 16 19 30 27 32 30 41 28 20 27 37 [[5]] [1] 2 2 3 6 1 2 3 1 1 7 2 5 4 4 0 2 2 5 5 8 11 1 14 5 4 [26] 0 0 3 4 3 2 1 5 3 12 3 3 1 1 6 4 0 1 6 6 3 3 4 3 3 [51] 5 5 9 4 6 0 16 3 5 3 4 1 6 3 0 5 3 3 2 6 3 3 6 1 2 [76] 6 3 9 4 5 7 1 4 5 7 0 9 1 0 3 2 7 8 2 7 2 8 5 6 2 [101] 9 7 6 3 0 4 2 5 15 18 1 6 5 3 13 4 6 4 1 2 4 1 5 3 4 [126] 2 4 7 13 5 3 4 7 5 20 3 8 1 7 3 10 10 7 2 5 10 4 2 9 5 [151] 1 5 2 2 8 7 3 4 5 12 7 7 4 4 3 5 4 6 6 9 11 9 2 3 1 [176] 3 9 7 9 10 12 5 17 5 8 4 12 7 12 6 3 9 1 7 7 15 7 8 12 15 [201] 14 12 21 20 11 18 11 27 26 16 20 23 23 29 31 23 22 27 31 22 29 43 24 29 25 [226] 31 37 41 54 54 52 50 40 51 52 67 61 65 47 62 97 73 67 93 87 68 86 78 77 69 > > > > > cleanEx() > nameEx("ExampleData.CW_OSL_Curve") > ### * ExampleData.CW_OSL_Curve > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.CW_OSL_Curve > ### Title: Example CW-OSL curve data for the package Luminescence > ### Aliases: ExampleData.CW_OSL_Curve CW_Curve.BosWallinga2012 > ### Keywords: datasets internal > > ### ** Examples > > > data(ExampleData.CW_OSL_Curve, envir = environment()) > plot(ExampleData.CW_OSL_Curve) > > > > > cleanEx() > nameEx("ExampleData.CobbleData") > ### * ExampleData.CobbleData > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.CobbleData > ### Title: Example data for calc_CobbleDoseRate() > ### Aliases: ExampleData.CobbleData > ### Keywords: datasets > > ### ** Examples > > > ## Load data > data("ExampleData.CobbleData", envir = environment()) > > > > > cleanEx() > nameEx("ExampleData.DeValues") > ### * ExampleData.DeValues > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.DeValues > ### Title: Example De data sets for the package Luminescence > ### Aliases: ExampleData.DeValues > ### Keywords: datasets > > ### ** Examples > > > ##(1) plot values as histogram > data(ExampleData.DeValues, envir = environment()) > plot_Histogram(ExampleData.DeValues$BT998, xlab = "De [s]") > > ##(2) plot values as histogram (with second to gray conversion) > data(ExampleData.DeValues, envir = environment()) > > De.values <- convert_Second2Gray(ExampleData.DeValues$BT998, + dose.rate = c(0.0438, 0.0019)) > > plot_Histogram(De.values, xlab = "De [Gy]") > > > > > cleanEx() > nameEx("ExampleData.Fading") > ### * ExampleData.Fading > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.Fading > ### Title: Example data for feldspar fading measurements > ### Aliases: ExampleData.Fading > ### Keywords: datasets > > ### ** Examples > > > ## 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) LxTx LxTx.error timeSinceIrradiation 1 0.980 0.0490 381.6 2 0.952 0.0476 12178.8 3 0.924 0.0462 18183.6 4 0.912 0.0456 30178.8 5 0.898 0.0449 54172.8 6 0.974 0.0487 378.0 > > ## Determine g-value and rho' for the IR50 signal > IR50_fading.res <- analyse_FadingMeasurement(IR50_fading) [analyse_FadingMeasurement()] n.MC: 100 tc: 3.78e+02 s --------------------------------------------------- T_0.5 interpolated: NA T_0.5 predicted: 4e+11 g-value: 5.18 ± 0.77 (%/decade) g-value (norm. 2 days): 6.01 ± 0.79 (%/decade) --------------------------------------------------- rho': 3.9e-06 ± 6.43e-07 log10(rho'): -5.41 ± 0.07 --------------------------------------------------- > > ## Show g-value and rho' results > gval <- get_RLum(IR50_fading.res) > rhop <- get_RLum(IR50_fading.res, "rho_prime") > > gval FIT MEAN SD Q_0.025 Q_0.16 Q_0.84 Q_0.975 G_VALUE_2DAYS 5.182106 5.07034 0.7726294 3.508286 4.463758 5.780692 6.519354 TC G_VALUE_2DAYS G_VALUE_2DAYS.ERROR T_0.5_INTERPOLATED G_VALUE_2DAYS 378 6.010655 0.788842 NA T_0.5_PREDICTED T_0.5_PREDICTED.LOWER T_0.5_PREDICTED.UPPER G_VALUE_2DAYS 395648134315 18339400088 18339400088 UID G_VALUE_2DAYS 8dd0b87fcc5377a6 > rhop FIT MEAN SD Q_0.025 Q_0.16 Q_0.84 1 3.904314e-06 3.904314e-06 6.43203e-07 2.493099e-06 3.254242e-06 4.500461e-06 Q_0.975 1 5.099556e-06 > > ## 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 <- fit_DoseResponseCurve(IR50_De.LxTx, + mode = "interpolation", + fit.method = "EXP") [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 977.38 | D01 = 4022.47 > > ## 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) [calc_FadingCorr()] >> Fading correction according to Huntley & Lamothe (2001) .. used g-value: 5.182 ± 0.773 %/decade .. used tc: 1.198e-08 ka .. used kappa: 0.0225 ± 0.0034 ---------------------------------------------- seed: NA n.MC: 10000 observations: 10000 ---------------------------------------------- Age (faded): 139.6261 ka ± 15.0482 ka Age (corr.): 288.1629 ka ± 65.1327 ka ---------------------------------------------- > > > > > cleanEx() > nameEx("ExampleData.FittingLM") > ### * ExampleData.FittingLM > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.FittingLM > ### Title: Example data for fit_LMCurve() in the package Luminescence > ### Aliases: ExampleData.FittingLM values.curve values.curveBG > ### Keywords: datasets internal > > ### ** Examples > > > ##show LM data > data(ExampleData.FittingLM, envir = environment()) > plot(values.curve,log="x") > > > > > cleanEx() > nameEx("ExampleData.LxTxData") > ### * ExampleData.LxTxData > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.LxTxData > ### Title: Example Lx/Tx data from CW-OSL SAR measurement > ### Aliases: ExampleData.LxTxData LxTxData > ### Keywords: datasets internal > > ### ** Examples > > > ## plot Lx/Tx data vs dose [s] > data(ExampleData.LxTxData, envir = environment()) > plot(LxTxData$Dose,LxTxData$LxTx) > > > > > cleanEx() > nameEx("ExampleData.LxTxOSLData") > ### * ExampleData.LxTxOSLData > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.LxTxOSLData > ### Title: Example Lx and Tx curve data from an artificial OSL measurement > ### Aliases: ExampleData.LxTxOSLData Lx.data Tx.data > ### Keywords: datasets internal > > ### ** Examples > > > ##load data > data(ExampleData.LxTxOSLData, envir = environment()) > > ##plot data > plot(Lx.data) > plot(Tx.data) > > > > > cleanEx() > nameEx("ExampleData.MortarData") > ### * ExampleData.MortarData > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.MortarData > ### Title: Example equivalent dose data from mortar samples > ### Aliases: ExampleData.MortarData MortarData > ### Keywords: datasets internal > > ### ** Examples > > > ##load data > data(ExampleData.MortarData, envir = environment()) > > ##plot data > plot(MortarData) > > > > > cleanEx() > nameEx("ExampleData.RF70Curves") > ### * ExampleData.RF70Curves > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.RF70Curves > ### Title: RF70 Example data as RLum.Analysis objects > ### Aliases: ExampleData.RF70Curves RF70Curves > ### Keywords: datasets internal > > ### ** Examples > > > ##load data > data(ExampleData.RF70Curves, envir = environment()) > > ##plot data > plot_RLum(RF70Curves) > > > > > cleanEx() > nameEx("ExampleData.RLum.Analysis") > ### * ExampleData.RLum.Analysis > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.RLum.Analysis > ### Title: Example data as RLum.Analysis objects > ### Aliases: ExampleData.RLum.Analysis IRSAR.RF.Data > ### Keywords: datasets internal > > ### ** Examples > > > ##load data > data(ExampleData.RLum.Analysis, envir = environment()) > > ##plot data > plot_RLum(IRSAR.RF.Data) > > > > > cleanEx() > nameEx("ExampleData.RLum.Data.Image") > ### * ExampleData.RLum.Data.Image > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.RLum.Data.Image > ### Title: Example data as RLum.Data.Image objects > ### Aliases: ExampleData.RLum.Data.Image > ### Keywords: datasets > > ### ** Examples > > > ##load data > data(ExampleData.RLum.Data.Image, envir = environment()) > > ##plot data > plot_RLum(ExampleData.RLum.Data.Image) > > > > > cleanEx() > nameEx("ExampleData.ScaleGammaDose") > ### * ExampleData.ScaleGammaDose > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.ScaleGammaDose > ### Title: Example data for scale_GammaDose() > ### Aliases: ExampleData.ScaleGammaDose > ### Keywords: datasets > > ### ** Examples > > > ## Load data > data("ExampleData.ScaleGammaDose", envir = environment()) > > > > > cleanEx() > nameEx("ExampleData.SurfaceExposure") > ### * ExampleData.SurfaceExposure > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.SurfaceExposure > ### Title: Example OSL surface exposure dating data > ### Aliases: ExampleData.SurfaceExposure > ### Keywords: datasets > > ### ** Examples > > > ## ExampleData.SurfaceExposure$sample_1 > sigmaphi <- 5e-10 > age <- 10000 > mu <- 0.9 > x <- seq(0, 10, 0.1) > fun <- exp(-sigmaphi * age * 365.25*24*3600 * exp(-mu * x)) > > set.seed(666) > synth_1 <- data.frame(depth = x, + intensity = jitter(fun, 1, 0.1), + error = runif(length(x), 0.01, 0.2)) > > ## VALIDATE sample_1 > fit_SurfaceExposure(synth_1, mu = mu, sigmaphi = sigmaphi) [fit_SurfaceExposure()] Estimated parameter(s): --------------------- age (a): 9890 ± 369 Fixed parameter(s): ------------------- sigmaphi: 5e-10 mu: 0.9 [RLum.Results-class] originator: fit_SurfaceExposure() data: 5 .. $summary : data.frame .. $data : data.frame .. $fit : nls .. $args : list .. $call : call additional info elements: 0 > > > ## ExampleData.SurfaceExposure$sample_2 > sigmaphi <- 5e-10 > age <- 10000 > mu <- 0.9 > x <- seq(0, 10, 0.1) > Ddot <- 2.5 / 1000 / 365.25 / 24 / 60 / 60 # 2.5 Gy/ka in Seconds > D0 <- 40 > fun <- (sigmaphi * exp(-mu * x) * + exp(-(age * 365.25*24*3600) * + (sigmaphi * exp(-mu * x) + Ddot/D0)) + Ddot/D0) / + (sigmaphi * exp(-mu * x) + Ddot/D0) > > set.seed(666) > synth_2 <- data.frame(depth = x, + intensity = jitter(fun, 1, 0.1), + error = runif(length(x), 0.01, 0.2)) > > ## VALIDATE sample_2 > fit_SurfaceExposure(synth_2, mu = mu, sigmaphi = sigmaphi, Ddot = 2.5, D0 = D0) [fit_SurfaceExposure()] Estimated parameter(s): --------------------- age (a): 9800 ± 675 Fixed parameter(s): ------------------- sigmaphi: 5e-10 mu: 0.9 [RLum.Results-class] originator: fit_SurfaceExposure() data: 5 .. $summary : data.frame .. $data : data.frame .. $fit : nls .. $args : list .. $call : call additional info elements: 0 > > > ## ExampleData.SurfaceExposure$set_1 > sigmaphi <- 5e-10 > mu <- 0.9 > x <- seq(0, 15, 0.2) > age <- c(1e3, 1e4, 1e5, 1e6) > set.seed(666) > > synth_3 <- vector("list", length = length(age)) > > for (i in 1:length(age)) { + fun <- exp(-sigmaphi * age[i] * 365.25*24*3600 * exp(-mu * x)) + synth_3[[i]] <- data.frame(depth = x, + intensity = jitter(fun, 1, 0.05)) + } > > > ## VALIDATE set_1 > fit_SurfaceExposure(synth_3, age = age, sigmaphi = sigmaphi) [fit_SurfaceExposure()] Shared estimated parameter(s): --------------------- mu: 0.901 ± 0.00161 Fixed parameter(s): ------------------- age (a): 1000, 10000, 1e+05, 1e+06 sigmaphi: 5e-10 To apply the estimated parameters to a sample of unknown age run: fit_SurfaceExposure(data = synth_3, sigmaphi = 5e-10, mu = c(0.901, 0.901, 0.901, 0.901)) [RLum.Results-class] originator: fit_SurfaceExposure() data: 5 .. $summary : data.frame .. $data : data.frame .. $fit : nls .. $args : list .. $call : call additional info elements: 0 > > > ## ExampleData.SurfaceExposure$set_2 > sigmaphi <- 5e-10 > mu <- 0.9 > x <- seq(0, 15, 0.2) > age <- c(1e2, 1e3, 1e4, 1e5, 1e6) > Ddot <- 1.0 / 1000 / 365.25 / 24 / 60 / 60 # 2.0 Gy/ka in Seconds > D0 <- 40 > set.seed(666) > > synth_4 <- vector("list", length = length(age)) > > for (i in 1:length(age)) { + fun <- (sigmaphi * exp(-mu * x) * + exp(-(age[i] * 365.25*24*3600) * + (sigmaphi * exp(-mu * x) + Ddot/D0)) + Ddot/D0) / + (sigmaphi * exp(-mu * x) + Ddot/D0) + + synth_4[[i]] <- data.frame(depth = x, + intensity = jitter(fun, 1, 0.05)) + } > > > ## VALIDATE set_2 > fit_SurfaceExposure(synth_4, age = age, sigmaphi = sigmaphi, D0 = D0, Ddot = 1.0) [fit_SurfaceExposure()] Shared estimated parameter(s): --------------------- mu: 0.899 ± 0.00232 Fixed parameter(s): ------------------- age (a): 100, 1000, 10000, 1e+05, 1e+06 sigmaphi: 5e-10 To apply the estimated parameters to a sample of unknown age run: fit_SurfaceExposure(data = synth_4, sigmaphi = 5e-10, mu = c(0.899, 0.899, 0.899, 0.899, 0.899)) [RLum.Results-class] originator: fit_SurfaceExposure() data: 5 .. $summary : data.frame .. $data : data.frame .. $fit : nls .. $args : list .. $call : call additional info elements: 0 > > ## Not run: > ##D ExampleData.SurfaceExposure <- list( > ##D sample_1 = synth_1, > ##D sample_2 = synth_2, > ##D set_1 = synth_3, > ##D set_2 = synth_4 > ##D ) > ## End(Not run) > > > > > cleanEx() > nameEx("ExampleData.TR_OSL") > ### * ExampleData.TR_OSL > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.TR_OSL > ### Title: Example TR-OSL data > ### Aliases: ExampleData.TR_OSL > ### Keywords: datasets > > ### ** Examples > > > ##(1) curves > data(ExampleData.TR_OSL, envir = environment()) > plot_RLum(ExampleData.TR_OSL) > > > > > cleanEx() > nameEx("ExampleData.XSYG") > ### * ExampleData.XSYG > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.XSYG > ### Title: Example data for a SAR OSL measurement and a TL spectrum using a > ### lexsyg reader > ### Aliases: ExampleData.XSYG OSL.SARMeasurement TL.Spectrum > ### Keywords: datasets internal > > ### ** Examples > > ##show data > data(ExampleData.XSYG, envir = environment()) > > ## ========================================= > ##(1) OSL.SARMeasurement > OSL.SARMeasurement $Sequence.Header state finished parentID 1002220348205854 name R Luminescence example dataset position 30 comment example dataset startDate 20140222034820 protocol SAR mineral quartz $Sequence.Object [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 0 number of records: 124 .. : RLum.Data.Curve : 124 .. .. : #1 TL (UVVIS) <> #2 _TL (NA) <> #3 _TL (NA) .. .. : #4 OSL (UVVIS) <> #5 _OSL (NA) <> #6 _OSL (NA) <> #7 _OSL (NA) <> #8 _OSL (NA) .. .. : #9 irradiation (NA) .. .. : #10 TL (UVVIS) <> #11 _TL (NA) <> #12 _TL (NA) .. .. : #13 OSL (UVVIS) <> #14 _OSL (NA) <> #15 _OSL (NA) <> #16 _OSL (NA) <> #17 _OSL (NA) .. .. : #18 irradiation (NA) .. .. : #19 TL (UVVIS) <> #20 _TL (NA) <> #21 _TL (NA) .. .. : #22 OSL (UVVIS) <> #23 _OSL (NA) <> #24 _OSL (NA) <> #25 _OSL (NA) <> #26 _OSL (NA) .. .. : #27 irradiation (NA) .. .. : #28 TL (UVVIS) <> #29 _TL (NA) <> #30 _TL (NA) .. .. : #31 OSL (UVVIS) <> #32 _OSL (NA) <> #33 _OSL (NA) <> #34 _OSL (NA) <> #35 _OSL (NA) .. .. : #36 irradiation (NA) .. .. : #37 TL (UVVIS) <> #38 _TL (NA) <> #39 _TL (NA) .. .. : #40 OSL (UVVIS) <> #41 _OSL (NA) <> #42 _OSL (NA) <> #43 _OSL (NA) <> #44 _OSL (NA) .. .. : #45 irradiation (NA) .. .. : #46 TL (UVVIS) <> #47 _TL (NA) <> #48 _TL (NA) .. .. : #49 OSL (UVVIS) <> #50 _OSL (NA) <> #51 _OSL (NA) <> #52 _OSL (NA) <> #53 _OSL (NA) .. .. : #54 irradiation (NA) .. .. : #55 TL (UVVIS) <> #56 _TL (NA) <> #57 _TL (NA) .. .. : #58 OSL (UVVIS) <> #59 _OSL (NA) <> #60 _OSL (NA) <> #61 _OSL (NA) <> #62 _OSL (NA) .. .. : #63 irradiation (NA) .. .. : #64 TL (UVVIS) <> #65 _TL (NA) <> #66 _TL (NA) .. .. : #67 OSL (UVVIS) <> #68 _OSL (NA) <> #69 _OSL (NA) <> #70 _OSL (NA) <> #71 _OSL (NA) .. .. : #72 irradiation (NA) .. .. : #73 TL (UVVIS) <> #74 _TL (NA) <> #75 _TL (NA) .. .. : #76 OSL (UVVIS) <> #77 _OSL (NA) <> #78 _OSL (NA) <> #79 _OSL (NA) <> #80 _OSL (NA) .. .. : #81 irradiation (NA) .. .. : #82 TL (UVVIS) <> #83 _TL (NA) <> #84 _TL (NA) .. .. : #85 OSL (UVVIS) <> #86 _OSL (NA) <> #87 _OSL (NA) <> #88 _OSL (NA) <> #89 _OSL (NA) .. .. : #90 TL (UVVIS) <> #91 _TL (NA) <> #92 _TL (NA) .. .. : #93 OSL (UVVIS) <> #94 _OSL (NA) <> #95 _OSL (NA) <> #96 _OSL (NA) <> #97 _OSL (NA) .. .. : #98 irradiation (NA) .. .. : #99 TL (UVVIS) <> #100 _TL (NA) <> #101 _TL (NA) .. .. : #102 OSL (UVVIS) <> #103 _OSL (NA) <> #104 _OSL (NA) <> #105 _OSL (NA) <> #106 _OSL (NA) .. .. : #107 irradiation (NA) .. .. : #108 TL (UVVIS) <> #109 _TL (NA) <> #110 _TL (NA) .. .. : #111 OSL (UVVIS) <> #112 _OSL (NA) <> #113 _OSL (NA) <> #114 _OSL (NA) <> #115 _OSL (NA) .. .. : #116 irradiation (NA) .. .. : #117 TL (UVVIS) <> #118 _TL (NA) <> #119 _TL (NA) .. .. : #120 OSL (UVVIS) <> #121 _OSL (NA) <> #122 _OSL (NA) <> #123 _OSL (NA) <> #124 _OSL (NA) > > ##show $Sequence.Object > OSL.SARMeasurement$Sequence.Object [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 0 number of records: 124 .. : RLum.Data.Curve : 124 .. .. : #1 TL (UVVIS) <> #2 _TL (NA) <> #3 _TL (NA) .. .. : #4 OSL (UVVIS) <> #5 _OSL (NA) <> #6 _OSL (NA) <> #7 _OSL (NA) <> #8 _OSL (NA) .. .. : #9 irradiation (NA) .. .. : #10 TL (UVVIS) <> #11 _TL (NA) <> #12 _TL (NA) .. .. : #13 OSL (UVVIS) <> #14 _OSL (NA) <> #15 _OSL (NA) <> #16 _OSL (NA) <> #17 _OSL (NA) .. .. : #18 irradiation (NA) .. .. : #19 TL (UVVIS) <> #20 _TL (NA) <> #21 _TL (NA) .. .. : #22 OSL (UVVIS) <> #23 _OSL (NA) <> #24 _OSL (NA) <> #25 _OSL (NA) <> #26 _OSL (NA) .. .. : #27 irradiation (NA) .. .. : #28 TL (UVVIS) <> #29 _TL (NA) <> #30 _TL (NA) .. .. : #31 OSL (UVVIS) <> #32 _OSL (NA) <> #33 _OSL (NA) <> #34 _OSL (NA) <> #35 _OSL (NA) .. .. : #36 irradiation (NA) .. .. : #37 TL (UVVIS) <> #38 _TL (NA) <> #39 _TL (NA) .. .. : #40 OSL (UVVIS) <> #41 _OSL (NA) <> #42 _OSL (NA) <> #43 _OSL (NA) <> #44 _OSL (NA) .. .. : #45 irradiation (NA) .. .. : #46 TL (UVVIS) <> #47 _TL (NA) <> #48 _TL (NA) .. .. : #49 OSL (UVVIS) <> #50 _OSL (NA) <> #51 _OSL (NA) <> #52 _OSL (NA) <> #53 _OSL (NA) .. .. : #54 irradiation (NA) .. .. : #55 TL (UVVIS) <> #56 _TL (NA) <> #57 _TL (NA) .. .. : #58 OSL (UVVIS) <> #59 _OSL (NA) <> #60 _OSL (NA) <> #61 _OSL (NA) <> #62 _OSL (NA) .. .. : #63 irradiation (NA) .. .. : #64 TL (UVVIS) <> #65 _TL (NA) <> #66 _TL (NA) .. .. : #67 OSL (UVVIS) <> #68 _OSL (NA) <> #69 _OSL (NA) <> #70 _OSL (NA) <> #71 _OSL (NA) .. .. : #72 irradiation (NA) .. .. : #73 TL (UVVIS) <> #74 _TL (NA) <> #75 _TL (NA) .. .. : #76 OSL (UVVIS) <> #77 _OSL (NA) <> #78 _OSL (NA) <> #79 _OSL (NA) <> #80 _OSL (NA) .. .. : #81 irradiation (NA) .. .. : #82 TL (UVVIS) <> #83 _TL (NA) <> #84 _TL (NA) .. .. : #85 OSL (UVVIS) <> #86 _OSL (NA) <> #87 _OSL (NA) <> #88 _OSL (NA) <> #89 _OSL (NA) .. .. : #90 TL (UVVIS) <> #91 _TL (NA) <> #92 _TL (NA) .. .. : #93 OSL (UVVIS) <> #94 _OSL (NA) <> #95 _OSL (NA) <> #96 _OSL (NA) <> #97 _OSL (NA) .. .. : #98 irradiation (NA) .. .. : #99 TL (UVVIS) <> #100 _TL (NA) <> #101 _TL (NA) .. .. : #102 OSL (UVVIS) <> #103 _OSL (NA) <> #104 _OSL (NA) <> #105 _OSL (NA) <> #106 _OSL (NA) .. .. : #107 irradiation (NA) .. .. : #108 TL (UVVIS) <> #109 _TL (NA) <> #110 _TL (NA) .. .. : #111 OSL (UVVIS) <> #112 _OSL (NA) <> #113 _OSL (NA) <> #114 _OSL (NA) <> #115 _OSL (NA) .. .. : #116 irradiation (NA) .. .. : #117 TL (UVVIS) <> #118 _TL (NA) <> #119 _TL (NA) .. .. : #120 OSL (UVVIS) <> #121 _OSL (NA) <> #122 _OSL (NA) <> #123 _OSL (NA) <> #124 _OSL (NA) > > ##grep OSL curves and plot the first curve > OSLcurve <- get_RLum(OSL.SARMeasurement$Sequence.Object, + recordType="OSL")[[1]] > plot_RLum(OSLcurve) > > ## ========================================= > ##(2) TL.Spectrum > TL.Spectrum [RLum.Data.Spectrum-class] recordType: TL (Spectrometer) curveType: measured .. recorded frames: 24 .. .. measured values per frame: 1024 .. .. range wavelength/pixel: 296.5 823.126 .. .. range time/temp.: 0.029 460.007 .. .. range count values: 554 65405 additional info elements: 14 > > ##plot simple spectrum (2D) > plot_RLum.Data.Spectrum(TL.Spectrum, + plot.type="contour", + xlim = c(310,750), + ylim = c(0,300), + bin.rows=10, + bin.cols = 1) Warning: [plot_RLum.Data.Spectrum()] 6 channels removed due to row (wavelength) binning > > ##plot 3d spectrum (uncomment for usage) > # plot_RLum.Data.Spectrum(TL.Spectrum, plot.type="persp", > # xlim = c(310,750), ylim = c(0,300), bin.rows=10, > # bin.cols = 1) > > > > > cleanEx() > nameEx("ExampleData.portableOSL") > ### * ExampleData.portableOSL > > flush(stderr()); flush(stdout()) > > ### Name: ExampleData.portableOSL > ### Title: Example portable OSL curve data for the package Luminescence > ### Aliases: ExampleData.portableOSL > ### Keywords: datasets > > ### ** Examples > > > data(ExampleData.portableOSL, envir = environment()) > plot_RLum(ExampleData.portableOSL) > > > > > cleanEx() > nameEx("RLum-class") > ### * RLum-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum-class > ### Title: Class '"RLum"' > ### Aliases: RLum-class > ### Keywords: classes > > ### ** Examples > > > showClass("RLum") Virtual Class "RLum" [package "Luminescence"] Slots: Name: originator info .uid .pid Class: character list character character Known Subclasses: Class "RLum.Analysis", directly Class "RLum.Data", directly Class "RLum.Results", directly Class "RLum.Data.Curve", by class "RLum.Data", distance 2 Class "RLum.Data.Image", by class "RLum.Data", distance 2 Class "RLum.Data.Spectrum", by class "RLum.Data", distance 2 > > > > > cleanEx() > nameEx("RLum.Analysis-class") > ### * RLum.Analysis-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum.Analysis-class > ### Title: Class '"RLum.Analysis"' > ### Aliases: RLum.Analysis-class > ### Keywords: classes methods > > ### ** Examples > > > ## show method > showClass("RLum.Analysis") Class "RLum.Analysis" [package "Luminescence"] Slots: Name: protocol records originator info .uid .pid Class: character list character list character character Extends: "RLum" > > ##set an empty object > set_RLum(class = "RLum.Analysis") [RLum.Analysis-class] originator: NA() protocol: NA additional info elements: 0 number of records: 0 >> This is an empty object, which cannot be used for further analysis! << > > ## use example data > ##load data > data(ExampleData.RLum.Analysis, envir = environment()) > > ##show curves in object > get_RLum(IRSAR.RF.Data) [[1]] [RLum.Data.Curve-class] recordType: RF (NA) curveType: NA measured values: 5 .. range of x-values: 0.1747448 6.311132 .. range of y-values: 1423.15 1437.8 additional info elements: 0 [[2]] [RLum.Data.Curve-class] recordType: RF (NA) curveType: NA measured values: 524 .. range of x-values: 0.3768403 715.4821 .. range of y-values: 1379.947 2103.4 additional info elements: 0 > > ##show only the first object, but by keeping the object > get_RLum(IRSAR.RF.Data, record.id = 1, drop = FALSE) [RLum.Analysis-class] originator: NA() protocol: IRSAR additional info elements: 0 number of records: 1 .. : RLum.Data.Curve : 1 .. .. : #1 RF (NA) > > ## subsetting with SAR sample data > data(ExampleData.BINfileData, envir = environment()) > sar <- object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data) > > ## get > get_RLum(sar, subset = "NPOINTS == 250") [[1]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[2]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[3]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[4]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[5]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[6]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[7]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[8]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[9]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[10]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[11]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[12]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[13]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[14]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[15]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[16]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[17]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[18]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[19]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[20]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[21]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[22]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[23]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) [[24]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 TL (PMT) | #2 TL (PMT) | #3 TL (PMT) | #4 TL (PMT) | #5 TL (PMT) | #6 TL (PMT) | #7 TL (PMT) .. .. : #8 TL (PMT) | #9 TL (PMT) | #10 TL (PMT) | #11 TL (PMT) | #12 TL (PMT) | #13 TL (PMT) | #14 TL (PMT) .. .. : #15 TL (PMT) > > ## remove > remove_RLum(sar, subset = "NPOINTS == 250") [[1]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[2]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[3]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[4]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[5]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[6]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[7]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[8]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[9]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[10]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[11]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[12]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[13]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[14]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[15]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[16]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[17]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[18]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[19]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[20]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[21]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[22]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[23]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) [[24]] [RLum.Analysis-class] originator: Risoe.BINfileData2RLum.Analysis() protocol: unknown additional info elements: 0 number of records: 15 .. : RLum.Data.Curve : 15 .. .. : #1 OSL (PMT) | #2 OSL (PMT) | #3 OSL (PMT) | #4 OSL (PMT) | #5 OSL (PMT) | #6 OSL (PMT) | #7 OSL (PMT) .. .. : #8 OSL (PMT) | #9 OSL (PMT) | #10 OSL (PMT) | #11 OSL (PMT) | #12 OSL (PMT) | #13 OSL (PMT) | #14 OSL (PMT) .. .. : #15 IRSL (PMT) > > > > > cleanEx() > nameEx("RLum.Data-class") > ### * RLum.Data-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum.Data-class > ### Title: Class '"RLum.Data"' > ### Aliases: RLum.Data-class > ### Keywords: classes internal > > ### ** Examples > > > showClass("RLum.Data") Virtual Class "RLum.Data" [package "Luminescence"] Slots: Name: originator info .uid .pid Class: character list character character Extends: "RLum" Known Subclasses: "RLum.Data.Curve", "RLum.Data.Image", "RLum.Data.Spectrum" > > > > > cleanEx() > nameEx("RLum.Data.Curve-class") > ### * RLum.Data.Curve-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum.Data.Curve-class > ### Title: Class '"RLum.Data.Curve"' > ### Aliases: RLum.Data.Curve-class > ### Keywords: classes > > ### ** Examples > > > showClass("RLum.Data.Curve") Class "RLum.Data.Curve" [package "Luminescence"] Slots: Name: recordType curveType data originator info .uid Class: character character matrix character list character Name: .pid Class: character Extends: Class "RLum.Data", directly Class "RLum", by class "RLum.Data", distance 2 > > ##set empty curve object > set_RLum(class = "RLum.Data.Curve") [RLum.Data.Curve-class] recordType: NA curveType: NA measured values: 1 .. range of x-values: 0 0 .. range of y-values: 0 0 additional info elements: 0 > > > > > cleanEx() > nameEx("RLum.Data.Image-class") > ### * RLum.Data.Image-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum.Data.Image-class > ### Title: Class '"RLum.Data.Image"' > ### Aliases: RLum.Data.Image-class > ### Keywords: classes > > ### ** Examples > > > showClass("RLum.Data.Image") Class "RLum.Data.Image" [package "Luminescence"] Slots: Name: recordType curveType data info originator .uid Class: character character array list character character Name: .pid Class: character Extends: Class "RLum.Data", directly Class "RLum", by class "RLum.Data", distance 2 > > ##create empty RLum.Data.Image object > set_RLum(class = "RLum.Data.Image") [RLum.Data.Image-class] recordType: Image curveType: NA .. recorded frames: 1 .. .. pixel per frame: NA .. .. x dimension [px]: 1 .. .. y dimension [px]: NA .. .. full pixel value range: NA : NA additional info elements: 0 > > > > > cleanEx() > nameEx("RLum.Data.Spectrum-class") > ### * RLum.Data.Spectrum-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum.Data.Spectrum-class > ### Title: Class '"RLum.Data.Spectrum"' > ### Aliases: RLum.Data.Spectrum-class > ### Keywords: classes > > ### ** Examples > > > showClass("RLum.Data.Spectrum") Class "RLum.Data.Spectrum" [package "Luminescence"] Slots: Name: recordType curveType data info originator .uid Class: character character matrix list character character Name: .pid Class: character Extends: Class "RLum.Data", directly Class "RLum", by class "RLum.Data", distance 2 > > ##show example data > data(ExampleData.XSYG, envir = environment()) > TL.Spectrum [RLum.Data.Spectrum-class] recordType: TL (Spectrometer) curveType: measured .. recorded frames: 24 .. .. measured values per frame: 1024 .. .. range wavelength/pixel: 296.5 823.126 .. .. range time/temp.: 0.029 460.007 .. .. range count values: 554 65405 additional info elements: 14 > > ##show data matrix > get_RLum(TL.Spectrum) 0.029 20.027 40.025 60.026 80.025 100.023 120.022 140.022 160.02 296.5 555 556.0 561 568 573 579 573 574 570 297.055 555 556.0 560 568 573 579 574 574 570 297.61 555 556.0 555 564 571 579 575 573 573 298.164 554 555.0 555 557 571 579 576 572 573 298.719 554 555.0 555 556 569 579 578 571 573 299.273 554 555.0 555 556 569 579 578 571 572 299.827 554 555.0 557 556 569 579 579 571 572 300.382 555 558.0 557 557 567 579 579 576 572 300.936 555 562.0 560 562 567 579 579 576 574 301.489 557 562.5 560 562 567 579 579 576 574 302.043 559 562.5 560 562 568 579 579 574 574 302.597 560 563.0 560 562 570 579 579 574 574 303.15 560 563.0 560 562 571 580 579 575 572 303.703 560 563.0 560 562 574 580 579 579 572 304.256 560 563.0 560 564 575 580 581 580 572 304.809 560 564.0 561 564 576 580 581 580 575 305.362 561 564.0 561 564 578 581 581 580 578 305.915 561 565.0 562 565 578 581 582 580 578 306.467 561 565.0 563 566 578 582 582 580 578 307.02 561 565.0 564 566 578 582 582 583 575 307.572 561 565.0 564 568 574 582 582 583 575 308.124 565 565.0 566 568 574 582 582 583 575 308.676 565 565.0 566 569 574 582 581 580 575 309.228 564 565.0 566 570 574 582 581 580 580 309.78 564 565.0 566 570 577 583 581 580 580 310.332 564 565.0 566 570 577 583 581 581 580 310.883 562 565.0 566 570 577 583 584 584 580 311.435 562 565.0 567 572 575 583 584 584 580 311.986 564 565.0 567 572 575 583 584 584 580 312.537 567 565.0 567 572 575 584 584 584 581 313.088 567 565.0 567 572 575 584 584 584 585 313.639 567 566.0 568 572 577 585 584 583 585 314.189 567 566.0 568 572 577 585 586 583 585 314.74 567 566.0 568 572 577 585 586 583 585 315.29 567 566.0 567 572 577 586 586 583 585 315.841 567 566.0 567 571 577 586 586 579 583 316.391 564 567.0 567 571 576 586 586 578 582 316.941 564 567.0 567 571 576 586 585 578 580 317.491 563 567.0 567 569 576 586 585 580 580 318.04 563 567.0 567 569 577 586 585 583 583 318.59 563 567.0 567 569 577 586 585 583 586 319.139 566 566.0 567 569 578 585 586 584 586 319.689 566 566.0 566 569 580 585 586 584 586 320.238 566 566.0 566 569 580 585 586 584 585 320.787 566 567.0 566 569 577 585 582 584 585 321.336 566 567.0 566 569 577 585 582 584 585 321.885 565 567.0 567 569 577 585 582 584 585 322.433 564 567.0 567 569 577 585 585 585 583 322.982 564 567.0 567 569 577 585 585 585 583 323.53 564 567.0 567 569 577 585 585 585 582 324.079 564 567.0 567 569 577 585 585 585 582 324.627 563 567.0 567 568 577 585 585 582 582 325.175 563 567.0 566 568 580 585 585 582 586 325.723 563 567.0 566 568 580 585 585 582 586 326.271 563 567.0 566 569 580 585 585 585 586 326.818 565 567.0 566 569 580 585 585 585 585 327.366 565 567.0 566 569 580 585 586 586 584 327.913 565 567.0 566 569 580 586 586 586 584 328.46 565 568.0 566 569 580 586 586 586 583 329.007 565 568.0 566 569 579 586 586 586 583 329.554 565 568.0 566 569 577 586 587 587 583 330.101 564 568.0 566 568 577 586 587 587 584 330.648 564 568.0 566 568 577 586 587 587 586 331.195 564 567.0 566 568 580 586 587 587 586 331.741 565 567.0 566 568 580 587 587 587 586 332.287 566 567.0 566 568 580 587 587 587 586 332.834 568 567.0 567 568 580 588 587 587 586 333.38 568 567.0 567 568 580 588 587 587 586 333.926 568 567.0 567 568 580 588 587 587 590 334.472 568 567.0 566 568 580 588 587 587 590 335.017 564 567.0 566 568 582 589 588 587 590 335.563 564 566.0 566 568 582 589 588 587 586 336.108 566 566.0 566 568 582 589 589 587 584 336.654 567 566.0 566 569 582 589 589 587 584 337.199 567 566.0 566 569 582 589 589 587 582 337.744 567 566.0 566 569 582 589 589 587 582 338.289 566 566.0 566 569 582 589 589 587 582 338.834 566 566.0 566 569 582 589 589 587 588 339.378 566 566.0 566 569 582 590 589 584 588 339.923 565 566.0 567 569 582 590 589 583 588 340.467 565 565.0 567 569 582 591 591 583 588 341.012 566 565.0 567 569 581 591 591 583 588 341.556 567 565.0 568 569 581 591 591 583 587 342.1 568 565.0 568 569 581 591 591 583 587 342.644 568 565.0 568 569 581 591 591 584 587 343.188 568 566.0 567 569 581 592 591 586 587 343.731 568 566.0 567 570 586 592 591 586 588 344.275 567 566.0 567 570 586 593 592 586 588 344.818 567 565.0 566 571 583 593 592 586 588 345.362 566 565.0 566 571 583 593 592 586 586 345.905 566 565.0 566 571 587 593 592 586 586 346.448 566 565.0 566 571 587 593 593 586 584 346.991 566 565.0 566 571 587 593 594 586 584 347.534 566 565.0 566 571 587 594 594 586 584 348.076 566 565.0 566 571 587 594 594 586 585 348.619 566 567.0 566 571 587 594 594 586 585 349.161 567 567.0 566 571 588 596 594 586 585 349.704 567 567.0 566 571 588 596 594 586 585 350.246 567 567.0 566 571 588 596 594 586 585 350.788 567 567.0 566 571 588 598 594 586 585 351.33 567 567.0 566 571 588 598 594 586 584 351.872 567 567.0 566 571 588 598 594 587 583 352.414 567 567.0 566 571 588 598 594 587 583 352.955 567 567.0 566 571 588 598 596 587 583 353.497 566 567.0 566 571 588 599 596 587 583 354.038 566 566.0 565 571 588 599 596 587 587 354.579 566 566.0 565 571 588 599 596 589 590 355.12 566 565.0 565 571 588 599 596 589 590 355.661 565 565.0 565 571 588 599 596 589 590 356.202 565 565.0 565 571 589 600 596 590 584 356.743 564 565.0 566 571 590 600 597 590 584 357.284 564 565.0 567 571 591 601 597 591 584 357.824 564 565.0 567 571 592 601 597 591 584 358.364 564 566.0 567 571 592 601 597 593 584 358.905 564 566.0 567 571 590 601 597 593 588 359.445 564 566.0 567 571 590 603 597 593 588 359.985 566 565.0 567 571 590 603 598 593 584 360.525 566 565.0 567 573 590 605 598 593 584 361.065 566 565.0 567 574 590 606 598 594 587 361.604 567 565.0 567 574 592 606 599 594 588 362.144 567 565.0 567 574 592 606 600 595 588 362.683 567 565.0 567 574 592 606 600 595 588 363.223 567 565.0 567 574 592 607 600 595 588 363.762 566 564.0 567 575 596 607 601 597 588 364.301 564 564.0 567 575 596 608 604 597 588 364.84 564 564.0 567 575 597 608 605 598 588 365.379 563 564.0 567 575 597 610 605 598 588 365.917 563 565.0 567 575 597 613 605 598 590 366.456 563 565.0 567 575 597 613 606 598 590 366.995 565 565.0 567 575 592 613 607 598 590 367.533 565 565.0 567 575 592 613 607 599 590 368.071 565 566.0 567 576 600 617 609 599 590 368.609 565 566.0 567 576 602 617 609 599 590 369.147 566 566.0 567 576 604 619 609 599 590 369.685 567 566.0 567 577 604 620 610 600 590 370.223 567 565.0 567 577 604 621 610 601 590 370.761 567 565.0 567 577 604 621 610 601 590 371.298 567 565.0 567 577 604 622 611 602 591 371.836 567 565.0 567 576 605 623 613 602 596 372.373 567 565.0 567 576 608 623 614 602 596 372.91 566 565.0 566 576 610 623 614 602 596 373.447 566 565.0 566 578 611 623 614 603 598 373.984 565 565.0 566 578 611 624 614 603 598 374.521 565 565.0 566 578 612 626 614 605 599 375.058 565 566.0 566 578 612 627 615 605 599 375.595 565 566.0 566 578 613 628 616 608 599 376.131 565 566.0 566 578 613 628 617 608 599 376.668 567 566.0 566 579 613 629 617 610 599 377.204 567 566.0 567 579 613 629 620 613 599 377.74 567 566.0 567 579 614 630 621 613 600 378.276 566 566.0 567 579 615 630 621 613 600 378.812 566 566.0 567 579 615 631 624 613 600 379.348 566 566.0 567 579 615 631 625 613 600 379.884 566 566.0 567 579 615 634 625 613 600 380.419 566 566.0 567 579 615 634 625 613 601 380.955 566 566.0 567 580 615 635 627 613 602 381.49 566 566.0 567 580 616 635 627 614 604 382.026 565 566.0 567 580 617 635 627 614 604 382.561 565 566.0 567 580 618 635 627 614 604 383.096 565 566.0 567 580 618 636 627 614 605 383.631 565 566.0 567 580 618 637 627 614 605 384.166 565 566.0 567 580 618 637 628 614 605 384.7 565 566.0 567 580 619 639 628 614 605 385.235 565 566.0 567 580 619 639 630 615 606 385.77 565 565.0 567 580 620 644 630 615 606 386.304 569 565.0 567 580 620 646 630 615 607 386.838 569 565.0 567 580 622 646 630 617 607 387.372 568 565.0 567 580 622 646 631 617 607 387.907 566 565.0 567 580 623 648 631 617 607 388.441 566 565.0 567 580 623 649 631 617 607 388.974 566 565.0 567 580 624 649 631 619 607 389.508 566 565.0 567 583 624 649 632 619 607 390.042 566 565.0 567 583 626 650 632 619 608 390.575 566 565.0 567 583 627 650 632 620 608 391.109 569 565.0 567 583 628 650 633 620 608 391.642 569 565.0 567 583 628 651 633 620 609 392.175 569 565.0 567 583 629 652 634 620 609 392.708 569 565.0 567 583 629 652 635 620 610 393.241 569 565.0 567 583 629 653 638 623 610 393.774 569 565.0 567 583 631 653 638 623 612 394.307 569 565.0 567 583 631 654 639 623 612 394.84 567 565.0 567 583 631 654 639 623 613 395.372 567 565.0 567 583 632 655 639 624 613 395.905 567 565.0 566 583 632 655 640 625 613 396.437 567 565.0 566 583 632 659 640 625 614 396.969 567 565.0 566 583 633 659 641 625 615 397.501 567 567.0 566 583 633 659 642 626 615 398.033 566 567.0 567 583 634 660 643 626 615 398.565 566 567.0 567 583 634 661 643 626 616 399.097 566 567.0 567 583 634 661 644 626 616 399.629 567 567.0 567 583 634 661 644 627 616 400.16 567 567.0 567 583 634 662 644 627 616 400.692 567 567.0 567 584 634 663 645 627 616 401.223 567 567.0 566 584 636 663 645 629 617 401.755 567 567.0 565 584 637 663 645 629 617 402.286 567 567.0 565 584 637 664 647 629 617 402.817 566 567.0 565 584 637 664 647 629 617 403.348 566 568.0 566 584 637 664 650 630 617 403.879 566 568.0 566 586 637 665 651 630 617 404.409 566 568.0 567 587 637 665 651 630 617 404.94 562 568.0 567 587 637 667 651 630 618 405.471 562 568.0 567 587 638 668 652 630 618 406.001 562 568.0 567 587 638 668 652 631 618 406.531 562 567.0 567 587 640 669 652 631 617 407.062 564 567.0 567 587 640 670 652 631 617 407.592 564 567.0 567 587 641 670 652 631 617 408.122 564 566.0 568 587 641 672 653 631 617 408.652 568 565.0 568 587 642 673 653 631 617 409.181 568 565.0 568 587 642 673 653 631 617 409.711 568 565.0 568 587 643 673 653 631 617 410.241 567 565.0 567 587 644 674 653 631 617 410.77 567 565.0 567 587 644 674 653 632 617 411.3 567 564.0 567 587 644 675 653 632 616 411.829 567 564.0 567 587 645 675 653 632 616 412.358 566 564.0 568 587 647 676 654 633 615 412.887 566 564.0 568 587 647 678 654 633 615 413.416 566 564.0 568 587 647 679 655 633 615 413.945 566 564.0 568 588 648 680 655 634 615 414.474 567 564.0 568 588 648 680 655 634 615 415.003 567 564.0 568 588 648 680 655 635 615 415.531 567 564.0 568 588 649 680 655 636 615 416.06 567 564.0 567 588 650 680 655 636 615 416.588 567 564.0 567 588 650 680 655 636 615 417.117 567 564.0 567 588 650 680 655 636 615 417.645 567 564.0 568 588 650 680 655 636 615 418.173 566 564.0 568 588 650 680 655 636 615 418.701 566 564.0 568 588 650 681 655 636 615 419.229 565 564.0 569 588 650 681 655 636 615 419.757 565 564.0 569 588 651 681 655 636 613 420.284 565 565.0 569 588 651 681 655 635 613 420.812 564 565.0 569 589 652 681 655 634 612 421.34 564 565.0 569 589 652 680 655 634 612 421.867 563 565.0 569 589 653 680 655 634 612 422.394 563 565.0 569 589 653 680 655 633 612 422.921 563 565.0 569 589 653 680 655 633 612 423.449 564 565.0 570 589 653 680 655 633 612 423.976 565 565.0 570 589 653 680 655 633 612 424.503 565 565.0 570 589 654 680 655 633 612 425.029 565 565.0 570 589 654 680 655 633 612 425.556 564 565.0 570 589 654 680 655 632 612 426.083 564 565.0 570 589 654 680 655 632 612 426.609 564 565.0 570 589 653 680 655 632 612 427.136 565 566.0 569 589 653 680 655 632 612 427.662 566 566.0 569 589 653 680 655 631 612 428.188 566 566.0 569 589 653 680 655 631 612 428.714 566 566.0 569 589 653 680 655 631 611 429.24 566 566.0 569 589 653 680 654 631 611 429.766 566 566.0 569 589 653 680 654 631 610 430.292 566 566.0 569 589 653 680 654 631 610 430.818 566 566.0 569 589 652 680 654 630 610 431.344 565 566.0 570 589 652 680 654 630 610 431.869 565 566.0 570 589 652 680 653 630 610 432.395 565 566.0 570 588 651 680 653 629 610 432.92 566 566.0 570 587 651 680 653 629 610 433.445 568 566.0 570 587 651 680 653 629 609 433.971 568 566.0 570 587 651 680 653 629 609 434.496 571 566.0 569 588 651 680 653 629 608 435.021 571 566.0 569 588 651 680 653 629 608 435.546 571 566.0 569 588 650 680 653 629 608 436.071 567 566.0 569 588 649 680 653 629 608 436.595 567 566.0 569 588 649 679 653 629 608 437.12 567 566.0 570 588 649 679 653 629 608 437.644 567 566.0 570 589 649 679 653 629 608 438.169 566 566.0 570 589 649 679 653 629 608 438.693 566 566.0 570 589 650 678 653 629 608 439.218 566 567.0 570 589 650 678 653 629 608 439.742 565 567.0 570 589 650 678 653 629 608 440.266 565 567.0 571 589 650 678 653 629 608 440.79 565 567.0 571 589 650 678 653 629 608 441.314 565 567.0 571 590 649 678 651 629 608 441.837 565 567.0 571 590 649 678 651 629 608 442.361 565 567.0 570 590 649 678 651 629 608 442.885 565 567.0 570 590 648 678 651 629 608 443.408 565 567.0 570 590 648 678 651 628 608 443.932 565 567.0 570 590 648 678 651 627 608 444.455 565 567.0 570 590 648 678 651 627 608 444.978 565 567.0 570 589 648 678 651 627 608 445.502 563 567.0 570 589 648 677 651 627 608 446.025 563 567.0 570 589 648 677 651 627 607 446.548 563 567.0 570 589 648 677 650 627 607 447.071 563 567.0 570 589 648 677 650 627 607 447.593 565 567.0 570 589 648 677 650 627 607 448.116 565 567.0 569 589 648 677 649 627 607 448.639 565 567.0 569 589 648 677 649 627 606 449.161 565 567.0 569 589 647 677 648 627 606 449.684 565 567.0 569 589 647 676 648 627 606 450.206 565 566.0 569 589 647 676 648 627 606 450.728 565 566.0 569 589 647 676 648 627 606 451.251 565 566.0 569 589 647 676 648 627 606 451.773 565 566.0 569 589 647 676 648 627 606 452.295 565 566.0 569 588 647 675 648 627 606 452.817 565 566.0 569 588 647 675 648 627 606 453.338 565 566.0 568 588 647 674 648 627 605 453.86 566 566.0 568 588 647 674 648 627 605 454.382 566 566.0 568 588 647 673 648 627 605 454.903 566 565.0 568 588 647 673 648 627 604 455.425 566 565.0 568 588 647 673 648 627 604 455.946 566 565.0 567 588 646 673 648 627 604 456.468 565 566.0 567 587 646 673 647 626 604 456.989 565 566.0 567 587 646 673 646 626 603 457.51 570 566.0 568 587 646 671 646 626 603 458.031 570 566.0 568 587 645 671 646 625 603 458.552 570 566.0 568 587 645 671 646 625 602 459.073 569 566.0 567 587 645 671 646 623 602 459.594 569 566.0 567 587 645 670 646 622 602 460.114 568 566.0 567 587 645 670 646 622 602 460.635 565 566.0 567 587 645 670 646 622 602 461.156 563 566.0 567 587 645 670 645 622 602 461.676 563 566.0 567 587 645 670 645 622 601 462.196 563 566.0 567 587 645 669 644 622 601 462.717 563 566.0 567 587 645 669 644 622 601 463.237 565 566.0 567 587 645 669 643 622 601 463.757 566 566.0 567 587 645 669 643 621 601 464.277 566 566.0 567 587 645 669 643 621 602 464.797 566 566.0 569 587 645 669 642 621 602 465.317 565 566.0 569 587 645 668 642 620 602 465.837 563 566.0 569 587 644 668 642 620 602 466.356 563 566.0 569 587 644 666 642 620 602 466.876 563 566.0 569 587 644 666 642 620 601 467.396 565 566.0 569 587 644 666 642 620 601 467.915 565 566.0 569 587 644 666 642 620 601 468.434 565 566.0 568 587 644 665 642 620 601 468.954 565 566.0 568 587 642 665 641 620 601 469.473 564 566.0 568 587 642 664 641 620 601 469.992 564 566.0 568 587 640 664 641 619 601 470.511 566 566.0 568 587 640 663 641 619 601 471.03 566 566.0 568 587 640 663 639 618 601 471.549 566 566.0 568 587 640 662 639 617 601 472.068 568 566.0 568 587 638 662 639 617 601 472.586 568 566.0 568 585 637 662 639 617 601 473.105 568 565.0 568 585 637 662 639 617 601 473.624 572 565.0 568 585 637 662 639 617 601 474.142 572 565.0 568 586 637 661 639 616 601 474.661 572 565.0 568 586 637 661 639 616 600 475.179 568 565.0 568 586 637 661 639 616 599 475.697 568 565.0 568 585 637 660 639 617 599 476.215 566 565.0 568 585 636 659 637 617 599 476.733 566 565.0 568 585 636 659 637 617 599 477.251 566 565.0 568 585 636 659 637 617 598 477.769 567 565.0 568 585 636 658 637 617 598 478.287 567 565.0 568 585 636 658 636 617 598 478.805 567 565.0 568 585 635 658 636 617 598 479.323 567 565.0 569 585 635 658 636 617 598 479.84 567 567.0 569 584 635 658 637 617 599 480.358 567 567.0 569 584 633 657 637 617 599 480.875 567 567.0 569 584 633 657 637 617 599 481.393 565 567.0 569 584 632 656 636 617 599 481.91 565 567.0 569 584 632 656 636 617 599 482.427 565 567.0 569 584 632 656 636 617 599 482.944 564 567.0 569 584 632 656 635 617 599 483.461 564 567.0 569 584 632 656 635 617 599 483.978 564 567.0 569 584 631 655 635 617 599 484.495 564 567.0 569 584 631 655 636 617 599 485.012 564 567.0 569 584 631 655 636 617 599 485.529 563 567.0 569 584 631 655 636 617 599 486.045 563 567.0 569 584 631 654 635 616 599 486.562 563 567.0 569 584 631 654 635 616 599 487.079 563 567.0 568 584 631 654 635 616 599 487.595 563 567.0 568 584 631 654 636 616 599 488.111 562 567.0 568 584 631 654 636 616 599 488.628 562 567.0 568 584 632 655 636 616 599 489.144 562 566.0 568 584 632 655 635 615 599 489.66 562 566.0 568 584 632 655 635 614 599 490.176 563 566.0 568 584 632 655 635 614 599 490.692 563 566.0 568 584 633 655 635 614 599 491.208 564 566.0 568 584 633 655 635 614 599 491.724 568 566.0 568 584 633 654 635 614 599 492.24 568 565.0 568 584 633 654 636 614 599 492.755 565 565.0 568 584 633 654 636 614 599 493.271 565 565.0 568 584 632 654 636 614 599 493.787 565 565.0 568 584 632 654 636 614 600 494.302 565 565.0 568 584 632 654 636 614 600 494.817 565 565.0 568 584 632 654 636 614 600 495.333 565 565.0 567 584 633 654 636 614 600 495.848 565 565.0 567 584 633 654 636 614 600 496.363 565 565.0 567 584 633 654 636 617 600 496.878 565 565.0 567 584 632 654 636 617 601 497.393 565 565.0 567 584 632 654 636 617 601 497.908 566 565.0 567 584 632 654 636 617 601 498.423 566 565.0 567 584 631 654 638 617 601 498.938 566 565.0 567 583 631 654 638 617 601 499.453 562 565.0 567 583 630 656 638 617 601 499.968 562 565.0 567 583 630 656 640 617 601 500.482 562 565.0 567 583 630 656 640 619 602 500.997 567 565.0 567 583 630 656 640 620 602 501.511 567 565.0 567 583 630 656 640 620 603 502.026 567 565.0 567 583 631 657 641 622 604 502.54 567 565.0 567 583 633 657 641 622 604 503.054 565 565.0 567 583 633 657 641 622 604 503.568 565 565.0 567 583 633 657 641 622 605 504.083 565 565.0 567 583 633 657 641 622 605 504.597 566 565.0 567 583 633 659 641 622 605 505.111 566 565.0 567 583 633 659 641 622 606 505.625 566 565.0 568 583 633 659 642 623 606 506.138 566 565.0 568 583 633 659 642 623 606 506.652 566 565.0 568 583 633 661 643 623 606 507.166 566 565.0 568 583 633 661 643 625 607 507.679 568 565.0 568 583 633 661 643 626 607 508.193 568 565.0 568 583 633 662 644 626 607 508.707 568 565.0 568 583 633 663 644 627 610 509.22 568 565.0 568 584 633 663 644 627 611 509.733 566 565.0 568 584 633 664 644 627 611 510.247 565 565.0 568 584 633 665 645 628 611 510.76 565 565.0 568 584 633 665 645 629 611 511.273 565 565.0 568 585 634 665 646 629 611 511.786 565 565.0 568 585 634 665 647 629 612 512.299 567 565.0 568 585 635 666 648 629 613 512.812 567 565.0 568 585 635 666 648 630 613 513.325 567 565.0 568 585 635 666 648 630 613 513.838 566 565.0 568 585 635 666 649 631 613 514.351 566 565.0 568 585 634 666 650 631 613 514.863 566 565.0 569 585 634 666 651 631 613 515.376 569 565.0 569 585 634 666 651 632 614 515.889 569 565.0 569 585 634 667 652 632 614 516.401 569 565.0 569 585 634 667 652 634 614 516.913 567 565.0 569 585 637 669 652 634 615 517.426 567 565.0 569 585 637 670 654 635 615 517.938 567 565.0 569 585 637 670 654 637 616 518.45 567 565.0 569 585 637 670 655 638 616 518.963 565 566.0 569 585 639 670 655 638 616 519.475 565 566.0 569 586 639 670 655 638 616 519.987 565 566.0 569 586 639 670 655 638 616 520.499 565 566.0 569 586 641 670 656 638 616 521.011 565 565.0 569 586 641 671 656 639 617 521.522 565 565.0 569 586 641 674 656 640 617 522.034 566 565.0 569 586 641 674 658 640 618 522.546 566 565.0 569 586 641 674 658 640 618 523.058 566 565.0 569 586 642 674 658 640 618 523.569 566 565.0 569 586 642 674 659 641 620 524.081 566 565.0 569 585 642 674 659 642 620 524.592 566 565.0 569 585 642 674 659 642 620 525.104 566 565.0 569 585 642 675 660 642 620 525.615 566 565.0 569 585 642 675 660 642 621 526.126 566 565.0 569 585 642 676 660 642 622 526.637 566 565.0 569 586 642 676 660 643 623 527.149 568 566.0 569 586 643 676 662 643 623 527.66 568 566.0 569 586 643 678 662 643 623 528.171 568 566.0 569 586 643 679 664 644 623 528.682 564 566.0 569 586 643 679 664 644 623 529.193 563 566.0 569 586 643 679 665 644 624 529.704 563 566.0 568 587 644 679 665 645 624 530.214 564 565.0 568 587 644 679 665 645 625 530.725 566 565.0 568 588 644 679 666 646 625 531.236 567 565.0 568 588 644 680 666 646 626 531.746 567 565.0 568 588 644 680 666 646 626 532.257 567 565.0 567 588 644 681 666 646 628 532.767 565 565.0 567 588 644 681 667 647 628 533.278 565 565.0 567 588 644 681 667 647 628 533.788 565 565.0 567 588 644 681 667 647 628 534.298 565 565.0 567 588 644 681 667 648 628 534.809 565 565.0 567 588 644 681 669 648 628 535.319 565 565.0 567 588 644 682 669 648 629 535.829 565 565.0 567 588 645 682 669 649 630 536.339 565 565.0 567 588 645 682 670 649 630 536.849 565 565.0 567 588 645 683 670 649 630 537.359 563 564.0 567 588 645 684 671 649 630 537.869 563 564.0 567 588 645 685 672 651 630 538.379 565 564.0 567 588 645 685 674 651 630 538.889 565 564.0 567 588 645 685 674 651 631 539.398 565 564.0 567 588 646 685 674 651 631 539.908 565 564.0 567 588 646 685 675 651 631 540.418 566 564.0 567 588 646 685 675 653 631 540.927 566 564.0 567 588 646 687 675 653 631 541.437 566 564.0 567 588 648 687 676 653 631 541.946 566 564.0 567 588 650 688 676 653 631 542.456 566 566.0 567 588 650 688 676 653 632 542.965 566 566.0 567 588 650 688 676 653 632 543.474 566 566.0 569 588 648 688 676 653 632 543.983 566 566.0 569 588 648 688 676 654 632 544.493 566 566.0 569 588 648 687 676 654 632 545.002 566 567.0 569 588 648 687 676 654 632 545.511 563 567.0 569 588 648 687 676 654 632 546.02 563 567.0 569 587 648 687 677 654 634 546.529 563 567.0 569 587 649 687 677 654 634 547.038 563 566.0 569 587 649 687 677 654 634 547.546 563 566.0 567 587 649 687 677 654 634 548.055 566 566.0 567 587 649 687 677 654 634 548.564 566 566.0 567 587 649 687 677 654 634 549.073 566 566.0 567 587 649 687 677 654 634 549.581 566 566.0 567 587 648 687 677 654 634 550.09 566 566.0 568 587 648 687 677 654 634 550.598 565 566.0 568 587 648 687 677 654 636 551.107 565 566.0 568 587 648 687 677 656 636 551.615 565 566.0 568 587 648 687 677 656 636 552.123 566 566.0 568 587 648 687 677 656 636 552.632 566 566.0 568 586 648 687 677 656 636 553.14 566 566.0 568 586 648 687 677 656 636 553.648 566 566.0 568 586 648 687 677 656 636 554.156 567 565.0 568 586 648 687 677 656 634 554.664 567 565.0 568 586 648 687 677 656 634 555.172 567 565.0 568 586 647 687 677 656 634 555.68 567 565.0 568 587 647 687 677 656 634 556.188 567 565.0 568 587 647 686 675 656 634 556.696 567 565.0 568 587 646 686 675 656 634 557.204 569 565.0 568 587 646 686 675 656 634 557.712 569 565.0 568 587 646 686 675 656 634 558.22 569 565.0 568 587 646 686 675 656 634 558.727 565 565.0 568 587 646 685 675 654 634 559.235 565 565.0 568 587 646 685 675 654 634 559.742 565 565.0 568 587 645 684 675 654 635 560.25 566 565.0 568 587 645 682 675 654 635 560.757 566 566.0 568 587 645 682 675 654 635 561.265 566 566.0 568 587 646 682 675 653 635 561.772 566 566.0 568 587 646 682 675 653 633 562.28 566 565.0 568 587 646 682 675 653 633 562.787 566 565.0 568 587 644 681 675 652 632 563.294 566 565.0 568 587 644 681 675 652 632 563.801 565 565.0 569 587 644 681 675 652 632 564.308 564 565.0 569 587 643 680 675 652 632 564.815 564 565.0 569 587 642 680 675 651 632 565.323 564 565.0 569 587 640 680 672 651 633 565.83 566 565.0 569 587 640 680 672 651 633 566.336 566 565.0 569 587 640 680 672 651 633 566.843 566 565.0 569 587 640 680 672 651 633 567.35 566 565.0 569 587 639 680 671 650 632 567.857 562 565.0 569 587 639 680 671 650 632 568.364 562 565.0 569 587 639 680 671 649 632 568.87 562 565.0 569 587 639 680 670 649 632 569.377 565 565.0 569 587 639 680 668 649 632 569.884 565 566.0 568 586 639 680 668 649 632 570.39 567 566.0 568 586 638 679 668 649 632 570.897 570 566.0 568 586 638 678 668 649 632 571.403 570 566.0 568 586 638 678 667 648 632 571.91 569 566.0 568 587 637 678 665 647 632 572.416 566 566.0 569 587 637 677 665 647 632 572.922 564 566.0 569 587 637 675 665 647 632 573.429 564 566.0 569 587 637 675 664 646 632 573.935 564 567.0 569 587 636 675 664 646 631 574.441 566 567.0 568 586 636 673 664 645 631 574.947 569 567.0 568 586 636 673 663 645 630 575.453 569 567.0 568 586 636 673 662 644 629 575.959 567 566.0 567 586 635 672 662 643 629 576.465 567 566.0 567 586 635 671 662 643 629 576.971 564 566.0 567 586 634 670 662 641 629 577.477 564 566.0 567 586 634 668 659 638 629 577.983 564 566.0 567 586 632 668 659 638 628 578.489 567 566.0 567 584 631 668 659 638 627 578.995 568 566.0 566 584 630 667 658 636 627 579.501 568 566.0 566 584 630 666 657 636 627 580.006 568 566.0 566 583 630 666 657 636 627 580.512 568 566.0 567 583 629 665 655 636 627 581.018 568 567.0 567 583 629 664 655 636 627 581.523 568 567.0 567 583 629 663 655 636 627 582.029 565 567.0 567 582 629 662 654 636 626 582.534 565 567.0 567 582 629 661 654 635 626 583.04 565 567.0 566 582 629 660 654 635 626 583.545 565 566.0 566 582 629 657 653 635 626 584.05 565 565.0 566 582 629 657 652 635 626 584.556 565 565.0 566 582 626 657 650 635 626 585.061 565 565.0 566 581 626 657 650 635 625 585.566 565 565.0 567 581 626 657 650 635 625 586.071 566 565.0 567 581 626 657 650 634 625 586.577 566 565.0 567 581 625 656 649 632 625 587.082 566 565.0 567 581 625 655 648 632 625 587.587 566 565.0 567 580 625 655 648 632 625 588.092 566 565.0 567 580 624 653 647 632 624 588.597 567 565.0 567 580 624 652 647 632 623 589.102 567 565.0 566 580 623 651 646 632 622 589.607 567 565.0 566 581 623 651 644 632 622 590.112 566 565.0 566 581 623 651 644 631 622 590.616 566 565.0 566 581 623 650 643 630 622 591.121 563 565.0 566 580 622 648 642 629 622 591.626 563 565.0 566 580 620 648 642 629 622 592.131 563 565.0 566 580 620 647 641 627 622 592.635 565 565.0 566 580 620 647 641 626 622 593.14 567 565.0 566 580 620 646 641 626 622 593.645 567 565.0 566 580 619 646 641 626 622 594.149 567 565.0 566 580 618 646 640 625 622 594.654 567 565.0 566 580 618 645 639 625 622 595.158 566 565.0 566 579 618 645 638 625 621 595.663 566 565.0 566 579 617 644 638 625 621 596.167 566 565.0 566 579 615 644 635 625 621 596.672 564 565.0 566 579 615 644 635 625 621 597.176 564 565.0 566 578 614 644 635 624 621 597.68 564 565.0 566 578 614 643 635 624 621 598.185 566 565.0 566 578 614 643 634 623 620 598.689 568 565.0 566 577 614 643 634 621 620 599.193 568 565.0 566 577 614 642 634 621 620 599.697 568 565.0 567 577 614 640 634 621 620 600.201 568 565.0 567 577 614 640 633 620 620 600.705 567 565.0 567 577 614 640 633 619 619 601.209 565 565.0 567 577 614 640 632 619 616 601.713 565 565.0 567 577 614 639 631 619 615 602.217 567 565.0 567 577 614 638 628 619 614 602.721 569 565.0 567 577 613 638 628 617 614 603.225 569 565.0 567 577 612 636 628 617 614 603.729 569 565.0 567 577 612 636 627 617 613 604.233 569 565.0 567 577 611 636 627 616 613 604.737 569 565.0 567 577 611 635 627 616 613 605.241 569 565.0 567 577 610 634 626 614 612 605.744 569 565.0 567 577 609 633 626 613 612 606.248 569 565.0 567 577 609 631 626 611 612 606.752 569 565.0 567 577 609 631 625 611 612 607.255 565 565.0 567 577 609 631 625 611 611 607.759 564 567.0 567 577 609 631 625 611 611 608.263 564 567.0 567 577 608 630 621 611 611 608.766 567 567.0 567 577 604 630 621 611 610 609.27 569 567.0 567 577 604 630 621 610 608 609.773 569 567.0 566 577 604 630 621 609 608 610.277 569 567.0 566 577 602 629 621 609 608 610.78 569 567.0 566 577 602 628 620 607 608 611.283 569 566.0 566 577 602 628 620 606 608 611.787 569 566.0 566 577 602 627 619 606 608 612.29 569 566.0 566 577 601 627 619 605 607 612.793 569 566.0 566 577 601 627 619 605 607 613.297 566 565.0 566 577 601 627 619 605 607 613.8 566 565.0 566 577 601 627 619 605 607 614.303 564 565.0 566 577 601 626 619 605 607 614.806 564 565.0 566 576 601 625 618 605 607 615.309 564 566.0 565 576 601 624 618 604 607 615.812 564 566.0 565 575 601 624 617 603 607 616.316 564 566.0 565 575 601 624 617 603 607 616.819 564 566.0 565 575 601 624 617 603 607 617.322 564 566.0 565 575 601 623 615 603 607 617.825 564 566.0 565 575 601 623 615 602 607 618.328 564 566.0 565 575 601 623 615 602 606 618.83 564 566.0 565 575 598 621 615 602 606 619.333 564 566.0 566 575 598 621 614 602 606 619.836 564 566.0 566 574 598 621 614 603 606 620.339 564 566.0 566 574 598 621 614 603 606 620.842 564 566.0 566 574 598 620 614 603 606 621.345 565 566.0 566 574 598 620 613 603 606 621.847 565 566.0 566 573 599 620 613 603 606 622.35 566 566.0 566 573 599 618 613 603 604 622.853 566 566.0 566 573 598 618 613 603 604 623.355 567 566.0 566 573 598 617 613 602 604 623.858 567 566.0 566 573 597 617 611 601 604 624.361 567 566.0 566 573 597 616 611 600 604 624.863 567 567.0 566 573 597 615 611 600 604 625.366 567 567.0 566 573 597 615 611 600 604 625.868 567 567.0 566 572 597 615 611 600 604 626.371 565 566.0 566 572 597 615 611 600 604 626.873 565 566.0 566 571 597 615 611 600 604 627.376 565 566.0 566 571 597 615 611 599 604 627.878 565 566.0 566 571 597 616 611 599 604 628.381 565 566.0 566 572 597 616 611 599 604 628.883 565 566.0 566 573 598 616 611 599 604 629.385 566 566.0 566 573 598 616 611 599 604 629.888 566 566.0 566 573 598 616 611 599 604 630.39 566 566.0 566 573 598 616 611 599 604 630.892 565 566.0 566 573 595 615 611 599 604 631.395 565 566.0 566 573 595 615 611 599 604 631.897 564 566.0 566 573 595 614 610 598 604 632.399 564 566.0 566 573 596 614 610 598 604 632.901 564 566.0 566 573 597 614 610 598 604 633.403 564 566.0 566 573 599 614 609 598 604 633.905 564 566.0 566 573 599 614 609 598 604 634.408 565 566.0 566 573 599 614 609 598 604 634.91 565 566.0 566 573 599 614 609 598 604 635.412 565 565.0 566 573 599 614 607 598 604 635.914 565 565.0 566 573 597 614 607 598 603 636.416 565 565.0 566 573 594 614 606 598 603 636.918 563 566.0 566 573 594 614 606 598 602 637.42 563 566.0 566 573 594 613 606 598 601 637.922 564 566.0 566 573 596 612 606 597 601 638.424 566 566.0 566 573 596 612 606 597 601 638.925 566 566.0 566 573 596 612 606 597 601 639.427 566 565.0 566 573 596 612 606 597 600 639.929 565 565.0 566 573 596 612 606 596 600 640.431 565 565.0 565 571 596 612 606 596 600 640.933 565 565.0 565 571 594 612 606 596 600 641.435 565 565.0 565 571 594 612 606 595 600 641.936 565 565.0 565 571 594 612 606 595 600 642.438 564 565.0 565 571 594 611 606 595 600 642.94 564 566.0 565 571 594 609 606 595 600 643.442 564 566.0 564 571 594 609 606 594 600 643.943 564 566.0 564 571 593 609 606 594 600 644.445 564 566.0 564 571 593 609 606 594 600 644.947 560 566.0 564 571 593 608 606 594 600 645.448 560 565.0 564 571 592 608 606 594 600 645.95 563 565.0 564 571 592 608 606 594 600 646.451 564 565.0 564 571 592 609 606 594 600 646.953 564 565.0 564 571 594 609 606 594 600 647.455 565 564.0 564 571 594 609 606 594 600 647.956 565 564.0 565 573 594 609 606 594 600 648.458 566 564.0 565 573 594 608 606 594 600 648.959 566 564.0 565 573 592 608 606 594 600 649.461 566 564.0 565 573 592 608 606 594 599 649.962 566 564.0 565 573 592 609 605 594 599 650.464 566 564.0 565 573 594 609 605 594 599 650.965 566 564.0 565 573 594 609 605 594 599 651.466 566 564.0 565 573 595 609 605 594 598 651.968 566 564.0 565 573 595 611 605 594 598 652.469 566 564.0 565 573 596 611 604 593 598 652.97 566 564.0 565 573 596 611 603 592 598 653.472 566 564.0 565 573 596 611 603 592 598 653.973 566 564.0 565 573 592 611 603 592 598 654.474 567 564.0 565 574 592 610 603 592 596 654.976 567 564.0 565 574 592 610 602 592 596 655.477 567 564.0 565 574 592 610 601 592 596 655.978 564 564.0 565 574 593 610 601 592 595 656.48 564 564.0 565 573 594 610 601 592 595 656.981 564 565.0 565 573 594 610 600 592 594 657.482 567 565.0 565 573 594 610 600 592 594 657.983 567 565.0 565 573 594 610 600 592 594 658.484 567 565.0 565 573 591 610 600 592 594 658.985 562 565.0 566 572 591 610 600 592 594 659.487 562 565.0 566 572 591 610 600 591 594 659.988 562 565.0 566 572 591 610 600 591 593 660.489 563 565.0 566 572 595 610 600 591 593 660.99 563 564.0 566 572 595 610 600 591 593 661.491 563 564.0 566 572 595 610 600 591 593 661.992 565 564.0 566 572 595 610 600 591 593 662.493 565 564.0 565 572 595 610 600 591 593 662.994 565 564.0 565 572 595 610 600 592 593 663.495 564 564.0 565 572 595 610 600 592 593 663.996 564 564.0 565 572 595 610 600 592 593 664.497 564 564.0 565 572 595 610 600 592 593 664.998 565 564.0 566 572 595 610 600 592 593 665.499 565 564.0 566 572 596 610 600 592 593 666 565 565.0 566 572 596 610 600 592 593 666.501 562 565.0 566 573 596 610 600 592 593 667.002 562 565.0 566 573 596 610 600 592 593 667.503 562 565.0 566 574 596 610 600 592 593 668.004 566 565.0 566 575 596 610 600 592 593 668.505 566 566.0 566 575 596 610 600 592 593 669.006 568 566.0 566 575 595 610 600 592 593 669.507 568 566.0 566 576 595 610 600 592 593 670.008 568 566.0 566 576 595 610 600 592 593 670.509 568 566.0 567 576 596 610 600 592 592 671.009 568 566.0 567 576 599 610 600 592 591 671.51 568 566.0 568 577 600 611 600 592 591 672.011 567 566.0 568 577 600 611 600 592 591 672.512 567 566.0 568 577 600 611 600 592 591 673.013 566 566.0 568 577 600 611 600 592 589 673.514 566 566.0 568 577 600 611 600 592 588 674.014 564 566.0 568 577 600 611 600 591 588 674.515 564 566.0 568 577 600 611 600 591 590 675.016 564 566.0 568 577 600 611 600 591 591 675.517 566 566.0 568 577 599 610 600 592 591 676.018 566 566.0 568 577 599 610 600 592 589 676.518 566 566.0 568 577 599 610 600 592 588 677.019 566 566.0 568 577 599 611 600 592 588 677.52 567 566.0 568 577 599 611 602 592 587 678.02 567 566.0 568 577 599 611 602 592 587 678.521 567 566.0 566 577 601 611 602 592 588 679.022 566 566.0 566 577 601 612 602 592 588 679.523 566 566.0 566 577 600 612 602 592 588 680.023 566 566.0 565 577 600 612 602 592 588 680.524 566 566.0 565 577 600 612 602 592 588 681.025 567 565.0 565 577 600 612 602 592 586 681.525 567 565.0 566 577 601 612 602 592 586 682.026 567 565.0 566 577 601 612 602 592 586 682.527 567 565.0 566 577 601 612 602 592 589 683.027 567 565.0 566 576 601 612 602 592 589 683.528 567 565.0 566 576 603 612 602 592 590 684.029 567 565.0 566 576 603 612 602 592 590 684.529 566 565.0 566 576 603 612 601 592 590 685.03 566 565.0 566 577 603 612 601 592 590 685.531 566 565.0 566 577 603 613 601 592 590 686.031 566 565.0 566 578 603 613 601 592 590 686.532 566 565.0 566 578 603 614 601 592 590 687.032 566 565.0 566 578 603 614 601 592 590 687.533 564 565.0 566 578 603 614 601 592 590 688.034 564 565.0 567 578 603 614 600 592 590 688.534 564 565.0 567 578 603 614 600 592 590 689.035 564 565.0 567 578 602 616 600 592 590 689.536 564 565.0 567 578 602 616 600 592 590 690.036 565 565.0 567 578 603 616 600 592 590 690.537 565 565.0 567 578 603 616 600 592 590 691.037 565 565.0 567 578 604 616 600 592 590 691.538 565 565.0 567 578 604 616 601 592 590 692.038 565 565.0 567 579 604 616 602 592 590 692.539 565 565.0 567 580 604 616 602 592 590 693.04 566 565.0 567 580 604 616 602 592 590 693.54 566 565.0 567 580 604 616 602 592 590 694.041 566 565.0 567 580 604 616 602 592 590 694.541 565 565.0 567 580 605 616 602 592 586 695.042 564 565.0 567 580 606 616 602 590 586 695.542 564 565.0 567 580 608 616 602 590 586 696.043 562 565.0 567 580 608 616 602 590 588 696.544 562 565.0 567 580 608 616 602 590 588 697.044 562 565.0 567 580 608 616 602 590 588 697.545 564 565.0 567 580 608 616 602 590 587 698.045 566 565.0 567 580 608 616 602 592 587 698.546 566 565.0 567 580 608 616 602 592 587 699.046 566 566.0 567 580 609 616 602 592 586 699.547 562 566.0 567 580 609 616 602 592 586 700.047 562 566.0 567 580 609 616 602 590 586 700.548 562 566.0 567 580 609 616 603 590 586 701.049 562 566.0 566 580 609 616 603 590 586 701.549 567 566.0 566 580 609 616 603 589 587 702.05 567 566.0 566 580 609 616 603 589 587 702.55 567 566.0 566 580 609 616 603 589 587 703.051 567 566.0 566 580 609 616 603 589 583 703.551 567 566.0 566 580 608 616 603 589 583 704.052 566 566.0 567 580 608 616 603 589 583 704.552 565 566.0 567 580 608 616 603 590 583 705.053 565 566.0 567 580 609 616 603 590 585 705.554 565 566.0 567 580 609 616 603 590 585 706.054 565 566.0 567 580 609 616 602 590 585 706.555 566 566.0 567 580 609 617 602 590 582 707.055 566 566.0 567 580 609 617 602 590 582 707.556 566 566.0 567 580 609 617 602 590 582 708.056 566 566.0 567 580 609 616 601 590 584 708.557 568 566.0 567 580 609 616 601 590 586 709.058 568 566.0 567 580 609 616 601 590 586 709.558 568 566.0 567 581 609 616 601 590 586 710.059 568 566.0 567 581 609 616 601 590 585 710.559 568 565.0 567 581 609 616 601 590 584 711.06 566 565.0 567 581 609 616 601 590 583 711.561 566 565.0 567 581 609 616 601 590 583 712.061 566 565.0 567 581 609 616 601 590 581 712.562 566 565.0 567 581 609 616 601 591 581 713.062 566 566.0 567 581 609 616 601 591 581 713.563 566 566.0 567 580 609 615 601 591 580 714.064 564 566.0 567 580 609 615 601 591 580 714.564 564 565.0 567 580 609 615 601 590 579 715.065 564 565.0 567 580 609 615 601 590 579 715.566 563 565.0 567 580 609 615 601 590 579 716.066 563 565.0 567 580 609 615 601 590 582 716.567 568 565.0 567 580 609 615 601 590 582 717.068 568 565.0 567 580 609 615 601 590 582 717.568 568 565.0 567 580 609 615 601 590 582 718.069 565 567.0 567 580 609 615 601 589 583 718.57 565 567.0 567 580 609 615 601 589 583 719.07 565 567.0 567 580 609 615 601 589 583 719.571 564 567.0 567 580 609 615 601 590 583 720.072 565 567.0 568 580 609 615 600 590 583 720.572 567 567.0 568 580 609 615 600 590 584 721.073 567 567.0 568 580 609 615 600 589 584 721.574 567 567.0 568 580 609 615 600 589 585 722.074 567 567.0 568 580 609 615 600 589 585 722.575 567 567.0 568 580 609 615 600 589 586 723.076 567 567.0 568 580 608 615 600 588 586 723.577 567 567.0 568 580 608 614 600 588 586 724.077 567 567.0 568 580 608 614 600 588 582 724.578 567 567.0 568 580 608 614 600 588 582 725.079 567 567.0 568 580 607 613 600 588 582 725.58 564 567.0 567 580 607 613 600 589 583 726.081 564 567.0 567 580 607 613 600 589 585 726.581 564 567.0 567 580 607 613 600 589 585 727.082 565 567.0 567 580 607 613 600 589 583 727.583 568 567.0 567 580 607 613 600 589 578 728.084 568 566.0 567 580 607 614 600 588 578 728.585 568 566.0 567 580 607 614 600 588 578 729.086 567 566.0 567 580 607 614 600 588 583 729.586 567 566.0 567 580 607 614 600 588 583 730.087 565 566.0 567 582 607 614 600 587 583 730.588 564 566.0 567 582 607 614 600 587 583 731.089 564 566.0 567 582 607 614 600 587 583 731.59 564 566.0 567 582 607 614 600 587 579 732.091 564 566.0 567 582 607 614 600 587 579 732.592 565 566.0 567 582 607 614 600 587 579 733.093 568 566.0 567 582 607 614 600 587 579 733.594 568 566.0 567 582 607 614 597 587 579 734.095 568 566.0 567 582 607 614 597 587 581 734.596 568 566.0 567 582 607 614 597 587 583 735.097 568 566.0 567 582 607 613 597 587 583 735.598 568 566.0 567 582 607 613 597 587 583 736.099 568 566.0 567 582 607 613 597 586 581 736.6 568 566.0 567 582 607 613 597 586 581 737.101 567 566.0 567 582 607 613 595 586 581 737.602 566 566.0 567 582 606 613 595 586 578 738.103 566 566.0 567 582 606 613 595 586 578 738.604 565 566.0 567 582 606 613 595 586 578 739.105 565 566.0 567 582 606 612 596 586 580 739.606 565 566.0 567 582 606 612 596 586 580 740.107 565 566.0 567 582 606 612 596 585 580 740.609 565 566.0 567 582 606 612 596 585 580 741.11 565 566.0 567 582 606 612 596 585 580 741.611 567 566.0 567 582 606 612 596 585 580 742.112 567 565.0 567 582 606 612 596 586 579 742.613 567 565.0 567 582 606 612 596 586 579 743.114 565 565.0 567 581 606 612 595 586 579 743.616 565 565.0 567 581 604 612 595 586 580 744.117 565 565.0 567 581 604 612 595 586 582 744.618 565 565.0 567 581 604 612 595 586 582 745.119 569 565.0 567 581 604 612 595 586 580 745.621 569 566.0 567 579 604 612 595 586 577 746.122 569 566.0 567 579 604 612 595 586 575 746.623 569 566.0 567 579 604 612 595 586 575 747.125 565 566.0 567 579 604 612 595 586 575 747.626 564 566.0 567 579 604 611 595 586 575 748.128 564 566.0 567 579 604 610 595 586 575 748.629 565 566.0 567 579 604 610 593 586 575 749.13 565 566.0 567 579 604 609 593 586 575 749.632 565 565.0 567 579 603 609 593 586 576 750.133 565 565.0 567 578 603 609 593 586 576 750.635 566 565.0 567 578 603 609 593 586 579 751.136 566 565.0 567 578 603 608 593 586 579 751.638 565 565.0 567 578 603 608 593 586 579 752.139 565 565.0 567 578 603 608 593 586 579 752.641 565 566.0 567 578 602 608 593 586 579 753.142 568 566.0 567 578 602 608 593 585 579 753.644 568 566.0 567 578 599 607 594 585 579 754.145 568 566.0 567 577 599 607 594 583 577 754.647 567 566.0 567 577 598 606 594 583 577 755.149 567 566.0 567 577 598 606 593 585 577 755.65 567 566.0 567 577 598 606 593 585 577 756.152 567 566.0 567 577 599 606 593 585 578 756.654 568 566.0 567 577 600 606 594 585 578 757.155 568 566.0 567 577 602 605 594 585 578 757.657 568 566.0 567 577 602 605 594 585 574 758.159 565 566.0 567 577 601 604 593 584 574 758.661 565 566.0 567 577 599 604 593 583 574 759.163 567 566.0 567 577 598 604 593 583 576 759.664 567 566.0 567 577 598 604 593 583 576 760.166 567 566.0 567 577 599 604 593 583 577 760.668 567 566.0 567 577 599 604 593 583 577 761.17 567 566.0 567 577 599 604 593 583 577 761.672 564 566.0 567 577 599 604 593 583 578 762.174 564 566.0 567 576 599 603 593 583 578 762.676 564 566.0 567 576 598 603 592 583 578 763.178 564 566.0 567 576 598 603 591 582 578 763.68 567 566.0 567 576 596 603 591 577 579 764.182 567 566.0 567 576 596 603 591 577 579 764.684 567 566.0 567 576 596 603 591 577 579 765.186 566 566.0 567 576 598 602 591 582 579 765.688 563 566.0 567 576 598 602 591 582 579 766.19 563 566.0 567 576 598 600 591 582 578 766.692 563 566.0 567 576 597 600 591 582 573 767.194 565 565.0 567 576 597 600 590 582 573 767.697 565 565.0 567 576 596 600 590 580 580 768.199 565 565.0 567 576 596 600 590 580 580 768.701 569 565.0 567 576 596 600 591 580 573 769.203 569 565.0 567 576 595 600 591 580 573 769.706 569 565.0 567 576 595 600 591 580 573 770.208 569 565.0 567 576 595 600 591 582 573 770.71 567 565.0 567 576 595 598 591 582 573 771.213 567 565.0 567 576 597 598 590 582 578 771.715 567 565.0 567 576 597 598 590 580 578 772.217 567 565.0 567 576 597 598 590 579 578 772.72 567 565.0 567 576 597 597 590 579 576 773.222 568 566.0 567 576 593 597 590 580 573 773.725 569 566.0 566 576 592 597 590 580 573 774.227 569 566.0 566 576 592 597 590 580 573 774.73 569 566.0 566 576 592 596 590 580 575 775.232 567 566.0 566 576 590 596 590 581 575 775.735 567 565.0 566 576 590 596 590 582 575 776.238 567 565.0 566 576 590 596 590 582 575 776.74 567 565.0 566 576 590 596 591 582 575 777.243 567 565.0 566 576 592 596 591 580 575 777.746 565 566.0 566 576 592 596 591 580 574 778.248 565 566.0 566 576 592 596 591 580 574 778.751 565 566.0 566 576 592 595 591 580 574 779.254 565 566.0 566 575 593 595 589 580 574 779.757 565 566.0 566 575 593 595 589 581 576 780.26 565 566.0 566 575 593 595 588 581 578 780.763 567 566.0 566 575 591 595 588 581 578 781.266 567 566.0 566 575 590 595 588 579 575 781.768 567 566.0 566 575 589 594 588 579 573 782.271 567 566.0 566 575 589 594 588 579 573 782.774 566 566.0 566 575 589 594 588 579 573 783.277 565 566.0 566 575 591 594 588 578 574 783.781 565 566.0 567 574 591 594 588 578 577 784.284 565 566.0 567 574 591 592 588 578 577 784.787 565 566.0 567 574 591 591 588 577 577 785.29 566 566.0 567 574 591 591 588 577 574 785.793 566 566.0 567 574 591 591 588 577 572 786.296 566 566.0 567 574 591 591 588 577 572 786.799 566 566.0 566 574 591 591 588 577 572 787.303 566 566.0 566 574 591 591 587 577 572 787.806 562 566.0 566 574 591 591 587 577 572 788.309 562 566.0 566 573 591 591 587 578 572 788.813 562 566.0 566 573 591 591 587 578 574 789.316 563 566.0 566 573 591 592 587 579 574 789.82 566 566.0 567 573 591 592 587 580 574 790.323 566 566.0 567 573 590 592 587 580 574 790.827 566 566.0 567 573 589 592 587 578 575 791.33 567 567.0 567 573 589 592 587 578 575 791.834 571 567.0 567 573 587 592 587 578 575 792.337 571 567.0 567 573 586 592 587 578 574 792.841 571 567.0 567 573 586 592 587 578 573 793.345 568 567.0 567 573 586 592 586 578 573 793.848 565 567.0 566 573 586 592 585 578 574 794.352 565 567.0 566 573 586 591 583 578 574 794.856 565 567.0 566 573 588 591 583 578 574 795.359 566 567.0 567 573 588 591 583 580 574 795.863 566 567.0 567 573 588 591 583 580 574 796.367 566 567.0 567 573 588 591 583 575 575 796.871 567 567.0 567 572 588 591 581 575 575 797.375 567 567.0 567 572 580 591 580 575 575 797.879 567 567.0 567 572 580 591 580 575 573 798.383 567 567.0 567 572 580 591 580 576 573 798.887 565 567.0 567 572 581 591 580 576 573 799.391 565 567.0 566 572 583 589 582 576 574 799.895 565 566.0 566 572 583 589 582 580 574 800.399 563 566.0 566 572 583 588 582 583 574 800.904 563 566.0 566 572 583 588 582 583 574 801.408 563 566.0 566 572 583 588 582 583 574 801.912 563 566.0 566 572 583 588 582 579 573 802.416 565 566.0 566 572 583 588 582 579 573 802.921 567 566.0 566 572 583 588 582 577 573 803.425 567 566.0 566 572 583 588 581 575 573 803.929 561 566.0 566 572 590 588 580 575 573 804.434 561 566.0 566 571 590 588 580 575 573 804.938 562 566.0 566 571 590 588 579 579 573 805.443 565 566.0 566 571 585 588 579 579 572 805.947 565 566.0 566 571 585 588 579 579 571 806.452 565 564.0 566 571 585 588 581 579 571 806.957 565 564.0 566 571 582 587 582 574 571 807.461 565 564.0 566 572 582 587 582 574 571 807.966 565 564.0 566 572 582 587 582 574 571 808.471 564 564.0 566 572 583 587 582 576 572 808.975 562 566.0 566 571 583 587 582 578 572 809.48 562 566.0 566 571 583 587 582 578 572 809.985 562 566.0 565 571 583 586 582 578 572 810.49 565 566.0 565 571 583 586 582 578 572 810.995 565 566.0 565 571 586 586 582 578 572 811.5 565 566.0 565 571 586 586 580 577 575 812.005 565 566.0 565 572 586 586 579 577 575 812.51 564 567.0 565 572 583 586 579 577 575 813.015 563 567.0 565 572 583 586 580 577 575 813.52 563 567.0 565 572 583 586 581 578 575 814.026 563 566.0 565 572 583 586 581 578 577 814.531 563 566.0 565 573 583 586 582 578 577 815.036 563 566.0 565 573 583 586 582 575 574 815.541 563 566.0 565 574 583 586 582 575 574 816.047 563 566.0 566 574 582 586 580 575 573 816.552 563 566.0 566 574 582 586 580 575 572 817.057 563 566.0 566 575 582 586 581 575 572 817.563 564 566.0 566 575 582 586 581 575 571 818.068 564 566.0 566 575 582 586 581 575 571 818.574 564 566.0 566 575 582 586 581 575 571 819.08 566 566.0 569 575 582 586 579 575 573 819.585 566 566.0 569 575 580 586 578 575 573 820.091 566 564.0 570 575 580 586 578 575 574 820.597 566 564.0 570 575 580 586 578 575 574 821.102 566 564.0 569 576 580 587 577 577 574 821.608 566 566.0 569 603 582 587 577 578 574 822.114 565 567.0 566 603 582 587 577 578 574 822.62 565 567.0 565 603 582 587 577 578 574 823.126 565 567.0 563 603 582 587 577 578 574 180.019 200.02 220.018 240.017 260.016 280.015 300.014 320.014 340.014 296.5 571 562 561.0 562.0 566 571 587 623 690 297.055 571 562 561.0 562.0 565 571 586 623 686 297.61 564 562 557.0 562.0 561 567 583 623 684 298.164 564 562 557.0 562.0 559 567 581 621 684 298.719 564 563 557.0 562.0 559 567 580 613 684 299.273 564 563 560.0 563.0 563 567 580 613 684 299.827 566 563 560.0 563.0 567 568 583 613 684 300.382 566 563 560.0 563.0 567 569 586 613 687 300.936 566 565 560.0 563.5 567 569 586 615 687 301.489 571 566 562.5 563.5 567 569 586 615 687 302.043 571 566 564.0 564.0 567 569 586 619 687 302.597 571 566 565.0 564.0 565 569 586 622 686 303.15 572 566 565.0 564.0 565 569 584 622 686 303.703 572 567 566.0 564.0 565 573 584 622 686 304.256 572 567 566.0 564.0 565 575 584 622 686 304.809 572 570 567.0 566.0 565 576 588 622 686 305.362 572 570 568.0 566.0 568 576 588 619 686 305.915 573 570 568.0 566.0 569 576 588 619 686 306.467 574 568 569.0 567.0 569 576 590 619 686 307.02 574 568 569.0 567.0 569 574 590 618 686 307.572 574 568 570.0 568.0 569 574 590 618 686 308.124 574 572 570.0 569.0 571 574 590 618 687 308.676 574 574 571.0 569.0 571 578 593 619 687 309.228 576 574 571.0 569.0 571 578 593 619 687 309.78 576 574 571.0 569.0 568 578 594 619 687 310.332 577 574 571.0 569.0 567 576 594 619 687 310.883 578 574 571.0 570.0 567 576 596 621 687 311.435 579 574 571.0 571.0 567 576 596 621 684 311.986 579 574 572.0 571.0 569 577 596 621 684 312.537 579 574 572.0 571.0 570 579 598 621 684 313.088 579 574 572.0 571.0 573 579 602 622 684 313.639 579 574 572.0 571.0 573 579 603 622 687 314.189 579 575 573.0 571.0 573 579 599 622 687 314.74 579 575 573.0 571.0 574 577 591 622 687 315.29 579 577 573.0 571.0 574 577 591 621 687 315.841 579 581 574.0 572.0 574 577 591 621 687 316.391 579 581 574.0 572.0 574 577 591 619 687 316.941 579 579 574.0 572.0 574 578 590 619 687 317.491 579 578 574.0 572.0 575 578 590 617 690 318.04 579 578 574.0 572.0 575 578 590 617 690 318.59 579 578 574.0 572.0 575 574 590 617 690 319.139 580 578 574.0 572.0 575 574 591 617 690 319.689 580 578 574.0 572.0 576 574 591 615 686 320.238 580 578 574.0 572.0 576 577 591 615 682 320.787 580 578 575.0 572.0 576 579 591 615 681 321.336 580 578 575.0 572.0 575 579 591 615 681 321.885 580 578 576.0 572.0 575 580 591 620 681 322.433 580 578 576.0 572.0 575 580 591 621 684 322.982 580 581 576.0 572.0 575 580 590 623 684 323.53 580 581 576.0 573.0 575 580 590 623 684 324.079 580 580 576.0 573.0 577 579 590 623 684 324.627 580 580 577.0 573.0 577 579 590 622 684 325.175 580 580 577.0 573.0 573 579 588 621 684 325.723 580 580 577.0 573.0 573 579 588 621 684 326.271 580 580 577.0 573.0 573 578 588 619 684 326.818 581 578 576.0 573.0 573 578 588 619 687 327.366 581 578 576.0 573.0 573 578 589 619 687 327.913 581 578 576.0 573.0 573 580 589 619 687 328.46 581 579 576.0 573.0 570 580 589 619 687 329.007 581 579 577.0 573.0 570 581 588 619 685 329.554 581 580 577.0 573.0 570 590 588 620 685 330.101 581 580 577.0 573.0 573 609 587 620 681 330.648 581 580 577.0 573.0 575 671 587 620 681 331.195 581 580 578.0 573.0 576 671 587 620 680 331.741 581 581 578.0 573.0 576 671 588 620 680 332.287 581 581 578.0 573.0 576 601 588 620 680 332.834 581 584 578.0 573.0 577 601 588 620 683 333.38 581 584 578.0 573.0 577 580 588 622 683 333.926 581 584 578.0 573.0 577 580 587 622 683 334.472 581 583 578.0 573.0 577 580 587 622 682 335.017 582 581 576.0 573.0 577 580 587 618 682 335.563 582 581 576.0 573.0 575 580 591 618 682 336.108 582 581 576.0 573.0 572 580 591 618 682 336.654 583 581 576.0 573.0 572 579 591 617 683 337.199 583 580 576.0 573.0 572 579 589 617 685 337.744 583 580 577.0 573.0 572 577 589 619 685 338.289 583 580 577.0 573.0 573 577 589 619 685 338.834 583 580 577.0 572.0 575 575 589 619 681 339.378 583 579 576.0 572.0 575 575 589 619 681 339.923 583 579 576.0 572.0 578 575 595 618 681 340.467 583 581 576.0 572.0 578 576 595 618 681 341.012 583 581 576.0 572.0 578 577 587 618 679 341.556 583 581 576.0 572.0 576 580 587 618 679 342.1 583 581 576.0 572.0 576 582 591 618 679 342.644 583 581 576.0 572.0 576 582 591 621 679 343.188 583 581 576.0 572.0 576 582 591 621 679 343.731 583 581 576.0 572.0 577 581 591 615 679 344.275 583 581 576.0 572.0 577 581 591 615 679 344.818 583 581 576.0 572.0 577 580 593 614 679 345.362 583 581 576.0 572.0 574 580 593 614 679 345.905 583 581 576.0 572.0 573 578 593 614 680 346.448 583 581 576.0 572.0 573 578 593 618 680 346.991 583 578 576.0 572.0 573 578 593 618 680 347.534 582 578 576.0 572.0 573 578 593 619 679 348.076 582 578 576.0 572.0 573 578 590 619 679 348.619 582 578 576.0 572.0 573 579 589 619 679 349.161 583 578 576.0 572.0 573 580 589 619 679 349.704 583 576 576.0 572.0 573 580 589 619 681 350.246 583 576 576.0 575.0 577 580 594 619 682 350.788 583 576 576.0 575.0 577 580 594 619 682 351.33 584 576 576.0 575.0 577 580 594 619 686 351.872 584 576 576.0 575.0 577 578 594 619 688 352.414 584 580 576.0 575.0 574 578 593 618 688 352.955 583 580 576.0 575.0 574 579 591 618 688 353.497 583 580 576.0 575.0 574 580 591 618 681 354.038 583 579 576.0 575.0 574 580 591 618 681 354.579 583 575 576.0 575.0 574 581 591 618 681 355.12 583 575 576.0 575.0 574 581 591 618 681 355.661 583 575 576.0 575.0 573 581 591 619 681 356.202 583 575 575.0 575.0 573 581 591 621 683 356.743 583 575 575.0 575.0 573 579 591 622 683 357.284 583 576 575.0 575.0 573 578 591 622 683 357.824 583 576 576.0 575.0 573 578 591 622 683 358.364 584 578 576.0 575.0 573 578 591 622 683 358.905 584 578 576.0 575.0 573 578 591 621 685 359.445 584 582 576.0 575.0 573 578 590 620 685 359.985 584 582 576.0 575.0 573 578 589 620 685 360.525 583 582 576.0 575.0 572 578 589 620 677 361.065 583 582 576.0 575.0 572 576 589 620 677 361.604 583 582 576.0 575.0 572 576 595 620 677 362.144 583 581 576.0 575.0 574 578 595 620 677 362.683 583 581 576.0 575.0 574 578 595 620 679 363.223 583 580 576.0 575.0 574 578 594 618 679 363.762 583 580 577.0 575.0 575 578 594 618 679 364.301 583 580 577.0 575.0 575 580 594 618 684 364.84 583 580 578.0 575.0 576 581 594 618 685 365.379 584 580 578.0 575.0 576 581 591 620 685 365.917 584 580 578.0 575.0 576 581 591 620 685 366.456 584 581 578.0 575.0 576 580 591 620 685 366.995 584 581 578.0 576.0 576 578 591 619 685 367.533 584 581 579.0 576.0 576 577 593 619 686 368.071 584 581 579.0 576.0 576 577 595 619 686 368.609 584 581 579.0 576.0 576 579 595 619 686 369.147 586 581 579.0 576.0 576 580 595 621 686 369.685 586 581 579.0 576.0 575 581 595 625 686 370.223 586 583 579.0 576.0 575 581 595 625 686 370.761 586 583 579.0 576.0 575 581 595 621 686 371.298 588 583 579.0 576.0 575 580 595 619 685 371.836 588 581 580.0 576.0 577 580 595 619 685 372.373 588 579 580.0 576.0 577 580 595 617 685 372.91 588 579 581.0 576.0 577 580 595 617 685 373.447 589 581 581.0 576.0 577 580 592 617 685 373.984 589 583 581.0 577.0 577 581 592 617 685 374.521 589 585 581.0 577.0 577 582 593 622 685 375.058 589 585 582.0 578.0 579 582 593 627 685 375.595 589 586 582.0 578.0 579 582 593 627 686 376.131 590 587 582.0 579.0 579 582 590 625 686 376.668 590 587 583.0 579.0 579 582 590 625 686 377.204 590 587 583.0 579.0 579 582 590 625 687 377.74 590 587 583.0 579.0 579 584 590 618 687 378.276 590 587 583.0 580.0 579 584 592 618 687 378.812 593 587 583.0 580.0 582 584 593 617 687 379.348 593 587 583.0 580.0 582 580 593 619 687 379.884 593 587 583.0 580.0 582 580 593 620 689 380.419 593 587 583.0 580.0 581 580 593 622 689 380.955 593 588 584.0 580.0 579 581 593 624 689 381.49 593 588 584.0 580.0 578 581 592 624 689 382.026 594 588 584.0 580.0 578 581 590 625 689 382.561 594 585 584.0 580.0 578 581 590 626 689 383.096 594 585 584.0 580.0 578 581 596 626 688 383.631 595 585 584.0 580.0 579 581 596 626 683 384.166 595 585 584.0 580.0 580 581 596 622 683 384.7 595 585 584.0 580.0 580 581 596 622 683 385.235 595 588 584.0 581.0 580 581 595 622 683 385.77 596 588 584.0 581.0 580 581 595 622 683 386.304 596 588 584.0 581.0 582 581 595 622 686 386.838 596 588 584.0 581.0 582 581 595 622 686 387.372 597 588 585.0 581.0 582 582 594 622 689 387.907 597 588 585.0 581.0 581 582 594 622 690 388.441 598 588 585.0 581.0 581 580 594 622 690 388.974 598 588 585.0 581.0 581 580 592 623 690 389.508 599 588 585.0 581.0 581 580 592 623 690 390.042 599 589 586.0 581.0 581 582 598 623 690 390.575 599 590 586.0 581.0 582 584 598 627 687 391.109 600 590 586.0 581.0 582 586 598 627 687 391.642 601 590 585.0 581.0 582 586 598 627 689 392.175 601 590 585.0 581.0 581 586 598 627 689 392.708 601 590 585.0 582.0 579 583 598 626 692 393.241 601 591 585.0 582.0 579 582 598 626 692 393.774 601 591 585.0 582.0 578 582 597 626 692 394.307 601 591 585.0 582.0 578 582 597 626 692 394.84 601 591 585.0 582.0 578 584 597 626 692 395.372 601 591 586.0 582.0 577 584 595 623 691 395.905 602 591 586.0 582.0 577 584 594 623 689 396.437 602 591 586.0 582.0 577 587 594 623 689 396.969 603 591 586.0 582.0 580 587 593 623 691 397.501 603 591 586.0 582.0 581 587 593 623 691 398.033 603 591 585.0 582.0 582 583 592 623 691 398.565 603 591 585.0 582.0 582 583 592 623 691 399.097 603 591 585.0 581.0 582 583 592 623 691 399.629 603 591 585.0 581.0 580 581 594 623 693 400.16 603 591 585.0 581.0 580 581 594 623 693 400.692 603 591 585.0 581.0 580 583 594 624 693 401.223 603 591 585.0 581.0 580 583 594 624 693 401.755 603 591 585.0 580.0 580 583 594 625 693 402.286 603 591 585.0 580.0 580 583 596 625 695 402.817 603 591 585.0 580.0 580 583 596 625 698 403.348 603 590 585.0 579.0 580 583 596 625 698 403.879 603 590 585.0 579.0 579 583 596 625 698 404.409 603 590 585.0 579.0 579 583 596 625 697 404.94 603 590 585.0 579.0 579 583 596 625 695 405.471 603 590 585.0 579.0 579 583 593 625 695 406.001 603 590 585.0 579.0 579 585 593 625 695 406.531 603 589 585.0 579.0 579 585 593 625 695 407.062 603 589 584.0 579.0 579 581 603 625 694 407.592 603 589 584.0 579.0 579 581 603 622 694 408.122 603 586 584.0 579.0 578 581 598 622 694 408.652 603 586 584.0 579.0 578 581 598 622 696 409.181 603 586 584.0 580.0 578 581 598 622 696 409.711 603 587 584.0 580.0 578 581 595 622 696 410.241 603 589 584.0 580.0 576 581 595 622 694 410.77 603 589 584.0 580.0 576 581 595 622 694 411.3 603 589 584.0 580.0 576 580 595 622 694 411.829 603 589 584.0 580.0 579 580 593 622 694 412.358 603 589 584.0 580.0 579 579 593 622 695 412.887 602 589 584.0 580.0 579 579 594 622 695 413.416 602 589 584.0 580.0 576 579 594 625 695 413.945 602 589 584.0 581.0 576 579 594 628 695 414.474 602 590 584.0 581.0 576 579 594 628 695 415.003 602 590 584.0 581.0 576 582 594 628 690 415.531 602 590 584.0 581.0 578 582 595 628 690 416.06 602 590 584.0 580.0 578 582 598 628 697 416.588 601 590 583.0 580.0 578 582 598 628 697 417.117 601 590 583.0 580.0 578 582 598 627 697 417.645 601 590 581.0 580.0 578 582 597 627 697 418.173 601 590 581.0 580.0 578 581 597 627 698 418.701 601 589 581.0 579.0 578 581 597 627 698 419.229 601 589 581.0 579.0 576 581 597 627 699 419.757 601 589 581.0 578.0 576 584 597 627 699 420.284 601 589 581.0 578.0 580 584 596 627 699 420.812 601 587 581.0 578.0 580 584 596 627 699 421.34 601 587 581.0 578.0 579 584 596 628 699 421.867 601 587 581.0 578.0 577 581 596 628 696 422.394 601 587 581.0 578.0 577 581 596 628 696 422.921 601 587 581.0 578.0 577 581 595 629 696 423.449 601 587 581.0 577.0 576 583 595 629 696 423.976 601 586 581.0 577.0 576 583 595 629 696 424.503 601 586 581.0 577.0 576 586 595 629 702 425.029 601 586 580.0 577.0 576 586 594 629 702 425.556 601 587 580.0 577.0 576 586 594 631 702 426.083 601 587 580.0 575.0 576 584 594 631 702 426.609 601 587 579.0 575.0 576 583 594 626 701 427.136 601 587 578.0 574.0 576 583 594 626 701 427.662 601 587 578.0 574.0 576 583 595 626 701 428.188 601 587 578.0 574.0 576 583 594 626 701 428.714 598 587 578.0 574.0 576 583 592 630 701 429.24 597 587 578.0 574.0 573 581 592 630 701 429.766 597 585 578.0 574.0 573 581 592 626 701 430.292 597 585 578.0 574.0 573 581 592 624 699 430.818 597 585 578.0 575.0 573 579 594 624 697 431.344 597 586 578.0 575.0 573 579 594 624 697 431.869 597 586 578.0 575.0 577 579 594 625 697 432.395 597 586 578.0 575.0 577 579 594 625 697 432.92 597 586 578.0 574.0 577 579 597 625 697 433.445 596 585 578.0 574.0 577 579 597 625 697 433.971 596 585 578.0 574.0 577 579 597 625 698 434.496 596 585 577.0 574.0 575 580 594 625 698 435.021 595 585 577.0 574.0 573 580 592 625 698 435.546 595 584 577.0 574.0 574 580 592 625 698 436.071 595 581 577.0 574.0 574 580 592 628 698 436.595 595 581 577.0 575.0 574 580 592 628 704 437.12 595 581 577.0 575.0 574 582 596 628 704 437.644 595 581 577.0 575.0 574 582 596 628 704 438.169 595 581 578.0 575.0 574 582 596 625 704 438.693 595 581 578.0 575.0 574 582 594 625 704 439.218 595 581 578.0 575.0 574 584 594 633 704 439.742 595 581 578.0 575.0 574 584 594 633 704 440.266 595 581 578.0 575.0 574 584 594 633 700 440.79 595 581 578.0 575.0 576 578 594 628 700 441.314 595 582 578.0 575.0 576 576 594 628 700 441.837 594 585 577.0 575.0 576 576 594 628 700 442.361 593 585 577.0 573.0 576 576 594 628 700 442.885 593 585 577.0 573.0 576 576 594 628 698 443.408 593 582 578.0 573.0 575 580 594 628 698 443.932 593 582 578.0 573.0 575 580 595 631 698 444.455 593 582 578.0 574.0 575 580 595 631 700 444.978 593 583 578.0 574.0 575 577 596 629 703 445.502 593 583 578.0 574.0 575 577 596 626 703 446.025 593 583 578.0 574.0 576 577 598 626 706 446.548 593 583 578.0 574.0 576 577 598 626 706 447.071 593 585 578.0 574.0 574 578 596 626 706 447.593 593 585 578.0 573.0 574 580 594 626 706 448.116 593 585 576.0 573.0 574 582 594 626 710 448.639 593 585 576.0 573.0 574 582 594 626 710 449.161 593 580 576.0 573.0 573 580 594 626 706 449.684 593 580 576.0 573.0 572 579 594 626 706 450.206 593 580 575.0 573.0 572 579 594 626 706 450.728 593 580 575.0 572.0 572 580 595 625 706 451.251 593 580 575.0 572.0 572 581 600 625 705 451.773 593 580 575.0 572.0 572 581 600 625 704 452.295 593 579 575.0 572.0 571 581 596 627 704 452.817 593 579 575.0 572.0 571 581 595 629 704 453.338 593 579 575.0 572.0 571 580 594 631 704 453.86 593 580 574.0 572.0 571 580 593 633 704 454.382 593 580 574.0 572.0 571 580 591 633 704 454.903 593 580 574.0 572.0 573 579 591 636 710 455.425 593 581 575.0 572.0 573 579 592 636 710 455.946 591 581 575.0 572.0 573 579 593 637 704 456.468 591 581 575.0 572.0 573 579 593 635 703 456.989 591 581 575.0 572.0 573 579 593 633 703 457.51 590 581 575.0 572.0 573 579 593 633 703 458.031 590 580 575.0 572.0 574 579 593 630 703 458.552 590 580 575.0 572.0 574 579 593 625 703 459.073 590 580 575.0 572.0 574 579 593 625 705 459.594 590 582 575.0 572.0 574 578 593 625 705 460.114 590 582 575.0 572.0 574 577 592 625 705 460.635 590 582 575.0 572.0 574 577 592 625 712 461.156 590 581 575.0 572.0 575 577 592 625 712 461.676 590 580 575.0 572.0 576 577 592 625 712 462.196 590 580 575.0 572.0 576 576 593 630 711 462.717 590 580 575.0 572.0 576 576 593 631 711 463.237 590 580 575.0 572.0 576 579 596 631 706 463.757 589 580 575.0 572.0 576 579 596 631 706 464.277 589 580 575.0 572.0 570 582 595 631 709 464.797 589 580 575.0 573.0 570 582 595 631 709 465.317 589 580 575.0 573.0 570 582 595 631 706 465.837 589 581 575.0 573.0 576 580 595 630 706 466.356 589 581 575.0 573.0 576 580 595 630 709 466.876 589 582 575.0 573.0 576 580 594 631 709 467.396 589 582 575.0 573.0 576 580 594 631 707 467.915 589 582 575.0 573.0 576 580 594 631 707 468.434 589 582 575.0 573.0 576 580 597 631 709 468.954 589 578 573.0 573.0 576 579 597 631 709 469.473 588 576 573.0 573.0 576 579 597 631 709 469.992 588 576 573.0 573.0 572 579 596 628 709 470.511 588 576 573.0 573.0 570 579 596 628 709 471.03 588 576 573.0 573.0 570 581 596 628 709 471.549 588 575 573.0 573.0 570 581 594 631 709 472.068 589 575 573.0 573.0 570 581 593 635 709 472.586 589 575 573.0 573.0 574 581 593 635 709 473.105 589 575 573.0 572.0 574 581 593 633 709 473.624 588 579 573.0 572.0 574 580 594 631 709 474.142 588 581 573.0 572.0 574 577 594 629 709 474.661 588 581 573.0 572.0 573 577 594 628 709 475.179 588 579 573.0 572.0 573 577 594 628 709 475.697 588 574 573.0 572.0 573 577 595 628 705 476.215 588 574 573.0 572.0 574 582 596 628 705 476.733 588 574 573.0 572.0 575 582 596 628 706 477.251 587 578 573.0 572.0 575 582 596 628 709 477.769 587 579 573.0 572.0 575 579 596 628 710 478.287 587 581 573.0 571.0 575 579 596 632 711 478.805 587 581 573.0 571.0 573 579 597 632 711 479.323 587 580 573.0 571.0 573 579 597 635 711 479.84 587 580 574.0 571.0 573 579 597 635 711 480.358 587 580 574.0 571.0 573 579 597 635 711 480.875 587 578 574.0 571.0 573 579 596 631 711 481.393 587 578 574.0 571.0 574 579 596 631 711 481.91 587 577 574.0 571.0 574 579 596 630 707 482.427 587 577 574.0 571.0 574 579 596 630 707 482.944 587 577 574.0 571.0 569 579 596 630 714 483.461 587 577 574.0 571.0 569 579 595 630 715 483.978 587 576 574.0 571.0 569 579 593 630 715 484.495 587 576 574.0 571.0 569 579 593 630 715 485.012 587 579 574.0 571.0 569 579 593 636 715 485.529 587 579 574.0 571.0 569 579 593 638 715 486.045 587 579 574.0 571.0 573 579 593 638 714 486.562 587 578 574.0 571.0 575 580 594 638 714 487.079 587 578 574.0 571.0 576 581 596 638 714 487.595 587 578 574.0 571.0 576 583 596 635 714 488.111 587 578 574.0 571.0 576 583 596 635 715 488.628 587 578 574.0 571.0 576 578 596 634 715 489.144 587 578 574.0 571.0 572 578 596 634 715 489.66 587 578 574.0 571.0 572 582 596 634 717 490.176 587 578 574.0 571.0 572 582 596 634 717 490.692 587 578 574.0 571.0 572 582 596 634 717 491.208 587 578 574.0 571.0 572 582 594 636 716 491.724 587 577 574.0 571.0 572 582 594 636 716 492.24 587 577 574.0 571.0 575 582 594 633 716 492.755 588 577 574.0 571.0 575 581 594 633 716 493.271 588 577 574.0 570.0 575 581 597 635 716 493.787 589 574 574.0 570.0 575 581 597 635 716 494.302 589 574 574.0 570.0 575 581 597 635 716 494.817 589 583 574.0 570.0 575 581 597 635 716 495.333 589 583 574.0 570.0 575 580 597 636 716 495.848 590 580 574.0 570.0 575 580 597 637 716 496.363 590 580 574.0 570.0 574 580 598 637 716 496.878 590 580 574.0 570.0 574 579 598 637 716 497.393 590 580 574.0 570.0 574 578 598 637 715 497.908 590 577 574.0 570.0 574 578 598 634 715 498.423 590 577 574.0 570.0 574 578 598 634 715 498.938 591 577 574.0 570.0 574 578 598 634 716 499.453 591 578 574.0 570.0 574 578 597 637 719 499.968 591 580 574.0 570.0 574 579 596 637 719 500.482 591 581 574.0 570.0 574 579 596 637 717 500.997 592 581 575.0 570.0 574 579 596 636 717 501.511 592 582 575.0 571.0 574 579 598 636 717 502.026 592 582 575.0 571.0 574 579 598 636 717 502.54 592 584 575.0 571.0 574 580 598 636 723 503.054 592 586 576.0 571.0 573 580 598 636 724 503.568 592 586 576.0 571.0 572 580 598 636 735 504.083 593 584 576.0 571.0 572 580 596 636 735 504.597 593 582 576.0 571.0 574 584 594 635 722 505.111 593 582 576.0 571.0 574 584 594 635 722 505.625 593 583 576.0 571.0 574 584 597 635 722 506.138 593 583 576.0 572.0 572 584 597 635 722 506.652 593 583 575.0 572.0 572 583 597 635 725 507.166 593 583 575.0 573.0 572 582 597 636 726 507.679 595 583 575.0 574.0 572 582 597 638 726 508.193 595 583 576.0 574.0 572 582 598 638 726 508.707 595 583 576.0 574.0 572 585 598 638 724 509.22 595 583 576.0 574.0 572 585 598 638 722 509.733 596 583 576.0 574.0 574 585 598 638 722 510.247 596 583 576.0 574.0 574 585 598 634 722 510.76 596 583 576.0 574.0 574 585 598 631 728 511.273 598 584 576.0 574.0 574 583 597 631 729 511.786 598 586 576.0 573.0 575 581 597 639 729 512.299 598 586 576.0 571.0 575 581 597 639 729 512.812 598 586 576.0 571.0 576 581 597 639 729 513.325 598 586 576.0 571.0 576 581 597 639 729 513.838 598 586 576.0 571.0 576 582 597 639 729 514.351 598 586 576.0 571.0 576 582 597 639 729 514.863 600 586 577.0 571.0 572 580 597 641 729 515.376 600 586 577.0 572.0 572 580 598 641 730 515.889 600 586 578.0 572.0 572 580 598 641 733 516.401 601 586 578.0 572.0 574 580 598 641 733 516.913 601 586 579.0 571.0 574 579 598 641 733 517.426 602 587 579.0 571.0 574 579 600 644 733 517.938 602 587 579.0 570.0 575 579 600 644 733 518.45 602 587 579.0 570.0 575 580 597 644 733 518.963 602 590 579.0 570.0 575 581 597 644 732 519.475 602 590 579.0 570.0 577 581 597 642 732 519.987 602 590 579.0 570.0 577 581 597 641 732 520.499 603 591 579.0 570.0 577 581 597 641 732 521.011 603 591 579.0 571.0 577 581 597 641 731 521.522 604 591 579.0 571.0 575 581 597 641 731 522.034 605 591 579.0 571.0 575 581 600 642 731 522.546 605 591 579.0 572.0 575 581 602 642 731 523.058 606 591 579.0 572.0 573 581 602 642 731 523.569 606 591 579.0 572.0 573 581 600 642 731 524.081 607 592 579.0 572.0 573 582 600 638 733 524.592 607 592 579.0 572.0 573 582 600 637 733 525.104 607 592 579.0 572.0 576 583 600 637 733 525.615 608 592 579.0 571.0 576 583 600 640 733 526.126 608 592 579.0 571.0 576 581 600 647 734 526.637 608 592 580.0 571.0 576 581 600 647 737 527.149 608 592 580.0 571.0 574 583 600 647 737 527.66 609 593 580.0 572.0 574 583 600 647 737 528.171 609 593 580.0 572.0 574 583 600 640 737 528.682 609 595 580.0 573.0 575 583 600 640 732 529.193 609 595 581.0 573.0 575 583 601 640 732 529.704 609 596 581.0 573.0 575 583 602 640 732 530.214 609 596 581.0 573.0 575 583 602 642 732 530.725 611 596 581.0 573.0 575 583 602 645 735 531.236 611 596 581.0 573.0 575 582 602 645 745 531.746 613 596 582.0 573.0 578 582 599 645 745 532.257 613 597 582.0 573.0 578 582 599 645 747 532.767 614 597 582.0 573.0 578 582 599 645 747 533.278 615 597 583.0 573.0 578 582 604 645 747 533.788 615 597 583.0 573.0 576 579 604 643 740 534.298 615 598 583.0 573.0 576 579 604 643 740 534.809 615 599 583.0 573.0 576 579 603 643 740 535.319 615 600 583.0 573.0 574 581 603 644 740 535.829 615 600 582.0 573.0 574 582 603 644 750 536.339 615 600 582.0 573.0 574 583 603 645 750 536.849 615 600 582.0 573.0 574 583 603 645 750 537.359 615 600 582.0 573.0 575 583 603 645 747 537.869 615 600 582.0 574.0 582 582 603 645 747 538.379 616 600 582.0 574.0 582 582 603 651 746 538.889 616 601 583.0 574.0 582 582 603 653 746 539.398 616 601 583.0 574.0 574 582 603 653 746 539.908 616 603 583.0 574.0 572 582 603 646 746 540.418 616 603 584.0 574.0 572 582 603 646 736 540.927 617 603 584.0 574.0 574 584 600 646 736 541.437 617 603 584.0 575.0 574 584 600 646 739 541.946 617 603 586.0 575.0 576 582 600 646 744 542.456 617 604 586.0 575.0 576 582 601 648 744 542.965 617 604 586.0 575.0 576 581 605 650 745 543.474 617 604 586.0 576.0 576 581 605 650 745 543.983 618 604 587.0 576.0 576 580 605 650 746 544.493 618 604 587.0 576.0 576 580 607 650 748 545.002 618 605 587.0 576.0 576 580 607 650 753 545.511 618 605 587.0 576.0 576 583 607 650 753 546.02 618 605 587.0 576.0 576 584 607 652 749 546.529 619 607 587.0 576.0 574 584 607 654 747 547.038 619 607 587.0 576.0 572 586 606 654 744 547.546 620 607 587.0 576.0 572 586 606 654 743 548.055 621 608 587.0 576.0 573 586 606 652 743 548.564 621 609 588.0 576.0 577 588 606 652 746 549.073 621 609 589.0 576.0 577 588 606 651 751 549.581 621 609 589.0 577.0 577 592 606 651 751 550.09 621 609 589.0 577.0 577 592 607 651 753 550.598 621 610 589.0 577.0 578 592 607 655 753 551.107 621 610 590.0 577.0 579 586 607 655 755 551.615 623 610 590.0 577.0 579 585 607 655 755 552.123 623 610 590.0 577.0 579 585 606 655 755 552.632 623 611 590.0 577.0 579 587 606 650 755 553.14 623 612 590.0 577.0 580 590 606 650 755 553.648 624 612 591.0 577.0 580 591 607 650 755 554.156 624 612 591.0 577.0 580 591 607 650 755 554.664 624 612 591.0 577.0 580 590 607 650 755 555.172 625 612 591.0 578.0 581 589 607 653 760 555.68 625 613 591.0 578.0 581 589 607 653 760 556.188 625 613 592.0 579.0 581 587 607 653 760 556.696 625 613 592.0 579.0 581 587 605 653 757 557.204 625 613 593.0 579.0 581 583 605 653 757 557.712 625 613 593.0 580.0 580 582 605 653 762 558.22 626 614 593.0 580.0 580 584 605 653 762 558.727 626 615 593.0 580.0 580 588 607 653 762 559.235 626 615 593.0 580.0 580 590 607 653 762 559.742 626 615 593.0 580.0 580 590 607 654 762 560.25 626 615 593.0 580.0 580 593 607 654 762 560.757 626 615 593.0 583.0 580 593 608 655 760 561.265 627 615 595.0 583.0 580 593 608 655 760 561.772 628 616 595.0 583.0 574 587 608 655 760 562.28 628 616 595.0 583.0 574 587 609 655 760 562.787 628 616 595.0 583.0 581 587 609 658 760 563.294 628 616 595.0 583.0 581 588 611 658 760 563.801 628 617 595.0 583.0 581 588 612 658 760 564.308 628 617 595.0 583.0 581 588 612 658 759 564.815 628 617 595.0 583.0 581 587 612 661 759 565.323 628 619 595.0 583.0 582 587 607 667 759 565.83 628 620 595.0 583.0 584 587 607 667 763 566.336 629 620 595.0 583.0 584 587 607 662 765 566.843 629 622 595.0 583.0 581 587 608 655 766 567.35 629 622 596.0 583.0 581 587 609 655 766 567.857 631 623 597.0 583.0 581 588 609 655 766 568.364 631 623 597.0 583.0 581 590 609 655 766 568.87 631 623 597.0 583.0 581 590 609 660 766 569.377 631 624 597.0 583.0 581 590 609 661 766 569.884 631 624 598.0 583.0 579 590 609 661 766 570.39 631 624 598.0 583.0 579 590 609 661 766 570.897 631 624 598.0 583.0 583 590 609 661 774 571.403 631 624 598.0 583.0 583 592 609 660 774 571.91 631 625 598.0 583.0 583 592 609 660 774 572.416 631 625 598.0 583.0 583 592 609 660 774 572.922 631 625 599.0 583.0 583 592 610 659 774 573.429 630 625 599.0 583.0 583 592 610 659 774 573.935 630 626 599.0 583.0 583 592 610 659 772 574.441 630 626 599.0 583.0 583 592 610 659 772 574.947 630 626 599.0 583.0 583 591 610 659 772 575.453 629 626 599.0 583.0 583 589 613 664 772 575.959 629 627 600.0 583.0 587 589 613 664 772 576.465 629 627 600.0 583.0 587 589 613 664 772 576.971 629 627 600.0 583.0 587 592 613 664 772 577.477 629 628 600.0 583.0 587 592 614 663 776 577.983 629 628 600.0 584.0 586 594 614 663 776 578.489 629 628 600.0 584.0 586 594 614 663 776 578.995 629 628 600.0 584.0 585 592 614 663 776 579.501 629 628 600.0 584.0 585 592 614 661 780 580.006 629 628 601.0 584.0 582 592 615 661 780 580.512 629 628 602.0 584.0 582 592 615 661 780 581.018 629 628 602.0 584.0 582 593 615 673 778 581.523 629 629 603.0 584.0 585 594 615 675 776 582.029 629 629 603.0 584.0 585 594 615 672 776 582.534 629 629 603.0 584.0 585 594 615 666 776 583.04 629 630 603.0 584.0 585 594 614 666 776 583.545 630 630 602.0 584.0 585 594 613 666 780 584.05 630 630 602.0 584.0 585 594 613 666 780 584.556 630 630 602.0 584.0 588 594 615 666 780 585.061 630 630 602.0 585.0 588 594 617 666 786 585.566 630 631 603.0 585.0 588 594 620 666 787 586.071 630 631 604.0 585.0 588 601 620 666 787 586.577 630 631 604.0 585.0 586 602 618 666 794 587.082 630 632 605.0 585.0 584 602 616 666 795 587.587 630 632 605.0 585.0 584 602 614 669 795 588.092 631 632 605.0 585.0 586 599 614 669 795 588.597 631 632 605.0 585.0 587 599 617 669 788 589.102 631 632 605.0 585.0 587 599 622 671 788 589.607 631 633 606.0 585.0 587 599 622 671 788 590.112 631 633 606.0 585.0 587 596 618 671 788 590.616 631 634 606.0 586.0 587 596 616 671 788 591.121 631 635 607.0 586.0 587 596 616 675 788 591.626 631 635 607.0 586.0 587 601 616 675 794 592.131 631 635 607.0 586.0 587 601 617 675 798 592.635 631 636 607.0 586.0 587 601 618 675 798 593.14 631 636 608.0 587.0 588 601 618 669 806 593.645 631 636 608.0 587.0 589 597 620 669 806 594.149 631 636 608.0 587.0 589 597 620 669 806 594.654 631 637 609.0 587.0 589 596 623 669 805 595.158 633 638 609.0 587.0 589 596 623 673 796 595.663 633 638 609.0 587.0 589 596 623 676 796 596.167 633 638 609.0 587.0 593 601 623 677 796 596.672 633 639 609.0 587.0 593 601 623 677 798 597.176 633 639 609.0 587.0 586 601 623 677 800 597.68 633 640 610.0 587.0 586 600 624 677 801 598.185 633 640 610.0 587.0 586 599 698 677 801 598.689 633 640 610.0 587.0 586 599 803 677 801 599.193 633 640 610.0 587.0 586 602 859 679 799 599.697 632 640 610.0 587.0 586 605 747 681 799 600.201 632 640 610.0 587.0 587 605 635 681 799 600.705 632 641 610.0 587.0 587 605 635 681 806 601.209 632 642 610.0 587.0 587 605 623 681 809 601.713 632 642 611.0 587.0 587 604 623 680 809 602.217 632 642 611.0 587.0 587 603 623 679 809 602.721 632 642 611.0 587.0 589 603 623 679 813 603.225 632 642 611.0 587.0 589 603 624 679 813 603.729 631 642 611.0 587.0 589 603 626 679 813 604.233 631 642 611.0 587.0 589 606 626 679 815 604.737 631 642 611.0 587.0 590 608 626 679 815 605.241 631 642 611.0 587.0 591 608 626 679 815 605.744 631 642 611.0 587.0 592 608 624 680 812 606.248 631 643 611.0 587.0 592 606 621 683 812 606.752 631 643 611.0 587.0 589 600 621 684 812 607.255 631 643 611.0 588.0 589 599 621 685 818 607.759 630 643 612.0 588.0 589 599 620 686 819 608.263 630 643 612.0 589.0 589 601 620 688 821 608.766 630 644 612.0 589.0 591 603 620 712 821 609.27 630 644 612.0 589.0 592 603 625 712 822 609.773 630 646 612.0 590.0 592 603 625 712 822 610.277 630 646 612.0 590.0 592 603 625 712 823 610.78 630 646 612.0 590.0 592 603 625 686 823 611.283 630 646 612.0 590.0 592 603 625 686 823 611.787 630 646 612.0 590.0 593 603 625 686 829 612.29 630 646 612.0 590.0 594 603 623 686 837 612.793 630 646 612.0 590.0 594 603 623 686 837 613.297 630 647 612.0 590.0 592 605 623 692 834 613.8 630 647 612.0 591.0 590 605 623 692 830 614.303 630 647 612.0 591.0 590 607 625 694 830 614.806 630 647 612.0 591.0 590 610 630 694 829 615.309 630 647 612.0 591.0 587 610 630 691 829 615.812 630 647 614.0 591.0 587 610 630 691 829 616.316 630 647 614.0 591.0 589 609 629 691 832 616.819 630 647 614.0 591.0 592 609 629 691 841 617.322 630 648 614.0 591.0 592 609 629 691 841 617.825 631 648 614.0 591.0 592 603 629 691 841 618.328 631 648 614.0 591.0 592 603 625 687 841 618.83 631 648 614.0 591.0 593 603 625 687 845 619.333 631 648 614.0 590.0 593 603 627 687 845 619.836 631 648 614.0 590.0 593 604 629 687 846 620.339 631 650 614.0 590.0 593 605 629 694 846 620.842 633 650 614.0 590.0 593 605 631 694 846 621.345 633 650 614.0 590.0 593 605 631 694 845 621.847 633 650 616.0 589.0 592 605 628 694 845 622.35 633 650 616.0 589.0 592 605 626 694 846 622.853 633 650 616.0 589.0 592 605 626 696 853 623.355 633 650 616.0 590.0 589 605 626 699 853 623.858 633 650 616.0 590.0 589 605 626 699 855 624.361 632 650 617.0 590.0 589 605 626 699 856 624.863 632 650 617.0 589.0 589 605 628 699 861 625.366 631 650 617.0 589.0 589 605 628 694 863 625.868 631 650 617.0 589.0 592 605 630 694 863 626.371 631 650 617.0 589.0 594 606 630 700 863 626.873 631 650 617.0 589.0 594 608 631 705 863 627.376 631 650 617.0 589.0 594 608 631 705 863 627.878 631 650 617.0 590.0 593 608 631 703 866 628.381 631 650 617.0 590.0 592 608 631 697 866 628.883 631 650 618.0 590.0 592 607 633 697 866 629.385 631 650 618.0 590.0 592 607 633 697 876 629.888 631 651 618.0 591.0 592 607 633 697 877 630.39 631 651 617.0 592.0 594 607 633 710 881 630.892 631 651 617.0 592.0 594 606 632 710 883 631.395 631 651 617.0 592.0 594 606 631 709 883 631.897 631 651 617.0 592.0 594 606 631 708 883 632.399 631 651 617.0 592.0 594 606 635 708 881 632.901 631 651 617.0 592.0 594 606 637 708 881 633.403 631 651 617.0 592.0 594 606 637 708 881 633.905 630 651 617.0 592.0 594 606 637 712 895 634.408 630 651 617.0 592.0 594 608 637 720 895 634.91 630 651 617.0 592.0 594 609 637 725 895 635.412 630 651 617.0 592.0 594 609 639 724 895 635.914 630 651 617.0 592.0 594 607 639 714 897 636.416 628 651 617.0 592.0 594 606 641 714 901 636.918 628 651 617.0 592.0 594 606 642 714 906 637.42 627 651 617.0 592.0 594 606 642 716 906 637.922 627 651 617.0 592.0 593 606 638 723 907 638.424 627 651 617.0 592.0 593 607 638 723 909 638.925 627 651 617.0 592.0 593 608 633 715 917 639.427 627 651 617.0 592.0 593 609 633 715 920 639.929 627 650 617.0 592.0 593 613 633 715 921 640.431 627 648 617.0 591.0 593 613 633 715 926 640.933 627 648 617.0 591.0 593 609 634 716 931 641.435 627 647 617.0 591.0 593 609 638 719 933 641.936 627 647 617.0 591.0 589 609 638 719 933 642.438 627 646 617.0 591.0 589 609 638 720 937 642.94 627 646 617.0 590.0 589 609 638 723 938 643.442 627 644 617.0 589.0 593 609 643 727 938 643.943 627 644 617.0 589.0 593 608 643 738 940 644.445 626 644 617.0 589.0 593 607 643 738 944 644.947 626 644 617.0 589.0 593 606 643 738 948 645.448 626 644 617.0 589.0 591 606 642 725 948 645.95 626 644 617.0 589.0 591 609 642 725 948 646.451 626 644 617.0 589.0 591 609 642 725 948 646.953 625 644 617.0 589.0 593 609 642 726 959 647.455 625 644 617.0 589.0 593 609 642 730 963 647.956 625 644 616.0 589.0 593 609 642 730 964 648.458 625 644 616.0 589.0 593 609 643 731 964 648.959 625 644 615.0 589.0 594 611 643 731 972 649.461 625 644 614.0 589.0 594 611 643 734 974 649.962 625 643 612.0 589.0 594 611 643 735 975 650.464 624 643 612.0 589.0 594 611 643 735 978 650.965 624 642 612.0 589.0 592 611 641 735 978 651.466 624 641 612.0 589.0 592 611 641 736 980 651.968 623 640 612.0 589.0 592 611 641 742 981 652.469 623 640 612.0 589.0 589 611 645 742 993 652.97 623 640 612.0 589.0 589 611 645 744 994 653.472 623 640 612.0 589.0 589 611 645 744 1002 653.973 623 639 611.0 589.0 589 611 645 744 1002 654.474 623 639 611.0 589.0 591 611 645 744 1005 654.976 622 638 610.0 589.0 591 611 645 748 1005 655.477 620 638 609.0 589.0 591 610 649 748 1008 655.978 620 635 609.0 589.0 591 610 649 748 1009 656.48 620 634 609.0 589.0 592 608 649 748 1011 656.981 619 634 609.0 589.0 592 608 649 748 1012 657.482 619 634 609.0 589.0 592 608 649 751 1023 657.983 619 634 609.0 588.0 592 608 649 751 1035 658.484 619 634 609.0 587.0 592 609 649 754 1039 658.985 619 633 609.0 587.0 592 609 649 757 1039 659.487 618 633 609.0 587.0 591 609 649 757 1044 659.988 618 633 608.0 586.0 591 609 651 763 1044 660.489 618 632 608.0 586.0 590 609 653 763 1054 660.99 618 632 608.0 586.0 590 609 653 763 1054 661.491 618 632 608.0 586.0 590 609 656 763 1063 661.992 618 629 608.0 586.0 590 610 662 763 1063 662.493 618 629 608.0 586.0 589 610 663 770 1063 662.994 618 629 608.0 586.0 589 610 662 770 1068 663.495 618 628 608.0 586.0 589 607 656 770 1069 663.996 617 628 606.0 586.0 589 607 656 772 1082 664.497 616 628 606.0 586.0 589 608 656 773 1085 664.998 616 628 606.0 586.0 595 608 656 780 1085 665.499 615 628 605.0 586.0 595 608 660 780 1085 666 615 628 605.0 586.0 593 608 660 780 1094 666.501 613 628 605.0 586.0 588 610 660 780 1105 667.002 613 627 605.0 586.0 588 613 662 781 1118 667.503 613 627 604.0 586.0 589 613 663 784 1128 668.004 613 627 604.0 586.0 589 616 663 793 1128 668.505 612 626 604.0 586.0 589 616 658 793 1134 669.006 611 625 604.0 586.0 589 616 654 797 1134 669.507 611 625 604.0 587.0 592 616 654 797 1135 670.008 611 625 604.0 587.0 592 614 654 797 1150 670.509 611 624 603.0 587.0 592 614 666 799 1155 671.009 611 624 603.0 587.0 592 614 666 799 1155 671.51 610 624 603.0 587.0 592 614 666 799 1165 672.011 610 624 603.0 587.0 592 610 662 800 1169 672.512 610 621 603.0 587.0 593 610 662 810 1169 673.013 610 621 602.0 587.0 593 610 662 811 1170 673.514 609 620 602.0 587.0 593 614 662 811 1198 674.014 609 620 602.0 587.0 592 614 662 811 1206 674.515 609 619 602.0 587.0 590 614 662 813 1206 675.016 608 619 602.0 587.0 590 614 667 819 1205 675.517 608 619 603.0 585.0 589 615 667 822 1205 676.018 608 619 603.0 585.0 589 615 667 825 1205 676.518 608 619 603.0 585.0 585 615 667 831 1232 677.019 608 619 603.0 585.0 585 615 670 836 1232 677.52 608 619 602.0 585.0 585 615 670 851 1232 678.02 608 619 602.0 585.0 591 615 670 851 1241 678.521 608 619 601.0 585.0 591 613 670 832 1241 679.022 608 619 599.0 584.0 591 612 673 832 1249 679.523 608 618 599.0 584.0 591 612 675 852 1267 680.023 608 618 599.0 583.0 591 612 676 852 1269 680.524 608 617 598.0 582.0 591 612 676 852 1274 681.025 607 617 597.0 582.0 589 615 676 852 1286 681.525 606 617 597.0 582.0 588 615 676 852 1288 682.026 606 616 597.0 582.0 588 615 676 855 1315 682.527 604 616 598.0 582.0 588 614 676 855 1315 683.027 604 616 598.0 582.0 588 616 679 856 1326 683.528 603 615 598.0 582.0 588 616 679 862 1326 684.029 603 614 597.0 582.0 588 620 681 863 1341 684.529 603 614 597.0 582.0 588 620 686 865 1342 685.03 603 614 596.0 582.0 590 621 686 867 1347 685.531 603 614 596.0 583.0 592 620 686 873 1354 686.031 603 613 594.0 584.0 592 620 686 878 1356 686.532 602 612 594.0 584.0 592 620 686 879 1366 687.032 602 612 594.0 584.0 592 620 691 880 1374 687.533 602 611 594.0 584.0 591 621 691 884 1408 688.034 602 611 594.0 584.0 587 621 691 896 1408 688.534 602 611 594.0 584.0 587 621 688 896 1419 689.035 602 611 594.0 584.0 587 621 688 898 1420 689.536 602 611 593.0 584.0 587 620 688 910 1426 690.036 602 610 593.0 584.0 588 619 693 911 1450 690.537 602 610 593.0 585.0 589 619 693 918 1450 691.037 601 610 593.0 585.0 589 619 699 922 1456 691.538 601 610 593.0 585.0 589 619 699 932 1456 692.038 599 608 593.0 585.0 589 619 699 941 1479 692.539 599 608 593.0 585.0 589 621 699 941 1488 693.04 598 607 593.0 585.0 589 621 700 941 1494 693.54 596 607 592.0 585.0 589 623 703 941 1502 694.041 596 607 592.0 585.0 588 623 706 941 1513 694.541 596 605 591.0 585.0 588 624 708 941 1523 695.042 596 605 591.0 585.0 588 624 712 942 1543 695.542 596 605 591.0 584.0 588 624 712 944 1545 696.043 596 604 591.0 583.0 589 624 713 953 1545 696.544 596 603 590.0 582.0 590 624 713 953 1556 697.044 596 603 590.0 582.0 590 624 717 956 1569 697.545 595 602 590.0 582.0 590 624 717 962 1592 698.045 595 601 590.0 581.0 590 625 718 968 1593 698.546 595 601 590.0 581.0 591 625 718 972 1604 699.046 594 601 590.0 581.0 591 625 718 973 1631 699.547 594 600 590.0 581.0 591 625 721 975 1639 700.047 594 600 588.0 581.0 591 624 732 983 1660 700.548 593 600 588.0 581.0 591 624 732 985 1665 701.049 593 600 588.0 580.0 591 624 732 987 1678 701.549 593 600 588.0 580.0 591 624 732 995 1691 702.05 593 600 588.0 580.0 591 625 733 995 1701 702.55 593 599 588.0 580.0 591 625 733 1002 1739 703.051 593 598 588.0 580.0 591 625 733 1009 1739 703.551 593 598 588.0 580.0 591 625 733 1014 1739 704.052 592 598 588.0 580.0 591 631 737 1014 1750 704.552 592 598 587.0 580.0 592 633 737 1018 1767 705.053 592 598 587.0 580.0 592 633 731 1019 1778 705.554 592 598 587.0 580.0 592 633 731 1024 1794 706.054 592 598 587.0 580.0 592 633 731 1036 1804 706.555 592 598 587.0 580.0 593 629 731 1044 1806 707.055 592 597 587.0 580.0 595 629 742 1046 1817 707.556 592 597 587.0 580.0 595 630 742 1052 1824 708.056 591 597 587.0 581.0 595 630 742 1064 1850 708.557 591 597 587.0 581.0 595 630 746 1068 1866 709.058 591 597 587.0 581.0 593 630 746 1071 1875 709.558 591 596 584.0 581.0 593 630 752 1072 1905 710.059 590 596 584.0 581.0 593 635 755 1077 1914 710.559 590 595 584.0 580.0 593 636 757 1086 1919 711.06 590 595 584.0 580.0 593 636 760 1087 1930 711.561 590 595 583.0 580.0 593 636 763 1098 1930 712.061 590 594 583.0 580.0 593 642 764 1098 1947 712.562 590 594 582.0 580.0 593 642 764 1103 1991 713.062 590 592 582.0 580.0 593 642 764 1107 1996 713.563 590 592 582.0 581.0 595 642 768 1118 2000 714.064 590 592 582.0 581.0 595 642 768 1129 2033 714.564 587 591 582.0 581.0 595 642 775 1129 2046 715.065 586 590 582.0 581.0 595 642 779 1129 2071 715.566 586 590 582.0 581.0 595 642 779 1130 2071 716.066 585 590 582.0 581.0 595 642 779 1130 2073 716.567 585 590 582.0 580.0 595 642 780 1150 2083 717.068 585 590 581.0 580.0 595 645 780 1163 2136 717.568 585 586 580.0 580.0 595 648 782 1164 2150 718.069 585 586 580.0 580.0 595 648 786 1166 2163 718.57 585 586 580.0 579.0 595 648 787 1166 2181 719.07 585 590 581.0 579.0 595 648 788 1185 2183 719.571 585 590 581.0 579.0 595 648 791 1196 2202 720.072 585 590 581.0 579.0 595 647 799 1210 2227 720.572 585 590 580.0 579.0 597 647 799 1212 2237 721.073 585 589 580.0 579.0 597 647 802 1214 2244 721.574 586 588 580.0 579.0 597 647 802 1214 2254 722.074 586 588 580.0 579.0 598 647 807 1214 2312 722.575 586 588 580.0 579.0 598 650 807 1232 2312 723.076 586 588 581.0 579.0 596 650 808 1243 2350 723.577 586 588 581.0 579.0 596 650 811 1246 2360 724.077 586 588 581.0 579.0 594 650 811 1260 2389 724.578 586 587 581.0 579.0 593 652 816 1266 2391 725.079 586 587 581.0 579.0 593 657 816 1268 2391 725.58 586 587 581.0 579.0 593 661 826 1268 2450 726.081 586 586 581.0 579.0 597 661 826 1268 2477 726.581 586 586 581.0 579.0 597 661 826 1281 2481 727.082 586 585 581.0 579.0 597 656 830 1297 2519 727.583 586 582 581.0 579.0 597 656 833 1309 2527 728.084 586 580 581.0 579.0 601 656 842 1321 2558 728.585 586 580 581.0 579.0 601 666 847 1328 2593 729.086 586 585 581.0 579.0 601 669 849 1342 2597 729.586 586 585 581.0 579.0 601 670 856 1342 2635 730.087 584 586 580.0 579.0 601 670 858 1362 2663 730.588 584 584 580.0 579.0 601 670 858 1366 2673 731.089 584 584 580.0 579.0 601 668 861 1396 2704 731.59 584 582 580.0 579.0 601 668 861 1406 2709 732.091 582 582 580.0 579.0 601 683 863 1406 2774 732.592 582 582 580.0 579.0 603 683 872 1409 2777 733.093 582 582 579.0 580.0 603 683 877 1415 2812 733.594 582 582 579.0 580.0 603 683 881 1447 2828 734.095 581 582 579.0 581.0 603 680 883 1447 2886 734.596 581 580 579.0 581.0 603 680 883 1454 2903 735.097 581 580 578.0 581.0 603 680 887 1457 2927 735.598 580 580 578.0 581.0 606 680 905 1469 2939 736.099 580 580 578.0 581.0 606 685 905 1491 2990 736.6 580 580 578.0 581.0 606 685 907 1494 3064 737.101 580 580 579.0 581.0 606 685 912 1511 3069 737.602 580 581 579.0 581.0 609 689 925 1539 3071 738.103 579 583 579.0 581.0 609 689 925 1544 3117 738.604 579 583 578.0 581.0 609 689 925 1555 3153 739.105 579 583 578.0 581.0 609 689 926 1559 3197 739.606 579 584 578.0 583.0 609 694 926 1591 3244 740.107 579 584 579.0 583.0 609 698 931 1611 3261 740.609 579 583 579.0 583.0 609 701 952 1611 3284 741.11 579 580 579.0 583.0 609 701 952 1623 3325 741.611 579 578 579.0 583.0 611 701 955 1637 3363 742.112 579 576 579.0 583.0 613 702 956 1659 3423 742.613 580 576 579.0 583.0 613 702 963 1670 3468 743.114 580 578 579.0 584.0 613 702 966 1679 3486 743.616 580 580 579.0 584.0 613 702 966 1692 3500 744.117 579 580 579.0 584.0 613 706 977 1696 3551 744.618 579 580 579.0 584.0 614 713 991 1704 3596 745.119 579 580 579.0 584.0 615 714 992 1733 3627 745.621 580 580 579.0 584.0 619 714 996 1760 3682 746.122 580 579 579.0 584.0 619 714 996 1762 3692 746.623 580 579 578.0 584.0 619 714 1005 1780 3719 747.125 580 579 578.0 584.0 619 714 1016 1791 3780 747.626 580 579 578.0 584.0 620 718 1017 1794 3785 748.128 580 581 577.0 584.0 620 718 1017 1813 3850 748.629 580 581 577.0 584.0 620 718 1019 1831 3907 749.13 580 583 577.0 584.0 620 723 1019 1847 3913 749.632 580 583 577.0 584.0 620 723 1040 1864 3970 750.133 579 583 577.0 584.0 622 723 1040 1872 4009 750.635 579 579 577.0 584.0 623 723 1046 1889 4061 751.136 579 578 577.0 584.0 623 731 1046 1924 4121 751.638 579 577 577.0 584.0 624 733 1047 1926 4180 752.139 579 577 577.0 584.0 624 737 1063 1941 4180 752.641 579 577 577.0 584.0 625 742 1063 1960 4199 753.142 579 579 577.0 585.0 625 742 1063 1963 4199 753.644 578 581 577.0 585.0 626 742 1078 1987 4259 754.145 578 581 577.0 585.0 626 742 1087 2010 4339 754.647 578 580 577.0 585.0 627 749 1088 2016 4378 755.149 578 580 577.0 586.0 627 755 1112 2029 4404 755.65 578 580 577.0 587.0 627 755 1116 2042 4423 756.152 578 577 577.0 587.0 628 755 1122 2071 4516 756.654 578 577 577.0 588.0 628 758 1122 2084 4542 757.155 578 577 577.0 588.0 629 762 1122 2103 4580 757.657 577 577 577.0 589.0 629 762 1123 2118 4582 758.159 577 578 577.0 589.0 630 765 1142 2127 4686 758.661 577 578 576.0 589.0 632 766 1147 2173 4704 759.163 576 578 576.0 589.0 633 768 1148 2173 4773 759.664 576 578 576.0 589.0 633 768 1155 2175 4775 760.166 576 578 576.0 589.0 633 768 1164 2221 4849 760.668 576 578 576.0 589.0 634 768 1175 2233 4892 761.17 576 578 576.0 589.0 637 773 1186 2244 4944 761.672 576 577 576.0 589.0 638 773 1192 2276 4964 762.174 576 576 574.0 590.0 639 773 1192 2276 5008 762.676 576 576 574.0 590.0 639 773 1201 2289 5118 763.178 576 576 574.0 590.0 640 786 1208 2325 5128 763.68 576 576 574.0 590.0 641 791 1208 2357 5168 764.182 576 576 574.0 590.0 642 791 1215 2365 5175 764.684 576 576 574.0 590.0 643 793 1232 2387 5267 765.186 576 576 574.0 591.0 644 799 1241 2396 5356 765.688 576 576 574.0 591.0 645 801 1244 2419 5358 766.19 576 576 574.0 591.0 645 804 1256 2426 5420 766.692 576 575 574.0 591.0 645 804 1261 2456 5489 767.194 576 575 574.0 591.0 646 805 1270 2474 5529 767.697 576 575 574.0 592.0 646 810 1272 2498 5562 768.199 576 577 575.0 592.0 648 810 1279 2516 5618 768.701 576 577 575.0 592.0 648 812 1282 2539 5672 769.203 576 577 575.0 592.0 649 817 1292 2568 5727 769.706 576 577 575.0 592.0 652 824 1312 2580 5789 770.208 576 576 575.0 592.0 652 824 1322 2621 5813 770.71 576 576 575.0 593.0 652 830 1339 2633 5872 771.213 576 576 575.0 593.0 654 830 1339 2644 5941 771.715 574 576 575.0 593.0 654 831 1339 2658 5971 772.217 574 576 575.0 593.0 656 835 1339 2658 6009 772.72 574 576 575.0 595.0 656 842 1342 2691 6097 773.222 574 577 575.0 596.0 656 844 1346 2736 6098 773.725 574 577 575.0 596.0 657 854 1372 2765 6263 774.227 574 577 575.0 596.0 658 854 1382 2792 6269 774.73 574 578 575.0 596.0 661 855 1388 2809 6346 775.232 574 578 575.0 596.0 662 861 1389 2832 6408 775.735 574 578 576.0 596.0 662 862 1404 2852 6431 776.238 574 578 576.0 596.0 664 863 1414 2866 6450 776.74 575 578 576.0 597.0 664 869 1418 2898 6616 777.243 575 575 576.0 597.0 664 873 1429 2924 7069 777.746 575 575 576.0 598.0 664 874 1446 2980 7069 778.248 575 575 577.0 599.0 664 875 1450 2991 7069 778.751 575 575 577.0 599.0 666 875 1457 3002 6952 779.254 575 576 577.0 599.0 667 875 1457 3002 6952 779.757 574 576 578.0 599.0 667 876 1480 3019 6952 780.26 574 576 578.0 599.0 668 885 1491 3063 6987 780.763 574 574 578.0 599.0 669 890 1499 3081 7055 781.266 574 574 578.0 600.0 670 892 1499 3112 7114 781.768 574 574 579.0 600.0 671 894 1519 3153 7231 782.271 574 575 579.0 601.0 672 899 1540 3176 7242 782.774 575 575 579.0 601.0 675 911 1549 3195 7296 783.277 575 575 579.0 601.0 677 916 1551 3208 7309 783.781 575 575 579.0 601.0 679 917 1560 3256 7366 784.284 574 575 579.0 602.0 681 918 1561 3265 7538 784.787 574 576 579.0 603.0 682 926 1601 3290 7577 785.29 574 576 579.0 603.0 683 926 1606 3336 7629 785.793 574 576 579.0 604.0 683 937 1606 3375 7706 786.296 574 576 579.0 604.0 687 938 1606 3396 7784 786.799 574 575 579.0 604.0 687 943 1627 3411 7810 787.303 574 575 579.0 605.0 690 944 1632 3476 7864 787.806 574 575 579.0 605.0 690 957 1633 3476 7942 788.309 574 575 580.0 605.0 694 958 1671 3477 7963 788.813 574 575 581.0 606.0 696 962 1677 3542 8077 789.316 574 573 581.0 607.0 696 962 1682 3581 8195 789.82 574 573 581.0 607.0 696 962 1702 3609 8280 790.323 574 573 581.0 607.0 698 962 1727 3609 8353 790.827 574 573 581.0 608.0 699 964 1727 3622 8418 791.33 574 573 581.0 608.0 700 974 1732 3703 8424 791.834 574 571 581.0 610.0 700 975 1734 3706 8516 792.337 573 570 581.0 610.0 701 981 1734 3760 8563 792.841 573 570 581.0 610.0 704 984 1761 3763 8692 793.345 573 571 581.0 610.0 704 989 1788 3799 8769 793.848 573 572 581.0 611.0 707 998 1794 3835 8856 794.352 573 575 581.0 611.0 707 1002 1798 3869 8929 794.856 573 575 581.0 611.0 709 1008 1822 3897 9014 795.359 573 575 581.0 611.0 710 1010 1831 3944 9063 795.863 573 575 581.0 612.0 711 1018 1843 3967 9122 796.367 573 575 581.0 612.0 713 1020 1848 3972 9138 796.871 573 575 582.0 612.0 717 1021 1851 3973 9282 797.375 574 575 582.0 613.0 720 1025 1871 4075 9387 797.879 574 575 582.0 613.0 721 1028 1907 4087 9455 798.383 574 575 582.0 614.0 721 1029 1907 4115 9564 798.887 573 578 582.0 615.0 727 1042 1907 4147 9631 799.391 573 578 582.0 615.0 730 1045 1918 4165 9709 799.895 573 578 582.0 615.0 730 1046 1939 4219 9851 800.399 573 578 582.0 615.0 732 1051 1959 4258 9852 800.904 573 578 582.0 615.0 733 1059 1966 4259 9905 801.408 573 578 582.0 617.0 738 1063 1966 4333 10031 801.912 573 574 582.0 618.0 738 1066 1990 4393 10156 802.416 574 574 582.0 619.0 746 1078 2014 4413 10228 802.921 574 574 583.0 620.0 746 1085 2030 4423 10330 803.425 574 573 583.0 620.0 746 1086 2050 4494 10381 803.929 574 570 583.0 623.0 747 1096 2052 4517 10451 804.434 574 570 583.0 624.0 751 1098 2055 4518 10606 804.938 573 570 584.0 624.0 752 1112 2080 4556 10647 805.443 573 571 585.0 624.0 753 1114 2103 4613 10661 805.947 573 571 585.0 624.0 754 1115 2110 4685 10878 806.452 573 572 585.0 625.0 757 1119 2142 4716 10886 806.957 572 572 585.0 625.0 757 1121 2143 4778 11042 807.461 572 572 585.0 625.0 758 1126 2179 4786 11177 807.966 572 572 585.0 625.0 758 1139 2242 4820 11279 808.471 572 577 585.0 628.0 759 1142 2242 4887 11291 808.975 572 577 585.0 628.0 760 1157 2244 4892 11403 809.48 572 577 586.0 628.0 760 1164 2244 4938 11488 809.985 572 575 586.0 628.0 760 1165 2244 4990 11617 810.49 572 574 586.0 628.0 762 1169 2247 5020 11714 810.995 572 574 587.0 629.0 764 1171 2273 5080 11869 811.5 572 574 587.0 629.0 765 1195 2288 5107 11955 812.005 572 574 587.0 629.0 767 1197 2307 5191 12029 812.51 572 574 587.0 629.0 773 1199 2318 5203 12089 813.015 572 575 587.0 634.0 773 1199 2344 5263 12288 813.52 572 575 587.0 634.0 780 1209 2353 5267 12338 814.026 572 577 587.0 635.0 780 1210 2357 5300 12414 814.531 572 577 587.0 637.0 782 1225 2377 5379 12526 815.036 572 577 587.0 638.0 783 1225 2406 5426 12678 815.541 572 577 589.0 639.0 785 1227 2418 5457 12708 816.047 572 577 589.0 641.0 787 1242 2453 5478 12790 816.552 572 573 591.0 641.0 788 1242 2456 5551 12950 817.057 572 572 591.0 643.0 790 1242 2471 5584 13142 817.563 573 572 591.0 643.0 799 1245 2507 5638 13240 818.068 574 572 589.0 644.0 801 1254 2518 5746 13256 818.574 574 572 589.0 644.0 809 1254 2523 5832 13403 819.08 574 574 589.0 648.0 809 1264 2571 5832 13556 819.585 574 576 591.0 648.0 809 1286 2573 5871 13563 820.091 573 576 591.0 648.0 806 1286 2579 5871 13719 820.597 573 576 591.0 644.0 806 1286 2609 5940 13911 821.102 575 578 593.0 644.0 806 1299 2625 5969 13964 821.608 576 578 593.0 644.0 825 1305 2644 5988 14027 822.114 576 576 591.0 648.0 825 1324 2670 6103 14112 822.62 576 575 589.0 649.0 825 1326 2690 6128 14255 823.126 576 574 589.0 649.0 825 1330 2690 6138 14419 360.012 380.012 400.01 420.009 440.008 460.007 296.5 828 1128 1612 2490 4157 6574 297.055 828 1110 1600 2490 4056 6438 297.61 851 1100 1594 2490 3990 6370 298.164 851 1100 1592 2490 3990 6370 298.719 826 1095 1591 2490 3990 6364 299.273 826 1095 1591 2479 3994 6361 299.827 826 1097 1591 2467 3994 6357 300.382 825 1097 1589 2462 3994 6342 300.936 825 1097 1581 2459 3951 6317 301.489 825 1097 1581 2458 3942 6316 302.043 829 1097 1575 2444 3938 6276 302.597 829 1097 1575 2444 3924 6269 303.15 829 1097 1567 2444 3924 6258 303.703 829 1097 1566 2437 3924 6253 304.256 818 1092 1566 2437 3915 6224 304.809 818 1092 1557 2436 3915 6224 305.362 818 1092 1557 2434 3905 6224 305.915 818 1092 1557 2421 3905 6208 306.467 820 1091 1557 2421 3905 6202 307.02 820 1078 1558 2421 3888 6169 307.572 820 1077 1564 2421 3878 6162 308.124 820 1077 1564 2414 3877 6162 308.676 818 1082 1562 2406 3877 6162 309.228 817 1082 1560 2406 3872 6162 309.78 817 1082 1558 2401 3861 6144 310.332 817 1078 1557 2401 3861 6123 310.883 816 1078 1553 2401 3850 6116 311.435 816 1078 1553 2386 3832 6102 311.986 816 1080 1549 2386 3826 6097 312.537 824 1080 1549 2386 3824 6097 313.088 824 1080 1549 2387 3824 6097 313.639 823 1080 1549 2387 3827 6097 314.189 823 1080 1551 2387 3827 6084 314.74 823 1078 1551 2377 3822 6077 315.29 823 1079 1535 2364 3822 6062 315.841 821 1077 1535 2364 3822 6062 316.391 818 1077 1534 2364 3798 6018 316.941 818 1074 1534 2361 3798 6017 317.491 818 1068 1534 2361 3790 6017 318.04 818 1068 1525 2358 3776 6020 318.59 818 1068 1525 2348 3776 6020 319.139 817 1086 1525 2348 3776 6020 319.689 813 1102 1525 2354 3776 6012 320.238 813 1102 1525 2354 3783 6012 320.787 813 1081 1525 2354 3783 6004 321.336 813 1068 1523 2354 3776 5996 321.885 813 1068 1523 2340 3776 5985 322.433 815 1068 1523 2340 3776 5985 322.982 815 1068 1523 2340 3776 5985 323.53 815 1073 1523 2333 3765 5957 324.079 815 1147 1524 2322 3765 5954 324.627 814 1167 1526 2322 3756 5954 325.175 812 1167 1526 2322 3747 5954 325.723 808 1095 1526 2328 3736 5940 326.271 808 1059 1535 2328 3736 5940 326.818 808 1057 1535 2328 3736 5940 327.366 812 1057 1518 2318 3730 5940 327.913 812 1057 1517 2313 3730 5942 328.46 812 1060 1508 2313 3730 5942 329.007 812 1060 1503 2313 3715 5942 329.554 807 1060 1503 2313 3715 5942 330.101 807 1060 1503 2307 3715 5942 330.648 807 1057 1505 2307 3716 5925 331.195 807 1053 1505 2307 3716 5905 331.741 808 1053 1507 2307 3716 5905 332.287 808 1053 1507 2307 3715 5889 332.834 808 1051 1507 2307 3715 5889 333.38 808 1051 1507 2297 3699 5883 333.926 808 1051 1507 2297 3699 5883 334.472 808 1051 1507 2297 3699 5883 335.017 815 1049 1501 2297 3699 5883 335.563 830 1049 1501 2297 3692 5892 336.108 830 1049 1501 2281 3691 5886 336.654 814 1049 1501 2281 3691 5868 337.199 806 1047 1505 2282 3691 5868 337.744 804 1047 1505 2288 3684 5868 338.289 800 1047 1679 2288 3684 5856 338.834 800 1047 1679 2288 3683 5856 339.378 799 1045 1679 2288 3678 5856 339.923 799 1045 1482 2288 3678 5856 340.467 799 1045 1482 2289 3678 5856 341.012 799 1045 1482 2290 3666 5853 341.556 809 1044 1487 2294 3662 5853 342.1 809 1044 1487 2298 3662 5853 342.644 809 1044 1490 2296 3668 5853 343.188 806 1044 1490 2285 3673 5853 343.731 806 1048 1490 2278 3673 5853 344.275 806 1048 1497 2278 3673 5853 344.818 806 1048 1497 2278 3673 5853 345.362 808 1043 1496 2278 3667 5853 345.905 808 1043 1496 2282 3667 5853 346.448 808 1043 1498 2282 3667 5852 346.991 807 1041 1499 2283 3667 5852 347.534 800 1041 1499 2283 3667 5852 348.076 800 1041 1499 2292 3676 5863 348.619 800 1041 1501 2292 3688 5881 349.161 802 1045 1501 2292 3688 5884 349.704 805 1049 1498 2292 3688 5884 350.246 805 1051 1491 2292 3688 5885 350.788 805 1051 1488 2306 3688 5885 351.33 805 1050 1488 2306 3688 5885 351.872 804 1050 1488 2306 3690 5894 352.414 804 1046 1488 2306 3690 5913 352.955 804 1042 1488 2298 3690 5913 353.497 804 1041 1488 2298 3690 5913 354.038 808 1041 1489 2298 3690 5913 354.579 811 1041 1493 2318 3690 5915 355.12 811 1041 1493 2318 3709 5917 355.661 810 1047 1493 2318 3709 5918 356.202 810 1047 1493 2318 3709 5944 356.743 810 1047 1493 2321 3709 5944 357.284 810 1047 1493 2321 3709 5944 357.824 810 1047 1502 2321 3709 5949 358.364 810 1056 1503 2321 3726 5949 358.905 812 1057 1503 2316 3726 5981 359.445 813 1057 1503 2316 3726 5997 359.985 812 1057 1506 2316 3729 5981 360.525 812 1057 1506 2324 3731 5973 361.065 812 1057 1489 2324 3738 5969 361.604 812 1048 1489 2324 3738 5958 362.144 811 1048 1489 2324 3738 5958 362.683 811 1060 1496 2320 3751 5958 363.223 811 1060 1509 2320 3751 5959 363.762 811 1048 1515 2323 3753 6008 364.301 811 1048 1515 2332 3762 6008 364.84 817 1056 1511 2336 3762 6008 365.379 819 1059 1509 2338 3762 6014 365.917 819 1059 1505 2338 3762 6014 366.456 817 1059 1503 2343 3762 6020 366.995 813 1059 1503 2344 3763 6020 367.533 812 1065 1512 2344 3763 6027 368.071 812 1065 1519 2344 3784 6027 368.609 813 1065 1519 2341 3784 6028 369.147 814 1065 1519 2341 3786 6045 369.685 814 1062 1519 2341 3786 6045 370.223 814 1062 1521 2347 3786 6049 370.761 814 1062 1521 2347 3786 6049 371.298 815 1062 1521 2347 3786 6049 371.836 816 1062 1522 2353 3796 6049 372.373 817 1062 1523 2353 3796 6076 372.91 817 1063 1523 2365 3796 6076 373.447 817 1063 1531 2365 3796 6076 373.984 817 1063 1531 2372 3796 6079 374.521 817 1063 1531 2381 3807 6079 375.058 817 1062 1531 2381 3809 6079 375.595 817 1062 1531 2386 3821 6093 376.131 817 1062 1531 2392 3824 6094 376.668 819 1062 1531 2392 3824 6094 377.204 819 1066 1531 2388 3824 6094 377.74 819 1067 1532 2381 3836 6156 378.276 819 1070 1534 2374 3836 6167 378.812 813 1070 1534 2374 3836 6195 379.348 813 1074 1534 2382 3836 6195 379.884 813 1074 1534 2386 3848 6195 380.419 816 1074 1534 2390 3868 6195 380.955 821 1070 1545 2390 3869 6195 381.49 821 1070 1545 2394 3871 6195 382.026 821 1070 1545 2397 3871 6195 382.561 819 1077 1545 2397 3871 6218 383.096 819 1081 1547 2397 3876 6218 383.631 819 1081 1562 2405 3876 6237 384.166 819 1081 1562 2411 3888 6237 384.7 819 1081 1562 2415 3888 6237 385.235 816 1077 1562 2419 3888 6237 385.77 816 1077 1562 2419 3907 6253 386.304 816 1077 1555 2417 3923 6269 386.838 819 1083 1553 2416 3936 6269 387.372 820 1083 1553 2416 3942 6282 387.907 820 1084 1553 2416 3945 6305 388.441 822 1084 1558 2416 3946 6305 388.974 826 1084 1569 2416 3948 6305 389.508 826 1080 1569 2419 3949 6314 390.042 827 1080 1569 2427 3948 6318 390.575 827 1080 1569 2427 3948 6318 391.109 827 1086 1566 2435 3948 6318 391.642 828 1090 1566 2435 3948 6318 392.175 828 1090 1559 2435 3962 6337 392.708 828 1090 1559 2438 3967 6365 393.241 826 1090 1571 2439 3967 6365 393.774 826 1090 1571 2454 3976 6365 394.307 826 1091 1571 2455 3976 6388 394.84 826 1091 1571 2455 3976 6401 395.372 832 1093 1574 2455 3976 6420 395.905 832 1093 1588 2455 3976 6420 396.437 832 1093 1590 2455 3976 6420 396.969 831 1092 1607 2458 3976 6420 397.501 821 1090 1607 2464 3976 6454 398.033 821 1090 1607 2465 4009 6454 398.565 830 1090 1583 2468 4024 6454 399.097 830 1100 1583 2470 4024 6474 399.629 830 1101 1583 2470 4024 6474 400.16 828 1101 1583 2470 4024 6474 400.692 827 1101 1592 2489 4025 6474 401.223 826 1099 1610 2491 4025 6474 401.755 826 1099 1611 2499 4025 6474 402.286 826 1099 1692 2499 4047 6474 402.817 833 1099 1692 2499 4047 6474 403.348 833 1099 1642 2499 4043 6474 403.879 833 1099 1618 2499 4044 6489 404.409 833 1099 1616 2496 4044 6496 404.94 838 1099 1603 2496 4046 6520 405.471 838 1099 1601 2496 4055 6520 406.001 840 1100 1601 2504 4055 6529 406.531 846 1103 1601 2504 4068 6547 407.062 846 1108 1601 2504 4082 6550 407.592 844 1110 1610 2507 4082 6550 408.122 833 1110 1610 2507 4082 6550 408.652 833 1107 1613 2507 4082 6564 409.181 828 1107 1613 2521 4082 6570 409.711 828 1107 1610 2521 4098 6596 410.241 828 1107 1610 2521 4112 6638 410.77 833 1111 1617 2520 4112 6642 411.3 835 1111 1617 2520 4106 6634 411.829 836 1111 1614 2520 4106 6622 412.358 836 1112 1614 2524 4106 6622 412.887 836 1112 1625 2539 4110 6641 413.416 836 1109 1625 2539 4118 6653 413.945 834 1105 1625 2539 4150 6659 414.474 834 1105 1622 2539 4150 6662 415.003 834 1107 1622 2536 4150 6674 415.531 834 1111 1622 2535 4137 6674 416.06 839 1115 1619 2534 4137 6674 416.588 839 1115 1619 2534 4137 6674 417.117 840 1115 1619 2534 4140 6702 417.645 840 1115 1619 2542 4157 6702 418.173 840 1119 1620 2542 4172 6702 418.701 843 1119 1620 2542 4174 6702 419.229 843 1119 1627 2560 4174 6702 419.757 843 1119 1641 2560 4174 6712 420.284 842 1116 1641 2560 4207 6715 420.812 842 1113 1641 2560 4207 6715 421.34 842 1113 1638 2560 4181 6716 421.867 842 1116 1635 2560 4181 6716 422.394 846 1124 1625 2557 4181 6716 422.921 846 1126 1620 2557 4191 6716 423.449 846 1129 1620 2558 4205 6756 423.976 846 1129 1626 2558 4209 6756 424.503 836 1129 1637 2565 4209 6756 425.029 836 1129 1637 2565 4209 6756 425.556 836 1129 1649 2584 4209 6759 426.083 836 1129 1649 2584 4224 6808 426.609 837 1122 1649 2584 4229 6808 427.136 837 1122 1646 2586 4232 6808 427.662 837 1122 1646 2589 4235 6808 428.188 837 1120 1644 2598 4238 6832 428.714 837 1120 1644 2598 4244 6838 429.24 837 1120 1647 2608 4244 6838 429.766 837 1129 1654 2608 4259 6838 430.292 843 1130 1659 2608 4259 6838 430.818 847 1130 1660 2608 4259 6839 431.344 848 1130 1660 2608 4246 6855 431.869 848 1137 1660 2612 4246 6855 432.395 848 1137 1654 2612 4246 6855 432.92 848 1127 1654 2612 4246 6883 433.445 848 1127 1654 2612 4262 6885 433.971 848 1129 1660 2612 4272 6901 434.496 848 1130 1660 2612 4273 6903 435.021 849 1136 1662 2612 4274 6905 435.546 854 1141 1662 2612 4276 6933 436.071 854 1141 1664 2612 4276 6935 436.595 854 1141 1664 2618 4276 6939 437.12 852 1142 1670 2624 4276 6942 437.644 848 1142 1670 2624 4276 6945 438.169 848 1142 1670 2626 4295 6942 438.693 848 1141 1670 2640 4312 6942 439.218 849 1140 1669 2644 4312 6942 439.742 855 1140 1669 2637 4312 6942 440.266 855 1138 1669 2637 4312 6946 440.79 855 1138 1670 2637 4312 6946 441.314 854 1138 1670 2637 4302 6946 441.837 852 1138 1676 2637 4302 6973 442.361 848 1138 1676 2645 4322 6999 442.885 848 1144 1678 2645 4322 6999 443.408 848 1144 1685 2656 4322 6997 443.932 850 1144 1685 2656 4344 6997 444.455 850 1144 1686 2656 4349 6997 444.978 850 1150 1687 2658 4357 6996 445.502 850 1150 1688 2675 4357 6996 446.025 852 1147 1688 2694 4359 6996 446.548 852 1146 1688 2694 4359 7014 447.071 854 1146 1688 2677 4359 7020 447.593 854 1146 1683 2677 4378 7028 448.116 854 1146 1681 2677 4379 7036 448.639 854 1152 1681 2677 4379 7036 449.161 854 1158 1683 2681 4379 7075 449.684 854 1158 1687 2681 4400 7075 450.206 856 1158 1690 2681 4400 7075 450.728 856 1158 1690 2697 4400 7075 451.251 856 1158 1690 2697 4391 7075 451.773 859 1158 1690 2697 4391 7075 452.295 859 1156 1695 2685 4391 7078 452.817 859 1156 1695 2685 4394 7123 453.338 859 1156 1697 2685 4402 7123 453.86 859 1156 1699 2698 4417 7143 454.382 851 1154 1699 2702 4418 7143 454.903 851 1154 1708 2702 4423 7143 455.425 851 1154 1708 2700 4423 7143 455.946 851 1159 1708 2697 4433 7143 456.468 860 1162 1712 2697 4453 7172 456.989 865 1162 1731 2703 4453 7172 457.51 865 1162 1733 2703 4453 7140 458.031 865 1162 1731 2704 4453 7140 458.552 865 1162 1727 2711 4453 7153 459.073 858 1159 1723 2711 4453 7156 459.594 858 1159 1723 2711 4455 7178 460.114 859 1156 1719 2711 4456 7198 460.635 862 1156 1719 2717 4456 7202 461.156 862 1156 1719 2717 4459 7202 461.676 862 1162 1722 2719 4477 7214 462.196 863 1162 1722 2719 4491 7214 462.717 863 1162 1722 2719 4494 7219 463.237 863 1162 1721 2727 4494 7219 463.757 853 1166 1721 2731 4494 7219 464.277 853 1172 1715 2756 4494 7219 464.797 853 1172 1715 2756 4494 7219 465.317 853 1172 1715 2756 4494 7238 465.837 862 1171 1718 2758 4494 7238 466.356 862 1169 1732 2759 4516 7238 466.876 862 1169 1736 2760 4516 7255 467.396 862 1170 1736 2760 4516 7255 467.915 862 1171 1745 2760 4515 7255 468.434 864 1171 1745 2760 4515 7305 468.954 867 1171 1745 2759 4517 7328 469.473 867 1171 1744 2757 4517 7328 469.992 866 1171 1744 2757 4525 7328 470.511 866 1171 1740 2757 4525 7326 471.03 866 1171 1732 2757 4545 7326 471.549 865 1175 1732 2757 4545 7326 472.068 865 1175 1732 2757 4553 7361 472.586 865 1175 1732 2769 4553 7361 473.105 867 1175 1741 2769 4564 7367 473.624 867 1176 1744 2769 4564 7378 474.142 867 1176 1750 2769 4567 7385 474.661 875 1177 1750 2773 4567 7385 475.179 1101 1177 1747 2773 4567 7385 475.697 1101 1177 1747 2773 4572 7385 476.215 869 1177 1747 2773 4575 7391 476.733 869 1177 1747 2772 4580 7391 477.251 867 1178 1744 2772 4580 7391 477.769 867 1178 1744 2781 4586 7391 478.287 861 1178 1744 2830 4586 7435 478.805 861 1179 1748 2920 4586 7435 479.323 863 1180 1766 2920 4586 7435 479.84 868 1180 1770 2835 4601 7468 480.358 870 1180 1770 2791 4603 7468 480.875 872 1180 1770 2791 4607 7482 481.393 872 1180 1763 2791 4607 7483 481.91 872 1183 1758 2791 4626 7483 482.427 876 1187 1758 2807 4638 7483 482.944 876 1187 1758 2814 4638 7487 483.461 876 1187 1770 2814 4638 7487 483.978 876 1197 1780 2829 4638 7487 484.495 878 1197 1780 2832 4641 7488 485.012 878 1197 1780 2832 4654 7489 485.529 878 1197 1780 2832 4654 7519 486.045 875 1197 1776 2832 4654 7521 486.562 875 1197 1776 2832 4654 7521 487.079 875 1197 1776 2839 4654 7521 487.595 875 1198 1776 2839 4654 7560 488.111 879 1198 1776 2834 4654 7570 488.628 880 1198 1782 2833 4658 7606 489.144 880 1200 1782 2833 4660 7606 489.66 880 1204 1783 2833 4660 7606 490.176 880 1204 1783 2835 4665 7609 490.692 880 1200 1785 2839 4685 7609 491.208 875 1199 1785 2840 4685 7609 491.724 875 1199 1784 2849 4701 7616 492.24 875 1199 1780 2861 4701 7616 492.755 873 1199 1780 2861 4702 7634 493.271 873 1206 1787 2861 4725 7638 493.787 885 1206 1841 2861 4731 7638 494.302 885 1206 1841 2864 4734 7670 494.817 885 1206 1837 2866 4734 7687 495.333 885 1208 1821 2868 4734 7691 495.848 885 1208 1805 2870 4736 7715 496.363 885 1208 1805 2873 4746 7715 496.878 885 1212 1800 2873 4746 7719 497.393 885 1220 1790 2890 4746 7733 497.908 888 1230 1790 2890 4764 7760 498.423 888 1230 1803 2898 4764 7762 498.938 888 1210 1812 2904 4769 7762 499.453 888 1210 1818 2904 4790 7762 499.968 881 1210 1826 2904 4812 7800 500.482 881 1210 1828 2915 4812 7820 500.997 881 1216 1828 2928 4812 7870 501.511 884 1216 1829 2928 4849 7870 502.026 891 1216 1831 2929 4849 7870 502.54 894 1216 1833 2929 4862 7882 503.054 908 1216 1833 2941 4862 7895 503.568 908 1221 1835 2941 4863 7895 504.083 897 1224 1839 2941 4869 7913 504.597 897 1224 1853 2941 4869 7982 505.111 897 1224 1853 2951 4873 7982 505.625 897 1227 1835 2966 4873 7982 506.138 897 1231 1835 2966 4873 8007 506.652 897 1231 1851 2978 4873 8024 507.166 896 1231 1855 2986 4928 8047 507.679 896 1231 1855 2986 4930 8052 508.193 898 1231 1857 2987 4930 8078 508.707 898 1233 1859 3001 4967 8078 509.22 898 1233 1860 3015 4997 8110 509.733 899 1234 1867 3018 5015 8110 510.247 899 1239 1867 3024 5016 8151 510.76 899 1239 1867 3026 5016 8179 511.273 896 1243 1867 3023 5036 8187 511.786 896 1250 1870 3028 5036 8197 512.299 896 1251 1872 3031 5037 8222 512.812 898 1251 1874 3035 5063 8247 513.325 906 1255 1890 3056 5063 8247 513.838 906 1255 1891 3060 5081 8247 514.351 906 1255 1896 3060 5115 8349 514.863 910 1255 1897 3073 5115 8386 515.376 915 1257 1897 3082 5115 8389 515.889 915 1258 1897 3082 5115 8389 516.401 915 1259 1897 3092 5159 8389 516.913 913 1259 1904 3106 5159 8437 517.426 911 1259 1908 3106 5159 8447 517.938 911 1275 1922 3111 5159 8450 518.45 913 1275 1927 3111 5166 8476 518.963 917 1275 1927 3114 5207 8510 519.475 917 1273 1927 3136 5241 8551 519.987 917 1269 1927 3138 5241 8578 520.499 918 1269 1928 3139 5254 8610 521.011 918 1269 1936 3141 5261 8615 521.522 918 1269 1939 3141 5261 8615 522.034 918 1278 1953 3141 5266 8615 522.546 919 1280 1953 3149 5275 8686 523.058 919 1282 1954 3181 5295 8686 523.569 919 1282 1954 3181 5325 8749 524.081 925 1282 1954 3181 5352 8749 524.592 926 1299 1959 3181 5356 8784 525.104 926 1299 1963 3188 5350 8809 525.615 926 1299 1964 3191 5379 8821 526.126 928 1299 1968 3213 5399 8821 526.637 928 1296 1970 3213 5409 8902 527.149 928 1296 1975 3213 5422 8912 527.66 928 1296 1975 3230 5438 8921 528.171 924 1296 1984 3231 5459 8950 528.682 924 1308 1989 3231 5459 8950 529.193 924 1308 1998 3248 5459 9025 529.704 926 1313 1998 3260 5465 9025 530.214 939 1314 2002 3271 5470 9040 530.725 939 1318 2002 3279 5502 9040 531.236 933 1318 2009 3293 5525 9110 531.746 931 1318 2009 3303 5531 9127 532.257 931 1319 2017 3303 5531 9173 532.767 931 1319 2017 3303 5560 9187 533.278 932 1319 2017 3303 5600 9241 533.788 934 1317 2017 3303 5615 9251 534.298 938 1315 2035 3303 5622 9290 534.809 940 1315 2035 3328 5629 9291 535.319 940 1316 2035 3350 5639 9352 535.829 940 1316 2036 3354 5639 9359 536.339 940 1316 2036 3378 5669 9359 536.849 940 1320 2045 3378 5684 9378 537.359 945 1320 2048 3387 5710 9419 537.869 945 1320 2057 3387 5716 9446 538.379 945 1320 2065 3387 5716 9455 538.889 945 1342 2065 3391 5716 9499 539.398 945 1342 2065 3387 5746 9501 539.908 945 1340 2065 3397 5788 9519 540.418 949 1340 2073 3420 5792 9587 540.927 949 1341 2084 3424 5800 9669 541.437 949 1343 2085 3424 5826 9669 541.946 949 1345 2098 3428 5826 9669 542.456 949 1352 2114 3428 5828 9715 542.965 949 1352 2114 3434 5860 9727 543.474 950 1352 2106 3463 5882 9802 543.983 955 1352 2106 3466 5882 9809 544.493 965 1352 2115 3474 5891 9815 545.002 965 1352 2121 3482 5894 9880 545.511 965 1352 2124 3504 5948 9907 546.02 965 1352 2135 3505 5973 9913 546.529 965 1365 2394 3505 5973 9979 547.038 960 1365 2394 3516 5982 9990 547.546 960 1365 2394 3516 5988 10006 548.055 960 1365 2394 3527 6001 10091 548.564 971 1365 2334 3556 6039 10091 549.073 971 1365 2200 3561 6061 10102 549.581 971 1365 2133 3563 6062 10102 550.09 963 1367 2133 3568 6067 10137 550.598 963 1373 2133 3577 6092 10194 551.107 963 1373 2134 3577 6101 10229 551.615 965 1376 2162 3590 6123 10281 552.123 965 1376 2163 3598 6134 10378 552.632 966 1376 2168 3622 6164 10378 553.14 966 1376 2168 3622 6208 10386 553.648 966 1378 2168 3625 6209 10440 554.156 966 1380 2172 3626 6209 10473 554.664 968 1385 2172 3626 6222 10526 555.172 971 1385 2172 3626 6260 10526 555.68 973 1385 2201 3645 6290 10559 556.188 973 1385 2207 3651 6300 10559 556.696 972 1398 2207 3657 6304 10641 557.204 968 1398 2211 3678 6316 10688 557.712 968 1400 2211 3691 6350 10749 558.22 968 1400 2211 3691 6371 10780 558.727 979 1400 2205 3703 6403 10823 559.235 979 1400 2205 3703 6403 10886 559.742 978 1400 2209 3714 6409 10891 560.25 978 1400 2219 3743 6450 10915 560.757 978 1398 2245 3763 6459 10926 561.265 978 1394 2251 3763 6469 11011 561.772 987 1394 2251 3783 6497 11057 562.28 987 1399 2251 3783 6551 11143 562.787 989 1414 2251 3791 6571 11153 563.294 989 1428 2260 3798 6578 11193 563.801 989 1428 2260 3798 6586 11247 564.308 983 1436 2260 3798 6625 11282 564.815 983 1436 2268 3824 6648 11308 565.323 983 1436 2279 3844 6684 11384 565.83 983 1436 2279 3851 6691 11418 566.336 984 1436 2279 3872 6703 11522 566.843 984 1438 2279 3897 6730 11529 567.35 985 1441 2282 3897 6739 11595 567.857 985 1441 2301 3897 6806 11643 568.364 989 1448 2308 3919 6813 11661 568.87 994 1448 2308 3930 6835 11701 569.377 997 1455 2308 3951 6842 11728 569.884 998 1458 2329 3951 6898 11810 570.39 998 1458 2329 3973 6901 11916 570.897 998 1458 2329 3984 6957 11981 571.403 1005 1458 2329 3989 6990 11988 571.91 1005 1458 2331 3998 7022 12085 572.416 1005 1461 2353 4002 7037 12115 572.922 1003 1463 2353 4027 7041 12181 573.429 1003 1474 2377 4037 7140 12246 573.935 1003 1474 2381 4058 7168 12294 574.441 1006 1474 2391 4067 7168 12405 574.947 1006 1474 2391 4086 7177 12475 575.453 1006 1474 2392 4092 7192 12525 575.959 1010 1484 2392 4092 7249 12562 576.465 1012 1492 2392 4092 7275 12593 576.971 1012 1492 2392 4161 7313 12725 577.477 1013 1492 2396 4161 7350 12786 577.983 1013 1495 2422 4172 7391 12869 578.489 1015 1501 2471 4173 7391 12891 578.995 1015 1505 2569 4196 7446 12921 579.501 1015 1505 2569 4211 7485 13022 580.006 1015 1505 2484 4222 7510 13182 580.512 1019 1505 2483 4231 7561 13200 581.018 1024 1505 2456 4236 7580 13263 581.523 1024 1505 2456 4281 7613 13291 582.029 1025 1513 2456 4284 7644 13303 582.534 1028 1514 2483 4314 7727 13497 583.04 1032 1516 2510 4314 7740 13530 583.545 1032 1527 2510 4314 7764 13649 584.05 1032 1529 2510 4378 7776 13743 584.556 1032 1543 2510 4378 7818 13859 585.061 1032 1547 2513 4386 7899 13884 585.566 1033 1551 2521 4437 7950 13955 586.071 1033 1551 2530 4442 7979 14050 586.577 1033 1551 2535 4446 8013 14071 587.082 1038 1562 2541 4446 8042 14226 587.587 1047 1562 2552 4488 8112 14306 588.092 1047 1562 2554 4520 8187 14391 588.597 1046 1571 2584 4532 8208 14597 589.102 1047 1573 2599 4532 8223 14604 589.607 1047 1574 2601 4549 8292 14714 590.112 1047 1580 2625 4578 8331 14765 590.616 1052 1586 2625 4642 8485 14921 591.121 1052 1588 2625 4644 8485 14967 591.626 1056 1588 2625 4701 8485 15127 592.131 1056 1594 2627 4703 8526 15264 592.635 1056 1595 2631 4703 8556 15320 593.14 1056 1608 2671 4727 8630 15472 593.645 1056 1610 2671 4737 8691 15564 594.149 1056 1612 2674 4778 8723 15656 594.654 1075 1626 2688 4807 8797 15683 595.158 1075 1627 2698 4828 8827 15892 595.663 1075 1629 2707 4840 8904 15953 596.167 1074 1629 2715 4897 8944 16122 596.672 1074 1629 2715 4897 9036 16313 597.176 1074 1629 2749 4904 9135 16473 597.68 1084 1646 2769 4947 9157 16590 598.185 1084 1646 2769 4986 9183 16723 598.689 1090 1655 2774 5008 9260 16788 599.193 1090 1666 2808 5029 9323 16848 599.697 1090 1666 2821 5064 9365 17116 600.201 1089 1671 2821 5089 9423 17163 600.705 1089 1674 2846 5134 9495 17273 601.209 1089 1683 2864 5164 9604 17449 601.713 1093 1683 2864 5191 9641 17537 602.217 1101 1683 2867 5229 9736 17698 602.721 1132 1683 2883 5239 9815 17813 603.225 1132 1698 2908 5260 9882 18072 603.729 1109 1704 2924 5283 9978 18129 604.233 1109 1705 2927 5323 9992 18332 604.737 1109 1709 2927 5371 10046 18422 605.241 1147 1710 2927 5377 10088 18689 605.744 1147 1710 2963 5458 10223 18733 606.248 1146 1737 2994 5467 10276 18886 606.752 1112 1741 2998 5503 10318 19027 607.255 1112 1741 3007 5528 10415 19208 607.759 1112 1752 3019 5537 10539 19389 608.263 1119 1759 3021 5601 10595 19556 608.766 1130 1760 3074 5647 10659 19694 609.27 1132 1768 3074 5654 10706 19869 609.773 1132 1787 3078 5702 10848 19986 610.277 1136 1793 3089 5741 10933 20172 610.78 1134 1797 3108 5794 11033 20311 611.283 1142 1797 3138 5823 11103 20544 611.787 1142 1817 3146 5860 11170 20709 612.29 1142 1818 3167 5912 11298 20984 612.793 1142 1819 3174 5936 11385 21055 613.297 1144 1822 3206 5964 11397 21266 613.8 1160 1837 3237 6014 11494 21418 614.303 1160 1845 3246 6032 11578 21652 614.806 1164 1850 3249 6072 11777 21876 615.309 1172 1850 3271 6197 11857 22092 615.812 1172 1850 3273 6202 11934 22255 616.316 1172 1880 3313 6252 11997 22468 616.819 1165 1887 3326 6253 12079 22800 617.322 1164 1891 3349 6372 12167 22900 617.825 1173 1900 3373 6377 12368 23095 618.328 1177 1900 3378 6398 12468 23371 618.83 1180 1903 3393 6436 12817 23540 619.333 1180 1908 3422 6505 12817 23846 619.836 1186 1923 3457 6589 12899 24064 620.339 1197 1931 3468 6606 12899 24601 620.842 1197 1948 3469 6667 12993 24686 621.345 1202 1955 3505 6721 13137 24686 621.847 1202 1973 3528 6781 13209 24988 622.35 1214 1992 3573 6805 13369 25177 622.853 1214 1993 3592 6884 13479 25626 623.355 1218 1995 3605 6971 13585 25759 623.858 1228 2001 3669 6980 13713 26014 624.361 1228 2001 3672 7004 13878 26239 624.863 1229 2034 3723 7111 13988 26435 625.366 1229 2047 3752 7154 14172 26763 625.868 1230 2076 3754 7211 14231 27079 626.371 1240 2083 3780 7273 14432 27404 626.873 1245 2083 3804 7330 14536 27681 627.376 1258 2089 3810 7435 14744 27924 627.878 1289 2094 3842 7466 14806 28156 628.381 1293 2100 3865 7471 14946 28459 628.883 1293 2130 3906 7574 15084 28876 629.385 1293 2160 3943 7683 15199 29059 629.888 1293 2160 3958 7747 15365 29361 630.39 1289 2184 3983 7844 15599 29821 630.892 1289 2184 4026 7849 15683 29946 631.395 1289 2184 4050 7978 15959 30305 631.897 1289 2204 4081 8029 15959 30612 632.399 1292 2205 4121 8086 16189 31263 632.901 1298 2205 4159 8253 16342 31299 633.403 1310 2218 4191 8286 16566 31683 633.905 1310 2247 4209 8333 16673 31882 634.408 1317 2261 4238 8385 16813 32388 634.91 1324 2269 4300 8438 17064 32617 635.412 1338 2273 4329 8520 17207 33028 635.914 1342 2306 4349 8628 17436 33394 636.416 1342 2317 4359 8684 17610 33831 636.918 1346 2319 4376 8773 17794 34218 637.42 1346 2338 4465 8871 17998 34536 637.922 1355 2371 4503 8983 18129 34816 638.424 1355 2388 4504 9084 18349 35351 638.925 1374 2394 4600 9105 18525 35710 639.427 1374 2402 4603 9311 18719 36088 639.929 1374 2421 4604 9336 18870 36416 640.431 1387 2438 4695 9429 19121 36899 640.933 1389 2467 4722 9472 19188 37332 641.435 1405 2467 4722 9605 19429 37758 641.936 1405 2486 4805 9679 19720 38125 642.438 1405 2517 4826 9810 19930 38665 642.94 1429 2547 4917 9897 20124 38912 643.442 1431 2549 4923 9999 20326 39546 643.943 1440 2555 4972 10098 20591 39946 644.445 1440 2567 4979 10150 20796 40342 644.947 1440 2612 5043 10297 20950 40791 645.448 1459 2612 5082 10379 21205 41160 645.95 1471 2627 5169 10498 21488 41586 646.451 1475 2627 5176 10551 21620 42135 646.953 1482 2668 5211 10671 21925 42699 647.455 1486 2705 5268 10762 22103 43152 647.956 1489 2722 5284 10855 22377 43615 648.458 1502 2729 5381 10958 22575 44173 648.959 1529 2742 5427 11097 22887 44512 649.461 1529 2769 5483 11193 23129 45184 649.962 1529 2783 5510 11350 23316 45680 650.464 1542 2822 5566 11502 23588 46067 650.965 1634 2831 5627 11598 23754 46667 651.466 1634 2869 5692 11631 24056 47120 651.968 1589 2871 5724 11774 24360 47632 652.469 1589 2896 5813 11944 24560 48252 652.97 1589 2916 5854 12038 24850 48725 653.472 1589 2934 5890 12194 25199 49386 653.973 1603 2993 5922 12400 25481 49725 654.474 1609 3010 5979 12428 25703 50516 654.976 1620 3013 6064 12497 26066 51041 655.477 1633 3054 6134 12737 26302 51597 655.978 1644 3082 6151 12848 26565 52141 656.48 1644 3090 6243 13018 26821 52913 656.981 1670 3125 6319 13134 27123 53172 657.482 1673 3152 6337 13296 27535 54151 657.983 1695 3187 6435 13437 27741 54679 658.484 1696 3210 6478 13526 28071 55124 658.985 1704 3224 6517 13691 28378 55632 659.487 1704 3236 6628 13809 28746 56461 659.988 1731 3251 6682 13966 29262 57107 660.489 1733 3298 6737 14194 29636 57828 660.99 1763 3320 6797 14257 29673 58447 661.491 1763 3363 6864 14494 30049 59014 661.992 1777 3395 6902 14567 30318 59720 662.493 1787 3424 7026 14801 30940 60524 662.994 1791 3460 7073 14939 30996 61376 663.495 1809 3483 7136 15133 31371 61896 663.996 1814 3534 7261 15246 31841 62522 664.497 1828 3549 7310 15478 32091 63076 664.998 1858 3566 7389 15630 32389 63609 665.499 1859 3634 7504 15798 32886 64016 666 1877 3675 7511 15986 33236 64335 666.501 1893 3705 7644 16134 33750 64593 667.002 1898 3734 7676 16301 33929 64815 667.503 1900 3746 7706 16421 34422 64991 668.004 1917 3776 7824 16669 34782 65183 668.505 1933 3805 7911 16824 35257 65290 669.006 1969 3830 8027 17088 35578 65293 669.507 1970 3881 8134 17147 36042 65293 670.008 1990 3893 8218 17444 36266 65293 670.509 1992 3956 8344 17543 36787 65303 671.009 2027 3973 8445 17879 37220 65303 671.51 2055 4027 8445 17963 37706 65304 672.011 2111 4028 8531 18191 38095 65304 672.512 2114 4121 8534 18363 38517 65311 673.013 2114 4165 8714 18583 39003 65317 673.514 2114 4207 8808 18845 39302 65325 674.014 2114 4221 8890 19035 39804 65325 674.515 2114 4243 9002 19358 40311 65325 675.016 2147 4310 9108 19481 40692 65325 675.517 2159 4369 9133 19537 41203 65325 676.018 2163 4379 9247 19886 41757 65325 676.518 2189 4439 9380 20130 42033 65333 677.019 2189 4488 9454 20298 42733 65333 677.52 2219 4546 9532 20483 43208 65333 678.02 2242 4573 9630 20704 43559 65349 678.521 2256 4580 9705 21015 44171 65362 679.022 2284 4611 10103 21171 44601 65362 679.523 2288 4684 10103 21444 45060 65362 680.023 2301 4775 10103 21706 45592 65378 680.524 2356 4776 10292 21898 46068 65378 681.025 2367 4841 10308 22217 46681 65378 681.525 2389 4877 10432 22430 47262 65379 682.026 2441 4949 10492 22750 47646 65382 682.527 2441 4991 10683 22790 48184 65382 683.027 2453 5054 10828 23182 48889 65382 683.528 2453 5086 10886 23441 49358 65395 684.029 2478 5129 10972 23636 50060 65395 684.529 2490 5183 11147 24008 50584 65395 685.03 2519 5231 11229 24203 51056 65395 685.531 2533 5295 11353 24524 51621 65399 686.031 2567 5340 11491 24673 52055 65404 686.532 2583 5393 11681 24978 52592 65405 687.032 2589 5469 11752 25313 53377 65405 687.533 2630 5480 11852 25577 54010 65404 688.034 2644 5575 12027 25903 54775 65390 688.534 2645 5638 12086 26164 55973 65385 689.035 2674 5683 12286 26439 55973 65385 689.536 2733 5741 12460 26760 56237 65377 690.036 2748 5765 12602 27086 57175 65352 690.537 2772 5855 12729 27405 57682 65343 691.037 2780 5895 12843 27597 58445 65343 691.538 2812 5975 13004 27949 58992 65350 692.038 2872 6025 13036 28235 59502 65350 692.539 2877 6159 13246 28592 60256 65350 693.04 2894 6175 13424 28976 61042 65375 693.54 2932 6259 13532 29202 61566 65384 694.041 2944 6288 13655 29604 62153 65386 694.541 2964 6375 13811 29773 62801 65377 695.042 2993 6395 13981 30281 63374 65375 695.542 3040 6509 14156 30597 63727 65374 696.043 3096 6589 14305 30948 64104 65346 696.544 3113 6593 14475 31278 64439 65312 697.044 3125 6704 14591 31723 64637 65312 697.545 3130 6796 14788 31955 64868 65301 698.045 3161 6840 14898 32216 64977 65298 698.546 3204 6913 15063 32669 65189 65298 699.046 3217 6977 15261 32898 65281 65296 699.547 3275 7039 15429 33389 65281 65296 700.047 3307 7108 15539 33640 65286 65296 700.548 3317 7186 15699 34041 65291 65281 701.049 3352 7272 16022 34427 65291 65278 701.549 3382 7357 16103 34774 65293 65270 702.05 3400 7388 16314 35090 65298 65262 702.55 3464 7520 16427 35514 65302 65262 703.051 3498 7557 16594 35996 65302 65262 703.551 3508 7651 16754 36294 65318 65270 704.052 3558 7752 17032 36638 65318 65278 704.552 3586 7818 17123 37095 65318 65290 705.053 3590 7901 17298 37522 65318 65290 705.554 3637 7964 17562 37896 65318 65290 706.054 3672 8227 17693 38233 65321 65285 706.555 3742 8227 17890 38640 65321 65285 707.055 3821 8313 18096 39166 65321 65279 707.556 3821 8313 18226 39514 65321 65279 708.056 3833 8417 18377 39839 65321 65275 708.557 3833 8477 18727 40286 65322 65275 709.058 3895 8528 18799 40672 65338 65267 709.558 3924 8666 18952 41168 65338 65267 710.059 3928 8742 19130 41389 65342 65267 710.559 3989 8826 19358 42008 65342 65267 711.06 4025 8862 19516 42402 65343 65278 711.561 4058 8996 19705 42775 65343 65278 712.061 4112 9037 19912 43174 65355 65287 712.562 4143 9077 20138 43694 65359 65287 713.062 4153 9235 20361 43922 65359 65287 713.563 4202 9280 20544 44395 65359 65287 714.064 4251 9442 20695 44941 65365 65287 714.564 4288 9460 20936 45259 65368 65296 715.065 4355 9546 21038 45723 65368 65296 715.566 4394 9631 21289 46030 65368 65296 716.066 4394 9748 21641 46650 65373 65277 716.567 4462 9850 21644 47005 65373 65277 717.068 4469 9960 21960 47413 65373 65277 717.568 4471 10005 22132 47898 65373 65272 718.069 4536 10197 22355 48267 65376 65272 718.57 4592 10335 22609 48766 65376 65272 719.07 4645 10428 22783 49446 65376 65272 719.571 4701 10428 23050 49841 65376 65272 720.072 4731 10579 23273 50379 65376 65272 720.572 4797 10679 23539 50871 65376 65288 721.073 4806 10706 23738 51408 65366 65288 721.574 4888 10915 23964 51925 65366 65288 722.074 4915 10971 24221 52436 65366 65285 722.575 4943 11087 24416 52930 65366 65285 723.076 4977 11184 24757 53531 65366 65270 723.577 5057 11268 25005 54116 65328 65270 724.077 5102 11464 25321 54569 65326 65280 724.578 5161 11544 25528 55124 65326 65288 725.079 5223 11725 25688 55753 65326 65288 725.58 5255 11815 26113 56387 65337 65288 726.081 5292 11950 26313 56805 65341 65288 726.581 5386 12013 26520 57517 65345 65288 727.082 5399 12213 26905 57972 65380 65288 727.583 5505 12318 27198 58530 65380 65283 728.084 5534 12458 27465 59556 65380 65283 728.585 5615 12648 27774 59838 65363 65283 729.086 5674 12785 28110 60826 65340 65283 729.586 5741 12867 28380 61274 65340 65283 730.087 5762 13057 28739 62094 65340 65283 730.588 5856 13207 29152 62702 65301 65291 731.089 5920 13362 29540 63330 65296 65291 731.59 6016 13443 29744 63657 65295 65290 732.091 6049 13609 30208 64007 65290 65286 732.592 6124 13809 30434 64512 65288 65286 733.093 6200 13969 30830 64687 65288 65286 733.594 6296 14212 31293 64868 65284 65286 734.095 6307 14375 31650 65072 65284 65294 734.596 6417 14566 32095 65276 65284 65294 735.097 6476 14706 32467 65281 65284 65297 735.598 6581 14982 32884 65288 65284 65297 736.099 6711 15115 33199 65302 65284 65297 736.6 6733 15282 33728 65303 65271 65297 737.101 6831 15522 34005 65303 65265 65297 737.602 6890 15700 34610 65303 65262 65297 738.103 6921 15973 34946 65303 65262 65297 738.604 7033 16113 35440 65310 65262 65297 739.105 7180 16184 35859 65314 65274 65297 739.606 7234 16534 36202 65319 65274 65297 740.107 7295 16651 36692 65320 65274 65297 740.609 7372 16934 37153 65320 65274 65297 741.11 7478 17006 37599 65330 65266 65297 741.611 7593 17381 38125 65346 65264 65297 742.112 7718 17564 38965 65346 65264 65297 742.613 7752 17695 39221 65346 65264 65297 743.114 7886 17900 39366 65346 65279 65297 743.616 7968 18103 39842 65345 65279 65297 744.117 8047 18362 40243 65336 65279 65300 744.618 8084 18561 40769 65336 65280 65300 745.119 8253 18755 41211 65356 65280 65300 745.621 8307 18864 41504 65359 65280 65300 746.122 8386 19122 42094 65359 65280 65300 746.623 8445 19394 42366 65359 65291 65300 747.125 8500 19530 42986 65367 65291 65300 747.626 8652 19789 43377 65367 65291 65300 748.128 8776 19984 43857 65375 65291 65300 748.629 8816 20250 44404 65375 65286 65300 749.13 8949 20374 44910 65375 65286 65300 749.632 9010 20496 45168 65375 65286 65300 750.133 9118 20701 45790 65371 65286 65300 750.635 9198 21017 46247 65371 65286 65300 751.136 9329 21314 46739 65371 65283 65300 751.638 9394 21380 47287 65389 65283 65300 752.139 9527 21688 47598 65389 65283 65300 752.641 9614 21825 48309 65389 65283 65300 753.142 9666 22053 48607 65389 65283 65296 753.644 9797 22280 49150 65378 65297 65296 754.145 9875 22553 49634 65378 65297 65296 754.647 9983 22765 50181 65368 65297 65293 755.149 10008 23048 50567 65366 65297 65293 755.65 10197 23203 51151 65366 65291 65293 756.152 10270 23451 51477 65366 65268 65298 756.654 10428 23612 52065 65357 65268 65298 757.155 10503 23841 52589 65349 65268 65298 757.657 10672 24163 53194 65346 65282 65298 758.159 10681 24402 53579 65314 65282 65295 758.661 10821 24675 54134 65311 65296 65295 759.163 10940 24849 54500 65311 65296 65295 759.664 11021 25240 55071 65313 65296 65295 760.166 11157 25436 55676 65314 65296 65295 760.668 11186 25568 56223 65322 65296 65291 761.17 11416 25897 56767 65355 65296 65291 761.672 11501 26159 57257 65361 65292 65291 762.174 11560 26484 57822 65361 65292 65291 762.676 11756 26630 58460 65342 65290 65291 763.178 11768 26894 58685 65342 65287 65291 763.68 11907 27079 59498 65342 65287 65291 764.182 12090 27406 60025 65336 65287 65300 764.684 12233 27556 60564 65309 65285 65300 765.186 12242 27878 60964 65309 65284 65316 765.688 12459 28136 61466 65308 65284 65316 766.19 12513 28399 62166 65298 65282 65316 766.692 12606 28706 62672 65285 65271 65283 767.194 12863 28864 63139 65273 65271 65283 767.697 12863 29164 63412 65273 65279 65305 768.199 12959 29377 63793 65273 65285 65307 768.701 13173 29671 64132 65273 65285 65307 769.203 13233 30071 64401 65273 65288 65307 769.706 13316 30297 64554 65273 65299 65307 770.208 13502 30594 64697 65275 65299 65307 770.71 13593 30905 64814 65275 65299 65307 771.213 13704 31124 64992 65277 65299 65307 771.715 13790 31395 65107 65288 65299 65307 772.217 13963 31604 65222 65292 65295 65305 772.72 14031 31858 65232 65292 65290 65305 773.222 14263 32236 65263 65282 65285 65303 773.725 14380 32624 65263 65278 65275 65303 774.227 14504 33033 65263 65265 65275 65303 774.73 14684 33260 65272 65265 65275 65303 775.232 14778 33459 65276 65265 65296 65303 775.735 15165 33678 65276 65265 65296 65291 776.238 15165 33919 65276 65265 65296 65291 776.74 15301 34317 65276 65265 65296 65291 777.243 15466 34633 65276 65265 65296 65291 777.746 15474 35133 65276 65265 65293 65297 778.248 15719 35387 65288 65265 65288 65306 778.751 15775 35758 65288 65268 65278 65306 779.254 15929 35896 65288 65277 65278 65295 779.757 15991 36141 65288 65277 65278 65295 780.26 16132 36499 65289 65286 65278 65295 780.763 16339 36908 65290 65286 65282 65295 781.266 16516 37266 65290 65286 65283 65319 781.768 16732 37794 65313 65271 65283 65320 782.271 16898 38078 65315 65271 65283 65320 782.774 16914 38166 65315 65271 65289 65304 783.277 17090 38513 65322 65282 65289 65296 783.781 17178 38817 65322 65282 65289 65296 784.284 17284 39220 65322 65287 65289 65309 784.787 17664 39698 65324 65287 65291 65317 785.29 17755 40054 65329 65287 65293 65319 785.793 17893 40420 65329 65287 65293 65319 786.296 18094 40750 65329 65287 65294 65319 786.799 18227 40964 65329 65287 65294 65319 787.303 18344 41240 65329 65287 65298 65319 787.806 18474 41606 65329 65300 65299 65311 788.309 18650 41927 65329 65300 65299 65307 788.813 18733 42415 65343 65300 65301 65305 789.316 19017 42612 65344 65300 65303 65294 789.82 19122 43225 65344 65285 65303 65294 790.323 19352 43456 65344 65285 65303 65294 790.827 19459 43794 65344 65285 65302 65294 791.33 19711 44030 65343 65285 65302 65305 791.834 19818 44334 65343 65287 65296 65307 792.337 19932 44829 65343 65287 65289 65307 792.841 20133 45115 65342 65287 65289 65308 793.345 20253 45537 65342 65287 65289 65323 793.848 20571 46061 65346 65287 65289 65328 794.352 20693 46667 65356 65287 65299 65328 794.856 20915 46836 65356 65287 65301 65328 795.359 21093 47302 65356 65287 65296 65328 795.863 21157 47406 65356 65287 65296 65323 796.367 21249 47690 65356 65287 65296 65318 796.871 21437 48030 65356 65293 65296 65316 797.375 21640 48588 65356 65293 65296 65312 797.879 21852 48888 65352 65293 65296 65312 798.383 22113 50178 65351 65293 65313 65300 798.887 22635 50184 65348 65293 65313 65300 799.391 22748 50548 65348 65293 65313 65300 799.895 22748 50664 65348 65293 65301 65300 800.399 22823 51076 65348 65293 65301 65300 800.904 22868 51283 65348 65293 65301 65312 801.408 23171 51911 65340 65281 65301 65322 801.912 23470 52389 65340 65281 65311 65322 802.416 23651 52911 65340 65281 65311 65322 802.921 23827 53395 65309 65281 65311 65322 803.425 24001 53808 65300 65281 65311 65313 803.929 24257 53994 65293 65281 65311 65313 804.434 24399 54470 65293 65294 65311 65313 804.938 24566 54877 65293 65294 65311 65313 805.443 24845 55414 65293 65294 65311 65313 805.947 25078 55813 65306 65294 65311 65308 806.452 25414 56408 65319 65294 65303 65308 806.957 25582 57003 65323 65294 65303 65308 807.461 25787 57484 65327 65292 65303 65308 807.966 25913 57835 65340 65292 65303 65320 808.471 26151 58209 65340 65292 65303 65320 808.975 26376 58802 65338 65292 65303 65320 809.48 26543 59002 65338 65280 65303 65320 809.985 26767 59588 65338 65275 65303 65320 810.49 26968 60062 65304 65275 65303 65320 810.995 27204 60470 65304 65275 65303 65332 811.5 27457 61322 65299 65283 65303 65332 812.005 27670 61640 65299 65283 65303 65326 812.51 27859 61998 65299 65283 65311 65326 813.015 28141 62586 65291 65301 65311 65326 813.52 28388 62926 65291 65301 65311 65326 814.026 28439 63174 65291 65301 65311 65323 814.531 28752 63589 65291 65301 65311 65323 815.036 29112 63756 65291 65298 65308 65323 815.541 29291 64176 65291 65293 65308 65323 816.047 29522 64529 65285 65293 65308 65323 816.552 29819 64657 65282 65293 65308 65323 817.057 30054 64657 65280 65291 65308 65315 817.563 30322 64806 65280 65291 65308 65315 818.068 30510 64933 65280 65291 65308 65315 818.574 30797 65028 65272 65292 65308 65315 819.08 30962 65219 65272 65292 65308 65315 819.585 31063 65254 65275 65292 65307 65327 820.091 31353 65254 65283 65292 65307 65327 820.597 31610 65257 65287 65316 65307 65327 821.102 31912 65257 65287 65316 65298 65327 821.608 32174 65261 65282 65290 65298 65327 822.114 32509 65261 65267 65288 65298 65334 822.62 32750 65261 65267 65288 65298 65337 823.126 33016 65261 65267 65288 65298 65337 > > ##plot spectrum > ## Not run: > ##D plot_RLum(TL.Spectrum) > ## End(Not run) > > > > > cleanEx() > nameEx("RLum.Results-class") > ### * RLum.Results-class > > flush(stderr()); flush(stdout()) > > ### Name: RLum.Results-class > ### Title: Class '"RLum.Results"' > ### Aliases: RLum.Results-class > ### Keywords: classes methods > > ### ** Examples > > > showClass("RLum.Results") Class "RLum.Results" [package "Luminescence"] Slots: Name: data originator info .uid .pid Class: list character list character character Extends: "RLum" > > ##create an empty object from this class > set_RLum(class = "RLum.Results") [RLum.Results-class] originator: NA() data: 0 .. $ : list additional info elements: 0 > > ##use another function to show how it works > > ##Basic calculation of the dose rate for a specific date > dose.rate <- calc_SourceDoseRate( + measurement.date = "2012-01-27", + calib.date = "2014-12-19", + calib.dose.rate = 0.0438, + calib.error = 0.0019) > > ##show object > dose.rate [RLum.Results-class] originator: calc_SourceDoseRate() data: 3 .. $dose.rate : data.frame .. $parameters : list .. $call : call additional info elements: 0 > > ##get results > get_RLum(dose.rate) dose.rate dose.rate.error date 1 0.04694815 0.002036563 2012-01-27 > > ##get parameters used for the calcualtion from the same object > get_RLum(dose.rate, data.object = "parameters") $source.type [1] "Sr-90" $halflife [1] 28.9 $dose.rate.unit [1] "Gy/s" > > ##alternatively objects can be accessed using S3 generics, such as > dose.rate$parameters $source.type [1] "Sr-90" $halflife [1] 28.9 $dose.rate.unit [1] "Gy/s" > > > > > cleanEx() > nameEx("Risoe.BINfileData-class") > ### * Risoe.BINfileData-class > > flush(stderr()); flush(stdout()) > > ### Name: Risoe.BINfileData-class > ### Title: Class '"Risoe.BINfileData"' > ### Aliases: Risoe.BINfileData-class set_Risoe.BINfileData,ANY-method > ### Keywords: classes > > ### ** Examples > > > showClass("Risoe.BINfileData") Class "Risoe.BINfileData" [package "Luminescence"] Slots: Name: METADATA DATA .RESERVED Class: data.frame list list > > > > > cleanEx() > nameEx("Risoe.BINfileData2RLum.Analysis") > ### * Risoe.BINfileData2RLum.Analysis > > flush(stderr()); flush(stdout()) > > ### Name: Risoe.BINfileData2RLum.Analysis > ### Title: Convert Risoe.BINfileData object to an RLum.Analysis object > ### Aliases: Risoe.BINfileData2RLum.Analysis > ### Keywords: manip > > ### ** Examples > > > ##load data > data(ExampleData.BINfileData, envir = environment()) > > ##convert values for position 1 > Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos = 1) > > > > > cleanEx() > nameEx("analyse_Al2O3C_CrossTalk") > ### * analyse_Al2O3C_CrossTalk > > flush(stderr()); flush(stdout()) > > ### Name: analyse_Al2O3C_CrossTalk > ### Title: Al2O3:C Reader Cross-Talk Analysis > ### Aliases: analyse_Al2O3C_CrossTalk > ### Keywords: datagen > > ### ** Examples > > > ##load data > data(ExampleData.Al2O3C, envir = environment()) > > ##run analysis > analyse_Al2O3C_CrossTalk(data_CrossTalk) [RLum.Results-class] originator: analyse_Al2O3C_CrossTalk() data: 4 .. $data : data.frame .. $data_full : data.frame .. $fit : lm .. $col.seq : character additional info elements: 1 > > > > > cleanEx() > nameEx("analyse_Al2O3C_ITC") > ### * analyse_Al2O3C_ITC > > flush(stderr()); flush(stdout()) > > ### Name: analyse_Al2O3C_ITC > ### Title: Al2O3 Irradiation Time Correction Analysis > ### Aliases: analyse_Al2O3C_ITC > ### Keywords: datagen > > ### ** Examples > > > ##load data > data(ExampleData.Al2O3C, envir = environment()) > > ##run analysis > analyse_Al2O3C_ITC(data_ITC) [analyse_Al2O3C_ITC()] Used fit method: EXP Time correction value: 2.587 ± 0.035 [RLum.Results-class] originator: analyse_Al2O3C_ITC() data: 4 .. $data : data.frame .. $table : data.frame .. $table_mean : data.frame .. $fit : nls additional info elements: 1 > > > > > cleanEx() > nameEx("analyse_Al2O3C_Measurement") > ### * analyse_Al2O3C_Measurement > > flush(stderr()); flush(stdout()) > > ### Name: analyse_Al2O3C_Measurement > ### Title: Al2O3:C Passive Dosimeter Measurement Analysis > ### Aliases: analyse_Al2O3C_Measurement > ### Keywords: datagen > > ### ** Examples > > ##load data > data(ExampleData.Al2O3C, envir = environment()) > > ##run analysis > analyse_Al2O3C_Measurement(data_CrossTalk) Warning: [analyse_Al2O3C_Measurement()] TL peak shift detected for aliquot position 1, check the curves [analyse_Al2O3_Measurement()] #1 DE: 0 ± 0 ... (#1 | ALQ POS: 1) [analyse_Al2O3_Measurement()] #2 DE: 0 ± 0 ... (#2 | ALQ POS: 2) [RLum.Results-class] originator: analyse_Al2O3C_Measurement() data: 3 .. $data : data.frame .. $data_table : data.frame .. $test_parameters : data.frame additional info elements: 1 > > > > > cleanEx() > nameEx("analyse_FadingMeasurement") > ### * analyse_FadingMeasurement > > flush(stderr()); flush(stdout()) > > ### Name: analyse_FadingMeasurement > ### Title: Analyse fading measurements and returns the fading rate per > ### decade (g-value) > ### Aliases: analyse_FadingMeasurement > ### Keywords: datagen > > ### ** Examples > > > ## load example data (sample UNIL/NB123, see ?ExampleData.Fading) > data("ExampleData.Fading", envir = environment()) > > ##(1) get fading measurement data (here a three column data.frame) > fading_data <- ExampleData.Fading$fading.data$IR50 > > ##(2) run analysis > g_value <- analyse_FadingMeasurement( + fading_data, + plot = TRUE, + verbose = TRUE, + n.MC = 10) [analyse_FadingMeasurement()] n.MC: 10 tc: 3.78e+02 s --------------------------------------------------- T_0.5 interpolated: NA T_0.5 predicted: 4e+11 g-value: 5.18 ± 0.67 (%/decade) g-value (norm. 2 days): 6.01 ± 0.68 (%/decade) --------------------------------------------------- rho': 3.79e-06 ± 8.17e-07 log10(rho'): -5.42 ± 0.09 --------------------------------------------------- > > ##(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) [calc_FadingCorr()] >> Fading correction according to Huntley & Lamothe (2001) .. used g-value: 5.182 ± 0.667 %/decade .. used tc: 1.198e-08 ka .. used kappa: 0.0225 ± 0.0029 ---------------------------------------------- seed: NA n.MC: 10 observations: 10 ---------------------------------------------- Age (faded): 100 ka ± 2 ka Age (corr.): 203.0812 ka ± 57.9552 ka ---------------------------------------------- > > > > > cleanEx() > nameEx("analyse_IRSAR.RF") > ### * analyse_IRSAR.RF > > flush(stderr()); flush(stdout()) > > ### Name: analyse_IRSAR.RF > ### Title: Analyse IRSAR RF measurements > ### Aliases: analyse_IRSAR.RF > ### Keywords: datagen > > ### ** Examples > > > ##load data > data(ExampleData.RLum.Analysis, envir = environment()) > > ##(1) perform analysis using the method 'FIT' > results <- analyse_IRSAR.RF(object = IRSAR.RF.Data) > > ##show De results and test parameter results > get_RLum(results, data.object = "data") DE DE.ERROR DE.LOWER DE.UPPER DE.STATUS RF_NAT.LIM RF_REG.LIM POSITION 1 623.25 NA 600.63 635.8 OK 1:5 1:524 NA DATE SEQUENCE_NAME UID 1 NA NA 4b01e2c7d11c526f > get_RLum(results, data.object = "test_parameters") POSITION PARAMETER THRESHOLD VALUE STATUS SEQUENCE_NAME 1 NA curves_ratio 1.001 6.845685e-01 OK NA 2 NA intersection_ratio NA 5.541736e-03 OK NA 3 NA residuals_slope NA NA OK NA 4 NA curves_bounds 716.000 6.358000e+02 OK NA 5 NA dynamic_ratio NA 1.524261e+00 OK NA 6 NA lambda NA 2.182234e-04 OK NA 7 NA beta NA 5.418718e-01 OK NA 8 NA delta.phi NA 2.103400e+03 OK NA UID 1 4b01e2c7d11c526f 2 4b01e2c7d11c526f 3 4b01e2c7d11c526f 4 4b01e2c7d11c526f 5 4b01e2c7d11c526f 6 4b01e2c7d11c526f 7 4b01e2c7d11c526f 8 4b01e2c7d11c526f > > ##(2) perform analysis using the method 'SLIDE' > data(ExampleData.RF70Curves, envir = environment()) > results <- analyse_IRSAR.RF( + object = RF70Curves, + method = "SLIDE", + n.MC = 1) ==1390668== Conditional jump or move depends on uninitialised value(s) ==1390668== at 0x17CC245E: analyse_IRSARRF_SRS (packages/tests-vg/Luminescence/src/src_analyse_IRSARRF_SRS.cpp:84) ==1390668== by 0x17CB49EC: _Luminescence_analyse_IRSARRF_SRS (packages/tests-vg/Luminescence/src/RcppExports.cpp:67) ==1390668== by 0x4A7FCD: R_doDotCall (svn/R-devel/src/main/dotcode.c:766) ==1390668== by 0x4E2083: bcEval_loop (svn/R-devel/src/main/eval.c:8682) ==1390668== by 0x4F21D7: bcEval (svn/R-devel/src/main/eval.c:7515) ==1390668== by 0x4F21D7: bcEval (svn/R-devel/src/main/eval.c:7500) ==1390668== by 0x4F250A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==1390668== by 0x4F428D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==1390668== by 0x4F4F46: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==1390668== by 0x4F781E: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==1390668== by 0x4F781E: R_forceAndCall (svn/R-devel/src/main/eval.c:2456) ==1390668== by 0x42C17E: do_lapply (svn/R-devel/src/main/apply.c:75) ==1390668== by 0x53AF14: do_internal (svn/R-devel/src/main/names.c:1411) ==1390668== by 0x4E3EB1: bcEval_loop (svn/R-devel/src/main/eval.c:8152) ==1390668== Uninitialised value was created by a stack allocation ==1390668== at 0x17CC226A: analyse_IRSARRF_SRS (packages/tests-vg/Luminescence/src/src_analyse_IRSARRF_SRS.cpp:34) ==1390668== ==1390668== Use of uninitialised value of size 8 ==1390668== at 0x17CC2469: analyse_IRSARRF_SRS (packages/tests-vg/Luminescence/src/src_analyse_IRSARRF_SRS.cpp:84) ==1390668== by 0x17CB49EC: _Luminescence_analyse_IRSARRF_SRS (packages/tests-vg/Luminescence/src/RcppExports.cpp:67) ==1390668== by 0x4A7FCD: R_doDotCall (svn/R-devel/src/main/dotcode.c:766) ==1390668== by 0x4E2083: bcEval_loop (svn/R-devel/src/main/eval.c:8682) ==1390668== by 0x4F21D7: bcEval (svn/R-devel/src/main/eval.c:7515) ==1390668== by 0x4F21D7: bcEval (svn/R-devel/src/main/eval.c:7500) ==1390668== by 0x4F250A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==1390668== by 0x4F428D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==1390668== by 0x4F4F46: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==1390668== by 0x4F781E: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==1390668== by 0x4F781E: R_forceAndCall (svn/R-devel/src/main/eval.c:2456) ==1390668== by 0x42C17E: do_lapply (svn/R-devel/src/main/apply.c:75) ==1390668== by 0x53AF14: do_internal (svn/R-devel/src/main/names.c:1411) ==1390668== by 0x4E3EB1: bcEval_loop (svn/R-devel/src/main/eval.c:8152) ==1390668== Uninitialised value was created by a stack allocation ==1390668== at 0x17CC226A: analyse_IRSARRF_SRS (packages/tests-vg/Luminescence/src/src_analyse_IRSARRF_SRS.cpp:34) ==1390668== Run Monte Carlo loops for error estimation | | | 0% | |======================================================================| 100% Warning: [analyse_IRSAR.RF()] Narrow density distribution, no density distribution plotted > > ## Not run: > ##D ##(3) perform analysis using the method 'VSLIDE' and method control option > ##D ## 'trace > ##D results <- analyse_IRSAR.RF( > ##D object = RF70Curves, > ##D method = "VSLIDE", > ##D method_control = list(trace = TRUE)) > ## End(Not run) > > > > > cleanEx() > nameEx("analyse_SAR.CWOSL") > ### * analyse_SAR.CWOSL > > flush(stderr()); flush(stdout()) > > ### Name: analyse_SAR.CWOSL > ### Title: Analyse SAR CW-OSL Measurements > ### Aliases: analyse_SAR.CWOSL > ### Keywords: datagen plot > > ### ** Examples > > > ##load data > ##ExampleData.BINfileData contains two BINfileData objects > ##CWOSL.SAR.Data and TL.SAR.Data > data(ExampleData.BINfileData, envir = environment()) > > ##transform the values from the first position in a RLum.Analysis object > object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > > ##perform SAR analysis and set rejection criteria > results <- analyse_SAR.CWOSL( + object = object, + signal_integral = 1:2, + background_integral = 900:1000, + log = "x", + fit.method = "EXP", + plot_onePage = TRUE, + rejection.criteria = list( + recycling.ratio = 10, + recuperation.rate = 10, + testdose.error = 10, + palaeodose.error = 10, + recuperation_reference = "Natural", + sn.ratio = 50, + sn_reference = "Natural", + exceed.max.regpoint = TRUE) + ) [analyse_SAR.CWOSL()] Fit: EXP (interpolation) | De = 1668.25 | D01 = 1982.76 > > ##show De results > get_RLum(results) De De.Error D01 D01.ERROR D02 D02.ERROR R R.ERROR Dc D63 1 1668.251 48.03113 1982.757 101.2798 NA NA NA NA NA NA n_N De.MC Fit Mode HPDI68_L HPDI68_U HPDI95_L HPDI95_U 1 0.4854696 1671.327 EXP interpolation 1618.305 1717.205 1571.654 1771.32 .De.plot .De.raw RC.Status signal.range background.range signal.range.Tx 1 1668.251 1668.251 OK 1:2 900:1000 NA:NA background.range.Tx ALQ POS GRAIN UID 1 NA:NA 1 1 0 f5901d874c43a377 > > ##show LnTnLxTx table > get_RLum(results, data.object = "LnLxTnTx.table") Name Repeated Dose LnLx LnLx.BG TnTx TnTx.BG Net_LnLx 1 Natural FALSE 0 20391 60.15842 4771 73.50495 20330.84158 2 R1 FALSE 450 7591 65.70297 4977 81.56436 7525.29703 3 R2 FALSE 1050 15150 96.17822 4960 101.92079 15053.82178 4 R3 FALSE 2000 23700 118.49505 5064 121.06931 23581.50495 5 R4 FALSE 2550 31094 155.92079 5715 145.84158 30938.07921 6 R5 TRUE 450 9376 122.37624 5860 127.60396 9253.62376 7 R0 FALSE 0 192 94.39604 6107 117.64356 97.60396 Net_LnLx.Error Net_TnTx Net_TnTx.Error SN_RATIO_LnLx SN_RATIO_TnTx LxTx 1 143.03415 4697.495 69.24882 338.955069 64.90719 4.32801767 2 87.39498 4895.436 71.06916 115.535112 61.01930 1.53720681 3 123.18402 4858.079 71.66840 157.520074 48.66524 3.09871888 4 154.46828 4942.931 72.07168 200.008356 41.82728 4.77075371 5 176.39564 5569.158 75.88226 199.421768 39.18635 5.55525214 6 97.54912 5732.396 77.37976 76.616181 45.92334 1.61426805 7 14.86509 5989.356 78.87190 2.033984 51.91104 0.01629624 LxTx.Error Test_Dose UID 1 0.070695494 -1 f5901d874c43a377 2 0.028578369 -1 f5901d874c43a377 3 0.052275097 -1 f5901d874c43a377 4 0.076258410 -1 f5901d874c43a377 5 0.082052531 -1 f5901d874c43a377 6 0.027647946 -1 f5901d874c43a377 7 0.002491179 -1 f5901d874c43a377 > > ## Run example with special case for > ## the OTORX fit > ## Not run: > ##D results <- analyse_SAR.CWOSL( > ##D object = object, > ##D signal_integral = 1:2, > ##D background_integral = 900:1000, > ##D dose.points.test = 15, > ##D n.MC = 10, > ##D fit.method = "OTORX") > ## End(Not run) > > > > > cleanEx() > nameEx("analyse_SAR.TL") > ### * analyse_SAR.TL > > flush(stderr()); flush(stdout()) > > ### Name: analyse_SAR.TL > ### Title: Analyse SAR TL measurements > ### Aliases: analyse_SAR.TL > ### Keywords: datagen plot > > ### ** Examples > > > ##load data > data(ExampleData.BINfileData, envir = environment()) > > ##transform the values from the first position in a RLum.Analysis object > object <- Risoe.BINfileData2RLum.Analysis(TL.SAR.Data, pos=3) > > ##perform analysis > analyse_SAR.TL( + object = object, + signal_integral = 210:220, + fit.method = "EXP OR LIN", + sequence.structure = c("SIGNAL", "BACKGROUND")) [fit_DoseResponseCurve()] Fit: EXP OR LIN (interpolation) | De = 415.66 | D01 = 7071425.97 [RLum.Results-class] originator: analyse_SAR.TL() data: 3 .. $data : data.frame .. $LnLxTnTx.table : data.frame .. $rejection.criteria : data.frame additional info elements: 1 > > > > > cleanEx() > nameEx("analyse_baSAR") > ### * analyse_baSAR > > flush(stderr()); flush(stdout()) > > ### Name: analyse_baSAR > ### Title: Bayesian models (baSAR) applied on luminescence data > ### Aliases: analyse_baSAR > ### Keywords: datagen > > ### ** Examples > > > ##(1) load package test data set > data(ExampleData.BINfileData, envir = environment()) > > ##(2) selecting relevant curves, and limit dataset > CWOSL.SAR.Data <- subset( + CWOSL.SAR.Data, + subset = POSITION%in%c(1:3) & LTYPE == "OSL") > > ## Not run: > ##D ##(3) run analysis > ##D ## please note that the parameters used here are > ##D ## chosen for performance, not for reliability > ##D results <- analyse_baSAR( > ##D object = CWOSL.SAR.Data, > ##D source_doserate = c(0.04, 0.001), > ##D signal_integral = 1:2, > ##D background_integral = 80:100, > ##D fit.method = "LIN", > ##D plot = FALSE, > ##D n.MCMC = 200 > ##D ) > ##D > ##D print(results) > ##D > ##D ##CSV_file template > ##D ##copy and paste this the code below in the terminal > ##D ##you can further use the function write.csv() to export the example > ##D > ##D CSV_file <- > ##D structure( > ##D list( > ##D BIN_FILE = NA_character_, > ##D DISC = NA_real_, > ##D GRAIN = NA_real_), > ##D .Names = c("BIN_FILE", "DISC", "GRAIN"), > ##D class = "data.frame", > ##D row.names = 1L) > ## End(Not run) > > > > > cleanEx() > nameEx("analyse_pIRIRSequence") > ### * analyse_pIRIRSequence > > flush(stderr()); flush(stdout()) > > ### Name: analyse_pIRIRSequence > ### Title: Analyse post-IR IRSL measurement sequences > ### Aliases: analyse_pIRIRSequence > ### Keywords: datagen plot > > ### ** Examples > > > ### NOTE: For this example existing example data are used. These data are non pIRIR data. > ### > ##(1) Compile example data set based on existing example data (SAR quartz measurement) > ##(a) Load example data > data(ExampleData.BINfileData, envir = environment()) > > ##(b) Transform the values from the first position in a RLum.Analysis object > object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > > ##(c) Grep curves and exclude the last two (one TL and one IRSL) > object <- get_RLum(object, record.id = c(-29,-30)) > > ##(d) Define new sequence structure and set new RLum.Analysis object > sequence.structure <- c(1,2,2,3,4,4) > sequence.structure <- as.vector(sapply(seq(0,length(object)-1,by = 4), + function(x){sequence.structure + x})) > > object <- sapply(1:length(sequence.structure), function(x){ + object[[sequence.structure[x]]] + }) > > object <- set_RLum(class = "RLum.Analysis", records = object, protocol = "pIRIR") > > ##(2) Perform pIRIR analysis (for this example with quartz OSL data!) > ## Note: output as single plots to avoid problems with this example > results <- analyse_pIRIRSequence(object, + signal_integral = 1:2, + background_integral = 900:1000, + fit.method = "EXP", + sequence.structure = c("TL", "pseudoIRSL1", "pseudoIRSL2"), + main = "Pseudo pIRIR data set based on quartz OSL", + plot_singlePanels = TRUE) [analyse_SAR.CWOSL()] Fit: EXP (interpolation) | De = 1668.25 | D01 = 1982.76 [analyse_SAR.CWOSL()] Fit: EXP (interpolation) | De = 1668.25 | D01 = 1982.76 > > > ##(3) Perform pIRIR analysis (for this example with quartz OSL data!) > ## Alternative for PDF output, uncomment and complete for usage > ## Not run: > ##D tempfile <- tempfile(fileext = ".pdf") > ##D pdf(file = tempfile, height = 18, width = 18) > ##D results <- analyse_pIRIRSequence(object, > ##D signal_integral = 1:2, > ##D background_integral = 900:1000, > ##D fit.method = "EXP", > ##D main = "Pseudo pIRIR data set based on quartz OSL") > ##D > ##D dev.off() > ## End(Not run) > > > > > cleanEx() > nameEx("analyse_portableOSL") > ### * analyse_portableOSL > > flush(stderr()); flush(stdout()) > > ### Name: analyse_portableOSL > ### Title: Analyse portable CW-OSL measurements > ### Aliases: analyse_portableOSL > ### Keywords: datagen plot > > ### ** Examples > > > ## example profile plot > # (1) load example data set > data("ExampleData.portableOSL", envir = environment()) > > # (2) merge and plot all RLum.Analysis objects > merged <- merge_RLum(ExampleData.portableOSL) > plot_RLum( + object = merged, + combine = TRUE, + records_max = 5, + legend.pos = "outside") > merged [RLum.Analysis-class] originator: merge_RLum.Analysis() protocol: portable OSL additional info elements: 196 number of records: 70 .. : RLum.Data.Curve : 70 .. .. : #1 USER (PMT) | #2 IRSL (PMT) | #3 USER (PMT) | #4 OSL (PMT) | #5 USER (PMT) | #6 USER (PMT) | #7 IRSL (PMT) .. .. : #8 USER (PMT) | #9 OSL (PMT) | #10 USER (PMT) | #11 USER (PMT) | #12 IRSL (PMT) | #13 USER (PMT) | #14 OSL (PMT) .. .. : #15 USER (PMT) | #16 USER (PMT) | #17 IRSL (PMT) | #18 USER (PMT) | #19 OSL (PMT) | #20 USER (PMT) | #21 USER (PMT) .. .. : #22 IRSL (PMT) | #23 USER (PMT) | #24 OSL (PMT) | #25 USER (PMT) | #26 USER (PMT) | #27 IRSL (PMT) | #28 USER (PMT) .. .. : #29 OSL (PMT) | #30 USER (PMT) | #31 USER (PMT) | #32 IRSL (PMT) | #33 USER (PMT) | #34 OSL (PMT) | #35 USER (PMT) .. .. : #36 USER (PMT) | #37 IRSL (PMT) | #38 USER (PMT) | #39 OSL (PMT) | #40 USER (PMT) | #41 USER (PMT) | #42 IRSL (PMT) .. .. : #43 USER (PMT) | #44 OSL (PMT) | #45 USER (PMT) | #46 USER (PMT) | #47 IRSL (PMT) | #48 USER (PMT) | #49 OSL (PMT) .. .. : #50 USER (PMT) | #51 USER (PMT) | #52 IRSL (PMT) | #53 USER (PMT) | #54 OSL (PMT) | #55 USER (PMT) | #56 USER (PMT) .. .. : #57 IRSL (PMT) | #58 USER (PMT) | #59 OSL (PMT) | #60 USER (PMT) | #61 USER (PMT) | #62 IRSL (PMT) | #63 USER (PMT) .. .. : #64 OSL (PMT) | #65 USER (PMT) | #66 USER (PMT) | #67 IRSL (PMT) | #68 USER (PMT) | #69 OSL (PMT) | #70 USER (PMT) > > # (3) analyse and plot > results <- analyse_portableOSL( + merged, + signal_integral = 1:5, + invert = FALSE, + normalise = TRUE) > get_RLum(results) ID RUN BSL BSL_error IRSL IRSL_error BSL_depletion 11 11 ALU 1.63105170 0.0025284109 1.40432450 0.0049269556 0.8899796 4 4 ALU 0.39980864 0.0012483733 0.42331051 0.0027004844 1.0490701 9 9 ALU 2.09649886 0.0028644330 2.08440551 0.0060688839 0.9090499 8 8 ALU 0.27824348 0.0010434799 0.39608610 0.0026434540 1.1796670 13 13 ALU 0.08261577 0.0005690871 0.06579380 0.0010890682 1.0486319 10 10 ALU 2.12595947 0.0028889095 2.17793540 0.0062025491 0.9572100 1 1 ALU 0.66751034 0.0016178539 0.69677206 0.0035040643 0.8675537 7 7 ALU 1.10402143 0.0020801568 0.95869456 0.0041114642 0.9922993 14 14 ALU 0.03332815 0.0003606878 0.03255285 0.0007974928 1.0492829 5 5 ALU 1.91016028 0.0027332907 1.93584455 0.0058476153 0.9097980 2 2 ALU 1.33608934 0.0022884430 1.43034913 0.0050268167 0.8811300 3 3 ALU 0.35999022 0.0011869945 0.45413426 0.0028330832 1.1992200 12 12 ALU 0.10425127 0.0006390972 0.10266938 0.0013732741 1.1011572 6 6 ALU 1.87047105 0.0027051257 1.83712738 0.0056976151 0.9659504 IRSL_depletion IRSL_BSL_RATIO DARK DARK_error COORD_X COORD_Y 11 1.0160485 0.8609933 0.2666667 11.993180 0.27724979 0.0005183129 4 1.0190504 1.0587828 -0.1555556 8.355607 0.58580031 0.0089457957 9 0.9673997 0.9942316 -2.6444444 11.790126 0.22160140 0.0242339098 8 0.9835481 1.4235234 0.5333333 7.322444 0.46629524 0.2078233170 13 1.1398779 0.7963831 1.0222222 6.471929 0.71032245 0.2461373017 10 0.9799674 1.0244482 1.4000000 12.498000 0.50747820 0.3067685061 1 0.9158216 1.0438371 1.1111111 8.568500 0.26550866 0.3721238996 7 1.0143051 0.8683659 -2.8888889 11.954882 0.98890930 0.3977454533 14 1.0740241 0.9767372 -1.0666667 4.750120 0.25403373 0.6378272984 5 0.9352608 1.0134461 -7.5333333 39.122535 0.20021445 0.6852185957 2 0.9087895 1.0705490 -0.8222222 12.384537 0.18488226 0.7023740360 3 1.0233685 1.2615183 -0.2444444 8.931954 0.16804153 0.8075163991 12 1.0718821 0.9848262 -6.4222222 38.856665 0.06936092 0.8177751987 6 0.9506562 0.9821737 0.5111111 14.822621 0.60626830 0.9376419729 > > > > > cleanEx() > nameEx("apply_CosmicRayRemoval") > ### * apply_CosmicRayRemoval > > flush(stderr()); flush(stdout()) > > ### Name: apply_CosmicRayRemoval > ### Title: Cosmic-ray removal and spectrum smoothing for RLum.Data.Spectrum > ### objects > ### Aliases: apply_CosmicRayRemoval > ### Keywords: manip > > ### ** Examples > > > ##(1) - use with your own data and combine (uncomment for usage) > ## run two times the default method and smooth with another method > ## your.spectrum <- apply_CosmicRayRemoval(your.spectrum, method = "Pych") > ## your.spectrum <- apply_CosmicRayRemoval(your.spectrum, method = "Pych") > ## your.spectrum <- apply_CosmicRayRemoval(your.spectrum, method = "smooth") > > > > > cleanEx() > nameEx("apply_Crosstalk") > ### * apply_Crosstalk > > flush(stderr()); flush(stdout()) > > ### Name: apply_Crosstalk > ### Title: Apply crosstalk > ### Aliases: apply_Crosstalk > ### Keywords: manip > > ### ** Examples > > ## Create artificial disc observation > observations <- set_RLum(class = "RLum.Results", + data = list(vn_values = rep(x = c(1,2), each = 50)) + ) > hist(get_RLum(object = observations)) > > ## Add crosstalk (with default set to 0.2), and visualize the difference > ## in the resulting histogram. > observations_with_simulated_crosstalk <- apply_Crosstalk(observations) > hist(observations_with_simulated_crosstalk) > > > > > cleanEx() > nameEx("apply_EfficiencyCorrection") > ### * apply_EfficiencyCorrection > > flush(stderr()); flush(stdout()) > > ### Name: apply_EfficiencyCorrection > ### Title: Apply spectral efficiency correction to RLum.Data.Spectrum > ### objects > ### Aliases: apply_EfficiencyCorrection > ### Keywords: manip > > ### ** Examples > > > ##(1) - use with your own data (uncomment for usage) > ## spectral.efficiency <- read.csv("your data") > ## > ## your.spectrum <- apply_EfficiencyCorrection(your.spectrum, ) > > > > > cleanEx() > nameEx("bin_RLum.Data") > ### * bin_RLum.Data > > flush(stderr()); flush(stdout()) > > ### Name: bin_RLum.Data > ### Title: Channel binning for RLum.Data-class objects > ### Aliases: bin_RLum.Data bin_RLum.Data,RLum.Data.Curve-method > ### bin_RLum.Data,RLum.Data.Spectrum-method > ### Keywords: utilities > > ### ** Examples > > > ## load example data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ## create RLum.Data.Curve object from this example > curve <- + set_RLum( + class = "RLum.Data.Curve", + recordType = "OSL", + data = as.matrix(ExampleData.CW_OSL_Curve) + ) > > ## plot data without and with 2 and 4 channel binning > plot_RLum(curve) > plot_RLum(bin_RLum.Data(curve, bin_size = 2)) > plot_RLum(bin_RLum.Data(curve, bin_size = 4)) > > > > > cleanEx() > nameEx("calc_AliquotSize") > ### * calc_AliquotSize > > flush(stderr()); flush(stdout()) > > ### Name: calc_AliquotSize > ### Title: Estimate the amount of grains on an aliquot > ### Aliases: calc_AliquotSize > > ### ** Examples > > > ## Estimate the amount of grains on a small aliquot > calc_AliquotSize(grain.size = c(100,150), sample.diameter = 1, MC.iter = 100) [calc_AliquotSize] --------------------------------------------------------- mean grain size (microns) : 125 sample diameter (mm) : 1 packing density : 0.65 number of grains : 42 --------------- Monte Carlo Estimates ------------------- number of iterations (n) : 100 median : 39 mean : 43 standard deviation (mean) : 19 standard error (mean) : 1.9 95% CI from t-test (mean) : 39 - 47 standard error from CI (mean): 2 --------------------------------------------------------- > > ## Calculate the mean packing density of large aliquots > calc_AliquotSize(grain.size = c(100,200), sample.diameter = 8, + grains.counted = c(2525,2312,2880), MC.iter = 100) [calc_AliquotSize()] Monte Carlo simulation is only available for estimating the amount of grains on the sample disc, 'MC' reset to FALSE [calc_AliquotSize] --------------------------------------------------------- mean grain size (microns) : 150 sample diameter (mm) : 8 mean counted grains : 2572 mean packing density : 0.904 standard deviation : 0.101 --------------------------------------------------------- > > > > > cleanEx() > nameEx("calc_AverageDose") > ### * calc_AverageDose > > flush(stderr()); flush(stdout()) > > ### Name: calc_AverageDose > ### Title: Calculate the Average Dose and the dose rate dispersion > ### Aliases: calc_AverageDose > ### Keywords: datagen > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## calculate Average dose (using only the first 56 values here) > AD <- calc_AverageDose(ExampleData.DeValues$CA1[1:56, ], sigma_m = 0.1) [calc_AverageDose()] >> Initialisation << n: 56 delta: 65.79393 sigma_m: 0.1 sigma_d: 0.2861594 >> Calculation << log likelihood: -19.251 confidence intervals -------------------------------------------------- IC_delta IC_sigma_d level 0.95 0.9500 CredibleIntervalInf 60.80 0.2339 CredibleIntervalSup 70.07 0.3958 -------------------------------------------------- >> Results << ---------------------------------------------------------- Average dose: 65.3597 se(Aver. dose): 2.4314 sigma_d: 0.3092 se(sigma_d): 0.0431 ---------------------------------------------------------- > > ## plot De and set Average dose as central value > plot_AbanicoPlot(AD, z.0 = AD$summary$de) > > > > > cleanEx() > nameEx("calc_CentralDose") > ### * calc_CentralDose > > flush(stderr()); flush(stdout()) > > ### Name: calc_CentralDose > ### Title: Apply the central age model (CAM) after Galbraith et al. (1999) > ### to a given De distribution > ### Aliases: calc_CentralDose > > ### ** Examples > > > ##load example data > data(ExampleData.DeValues, envir = environment()) > > ##apply the central dose model > calc_CentralDose(ExampleData.DeValues$CA1) [calc_CentralDose] ----------- meta data ---------------- n: 62 log: TRUE ----------- dose estimate ------------ abs. central dose: 65.71 abs. SE: 3.05 rel. SE [%]: 4.65 ----------- overdispersion ----------- abs. OD: 22.79 abs. SE: 2.27 OD [%]: 34.69 SE [%]: 3.46 ------------------------------------- > > > > > cleanEx() > nameEx("calc_CobbleDoseRate") > ### * calc_CobbleDoseRate > > flush(stderr()); flush(stdout()) > > ### Name: calc_CobbleDoseRate > ### Title: Calculate dose rate of slices in a spherical cobble > ### Aliases: calc_CobbleDoseRate > ### Keywords: datagen > > ### ** Examples > > ## load example data > data("ExampleData.CobbleData", envir = environment()) > > ## run function > calc_CobbleDoseRate(ExampleData.CobbleData) [RLum.Results-class] originator: calc_CobbleDoseRate() data: 3 .. $DataIndividual : matrix .. $DataComponent : matrix .. $input : data.frame additional info elements: 1 > > > > > cleanEx() > nameEx("calc_CommonDose") > ### * calc_CommonDose > > flush(stderr()); flush(stdout()) > > ### Name: calc_CommonDose > ### Title: Apply the (un-)logged common age model after Galbraith et al. > ### (1999) to a given De distribution > ### Aliases: calc_CommonDose > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## apply the common dose model > calc_CommonDose(ExampleData.DeValues$CA1) [calc_CommonDose] ----------- meta data -------------- n: 62 log: TRUE ----------- dose estimate ---------- common dose: 62.16 SE: 0.78 rel. SE [%]: 1.26 ------------------------------------ [RLum.Results-class] originator: calc_CommonDose() data: 4 .. $summary : data.frame .. $data : data.frame .. $args : list .. $call : call additional info elements: 0 > > > > > cleanEx() > nameEx("calc_CosmicDoseRate") > ### * calc_CosmicDoseRate > > flush(stderr()); flush(stdout()) > > ### Name: calc_CosmicDoseRate > ### Title: Calculate the cosmic dose rate > ### Aliases: calc_CosmicDoseRate > > ### ** Examples > > > ##(1) calculate cosmic dose rate (one absorber) > calc_CosmicDoseRate(depth = 2.78, density = 1.7, + latitude = 38.06451, longitude = 1.49646, + altitude = 364, error = 10) [calc_CosmicDoseRate] --------------------------------------------------------- depth (m) : 2.78 density (g cm^-3) : 1.7 latitude (N deg.) : 38.06451 longitude (E deg.) : 1.49646 altitude (m) : 364 --------------------------------------------------------- total absorber (g cm^-2) : 472.6 cosmic dose rate (Gy ka^-1) : 0.1518 [@sea-level & 55 deg. N G.lat] geomagnetic latitude (deg.) : 41.1 cosmic dose rate (Gy ka^-1) : 0.161 +- 0.0161 [corrected] --------------------------------------------------------- [RLum.Results-class] originator: calc_CosmicDoseRate() data: 3 .. $summary : data.frame .. $args : list .. $call : call additional info elements: 0 > > ##(2a) calculate cosmic dose rate (two absorber) > calc_CosmicDoseRate(depth = c(5.0, 2.78), density = c(2.65, 1.7), + latitude = 38.06451, longitude = 1.49646, + altitude = 364, error = 10) [calc_CosmicDoseRate] --------------------------------------------------------- depth (m) : 5 2.78 density (g cm^-3) : 2.65 1.7 latitude (N deg.) : 38.06451 longitude (E deg.) : 1.49646 altitude (m) : 364 --------------------------------------------------------- total absorber (g cm^-2) : 1797.6 cosmic dose rate (Gy ka^-1) : 0.0705 [@sea-level & 55 deg. N G.lat] geomagnetic latitude (deg.) : 41.1 cosmic dose rate (Gy ka^-1) : 0.0747 +- 0.0075 [corrected] --------------------------------------------------------- [RLum.Results-class] originator: calc_CosmicDoseRate() data: 3 .. $summary : data.frame .. $args : list .. $call : call additional info elements: 0 > > ##(2b) calculate cosmic dose rate (two absorber) and > ##correct for geomagnetic field changes > calc_CosmicDoseRate(depth = c(5.0, 2.78), density = c(2.65, 1.7), + latitude = 12.04332, longitude = 4.43243, + altitude = 364, corr.fieldChanges = TRUE, + est.age = 67, error = 15) corr.fac: 1.045626 diff.one: 0.04562629 alt.fac: 1.281314 [calc_CosmicDoseRate] --------------------------------------------------------- depth (m) : 5 2.78 density (g cm^-3) : 2.65 1.7 latitude (N deg.) : 12.04332 longitude (E deg.) : 4.43243 altitude (m) : 364 --------------------------------------------------------- total absorber (g cm^-2) : 1797.6 cosmic dose rate (Gy ka^-1) : 0.0705 [@sea-level & 55 deg. N G.lat] geomagnetic latitude (deg.) : 15.1 cosmic dose rate (Gy ka^-1) : 0.072 +- 0.0108 [corrected] --------------------------------------------------------- [RLum.Results-class] originator: calc_CosmicDoseRate() data: 3 .. $summary : data.frame .. $args : list .. $call : call additional info elements: 0 > > > ##(3) calculate cosmic dose rate and export results to .csv file > #calculate cosmic dose rate and save to variable > results<- calc_CosmicDoseRate(depth = 2.78, density = 1.7, + latitude = 38.06451, longitude = 1.49646, + altitude = 364, error = 10) [calc_CosmicDoseRate] --------------------------------------------------------- depth (m) : 2.78 density (g cm^-3) : 1.7 latitude (N deg.) : 38.06451 longitude (E deg.) : 1.49646 altitude (m) : 364 --------------------------------------------------------- total absorber (g cm^-2) : 472.6 cosmic dose rate (Gy ka^-1) : 0.1518 [@sea-level & 55 deg. N G.lat] geomagnetic latitude (deg.) : 41.1 cosmic dose rate (Gy ka^-1) : 0.161 +- 0.0161 [corrected] --------------------------------------------------------- > > # the results can be accessed by > get_RLum(results, "summary") depth density latitude longitude altitude total_absorber.gcm2 d0 1 2.78 1.7 38.06451 1.49646 364 472.6 0.1518269 geom_lat dc 1 41.0685 0.161002 > > #export results to .csv file - uncomment for usage > #write.csv(results, file = "c:/users/public/results.csv") > > ##(4) calculate cosmic dose rate for 6 samples from the same profile > ## and save to .csv file > #calculate cosmic dose rate and save to variable > results<- calc_CosmicDoseRate(depth = c(0.1, 0.5 , 2.1, 2.7, 4.2, 6.3), + density = 1.7, latitude = 38.06451, + longitude = 1.49646, altitude = 364, + error = 10) [calc_CosmicDoseRate] Calculating cosmic dose rate for 6 samples. depth (m) d0 (Gy/ka) dc (Gy/ka) dc_error (Gy/ka) 1 0.1 0.2599 0.2756 0.0276 2 0.5 0.1999 0.2120 0.0212 3 2.1 0.1640 0.1739 0.0174 4 2.7 0.1532 0.1625 0.0162 5 4.2 0.1299 0.1377 0.0138 6 6.3 0.1045 0.1109 0.0111 > > #export results to .csv file - uncomment for usage > #write.csv(results, file = "c:/users/public/results_profile.csv") > > > > > cleanEx() > nameEx("calc_EED_Model") > ### * calc_EED_Model > > flush(stderr()); flush(stdout()) > > ### Name: calc_EED_Model > ### Title: Modelling Exponential Exposure Distribution > ### Aliases: calc_EED_Model > ### Keywords: datagen > > ### ** Examples > > > data(ExampleData.MortarData, envir = environment()) > calc_EED_Model( + data = MortarData, + kappa = 14, + sigma_distr = 0.37, + expected_dose = 11.7) [calc_EED_Model()] ------------------------------------ Maximal Individual Equivalent Dose integrated: 24.75 Gy Averaged Corrected Equivalent Dose: 11.35 ± 0.64 Gy [RLum.Results-class] originator: calc_EED_Model() data: 1 .. $M_Data : matrix additional info elements: 1 > > ## automated estimation of > ## sigma_distribution and > ## kappa > ## Not run: > ##D calc_EED_Model( > ##D data = MortarData, > ##D kappa = NULL, > ##D sigma_distr = NULL, > ##D expected_dose = 11.7) > ## End(Not run) > > > > > cleanEx() > nameEx("calc_FadingCorr") > ### * calc_FadingCorr > > flush(stderr()); flush(stdout()) > > ### Name: calc_FadingCorr > ### Title: Fading Correction after Huntley & Lamothe (2001) > ### Aliases: calc_FadingCorr > ### Keywords: datagen > > ### ** Examples > > > ##run the examples given in the appendix of Huntley and Lamothe, 2001 > > ##(1) faded age: 100 a > results <- calc_FadingCorr( + age.faded = c(0.1,0), + g_value = c(5.0, 1.0), + tc = 2592000, + tc.g_value = 172800, + n.MC = 100) [calc_FadingCorr()] >> Fading correction according to Huntley & Lamothe (2001) >> g-value re-calculated for the given tc .. used g-value: 5.312 ± 1.012 %/decade .. used tc: 8.214e-05 ka .. used kappa: 0.0231 ± 0.0044 ---------------------------------------------- seed: NA n.MC: 100 observations: 100 ---------------------------------------------- Age (faded): 0.1 ka ± 0 ka Age (corr.): 0.1169 ka ± 0.0035 ka ---------------------------------------------- > > ##(2) faded age: 1 ka > results <- calc_FadingCorr( + age.faded = c(1,0), + g_value = c(5.0, 1.0), + tc = 2592000, + tc.g_value = 172800, + n.MC = 100) [calc_FadingCorr()] >> Fading correction according to Huntley & Lamothe (2001) >> g-value re-calculated for the given tc .. used g-value: 5.312 ± 1.012 %/decade .. used tc: 8.214e-05 ka .. used kappa: 0.0231 ± 0.0044 ---------------------------------------------- seed: NA n.MC: 100 observations: 100 ---------------------------------------------- Age (faded): 1 ka ± 0 ka Age (corr.): 1.2486 ka ± 0.0613 ka ---------------------------------------------- > > ##(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) [calc_FadingCorr()] >> Fading correction according to Huntley & Lamothe (2001) >> g-value re-calculated for the given tc .. used g-value: 5.312 ± 1.012 %/decade .. used tc: 8.214e-05 ka .. used kappa: 0.0231 ± 0.0044 ---------------------------------------------- seed: NA n.MC: 100 observations: 100 ---------------------------------------------- Age (faded): 10 ka ± 0 ka Age (corr.): 13.402 ka ± 0.9412 ka ---------------------------------------------- > > ##access the last output > get_RLum(results) AGE AGE.ERROR AGE_FADED AGE_FADED.ERROR G_VALUE G_VALUE.ERROR KAPPA 1 13.402 0.9412 10 0 5.312393 1.011901 0.02307143 KAPPA.ERROR TC TC.G_VALUE n.MC OBSERVATIONS SEED 1 0.00439463 8.213721e-05 5.475814e-06 100 100 NA > > > > > cleanEx() > nameEx("calc_FastRatio") > ### * calc_FastRatio > > flush(stderr()); flush(stdout()) > > ### Name: calc_FastRatio > ### Title: Calculate the Fast Ratio for CW-OSL curves > ### Aliases: calc_FastRatio > > ### ** Examples > > # load example CW-OSL curve > data("ExampleData.CW_OSL_Curve") > > # calculate the fast ratio w/o further adjustments > res <- calc_FastRatio(ExampleData.CW_OSL_Curve) [calc_FastRatio()] ------------------------------- Fast Ratio : 405.12 ˪ Absolute error : 119.74 ˪ Relative error (%) : 29.56 Channels : 1000 Channel width (s) : 0.04 Dead channels start : 0 Dead channels end : 0 Sigma Fast : 2.6e-17 Sigma Medium : 4.3e-18 I0 : 7.2e+16 Stim. power (mW/cm^2) : 30.60 Wavelength (nm) : 470.00 - Time L1 (s) : 0.00 Time L2 (s) : 2.45 Time L3 start (s) : 14.86 Time L3 end (s) : 22.29 - Channel L1 : 1 Channel L2 : 62 Channel L3 start : 373 Channel L3 end : 558 - Counts L1 : 11111 Counts L2 : 65 Counts L3 : 37.67 ------------------------------- > > # show the summary table > get_RLum(res) fast.ratio fast.ratio.se fast.ratio.rse channels channel.width 1 405.122 119.7442 29.55756 1000 0.04 dead.channels.start dead.channels.end sigmaF sigmaM I0 1 0 0 2.6e-17 4.28e-18 7.240066e+16 stimulation.power wavelength t_L1 t_L2 t_L3_start t_L3_end Ch_L1 Ch_L2 1 30.6 470 0 2.446413 14.86139 22.29208 1 62 Ch_L3_start Ch_L3_end Cts_L1 Cts_L2 Cts_L3 1 373 558 11111 65 37.66667 > > > > > cleanEx() > nameEx("calc_FiniteMixture") > ### * calc_FiniteMixture > > flush(stderr()); flush(stdout()) > > ### Name: calc_FiniteMixture > ### Title: Apply the finite mixture model (FMM) after Galbraith (2005) to a > ### given De distribution > ### Aliases: calc_FiniteMixture > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## (1) apply the finite mixture model > ## NOTE: the data set is not suitable for the finite mixture model, > ## which is why a very small sigmab is necessary > calc_FiniteMixture(ExampleData.DeValues$CA1, + sigmab = 0.2, n.components = 2, + grain.probability = TRUE) [calc_FiniteMixture] ----------- meta data ------------ n: 62 sigmab: 0.2 number of components: 2 llik: -20.3938 BIC: 53.169 --- covariance matrix of mle's --- [,1] [,2] [,3] [1,] 0.002144 0.001821 0.000283 [2,] 0.001821 0.013319 0.000877 [3,] 0.000283 0.000877 0.001118 ----------- components ----------- comp1 comp2 dose (Gy) 31.5299 72.0333 rse(dose) 0.1154 0.0334 se(dose)(Gy) 3.6387 2.4082 proportion 0.1096 0.8904 -------- grain probability ------- [,1] [,2] [1,] 1.00 0.00 [2,] 1.00 0.00 [3,] 1.00 0.00 [4,] 0.99 0.01 [5,] 0.94 0.06 [6,] 0.91 0.09 [7,] 0.29 0.71 [8,] 0.13 0.87 [9,] 0.11 0.89 [10,] 0.10 0.90 [11,] 0.09 0.91 [12,] 0.06 0.94 [13,] 0.04 0.96 [14,] 0.03 0.97 [15,] 0.04 0.96 [16,] 0.02 0.98 [17,] 0.01 0.99 [18,] 0.01 0.99 [19,] 0.01 0.99 [20,] 0.00 1.00 [21,] 0.00 1.00 [22,] 0.00 1.00 [23,] 0.00 1.00 [24,] 0.00 1.00 [25,] 0.00 1.00 [26,] 0.00 1.00 [27,] 0.00 1.00 [28,] 0.00 1.00 [29,] 0.00 1.00 [30,] 0.00 1.00 [31,] 0.00 1.00 [32,] 0.00 1.00 [33,] 0.00 1.00 [34,] 0.00 1.00 [35,] 0.00 1.00 [36,] 0.00 1.00 [37,] 0.00 1.00 [38,] 0.00 1.00 [39,] 0.00 1.00 [40,] 0.00 1.00 [41,] 0.00 1.00 [42,] 0.00 1.00 [43,] 0.00 1.00 [44,] 0.00 1.00 [45,] 0.00 1.00 [46,] 0.00 1.00 [47,] 0.00 1.00 [48,] 0.00 1.00 [49,] 0.00 1.00 [50,] 0.00 1.00 [51,] 0.00 1.00 [52,] 0.00 1.00 [53,] 0.00 1.00 [54,] 0.00 1.00 [55,] 0.00 1.00 [56,] 0.00 1.00 [57,] 0.00 1.00 [58,] 0.00 1.00 [59,] 0.00 1.00 [60,] 0.00 1.00 [61,] 0.00 1.00 [62,] 0.00 1.00 -------- single component -------- mu: 65.2273 sigmab: 0.2 llik: -44.96 BIC: 94.047 [calc_FiniteMixture()] 'n.components' specified only one component, nothing plotted > > ## (2) repeat the finite mixture model for 2, 3 and 4 maximum number of fitted > ## components and save results > ## NOTE: The following example is computationally intensive. Please un-comment > ## the following lines to make the example work. > FMM<- calc_FiniteMixture(ExampleData.DeValues$CA1, + sigmab = 0.2, n.components = c(2:4), + pdf.weight = TRUE) [calc_FiniteMixture] ----------- meta data ------------ n: 62 sigmab: 0.2 number of components: 2, 3, 4 -------- single component -------- mu: 65.2273 sigmab: 0.2 llik: -44.96 BIC: 94.047 ---------- k components ---------- 2 3 4 c1_dose 31.53 29.91 29.91 c1_se 3.64 3.97 4.32 c1_prop 0.11 0.09 0.09 c2_dose 72.03 56.65 56.65 c2_se 2.41 13.05 33.16 c2_prop 0.89 0.25 0.07 c3_dose 77.49 56.65 c3_se 6.37 21.30 c3_prop 0.66 0.18 c4_dose 77.49 c4_se 7.67 c4_prop 0.66 ------ statistical criteria ------ 1 2 3 4 BIC 94.047 53.169 59.719 67.973 loglik -44.96 -20.394 -19.542 -19.542 signif *** Lowest BIC score for k = 2 First significant increase in maximum log-likelihood for k = 2 > > ## show structure of the results > FMM [RLum.Results-class] originator: calc_FiniteMixture() data: 10 .. $summary : data.frame .. $data : data.frame .. $args : list .. $call : call .. $mle : list .. $BIC : data.frame .. $llik : data.frame .. $grain.probability : list .. $components : matrix .. $single.comp : data.frame additional info elements: 0 > > ## show the results on equivalent dose, standard error and proportion of > ## fitted components > get_RLum(object = FMM, data.object = "components") 2 3 4 c1_dose 31.5299 29.9146 29.9147 c1_se 3.6387 3.9695 4.3213 c1_prop 0.1096 0.0891 0.0891 c2_dose 72.0333 56.6455 56.6458 c2_se 2.4082 13.0496 33.1592 c2_prop 0.8904 0.2480 0.0725 c3_dose NA 77.4938 56.6458 c3_se NA 6.3696 21.3035 c3_prop NA 0.6629 0.1755 c4_dose NA NA 77.4940 c4_se NA NA 7.6739 c4_prop NA NA 0.6629 > > > > > cleanEx() > nameEx("calc_FuchsLang2001") > ### * calc_FuchsLang2001 > > flush(stderr()); flush(stdout()) > > ### Name: calc_FuchsLang2001 > ### Title: Apply the model after Fuchs & Lang (2001) to a given De > ### distribution > ### Aliases: calc_FuchsLang2001 > ### Keywords: dplot > > ### ** Examples > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## calculate De according to Fuchs & Lang (2001) > temp<- calc_FuchsLang2001(ExampleData.DeValues$BT998, cvThreshold = 5) [calc_FuchsLang2001] ----------- meta data -------------- cvThreshold: 5 % used values: 22 ----------- dose estimate ---------- mean: 2866.11 sd: 157.35 weighted mean: 2846.66 weighted sd: 20.58 se: 33.55 ------------------------------------ > > > > > cleanEx() > nameEx("calc_HomogeneityTest") > ### * calc_HomogeneityTest > > flush(stderr()); flush(stdout()) > > ### Name: calc_HomogeneityTest > ### Title: Apply a simple homogeneity test after Galbraith (2003) > ### Aliases: calc_HomogeneityTest > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## apply the homogeneity test > calc_HomogeneityTest(ExampleData.DeValues$BT998) [calc_HomogeneityTest()] --------------------------------- n: 25 --------------------------------- mu: 7.9812 G-value: 155.5127 Degrees of freedom: 24 P-value: 0 --------------------------------- [RLum.Results-class] originator: calc_HomogeneityTest() data: 3 .. $summary : data.frame .. $data : data.frame .. $args : list additional info elements: 1 > > ## using the data presented by Galbraith (2003) > df <- + data.frame( + x = c(30.1, 53.8, 54.3, 29.0, 47.6, 44.2, 43.1), + y = c(4.8, 7.1, 6.8, 4.3, 5.2, 5.9, 3.0)) > > calc_HomogeneityTest(df) [calc_HomogeneityTest()] --------------------------------- n: 7 --------------------------------- mu: 3.7727 G-value: 19.2505 Degrees of freedom: 6 P-value: 0.0038 --------------------------------- [RLum.Results-class] originator: calc_HomogeneityTest() data: 3 .. $summary : data.frame .. $data : data.frame .. $args : list additional info elements: 1 > > > > > > cleanEx() > nameEx("calc_Huntley2006") > ### * calc_Huntley2006 > > flush(stderr()); flush(stdout()) > > ### Name: calc_Huntley2006 > ### Title: Apply the Huntley (2006) model > ### Aliases: calc_Huntley2006 > ### Keywords: datagen > > ### ** Examples > > > ## Load example data (sample UNIL/NB123, see ?ExampleData.Fading) > data("ExampleData.Fading", envir = environment()) > > ## (1) Set all relevant parameters > # a. fading measurement data (IR50) > fading_data <- ExampleData.Fading$fading.data$IR50 > > # b. Dose response curve data > data <- ExampleData.Fading$equivalentDose.data$IR50 > > ## (2) Define required function parameters > ddot <- c(7.00, 0.004) > readerDdot <- c(0.134, 0.0067) > > # Analyse fading measurement and get an estimate of rho'. > # Note that the RLum.Results object can be directly used for further processing. > # The number of MC runs is reduced for this example > rhop <- analyse_FadingMeasurement(fading_data, plot = TRUE, verbose = FALSE, n.MC = 10) > > ## (3) Apply the Kars et al. (2008) model to the data > kars <- calc_Huntley2006( + data = data, + rhop = rhop, + ddot = ddot, + readerDdot = readerDdot, + n.MC = 25) [calc_Huntley2006()] ------------------------------- (n/N) [-]: 0.15 ± 0.02 (n/N)_SS [-]: 0.38 ± 0.09 ---------- Measured ----------- DE [Gy]: 130.97 ± 13.52 D0 [Gy]: 539.01 ± 22.48 Age [ka]: 18.71 ± 2.15 ---------- Un-faded ----------- D0 [Gy]: 636.93 ± 13.35 ---------- Simulated ---------- DE [Gy]: 242.79 ± 39.51 D0 [Gy]: 609.35 ± 7.8 Age [ka]: 34.68 ± 5.9 Age @2D0 [ka]: 174.1 ± 8.99 ------------------------------- > > ## Not run: > ##D # You can also provide LnTn values separately via the 'LnTn' argument. > ##D # Note, however, that the data frame for 'data' must then NOT contain > ##D # a LnTn value. See argument descriptions! > ##D LnTn <- data.frame( > ##D LnTn = c(1.84833, 2.24833), > ##D nTn.error = c(0.17, 0.22)) > ##D > ##D LxTx <- data[2:nrow(data), ] > ##D > ##D kars <- calc_Huntley2006( > ##D data = LxTx, > ##D LnTn = LnTn, > ##D rhop = rhop, > ##D ddot = ddot, > ##D readerDdot = readerDdot, > ##D n.MC = 25) > ## End(Not run) > > > > cleanEx() > nameEx("calc_IEU") > ### * calc_IEU > > flush(stderr()); flush(stdout()) > > ### Name: calc_IEU > ### Title: Apply the internal-external-uncertainty (IEU) model after > ### Thomsen et al. (2007) to a given De distribution > ### Aliases: calc_IEU > > ### ** Examples > > > ## load data > data(ExampleData.DeValues, envir = environment()) > > ## apply the IEU model > ieu <- calc_IEU(ExampleData.DeValues$CA1, a = 0.2, b = 1.9, interval = 1) [calc_IEU] Dbar: 46.67 IEU.De (Gy): 46.67 IEU.Error (Gy): 2.55 Number of De: 24 a: 0.2000 b: 1.9000 > > > > > cleanEx() > nameEx("calc_Lamothe2003") > ### * calc_Lamothe2003 > > flush(stderr()); flush(stdout()) > > ### Name: calc_Lamothe2003 > ### Title: Apply fading correction after Lamothe et al., 2003 > ### Aliases: calc_Lamothe2003 > ### Keywords: datagen > > ### ** Examples > > > ##load data > ##ExampleData.BINfileData contains two BINfileData objects > ##CWOSL.SAR.Data and TL.SAR.Data > data(ExampleData.BINfileData, envir = environment()) > > ##transform the values from the first position in a RLum.Analysis object > object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > > ##perform SAR analysis and set rejection criteria > results <- analyse_SAR.CWOSL( + object = object, + signal_integral = 1:2, + background_integral = 900:900, + verbose = FALSE, + plot = FALSE, + onlyLxTxTable = TRUE + ) Warning: [analyse_SAR.CWOSL()] Background integral should contain at least two values, reset to 875:900 > > ##run fading correction > results_corr <- calc_Lamothe2003( + object = results, + dose_rate.envir = c(1.676 , 0.180), + dose_rate.source = c(0.184, 0.003), + g_value = c(2.36, 0.6), + plot = TRUE, + fit.method = "EXP") [calc_Lamothe2003()] Used g_value: 2.36 ± 0.6 %/decade Fading_C: 0.785 ± 0.055 Corrected Ln/Tn: 5.515 ± 0.391 Corrected De: 472.48 ± 69.53 Gy -------------------------------------------------------- Corrected Age: 281.91 ± 51.36 ka -------------------------------------------------------- > > > > > > cleanEx() > nameEx("calc_MaxDose") > ### * calc_MaxDose > > flush(stderr()); flush(stdout()) > > ### Name: calc_MaxDose > ### Title: Apply the maximum age model to a given De distribution > ### Aliases: calc_MaxDose > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > # apply the maximum dose model > calc_MaxDose(ExampleData.DeValues$CA1, sigmab = 0.2, par = 3) ----------- Meta data ----------- n par sigmab logged Lmax BIC 62 3 0.2 TRUE -19.79245 58.86603 --- Final parameter estimates --- gamma sigma p0 Estimate 76.58 1.71 0.65 ------ Confidence intervals ----- 2.5 % 97.5 % gamma 69.65 99.33 sigma 1.43 2.61 p0 NA 0.87 ------ De (asymmetric error) ----- De lower upper 76.58 69.65 99.33 ------ De (symmetric error) ----- De error 76.58 7.57 > > > > > cleanEx() > nameEx("calc_MinDose") > ### * calc_MinDose > > flush(stderr()); flush(stdout()) > > ### Name: calc_MinDose > ### Title: (Un-)logged minimum age model (MAM) after Galbraith et al. > ### (1999) > ### Aliases: calc_MinDose > > ### ** Examples > > > ## Load example data > data(ExampleData.DeValues, envir = environment()) > > # (1) Apply the minimum age model with minimum required parameters. > # By default, this will apply the un-logged 3-parameter MAM. > calc_MinDose(data = ExampleData.DeValues$CA1, sigmab = 0.1) ----------- Meta data ----------- n par sigmab logged Lmax BIC 62 3 0.1 TRUE -43.57969 106.4405 --- Final parameter estimates --- gamma sigma p0 Estimate 34.32 2.07 0.01 ------ Confidence intervals ----- 2.5 % 97.5 % gamma 29.38 39.38 sigma 1.76 2.57 p0 NA 0.11 ------ De (asymmetric error) ----- De lower upper 34.32 29.38 39.38 ------ De (symmetric error) ----- De error 34.32 2.55 [RLum.Results-class] originator: calc_MinDose() data: 9 .. $summary : data.frame .. $data : data.frame .. $args : list .. $call : call .. $mle : mle2 .. $BIC : numeric .. $confint : data.frame .. $profile : profile.mle2 .. $bootstrap : list additional info elements: 0 > > ## Not run: > ##D # (2) Re-run the model, but save results to a variable and turn > ##D # plotting of the log-likelihood profiles off. > ##D mam <- calc_MinDose( > ##D data = ExampleData.DeValues$CA1, > ##D sigmab = 0.1, > ##D plot = FALSE) > ##D > ##D # Show structure of the RLum.Results object > ##D mam > ##D > ##D # Show summary table that contains the most relevant results > ##D res <- get_RLum(mam, "summary") > ##D res > ##D > ##D # Plot the log likelihood profiles retroactively, because before > ##D # we set plot = FALSE > ##D plot_RLum(mam) > ##D > ##D # Plot the dose distribution in an abanico plot and draw a line > ##D # at the minimum dose estimate > ##D plot_AbanicoPlot(data = mam, > ##D main = "3-parameter Minimum Age Model", > ##D polygon.col = "none", > ##D hist = TRUE, > ##D rug = TRUE, > ##D summary = c("n", "mean", "mean.weighted", "median", "in.ci"), > ##D centrality = res$de, > ##D grid.col = "none", > ##D line.col = "red", > ##D line.label = paste0(round(res$de, 1), "\U00B1", > ##D round(res$de_err, 1), " Gy"), > ##D bw = 0.1, > ##D ylim = c(-25, 18), > ##D summary.pos = "topleft", > ##D mtext = bquote("Parameters: " ~ > ##D sigma[b] == .(get_RLum(mam, "args")$sigmab) ~ ", " ~ > ##D gamma == .(round(log(res$de), 1)) ~ ", " ~ > ##D sigma == .(round(res$sig, 1)) ~ ", " ~ > ##D rho == .(round(res$p0, 2)))) > ##D > ##D # (3) Run the minimum age model with bootstrap > ##D # NOTE: Bootstrapping is computationally intensive > ##D # (3.1) run the minimum age model with default values for bootstrapping > ##D calc_MinDose(data = ExampleData.DeValues$CA1, > ##D sigmab = 0.15, > ##D bootstrap = TRUE) > ##D > ##D # (3.2) Bootstrap control parameters > ##D mam <- calc_MinDose(data = ExampleData.DeValues$CA1, > ##D sigmab = 0.15, > ##D bootstrap = TRUE, > ##D bs.M = 300, > ##D bs.N = 500, > ##D bs.h = 4, > ##D sigmab.sd = 0.06, > ##D plot = FALSE) > ##D > ##D # Plot the results > ##D plot_RLum(mam) > ##D > ##D # save bootstrap results in a separate variable > ##D bs <- get_RLum(mam, "bootstrap") > ##D > ##D # show structure of the bootstrap results > ##D str(bs, max.level = 2, give.attr = FALSE) > ##D > ##D # print summary of minimum dose and likelihood pairs > ##D summary(bs$pairs$gamma) > ##D > ##D # Show polynomial fits of the bootstrap pairs > ##D bs$poly.fits$poly.three > ##D > ##D # Plot various statistics of the fit using the generic plot() function > ##D par(mfcol=c(2,2)) > ##D plot(bs$poly.fits$poly.three, ask = FALSE) > ##D > ##D # Show the fitted values of the polynomials > ##D summary(bs$poly.fits$poly.three$fitted.values) > ## End(Not run) > > > > > cleanEx() > nameEx("calc_MoransI") > ### * calc_MoransI > > flush(stderr()); flush(stdout()) > > ### Name: calc_MoransI > ### Title: Calculate Moran's I > ### Aliases: calc_MoransI > > ### ** Examples > > > ## Test a fictional sample with spatial correlation > calc_MoransI(object = c(1:100)) [1] 0.8888889 > > ## Test some fictional samples without spatial correlation; > ## note the randomness with each repetition > calc_MoransI(object = rnorm(n = 100)) [1] 0.00603312 > calc_MoransI(object = rnorm(n = 100)) [1] -0.0814557 > calc_MoransI(object = rnorm(n = 100)) [1] -0.02725502 > > > > > cleanEx() > nameEx("calc_OSLLxTxRatio") > ### * calc_OSLLxTxRatio > > flush(stderr()); flush(stdout()) > > ### Name: calc_OSLLxTxRatio > ### Title: Calculate 'Lx/Tx' ratio for CW-OSL curves > ### Aliases: calc_OSLLxTxRatio > ### Keywords: datagen > > ### ** Examples > > > ##load data > data(ExampleData.LxTxOSLData, envir = environment()) > > ##calculate Lx/Tx ratio > results <- calc_OSLLxTxRatio( + Lx.data = Lx.data, + Tx.data = Tx.data, + signal_integral = 1:2, + background_integral = 85:100) > > ##get results object > get_RLum(results) LnLx LnLx.BG TnTx TnTx.BG Net_LnLx Net_LnLx.Error Net_TnTx Net_TnTx.Error 1 81709 530 7403 513 81179 286.5461 6890 88.53581 SN_RATIO_LnLx SN_RATIO_TnTx LxTx LxTx.Error 1 154.1679 14.4308 11.78215 0.1570077 > > > > > cleanEx() > nameEx("calc_SourceDoseRate") > ### * calc_SourceDoseRate > > flush(stderr()); flush(stdout()) > > ### Name: calc_SourceDoseRate > ### Title: Calculation of the source dose rate via the date of measurement > ### Aliases: calc_SourceDoseRate > ### Keywords: manip > > ### ** Examples > > > ##(1) Simple function usage > ##Basic calculation of the dose rate for a specific date > dose.rate <- calc_SourceDoseRate(measurement.date = "2012-01-27", + calib.date = "2014-12-19", + calib.dose.rate = 0.0438, + calib.error = 0.0019) > > ##show results > get_RLum(dose.rate) dose.rate dose.rate.error date 1 0.04694815 0.002036563 2012-01-27 > > ##(2) Usage in combination with another function (e.g., convert_Second2Gray() ) > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## use the calculated variable dose.rate as input argument > ## to convert De(s) to De(Gy) > convert_Second2Gray(ExampleData.DeValues$BT998, dose.rate) De De.error 1 162.37 5.717 2 163.01 5.514 3 177.72 7.294 4 145.93 4.939 5 154.80 4.976 6 132.31 4.792 7 132.53 4.531 8 136.21 4.712 9 134.04 4.962 10 133.39 4.561 11 127.12 4.340 12 137.29 4.724 13 118.74 3.967 14 129.71 4.488 15 133.01 4.426 16 133.66 4.334 17 132.57 4.568 18 135.42 4.531 19 137.83 4.560 20 140.91 4.768 21 136.96 4.641 22 140.47 5.384 23 135.42 4.628 24 123.79 3.729 25 128.18 4.090 > > ##(3) source rate prediction and plotting > dose.rate <- calc_SourceDoseRate(measurement.date = "2012-01-27", + calib.date = "2014-12-19", + calib.dose.rate = 0.0438, + calib.error = 0.0019, + predict = 1000) > plot_RLum(dose.rate) > > ##(4) export output to a LaTeX table (example using the package 'xtable') > ## Not run: > ##D xtable::xtable(get_RLum(dose.rate)) > ## End(Not run) > > > > > cleanEx() > nameEx("calc_Statistics") > ### * calc_Statistics > > flush(stderr()); flush(stdout()) > > ### Name: calc_Statistics > ### Title: Function to calculate statistic measures > ### Aliases: calc_Statistics > ### Keywords: datagen > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## show a rough plot of the data to illustrate the non-normal distribution > plot_KDE(ExampleData.DeValues$BT998) > > ## calculate statistics and show output > str(calc_Statistics(ExampleData.DeValues$BT998)) List of 3 $ weighted :List of 9 ..$ n : int 25 ..$ mean : num 2896 ..$ median : num 2847 ..$ sd.abs : num 240 ..$ sd.rel : num 8.29 ..$ se.abs : num 48 ..$ se.rel : num 1.66 ..$ skewness: num 1.34 ..$ kurtosis: num 4.39 $ unweighted:List of 9 ..$ n : int 25 ..$ mean : num 2951 ..$ median : num 2884 ..$ sd.abs : num 282 ..$ sd.rel : num 9.54 ..$ se.abs : num 56.3 ..$ se.rel : num 1.91 ..$ skewness: num 1.34 ..$ kurtosis: num 4.39 $ MCM :List of 9 ..$ n : int 25 ..$ mean : num 2951 ..$ median : num 2884 ..$ sd.abs : num 282 ..$ sd.rel : num 9.54 ..$ se.abs : num 56.3 ..$ se.rel : num 1.91 ..$ skewness: num 1.34 ..$ kurtosis: num 4.39 > > ## Not run: > ##D ## now the same for 10000 normal distributed random numbers with equal errors > ##D x <- as.data.frame(cbind(rnorm(n = 10^5, mean = 0, sd = 1), > ##D rep(0.001, 10^5))) > ##D > ##D ## note the congruent results for weighted and unweighted measures > ##D str(calc_Statistics(x)) > ## End(Not run) > > > > > cleanEx() > nameEx("calc_TLLxTxRatio") > ### * calc_TLLxTxRatio > > flush(stderr()); flush(stdout()) > > ### Name: calc_TLLxTxRatio > ### Title: Calculate the Lx/Tx ratio for a given set of TL curves -beta > ### version- > ### Aliases: calc_TLLxTxRatio > ### Keywords: datagen > > ### ** Examples > > > ##load package example data > data(ExampleData.BINfileData, envir = environment()) > > ##convert Risoe.BINfileData into a curve object > temp <- Risoe.BINfileData2RLum.Analysis(TL.SAR.Data, pos = 3) > > Lx.data.signal <- get_RLum(temp, record.id=1) > Lx.data.background <- get_RLum(temp, record.id=2) > Tx.data.signal <- get_RLum(temp, record.id=3) > Tx.data.background <- get_RLum(temp, record.id=4) > signal_integral <- 210:230 > > output <- calc_TLLxTxRatio( + Lx.data.signal, + Lx.data.background, + Tx.data.signal, + Tx.data.background, + signal_integral) > get_RLum(output) LnLx LnLx.BG TnTx TnTx.BG net_LnLx net_LnLx.Error net_TnTx net_TnTx.Error 1 257042 4068 82298 2943 252974 49468.92 79355 21449.72 SN_RATIO_LnLx SN_RATIO_TnTx LxTx LxTx.Error 1 63.18633 27.96398 3.187877 1.485073 > > > > > cleanEx() > nameEx("calc_ThermalLifetime") > ### * calc_ThermalLifetime > > flush(stderr()); flush(stdout()) > > ### Name: calc_ThermalLifetime > ### Title: Calculates the Thermal Lifetime using the Arrhenius equation > ### Aliases: calc_ThermalLifetime > ### Keywords: datagen > > ### ** Examples > > > ##EXAMPLE 1 > ##calculation for two trap-depths with similar frequency factor for different temperatures > E <- c(1.66, 1.70) > s <- 1e+13 > T <- 10:20 > temp <- calc_ThermalLifetime( + E = E, + s = s, + T = T, + output_unit = "Ma" + ) [calc_ThermalLifetime()] mean: 1.354649e+03 Ma sd: 1.515822e+03 Ma min: 1.094723e+02 Ma (@ 20 °C) max: 5.743187e+03 Ma (@ 10 °C) -------------------------- (22 lifetimes calculated in total) > graphics::contour(x = E, y = T, z = temp$lifetimes[1,,], + ylab = "Temperature [\u00B0C]", + xlab = "Trap depth [eV]", + main = "Thermal Lifetime Contour Plot" + ) > mtext(side = 3, "(values quoted in Ma)") > > ##EXAMPLE 2 > ##profiling of thermal life time for E and s and their standard error > E <- c(1.600, 0.003) > s <- c(1e+13,1e+011) > T <- 20 > calc_ThermalLifetime( + E = E, + s = s, + T = T, + profiling = TRUE, + output_unit = "Ma" + ) [calc_ThermalLifetime()] profiling = TRUE -------------------------- mean: 1.023766e+01 Ma sd: 1.229966e+00 Ma min: 6.86845e+00 Ma max: 1.48863e+01 Ma -------------------------- (1000 lifetimes calculated in total) [RLum.Results-class] originator: calc_ThermalLifetime() data: 2 .. $lifetimes : numeric .. $profiling_matrix : matrix additional info elements: 1 > > > > > cleanEx() > nameEx("calc_WodaFuchs2008") > ### * calc_WodaFuchs2008 > > flush(stderr()); flush(stdout()) > > ### Name: calc_WodaFuchs2008 > ### Title: Obtain the equivalent dose using the approach by Woda and Fuchs > ### 2008 > ### Aliases: calc_WodaFuchs2008 > > ### ** Examples > > > ## read example data set > data(ExampleData.DeValues, envir = environment()) > > results <- calc_WodaFuchs2008( + data = ExampleData.DeValues$CA1, + xlab = expression(paste(D[e], " [Gy]")) + ) > > > > > cleanEx() > nameEx("calc_gSGC") > ### * calc_gSGC > > flush(stderr()); flush(stdout()) > > ### Name: calc_gSGC > ### Title: Calculate De value based on the gSGC by Li et al., 2015 > ### Aliases: calc_gSGC > ### Keywords: datagen > > ### ** Examples > > > results <- calc_gSGC(data = data.frame( + LnTn = 2.361, LnTn.error = 0.087, + Lr1Tr1 = 2.744, Lr1Tr1.error = 0.091, + Dr1 = 34.4)) [calc_gSGC()] Corresponding De based on the gSGC Ln/Tn: 2.361 ± 0.087 Lr1/Tr1: 2.744 ± 0.091 Dr1: 34.4 f(D): 0.787 * (1 - exp(-D /73.9)) + c * D + 0.01791 n.MC: 100 ------------------------------ De: 28.43 ± 1.83 ------------------------------ > > get_RLum(results, data.object = "De") DE DE.ERROR ETA 1 28.42881 1.832833 0.1325632 > > > > > cleanEx() > nameEx("calc_gSGC_feldspar") > ### * calc_gSGC_feldspar > > flush(stderr()); flush(stdout()) > > ### Name: calc_gSGC_feldspar > ### Title: Calculate Global Standardised Growth Curve (gSGC) for Feldspar > ### MET-pIRIR > ### Aliases: calc_gSGC_feldspar > ### Keywords: datagen > > ### ** Examples > > > ##test on a generated random sample > n_samples <- 10 > data <- data.frame( + LnTn = rnorm(n=n_samples, mean=1.0, sd=0.02), + LnTn.error = rnorm(n=n_samples, mean=0.05, sd=0.002), + Lr1Tr1 = rnorm(n=n_samples, mean=1.0, sd=0.02), + Lr1Tr1.error = rnorm(n=n_samples, mean=0.05, sd=0.002), + Dr1 = rep(100,n_samples)) > > results <- calc_gSGC_feldspar( + data = data, gSGC.type = "50LxTx", + plot = FALSE) > > plot_AbanicoPlot(results) > > > > > cleanEx() > nameEx("combine_De_Dr") > ### * combine_De_Dr > > flush(stderr()); flush(stdout()) > > ### Name: combine_De_Dr > ### Title: Combine Dose Rate and Equivalent Dose Distribution > ### Aliases: combine_De_Dr > ### Keywords: datagen distribution dplot > > ### ** Examples > > ## set parameters > Dr <- stats::rlnorm (1000, 0, 0.3) > De <- 50*sample(Dr, 50, replace = TRUE) > s <- stats::rnorm(50, 10, 2) > > ## run modelling > ## note: modify parameters for more realistic results > ## Not run: > ##D results <- combine_De_Dr( > ##D Dr = Dr, > ##D int_OD = 0.1, > ##D De, > ##D s, > ##D Age_range = c(0,100), > ##D method_control = list( > ##D n.iter = 100, > ##D n.chains = 1)) > ##D > ##D ## show models used > ##D writeLines(results@info$model_IAM) > ##D writeLines(results@info$model_BCAM) > ## End(Not run) > > > > > cleanEx() > nameEx("convert_Activity2Concentration") > ### * convert_Activity2Concentration > > flush(stderr()); flush(stdout()) > > ### Name: convert_Activity2Concentration > ### Title: Convert Nuclide Activities to Abundance and Vice Versa > ### Aliases: convert_Activity2Concentration > ### Keywords: IO > > ### ** Examples > > > ##construct data.frame > data <- data.frame( + NUCLIDES = c("U-238", "Th-232", "K-40"), + VALUE = c(40,80,100), + VALUE_ERROR = c(4,8,10), + stringsAsFactors = FALSE) > > ##perform analysis > convert_Activity2Concentration(data) NUCLIDE ACTIVIY (Bq/kg) ACTIVIY ERROR (Bq/kg) ABUND. (mug/g or mass. %) 1 U-238 40 4 3.2398475 2 Th-232 80 8 19.6469710 3 K-40 100 10 0.3222668 ABUND. ERROR (mug/g or mass. %) 1 0.32398475 2 1.96469710 3 0.03222668 > > > > > cleanEx() > nameEx("convert_BIN2CSV") > ### * convert_BIN2CSV > > flush(stderr()); flush(stdout()) > > ### Name: convert_BIN2CSV > ### Title: Export Risoe BIN-file(s) to CSV-files > ### Aliases: convert_BIN2CSV > ### Keywords: IO > > ### ** Examples > > > ##transform Risoe.BINfileData values to a list > data(ExampleData.BINfileData, envir = environment()) > convert_BIN2CSV(subset(CWOSL.SAR.Data, POSITION == 1), export = FALSE) $`1_TL (PMT)` [,1] [,2] [1,] 0.884 2 [2,] 1.768 0 [3,] 2.652 13 [4,] 3.536 1 [5,] 4.420 1 [6,] 5.304 5 [7,] 6.188 6 [8,] 7.072 12 [9,] 7.956 12 [10,] 8.840 0 [11,] 9.724 2 [12,] 10.608 4 [13,] 11.492 2 [14,] 12.376 4 [15,] 13.260 6 [16,] 14.144 6 [17,] 15.028 4 [18,] 15.912 8 [19,] 16.796 6 [20,] 17.680 8 [21,] 18.564 3 [22,] 19.448 2 [23,] 20.332 8 [24,] 21.216 1 [25,] 22.100 4 [26,] 22.984 3 [27,] 23.868 6 [28,] 24.752 8 [29,] 25.636 3 [30,] 26.520 1 [31,] 27.404 3 [32,] 28.288 1 [33,] 29.172 1 [34,] 30.056 1 [35,] 30.940 12 [36,] 31.824 5 [37,] 32.708 1 [38,] 33.592 10 [39,] 34.476 0 [40,] 35.360 0 [41,] 36.244 2 [42,] 37.128 2 [43,] 38.012 2 [44,] 38.896 1 [45,] 39.780 12 [46,] 40.664 1 [47,] 41.548 3 [48,] 42.432 4 [49,] 43.316 2 [50,] 44.200 6 [51,] 45.084 4 [52,] 45.968 1 [53,] 46.852 3 [54,] 47.736 6 [55,] 48.620 6 [56,] 49.504 5 [57,] 50.388 5 [58,] 51.272 0 [59,] 52.156 0 [60,] 53.040 5 [61,] 53.924 2 [62,] 54.808 2 [63,] 55.692 0 [64,] 56.576 2 [65,] 57.460 2 [66,] 58.344 3 [67,] 59.228 15 [68,] 60.112 4 [69,] 60.996 0 [70,] 61.880 7 [71,] 62.764 4 [72,] 63.648 4 [73,] 64.532 0 [74,] 65.416 3 [75,] 66.300 14 [76,] 67.184 4 [77,] 68.068 7 [78,] 68.952 7 [79,] 69.836 4 [80,] 70.720 4 [81,] 71.604 2 [82,] 72.488 4 [83,] 73.372 1 [84,] 74.256 8 [85,] 75.140 3 [86,] 76.024 1 [87,] 76.908 3 [88,] 77.792 2 [89,] 78.676 5 [90,] 79.560 2 [91,] 80.444 17 [92,] 81.328 12 [93,] 82.212 5 [94,] 83.096 4 [95,] 83.980 3 [96,] 84.864 3 [97,] 85.748 18 [98,] 86.632 3 [99,] 87.516 12 [100,] 88.400 2 [101,] 89.284 4 [102,] 90.168 5 [103,] 91.052 7 [104,] 91.936 4 [105,] 92.820 4 [106,] 93.704 2 [107,] 94.588 8 [108,] 95.472 7 [109,] 96.356 1 [110,] 97.240 9 [111,] 98.124 5 [112,] 99.008 9 [113,] 99.892 5 [114,] 100.776 13 [115,] 101.660 0 [116,] 102.544 10 [117,] 103.428 1 [118,] 104.312 1 [119,] 105.196 1 [120,] 106.080 2 [121,] 106.964 6 [122,] 107.848 6 [123,] 108.732 9 [124,] 109.616 4 [125,] 110.500 12 [126,] 111.384 8 [127,] 112.268 1 [128,] 113.152 8 [129,] 114.036 2 [130,] 114.920 7 [131,] 115.804 6 [132,] 116.688 7 [133,] 117.572 1 [134,] 118.456 2 [135,] 119.340 5 [136,] 120.224 1 [137,] 121.108 6 [138,] 121.992 0 [139,] 122.876 11 [140,] 123.760 5 [141,] 124.644 1 [142,] 125.528 3 [143,] 126.412 13 [144,] 127.296 11 [145,] 128.180 1 [146,] 129.064 3 [147,] 129.948 5 [148,] 130.832 6 [149,] 131.716 5 [150,] 132.600 2 [151,] 133.484 5 [152,] 134.368 0 [153,] 135.252 16 [154,] 136.136 5 [155,] 137.020 10 [156,] 137.904 1 [157,] 138.788 3 [158,] 139.672 17 [159,] 140.556 4 [160,] 141.440 7 [161,] 142.324 10 [162,] 143.208 10 [163,] 144.092 4 [164,] 144.976 6 [165,] 145.860 3 [166,] 146.744 8 [167,] 147.628 4 [168,] 148.512 9 [169,] 149.396 5 [170,] 150.280 7 [171,] 151.164 6 [172,] 152.048 5 [173,] 152.932 8 [174,] 153.816 10 [175,] 154.700 8 [176,] 155.584 3 [177,] 156.468 7 [178,] 157.352 11 [179,] 158.236 4 [180,] 159.120 21 [181,] 160.004 14 [182,] 160.888 3 [183,] 161.772 4 [184,] 162.656 20 [185,] 163.540 9 [186,] 164.424 11 [187,] 165.308 8 [188,] 166.192 11 [189,] 167.076 14 [190,] 167.960 13 [191,] 168.844 12 [192,] 169.728 11 [193,] 170.612 25 [194,] 171.496 7 [195,] 172.380 9 [196,] 173.264 10 [197,] 174.148 18 [198,] 175.032 9 [199,] 175.916 15 [200,] 176.800 11 [201,] 177.684 19 [202,] 178.568 24 [203,] 179.452 29 [204,] 180.336 18 [205,] 181.220 27 [206,] 182.104 26 [207,] 182.988 25 [208,] 183.872 21 [209,] 184.756 17 [210,] 185.640 24 [211,] 186.524 32 [212,] 187.408 22 [213,] 188.292 25 [214,] 189.176 29 [215,] 190.060 35 [216,] 190.944 25 [217,] 191.828 27 [218,] 192.712 45 [219,] 193.596 43 [220,] 194.480 43 [221,] 195.364 44 [222,] 196.248 53 [223,] 197.132 51 [224,] 198.016 42 [225,] 198.900 56 [226,] 199.784 40 [227,] 200.668 49 [228,] 201.552 45 [229,] 202.436 85 [230,] 203.320 66 [231,] 204.204 72 [232,] 205.088 67 [233,] 205.972 83 [234,] 206.856 88 [235,] 207.740 90 [236,] 208.624 78 [237,] 209.508 81 [238,] 210.392 74 [239,] 211.276 108 [240,] 212.160 87 [241,] 213.044 110 [242,] 213.928 99 [243,] 214.812 123 [244,] 215.696 127 [245,] 216.580 144 [246,] 217.464 108 [247,] 218.348 120 [248,] 219.232 129 [249,] 220.116 131 [250,] 221.000 72 $`2_OSL (PMT)` [,1] [,2] [1,] 0.04 11111 [2,] 0.08 9280 [3,] 0.12 8218 [4,] 0.16 6794 [5,] 0.20 5743 [6,] 0.24 5050 [7,] 0.28 4156 [8,] 0.32 3750 [9,] 0.36 3170 [10,] 0.40 2703 [11,] 0.44 2408 [12,] 0.48 2066 [13,] 0.52 1790 [14,] 0.56 1647 [15,] 0.60 1461 [16,] 0.64 1289 [17,] 0.68 1010 [18,] 0.72 971 [19,] 0.76 829 [20,] 0.80 766 [21,] 0.84 713 [22,] 0.88 600 [23,] 0.92 555 [24,] 0.96 475 [25,] 1.00 433 [26,] 1.04 473 [27,] 1.08 362 [28,] 1.12 371 [29,] 1.16 313 [30,] 1.20 281 [31,] 1.24 269 [32,] 1.28 245 [33,] 1.32 247 [34,] 1.36 213 [35,] 1.40 185 [36,] 1.44 179 [37,] 1.48 186 [38,] 1.52 177 [39,] 1.56 113 [40,] 1.60 156 [41,] 1.64 117 [42,] 1.68 167 [43,] 1.72 116 [44,] 1.76 123 [45,] 1.80 120 [46,] 1.84 116 [47,] 1.88 87 [48,] 1.92 93 [49,] 1.96 109 [50,] 2.00 109 [51,] 2.04 80 [52,] 2.08 91 [53,] 2.12 94 [54,] 2.16 90 [55,] 2.20 101 [56,] 2.24 86 [57,] 2.28 107 [58,] 2.32 91 [59,] 2.36 73 [60,] 2.40 89 [61,] 2.44 68 [62,] 2.48 65 [63,] 2.52 72 [64,] 2.56 90 [65,] 2.60 72 [66,] 2.64 92 [67,] 2.68 77 [68,] 2.72 94 [69,] 2.76 86 [70,] 2.80 95 [71,] 2.84 107 [72,] 2.88 91 [73,] 2.92 52 [74,] 2.96 73 [75,] 3.00 74 [76,] 3.04 75 [77,] 3.08 75 [78,] 3.12 72 [79,] 3.16 102 [80,] 3.20 72 [81,] 3.24 65 [82,] 3.28 56 [83,] 3.32 90 [84,] 3.36 68 [85,] 3.40 70 [86,] 3.44 55 [87,] 3.48 51 [88,] 3.52 62 [89,] 3.56 53 [90,] 3.60 73 [91,] 3.64 74 [92,] 3.68 50 [93,] 3.72 66 [94,] 3.76 83 [95,] 3.80 51 [96,] 3.84 64 [97,] 3.88 38 [98,] 3.92 61 [99,] 3.96 50 [100,] 4.00 74 [101,] 4.04 54 [102,] 4.08 72 [103,] 4.12 74 [104,] 4.16 57 [105,] 4.20 64 [106,] 4.24 46 [107,] 4.28 55 [108,] 4.32 65 [109,] 4.36 80 [110,] 4.40 49 [111,] 4.44 31 [112,] 4.48 61 [113,] 4.52 67 [114,] 4.56 60 [115,] 4.60 49 [116,] 4.64 75 [117,] 4.68 58 [118,] 4.72 46 [119,] 4.76 55 [120,] 4.80 56 [121,] 4.84 53 [122,] 4.88 69 [123,] 4.92 55 [124,] 4.96 49 [125,] 5.00 56 [126,] 5.04 63 [127,] 5.08 46 [128,] 5.12 67 [129,] 5.16 69 [130,] 5.20 59 [131,] 5.24 57 [132,] 5.28 68 [133,] 5.32 74 [134,] 5.36 64 [135,] 5.40 45 [136,] 5.44 54 [137,] 5.48 45 [138,] 5.52 44 [139,] 5.56 85 [140,] 5.60 54 [141,] 5.64 46 [142,] 5.68 49 [143,] 5.72 67 [144,] 5.76 56 [145,] 5.80 37 [146,] 5.84 48 [147,] 5.88 56 [148,] 5.92 53 [149,] 5.96 42 [150,] 6.00 67 [151,] 6.04 63 [152,] 6.08 63 [153,] 6.12 57 [154,] 6.16 51 [155,] 6.20 52 [156,] 6.24 51 [157,] 6.28 52 [158,] 6.32 67 [159,] 6.36 39 [160,] 6.40 38 [161,] 6.44 46 [162,] 6.48 45 [163,] 6.52 48 [164,] 6.56 53 [165,] 6.60 45 [166,] 6.64 48 [167,] 6.68 40 [168,] 6.72 40 [169,] 6.76 47 [170,] 6.80 75 [171,] 6.84 37 [172,] 6.88 56 [173,] 6.92 47 [174,] 6.96 33 [175,] 7.00 47 [176,] 7.04 39 [177,] 7.08 50 [178,] 7.12 46 [179,] 7.16 44 [180,] 7.20 44 [181,] 7.24 36 [182,] 7.28 51 [183,] 7.32 44 [184,] 7.36 43 [185,] 7.40 39 [186,] 7.44 58 [187,] 7.48 60 [188,] 7.52 53 [189,] 7.56 61 [190,] 7.60 42 [191,] 7.64 66 [192,] 7.68 42 [193,] 7.72 59 [194,] 7.76 54 [195,] 7.80 66 [196,] 7.84 41 [197,] 7.88 42 [198,] 7.92 51 [199,] 7.96 28 [200,] 8.00 29 [201,] 8.04 52 [202,] 8.08 50 [203,] 8.12 54 [204,] 8.16 53 [205,] 8.20 53 [206,] 8.24 36 [207,] 8.28 35 [208,] 8.32 53 [209,] 8.36 31 [210,] 8.40 45 [211,] 8.44 40 [212,] 8.48 27 [213,] 8.52 52 [214,] 8.56 48 [215,] 8.60 49 [216,] 8.64 51 [217,] 8.68 51 [218,] 8.72 32 [219,] 8.76 44 [220,] 8.80 48 [221,] 8.84 56 [222,] 8.88 44 [223,] 8.92 55 [224,] 8.96 30 [225,] 9.00 35 [226,] 9.04 60 [227,] 9.08 47 [228,] 9.12 43 [229,] 9.16 31 [230,] 9.20 38 [231,] 9.24 34 [232,] 9.28 43 [233,] 9.32 44 [234,] 9.36 41 [235,] 9.40 53 [236,] 9.44 35 [237,] 9.48 82 [238,] 9.52 33 [239,] 9.56 44 [240,] 9.60 43 [241,] 9.64 40 [242,] 9.68 31 [243,] 9.72 46 [244,] 9.76 50 [245,] 9.80 42 [246,] 9.84 64 [247,] 9.88 47 [248,] 9.92 39 [249,] 9.96 48 [250,] 10.00 53 [251,] 10.04 47 [252,] 10.08 49 [253,] 10.12 35 [254,] 10.16 40 [255,] 10.20 35 [256,] 10.24 42 [257,] 10.28 38 [258,] 10.32 35 [259,] 10.36 38 [260,] 10.40 53 [261,] 10.44 48 [262,] 10.48 34 [263,] 10.52 55 [264,] 10.56 36 [265,] 10.60 52 [266,] 10.64 52 [267,] 10.68 41 [268,] 10.72 47 [269,] 10.76 37 [270,] 10.80 43 [271,] 10.84 39 [272,] 10.88 36 [273,] 10.92 36 [274,] 10.96 27 [275,] 11.00 41 [276,] 11.04 47 [277,] 11.08 38 [278,] 11.12 36 [279,] 11.16 39 [280,] 11.20 32 [281,] 11.24 32 [282,] 11.28 37 [283,] 11.32 43 [284,] 11.36 39 [285,] 11.40 48 [286,] 11.44 41 [287,] 11.48 43 [288,] 11.52 42 [289,] 11.56 50 [290,] 11.60 48 [291,] 11.64 48 [292,] 11.68 54 [293,] 11.72 42 [294,] 11.76 44 [295,] 11.80 39 [296,] 11.84 30 [297,] 11.88 32 [298,] 11.92 43 [299,] 11.96 52 [300,] 12.00 36 [301,] 12.04 37 [302,] 12.08 44 [303,] 12.12 39 [304,] 12.16 46 [305,] 12.20 44 [306,] 12.24 31 [307,] 12.28 44 [308,] 12.32 45 [309,] 12.36 33 [310,] 12.40 39 [311,] 12.44 61 [312,] 12.48 35 [313,] 12.52 27 [314,] 12.56 47 [315,] 12.60 50 [316,] 12.64 39 [317,] 12.68 25 [318,] 12.72 31 [319,] 12.76 47 [320,] 12.80 46 [321,] 12.84 40 [322,] 12.88 55 [323,] 12.92 50 [324,] 12.96 51 [325,] 13.00 46 [326,] 13.04 46 [327,] 13.08 50 [328,] 13.12 43 [329,] 13.16 44 [330,] 13.20 37 [331,] 13.24 45 [332,] 13.28 38 [333,] 13.32 40 [334,] 13.36 28 [335,] 13.40 51 [336,] 13.44 31 [337,] 13.48 41 [338,] 13.52 42 [339,] 13.56 39 [340,] 13.60 33 [341,] 13.64 49 [342,] 13.68 46 [343,] 13.72 37 [344,] 13.76 27 [345,] 13.80 40 [346,] 13.84 40 [347,] 13.88 25 [348,] 13.92 30 [349,] 13.96 32 [350,] 14.00 42 [351,] 14.04 30 [352,] 14.08 33 [353,] 14.12 59 [354,] 14.16 36 [355,] 14.20 45 [356,] 14.24 38 [357,] 14.28 40 [358,] 14.32 31 [359,] 14.36 30 [360,] 14.40 53 [361,] 14.44 42 [362,] 14.48 48 [363,] 14.52 37 [364,] 14.56 43 [365,] 14.60 28 [366,] 14.64 33 [367,] 14.68 41 [368,] 14.72 35 [369,] 14.76 28 [370,] 14.80 24 [371,] 14.84 28 [372,] 14.88 36 [373,] 14.92 42 [374,] 14.96 49 [375,] 15.00 55 [376,] 15.04 25 [377,] 15.08 30 [378,] 15.12 38 [379,] 15.16 31 [380,] 15.20 34 [381,] 15.24 43 [382,] 15.28 51 [383,] 15.32 50 [384,] 15.36 45 [385,] 15.40 39 [386,] 15.44 41 [387,] 15.48 42 [388,] 15.52 27 [389,] 15.56 27 [390,] 15.60 62 [391,] 15.64 30 [392,] 15.68 24 [393,] 15.72 44 [394,] 15.76 40 [395,] 15.80 35 [396,] 15.84 51 [397,] 15.88 52 [398,] 15.92 23 [399,] 15.96 42 [400,] 16.00 34 [401,] 16.04 70 [402,] 16.08 41 [403,] 16.12 44 [404,] 16.16 45 [405,] 16.20 37 [406,] 16.24 31 [407,] 16.28 34 [408,] 16.32 32 [409,] 16.36 47 [410,] 16.40 37 [411,] 16.44 37 [412,] 16.48 28 [413,] 16.52 47 [414,] 16.56 39 [415,] 16.60 40 [416,] 16.64 39 [417,] 16.68 48 [418,] 16.72 32 [419,] 16.76 25 [420,] 16.80 37 [421,] 16.84 42 [422,] 16.88 31 [423,] 16.92 43 [424,] 16.96 26 [425,] 17.00 40 [426,] 17.04 43 [427,] 17.08 36 [428,] 17.12 37 [429,] 17.16 32 [430,] 17.20 42 [431,] 17.24 31 [432,] 17.28 35 [433,] 17.32 28 [434,] 17.36 38 [435,] 17.40 34 [436,] 17.44 43 [437,] 17.48 48 [438,] 17.52 46 [439,] 17.56 44 [440,] 17.60 37 [441,] 17.64 37 [442,] 17.68 49 [443,] 17.72 31 [444,] 17.76 41 [445,] 17.80 41 [446,] 17.84 22 [447,] 17.88 37 [448,] 17.92 32 [449,] 17.96 48 [450,] 18.00 36 [451,] 18.04 33 [452,] 18.08 33 [453,] 18.12 43 [454,] 18.16 51 [455,] 18.20 22 [456,] 18.24 39 [457,] 18.28 45 [458,] 18.32 33 [459,] 18.36 36 [460,] 18.40 38 [461,] 18.44 30 [462,] 18.48 35 [463,] 18.52 36 [464,] 18.56 32 [465,] 18.60 39 [466,] 18.64 39 [467,] 18.68 28 [468,] 18.72 41 [469,] 18.76 28 [470,] 18.80 41 [471,] 18.84 32 [472,] 18.88 32 [473,] 18.92 51 [474,] 18.96 29 [475,] 19.00 41 [476,] 19.04 49 [477,] 19.08 30 [478,] 19.12 37 [479,] 19.16 32 [480,] 19.20 37 [481,] 19.24 38 [482,] 19.28 31 [483,] 19.32 40 [484,] 19.36 35 [485,] 19.40 44 [486,] 19.44 36 [487,] 19.48 44 [488,] 19.52 33 [489,] 19.56 35 [490,] 19.60 46 [491,] 19.64 45 [492,] 19.68 25 [493,] 19.72 47 [494,] 19.76 35 [495,] 19.80 25 [496,] 19.84 26 [497,] 19.88 28 [498,] 19.92 36 [499,] 19.96 39 [500,] 20.00 43 [501,] 20.04 46 [502,] 20.08 28 [503,] 20.12 40 [504,] 20.16 50 [505,] 20.20 26 [506,] 20.24 37 [507,] 20.28 43 [508,] 20.32 33 [509,] 20.36 24 [510,] 20.40 42 [511,] 20.44 40 [512,] 20.48 39 [513,] 20.52 41 [514,] 20.56 34 [515,] 20.60 48 [516,] 20.64 46 [517,] 20.68 44 [518,] 20.72 36 [519,] 20.76 40 [520,] 20.80 40 [521,] 20.84 47 [522,] 20.88 38 [523,] 20.92 43 [524,] 20.96 35 [525,] 21.00 56 [526,] 21.04 34 [527,] 21.08 36 [528,] 21.12 26 [529,] 21.16 36 [530,] 21.20 43 [531,] 21.24 43 [532,] 21.28 40 [533,] 21.32 42 [534,] 21.36 30 [535,] 21.40 32 [536,] 21.44 32 [537,] 21.48 29 [538,] 21.52 39 [539,] 21.56 26 [540,] 21.60 40 [541,] 21.64 39 [542,] 21.68 42 [543,] 21.72 28 [544,] 21.76 39 [545,] 21.80 42 [546,] 21.84 33 [547,] 21.88 47 [548,] 21.92 35 [549,] 21.96 28 [550,] 22.00 36 [551,] 22.04 29 [552,] 22.08 22 [553,] 22.12 31 [554,] 22.16 28 [555,] 22.20 30 [556,] 22.24 44 [557,] 22.28 44 [558,] 22.32 36 [559,] 22.36 46 [560,] 22.40 29 [561,] 22.44 30 [562,] 22.48 42 [563,] 22.52 23 [564,] 22.56 28 [565,] 22.60 34 [566,] 22.64 21 [567,] 22.68 51 [568,] 22.72 40 [569,] 22.76 37 [570,] 22.80 24 [571,] 22.84 40 [572,] 22.88 47 [573,] 22.92 45 [574,] 22.96 34 [575,] 23.00 42 [576,] 23.04 36 [577,] 23.08 59 [578,] 23.12 34 [579,] 23.16 31 [580,] 23.20 39 [581,] 23.24 27 [582,] 23.28 31 [583,] 23.32 35 [584,] 23.36 48 [585,] 23.40 30 [586,] 23.44 46 [587,] 23.48 17 [588,] 23.52 47 [589,] 23.56 28 [590,] 23.60 42 [591,] 23.64 38 [592,] 23.68 37 [593,] 23.72 33 [594,] 23.76 42 [595,] 23.80 32 [596,] 23.84 21 [597,] 23.88 20 [598,] 23.92 33 [599,] 23.96 30 [600,] 24.00 32 [601,] 24.04 31 [602,] 24.08 28 [603,] 24.12 23 [604,] 24.16 36 [605,] 24.20 20 [606,] 24.24 34 [607,] 24.28 29 [608,] 24.32 44 [609,] 24.36 43 [610,] 24.40 43 [611,] 24.44 31 [612,] 24.48 39 [613,] 24.52 37 [614,] 24.56 35 [615,] 24.60 37 [616,] 24.64 30 [617,] 24.68 41 [618,] 24.72 37 [619,] 24.76 32 [620,] 24.80 31 [621,] 24.84 37 [622,] 24.88 45 [623,] 24.92 32 [624,] 24.96 29 [625,] 25.00 34 [626,] 25.04 41 [627,] 25.08 22 [628,] 25.12 25 [629,] 25.16 43 [630,] 25.20 15 [631,] 25.24 24 [632,] 25.28 29 [633,] 25.32 30 [634,] 25.36 24 [635,] 25.40 27 [636,] 25.44 29 [637,] 25.48 53 [638,] 25.52 29 [639,] 25.56 32 [640,] 25.60 19 [641,] 25.64 39 [642,] 25.68 37 [643,] 25.72 42 [644,] 25.76 40 [645,] 25.80 35 [646,] 25.84 27 [647,] 25.88 39 [648,] 25.92 23 [649,] 25.96 25 [650,] 26.00 50 [651,] 26.04 25 [652,] 26.08 35 [653,] 26.12 40 [654,] 26.16 39 [655,] 26.20 32 [656,] 26.24 41 [657,] 26.28 28 [658,] 26.32 29 [659,] 26.36 28 [660,] 26.40 41 [661,] 26.44 28 [662,] 26.48 45 [663,] 26.52 23 [664,] 26.56 32 [665,] 26.60 43 [666,] 26.64 34 [667,] 26.68 36 [668,] 26.72 27 [669,] 26.76 22 [670,] 26.80 45 [671,] 26.84 41 [672,] 26.88 42 [673,] 26.92 18 [674,] 26.96 42 [675,] 27.00 31 [676,] 27.04 50 [677,] 27.08 24 [678,] 27.12 49 [679,] 27.16 31 [680,] 27.20 23 [681,] 27.24 43 [682,] 27.28 27 [683,] 27.32 32 [684,] 27.36 19 [685,] 27.40 31 [686,] 27.44 36 [687,] 27.48 29 [688,] 27.52 46 [689,] 27.56 36 [690,] 27.60 28 [691,] 27.64 28 [692,] 27.68 24 [693,] 27.72 36 [694,] 27.76 40 [695,] 27.80 41 [696,] 27.84 44 [697,] 27.88 38 [698,] 27.92 28 [699,] 27.96 30 [700,] 28.00 33 [701,] 28.04 24 [702,] 28.08 21 [703,] 28.12 32 [704,] 28.16 41 [705,] 28.20 31 [706,] 28.24 30 [707,] 28.28 35 [708,] 28.32 44 [709,] 28.36 36 [710,] 28.40 32 [711,] 28.44 40 [712,] 28.48 49 [713,] 28.52 37 [714,] 28.56 26 [715,] 28.60 30 [716,] 28.64 29 [717,] 28.68 28 [718,] 28.72 20 [719,] 28.76 28 [720,] 28.80 26 [721,] 28.84 41 [722,] 28.88 34 [723,] 28.92 26 [724,] 28.96 27 [725,] 29.00 25 [726,] 29.04 41 [727,] 29.08 34 [728,] 29.12 25 [729,] 29.16 35 [730,] 29.20 31 [731,] 29.24 44 [732,] 29.28 25 [733,] 29.32 41 [734,] 29.36 23 [735,] 29.40 52 [736,] 29.44 38 [737,] 29.48 26 [738,] 29.52 31 [739,] 29.56 27 [740,] 29.60 45 [741,] 29.64 33 [742,] 29.68 30 [743,] 29.72 27 [744,] 29.76 26 [745,] 29.80 30 [746,] 29.84 32 [747,] 29.88 28 [748,] 29.92 27 [749,] 29.96 34 [750,] 30.00 30 [751,] 30.04 31 [752,] 30.08 25 [753,] 30.12 23 [754,] 30.16 30 [755,] 30.20 32 [756,] 30.24 30 [757,] 30.28 27 [758,] 30.32 17 [759,] 30.36 33 [760,] 30.40 35 [761,] 30.44 29 [762,] 30.48 35 [763,] 30.52 39 [764,] 30.56 32 [765,] 30.60 41 [766,] 30.64 36 [767,] 30.68 28 [768,] 30.72 32 [769,] 30.76 26 [770,] 30.80 28 [771,] 30.84 24 [772,] 30.88 25 [773,] 30.92 33 [774,] 30.96 25 [775,] 31.00 30 [776,] 31.04 34 [777,] 31.08 31 [778,] 31.12 33 [779,] 31.16 22 [780,] 31.20 27 [781,] 31.24 29 [782,] 31.28 22 [783,] 31.32 29 [784,] 31.36 61 [785,] 31.40 59 [786,] 31.44 40 [787,] 31.48 22 [788,] 31.52 44 [789,] 31.56 28 [790,] 31.60 28 [791,] 31.64 26 [792,] 31.68 27 [793,] 31.72 43 [794,] 31.76 29 [795,] 31.80 21 [796,] 31.84 35 [797,] 31.88 25 [798,] 31.92 36 [799,] 31.96 17 [800,] 32.00 39 [801,] 32.04 37 [802,] 32.08 28 [803,] 32.12 37 [804,] 32.16 33 [805,] 32.20 33 [806,] 32.24 27 [807,] 32.28 24 [808,] 32.32 30 [809,] 32.36 30 [810,] 32.40 42 [811,] 32.44 32 [812,] 32.48 33 [813,] 32.52 43 [814,] 32.56 39 [815,] 32.60 31 [816,] 32.64 34 [817,] 32.68 31 [818,] 32.72 32 [819,] 32.76 34 [820,] 32.80 33 [821,] 32.84 23 [822,] 32.88 17 [823,] 32.92 36 [824,] 32.96 26 [825,] 33.00 31 [826,] 33.04 36 [827,] 33.08 27 [828,] 33.12 49 [829,] 33.16 26 [830,] 33.20 30 [831,] 33.24 32 [832,] 33.28 26 [833,] 33.32 29 [834,] 33.36 27 [835,] 33.40 27 [836,] 33.44 18 [837,] 33.48 32 [838,] 33.52 22 [839,] 33.56 37 [840,] 33.60 29 [841,] 33.64 23 [842,] 33.68 40 [843,] 33.72 48 [844,] 33.76 31 [845,] 33.80 30 [846,] 33.84 29 [847,] 33.88 35 [848,] 33.92 19 [849,] 33.96 25 [850,] 34.00 18 [851,] 34.04 24 [852,] 34.08 32 [853,] 34.12 35 [854,] 34.16 38 [855,] 34.20 17 [856,] 34.24 25 [857,] 34.28 28 [858,] 34.32 18 [859,] 34.36 23 [860,] 34.40 30 [861,] 34.44 21 [862,] 34.48 23 [863,] 34.52 38 [864,] 34.56 24 [865,] 34.60 37 [866,] 34.64 29 [867,] 34.68 32 [868,] 34.72 42 [869,] 34.76 32 [870,] 34.80 31 [871,] 34.84 34 [872,] 34.88 18 [873,] 34.92 37 [874,] 34.96 26 [875,] 35.00 30 [876,] 35.04 24 [877,] 35.08 41 [878,] 35.12 34 [879,] 35.16 30 [880,] 35.20 36 [881,] 35.24 35 [882,] 35.28 29 [883,] 35.32 38 [884,] 35.36 30 [885,] 35.40 26 [886,] 35.44 36 [887,] 35.48 34 [888,] 35.52 35 [889,] 35.56 31 [890,] 35.60 25 [891,] 35.64 18 [892,] 35.68 38 [893,] 35.72 36 [894,] 35.76 30 [895,] 35.80 29 [896,] 35.84 25 [897,] 35.88 21 [898,] 35.92 33 [899,] 35.96 40 [900,] 36.00 24 [901,] 36.04 36 [902,] 36.08 27 [903,] 36.12 27 [904,] 36.16 32 [905,] 36.20 39 [906,] 36.24 14 [907,] 36.28 26 [908,] 36.32 31 [909,] 36.36 23 [910,] 36.40 41 [911,] 36.44 33 [912,] 36.48 22 [913,] 36.52 27 [914,] 36.56 33 [915,] 36.60 25 [916,] 36.64 40 [917,] 36.68 34 [918,] 36.72 35 [919,] 36.76 15 [920,] 36.80 30 [921,] 36.84 24 [922,] 36.88 39 [923,] 36.92 32 [924,] 36.96 29 [925,] 37.00 32 [926,] 37.04 32 [927,] 37.08 36 [928,] 37.12 24 [929,] 37.16 33 [930,] 37.20 32 [931,] 37.24 26 [932,] 37.28 38 [933,] 37.32 19 [934,] 37.36 22 [935,] 37.40 24 [936,] 37.44 23 [937,] 37.48 29 [938,] 37.52 30 [939,] 37.56 32 [940,] 37.60 39 [941,] 37.64 31 [942,] 37.68 42 [943,] 37.72 20 [944,] 37.76 24 [945,] 37.80 22 [946,] 37.84 15 [947,] 37.88 32 [948,] 37.92 26 [949,] 37.96 30 [950,] 38.00 32 [951,] 38.04 41 [952,] 38.08 33 [953,] 38.12 24 [954,] 38.16 40 [955,] 38.20 22 [956,] 38.24 31 [957,] 38.28 25 [958,] 38.32 27 [959,] 38.36 28 [960,] 38.40 26 [961,] 38.44 29 [962,] 38.48 28 [963,] 38.52 33 [964,] 38.56 30 [965,] 38.60 22 [966,] 38.64 30 [967,] 38.68 34 [968,] 38.72 22 [969,] 38.76 37 [970,] 38.80 47 [971,] 38.84 23 [972,] 38.88 22 [973,] 38.92 21 [974,] 38.96 34 [975,] 39.00 30 [976,] 39.04 25 [977,] 39.08 31 [978,] 39.12 33 [979,] 39.16 29 [980,] 39.20 20 [981,] 39.24 27 [982,] 39.28 46 [983,] 39.32 29 [984,] 39.36 28 [985,] 39.40 38 [986,] 39.44 30 [987,] 39.48 36 [988,] 39.52 23 [989,] 39.56 25 [990,] 39.60 25 [991,] 39.64 44 [992,] 39.68 32 [993,] 39.72 37 [994,] 39.76 46 [995,] 39.80 24 [996,] 39.84 34 [997,] 39.88 29 [998,] 39.92 46 [999,] 39.96 44 [1000,] 40.00 35 $`3_TL (PMT)` [,1] [,2] [1,] 0.64 4 [2,] 1.28 8 [3,] 1.92 5 [4,] 2.56 7 [5,] 3.20 2 [6,] 3.84 3 [7,] 4.48 0 [8,] 5.12 4 [9,] 5.76 1 [10,] 6.40 4 [11,] 7.04 8 [12,] 7.68 10 [13,] 8.32 25 [14,] 8.96 6 [15,] 9.60 6 [16,] 10.24 2 [17,] 10.88 1 [18,] 11.52 4 [19,] 12.16 6 [20,] 12.80 0 [21,] 13.44 0 [22,] 14.08 4 [23,] 14.72 1 [24,] 15.36 12 [25,] 16.00 14 [26,] 16.64 3 [27,] 17.28 2 [28,] 17.92 5 [29,] 18.56 4 [30,] 19.20 3 [31,] 19.84 6 [32,] 20.48 5 [33,] 21.12 6 [34,] 21.76 1 [35,] 22.40 4 [36,] 23.04 0 [37,] 23.68 3 [38,] 24.32 2 [39,] 24.96 0 [40,] 25.60 5 [41,] 26.24 2 [42,] 26.88 7 [43,] 27.52 0 [44,] 28.16 4 [45,] 28.80 3 [46,] 29.44 7 [47,] 30.08 6 [48,] 30.72 3 [49,] 31.36 10 [50,] 32.00 2 [51,] 32.64 0 [52,] 33.28 0 [53,] 33.92 0 [54,] 34.56 2 [55,] 35.20 6 [56,] 35.84 2 [57,] 36.48 1 [58,] 37.12 6 [59,] 37.76 2 [60,] 38.40 12 [61,] 39.04 3 [62,] 39.68 10 [63,] 40.32 3 [64,] 40.96 6 [65,] 41.60 2 [66,] 42.24 6 [67,] 42.88 4 [68,] 43.52 6 [69,] 44.16 12 [70,] 44.80 5 [71,] 45.44 5 [72,] 46.08 7 [73,] 46.72 1 [74,] 47.36 3 [75,] 48.00 9 [76,] 48.64 4 [77,] 49.28 2 [78,] 49.92 3 [79,] 50.56 4 [80,] 51.20 5 [81,] 51.84 10 [82,] 52.48 5 [83,] 53.12 15 [84,] 53.76 17 [85,] 54.40 9 [86,] 55.04 8 [87,] 55.68 12 [88,] 56.32 1 [89,] 56.96 8 [90,] 57.60 6 [91,] 58.24 11 [92,] 58.88 10 [93,] 59.52 4 [94,] 60.16 5 [95,] 60.80 6 [96,] 61.44 10 [97,] 62.08 13 [98,] 62.72 23 [99,] 63.36 18 [100,] 64.00 20 [101,] 64.64 20 [102,] 65.28 19 [103,] 65.92 15 [104,] 66.56 21 [105,] 67.20 17 [106,] 67.84 24 [107,] 68.48 28 [108,] 69.12 25 [109,] 69.76 15 [110,] 70.40 34 [111,] 71.04 47 [112,] 71.68 32 [113,] 72.32 33 [114,] 72.96 27 [115,] 73.60 31 [116,] 74.24 32 [117,] 74.88 33 [118,] 75.52 50 [119,] 76.16 38 [120,] 76.80 33 [121,] 77.44 42 [122,] 78.08 53 [123,] 78.72 60 [124,] 79.36 51 [125,] 80.00 62 [126,] 80.64 67 [127,] 81.28 64 [128,] 81.92 68 [129,] 82.56 74 [130,] 83.20 62 [131,] 83.84 66 [132,] 84.48 69 [133,] 85.12 103 [134,] 85.76 94 [135,] 86.40 93 [136,] 87.04 103 [137,] 87.68 108 [138,] 88.32 112 [139,] 88.96 96 [140,] 89.60 119 [141,] 90.24 137 [142,] 90.88 121 [143,] 91.52 132 [144,] 92.16 165 [145,] 92.80 138 [146,] 93.44 141 [147,] 94.08 146 [148,] 94.72 160 [149,] 95.36 134 [150,] 96.00 170 [151,] 96.64 157 [152,] 97.28 195 [153,] 97.92 173 [154,] 98.56 170 [155,] 99.20 207 [156,] 99.84 189 [157,] 100.48 209 [158,] 101.12 210 [159,] 101.76 188 [160,] 102.40 233 [161,] 103.04 216 [162,] 103.68 212 [163,] 104.32 251 [164,] 104.96 256 [165,] 105.60 173 [166,] 106.24 239 [167,] 106.88 204 [168,] 107.52 218 [169,] 108.16 199 [170,] 108.80 249 [171,] 109.44 199 [172,] 110.08 214 [173,] 110.72 204 [174,] 111.36 176 [175,] 112.00 182 [176,] 112.64 220 [177,] 113.28 167 [178,] 113.92 194 [179,] 114.56 174 [180,] 115.20 163 [181,] 115.84 158 [182,] 116.48 174 [183,] 117.12 126 [184,] 117.76 128 [185,] 118.40 135 [186,] 119.04 125 [187,] 119.68 105 [188,] 120.32 93 [189,] 120.96 110 [190,] 121.60 92 [191,] 122.24 85 [192,] 122.88 76 [193,] 123.52 92 [194,] 124.16 56 [195,] 124.80 75 [196,] 125.44 68 [197,] 126.08 52 [198,] 126.72 50 [199,] 127.36 62 [200,] 128.00 81 [201,] 128.64 66 [202,] 129.28 62 [203,] 129.92 53 [204,] 130.56 64 [205,] 131.20 56 [206,] 131.84 79 [207,] 132.48 56 [208,] 133.12 57 [209,] 133.76 62 [210,] 134.40 51 [211,] 135.04 57 [212,] 135.68 54 [213,] 136.32 72 [214,] 136.96 57 [215,] 137.60 74 [216,] 138.24 57 [217,] 138.88 65 [218,] 139.52 76 [219,] 140.16 62 [220,] 140.80 60 [221,] 141.44 63 [222,] 142.08 66 [223,] 142.72 64 [224,] 143.36 61 [225,] 144.00 54 [226,] 144.64 77 [227,] 145.28 75 [228,] 145.92 72 [229,] 146.56 61 [230,] 147.20 75 [231,] 147.84 83 [232,] 148.48 53 [233,] 149.12 64 [234,] 149.76 53 [235,] 150.40 54 [236,] 151.04 59 [237,] 151.68 61 [238,] 152.32 50 [239,] 152.96 67 [240,] 153.60 71 [241,] 154.24 62 [242,] 154.88 59 [243,] 155.52 75 [244,] 156.16 77 [245,] 156.80 68 [246,] 157.44 72 [247,] 158.08 52 [248,] 158.72 71 [249,] 159.36 56 [250,] 160.00 65 $`4_OSL (PMT)` [,1] [,2] [1,] 0.04 2538 [2,] 0.08 2233 [3,] 0.12 1860 [4,] 0.16 1680 [5,] 0.20 1376 [6,] 0.24 1314 [7,] 0.28 1195 [8,] 0.32 979 [9,] 0.36 915 [10,] 0.40 787 [11,] 0.44 582 [12,] 0.48 546 [13,] 0.52 572 [14,] 0.56 555 [15,] 0.60 444 [16,] 0.64 433 [17,] 0.68 373 [18,] 0.72 361 [19,] 0.76 283 [20,] 0.80 301 [21,] 0.84 238 [22,] 0.88 254 [23,] 0.92 241 [24,] 0.96 214 [25,] 1.00 243 [26,] 1.04 209 [27,] 1.08 175 [28,] 1.12 174 [29,] 1.16 168 [30,] 1.20 151 [31,] 1.24 146 [32,] 1.28 172 [33,] 1.32 152 [34,] 1.36 126 [35,] 1.40 113 [36,] 1.44 126 [37,] 1.48 120 [38,] 1.52 127 [39,] 1.56 108 [40,] 1.60 114 [41,] 1.64 131 [42,] 1.68 109 [43,] 1.72 120 [44,] 1.76 100 [45,] 1.80 97 [46,] 1.84 102 [47,] 1.88 106 [48,] 1.92 75 [49,] 1.96 117 [50,] 2.00 106 [51,] 2.04 93 [52,] 2.08 104 [53,] 2.12 91 [54,] 2.16 113 [55,] 2.20 95 [56,] 2.24 90 [57,] 2.28 96 [58,] 2.32 70 [59,] 2.36 127 [60,] 2.40 85 [61,] 2.44 100 [62,] 2.48 72 [63,] 2.52 80 [64,] 2.56 72 [65,] 2.60 83 [66,] 2.64 83 [67,] 2.68 72 [68,] 2.72 69 [69,] 2.76 68 [70,] 2.80 77 [71,] 2.84 79 [72,] 2.88 98 [73,] 2.92 93 [74,] 2.96 87 [75,] 3.00 89 [76,] 3.04 42 [77,] 3.08 51 [78,] 3.12 78 [79,] 3.16 93 [80,] 3.20 78 [81,] 3.24 78 [82,] 3.28 79 [83,] 3.32 60 [84,] 3.36 65 [85,] 3.40 83 [86,] 3.44 78 [87,] 3.48 71 [88,] 3.52 71 [89,] 3.56 74 [90,] 3.60 74 [91,] 3.64 76 [92,] 3.68 72 [93,] 3.72 77 [94,] 3.76 88 [95,] 3.80 80 [96,] 3.84 55 [97,] 3.88 55 [98,] 3.92 60 [99,] 3.96 73 [100,] 4.00 63 [101,] 4.04 70 [102,] 4.08 53 [103,] 4.12 62 [104,] 4.16 57 [105,] 4.20 81 [106,] 4.24 53 [107,] 4.28 40 [108,] 4.32 75 [109,] 4.36 65 [110,] 4.40 64 [111,] 4.44 77 [112,] 4.48 61 [113,] 4.52 69 [114,] 4.56 63 [115,] 4.60 59 [116,] 4.64 56 [117,] 4.68 62 [118,] 4.72 70 [119,] 4.76 79 [120,] 4.80 83 [121,] 4.84 68 [122,] 4.88 71 [123,] 4.92 59 [124,] 4.96 62 [125,] 5.00 71 [126,] 5.04 45 [127,] 5.08 88 [128,] 5.12 70 [129,] 5.16 54 [130,] 5.20 72 [131,] 5.24 57 [132,] 5.28 59 [133,] 5.32 64 [134,] 5.36 62 [135,] 5.40 68 [136,] 5.44 67 [137,] 5.48 60 [138,] 5.52 57 [139,] 5.56 82 [140,] 5.60 60 [141,] 5.64 53 [142,] 5.68 75 [143,] 5.72 53 [144,] 5.76 66 [145,] 5.80 61 [146,] 5.84 65 [147,] 5.88 51 [148,] 5.92 68 [149,] 5.96 54 [150,] 6.00 64 [151,] 6.04 42 [152,] 6.08 54 [153,] 6.12 62 [154,] 6.16 41 [155,] 6.20 41 [156,] 6.24 81 [157,] 6.28 48 [158,] 6.32 67 [159,] 6.36 61 [160,] 6.40 82 [161,] 6.44 58 [162,] 6.48 48 [163,] 6.52 69 [164,] 6.56 51 [165,] 6.60 56 [166,] 6.64 43 [167,] 6.68 55 [168,] 6.72 62 [169,] 6.76 41 [170,] 6.80 61 [171,] 6.84 59 [172,] 6.88 76 [173,] 6.92 65 [174,] 6.96 67 [175,] 7.00 68 [176,] 7.04 36 [177,] 7.08 45 [178,] 7.12 47 [179,] 7.16 52 [180,] 7.20 53 [181,] 7.24 52 [182,] 7.28 70 [183,] 7.32 57 [184,] 7.36 33 [185,] 7.40 38 [186,] 7.44 62 [187,] 7.48 64 [188,] 7.52 56 [189,] 7.56 49 [190,] 7.60 51 [191,] 7.64 49 [192,] 7.68 64 [193,] 7.72 47 [194,] 7.76 61 [195,] 7.80 69 [196,] 7.84 55 [197,] 7.88 63 [198,] 7.92 50 [199,] 7.96 45 [200,] 8.00 46 [201,] 8.04 44 [202,] 8.08 54 [203,] 8.12 54 [204,] 8.16 38 [205,] 8.20 55 [206,] 8.24 64 [207,] 8.28 45 [208,] 8.32 47 [209,] 8.36 45 [210,] 8.40 42 [211,] 8.44 56 [212,] 8.48 64 [213,] 8.52 47 [214,] 8.56 46 [215,] 8.60 73 [216,] 8.64 50 [217,] 8.68 50 [218,] 8.72 58 [219,] 8.76 42 [220,] 8.80 56 [221,] 8.84 37 [222,] 8.88 52 [223,] 8.92 50 [224,] 8.96 52 [225,] 9.00 58 [226,] 9.04 49 [227,] 9.08 58 [228,] 9.12 36 [229,] 9.16 56 [230,] 9.20 44 [231,] 9.24 51 [232,] 9.28 40 [233,] 9.32 59 [234,] 9.36 51 [235,] 9.40 43 [236,] 9.44 49 [237,] 9.48 62 [238,] 9.52 57 [239,] 9.56 53 [240,] 9.60 57 [241,] 9.64 51 [242,] 9.68 48 [243,] 9.72 46 [244,] 9.76 53 [245,] 9.80 56 [246,] 9.84 61 [247,] 9.88 71 [248,] 9.92 39 [249,] 9.96 52 [250,] 10.00 44 [251,] 10.04 45 [252,] 10.08 49 [253,] 10.12 56 [254,] 10.16 49 [255,] 10.20 58 [256,] 10.24 49 [257,] 10.28 58 [258,] 10.32 56 [259,] 10.36 147 [260,] 10.40 64 [261,] 10.44 57 [262,] 10.48 43 [263,] 10.52 51 [264,] 10.56 47 [265,] 10.60 39 [266,] 10.64 47 [267,] 10.68 45 [268,] 10.72 32 [269,] 10.76 54 [270,] 10.80 49 [271,] 10.84 42 [272,] 10.88 53 [273,] 10.92 52 [274,] 10.96 41 [275,] 11.00 54 [276,] 11.04 37 [277,] 11.08 44 [278,] 11.12 50 [279,] 11.16 47 [280,] 11.20 65 [281,] 11.24 51 [282,] 11.28 38 [283,] 11.32 65 [284,] 11.36 60 [285,] 11.40 46 [286,] 11.44 42 [287,] 11.48 51 [288,] 11.52 60 [289,] 11.56 43 [290,] 11.60 45 [291,] 11.64 44 [292,] 11.68 45 [293,] 11.72 48 [294,] 11.76 60 [295,] 11.80 29 [296,] 11.84 53 [297,] 11.88 47 [298,] 11.92 44 [299,] 11.96 27 [300,] 12.00 51 [301,] 12.04 48 [302,] 12.08 33 [303,] 12.12 39 [304,] 12.16 31 [305,] 12.20 35 [306,] 12.24 49 [307,] 12.28 42 [308,] 12.32 64 [309,] 12.36 45 [310,] 12.40 34 [311,] 12.44 41 [312,] 12.48 34 [313,] 12.52 51 [314,] 12.56 54 [315,] 12.60 38 [316,] 12.64 49 [317,] 12.68 61 [318,] 12.72 35 [319,] 12.76 51 [320,] 12.80 36 [321,] 12.84 60 [322,] 12.88 43 [323,] 12.92 60 [324,] 12.96 41 [325,] 13.00 34 [326,] 13.04 47 [327,] 13.08 50 [328,] 13.12 53 [329,] 13.16 44 [330,] 13.20 51 [331,] 13.24 42 [332,] 13.28 40 [333,] 13.32 48 [334,] 13.36 46 [335,] 13.40 31 [336,] 13.44 39 [337,] 13.48 48 [338,] 13.52 50 [339,] 13.56 28 [340,] 13.60 35 [341,] 13.64 46 [342,] 13.68 52 [343,] 13.72 42 [344,] 13.76 51 [345,] 13.80 37 [346,] 13.84 49 [347,] 13.88 42 [348,] 13.92 53 [349,] 13.96 48 [350,] 14.00 50 [351,] 14.04 55 [352,] 14.08 43 [353,] 14.12 57 [354,] 14.16 54 [355,] 14.20 37 [356,] 14.24 47 [357,] 14.28 54 [358,] 14.32 43 [359,] 14.36 51 [360,] 14.40 49 [361,] 14.44 51 [362,] 14.48 48 [363,] 14.52 52 [364,] 14.56 49 [365,] 14.60 34 [366,] 14.64 34 [367,] 14.68 44 [368,] 14.72 36 [369,] 14.76 36 [370,] 14.80 54 [371,] 14.84 39 [372,] 14.88 65 [373,] 14.92 55 [374,] 14.96 47 [375,] 15.00 42 [376,] 15.04 33 [377,] 15.08 59 [378,] 15.12 43 [379,] 15.16 27 [380,] 15.20 40 [381,] 15.24 50 [382,] 15.28 53 [383,] 15.32 43 [384,] 15.36 39 [385,] 15.40 29 [386,] 15.44 46 [387,] 15.48 36 [388,] 15.52 28 [389,] 15.56 43 [390,] 15.60 50 [391,] 15.64 49 [392,] 15.68 46 [393,] 15.72 53 [394,] 15.76 48 [395,] 15.80 40 [396,] 15.84 37 [397,] 15.88 47 [398,] 15.92 39 [399,] 15.96 40 [400,] 16.00 38 [401,] 16.04 49 [402,] 16.08 39 [403,] 16.12 41 [404,] 16.16 44 [405,] 16.20 59 [406,] 16.24 38 [407,] 16.28 48 [408,] 16.32 42 [409,] 16.36 48 [410,] 16.40 35 [411,] 16.44 42 [412,] 16.48 41 [413,] 16.52 60 [414,] 16.56 22 [415,] 16.60 42 [416,] 16.64 55 [417,] 16.68 63 [418,] 16.72 45 [419,] 16.76 53 [420,] 16.80 46 [421,] 16.84 39 [422,] 16.88 36 [423,] 16.92 50 [424,] 16.96 48 [425,] 17.00 38 [426,] 17.04 44 [427,] 17.08 38 [428,] 17.12 35 [429,] 17.16 49 [430,] 17.20 36 [431,] 17.24 45 [432,] 17.28 37 [433,] 17.32 31 [434,] 17.36 48 [435,] 17.40 23 [436,] 17.44 57 [437,] 17.48 51 [438,] 17.52 40 [439,] 17.56 29 [440,] 17.60 41 [441,] 17.64 35 [442,] 17.68 78 [443,] 17.72 47 [444,] 17.76 43 [445,] 17.80 50 [446,] 17.84 52 [447,] 17.88 58 [448,] 17.92 44 [449,] 17.96 31 [450,] 18.00 52 [451,] 18.04 48 [452,] 18.08 46 [453,] 18.12 49 [454,] 18.16 41 [455,] 18.20 41 [456,] 18.24 34 [457,] 18.28 49 [458,] 18.32 31 [459,] 18.36 43 [460,] 18.40 41 [461,] 18.44 37 [462,] 18.48 44 [463,] 18.52 48 [464,] 18.56 47 [465,] 18.60 37 [466,] 18.64 42 [467,] 18.68 38 [468,] 18.72 30 [469,] 18.76 48 [470,] 18.80 43 [471,] 18.84 56 [472,] 18.88 49 [473,] 18.92 51 [474,] 18.96 41 [475,] 19.00 41 [476,] 19.04 40 [477,] 19.08 42 [478,] 19.12 44 [479,] 19.16 55 [480,] 19.20 52 [481,] 19.24 52 [482,] 19.28 38 [483,] 19.32 42 [484,] 19.36 34 [485,] 19.40 45 [486,] 19.44 36 [487,] 19.48 52 [488,] 19.52 37 [489,] 19.56 35 [490,] 19.60 23 [491,] 19.64 51 [492,] 19.68 44 [493,] 19.72 43 [494,] 19.76 33 [495,] 19.80 47 [496,] 19.84 39 [497,] 19.88 43 [498,] 19.92 53 [499,] 19.96 40 [500,] 20.00 55 [501,] 20.04 35 [502,] 20.08 34 [503,] 20.12 31 [504,] 20.16 35 [505,] 20.20 46 [506,] 20.24 37 [507,] 20.28 43 [508,] 20.32 44 [509,] 20.36 32 [510,] 20.40 66 [511,] 20.44 36 [512,] 20.48 39 [513,] 20.52 45 [514,] 20.56 45 [515,] 20.60 34 [516,] 20.64 26 [517,] 20.68 42 [518,] 20.72 24 [519,] 20.76 67 [520,] 20.80 50 [521,] 20.84 59 [522,] 20.88 35 [523,] 20.92 38 [524,] 20.96 45 [525,] 21.00 53 [526,] 21.04 42 [527,] 21.08 54 [528,] 21.12 42 [529,] 21.16 49 [530,] 21.20 39 [531,] 21.24 32 [532,] 21.28 45 [533,] 21.32 41 [534,] 21.36 36 [535,] 21.40 41 [536,] 21.44 34 [537,] 21.48 66 [538,] 21.52 39 [539,] 21.56 24 [540,] 21.60 42 [541,] 21.64 34 [542,] 21.68 22 [543,] 21.72 49 [544,] 21.76 50 [545,] 21.80 42 [546,] 21.84 54 [547,] 21.88 36 [548,] 21.92 31 [549,] 21.96 28 [550,] 22.00 32 [551,] 22.04 44 [552,] 22.08 47 [553,] 22.12 37 [554,] 22.16 46 [555,] 22.20 36 [556,] 22.24 57 [557,] 22.28 50 [558,] 22.32 44 [559,] 22.36 48 [560,] 22.40 37 [561,] 22.44 31 [562,] 22.48 43 [563,] 22.52 39 [564,] 22.56 49 [565,] 22.60 32 [566,] 22.64 34 [567,] 22.68 47 [568,] 22.72 42 [569,] 22.76 37 [570,] 22.80 39 [571,] 22.84 42 [572,] 22.88 36 [573,] 22.92 40 [574,] 22.96 26 [575,] 23.00 51 [576,] 23.04 39 [577,] 23.08 45 [578,] 23.12 53 [579,] 23.16 24 [580,] 23.20 59 [581,] 23.24 43 [582,] 23.28 39 [583,] 23.32 43 [584,] 23.36 30 [585,] 23.40 45 [586,] 23.44 43 [587,] 23.48 38 [588,] 23.52 44 [589,] 23.56 30 [590,] 23.60 41 [591,] 23.64 34 [592,] 23.68 44 [593,] 23.72 46 [594,] 23.76 46 [595,] 23.80 38 [596,] 23.84 39 [597,] 23.88 44 [598,] 23.92 36 [599,] 23.96 38 [600,] 24.00 48 [601,] 24.04 44 [602,] 24.08 51 [603,] 24.12 43 [604,] 24.16 41 [605,] 24.20 55 [606,] 24.24 37 [607,] 24.28 41 [608,] 24.32 37 [609,] 24.36 44 [610,] 24.40 60 [611,] 24.44 46 [612,] 24.48 45 [613,] 24.52 57 [614,] 24.56 35 [615,] 24.60 45 [616,] 24.64 33 [617,] 24.68 34 [618,] 24.72 24 [619,] 24.76 52 [620,] 24.80 40 [621,] 24.84 42 [622,] 24.88 42 [623,] 24.92 57 [624,] 24.96 44 [625,] 25.00 42 [626,] 25.04 36 [627,] 25.08 30 [628,] 25.12 44 [629,] 25.16 38 [630,] 25.20 44 [631,] 25.24 24 [632,] 25.28 42 [633,] 25.32 33 [634,] 25.36 40 [635,] 25.40 33 [636,] 25.44 33 [637,] 25.48 42 [638,] 25.52 36 [639,] 25.56 39 [640,] 25.60 40 [641,] 25.64 28 [642,] 25.68 30 [643,] 25.72 32 [644,] 25.76 46 [645,] 25.80 31 [646,] 25.84 56 [647,] 25.88 49 [648,] 25.92 26 [649,] 25.96 45 [650,] 26.00 39 [651,] 26.04 33 [652,] 26.08 40 [653,] 26.12 44 [654,] 26.16 36 [655,] 26.20 44 [656,] 26.24 43 [657,] 26.28 30 [658,] 26.32 38 [659,] 26.36 43 [660,] 26.40 49 [661,] 26.44 37 [662,] 26.48 49 [663,] 26.52 41 [664,] 26.56 29 [665,] 26.60 50 [666,] 26.64 30 [667,] 26.68 44 [668,] 26.72 60 [669,] 26.76 30 [670,] 26.80 41 [671,] 26.84 52 [672,] 26.88 47 [673,] 26.92 44 [674,] 26.96 41 [675,] 27.00 34 [676,] 27.04 28 [677,] 27.08 39 [678,] 27.12 31 [679,] 27.16 28 [680,] 27.20 38 [681,] 27.24 28 [682,] 27.28 30 [683,] 27.32 38 [684,] 27.36 32 [685,] 27.40 42 [686,] 27.44 38 [687,] 27.48 40 [688,] 27.52 37 [689,] 27.56 34 [690,] 27.60 44 [691,] 27.64 49 [692,] 27.68 31 [693,] 27.72 51 [694,] 27.76 31 [695,] 27.80 44 [696,] 27.84 35 [697,] 27.88 25 [698,] 27.92 36 [699,] 27.96 48 [700,] 28.00 41 [701,] 28.04 40 [702,] 28.08 39 [703,] 28.12 40 [704,] 28.16 33 [705,] 28.20 56 [706,] 28.24 23 [707,] 28.28 37 [708,] 28.32 39 [709,] 28.36 54 [710,] 28.40 38 [711,] 28.44 48 [712,] 28.48 42 [713,] 28.52 43 [714,] 28.56 30 [715,] 28.60 39 [716,] 28.64 41 [717,] 28.68 43 [718,] 28.72 29 [719,] 28.76 38 [720,] 28.80 31 [721,] 28.84 35 [722,] 28.88 33 [723,] 28.92 40 [724,] 28.96 56 [725,] 29.00 39 [726,] 29.04 36 [727,] 29.08 40 [728,] 29.12 47 [729,] 29.16 47 [730,] 29.20 30 [731,] 29.24 55 [732,] 29.28 37 [733,] 29.32 44 [734,] 29.36 41 [735,] 29.40 38 [736,] 29.44 54 [737,] 29.48 34 [738,] 29.52 49 [739,] 29.56 34 [740,] 29.60 44 [741,] 29.64 42 [742,] 29.68 32 [743,] 29.72 35 [744,] 29.76 39 [745,] 29.80 43 [746,] 29.84 43 [747,] 29.88 41 [748,] 29.92 47 [749,] 29.96 35 [750,] 30.00 34 [751,] 30.04 38 [752,] 30.08 32 [753,] 30.12 36 [754,] 30.16 32 [755,] 30.20 45 [756,] 30.24 25 [757,] 30.28 38 [758,] 30.32 23 [759,] 30.36 43 [760,] 30.40 34 [761,] 30.44 32 [762,] 30.48 42 [763,] 30.52 38 [764,] 30.56 31 [765,] 30.60 54 [766,] 30.64 46 [767,] 30.68 53 [768,] 30.72 35 [769,] 30.76 40 [770,] 30.80 36 [771,] 30.84 32 [772,] 30.88 50 [773,] 30.92 48 [774,] 30.96 42 [775,] 31.00 50 [776,] 31.04 26 [777,] 31.08 36 [778,] 31.12 27 [779,] 31.16 39 [780,] 31.20 37 [781,] 31.24 31 [782,] 31.28 37 [783,] 31.32 39 [784,] 31.36 27 [785,] 31.40 46 [786,] 31.44 46 [787,] 31.48 30 [788,] 31.52 39 [789,] 31.56 31 [790,] 31.60 32 [791,] 31.64 38 [792,] 31.68 54 [793,] 31.72 39 [794,] 31.76 51 [795,] 31.80 42 [796,] 31.84 44 [797,] 31.88 38 [798,] 31.92 35 [799,] 31.96 34 [800,] 32.00 48 [801,] 32.04 36 [802,] 32.08 44 [803,] 32.12 35 [804,] 32.16 41 [805,] 32.20 52 [806,] 32.24 35 [807,] 32.28 44 [808,] 32.32 38 [809,] 32.36 31 [810,] 32.40 38 [811,] 32.44 38 [812,] 32.48 39 [813,] 32.52 36 [814,] 32.56 22 [815,] 32.60 30 [816,] 32.64 33 [817,] 32.68 33 [818,] 32.72 24 [819,] 32.76 55 [820,] 32.80 39 [821,] 32.84 33 [822,] 32.88 43 [823,] 32.92 47 [824,] 32.96 53 [825,] 33.00 25 [826,] 33.04 40 [827,] 33.08 57 [828,] 33.12 34 [829,] 33.16 41 [830,] 33.20 34 [831,] 33.24 33 [832,] 33.28 30 [833,] 33.32 36 [834,] 33.36 54 [835,] 33.40 50 [836,] 33.44 57 [837,] 33.48 49 [838,] 33.52 29 [839,] 33.56 33 [840,] 33.60 22 [841,] 33.64 39 [842,] 33.68 38 [843,] 33.72 29 [844,] 33.76 44 [845,] 33.80 39 [846,] 33.84 36 [847,] 33.88 29 [848,] 33.92 43 [849,] 33.96 39 [850,] 34.00 35 [851,] 34.04 45 [852,] 34.08 28 [853,] 34.12 38 [854,] 34.16 50 [855,] 34.20 32 [856,] 34.24 41 [857,] 34.28 37 [858,] 34.32 31 [859,] 34.36 25 [860,] 34.40 50 [861,] 34.44 30 [862,] 34.48 44 [863,] 34.52 36 [864,] 34.56 34 [865,] 34.60 48 [866,] 34.64 41 [867,] 34.68 29 [868,] 34.72 31 [869,] 34.76 43 [870,] 34.80 45 [871,] 34.84 42 [872,] 34.88 35 [873,] 34.92 43 [874,] 34.96 39 [875,] 35.00 48 [876,] 35.04 45 [877,] 35.08 50 [878,] 35.12 37 [879,] 35.16 48 [880,] 35.20 37 [881,] 35.24 38 [882,] 35.28 37 [883,] 35.32 30 [884,] 35.36 22 [885,] 35.40 30 [886,] 35.44 45 [887,] 35.48 38 [888,] 35.52 33 [889,] 35.56 39 [890,] 35.60 38 [891,] 35.64 25 [892,] 35.68 29 [893,] 35.72 37 [894,] 35.76 48 [895,] 35.80 29 [896,] 35.84 37 [897,] 35.88 32 [898,] 35.92 38 [899,] 35.96 53 [900,] 36.00 43 [901,] 36.04 42 [902,] 36.08 33 [903,] 36.12 39 [904,] 36.16 33 [905,] 36.20 40 [906,] 36.24 37 [907,] 36.28 44 [908,] 36.32 21 [909,] 36.36 40 [910,] 36.40 47 [911,] 36.44 34 [912,] 36.48 36 [913,] 36.52 34 [914,] 36.56 38 [915,] 36.60 44 [916,] 36.64 36 [917,] 36.68 38 [918,] 36.72 25 [919,] 36.76 41 [920,] 36.80 36 [921,] 36.84 31 [922,] 36.88 36 [923,] 36.92 37 [924,] 36.96 42 [925,] 37.00 48 [926,] 37.04 43 [927,] 37.08 34 [928,] 37.12 31 [929,] 37.16 30 [930,] 37.20 37 [931,] 37.24 30 [932,] 37.28 27 [933,] 37.32 46 [934,] 37.36 34 [935,] 37.40 27 [936,] 37.44 30 [937,] 37.48 45 [938,] 37.52 29 [939,] 37.56 34 [940,] 37.60 48 [941,] 37.64 43 [942,] 37.68 48 [943,] 37.72 32 [944,] 37.76 49 [945,] 37.80 40 [946,] 37.84 41 [947,] 37.88 39 [948,] 37.92 24 [949,] 37.96 40 [950,] 38.00 51 [951,] 38.04 34 [952,] 38.08 36 [953,] 38.12 32 [954,] 38.16 34 [955,] 38.20 40 [956,] 38.24 42 [957,] 38.28 34 [958,] 38.32 46 [959,] 38.36 30 [960,] 38.40 38 [961,] 38.44 31 [962,] 38.48 29 [963,] 38.52 51 [964,] 38.56 44 [965,] 38.60 26 [966,] 38.64 32 [967,] 38.68 28 [968,] 38.72 35 [969,] 38.76 33 [970,] 38.80 32 [971,] 38.84 35 [972,] 38.88 48 [973,] 38.92 41 [974,] 38.96 34 [975,] 39.00 34 [976,] 39.04 32 [977,] 39.08 41 [978,] 39.12 41 [979,] 39.16 27 [980,] 39.20 38 [981,] 39.24 37 [982,] 39.28 52 [983,] 39.32 26 [984,] 39.36 38 [985,] 39.40 45 [986,] 39.44 44 [987,] 39.48 36 [988,] 39.52 36 [989,] 39.56 35 [990,] 39.60 34 [991,] 39.64 26 [992,] 39.68 28 [993,] 39.72 40 [994,] 39.76 37 [995,] 39.80 37 [996,] 39.84 50 [997,] 39.88 28 [998,] 39.92 41 [999,] 39.96 31 [1000,] 40.00 26 $`5_TL (PMT)` [,1] [,2] [1,] 0.884 2 [2,] 1.768 2 [3,] 2.652 11 [4,] 3.536 13 [5,] 4.420 1 [6,] 5.304 5 [7,] 6.188 5 [8,] 7.072 11 [9,] 7.956 15 [10,] 8.840 4 [11,] 9.724 18 [12,] 10.608 13 [13,] 11.492 5 [14,] 12.376 1 [15,] 13.260 19 [16,] 14.144 4 [17,] 15.028 6 [18,] 15.912 5 [19,] 16.796 3 [20,] 17.680 2 [21,] 18.564 6 [22,] 19.448 16 [23,] 20.332 15 [24,] 21.216 12 [25,] 22.100 3 [26,] 22.984 4 [27,] 23.868 6 [28,] 24.752 2 [29,] 25.636 6 [30,] 26.520 2 [31,] 27.404 2 [32,] 28.288 9 [33,] 29.172 2 [34,] 30.056 1 [35,] 30.940 8 [36,] 31.824 10 [37,] 32.708 8 [38,] 33.592 3 [39,] 34.476 8 [40,] 35.360 5 [41,] 36.244 4 [42,] 37.128 11 [43,] 38.012 3 [44,] 38.896 0 [45,] 39.780 3 [46,] 40.664 0 [47,] 41.548 9 [48,] 42.432 3 [49,] 43.316 2 [50,] 44.200 1 [51,] 45.084 3 [52,] 45.968 5 [53,] 46.852 5 [54,] 47.736 8 [55,] 48.620 9 [56,] 49.504 2 [57,] 50.388 8 [58,] 51.272 4 [59,] 52.156 4 [60,] 53.040 13 [61,] 53.924 12 [62,] 54.808 3 [63,] 55.692 7 [64,] 56.576 10 [65,] 57.460 7 [66,] 58.344 7 [67,] 59.228 6 [68,] 60.112 8 [69,] 60.996 11 [70,] 61.880 17 [71,] 62.764 17 [72,] 63.648 15 [73,] 64.532 11 [74,] 65.416 22 [75,] 66.300 18 [76,] 67.184 26 [77,] 68.068 16 [78,] 68.952 22 [79,] 69.836 37 [80,] 70.720 25 [81,] 71.604 29 [82,] 72.488 27 [83,] 73.372 20 [84,] 74.256 23 [85,] 75.140 58 [86,] 76.024 26 [87,] 76.908 48 [88,] 77.792 41 [89,] 78.676 45 [90,] 79.560 41 [91,] 80.444 47 [92,] 81.328 54 [93,] 82.212 67 [94,] 83.096 78 [95,] 83.980 52 [96,] 84.864 65 [97,] 85.748 72 [98,] 86.632 88 [99,] 87.516 66 [100,] 88.400 68 [101,] 89.284 82 [102,] 90.168 97 [103,] 91.052 109 [104,] 91.936 106 [105,] 92.820 100 [106,] 93.704 136 [107,] 94.588 132 [108,] 95.472 160 [109,] 96.356 127 [110,] 97.240 146 [111,] 98.124 153 [112,] 99.008 158 [113,] 99.892 177 [114,] 100.776 129 [115,] 101.660 202 [116,] 102.544 154 [117,] 103.428 188 [118,] 104.312 233 [119,] 105.196 202 [120,] 106.080 182 [121,] 106.964 217 [122,] 107.848 197 [123,] 108.732 171 [124,] 109.616 215 [125,] 110.500 214 [126,] 111.384 208 [127,] 112.268 176 [128,] 113.152 169 [129,] 114.036 189 [130,] 114.920 182 [131,] 115.804 169 [132,] 116.688 170 [133,] 117.572 180 [134,] 118.456 144 [135,] 119.340 136 [136,] 120.224 127 [137,] 121.108 149 [138,] 121.992 103 [139,] 122.876 112 [140,] 123.760 126 [141,] 124.644 124 [142,] 125.528 112 [143,] 126.412 115 [144,] 127.296 95 [145,] 128.180 104 [146,] 129.064 135 [147,] 129.948 128 [148,] 130.832 114 [149,] 131.716 117 [150,] 132.600 115 [151,] 133.484 121 [152,] 134.368 119 [153,] 135.252 105 [154,] 136.136 104 [155,] 137.020 122 [156,] 137.904 120 [157,] 138.788 138 [158,] 139.672 117 [159,] 140.556 128 [160,] 141.440 109 [161,] 142.324 125 [162,] 143.208 142 [163,] 144.092 125 [164,] 144.976 117 [165,] 145.860 146 [166,] 146.744 107 [167,] 147.628 127 [168,] 148.512 145 [169,] 149.396 110 [170,] 150.280 151 [171,] 151.164 144 [172,] 152.048 127 [173,] 152.932 120 [174,] 153.816 154 [175,] 154.700 144 [176,] 155.584 97 [177,] 156.468 140 [178,] 157.352 110 [179,] 158.236 126 [180,] 159.120 120 [181,] 160.004 151 [182,] 160.888 147 [183,] 161.772 120 [184,] 162.656 104 [185,] 163.540 145 [186,] 164.424 117 [187,] 165.308 111 [188,] 166.192 135 [189,] 167.076 152 [190,] 167.960 148 [191,] 168.844 136 [192,] 169.728 135 [193,] 170.612 88 [194,] 171.496 147 [195,] 172.380 146 [196,] 173.264 145 [197,] 174.148 120 [198,] 175.032 117 [199,] 175.916 135 [200,] 176.800 131 [201,] 177.684 123 [202,] 178.568 115 [203,] 179.452 110 [204,] 180.336 120 [205,] 181.220 112 [206,] 182.104 137 [207,] 182.988 138 [208,] 183.872 123 [209,] 184.756 125 [210,] 185.640 141 [211,] 186.524 130 [212,] 187.408 129 [213,] 188.292 113 [214,] 189.176 131 [215,] 190.060 135 [216,] 190.944 166 [217,] 191.828 137 [218,] 192.712 132 [219,] 193.596 148 [220,] 194.480 171 [221,] 195.364 128 [222,] 196.248 137 [223,] 197.132 180 [224,] 198.016 143 [225,] 198.900 158 [226,] 199.784 194 [227,] 200.668 162 [228,] 201.552 196 [229,] 202.436 161 [230,] 203.320 148 [231,] 204.204 192 [232,] 205.088 183 [233,] 205.972 156 [234,] 206.856 171 [235,] 207.740 190 [236,] 208.624 170 [237,] 209.508 185 [238,] 210.392 212 [239,] 211.276 174 [240,] 212.160 196 [241,] 213.044 183 [242,] 213.928 189 [243,] 214.812 174 [244,] 215.696 179 [245,] 216.580 189 [246,] 217.464 170 [247,] 218.348 174 [248,] 219.232 190 [249,] 220.116 181 [250,] 221.000 87 $`6_OSL (PMT)` [,1] [,2] [1,] 0.04 4129 [2,] 0.08 3462 [3,] 0.12 3093 [4,] 0.16 2619 [5,] 0.20 2237 [6,] 0.24 1971 [7,] 0.28 1670 [8,] 0.32 1528 [9,] 0.36 1319 [10,] 0.40 1155 [11,] 0.44 963 [12,] 0.48 907 [13,] 0.52 841 [14,] 0.56 726 [15,] 0.60 641 [16,] 0.64 544 [17,] 0.68 495 [18,] 0.72 409 [19,] 0.76 410 [20,] 0.80 409 [21,] 0.84 345 [22,] 0.88 284 [23,] 0.92 259 [24,] 0.96 256 [25,] 1.00 232 [26,] 1.04 252 [27,] 1.08 173 [28,] 1.12 170 [29,] 1.16 158 [30,] 1.20 169 [31,] 1.24 137 [32,] 1.28 170 [33,] 1.32 127 [34,] 1.36 142 [35,] 1.40 81 [36,] 1.44 114 [37,] 1.48 117 [38,] 1.52 100 [39,] 1.56 101 [40,] 1.60 109 [41,] 1.64 97 [42,] 1.68 96 [43,] 1.72 110 [44,] 1.76 82 [45,] 1.80 114 [46,] 1.84 84 [47,] 1.88 96 [48,] 1.92 84 [49,] 1.96 93 [50,] 2.00 57 [51,] 2.04 85 [52,] 2.08 93 [53,] 2.12 69 [54,] 2.16 81 [55,] 2.20 74 [56,] 2.24 76 [57,] 2.28 72 [58,] 2.32 94 [59,] 2.36 61 [60,] 2.40 61 [61,] 2.44 55 [62,] 2.48 73 [63,] 2.52 73 [64,] 2.56 73 [65,] 2.60 54 [66,] 2.64 73 [67,] 2.68 48 [68,] 2.72 57 [69,] 2.76 63 [70,] 2.80 68 [71,] 2.84 41 [72,] 2.88 52 [73,] 2.92 55 [74,] 2.96 74 [75,] 3.00 61 [76,] 3.04 61 [77,] 3.08 71 [78,] 3.12 45 [79,] 3.16 57 [80,] 3.20 69 [81,] 3.24 66 [82,] 3.28 58 [83,] 3.32 64 [84,] 3.36 69 [85,] 3.40 40 [86,] 3.44 46 [87,] 3.48 58 [88,] 3.52 62 [89,] 3.56 42 [90,] 3.60 49 [91,] 3.64 60 [92,] 3.68 55 [93,] 3.72 63 [94,] 3.76 58 [95,] 3.80 66 [96,] 3.84 42 [97,] 3.88 64 [98,] 3.92 39 [99,] 3.96 45 [100,] 4.00 58 [101,] 4.04 65 [102,] 4.08 70 [103,] 4.12 47 [104,] 4.16 38 [105,] 4.20 39 [106,] 4.24 47 [107,] 4.28 54 [108,] 4.32 52 [109,] 4.36 51 [110,] 4.40 50 [111,] 4.44 53 [112,] 4.48 54 [113,] 4.52 41 [114,] 4.56 55 [115,] 4.60 58 [116,] 4.64 34 [117,] 4.68 54 [118,] 4.72 48 [119,] 4.76 41 [120,] 4.80 42 [121,] 4.84 57 [122,] 4.88 66 [123,] 4.92 43 [124,] 4.96 43 [125,] 5.00 58 [126,] 5.04 52 [127,] 5.08 48 [128,] 5.12 49 [129,] 5.16 55 [130,] 5.20 53 [131,] 5.24 53 [132,] 5.28 42 [133,] 5.32 49 [134,] 5.36 49 [135,] 5.40 50 [136,] 5.44 46 [137,] 5.48 50 [138,] 5.52 43 [139,] 5.56 59 [140,] 5.60 55 [141,] 5.64 55 [142,] 5.68 64 [143,] 5.72 43 [144,] 5.76 34 [145,] 5.80 56 [146,] 5.84 39 [147,] 5.88 55 [148,] 5.92 53 [149,] 5.96 51 [150,] 6.00 39 [151,] 6.04 52 [152,] 6.08 55 [153,] 6.12 38 [154,] 6.16 41 [155,] 6.20 46 [156,] 6.24 56 [157,] 6.28 58 [158,] 6.32 45 [159,] 6.36 55 [160,] 6.40 38 [161,] 6.44 44 [162,] 6.48 46 [163,] 6.52 51 [164,] 6.56 50 [165,] 6.60 42 [166,] 6.64 45 [167,] 6.68 39 [168,] 6.72 62 [169,] 6.76 37 [170,] 6.80 41 [171,] 6.84 44 [172,] 6.88 47 [173,] 6.92 62 [174,] 6.96 47 [175,] 7.00 42 [176,] 7.04 50 [177,] 7.08 56 [178,] 7.12 49 [179,] 7.16 42 [180,] 7.20 51 [181,] 7.24 51 [182,] 7.28 50 [183,] 7.32 50 [184,] 7.36 45 [185,] 7.40 38 [186,] 7.44 38 [187,] 7.48 26 [188,] 7.52 51 [189,] 7.56 31 [190,] 7.60 42 [191,] 7.64 31 [192,] 7.68 45 [193,] 7.72 68 [194,] 7.76 47 [195,] 7.80 39 [196,] 7.84 36 [197,] 7.88 31 [198,] 7.92 56 [199,] 7.96 53 [200,] 8.00 48 [201,] 8.04 56 [202,] 8.08 42 [203,] 8.12 43 [204,] 8.16 64 [205,] 8.20 41 [206,] 8.24 59 [207,] 8.28 43 [208,] 8.32 38 [209,] 8.36 54 [210,] 8.40 52 [211,] 8.44 52 [212,] 8.48 41 [213,] 8.52 48 [214,] 8.56 37 [215,] 8.60 53 [216,] 8.64 44 [217,] 8.68 54 [218,] 8.72 45 [219,] 8.76 61 [220,] 8.80 43 [221,] 8.84 50 [222,] 8.88 44 [223,] 8.92 35 [224,] 8.96 35 [225,] 9.00 49 [226,] 9.04 40 [227,] 9.08 41 [228,] 9.12 53 [229,] 9.16 34 [230,] 9.20 38 [231,] 9.24 47 [232,] 9.28 48 [233,] 9.32 55 [234,] 9.36 37 [235,] 9.40 37 [236,] 9.44 25 [237,] 9.48 53 [238,] 9.52 31 [239,] 9.56 37 [240,] 9.60 33 [241,] 9.64 45 [242,] 9.68 42 [243,] 9.72 39 [244,] 9.76 44 [245,] 9.80 43 [246,] 9.84 43 [247,] 9.88 41 [248,] 9.92 43 [249,] 9.96 43 [250,] 10.00 42 [251,] 10.04 26 [252,] 10.08 41 [253,] 10.12 52 [254,] 10.16 41 [255,] 10.20 47 [256,] 10.24 43 [257,] 10.28 46 [258,] 10.32 45 [259,] 10.36 51 [260,] 10.40 46 [261,] 10.44 47 [262,] 10.48 34 [263,] 10.52 34 [264,] 10.56 44 [265,] 10.60 50 [266,] 10.64 60 [267,] 10.68 43 [268,] 10.72 39 [269,] 10.76 47 [270,] 10.80 50 [271,] 10.84 36 [272,] 10.88 33 [273,] 10.92 35 [274,] 10.96 42 [275,] 11.00 35 [276,] 11.04 45 [277,] 11.08 32 [278,] 11.12 35 [279,] 11.16 39 [280,] 11.20 38 [281,] 11.24 30 [282,] 11.28 34 [283,] 11.32 45 [284,] 11.36 55 [285,] 11.40 58 [286,] 11.44 29 [287,] 11.48 22 [288,] 11.52 44 [289,] 11.56 36 [290,] 11.60 35 [291,] 11.64 33 [292,] 11.68 50 [293,] 11.72 49 [294,] 11.76 60 [295,] 11.80 38 [296,] 11.84 48 [297,] 11.88 34 [298,] 11.92 39 [299,] 11.96 48 [300,] 12.00 40 [301,] 12.04 31 [302,] 12.08 45 [303,] 12.12 50 [304,] 12.16 51 [305,] 12.20 36 [306,] 12.24 43 [307,] 12.28 54 [308,] 12.32 45 [309,] 12.36 40 [310,] 12.40 37 [311,] 12.44 46 [312,] 12.48 29 [313,] 12.52 42 [314,] 12.56 35 [315,] 12.60 47 [316,] 12.64 42 [317,] 12.68 35 [318,] 12.72 29 [319,] 12.76 39 [320,] 12.80 34 [321,] 12.84 39 [322,] 12.88 31 [323,] 12.92 34 [324,] 12.96 36 [325,] 13.00 43 [326,] 13.04 29 [327,] 13.08 57 [328,] 13.12 33 [329,] 13.16 46 [330,] 13.20 55 [331,] 13.24 57 [332,] 13.28 47 [333,] 13.32 35 [334,] 13.36 34 [335,] 13.40 42 [336,] 13.44 43 [337,] 13.48 35 [338,] 13.52 42 [339,] 13.56 52 [340,] 13.60 34 [341,] 13.64 31 [342,] 13.68 45 [343,] 13.72 29 [344,] 13.76 44 [345,] 13.80 38 [346,] 13.84 34 [347,] 13.88 44 [348,] 13.92 28 [349,] 13.96 37 [350,] 14.00 42 [351,] 14.04 44 [352,] 14.08 43 [353,] 14.12 40 [354,] 14.16 35 [355,] 14.20 48 [356,] 14.24 43 [357,] 14.28 43 [358,] 14.32 36 [359,] 14.36 37 [360,] 14.40 38 [361,] 14.44 42 [362,] 14.48 40 [363,] 14.52 51 [364,] 14.56 45 [365,] 14.60 39 [366,] 14.64 35 [367,] 14.68 36 [368,] 14.72 24 [369,] 14.76 35 [370,] 14.80 34 [371,] 14.84 34 [372,] 14.88 28 [373,] 14.92 42 [374,] 14.96 40 [375,] 15.00 27 [376,] 15.04 35 [377,] 15.08 39 [378,] 15.12 29 [379,] 15.16 50 [380,] 15.20 50 [381,] 15.24 41 [382,] 15.28 30 [383,] 15.32 40 [384,] 15.36 46 [385,] 15.40 42 [386,] 15.44 46 [387,] 15.48 40 [388,] 15.52 46 [389,] 15.56 38 [390,] 15.60 39 [391,] 15.64 33 [392,] 15.68 47 [393,] 15.72 42 [394,] 15.76 30 [395,] 15.80 38 [396,] 15.84 41 [397,] 15.88 35 [398,] 15.92 37 [399,] 15.96 42 [400,] 16.00 29 [401,] 16.04 34 [402,] 16.08 57 [403,] 16.12 32 [404,] 16.16 55 [405,] 16.20 38 [406,] 16.24 29 [407,] 16.28 44 [408,] 16.32 47 [409,] 16.36 31 [410,] 16.40 55 [411,] 16.44 36 [412,] 16.48 33 [413,] 16.52 51 [414,] 16.56 34 [415,] 16.60 28 [416,] 16.64 33 [417,] 16.68 39 [418,] 16.72 46 [419,] 16.76 49 [420,] 16.80 48 [421,] 16.84 34 [422,] 16.88 33 [423,] 16.92 25 [424,] 16.96 48 [425,] 17.00 27 [426,] 17.04 48 [427,] 17.08 36 [428,] 17.12 44 [429,] 17.16 34 [430,] 17.20 46 [431,] 17.24 36 [432,] 17.28 40 [433,] 17.32 37 [434,] 17.36 28 [435,] 17.40 42 [436,] 17.44 26 [437,] 17.48 29 [438,] 17.52 35 [439,] 17.56 54 [440,] 17.60 28 [441,] 17.64 47 [442,] 17.68 43 [443,] 17.72 46 [444,] 17.76 51 [445,] 17.80 56 [446,] 17.84 49 [447,] 17.88 49 [448,] 17.92 45 [449,] 17.96 31 [450,] 18.00 33 [451,] 18.04 27 [452,] 18.08 39 [453,] 18.12 31 [454,] 18.16 23 [455,] 18.20 29 [456,] 18.24 38 [457,] 18.28 38 [458,] 18.32 39 [459,] 18.36 35 [460,] 18.40 40 [461,] 18.44 43 [462,] 18.48 26 [463,] 18.52 42 [464,] 18.56 40 [465,] 18.60 49 [466,] 18.64 42 [467,] 18.68 42 [468,] 18.72 38 [469,] 18.76 34 [470,] 18.80 33 [471,] 18.84 35 [472,] 18.88 44 [473,] 18.92 45 [474,] 18.96 30 [475,] 19.00 45 [476,] 19.04 29 [477,] 19.08 39 [478,] 19.12 54 [479,] 19.16 28 [480,] 19.20 43 [481,] 19.24 52 [482,] 19.28 30 [483,] 19.32 44 [484,] 19.36 43 [485,] 19.40 47 [486,] 19.44 42 [487,] 19.48 41 [488,] 19.52 45 [489,] 19.56 45 [490,] 19.60 41 [491,] 19.64 43 [492,] 19.68 39 [493,] 19.72 23 [494,] 19.76 50 [495,] 19.80 34 [496,] 19.84 34 [497,] 19.88 47 [498,] 19.92 39 [499,] 19.96 26 [500,] 20.00 39 [501,] 20.04 52 [502,] 20.08 34 [503,] 20.12 42 [504,] 20.16 50 [505,] 20.20 38 [506,] 20.24 50 [507,] 20.28 38 [508,] 20.32 33 [509,] 20.36 36 [510,] 20.40 33 [511,] 20.44 20 [512,] 20.48 31 [513,] 20.52 42 [514,] 20.56 42 [515,] 20.60 54 [516,] 20.64 39 [517,] 20.68 35 [518,] 20.72 34 [519,] 20.76 30 [520,] 20.80 36 [521,] 20.84 33 [522,] 20.88 33 [523,] 20.92 46 [524,] 20.96 45 [525,] 21.00 37 [526,] 21.04 39 [527,] 21.08 51 [528,] 21.12 50 [529,] 21.16 36 [530,] 21.20 37 [531,] 21.24 32 [532,] 21.28 40 [533,] 21.32 43 [534,] 21.36 43 [535,] 21.40 27 [536,] 21.44 49 [537,] 21.48 38 [538,] 21.52 29 [539,] 21.56 38 [540,] 21.60 39 [541,] 21.64 30 [542,] 21.68 39 [543,] 21.72 35 [544,] 21.76 27 [545,] 21.80 26 [546,] 21.84 32 [547,] 21.88 37 [548,] 21.92 34 [549,] 21.96 35 [550,] 22.00 33 [551,] 22.04 32 [552,] 22.08 26 [553,] 22.12 30 [554,] 22.16 35 [555,] 22.20 37 [556,] 22.24 36 [557,] 22.28 34 [558,] 22.32 29 [559,] 22.36 46 [560,] 22.40 21 [561,] 22.44 40 [562,] 22.48 44 [563,] 22.52 35 [564,] 22.56 23 [565,] 22.60 34 [566,] 22.64 40 [567,] 22.68 42 [568,] 22.72 39 [569,] 22.76 46 [570,] 22.80 35 [571,] 22.84 19 [572,] 22.88 36 [573,] 22.92 31 [574,] 22.96 38 [575,] 23.00 32 [576,] 23.04 38 [577,] 23.08 37 [578,] 23.12 35 [579,] 23.16 31 [580,] 23.20 32 [581,] 23.24 31 [582,] 23.28 37 [583,] 23.32 40 [584,] 23.36 37 [585,] 23.40 36 [586,] 23.44 49 [587,] 23.48 35 [588,] 23.52 41 [589,] 23.56 26 [590,] 23.60 38 [591,] 23.64 45 [592,] 23.68 35 [593,] 23.72 35 [594,] 23.76 40 [595,] 23.80 38 [596,] 23.84 35 [597,] 23.88 30 [598,] 23.92 36 [599,] 23.96 23 [600,] 24.00 51 [601,] 24.04 39 [602,] 24.08 28 [603,] 24.12 31 [604,] 24.16 38 [605,] 24.20 38 [606,] 24.24 36 [607,] 24.28 47 [608,] 24.32 41 [609,] 24.36 27 [610,] 24.40 25 [611,] 24.44 29 [612,] 24.48 43 [613,] 24.52 45 [614,] 24.56 33 [615,] 24.60 41 [616,] 24.64 28 [617,] 24.68 31 [618,] 24.72 55 [619,] 24.76 31 [620,] 24.80 29 [621,] 24.84 40 [622,] 24.88 29 [623,] 24.92 31 [624,] 24.96 51 [625,] 25.00 35 [626,] 25.04 38 [627,] 25.08 34 [628,] 25.12 42 [629,] 25.16 41 [630,] 25.20 25 [631,] 25.24 30 [632,] 25.28 42 [633,] 25.32 21 [634,] 25.36 46 [635,] 25.40 45 [636,] 25.44 33 [637,] 25.48 38 [638,] 25.52 40 [639,] 25.56 47 [640,] 25.60 30 [641,] 25.64 31 [642,] 25.68 29 [643,] 25.72 29 [644,] 25.76 32 [645,] 25.80 47 [646,] 25.84 36 [647,] 25.88 28 [648,] 25.92 39 [649,] 25.96 47 [650,] 26.00 36 [651,] 26.04 25 [652,] 26.08 50 [653,] 26.12 36 [654,] 26.16 29 [655,] 26.20 45 [656,] 26.24 39 [657,] 26.28 46 [658,] 26.32 39 [659,] 26.36 37 [660,] 26.40 24 [661,] 26.44 35 [662,] 26.48 24 [663,] 26.52 35 [664,] 26.56 37 [665,] 26.60 38 [666,] 26.64 43 [667,] 26.68 38 [668,] 26.72 42 [669,] 26.76 37 [670,] 26.80 31 [671,] 26.84 36 [672,] 26.88 38 [673,] 26.92 42 [674,] 26.96 30 [675,] 27.00 49 [676,] 27.04 37 [677,] 27.08 46 [678,] 27.12 42 [679,] 27.16 32 [680,] 27.20 32 [681,] 27.24 36 [682,] 27.28 22 [683,] 27.32 45 [684,] 27.36 34 [685,] 27.40 42 [686,] 27.44 40 [687,] 27.48 40 [688,] 27.52 42 [689,] 27.56 29 [690,] 27.60 25 [691,] 27.64 47 [692,] 27.68 44 [693,] 27.72 34 [694,] 27.76 32 [695,] 27.80 22 [696,] 27.84 40 [697,] 27.88 32 [698,] 27.92 31 [699,] 27.96 31 [700,] 28.00 35 [701,] 28.04 51 [702,] 28.08 36 [703,] 28.12 46 [704,] 28.16 27 [705,] 28.20 27 [706,] 28.24 26 [707,] 28.28 42 [708,] 28.32 32 [709,] 28.36 40 [710,] 28.40 34 [711,] 28.44 33 [712,] 28.48 41 [713,] 28.52 49 [714,] 28.56 39 [715,] 28.60 38 [716,] 28.64 37 [717,] 28.68 37 [718,] 28.72 44 [719,] 28.76 21 [720,] 28.80 64 [721,] 28.84 37 [722,] 28.88 37 [723,] 28.92 25 [724,] 28.96 21 [725,] 29.00 33 [726,] 29.04 35 [727,] 29.08 26 [728,] 29.12 25 [729,] 29.16 38 [730,] 29.20 39 [731,] 29.24 42 [732,] 29.28 36 [733,] 29.32 26 [734,] 29.36 36 [735,] 29.40 21 [736,] 29.44 30 [737,] 29.48 37 [738,] 29.52 39 [739,] 29.56 49 [740,] 29.60 36 [741,] 29.64 44 [742,] 29.68 32 [743,] 29.72 23 [744,] 29.76 31 [745,] 29.80 28 [746,] 29.84 26 [747,] 29.88 38 [748,] 29.92 27 [749,] 29.96 47 [750,] 30.00 43 [751,] 30.04 39 [752,] 30.08 45 [753,] 30.12 43 [754,] 30.16 43 [755,] 30.20 37 [756,] 30.24 33 [757,] 30.28 23 [758,] 30.32 51 [759,] 30.36 20 [760,] 30.40 52 [761,] 30.44 30 [762,] 30.48 27 [763,] 30.52 32 [764,] 30.56 30 [765,] 30.60 35 [766,] 30.64 40 [767,] 30.68 27 [768,] 30.72 41 [769,] 30.76 29 [770,] 30.80 46 [771,] 30.84 23 [772,] 30.88 32 [773,] 30.92 27 [774,] 30.96 25 [775,] 31.00 29 [776,] 31.04 33 [777,] 31.08 47 [778,] 31.12 34 [779,] 31.16 40 [780,] 31.20 43 [781,] 31.24 33 [782,] 31.28 42 [783,] 31.32 38 [784,] 31.36 35 [785,] 31.40 39 [786,] 31.44 34 [787,] 31.48 47 [788,] 31.52 35 [789,] 31.56 50 [790,] 31.60 27 [791,] 31.64 33 [792,] 31.68 25 [793,] 31.72 34 [794,] 31.76 40 [795,] 31.80 35 [796,] 31.84 49 [797,] 31.88 37 [798,] 31.92 30 [799,] 31.96 21 [800,] 32.00 40 [801,] 32.04 38 [802,] 32.08 39 [803,] 32.12 31 [804,] 32.16 26 [805,] 32.20 33 [806,] 32.24 39 [807,] 32.28 36 [808,] 32.32 31 [809,] 32.36 24 [810,] 32.40 36 [811,] 32.44 39 [812,] 32.48 31 [813,] 32.52 30 [814,] 32.56 32 [815,] 32.60 19 [816,] 32.64 26 [817,] 32.68 38 [818,] 32.72 23 [819,] 32.76 30 [820,] 32.80 16 [821,] 32.84 31 [822,] 32.88 24 [823,] 32.92 39 [824,] 32.96 30 [825,] 33.00 26 [826,] 33.04 35 [827,] 33.08 34 [828,] 33.12 38 [829,] 33.16 49 [830,] 33.20 32 [831,] 33.24 27 [832,] 33.28 33 [833,] 33.32 23 [834,] 33.36 31 [835,] 33.40 37 [836,] 33.44 48 [837,] 33.48 26 [838,] 33.52 28 [839,] 33.56 27 [840,] 33.60 39 [841,] 33.64 28 [842,] 33.68 43 [843,] 33.72 31 [844,] 33.76 46 [845,] 33.80 36 [846,] 33.84 41 [847,] 33.88 38 [848,] 33.92 29 [849,] 33.96 41 [850,] 34.00 33 [851,] 34.04 28 [852,] 34.08 45 [853,] 34.12 41 [854,] 34.16 35 [855,] 34.20 27 [856,] 34.24 41 [857,] 34.28 48 [858,] 34.32 31 [859,] 34.36 28 [860,] 34.40 30 [861,] 34.44 30 [862,] 34.48 32 [863,] 34.52 26 [864,] 34.56 34 [865,] 34.60 39 [866,] 34.64 32 [867,] 34.68 21 [868,] 34.72 29 [869,] 34.76 31 [870,] 34.80 38 [871,] 34.84 35 [872,] 34.88 39 [873,] 34.92 28 [874,] 34.96 46 [875,] 35.00 48 [876,] 35.04 40 [877,] 35.08 30 [878,] 35.12 25 [879,] 35.16 34 [880,] 35.20 35 [881,] 35.24 32 [882,] 35.28 33 [883,] 35.32 43 [884,] 35.36 18 [885,] 35.40 51 [886,] 35.44 26 [887,] 35.48 38 [888,] 35.52 26 [889,] 35.56 32 [890,] 35.60 35 [891,] 35.64 35 [892,] 35.68 27 [893,] 35.72 26 [894,] 35.76 34 [895,] 35.80 34 [896,] 35.84 35 [897,] 35.88 29 [898,] 35.92 41 [899,] 35.96 41 [900,] 36.00 44 [901,] 36.04 28 [902,] 36.08 31 [903,] 36.12 15 [904,] 36.16 37 [905,] 36.20 23 [906,] 36.24 30 [907,] 36.28 32 [908,] 36.32 32 [909,] 36.36 29 [910,] 36.40 38 [911,] 36.44 30 [912,] 36.48 31 [913,] 36.52 38 [914,] 36.56 32 [915,] 36.60 31 [916,] 36.64 27 [917,] 36.68 25 [918,] 36.72 48 [919,] 36.76 42 [920,] 36.80 36 [921,] 36.84 35 [922,] 36.88 44 [923,] 36.92 46 [924,] 36.96 34 [925,] 37.00 18 [926,] 37.04 33 [927,] 37.08 42 [928,] 37.12 39 [929,] 37.16 44 [930,] 37.20 29 [931,] 37.24 29 [932,] 37.28 34 [933,] 37.32 23 [934,] 37.36 20 [935,] 37.40 30 [936,] 37.44 30 [937,] 37.48 32 [938,] 37.52 23 [939,] 37.56 26 [940,] 37.60 32 [941,] 37.64 35 [942,] 37.68 31 [943,] 37.72 27 [944,] 37.76 32 [945,] 37.80 32 [946,] 37.84 32 [947,] 37.88 29 [948,] 37.92 45 [949,] 37.96 30 [950,] 38.00 34 [951,] 38.04 28 [952,] 38.08 32 [953,] 38.12 30 [954,] 38.16 37 [955,] 38.20 36 [956,] 38.24 37 [957,] 38.28 27 [958,] 38.32 29 [959,] 38.36 37 [960,] 38.40 40 [961,] 38.44 45 [962,] 38.48 25 [963,] 38.52 40 [964,] 38.56 39 [965,] 38.60 34 [966,] 38.64 31 [967,] 38.68 33 [968,] 38.72 47 [969,] 38.76 29 [970,] 38.80 38 [971,] 38.84 34 [972,] 38.88 45 [973,] 38.92 28 [974,] 38.96 46 [975,] 39.00 38 [976,] 39.04 37 [977,] 39.08 30 [978,] 39.12 32 [979,] 39.16 31 [980,] 39.20 37 [981,] 39.24 26 [982,] 39.28 29 [983,] 39.32 33 [984,] 39.36 28 [985,] 39.40 35 [986,] 39.44 37 [987,] 39.48 36 [988,] 39.52 24 [989,] 39.56 33 [990,] 39.60 31 [991,] 39.64 30 [992,] 39.68 24 [993,] 39.72 34 [994,] 39.76 38 [995,] 39.80 31 [996,] 39.84 26 [997,] 39.88 39 [998,] 39.92 28 [999,] 39.96 34 [1000,] 40.00 21 $`7_TL (PMT)` [,1] [,2] [1,] 0.64 5 [2,] 1.28 8 [3,] 1.92 0 [4,] 2.56 7 [5,] 3.20 1 [6,] 3.84 1 [7,] 4.48 0 [8,] 5.12 3 [9,] 5.76 8 [10,] 6.40 5 [11,] 7.04 7 [12,] 7.68 3 [13,] 8.32 6 [14,] 8.96 1 [15,] 9.60 18 [16,] 10.24 2 [17,] 10.88 0 [18,] 11.52 3 [19,] 12.16 0 [20,] 12.80 4 [21,] 13.44 8 [22,] 14.08 1 [23,] 14.72 6 [24,] 15.36 4 [25,] 16.00 3 [26,] 16.64 1 [27,] 17.28 2 [28,] 17.92 2 [29,] 18.56 0 [30,] 19.20 2 [31,] 19.84 13 [32,] 20.48 0 [33,] 21.12 1 [34,] 21.76 5 [35,] 22.40 1 [36,] 23.04 0 [37,] 23.68 3 [38,] 24.32 4 [39,] 24.96 1 [40,] 25.60 5 [41,] 26.24 1 [42,] 26.88 3 [43,] 27.52 6 [44,] 28.16 14 [45,] 28.80 7 [46,] 29.44 3 [47,] 30.08 8 [48,] 30.72 2 [49,] 31.36 5 [50,] 32.00 5 [51,] 32.64 3 [52,] 33.28 3 [53,] 33.92 10 [54,] 34.56 2 [55,] 35.20 6 [56,] 35.84 5 [57,] 36.48 6 [58,] 37.12 3 [59,] 37.76 6 [60,] 38.40 6 [61,] 39.04 1 [62,] 39.68 7 [63,] 40.32 4 [64,] 40.96 5 [65,] 41.60 1 [66,] 42.24 3 [67,] 42.88 5 [68,] 43.52 1 [69,] 44.16 6 [70,] 44.80 10 [71,] 45.44 4 [72,] 46.08 16 [73,] 46.72 6 [74,] 47.36 6 [75,] 48.00 10 [76,] 48.64 9 [77,] 49.28 4 [78,] 49.92 6 [79,] 50.56 8 [80,] 51.20 7 [81,] 51.84 3 [82,] 52.48 7 [83,] 53.12 5 [84,] 53.76 8 [85,] 54.40 12 [86,] 55.04 5 [87,] 55.68 13 [88,] 56.32 5 [89,] 56.96 15 [90,] 57.60 5 [91,] 58.24 11 [92,] 58.88 17 [93,] 59.52 21 [94,] 60.16 15 [95,] 60.80 9 [96,] 61.44 17 [97,] 62.08 5 [98,] 62.72 25 [99,] 63.36 6 [100,] 64.00 12 [101,] 64.64 10 [102,] 65.28 28 [103,] 65.92 11 [104,] 66.56 18 [105,] 67.20 31 [106,] 67.84 24 [107,] 68.48 19 [108,] 69.12 20 [109,] 69.76 36 [110,] 70.40 23 [111,] 71.04 32 [112,] 71.68 33 [113,] 72.32 25 [114,] 72.96 33 [115,] 73.60 31 [116,] 74.24 35 [117,] 74.88 48 [118,] 75.52 40 [119,] 76.16 50 [120,] 76.80 44 [121,] 77.44 47 [122,] 78.08 58 [123,] 78.72 63 [124,] 79.36 68 [125,] 80.00 59 [126,] 80.64 56 [127,] 81.28 81 [128,] 81.92 91 [129,] 82.56 81 [130,] 83.20 97 [131,] 83.84 88 [132,] 84.48 103 [133,] 85.12 92 [134,] 85.76 101 [135,] 86.40 117 [136,] 87.04 127 [137,] 87.68 110 [138,] 88.32 134 [139,] 88.96 113 [140,] 89.60 144 [141,] 90.24 156 [142,] 90.88 152 [143,] 91.52 153 [144,] 92.16 159 [145,] 92.80 160 [146,] 93.44 164 [147,] 94.08 187 [148,] 94.72 168 [149,] 95.36 219 [150,] 96.00 207 [151,] 96.64 170 [152,] 97.28 206 [153,] 97.92 217 [154,] 98.56 247 [155,] 99.20 199 [156,] 99.84 234 [157,] 100.48 222 [158,] 101.12 231 [159,] 101.76 244 [160,] 102.40 280 [161,] 103.04 226 [162,] 103.68 247 [163,] 104.32 253 [164,] 104.96 296 [165,] 105.60 239 [166,] 106.24 289 [167,] 106.88 233 [168,] 107.52 274 [169,] 108.16 277 [170,] 108.80 230 [171,] 109.44 230 [172,] 110.08 279 [173,] 110.72 245 [174,] 111.36 231 [175,] 112.00 228 [176,] 112.64 232 [177,] 113.28 194 [178,] 113.92 222 [179,] 114.56 209 [180,] 115.20 178 [181,] 115.84 188 [182,] 116.48 167 [183,] 117.12 163 [184,] 117.76 148 [185,] 118.40 121 [186,] 119.04 126 [187,] 119.68 102 [188,] 120.32 105 [189,] 120.96 112 [190,] 121.60 125 [191,] 122.24 94 [192,] 122.88 115 [193,] 123.52 87 [194,] 124.16 77 [195,] 124.80 75 [196,] 125.44 93 [197,] 126.08 92 [198,] 126.72 73 [199,] 127.36 77 [200,] 128.00 81 [201,] 128.64 84 [202,] 129.28 63 [203,] 129.92 55 [204,] 130.56 67 [205,] 131.20 78 [206,] 131.84 65 [207,] 132.48 60 [208,] 133.12 78 [209,] 133.76 66 [210,] 134.40 62 [211,] 135.04 69 [212,] 135.68 65 [213,] 136.32 75 [214,] 136.96 56 [215,] 137.60 70 [216,] 138.24 65 [217,] 138.88 66 [218,] 139.52 81 [219,] 140.16 78 [220,] 140.80 86 [221,] 141.44 64 [222,] 142.08 49 [223,] 142.72 59 [224,] 143.36 75 [225,] 144.00 79 [226,] 144.64 79 [227,] 145.28 88 [228,] 145.92 73 [229,] 146.56 64 [230,] 147.20 68 [231,] 147.84 58 [232,] 148.48 80 [233,] 149.12 72 [234,] 149.76 59 [235,] 150.40 65 [236,] 151.04 59 [237,] 151.68 56 [238,] 152.32 56 [239,] 152.96 68 [240,] 153.60 48 [241,] 154.24 76 [242,] 154.88 77 [243,] 155.52 94 [244,] 156.16 50 [245,] 156.80 47 [246,] 157.44 70 [247,] 158.08 58 [248,] 158.72 83 [249,] 159.36 41 [250,] 160.00 58 $`8_OSL (PMT)` [,1] [,2] [1,] 0.04 2726 [2,] 0.08 2251 [3,] 0.12 1972 [4,] 0.16 1678 [5,] 0.20 1554 [6,] 0.24 1359 [7,] 0.28 1232 [8,] 0.32 1053 [9,] 0.36 921 [10,] 0.40 778 [11,] 0.44 680 [12,] 0.48 604 [13,] 0.52 505 [14,] 0.56 559 [15,] 0.60 474 [16,] 0.64 420 [17,] 0.68 414 [18,] 0.72 321 [19,] 0.76 329 [20,] 0.80 332 [21,] 0.84 249 [22,] 0.88 254 [23,] 0.92 249 [24,] 0.96 205 [25,] 1.00 214 [26,] 1.04 190 [27,] 1.08 193 [28,] 1.12 175 [29,] 1.16 153 [30,] 1.20 154 [31,] 1.24 166 [32,] 1.28 158 [33,] 1.32 146 [34,] 1.36 129 [35,] 1.40 136 [36,] 1.44 101 [37,] 1.48 122 [38,] 1.52 96 [39,] 1.56 125 [40,] 1.60 117 [41,] 1.64 97 [42,] 1.68 103 [43,] 1.72 130 [44,] 1.76 87 [45,] 1.80 104 [46,] 1.84 116 [47,] 1.88 133 [48,] 1.92 122 [49,] 1.96 92 [50,] 2.00 86 [51,] 2.04 89 [52,] 2.08 89 [53,] 2.12 117 [54,] 2.16 90 [55,] 2.20 96 [56,] 2.24 88 [57,] 2.28 90 [58,] 2.32 78 [59,] 2.36 95 [60,] 2.40 93 [61,] 2.44 76 [62,] 2.48 73 [63,] 2.52 79 [64,] 2.56 86 [65,] 2.60 85 [66,] 2.64 59 [67,] 2.68 91 [68,] 2.72 84 [69,] 2.76 95 [70,] 2.80 83 [71,] 2.84 78 [72,] 2.88 82 [73,] 2.92 87 [74,] 2.96 76 [75,] 3.00 97 [76,] 3.04 83 [77,] 3.08 84 [78,] 3.12 74 [79,] 3.16 91 [80,] 3.20 79 [81,] 3.24 73 [82,] 3.28 76 [83,] 3.32 94 [84,] 3.36 74 [85,] 3.40 78 [86,] 3.44 76 [87,] 3.48 82 [88,] 3.52 75 [89,] 3.56 75 [90,] 3.60 77 [91,] 3.64 84 [92,] 3.68 80 [93,] 3.72 77 [94,] 3.76 67 [95,] 3.80 69 [96,] 3.84 85 [97,] 3.88 66 [98,] 3.92 68 [99,] 3.96 64 [100,] 4.00 73 [101,] 4.04 71 [102,] 4.08 61 [103,] 4.12 61 [104,] 4.16 87 [105,] 4.20 83 [106,] 4.24 94 [107,] 4.28 56 [108,] 4.32 77 [109,] 4.36 69 [110,] 4.40 80 [111,] 4.44 62 [112,] 4.48 79 [113,] 4.52 64 [114,] 4.56 77 [115,] 4.60 61 [116,] 4.64 60 [117,] 4.68 75 [118,] 4.72 71 [119,] 4.76 59 [120,] 4.80 67 [121,] 4.84 61 [122,] 4.88 63 [123,] 4.92 92 [124,] 4.96 61 [125,] 5.00 76 [126,] 5.04 65 [127,] 5.08 91 [128,] 5.12 90 [129,] 5.16 56 [130,] 5.20 59 [131,] 5.24 56 [132,] 5.28 63 [133,] 5.32 45 [134,] 5.36 61 [135,] 5.40 43 [136,] 5.44 67 [137,] 5.48 76 [138,] 5.52 62 [139,] 5.56 60 [140,] 5.60 80 [141,] 5.64 77 [142,] 5.68 78 [143,] 5.72 62 [144,] 5.76 67 [145,] 5.80 50 [146,] 5.84 57 [147,] 5.88 48 [148,] 5.92 54 [149,] 5.96 62 [150,] 6.00 63 [151,] 6.04 54 [152,] 6.08 80 [153,] 6.12 55 [154,] 6.16 68 [155,] 6.20 63 [156,] 6.24 61 [157,] 6.28 60 [158,] 6.32 73 [159,] 6.36 54 [160,] 6.40 72 [161,] 6.44 52 [162,] 6.48 48 [163,] 6.52 66 [164,] 6.56 77 [165,] 6.60 58 [166,] 6.64 52 [167,] 6.68 51 [168,] 6.72 52 [169,] 6.76 53 [170,] 6.80 75 [171,] 6.84 39 [172,] 6.88 54 [173,] 6.92 46 [174,] 6.96 51 [175,] 7.00 50 [176,] 7.04 64 [177,] 7.08 51 [178,] 7.12 61 [179,] 7.16 54 [180,] 7.20 71 [181,] 7.24 55 [182,] 7.28 59 [183,] 7.32 72 [184,] 7.36 84 [185,] 7.40 47 [186,] 7.44 60 [187,] 7.48 47 [188,] 7.52 42 [189,] 7.56 71 [190,] 7.60 51 [191,] 7.64 52 [192,] 7.68 53 [193,] 7.72 65 [194,] 7.76 56 [195,] 7.80 59 [196,] 7.84 52 [197,] 7.88 52 [198,] 7.92 40 [199,] 7.96 55 [200,] 8.00 53 [201,] 8.04 87 [202,] 8.08 55 [203,] 8.12 32 [204,] 8.16 46 [205,] 8.20 53 [206,] 8.24 52 [207,] 8.28 44 [208,] 8.32 54 [209,] 8.36 51 [210,] 8.40 77 [211,] 8.44 44 [212,] 8.48 45 [213,] 8.52 35 [214,] 8.56 58 [215,] 8.60 51 [216,] 8.64 49 [217,] 8.68 45 [218,] 8.72 71 [219,] 8.76 50 [220,] 8.80 62 [221,] 8.84 40 [222,] 8.88 54 [223,] 8.92 70 [224,] 8.96 61 [225,] 9.00 53 [226,] 9.04 52 [227,] 9.08 39 [228,] 9.12 78 [229,] 9.16 47 [230,] 9.20 61 [231,] 9.24 31 [232,] 9.28 50 [233,] 9.32 48 [234,] 9.36 59 [235,] 9.40 53 [236,] 9.44 53 [237,] 9.48 78 [238,] 9.52 57 [239,] 9.56 58 [240,] 9.60 55 [241,] 9.64 63 [242,] 9.68 66 [243,] 9.72 48 [244,] 9.76 38 [245,] 9.80 45 [246,] 9.84 57 [247,] 9.88 58 [248,] 9.92 55 [249,] 9.96 51 [250,] 10.00 73 [251,] 10.04 46 [252,] 10.08 71 [253,] 10.12 56 [254,] 10.16 35 [255,] 10.20 43 [256,] 10.24 71 [257,] 10.28 66 [258,] 10.32 49 [259,] 10.36 45 [260,] 10.40 51 [261,] 10.44 44 [262,] 10.48 54 [263,] 10.52 53 [264,] 10.56 57 [265,] 10.60 61 [266,] 10.64 32 [267,] 10.68 61 [268,] 10.72 58 [269,] 10.76 47 [270,] 10.80 57 [271,] 10.84 50 [272,] 10.88 67 [273,] 10.92 47 [274,] 10.96 43 [275,] 11.00 68 [276,] 11.04 49 [277,] 11.08 61 [278,] 11.12 70 [279,] 11.16 45 [280,] 11.20 49 [281,] 11.24 48 [282,] 11.28 56 [283,] 11.32 45 [284,] 11.36 56 [285,] 11.40 55 [286,] 11.44 37 [287,] 11.48 69 [288,] 11.52 46 [289,] 11.56 51 [290,] 11.60 54 [291,] 11.64 41 [292,] 11.68 55 [293,] 11.72 49 [294,] 11.76 50 [295,] 11.80 52 [296,] 11.84 48 [297,] 11.88 55 [298,] 11.92 63 [299,] 11.96 58 [300,] 12.00 48 [301,] 12.04 52 [302,] 12.08 53 [303,] 12.12 65 [304,] 12.16 54 [305,] 12.20 53 [306,] 12.24 51 [307,] 12.28 59 [308,] 12.32 46 [309,] 12.36 44 [310,] 12.40 83 [311,] 12.44 44 [312,] 12.48 29 [313,] 12.52 56 [314,] 12.56 53 [315,] 12.60 74 [316,] 12.64 67 [317,] 12.68 44 [318,] 12.72 39 [319,] 12.76 48 [320,] 12.80 55 [321,] 12.84 58 [322,] 12.88 42 [323,] 12.92 46 [324,] 12.96 57 [325,] 13.00 59 [326,] 13.04 58 [327,] 13.08 56 [328,] 13.12 53 [329,] 13.16 46 [330,] 13.20 48 [331,] 13.24 54 [332,] 13.28 42 [333,] 13.32 57 [334,] 13.36 55 [335,] 13.40 44 [336,] 13.44 58 [337,] 13.48 53 [338,] 13.52 50 [339,] 13.56 45 [340,] 13.60 35 [341,] 13.64 56 [342,] 13.68 53 [343,] 13.72 52 [344,] 13.76 58 [345,] 13.80 44 [346,] 13.84 48 [347,] 13.88 44 [348,] 13.92 52 [349,] 13.96 32 [350,] 14.00 49 [351,] 14.04 47 [352,] 14.08 31 [353,] 14.12 58 [354,] 14.16 50 [355,] 14.20 57 [356,] 14.24 40 [357,] 14.28 46 [358,] 14.32 54 [359,] 14.36 48 [360,] 14.40 45 [361,] 14.44 43 [362,] 14.48 56 [363,] 14.52 48 [364,] 14.56 50 [365,] 14.60 33 [366,] 14.64 42 [367,] 14.68 54 [368,] 14.72 78 [369,] 14.76 62 [370,] 14.80 44 [371,] 14.84 45 [372,] 14.88 62 [373,] 14.92 50 [374,] 14.96 54 [375,] 15.00 55 [376,] 15.04 49 [377,] 15.08 54 [378,] 15.12 56 [379,] 15.16 42 [380,] 15.20 49 [381,] 15.24 51 [382,] 15.28 61 [383,] 15.32 46 [384,] 15.36 49 [385,] 15.40 41 [386,] 15.44 52 [387,] 15.48 47 [388,] 15.52 43 [389,] 15.56 62 [390,] 15.60 42 [391,] 15.64 42 [392,] 15.68 44 [393,] 15.72 47 [394,] 15.76 49 [395,] 15.80 60 [396,] 15.84 51 [397,] 15.88 62 [398,] 15.92 49 [399,] 15.96 60 [400,] 16.00 32 [401,] 16.04 75 [402,] 16.08 33 [403,] 16.12 59 [404,] 16.16 51 [405,] 16.20 48 [406,] 16.24 40 [407,] 16.28 44 [408,] 16.32 40 [409,] 16.36 41 [410,] 16.40 49 [411,] 16.44 52 [412,] 16.48 49 [413,] 16.52 50 [414,] 16.56 51 [415,] 16.60 48 [416,] 16.64 45 [417,] 16.68 57 [418,] 16.72 36 [419,] 16.76 48 [420,] 16.80 48 [421,] 16.84 47 [422,] 16.88 50 [423,] 16.92 42 [424,] 16.96 46 [425,] 17.00 52 [426,] 17.04 40 [427,] 17.08 46 [428,] 17.12 60 [429,] 17.16 41 [430,] 17.20 42 [431,] 17.24 51 [432,] 17.28 45 [433,] 17.32 29 [434,] 17.36 57 [435,] 17.40 53 [436,] 17.44 37 [437,] 17.48 43 [438,] 17.52 32 [439,] 17.56 50 [440,] 17.60 62 [441,] 17.64 51 [442,] 17.68 59 [443,] 17.72 42 [444,] 17.76 49 [445,] 17.80 39 [446,] 17.84 56 [447,] 17.88 53 [448,] 17.92 46 [449,] 17.96 59 [450,] 18.00 53 [451,] 18.04 64 [452,] 18.08 31 [453,] 18.12 45 [454,] 18.16 44 [455,] 18.20 53 [456,] 18.24 37 [457,] 18.28 36 [458,] 18.32 52 [459,] 18.36 57 [460,] 18.40 44 [461,] 18.44 48 [462,] 18.48 46 [463,] 18.52 31 [464,] 18.56 67 [465,] 18.60 43 [466,] 18.64 58 [467,] 18.68 53 [468,] 18.72 47 [469,] 18.76 59 [470,] 18.80 47 [471,] 18.84 31 [472,] 18.88 51 [473,] 18.92 44 [474,] 18.96 43 [475,] 19.00 49 [476,] 19.04 42 [477,] 19.08 48 [478,] 19.12 42 [479,] 19.16 37 [480,] 19.20 45 [481,] 19.24 54 [482,] 19.28 42 [483,] 19.32 50 [484,] 19.36 42 [485,] 19.40 47 [486,] 19.44 51 [487,] 19.48 54 [488,] 19.52 46 [489,] 19.56 39 [490,] 19.60 42 [491,] 19.64 38 [492,] 19.68 49 [493,] 19.72 63 [494,] 19.76 41 [495,] 19.80 50 [496,] 19.84 44 [497,] 19.88 52 [498,] 19.92 57 [499,] 19.96 43 [500,] 20.00 48 [501,] 20.04 38 [502,] 20.08 38 [503,] 20.12 53 [504,] 20.16 30 [505,] 20.20 47 [506,] 20.24 46 [507,] 20.28 48 [508,] 20.32 56 [509,] 20.36 54 [510,] 20.40 45 [511,] 20.44 48 [512,] 20.48 28 [513,] 20.52 48 [514,] 20.56 42 [515,] 20.60 42 [516,] 20.64 39 [517,] 20.68 46 [518,] 20.72 38 [519,] 20.76 48 [520,] 20.80 44 [521,] 20.84 26 [522,] 20.88 37 [523,] 20.92 41 [524,] 20.96 37 [525,] 21.00 54 [526,] 21.04 52 [527,] 21.08 36 [528,] 21.12 53 [529,] 21.16 43 [530,] 21.20 51 [531,] 21.24 54 [532,] 21.28 51 [533,] 21.32 55 [534,] 21.36 57 [535,] 21.40 61 [536,] 21.44 33 [537,] 21.48 51 [538,] 21.52 37 [539,] 21.56 28 [540,] 21.60 46 [541,] 21.64 46 [542,] 21.68 28 [543,] 21.72 39 [544,] 21.76 60 [545,] 21.80 48 [546,] 21.84 55 [547,] 21.88 35 [548,] 21.92 54 [549,] 21.96 39 [550,] 22.00 48 [551,] 22.04 46 [552,] 22.08 31 [553,] 22.12 51 [554,] 22.16 46 [555,] 22.20 44 [556,] 22.24 62 [557,] 22.28 33 [558,] 22.32 55 [559,] 22.36 44 [560,] 22.40 51 [561,] 22.44 39 [562,] 22.48 49 [563,] 22.52 29 [564,] 22.56 45 [565,] 22.60 59 [566,] 22.64 44 [567,] 22.68 27 [568,] 22.72 65 [569,] 22.76 41 [570,] 22.80 40 [571,] 22.84 43 [572,] 22.88 43 [573,] 22.92 49 [574,] 22.96 31 [575,] 23.00 38 [576,] 23.04 53 [577,] 23.08 34 [578,] 23.12 54 [579,] 23.16 37 [580,] 23.20 34 [581,] 23.24 72 [582,] 23.28 46 [583,] 23.32 45 [584,] 23.36 39 [585,] 23.40 37 [586,] 23.44 58 [587,] 23.48 46 [588,] 23.52 39 [589,] 23.56 58 [590,] 23.60 43 [591,] 23.64 46 [592,] 23.68 57 [593,] 23.72 40 [594,] 23.76 46 [595,] 23.80 56 [596,] 23.84 42 [597,] 23.88 44 [598,] 23.92 54 [599,] 23.96 61 [600,] 24.00 36 [601,] 24.04 38 [602,] 24.08 46 [603,] 24.12 58 [604,] 24.16 50 [605,] 24.20 43 [606,] 24.24 51 [607,] 24.28 40 [608,] 24.32 31 [609,] 24.36 30 [610,] 24.40 50 [611,] 24.44 38 [612,] 24.48 38 [613,] 24.52 47 [614,] 24.56 55 [615,] 24.60 44 [616,] 24.64 27 [617,] 24.68 40 [618,] 24.72 46 [619,] 24.76 49 [620,] 24.80 39 [621,] 24.84 39 [622,] 24.88 25 [623,] 24.92 35 [624,] 24.96 38 [625,] 25.00 43 [626,] 25.04 53 [627,] 25.08 51 [628,] 25.12 67 [629,] 25.16 46 [630,] 25.20 61 [631,] 25.24 41 [632,] 25.28 44 [633,] 25.32 35 [634,] 25.36 46 [635,] 25.40 49 [636,] 25.44 43 [637,] 25.48 47 [638,] 25.52 36 [639,] 25.56 68 [640,] 25.60 52 [641,] 25.64 52 [642,] 25.68 43 [643,] 25.72 33 [644,] 25.76 42 [645,] 25.80 62 [646,] 25.84 40 [647,] 25.88 51 [648,] 25.92 46 [649,] 25.96 45 [650,] 26.00 54 [651,] 26.04 41 [652,] 26.08 41 [653,] 26.12 40 [654,] 26.16 37 [655,] 26.20 44 [656,] 26.24 49 [657,] 26.28 54 [658,] 26.32 49 [659,] 26.36 44 [660,] 26.40 43 [661,] 26.44 49 [662,] 26.48 41 [663,] 26.52 47 [664,] 26.56 44 [665,] 26.60 40 [666,] 26.64 51 [667,] 26.68 44 [668,] 26.72 41 [669,] 26.76 52 [670,] 26.80 47 [671,] 26.84 37 [672,] 26.88 37 [673,] 26.92 42 [674,] 26.96 36 [675,] 27.00 49 [676,] 27.04 29 [677,] 27.08 30 [678,] 27.12 34 [679,] 27.16 52 [680,] 27.20 42 [681,] 27.24 33 [682,] 27.28 44 [683,] 27.32 41 [684,] 27.36 44 [685,] 27.40 46 [686,] 27.44 32 [687,] 27.48 43 [688,] 27.52 62 [689,] 27.56 54 [690,] 27.60 25 [691,] 27.64 41 [692,] 27.68 45 [693,] 27.72 42 [694,] 27.76 54 [695,] 27.80 46 [696,] 27.84 43 [697,] 27.88 45 [698,] 27.92 39 [699,] 27.96 44 [700,] 28.00 56 [701,] 28.04 52 [702,] 28.08 48 [703,] 28.12 55 [704,] 28.16 36 [705,] 28.20 43 [706,] 28.24 36 [707,] 28.28 39 [708,] 28.32 56 [709,] 28.36 37 [710,] 28.40 48 [711,] 28.44 46 [712,] 28.48 56 [713,] 28.52 39 [714,] 28.56 52 [715,] 28.60 37 [716,] 28.64 57 [717,] 28.68 40 [718,] 28.72 41 [719,] 28.76 41 [720,] 28.80 32 [721,] 28.84 52 [722,] 28.88 38 [723,] 28.92 45 [724,] 28.96 49 [725,] 29.00 52 [726,] 29.04 34 [727,] 29.08 34 [728,] 29.12 60 [729,] 29.16 46 [730,] 29.20 37 [731,] 29.24 43 [732,] 29.28 39 [733,] 29.32 56 [734,] 29.36 35 [735,] 29.40 43 [736,] 29.44 38 [737,] 29.48 44 [738,] 29.52 52 [739,] 29.56 63 [740,] 29.60 43 [741,] 29.64 31 [742,] 29.68 41 [743,] 29.72 43 [744,] 29.76 46 [745,] 29.80 51 [746,] 29.84 53 [747,] 29.88 29 [748,] 29.92 46 [749,] 29.96 47 [750,] 30.00 48 [751,] 30.04 50 [752,] 30.08 34 [753,] 30.12 36 [754,] 30.16 50 [755,] 30.20 50 [756,] 30.24 45 [757,] 30.28 40 [758,] 30.32 37 [759,] 30.36 39 [760,] 30.40 54 [761,] 30.44 51 [762,] 30.48 35 [763,] 30.52 45 [764,] 30.56 37 [765,] 30.60 36 [766,] 30.64 39 [767,] 30.68 38 [768,] 30.72 40 [769,] 30.76 31 [770,] 30.80 34 [771,] 30.84 28 [772,] 30.88 53 [773,] 30.92 43 [774,] 30.96 43 [775,] 31.00 38 [776,] 31.04 34 [777,] 31.08 41 [778,] 31.12 39 [779,] 31.16 44 [780,] 31.20 54 [781,] 31.24 57 [782,] 31.28 42 [783,] 31.32 54 [784,] 31.36 25 [785,] 31.40 56 [786,] 31.44 45 [787,] 31.48 43 [788,] 31.52 38 [789,] 31.56 36 [790,] 31.60 42 [791,] 31.64 50 [792,] 31.68 35 [793,] 31.72 48 [794,] 31.76 35 [795,] 31.80 60 [796,] 31.84 43 [797,] 31.88 40 [798,] 31.92 46 [799,] 31.96 44 [800,] 32.00 46 [801,] 32.04 52 [802,] 32.08 34 [803,] 32.12 56 [804,] 32.16 44 [805,] 32.20 47 [806,] 32.24 49 [807,] 32.28 43 [808,] 32.32 43 [809,] 32.36 40 [810,] 32.40 31 [811,] 32.44 46 [812,] 32.48 43 [813,] 32.52 59 [814,] 32.56 46 [815,] 32.60 29 [816,] 32.64 49 [817,] 32.68 29 [818,] 32.72 42 [819,] 32.76 44 [820,] 32.80 44 [821,] 32.84 48 [822,] 32.88 47 [823,] 32.92 48 [824,] 32.96 36 [825,] 33.00 41 [826,] 33.04 46 [827,] 33.08 32 [828,] 33.12 44 [829,] 33.16 51 [830,] 33.20 37 [831,] 33.24 52 [832,] 33.28 32 [833,] 33.32 46 [834,] 33.36 50 [835,] 33.40 33 [836,] 33.44 44 [837,] 33.48 49 [838,] 33.52 48 [839,] 33.56 23 [840,] 33.60 36 [841,] 33.64 46 [842,] 33.68 39 [843,] 33.72 49 [844,] 33.76 40 [845,] 33.80 40 [846,] 33.84 53 [847,] 33.88 43 [848,] 33.92 38 [849,] 33.96 52 [850,] 34.00 30 [851,] 34.04 30 [852,] 34.08 31 [853,] 34.12 49 [854,] 34.16 41 [855,] 34.20 39 [856,] 34.24 42 [857,] 34.28 47 [858,] 34.32 49 [859,] 34.36 42 [860,] 34.40 42 [861,] 34.44 43 [862,] 34.48 47 [863,] 34.52 40 [864,] 34.56 31 [865,] 34.60 47 [866,] 34.64 39 [867,] 34.68 41 [868,] 34.72 26 [869,] 34.76 29 [870,] 34.80 24 [871,] 34.84 41 [872,] 34.88 49 [873,] 34.92 53 [874,] 34.96 43 [875,] 35.00 36 [876,] 35.04 39 [877,] 35.08 38 [878,] 35.12 39 [879,] 35.16 33 [880,] 35.20 51 [881,] 35.24 31 [882,] 35.28 36 [883,] 35.32 34 [884,] 35.36 45 [885,] 35.40 56 [886,] 35.44 26 [887,] 35.48 48 [888,] 35.52 38 [889,] 35.56 38 [890,] 35.60 42 [891,] 35.64 24 [892,] 35.68 31 [893,] 35.72 46 [894,] 35.76 38 [895,] 35.80 35 [896,] 35.84 32 [897,] 35.88 51 [898,] 35.92 44 [899,] 35.96 35 [900,] 36.00 51 [901,] 36.04 45 [902,] 36.08 41 [903,] 36.12 36 [904,] 36.16 36 [905,] 36.20 33 [906,] 36.24 50 [907,] 36.28 47 [908,] 36.32 51 [909,] 36.36 38 [910,] 36.40 34 [911,] 36.44 32 [912,] 36.48 44 [913,] 36.52 43 [914,] 36.56 43 [915,] 36.60 29 [916,] 36.64 33 [917,] 36.68 54 [918,] 36.72 47 [919,] 36.76 36 [920,] 36.80 47 [921,] 36.84 56 [922,] 36.88 47 [923,] 36.92 43 [924,] 36.96 56 [925,] 37.00 28 [926,] 37.04 39 [927,] 37.08 44 [928,] 37.12 37 [929,] 37.16 43 [930,] 37.20 44 [931,] 37.24 38 [932,] 37.28 46 [933,] 37.32 42 [934,] 37.36 34 [935,] 37.40 44 [936,] 37.44 36 [937,] 37.48 39 [938,] 37.52 48 [939,] 37.56 46 [940,] 37.60 34 [941,] 37.64 43 [942,] 37.68 30 [943,] 37.72 44 [944,] 37.76 29 [945,] 37.80 44 [946,] 37.84 49 [947,] 37.88 42 [948,] 37.92 30 [949,] 37.96 40 [950,] 38.00 36 [951,] 38.04 43 [952,] 38.08 28 [953,] 38.12 34 [954,] 38.16 46 [955,] 38.20 39 [956,] 38.24 34 [957,] 38.28 43 [958,] 38.32 32 [959,] 38.36 39 [960,] 38.40 38 [961,] 38.44 33 [962,] 38.48 26 [963,] 38.52 38 [964,] 38.56 40 [965,] 38.60 31 [966,] 38.64 35 [967,] 38.68 52 [968,] 38.72 35 [969,] 38.76 58 [970,] 38.80 44 [971,] 38.84 34 [972,] 38.88 39 [973,] 38.92 45 [974,] 38.96 50 [975,] 39.00 43 [976,] 39.04 43 [977,] 39.08 53 [978,] 39.12 55 [979,] 39.16 39 [980,] 39.20 38 [981,] 39.24 41 [982,] 39.28 36 [983,] 39.32 36 [984,] 39.36 43 [985,] 39.40 34 [986,] 39.44 29 [987,] 39.48 36 [988,] 39.52 37 [989,] 39.56 40 [990,] 39.60 50 [991,] 39.64 48 [992,] 39.68 46 [993,] 39.72 51 [994,] 39.76 50 [995,] 39.80 32 [996,] 39.84 41 [997,] 39.88 41 [998,] 39.92 41 [999,] 39.96 31 [1000,] 40.00 48 $`9_TL (PMT)` [,1] [,2] [1,] 0.884 13 [2,] 1.768 98 [3,] 2.652 6 [4,] 3.536 6 [5,] 4.420 9 [6,] 5.304 8 [7,] 6.188 9 [8,] 7.072 9 [9,] 7.956 4 [10,] 8.840 13 [11,] 9.724 10 [12,] 10.608 5 [13,] 11.492 5 [14,] 12.376 19 [15,] 13.260 11 [16,] 14.144 4 [17,] 15.028 6 [18,] 15.912 10 [19,] 16.796 9 [20,] 17.680 4 [21,] 18.564 8 [22,] 19.448 10 [23,] 20.332 7 [24,] 21.216 3 [25,] 22.100 6 [26,] 22.984 5 [27,] 23.868 5 [28,] 24.752 4 [29,] 25.636 6 [30,] 26.520 11 [31,] 27.404 3 [32,] 28.288 0 [33,] 29.172 8 [34,] 30.056 2 [35,] 30.940 2 [36,] 31.824 4 [37,] 32.708 10 [38,] 33.592 6 [39,] 34.476 11 [40,] 35.360 25 [41,] 36.244 4 [42,] 37.128 4 [43,] 38.012 4 [44,] 38.896 10 [45,] 39.780 5 [46,] 40.664 17 [47,] 41.548 5 [48,] 42.432 11 [49,] 43.316 13 [50,] 44.200 6 [51,] 45.084 2 [52,] 45.968 3 [53,] 46.852 11 [54,] 47.736 10 [55,] 48.620 6 [56,] 49.504 5 [57,] 50.388 10 [58,] 51.272 4 [59,] 52.156 1 [60,] 53.040 11 [61,] 53.924 12 [62,] 54.808 10 [63,] 55.692 3 [64,] 56.576 5 [65,] 57.460 7 [66,] 58.344 5 [67,] 59.228 5 [68,] 60.112 7 [69,] 60.996 3 [70,] 61.880 6 [71,] 62.764 3 [72,] 63.648 10 [73,] 64.532 4 [74,] 65.416 5 [75,] 66.300 13 [76,] 67.184 2 [77,] 68.068 5 [78,] 68.952 4 [79,] 69.836 4 [80,] 70.720 3 [81,] 71.604 13 [82,] 72.488 12 [83,] 73.372 4 [84,] 74.256 9 [85,] 75.140 24 [86,] 76.024 7 [87,] 76.908 8 [88,] 77.792 21 [89,] 78.676 11 [90,] 79.560 19 [91,] 80.444 7 [92,] 81.328 7 [93,] 82.212 15 [94,] 83.096 27 [95,] 83.980 15 [96,] 84.864 27 [97,] 85.748 21 [98,] 86.632 33 [99,] 87.516 30 [100,] 88.400 26 [101,] 89.284 31 [102,] 90.168 26 [103,] 91.052 52 [104,] 91.936 22 [105,] 92.820 33 [106,] 93.704 31 [107,] 94.588 35 [108,] 95.472 43 [109,] 96.356 47 [110,] 97.240 35 [111,] 98.124 60 [112,] 99.008 66 [113,] 99.892 59 [114,] 100.776 51 [115,] 101.660 63 [116,] 102.544 59 [117,] 103.428 60 [118,] 104.312 76 [119,] 105.196 80 [120,] 106.080 77 [121,] 106.964 91 [122,] 107.848 111 [123,] 108.732 73 [124,] 109.616 91 [125,] 110.500 106 [126,] 111.384 96 [127,] 112.268 101 [128,] 113.152 102 [129,] 114.036 127 [130,] 114.920 136 [131,] 115.804 134 [132,] 116.688 147 [133,] 117.572 129 [134,] 118.456 144 [135,] 119.340 129 [136,] 120.224 150 [137,] 121.108 155 [138,] 121.992 166 [139,] 122.876 152 [140,] 123.760 222 [141,] 124.644 181 [142,] 125.528 175 [143,] 126.412 211 [144,] 127.296 202 [145,] 128.180 192 [146,] 129.064 217 [147,] 129.948 215 [148,] 130.832 223 [149,] 131.716 213 [150,] 132.600 234 [151,] 133.484 271 [152,] 134.368 221 [153,] 135.252 295 [154,] 136.136 285 [155,] 137.020 246 [156,] 137.904 245 [157,] 138.788 295 [158,] 139.672 272 [159,] 140.556 260 [160,] 141.440 273 [161,] 142.324 238 [162,] 143.208 277 [163,] 144.092 303 [164,] 144.976 281 [165,] 145.860 290 [166,] 146.744 288 [167,] 147.628 245 [168,] 148.512 260 [169,] 149.396 289 [170,] 150.280 292 [171,] 151.164 238 [172,] 152.048 283 [173,] 152.932 290 [174,] 153.816 287 [175,] 154.700 303 [176,] 155.584 308 [177,] 156.468 270 [178,] 157.352 282 [179,] 158.236 272 [180,] 159.120 299 [181,] 160.004 269 [182,] 160.888 259 [183,] 161.772 257 [184,] 162.656 284 [185,] 163.540 278 [186,] 164.424 278 [187,] 165.308 317 [188,] 166.192 286 [189,] 167.076 291 [190,] 167.960 296 [191,] 168.844 319 [192,] 169.728 270 [193,] 170.612 276 [194,] 171.496 268 [195,] 172.380 232 [196,] 173.264 302 [197,] 174.148 238 [198,] 175.032 261 [199,] 175.916 247 [200,] 176.800 271 [201,] 177.684 267 [202,] 178.568 271 [203,] 179.452 286 [204,] 180.336 259 [205,] 181.220 298 [206,] 182.104 299 [207,] 182.988 276 [208,] 183.872 276 [209,] 184.756 272 [210,] 185.640 266 [211,] 186.524 279 [212,] 187.408 264 [213,] 188.292 291 [214,] 189.176 269 [215,] 190.060 302 [216,] 190.944 296 [217,] 191.828 263 [218,] 192.712 281 [219,] 193.596 352 [220,] 194.480 321 [221,] 195.364 302 [222,] 196.248 262 [223,] 197.132 299 [224,] 198.016 342 [225,] 198.900 319 [226,] 199.784 309 [227,] 200.668 302 [228,] 201.552 366 [229,] 202.436 295 [230,] 203.320 349 [231,] 204.204 348 [232,] 205.088 343 [233,] 205.972 366 [234,] 206.856 315 [235,] 207.740 348 [236,] 208.624 393 [237,] 209.508 366 [238,] 210.392 389 [239,] 211.276 379 [240,] 212.160 411 [241,] 213.044 467 [242,] 213.928 369 [243,] 214.812 358 [244,] 215.696 371 [245,] 216.580 349 [246,] 217.464 360 [247,] 218.348 376 [248,] 219.232 359 [249,] 220.116 364 [250,] 221.000 105 $`10_OSL (PMT)` [,1] [,2] [1,] 0.04 8150 [2,] 0.08 7000 [3,] 0.12 5947 [4,] 0.16 5118 [5,] 0.20 4534 [6,] 0.24 3776 [7,] 0.28 3512 [8,] 0.32 2887 [9,] 0.36 2479 [10,] 0.40 2130 [11,] 0.44 1991 [12,] 0.48 1783 [13,] 0.52 1495 [14,] 0.56 1359 [15,] 0.60 1161 [16,] 0.64 1033 [17,] 0.68 982 [18,] 0.72 846 [19,] 0.76 884 [20,] 0.80 700 [21,] 0.84 612 [22,] 0.88 543 [23,] 0.92 527 [24,] 0.96 471 [25,] 1.00 440 [26,] 1.04 410 [27,] 1.08 372 [28,] 1.12 343 [29,] 1.16 337 [30,] 1.20 282 [31,] 1.24 292 [32,] 1.28 288 [33,] 1.32 274 [34,] 1.36 272 [35,] 1.40 197 [36,] 1.44 203 [37,] 1.48 228 [38,] 1.52 244 [39,] 1.56 214 [40,] 1.60 184 [41,] 1.64 229 [42,] 1.68 187 [43,] 1.72 171 [44,] 1.76 166 [45,] 1.80 130 [46,] 1.84 140 [47,] 1.88 150 [48,] 1.92 161 [49,] 1.96 143 [50,] 2.00 129 [51,] 2.04 137 [52,] 2.08 142 [53,] 2.12 124 [54,] 2.16 140 [55,] 2.20 146 [56,] 2.24 150 [57,] 2.28 108 [58,] 2.32 145 [59,] 2.36 146 [60,] 2.40 125 [61,] 2.44 102 [62,] 2.48 135 [63,] 2.52 119 [64,] 2.56 145 [65,] 2.60 112 [66,] 2.64 105 [67,] 2.68 127 [68,] 2.72 112 [69,] 2.76 107 [70,] 2.80 105 [71,] 2.84 108 [72,] 2.88 117 [73,] 2.92 135 [74,] 2.96 100 [75,] 3.00 108 [76,] 3.04 112 [77,] 3.08 100 [78,] 3.12 112 [79,] 3.16 93 [80,] 3.20 96 [81,] 3.24 99 [82,] 3.28 94 [83,] 3.32 110 [84,] 3.36 96 [85,] 3.40 76 [86,] 3.44 97 [87,] 3.48 88 [88,] 3.52 85 [89,] 3.56 96 [90,] 3.60 89 [91,] 3.64 99 [92,] 3.68 64 [93,] 3.72 80 [94,] 3.76 86 [95,] 3.80 86 [96,] 3.84 87 [97,] 3.88 111 [98,] 3.92 90 [99,] 3.96 80 [100,] 4.00 109 [101,] 4.04 105 [102,] 4.08 94 [103,] 4.12 75 [104,] 4.16 80 [105,] 4.20 90 [106,] 4.24 88 [107,] 4.28 95 [108,] 4.32 94 [109,] 4.36 90 [110,] 4.40 79 [111,] 4.44 82 [112,] 4.48 74 [113,] 4.52 84 [114,] 4.56 82 [115,] 4.60 75 [116,] 4.64 83 [117,] 4.68 83 [118,] 4.72 79 [119,] 4.76 57 [120,] 4.80 62 [121,] 4.84 65 [122,] 4.88 100 [123,] 4.92 68 [124,] 4.96 94 [125,] 5.00 92 [126,] 5.04 90 [127,] 5.08 70 [128,] 5.12 77 [129,] 5.16 83 [130,] 5.20 75 [131,] 5.24 81 [132,] 5.28 78 [133,] 5.32 84 [134,] 5.36 80 [135,] 5.40 98 [136,] 5.44 79 [137,] 5.48 59 [138,] 5.52 95 [139,] 5.56 85 [140,] 5.60 86 [141,] 5.64 94 [142,] 5.68 89 [143,] 5.72 86 [144,] 5.76 93 [145,] 5.80 83 [146,] 5.84 103 [147,] 5.88 64 [148,] 5.92 60 [149,] 5.96 76 [150,] 6.00 57 [151,] 6.04 68 [152,] 6.08 72 [153,] 6.12 74 [154,] 6.16 65 [155,] 6.20 106 [156,] 6.24 81 [157,] 6.28 61 [158,] 6.32 66 [159,] 6.36 78 [160,] 6.40 62 [161,] 6.44 53 [162,] 6.48 67 [163,] 6.52 70 [164,] 6.56 69 [165,] 6.60 61 [166,] 6.64 84 [167,] 6.68 91 [168,] 6.72 79 [169,] 6.76 84 [170,] 6.80 63 [171,] 6.84 72 [172,] 6.88 60 [173,] 6.92 64 [174,] 6.96 75 [175,] 7.00 72 [176,] 7.04 72 [177,] 7.08 76 [178,] 7.12 64 [179,] 7.16 89 [180,] 7.20 64 [181,] 7.24 79 [182,] 7.28 60 [183,] 7.32 94 [184,] 7.36 75 [185,] 7.40 80 [186,] 7.44 84 [187,] 7.48 66 [188,] 7.52 73 [189,] 7.56 80 [190,] 7.60 66 [191,] 7.64 61 [192,] 7.68 62 [193,] 7.72 78 [194,] 7.76 73 [195,] 7.80 54 [196,] 7.84 63 [197,] 7.88 60 [198,] 7.92 72 [199,] 7.96 61 [200,] 8.00 73 [201,] 8.04 71 [202,] 8.08 49 [203,] 8.12 72 [204,] 8.16 68 [205,] 8.20 66 [206,] 8.24 59 [207,] 8.28 78 [208,] 8.32 60 [209,] 8.36 85 [210,] 8.40 59 [211,] 8.44 72 [212,] 8.48 78 [213,] 8.52 66 [214,] 8.56 60 [215,] 8.60 70 [216,] 8.64 69 [217,] 8.68 58 [218,] 8.72 65 [219,] 8.76 65 [220,] 8.80 50 [221,] 8.84 65 [222,] 8.88 76 [223,] 8.92 68 [224,] 8.96 65 [225,] 9.00 51 [226,] 9.04 70 [227,] 9.08 60 [228,] 9.12 65 [229,] 9.16 77 [230,] 9.20 71 [231,] 9.24 70 [232,] 9.28 95 [233,] 9.32 63 [234,] 9.36 70 [235,] 9.40 61 [236,] 9.44 64 [237,] 9.48 70 [238,] 9.52 69 [239,] 9.56 60 [240,] 9.60 69 [241,] 9.64 66 [242,] 9.68 69 [243,] 9.72 64 [244,] 9.76 81 [245,] 9.80 61 [246,] 9.84 57 [247,] 9.88 63 [248,] 9.92 86 [249,] 9.96 74 [250,] 10.00 51 [251,] 10.04 42 [252,] 10.08 61 [253,] 10.12 73 [254,] 10.16 87 [255,] 10.20 61 [256,] 10.24 62 [257,] 10.28 91 [258,] 10.32 60 [259,] 10.36 78 [260,] 10.40 64 [261,] 10.44 50 [262,] 10.48 58 [263,] 10.52 82 [264,] 10.56 52 [265,] 10.60 63 [266,] 10.64 74 [267,] 10.68 68 [268,] 10.72 71 [269,] 10.76 51 [270,] 10.80 73 [271,] 10.84 71 [272,] 10.88 53 [273,] 10.92 67 [274,] 10.96 56 [275,] 11.00 38 [276,] 11.04 60 [277,] 11.08 77 [278,] 11.12 64 [279,] 11.16 47 [280,] 11.20 69 [281,] 11.24 59 [282,] 11.28 54 [283,] 11.32 41 [284,] 11.36 68 [285,] 11.40 63 [286,] 11.44 43 [287,] 11.48 80 [288,] 11.52 54 [289,] 11.56 76 [290,] 11.60 62 [291,] 11.64 58 [292,] 11.68 52 [293,] 11.72 49 [294,] 11.76 68 [295,] 11.80 43 [296,] 11.84 53 [297,] 11.88 48 [298,] 11.92 63 [299,] 11.96 68 [300,] 12.00 65 [301,] 12.04 79 [302,] 12.08 57 [303,] 12.12 52 [304,] 12.16 61 [305,] 12.20 61 [306,] 12.24 64 [307,] 12.28 71 [308,] 12.32 71 [309,] 12.36 49 [310,] 12.40 58 [311,] 12.44 58 [312,] 12.48 55 [313,] 12.52 57 [314,] 12.56 68 [315,] 12.60 60 [316,] 12.64 75 [317,] 12.68 52 [318,] 12.72 49 [319,] 12.76 60 [320,] 12.80 58 [321,] 12.84 54 [322,] 12.88 51 [323,] 12.92 57 [324,] 12.96 65 [325,] 13.00 45 [326,] 13.04 56 [327,] 13.08 54 [328,] 13.12 67 [329,] 13.16 89 [330,] 13.20 68 [331,] 13.24 65 [332,] 13.28 50 [333,] 13.32 58 [334,] 13.36 62 [335,] 13.40 61 [336,] 13.44 53 [337,] 13.48 59 [338,] 13.52 65 [339,] 13.56 65 [340,] 13.60 51 [341,] 13.64 50 [342,] 13.68 49 [343,] 13.72 47 [344,] 13.76 57 [345,] 13.80 53 [346,] 13.84 66 [347,] 13.88 54 [348,] 13.92 49 [349,] 13.96 75 [350,] 14.00 58 [351,] 14.04 40 [352,] 14.08 65 [353,] 14.12 69 [354,] 14.16 55 [355,] 14.20 51 [356,] 14.24 58 [357,] 14.28 55 [358,] 14.32 54 [359,] 14.36 67 [360,] 14.40 39 [361,] 14.44 48 [362,] 14.48 58 [363,] 14.52 68 [364,] 14.56 62 [365,] 14.60 57 [366,] 14.64 75 [367,] 14.68 47 [368,] 14.72 47 [369,] 14.76 56 [370,] 14.80 47 [371,] 14.84 54 [372,] 14.88 57 [373,] 14.92 76 [374,] 14.96 75 [375,] 15.00 62 [376,] 15.04 60 [377,] 15.08 48 [378,] 15.12 60 [379,] 15.16 66 [380,] 15.20 54 [381,] 15.24 55 [382,] 15.28 71 [383,] 15.32 53 [384,] 15.36 68 [385,] 15.40 42 [386,] 15.44 53 [387,] 15.48 74 [388,] 15.52 54 [389,] 15.56 56 [390,] 15.60 57 [391,] 15.64 55 [392,] 15.68 51 [393,] 15.72 42 [394,] 15.76 49 [395,] 15.80 51 [396,] 15.84 60 [397,] 15.88 62 [398,] 15.92 53 [399,] 15.96 46 [400,] 16.00 62 [401,] 16.04 78 [402,] 16.08 60 [403,] 16.12 63 [404,] 16.16 74 [405,] 16.20 41 [406,] 16.24 57 [407,] 16.28 61 [408,] 16.32 47 [409,] 16.36 62 [410,] 16.40 71 [411,] 16.44 57 [412,] 16.48 55 [413,] 16.52 68 [414,] 16.56 43 [415,] 16.60 57 [416,] 16.64 43 [417,] 16.68 57 [418,] 16.72 59 [419,] 16.76 60 [420,] 16.80 70 [421,] 16.84 81 [422,] 16.88 52 [423,] 16.92 45 [424,] 16.96 65 [425,] 17.00 36 [426,] 17.04 58 [427,] 17.08 65 [428,] 17.12 71 [429,] 17.16 57 [430,] 17.20 51 [431,] 17.24 60 [432,] 17.28 55 [433,] 17.32 43 [434,] 17.36 59 [435,] 17.40 64 [436,] 17.44 52 [437,] 17.48 50 [438,] 17.52 52 [439,] 17.56 61 [440,] 17.60 54 [441,] 17.64 63 [442,] 17.68 65 [443,] 17.72 53 [444,] 17.76 50 [445,] 17.80 43 [446,] 17.84 47 [447,] 17.88 65 [448,] 17.92 61 [449,] 17.96 49 [450,] 18.00 58 [451,] 18.04 64 [452,] 18.08 42 [453,] 18.12 66 [454,] 18.16 64 [455,] 18.20 51 [456,] 18.24 73 [457,] 18.28 59 [458,] 18.32 55 [459,] 18.36 50 [460,] 18.40 54 [461,] 18.44 53 [462,] 18.48 68 [463,] 18.52 49 [464,] 18.56 59 [465,] 18.60 60 [466,] 18.64 41 [467,] 18.68 55 [468,] 18.72 56 [469,] 18.76 46 [470,] 18.80 47 [471,] 18.84 54 [472,] 18.88 57 [473,] 18.92 57 [474,] 18.96 61 [475,] 19.00 62 [476,] 19.04 56 [477,] 19.08 57 [478,] 19.12 55 [479,] 19.16 65 [480,] 19.20 52 [481,] 19.24 69 [482,] 19.28 61 [483,] 19.32 54 [484,] 19.36 56 [485,] 19.40 51 [486,] 19.44 58 [487,] 19.48 65 [488,] 19.52 55 [489,] 19.56 39 [490,] 19.60 69 [491,] 19.64 55 [492,] 19.68 60 [493,] 19.72 52 [494,] 19.76 49 [495,] 19.80 59 [496,] 19.84 57 [497,] 19.88 47 [498,] 19.92 59 [499,] 19.96 48 [500,] 20.00 51 [501,] 20.04 49 [502,] 20.08 48 [503,] 20.12 53 [504,] 20.16 63 [505,] 20.20 68 [506,] 20.24 62 [507,] 20.28 65 [508,] 20.32 60 [509,] 20.36 54 [510,] 20.40 40 [511,] 20.44 40 [512,] 20.48 42 [513,] 20.52 47 [514,] 20.56 55 [515,] 20.60 51 [516,] 20.64 67 [517,] 20.68 42 [518,] 20.72 47 [519,] 20.76 52 [520,] 20.80 55 [521,] 20.84 58 [522,] 20.88 50 [523,] 20.92 50 [524,] 20.96 46 [525,] 21.00 54 [526,] 21.04 64 [527,] 21.08 50 [528,] 21.12 36 [529,] 21.16 62 [530,] 21.20 57 [531,] 21.24 65 [532,] 21.28 43 [533,] 21.32 39 [534,] 21.36 57 [535,] 21.40 40 [536,] 21.44 53 [537,] 21.48 66 [538,] 21.52 46 [539,] 21.56 65 [540,] 21.60 53 [541,] 21.64 46 [542,] 21.68 43 [543,] 21.72 57 [544,] 21.76 54 [545,] 21.80 61 [546,] 21.84 36 [547,] 21.88 67 [548,] 21.92 44 [549,] 21.96 41 [550,] 22.00 68 [551,] 22.04 67 [552,] 22.08 69 [553,] 22.12 60 [554,] 22.16 57 [555,] 22.20 50 [556,] 22.24 55 [557,] 22.28 51 [558,] 22.32 66 [559,] 22.36 33 [560,] 22.40 76 [561,] 22.44 47 [562,] 22.48 42 [563,] 22.52 53 [564,] 22.56 58 [565,] 22.60 44 [566,] 22.64 52 [567,] 22.68 45 [568,] 22.72 58 [569,] 22.76 57 [570,] 22.80 49 [571,] 22.84 42 [572,] 22.88 47 [573,] 22.92 64 [574,] 22.96 35 [575,] 23.00 48 [576,] 23.04 54 [577,] 23.08 35 [578,] 23.12 44 [579,] 23.16 40 [580,] 23.20 42 [581,] 23.24 56 [582,] 23.28 56 [583,] 23.32 73 [584,] 23.36 53 [585,] 23.40 37 [586,] 23.44 49 [587,] 23.48 45 [588,] 23.52 64 [589,] 23.56 56 [590,] 23.60 47 [591,] 23.64 48 [592,] 23.68 47 [593,] 23.72 51 [594,] 23.76 74 [595,] 23.80 43 [596,] 23.84 56 [597,] 23.88 47 [598,] 23.92 58 [599,] 23.96 57 [600,] 24.00 52 [601,] 24.04 34 [602,] 24.08 47 [603,] 24.12 66 [604,] 24.16 40 [605,] 24.20 56 [606,] 24.24 56 [607,] 24.28 44 [608,] 24.32 51 [609,] 24.36 62 [610,] 24.40 45 [611,] 24.44 46 [612,] 24.48 43 [613,] 24.52 57 [614,] 24.56 39 [615,] 24.60 46 [616,] 24.64 58 [617,] 24.68 49 [618,] 24.72 46 [619,] 24.76 52 [620,] 24.80 40 [621,] 24.84 49 [622,] 24.88 57 [623,] 24.92 46 [624,] 24.96 59 [625,] 25.00 60 [626,] 25.04 37 [627,] 25.08 62 [628,] 25.12 54 [629,] 25.16 53 [630,] 25.20 57 [631,] 25.24 41 [632,] 25.28 52 [633,] 25.32 73 [634,] 25.36 52 [635,] 25.40 71 [636,] 25.44 62 [637,] 25.48 55 [638,] 25.52 51 [639,] 25.56 41 [640,] 25.60 62 [641,] 25.64 59 [642,] 25.68 48 [643,] 25.72 64 [644,] 25.76 54 [645,] 25.80 51 [646,] 25.84 50 [647,] 25.88 48 [648,] 25.92 45 [649,] 25.96 53 [650,] 26.00 61 [651,] 26.04 39 [652,] 26.08 49 [653,] 26.12 56 [654,] 26.16 60 [655,] 26.20 51 [656,] 26.24 40 [657,] 26.28 45 [658,] 26.32 60 [659,] 26.36 34 [660,] 26.40 53 [661,] 26.44 39 [662,] 26.48 48 [663,] 26.52 39 [664,] 26.56 57 [665,] 26.60 55 [666,] 26.64 46 [667,] 26.68 50 [668,] 26.72 46 [669,] 26.76 50 [670,] 26.80 59 [671,] 26.84 55 [672,] 26.88 40 [673,] 26.92 55 [674,] 26.96 57 [675,] 27.00 31 [676,] 27.04 38 [677,] 27.08 61 [678,] 27.12 49 [679,] 27.16 50 [680,] 27.20 40 [681,] 27.24 52 [682,] 27.28 51 [683,] 27.32 65 [684,] 27.36 46 [685,] 27.40 57 [686,] 27.44 46 [687,] 27.48 47 [688,] 27.52 58 [689,] 27.56 58 [690,] 27.60 55 [691,] 27.64 43 [692,] 27.68 54 [693,] 27.72 47 [694,] 27.76 50 [695,] 27.80 50 [696,] 27.84 51 [697,] 27.88 42 [698,] 27.92 60 [699,] 27.96 60 [700,] 28.00 68 [701,] 28.04 49 [702,] 28.08 42 [703,] 28.12 58 [704,] 28.16 56 [705,] 28.20 41 [706,] 28.24 43 [707,] 28.28 45 [708,] 28.32 53 [709,] 28.36 61 [710,] 28.40 54 [711,] 28.44 57 [712,] 28.48 47 [713,] 28.52 65 [714,] 28.56 65 [715,] 28.60 60 [716,] 28.64 34 [717,] 28.68 64 [718,] 28.72 54 [719,] 28.76 58 [720,] 28.80 68 [721,] 28.84 43 [722,] 28.88 45 [723,] 28.92 44 [724,] 28.96 57 [725,] 29.00 57 [726,] 29.04 55 [727,] 29.08 44 [728,] 29.12 53 [729,] 29.16 40 [730,] 29.20 54 [731,] 29.24 40 [732,] 29.28 54 [733,] 29.32 47 [734,] 29.36 49 [735,] 29.40 40 [736,] 29.44 60 [737,] 29.48 51 [738,] 29.52 43 [739,] 29.56 60 [740,] 29.60 55 [741,] 29.64 35 [742,] 29.68 38 [743,] 29.72 44 [744,] 29.76 38 [745,] 29.80 47 [746,] 29.84 63 [747,] 29.88 58 [748,] 29.92 49 [749,] 29.96 55 [750,] 30.00 60 [751,] 30.04 58 [752,] 30.08 53 [753,] 30.12 67 [754,] 30.16 55 [755,] 30.20 62 [756,] 30.24 52 [757,] 30.28 56 [758,] 30.32 70 [759,] 30.36 58 [760,] 30.40 44 [761,] 30.44 55 [762,] 30.48 53 [763,] 30.52 55 [764,] 30.56 50 [765,] 30.60 67 [766,] 30.64 40 [767,] 30.68 48 [768,] 30.72 76 [769,] 30.76 55 [770,] 30.80 49 [771,] 30.84 44 [772,] 30.88 55 [773,] 30.92 47 [774,] 30.96 48 [775,] 31.00 49 [776,] 31.04 50 [777,] 31.08 65 [778,] 31.12 67 [779,] 31.16 55 [780,] 31.20 50 [781,] 31.24 42 [782,] 31.28 56 [783,] 31.32 52 [784,] 31.36 36 [785,] 31.40 41 [786,] 31.44 53 [787,] 31.48 58 [788,] 31.52 32 [789,] 31.56 34 [790,] 31.60 46 [791,] 31.64 68 [792,] 31.68 49 [793,] 31.72 48 [794,] 31.76 36 [795,] 31.80 39 [796,] 31.84 60 [797,] 31.88 59 [798,] 31.92 57 [799,] 31.96 42 [800,] 32.00 43 [801,] 32.04 39 [802,] 32.08 52 [803,] 32.12 63 [804,] 32.16 53 [805,] 32.20 47 [806,] 32.24 51 [807,] 32.28 36 [808,] 32.32 33 [809,] 32.36 70 [810,] 32.40 44 [811,] 32.44 59 [812,] 32.48 54 [813,] 32.52 37 [814,] 32.56 48 [815,] 32.60 40 [816,] 32.64 32 [817,] 32.68 35 [818,] 32.72 53 [819,] 32.76 52 [820,] 32.80 44 [821,] 32.84 47 [822,] 32.88 41 [823,] 32.92 49 [824,] 32.96 33 [825,] 33.00 35 [826,] 33.04 44 [827,] 33.08 50 [828,] 33.12 49 [829,] 33.16 45 [830,] 33.20 33 [831,] 33.24 54 [832,] 33.28 60 [833,] 33.32 71 [834,] 33.36 47 [835,] 33.40 46 [836,] 33.44 67 [837,] 33.48 62 [838,] 33.52 46 [839,] 33.56 53 [840,] 33.60 48 [841,] 33.64 64 [842,] 33.68 40 [843,] 33.72 48 [844,] 33.76 55 [845,] 33.80 50 [846,] 33.84 48 [847,] 33.88 52 [848,] 33.92 45 [849,] 33.96 45 [850,] 34.00 51 [851,] 34.04 33 [852,] 34.08 37 [853,] 34.12 45 [854,] 34.16 53 [855,] 34.20 59 [856,] 34.24 49 [857,] 34.28 52 [858,] 34.32 40 [859,] 34.36 43 [860,] 34.40 66 [861,] 34.44 50 [862,] 34.48 42 [863,] 34.52 52 [864,] 34.56 32 [865,] 34.60 34 [866,] 34.64 31 [867,] 34.68 61 [868,] 34.72 51 [869,] 34.76 44 [870,] 34.80 44 [871,] 34.84 56 [872,] 34.88 40 [873,] 34.92 48 [874,] 34.96 52 [875,] 35.00 35 [876,] 35.04 41 [877,] 35.08 31 [878,] 35.12 48 [879,] 35.16 48 [880,] 35.20 46 [881,] 35.24 38 [882,] 35.28 60 [883,] 35.32 50 [884,] 35.36 42 [885,] 35.40 62 [886,] 35.44 42 [887,] 35.48 56 [888,] 35.52 47 [889,] 35.56 44 [890,] 35.60 40 [891,] 35.64 42 [892,] 35.68 53 [893,] 35.72 59 [894,] 35.76 52 [895,] 35.80 71 [896,] 35.84 42 [897,] 35.88 32 [898,] 35.92 46 [899,] 35.96 57 [900,] 36.00 48 [901,] 36.04 60 [902,] 36.08 54 [903,] 36.12 54 [904,] 36.16 40 [905,] 36.20 48 [906,] 36.24 36 [907,] 36.28 69 [908,] 36.32 49 [909,] 36.36 58 [910,] 36.40 57 [911,] 36.44 42 [912,] 36.48 52 [913,] 36.52 56 [914,] 36.56 40 [915,] 36.60 71 [916,] 36.64 47 [917,] 36.68 51 [918,] 36.72 66 [919,] 36.76 48 [920,] 36.80 45 [921,] 36.84 37 [922,] 36.88 65 [923,] 36.92 46 [924,] 36.96 48 [925,] 37.00 37 [926,] 37.04 43 [927,] 37.08 52 [928,] 37.12 40 [929,] 37.16 65 [930,] 37.20 47 [931,] 37.24 50 [932,] 37.28 38 [933,] 37.32 38 [934,] 37.36 44 [935,] 37.40 53 [936,] 37.44 47 [937,] 37.48 44 [938,] 37.52 47 [939,] 37.56 36 [940,] 37.60 51 [941,] 37.64 49 [942,] 37.68 51 [943,] 37.72 34 [944,] 37.76 52 [945,] 37.80 40 [946,] 37.84 46 [947,] 37.88 58 [948,] 37.92 41 [949,] 37.96 52 [950,] 38.00 42 [951,] 38.04 46 [952,] 38.08 49 [953,] 38.12 51 [954,] 38.16 38 [955,] 38.20 40 [956,] 38.24 46 [957,] 38.28 45 [958,] 38.32 61 [959,] 38.36 51 [960,] 38.40 46 [961,] 38.44 49 [962,] 38.48 57 [963,] 38.52 42 [964,] 38.56 57 [965,] 38.60 62 [966,] 38.64 44 [967,] 38.68 42 [968,] 38.72 44 [969,] 38.76 51 [970,] 38.80 38 [971,] 38.84 44 [972,] 38.88 39 [973,] 38.92 41 [974,] 38.96 48 [975,] 39.00 61 [976,] 39.04 47 [977,] 39.08 51 [978,] 39.12 38 [979,] 39.16 65 [980,] 39.20 39 [981,] 39.24 48 [982,] 39.28 45 [983,] 39.32 64 [984,] 39.36 44 [985,] 39.40 33 [986,] 39.44 45 [987,] 39.48 42 [988,] 39.52 36 [989,] 39.56 43 [990,] 39.60 48 [991,] 39.64 44 [992,] 39.68 67 [993,] 39.72 38 [994,] 39.76 47 [995,] 39.80 57 [996,] 39.84 40 [997,] 39.88 55 [998,] 39.92 49 [999,] 39.96 36 [1000,] 40.00 60 $`11_TL (PMT)` [,1] [,2] [1,] 0.64 4 [2,] 1.28 9 [3,] 1.92 0 [4,] 2.56 4 [5,] 3.20 5 [6,] 3.84 7 [7,] 4.48 3 [8,] 5.12 3 [9,] 5.76 4 [10,] 6.40 8 [11,] 7.04 1 [12,] 7.68 3 [13,] 8.32 6 [14,] 8.96 0 [15,] 9.60 7 [16,] 10.24 10 [17,] 10.88 2 [18,] 11.52 3 [19,] 12.16 8 [20,] 12.80 7 [21,] 13.44 2 [22,] 14.08 3 [23,] 14.72 7 [24,] 15.36 3 [25,] 16.00 1 [26,] 16.64 4 [27,] 17.28 5 [28,] 17.92 5 [29,] 18.56 4 [30,] 19.20 10 [31,] 19.84 9 [32,] 20.48 0 [33,] 21.12 2 [34,] 21.76 6 [35,] 22.40 12 [36,] 23.04 6 [37,] 23.68 1 [38,] 24.32 0 [39,] 24.96 0 [40,] 25.60 4 [41,] 26.24 1 [42,] 26.88 4 [43,] 27.52 1 [44,] 28.16 1 [45,] 28.80 3 [46,] 29.44 7 [47,] 30.08 1 [48,] 30.72 21 [49,] 31.36 2 [50,] 32.00 3 [51,] 32.64 4 [52,] 33.28 6 [53,] 33.92 4 [54,] 34.56 6 [55,] 35.20 5 [56,] 35.84 3 [57,] 36.48 12 [58,] 37.12 5 [59,] 37.76 3 [60,] 38.40 9 [61,] 39.04 3 [62,] 39.68 9 [63,] 40.32 11 [64,] 40.96 13 [65,] 41.60 3 [66,] 42.24 4 [67,] 42.88 3 [68,] 43.52 3 [69,] 44.16 4 [70,] 44.80 4 [71,] 45.44 14 [72,] 46.08 5 [73,] 46.72 2 [74,] 47.36 2 [75,] 48.00 2 [76,] 48.64 0 [77,] 49.28 7 [78,] 49.92 9 [79,] 50.56 4 [80,] 51.20 2 [81,] 51.84 9 [82,] 52.48 10 [83,] 53.12 6 [84,] 53.76 5 [85,] 54.40 5 [86,] 55.04 11 [87,] 55.68 13 [88,] 56.32 11 [89,] 56.96 4 [90,] 57.60 13 [91,] 58.24 6 [92,] 58.88 9 [93,] 59.52 10 [94,] 60.16 9 [95,] 60.80 11 [96,] 61.44 16 [97,] 62.08 4 [98,] 62.72 16 [99,] 63.36 18 [100,] 64.00 17 [101,] 64.64 14 [102,] 65.28 18 [103,] 65.92 27 [104,] 66.56 15 [105,] 67.20 22 [106,] 67.84 18 [107,] 68.48 26 [108,] 69.12 22 [109,] 69.76 26 [110,] 70.40 21 [111,] 71.04 29 [112,] 71.68 31 [113,] 72.32 40 [114,] 72.96 19 [115,] 73.60 41 [116,] 74.24 33 [117,] 74.88 43 [118,] 75.52 35 [119,] 76.16 35 [120,] 76.80 45 [121,] 77.44 41 [122,] 78.08 38 [123,] 78.72 59 [124,] 79.36 47 [125,] 80.00 50 [126,] 80.64 70 [127,] 81.28 47 [128,] 81.92 64 [129,] 82.56 62 [130,] 83.20 85 [131,] 83.84 84 [132,] 84.48 98 [133,] 85.12 82 [134,] 85.76 107 [135,] 86.40 86 [136,] 87.04 89 [137,] 87.68 96 [138,] 88.32 105 [139,] 88.96 132 [140,] 89.60 118 [141,] 90.24 145 [142,] 90.88 116 [143,] 91.52 150 [144,] 92.16 142 [145,] 92.80 157 [146,] 93.44 168 [147,] 94.08 151 [148,] 94.72 179 [149,] 95.36 165 [150,] 96.00 169 [151,] 96.64 152 [152,] 97.28 190 [153,] 97.92 236 [154,] 98.56 198 [155,] 99.20 213 [156,] 99.84 233 [157,] 100.48 204 [158,] 101.12 227 [159,] 101.76 228 [160,] 102.40 255 [161,] 103.04 231 [162,] 103.68 232 [163,] 104.32 232 [164,] 104.96 268 [165,] 105.60 255 [166,] 106.24 217 [167,] 106.88 219 [168,] 107.52 242 [169,] 108.16 229 [170,] 108.80 265 [171,] 109.44 210 [172,] 110.08 251 [173,] 110.72 199 [174,] 111.36 208 [175,] 112.00 242 [176,] 112.64 226 [177,] 113.28 217 [178,] 113.92 203 [179,] 114.56 162 [180,] 115.20 207 [181,] 115.84 179 [182,] 116.48 177 [183,] 117.12 147 [184,] 117.76 147 [185,] 118.40 164 [186,] 119.04 120 [187,] 119.68 128 [188,] 120.32 141 [189,] 120.96 117 [190,] 121.60 124 [191,] 122.24 116 [192,] 122.88 93 [193,] 123.52 91 [194,] 124.16 73 [195,] 124.80 61 [196,] 125.44 92 [197,] 126.08 77 [198,] 126.72 68 [199,] 127.36 77 [200,] 128.00 59 [201,] 128.64 74 [202,] 129.28 73 [203,] 129.92 75 [204,] 130.56 103 [205,] 131.20 69 [206,] 131.84 87 [207,] 132.48 66 [208,] 133.12 78 [209,] 133.76 68 [210,] 134.40 76 [211,] 135.04 56 [212,] 135.68 88 [213,] 136.32 77 [214,] 136.96 76 [215,] 137.60 76 [216,] 138.24 99 [217,] 138.88 82 [218,] 139.52 83 [219,] 140.16 69 [220,] 140.80 73 [221,] 141.44 78 [222,] 142.08 58 [223,] 142.72 91 [224,] 143.36 62 [225,] 144.00 110 [226,] 144.64 81 [227,] 145.28 74 [228,] 145.92 62 [229,] 146.56 71 [230,] 147.20 65 [231,] 147.84 79 [232,] 148.48 68 [233,] 149.12 101 [234,] 149.76 73 [235,] 150.40 69 [236,] 151.04 70 [237,] 151.68 85 [238,] 152.32 66 [239,] 152.96 62 [240,] 153.60 78 [241,] 154.24 85 [242,] 154.88 58 [243,] 155.52 70 [244,] 156.16 85 [245,] 156.80 74 [246,] 157.44 60 [247,] 158.08 67 [248,] 158.72 85 [249,] 159.36 60 [250,] 160.00 64 $`12_OSL (PMT)` [,1] [,2] [1,] 0.04 2656 [2,] 0.08 2304 [3,] 0.12 2055 [4,] 0.16 1796 [5,] 0.20 1505 [6,] 0.24 1379 [7,] 0.28 1219 [8,] 0.32 1047 [9,] 0.36 973 [10,] 0.40 869 [11,] 0.44 711 [12,] 0.48 638 [13,] 0.52 630 [14,] 0.56 559 [15,] 0.60 454 [16,] 0.64 491 [17,] 0.68 431 [18,] 0.72 370 [19,] 0.76 351 [20,] 0.80 287 [21,] 0.84 258 [22,] 0.88 301 [23,] 0.92 247 [24,] 0.96 229 [25,] 1.00 236 [26,] 1.04 197 [27,] 1.08 191 [28,] 1.12 202 [29,] 1.16 192 [30,] 1.20 154 [31,] 1.24 172 [32,] 1.28 156 [33,] 1.32 171 [34,] 1.36 142 [35,] 1.40 126 [36,] 1.44 130 [37,] 1.48 128 [38,] 1.52 161 [39,] 1.56 147 [40,] 1.60 137 [41,] 1.64 129 [42,] 1.68 132 [43,] 1.72 133 [44,] 1.76 113 [45,] 1.80 114 [46,] 1.84 126 [47,] 1.88 109 [48,] 1.92 102 [49,] 1.96 127 [50,] 2.00 139 [51,] 2.04 146 [52,] 2.08 99 [53,] 2.12 97 [54,] 2.16 120 [55,] 2.20 111 [56,] 2.24 108 [57,] 2.28 110 [58,] 2.32 96 [59,] 2.36 88 [60,] 2.40 96 [61,] 2.44 88 [62,] 2.48 86 [63,] 2.52 90 [64,] 2.56 101 [65,] 2.60 106 [66,] 2.64 111 [67,] 2.68 96 [68,] 2.72 108 [69,] 2.76 93 [70,] 2.80 97 [71,] 2.84 107 [72,] 2.88 105 [73,] 2.92 110 [74,] 2.96 107 [75,] 3.00 94 [76,] 3.04 105 [77,] 3.08 106 [78,] 3.12 113 [79,] 3.16 102 [80,] 3.20 79 [81,] 3.24 62 [82,] 3.28 86 [83,] 3.32 98 [84,] 3.36 105 [85,] 3.40 85 [86,] 3.44 98 [87,] 3.48 98 [88,] 3.52 81 [89,] 3.56 81 [90,] 3.60 75 [91,] 3.64 98 [92,] 3.68 90 [93,] 3.72 70 [94,] 3.76 69 [95,] 3.80 92 [96,] 3.84 93 [97,] 3.88 107 [98,] 3.92 95 [99,] 3.96 110 [100,] 4.00 95 [101,] 4.04 80 [102,] 4.08 90 [103,] 4.12 77 [104,] 4.16 82 [105,] 4.20 70 [106,] 4.24 79 [107,] 4.28 78 [108,] 4.32 71 [109,] 4.36 91 [110,] 4.40 78 [111,] 4.44 76 [112,] 4.48 64 [113,] 4.52 76 [114,] 4.56 76 [115,] 4.60 86 [116,] 4.64 93 [117,] 4.68 91 [118,] 4.72 84 [119,] 4.76 78 [120,] 4.80 65 [121,] 4.84 86 [122,] 4.88 72 [123,] 4.92 79 [124,] 4.96 94 [125,] 5.00 59 [126,] 5.04 77 [127,] 5.08 70 [128,] 5.12 84 [129,] 5.16 76 [130,] 5.20 86 [131,] 5.24 87 [132,] 5.28 75 [133,] 5.32 81 [134,] 5.36 83 [135,] 5.40 68 [136,] 5.44 82 [137,] 5.48 80 [138,] 5.52 83 [139,] 5.56 43 [140,] 5.60 80 [141,] 5.64 77 [142,] 5.68 69 [143,] 5.72 98 [144,] 5.76 72 [145,] 5.80 82 [146,] 5.84 91 [147,] 5.88 85 [148,] 5.92 66 [149,] 5.96 76 [150,] 6.00 57 [151,] 6.04 80 [152,] 6.08 70 [153,] 6.12 60 [154,] 6.16 67 [155,] 6.20 59 [156,] 6.24 74 [157,] 6.28 68 [158,] 6.32 75 [159,] 6.36 89 [160,] 6.40 82 [161,] 6.44 66 [162,] 6.48 67 [163,] 6.52 84 [164,] 6.56 83 [165,] 6.60 73 [166,] 6.64 99 [167,] 6.68 72 [168,] 6.72 70 [169,] 6.76 78 [170,] 6.80 55 [171,] 6.84 88 [172,] 6.88 48 [173,] 6.92 69 [174,] 6.96 73 [175,] 7.00 66 [176,] 7.04 77 [177,] 7.08 83 [178,] 7.12 78 [179,] 7.16 72 [180,] 7.20 73 [181,] 7.24 72 [182,] 7.28 78 [183,] 7.32 64 [184,] 7.36 72 [185,] 7.40 71 [186,] 7.44 78 [187,] 7.48 66 [188,] 7.52 66 [189,] 7.56 65 [190,] 7.60 67 [191,] 7.64 78 [192,] 7.68 77 [193,] 7.72 67 [194,] 7.76 79 [195,] 7.80 72 [196,] 7.84 73 [197,] 7.88 69 [198,] 7.92 61 [199,] 7.96 58 [200,] 8.00 69 [201,] 8.04 63 [202,] 8.08 69 [203,] 8.12 63 [204,] 8.16 56 [205,] 8.20 76 [206,] 8.24 74 [207,] 8.28 65 [208,] 8.32 70 [209,] 8.36 89 [210,] 8.40 72 [211,] 8.44 81 [212,] 8.48 60 [213,] 8.52 78 [214,] 8.56 61 [215,] 8.60 65 [216,] 8.64 68 [217,] 8.68 86 [218,] 8.72 79 [219,] 8.76 72 [220,] 8.80 63 [221,] 8.84 73 [222,] 8.88 85 [223,] 8.92 60 [224,] 8.96 65 [225,] 9.00 69 [226,] 9.04 76 [227,] 9.08 73 [228,] 9.12 56 [229,] 9.16 87 [230,] 9.20 69 [231,] 9.24 60 [232,] 9.28 72 [233,] 9.32 62 [234,] 9.36 86 [235,] 9.40 58 [236,] 9.44 64 [237,] 9.48 71 [238,] 9.52 53 [239,] 9.56 75 [240,] 9.60 41 [241,] 9.64 58 [242,] 9.68 67 [243,] 9.72 52 [244,] 9.76 53 [245,] 9.80 73 [246,] 9.84 61 [247,] 9.88 71 [248,] 9.92 64 [249,] 9.96 74 [250,] 10.00 64 [251,] 10.04 85 [252,] 10.08 63 [253,] 10.12 66 [254,] 10.16 73 [255,] 10.20 65 [256,] 10.24 67 [257,] 10.28 67 [258,] 10.32 63 [259,] 10.36 75 [260,] 10.40 60 [261,] 10.44 57 [262,] 10.48 83 [263,] 10.52 88 [264,] 10.56 57 [265,] 10.60 49 [266,] 10.64 49 [267,] 10.68 63 [268,] 10.72 55 [269,] 10.76 60 [270,] 10.80 71 [271,] 10.84 61 [272,] 10.88 61 [273,] 10.92 65 [274,] 10.96 45 [275,] 11.00 65 [276,] 11.04 63 [277,] 11.08 64 [278,] 11.12 64 [279,] 11.16 70 [280,] 11.20 51 [281,] 11.24 73 [282,] 11.28 49 [283,] 11.32 64 [284,] 11.36 75 [285,] 11.40 38 [286,] 11.44 58 [287,] 11.48 55 [288,] 11.52 70 [289,] 11.56 46 [290,] 11.60 61 [291,] 11.64 58 [292,] 11.68 54 [293,] 11.72 69 [294,] 11.76 47 [295,] 11.80 57 [296,] 11.84 51 [297,] 11.88 58 [298,] 11.92 53 [299,] 11.96 68 [300,] 12.00 61 [301,] 12.04 61 [302,] 12.08 60 [303,] 12.12 45 [304,] 12.16 72 [305,] 12.20 46 [306,] 12.24 54 [307,] 12.28 65 [308,] 12.32 74 [309,] 12.36 53 [310,] 12.40 57 [311,] 12.44 67 [312,] 12.48 57 [313,] 12.52 88 [314,] 12.56 53 [315,] 12.60 56 [316,] 12.64 70 [317,] 12.68 67 [318,] 12.72 63 [319,] 12.76 60 [320,] 12.80 67 [321,] 12.84 62 [322,] 12.88 55 [323,] 12.92 77 [324,] 12.96 63 [325,] 13.00 50 [326,] 13.04 66 [327,] 13.08 69 [328,] 13.12 70 [329,] 13.16 83 [330,] 13.20 63 [331,] 13.24 67 [332,] 13.28 51 [333,] 13.32 52 [334,] 13.36 78 [335,] 13.40 60 [336,] 13.44 68 [337,] 13.48 49 [338,] 13.52 64 [339,] 13.56 58 [340,] 13.60 68 [341,] 13.64 69 [342,] 13.68 60 [343,] 13.72 52 [344,] 13.76 52 [345,] 13.80 70 [346,] 13.84 57 [347,] 13.88 61 [348,] 13.92 56 [349,] 13.96 54 [350,] 14.00 64 [351,] 14.04 66 [352,] 14.08 55 [353,] 14.12 57 [354,] 14.16 65 [355,] 14.20 83 [356,] 14.24 56 [357,] 14.28 54 [358,] 14.32 58 [359,] 14.36 70 [360,] 14.40 44 [361,] 14.44 67 [362,] 14.48 61 [363,] 14.52 53 [364,] 14.56 76 [365,] 14.60 58 [366,] 14.64 56 [367,] 14.68 60 [368,] 14.72 56 [369,] 14.76 66 [370,] 14.80 67 [371,] 14.84 48 [372,] 14.88 68 [373,] 14.92 53 [374,] 14.96 59 [375,] 15.00 59 [376,] 15.04 66 [377,] 15.08 68 [378,] 15.12 73 [379,] 15.16 63 [380,] 15.20 55 [381,] 15.24 68 [382,] 15.28 59 [383,] 15.32 48 [384,] 15.36 94 [385,] 15.40 57 [386,] 15.44 71 [387,] 15.48 56 [388,] 15.52 56 [389,] 15.56 53 [390,] 15.60 67 [391,] 15.64 58 [392,] 15.68 68 [393,] 15.72 66 [394,] 15.76 53 [395,] 15.80 58 [396,] 15.84 63 [397,] 15.88 76 [398,] 15.92 42 [399,] 15.96 66 [400,] 16.00 76 [401,] 16.04 62 [402,] 16.08 63 [403,] 16.12 38 [404,] 16.16 63 [405,] 16.20 68 [406,] 16.24 60 [407,] 16.28 48 [408,] 16.32 58 [409,] 16.36 60 [410,] 16.40 67 [411,] 16.44 58 [412,] 16.48 72 [413,] 16.52 39 [414,] 16.56 45 [415,] 16.60 38 [416,] 16.64 67 [417,] 16.68 50 [418,] 16.72 73 [419,] 16.76 73 [420,] 16.80 61 [421,] 16.84 70 [422,] 16.88 60 [423,] 16.92 55 [424,] 16.96 66 [425,] 17.00 65 [426,] 17.04 60 [427,] 17.08 54 [428,] 17.12 53 [429,] 17.16 70 [430,] 17.20 39 [431,] 17.24 55 [432,] 17.28 69 [433,] 17.32 54 [434,] 17.36 65 [435,] 17.40 80 [436,] 17.44 39 [437,] 17.48 63 [438,] 17.52 64 [439,] 17.56 66 [440,] 17.60 60 [441,] 17.64 62 [442,] 17.68 50 [443,] 17.72 57 [444,] 17.76 56 [445,] 17.80 54 [446,] 17.84 48 [447,] 17.88 52 [448,] 17.92 42 [449,] 17.96 60 [450,] 18.00 56 [451,] 18.04 47 [452,] 18.08 56 [453,] 18.12 63 [454,] 18.16 66 [455,] 18.20 48 [456,] 18.24 58 [457,] 18.28 62 [458,] 18.32 54 [459,] 18.36 55 [460,] 18.40 64 [461,] 18.44 37 [462,] 18.48 72 [463,] 18.52 49 [464,] 18.56 44 [465,] 18.60 72 [466,] 18.64 44 [467,] 18.68 66 [468,] 18.72 60 [469,] 18.76 69 [470,] 18.80 55 [471,] 18.84 59 [472,] 18.88 52 [473,] 18.92 69 [474,] 18.96 47 [475,] 19.00 36 [476,] 19.04 40 [477,] 19.08 61 [478,] 19.12 52 [479,] 19.16 58 [480,] 19.20 56 [481,] 19.24 54 [482,] 19.28 48 [483,] 19.32 67 [484,] 19.36 68 [485,] 19.40 85 [486,] 19.44 58 [487,] 19.48 55 [488,] 19.52 69 [489,] 19.56 58 [490,] 19.60 50 [491,] 19.64 44 [492,] 19.68 43 [493,] 19.72 56 [494,] 19.76 63 [495,] 19.80 47 [496,] 19.84 65 [497,] 19.88 59 [498,] 19.92 51 [499,] 19.96 29 [500,] 20.00 54 [501,] 20.04 65 [502,] 20.08 74 [503,] 20.12 63 [504,] 20.16 58 [505,] 20.20 34 [506,] 20.24 51 [507,] 20.28 57 [508,] 20.32 44 [509,] 20.36 53 [510,] 20.40 66 [511,] 20.44 46 [512,] 20.48 67 [513,] 20.52 59 [514,] 20.56 51 [515,] 20.60 54 [516,] 20.64 54 [517,] 20.68 60 [518,] 20.72 58 [519,] 20.76 66 [520,] 20.80 64 [521,] 20.84 72 [522,] 20.88 33 [523,] 20.92 53 [524,] 20.96 52 [525,] 21.00 63 [526,] 21.04 58 [527,] 21.08 46 [528,] 21.12 47 [529,] 21.16 65 [530,] 21.20 68 [531,] 21.24 40 [532,] 21.28 51 [533,] 21.32 54 [534,] 21.36 41 [535,] 21.40 55 [536,] 21.44 54 [537,] 21.48 63 [538,] 21.52 81 [539,] 21.56 50 [540,] 21.60 55 [541,] 21.64 83 [542,] 21.68 68 [543,] 21.72 51 [544,] 21.76 52 [545,] 21.80 65 [546,] 21.84 66 [547,] 21.88 45 [548,] 21.92 57 [549,] 21.96 67 [550,] 22.00 58 [551,] 22.04 57 [552,] 22.08 59 [553,] 22.12 56 [554,] 22.16 58 [555,] 22.20 47 [556,] 22.24 56 [557,] 22.28 50 [558,] 22.32 56 [559,] 22.36 45 [560,] 22.40 67 [561,] 22.44 51 [562,] 22.48 57 [563,] 22.52 58 [564,] 22.56 45 [565,] 22.60 37 [566,] 22.64 59 [567,] 22.68 68 [568,] 22.72 54 [569,] 22.76 56 [570,] 22.80 66 [571,] 22.84 49 [572,] 22.88 64 [573,] 22.92 64 [574,] 22.96 45 [575,] 23.00 77 [576,] 23.04 58 [577,] 23.08 37 [578,] 23.12 48 [579,] 23.16 67 [580,] 23.20 69 [581,] 23.24 65 [582,] 23.28 44 [583,] 23.32 43 [584,] 23.36 55 [585,] 23.40 69 [586,] 23.44 54 [587,] 23.48 68 [588,] 23.52 45 [589,] 23.56 64 [590,] 23.60 64 [591,] 23.64 51 [592,] 23.68 70 [593,] 23.72 57 [594,] 23.76 44 [595,] 23.80 67 [596,] 23.84 62 [597,] 23.88 52 [598,] 23.92 51 [599,] 23.96 50 [600,] 24.00 65 [601,] 24.04 40 [602,] 24.08 60 [603,] 24.12 56 [604,] 24.16 50 [605,] 24.20 60 [606,] 24.24 59 [607,] 24.28 57 [608,] 24.32 52 [609,] 24.36 55 [610,] 24.40 56 [611,] 24.44 53 [612,] 24.48 65 [613,] 24.52 77 [614,] 24.56 60 [615,] 24.60 57 [616,] 24.64 61 [617,] 24.68 44 [618,] 24.72 54 [619,] 24.76 42 [620,] 24.80 53 [621,] 24.84 64 [622,] 24.88 35 [623,] 24.92 59 [624,] 24.96 61 [625,] 25.00 46 [626,] 25.04 58 [627,] 25.08 63 [628,] 25.12 55 [629,] 25.16 61 [630,] 25.20 62 [631,] 25.24 31 [632,] 25.28 67 [633,] 25.32 50 [634,] 25.36 40 [635,] 25.40 44 [636,] 25.44 47 [637,] 25.48 54 [638,] 25.52 65 [639,] 25.56 56 [640,] 25.60 63 [641,] 25.64 43 [642,] 25.68 57 [643,] 25.72 50 [644,] 25.76 49 [645,] 25.80 47 [646,] 25.84 41 [647,] 25.88 64 [648,] 25.92 45 [649,] 25.96 44 [650,] 26.00 71 [651,] 26.04 57 [652,] 26.08 76 [653,] 26.12 51 [654,] 26.16 49 [655,] 26.20 57 [656,] 26.24 53 [657,] 26.28 61 [658,] 26.32 47 [659,] 26.36 56 [660,] 26.40 43 [661,] 26.44 53 [662,] 26.48 43 [663,] 26.52 64 [664,] 26.56 63 [665,] 26.60 52 [666,] 26.64 47 [667,] 26.68 45 [668,] 26.72 45 [669,] 26.76 57 [670,] 26.80 58 [671,] 26.84 61 [672,] 26.88 45 [673,] 26.92 50 [674,] 26.96 49 [675,] 27.00 60 [676,] 27.04 55 [677,] 27.08 76 [678,] 27.12 50 [679,] 27.16 61 [680,] 27.20 49 [681,] 27.24 63 [682,] 27.28 50 [683,] 27.32 57 [684,] 27.36 63 [685,] 27.40 63 [686,] 27.44 37 [687,] 27.48 53 [688,] 27.52 49 [689,] 27.56 75 [690,] 27.60 43 [691,] 27.64 67 [692,] 27.68 54 [693,] 27.72 60 [694,] 27.76 43 [695,] 27.80 58 [696,] 27.84 44 [697,] 27.88 59 [698,] 27.92 70 [699,] 27.96 39 [700,] 28.00 55 [701,] 28.04 57 [702,] 28.08 52 [703,] 28.12 86 [704,] 28.16 53 [705,] 28.20 45 [706,] 28.24 56 [707,] 28.28 54 [708,] 28.32 62 [709,] 28.36 52 [710,] 28.40 51 [711,] 28.44 47 [712,] 28.48 50 [713,] 28.52 51 [714,] 28.56 44 [715,] 28.60 60 [716,] 28.64 51 [717,] 28.68 47 [718,] 28.72 46 [719,] 28.76 59 [720,] 28.80 43 [721,] 28.84 41 [722,] 28.88 69 [723,] 28.92 37 [724,] 28.96 55 [725,] 29.00 70 [726,] 29.04 49 [727,] 29.08 70 [728,] 29.12 53 [729,] 29.16 56 [730,] 29.20 55 [731,] 29.24 34 [732,] 29.28 62 [733,] 29.32 66 [734,] 29.36 47 [735,] 29.40 82 [736,] 29.44 37 [737,] 29.48 50 [738,] 29.52 63 [739,] 29.56 53 [740,] 29.60 62 [741,] 29.64 59 [742,] 29.68 41 [743,] 29.72 55 [744,] 29.76 52 [745,] 29.80 52 [746,] 29.84 55 [747,] 29.88 60 [748,] 29.92 49 [749,] 29.96 46 [750,] 30.00 55 [751,] 30.04 50 [752,] 30.08 58 [753,] 30.12 62 [754,] 30.16 51 [755,] 30.20 43 [756,] 30.24 43 [757,] 30.28 63 [758,] 30.32 33 [759,] 30.36 55 [760,] 30.40 57 [761,] 30.44 40 [762,] 30.48 66 [763,] 30.52 52 [764,] 30.56 51 [765,] 30.60 52 [766,] 30.64 54 [767,] 30.68 49 [768,] 30.72 41 [769,] 30.76 48 [770,] 30.80 50 [771,] 30.84 66 [772,] 30.88 48 [773,] 30.92 42 [774,] 30.96 40 [775,] 31.00 69 [776,] 31.04 49 [777,] 31.08 56 [778,] 31.12 45 [779,] 31.16 47 [780,] 31.20 43 [781,] 31.24 61 [782,] 31.28 57 [783,] 31.32 42 [784,] 31.36 74 [785,] 31.40 59 [786,] 31.44 64 [787,] 31.48 64 [788,] 31.52 48 [789,] 31.56 56 [790,] 31.60 67 [791,] 31.64 31 [792,] 31.68 43 [793,] 31.72 43 [794,] 31.76 43 [795,] 31.80 51 [796,] 31.84 44 [797,] 31.88 56 [798,] 31.92 69 [799,] 31.96 49 [800,] 32.00 36 [801,] 32.04 72 [802,] 32.08 46 [803,] 32.12 54 [804,] 32.16 63 [805,] 32.20 55 [806,] 32.24 57 [807,] 32.28 39 [808,] 32.32 71 [809,] 32.36 47 [810,] 32.40 69 [811,] 32.44 48 [812,] 32.48 71 [813,] 32.52 51 [814,] 32.56 60 [815,] 32.60 49 [816,] 32.64 58 [817,] 32.68 47 [818,] 32.72 51 [819,] 32.76 57 [820,] 32.80 41 [821,] 32.84 57 [822,] 32.88 62 [823,] 32.92 49 [824,] 32.96 64 [825,] 33.00 46 [826,] 33.04 54 [827,] 33.08 52 [828,] 33.12 54 [829,] 33.16 46 [830,] 33.20 67 [831,] 33.24 47 [832,] 33.28 50 [833,] 33.32 36 [834,] 33.36 45 [835,] 33.40 56 [836,] 33.44 42 [837,] 33.48 47 [838,] 33.52 51 [839,] 33.56 41 [840,] 33.60 57 [841,] 33.64 32 [842,] 33.68 62 [843,] 33.72 44 [844,] 33.76 46 [845,] 33.80 49 [846,] 33.84 52 [847,] 33.88 41 [848,] 33.92 52 [849,] 33.96 44 [850,] 34.00 60 [851,] 34.04 55 [852,] 34.08 56 [853,] 34.12 47 [854,] 34.16 43 [855,] 34.20 57 [856,] 34.24 62 [857,] 34.28 61 [858,] 34.32 48 [859,] 34.36 51 [860,] 34.40 63 [861,] 34.44 68 [862,] 34.48 49 [863,] 34.52 48 [864,] 34.56 65 [865,] 34.60 57 [866,] 34.64 51 [867,] 34.68 44 [868,] 34.72 49 [869,] 34.76 63 [870,] 34.80 58 [871,] 34.84 56 [872,] 34.88 70 [873,] 34.92 47 [874,] 34.96 42 [875,] 35.00 53 [876,] 35.04 41 [877,] 35.08 59 [878,] 35.12 42 [879,] 35.16 55 [880,] 35.20 53 [881,] 35.24 72 [882,] 35.28 59 [883,] 35.32 59 [884,] 35.36 40 [885,] 35.40 61 [886,] 35.44 38 [887,] 35.48 49 [888,] 35.52 55 [889,] 35.56 58 [890,] 35.60 69 [891,] 35.64 48 [892,] 35.68 44 [893,] 35.72 47 [894,] 35.76 56 [895,] 35.80 40 [896,] 35.84 49 [897,] 35.88 38 [898,] 35.92 57 [899,] 35.96 45 [900,] 36.00 39 [901,] 36.04 54 [902,] 36.08 35 [903,] 36.12 59 [904,] 36.16 34 [905,] 36.20 55 [906,] 36.24 45 [907,] 36.28 40 [908,] 36.32 58 [909,] 36.36 51 [910,] 36.40 57 [911,] 36.44 61 [912,] 36.48 44 [913,] 36.52 49 [914,] 36.56 61 [915,] 36.60 74 [916,] 36.64 61 [917,] 36.68 50 [918,] 36.72 63 [919,] 36.76 53 [920,] 36.80 68 [921,] 36.84 47 [922,] 36.88 62 [923,] 36.92 47 [924,] 36.96 61 [925,] 37.00 64 [926,] 37.04 57 [927,] 37.08 67 [928,] 37.12 49 [929,] 37.16 53 [930,] 37.20 41 [931,] 37.24 49 [932,] 37.28 41 [933,] 37.32 63 [934,] 37.36 55 [935,] 37.40 39 [936,] 37.44 45 [937,] 37.48 45 [938,] 37.52 60 [939,] 37.56 56 [940,] 37.60 43 [941,] 37.64 57 [942,] 37.68 41 [943,] 37.72 44 [944,] 37.76 38 [945,] 37.80 48 [946,] 37.84 74 [947,] 37.88 55 [948,] 37.92 38 [949,] 37.96 56 [950,] 38.00 52 [951,] 38.04 47 [952,] 38.08 58 [953,] 38.12 63 [954,] 38.16 49 [955,] 38.20 47 [956,] 38.24 37 [957,] 38.28 67 [958,] 38.32 51 [959,] 38.36 57 [960,] 38.40 63 [961,] 38.44 47 [962,] 38.48 35 [963,] 38.52 54 [964,] 38.56 53 [965,] 38.60 51 [966,] 38.64 48 [967,] 38.68 54 [968,] 38.72 38 [969,] 38.76 46 [970,] 38.80 62 [971,] 38.84 44 [972,] 38.88 50 [973,] 38.92 43 [974,] 38.96 52 [975,] 39.00 56 [976,] 39.04 41 [977,] 39.08 59 [978,] 39.12 57 [979,] 39.16 51 [980,] 39.20 33 [981,] 39.24 52 [982,] 39.28 63 [983,] 39.32 61 [984,] 39.36 43 [985,] 39.40 37 [986,] 39.44 43 [987,] 39.48 79 [988,] 39.52 54 [989,] 39.56 46 [990,] 39.60 40 [991,] 39.64 44 [992,] 39.68 34 [993,] 39.72 36 [994,] 39.76 49 [995,] 39.80 64 [996,] 39.84 42 [997,] 39.88 41 [998,] 39.92 48 [999,] 39.96 49 [1000,] 40.00 51 $`13_TL (PMT)` [,1] [,2] [1,] 0.884 11 [2,] 1.768 11 [3,] 2.652 2 [4,] 3.536 3 [5,] 4.420 4 [6,] 5.304 2 [7,] 6.188 9 [8,] 7.072 0 [9,] 7.956 12 [10,] 8.840 8 [11,] 9.724 2 [12,] 10.608 0 [13,] 11.492 4 [14,] 12.376 5 [15,] 13.260 0 [16,] 14.144 6 [17,] 15.028 10 [18,] 15.912 3 [19,] 16.796 5 [20,] 17.680 3 [21,] 18.564 6 [22,] 19.448 8 [23,] 20.332 4 [24,] 21.216 4 [25,] 22.100 5 [26,] 22.984 3 [27,] 23.868 0 [28,] 24.752 2 [29,] 25.636 2 [30,] 26.520 1 [31,] 27.404 6 [32,] 28.288 1 [33,] 29.172 2 [34,] 30.056 8 [35,] 30.940 4 [36,] 31.824 2 [37,] 32.708 8 [38,] 33.592 8 [39,] 34.476 8 [40,] 35.360 3 [41,] 36.244 3 [42,] 37.128 3 [43,] 38.012 5 [44,] 38.896 3 [45,] 39.780 6 [46,] 40.664 3 [47,] 41.548 10 [48,] 42.432 8 [49,] 43.316 1 [50,] 44.200 5 [51,] 45.084 8 [52,] 45.968 3 [53,] 46.852 5 [54,] 47.736 1 [55,] 48.620 11 [56,] 49.504 3 [57,] 50.388 2 [58,] 51.272 5 [59,] 52.156 5 [60,] 53.040 4 [61,] 53.924 3 [62,] 54.808 5 [63,] 55.692 2 [64,] 56.576 6 [65,] 57.460 3 [66,] 58.344 3 [67,] 59.228 6 [68,] 60.112 3 [69,] 60.996 8 [70,] 61.880 7 [71,] 62.764 6 [72,] 63.648 7 [73,] 64.532 4 [74,] 65.416 2 [75,] 66.300 8 [76,] 67.184 6 [77,] 68.068 0 [78,] 68.952 4 [79,] 69.836 5 [80,] 70.720 11 [81,] 71.604 7 [82,] 72.488 10 [83,] 73.372 12 [84,] 74.256 3 [85,] 75.140 15 [86,] 76.024 4 [87,] 76.908 10 [88,] 77.792 18 [89,] 78.676 15 [90,] 79.560 12 [91,] 80.444 13 [92,] 81.328 17 [93,] 82.212 7 [94,] 83.096 24 [95,] 83.980 9 [96,] 84.864 31 [97,] 85.748 16 [98,] 86.632 15 [99,] 87.516 27 [100,] 88.400 11 [101,] 89.284 24 [102,] 90.168 25 [103,] 91.052 22 [104,] 91.936 40 [105,] 92.820 27 [106,] 93.704 17 [107,] 94.588 35 [108,] 95.472 25 [109,] 96.356 56 [110,] 97.240 39 [111,] 98.124 50 [112,] 99.008 36 [113,] 99.892 72 [114,] 100.776 56 [115,] 101.660 42 [116,] 102.544 36 [117,] 103.428 65 [118,] 104.312 50 [119,] 105.196 64 [120,] 106.080 74 [121,] 106.964 92 [122,] 107.848 80 [123,] 108.732 81 [124,] 109.616 96 [125,] 110.500 108 [126,] 111.384 109 [127,] 112.268 114 [128,] 113.152 103 [129,] 114.036 134 [130,] 114.920 140 [131,] 115.804 149 [132,] 116.688 151 [133,] 117.572 162 [134,] 118.456 163 [135,] 119.340 201 [136,] 120.224 179 [137,] 121.108 219 [138,] 121.992 248 [139,] 122.876 220 [140,] 123.760 239 [141,] 124.644 257 [142,] 125.528 288 [143,] 126.412 276 [144,] 127.296 263 [145,] 128.180 275 [146,] 129.064 281 [147,] 129.948 332 [148,] 130.832 376 [149,] 131.716 371 [150,] 132.600 358 [151,] 133.484 371 [152,] 134.368 391 [153,] 135.252 403 [154,] 136.136 396 [155,] 137.020 456 [156,] 137.904 419 [157,] 138.788 419 [158,] 139.672 446 [159,] 140.556 418 [160,] 141.440 454 [161,] 142.324 454 [162,] 143.208 465 [163,] 144.092 494 [164,] 144.976 447 [165,] 145.860 475 [166,] 146.744 451 [167,] 147.628 430 [168,] 148.512 482 [169,] 149.396 480 [170,] 150.280 463 [171,] 151.164 473 [172,] 152.048 492 [173,] 152.932 480 [174,] 153.816 450 [175,] 154.700 437 [176,] 155.584 488 [177,] 156.468 457 [178,] 157.352 466 [179,] 158.236 485 [180,] 159.120 414 [181,] 160.004 424 [182,] 160.888 456 [183,] 161.772 428 [184,] 162.656 428 [185,] 163.540 480 [186,] 164.424 442 [187,] 165.308 457 [188,] 166.192 474 [189,] 167.076 449 [190,] 167.960 495 [191,] 168.844 451 [192,] 169.728 521 [193,] 170.612 456 [194,] 171.496 476 [195,] 172.380 472 [196,] 173.264 467 [197,] 174.148 474 [198,] 175.032 450 [199,] 175.916 515 [200,] 176.800 469 [201,] 177.684 483 [202,] 178.568 429 [203,] 179.452 469 [204,] 180.336 458 [205,] 181.220 480 [206,] 182.104 446 [207,] 182.988 491 [208,] 183.872 454 [209,] 184.756 526 [210,] 185.640 441 [211,] 186.524 472 [212,] 187.408 520 [213,] 188.292 491 [214,] 189.176 458 [215,] 190.060 510 [216,] 190.944 540 [217,] 191.828 519 [218,] 192.712 549 [219,] 193.596 507 [220,] 194.480 520 [221,] 195.364 496 [222,] 196.248 524 [223,] 197.132 587 [224,] 198.016 546 [225,] 198.900 554 [226,] 199.784 581 [227,] 200.668 583 [228,] 201.552 582 [229,] 202.436 574 [230,] 203.320 630 [231,] 204.204 592 [232,] 205.088 645 [233,] 205.972 574 [234,] 206.856 560 [235,] 207.740 630 [236,] 208.624 595 [237,] 209.508 612 [238,] 210.392 642 [239,] 211.276 622 [240,] 212.160 589 [241,] 213.044 633 [242,] 213.928 565 [243,] 214.812 613 [244,] 215.696 646 [245,] 216.580 613 [246,] 217.464 556 [247,] 218.348 617 [248,] 219.232 595 [249,] 220.116 628 [250,] 221.000 213 $`14_OSL (PMT)` [,1] [,2] [1,] 0.04 12801 [2,] 0.08 10899 [3,] 0.12 9374 [4,] 0.16 7790 [5,] 0.20 6619 [6,] 0.24 5908 [7,] 0.28 5074 [8,] 0.32 4316 [9,] 0.36 3749 [10,] 0.40 3334 [11,] 0.44 2885 [12,] 0.48 2446 [13,] 0.52 2211 [14,] 0.56 2105 [15,] 0.60 1835 [16,] 0.64 1513 [17,] 0.68 1376 [18,] 0.72 1296 [19,] 0.76 1110 [20,] 0.80 1068 [21,] 0.84 937 [22,] 0.88 840 [23,] 0.92 776 [24,] 0.96 746 [25,] 1.00 658 [26,] 1.04 610 [27,] 1.08 564 [28,] 1.12 533 [29,] 1.16 509 [30,] 1.20 465 [31,] 1.24 434 [32,] 1.28 415 [33,] 1.32 405 [34,] 1.36 352 [35,] 1.40 366 [36,] 1.44 316 [37,] 1.48 305 [38,] 1.52 348 [39,] 1.56 274 [40,] 1.60 301 [41,] 1.64 239 [42,] 1.68 298 [43,] 1.72 313 [44,] 1.76 270 [45,] 1.80 261 [46,] 1.84 236 [47,] 1.88 267 [48,] 1.92 225 [49,] 1.96 223 [50,] 2.00 183 [51,] 2.04 197 [52,] 2.08 208 [53,] 2.12 196 [54,] 2.16 169 [55,] 2.20 197 [56,] 2.24 203 [57,] 2.28 160 [58,] 2.32 195 [59,] 2.36 180 [60,] 2.40 201 [61,] 2.44 159 [62,] 2.48 182 [63,] 2.52 187 [64,] 2.56 151 [65,] 2.60 151 [66,] 2.64 180 [67,] 2.68 174 [68,] 2.72 156 [69,] 2.76 192 [70,] 2.80 142 [71,] 2.84 150 [72,] 2.88 168 [73,] 2.92 159 [74,] 2.96 138 [75,] 3.00 137 [76,] 3.04 129 [77,] 3.08 135 [78,] 3.12 138 [79,] 3.16 150 [80,] 3.20 140 [81,] 3.24 177 [82,] 3.28 128 [83,] 3.32 141 [84,] 3.36 140 [85,] 3.40 173 [86,] 3.44 132 [87,] 3.48 162 [88,] 3.52 115 [89,] 3.56 124 [90,] 3.60 130 [91,] 3.64 151 [92,] 3.68 150 [93,] 3.72 134 [94,] 3.76 140 [95,] 3.80 149 [96,] 3.84 149 [97,] 3.88 118 [98,] 3.92 129 [99,] 3.96 122 [100,] 4.00 115 [101,] 4.04 117 [102,] 4.08 125 [103,] 4.12 148 [104,] 4.16 124 [105,] 4.20 104 [106,] 4.24 137 [107,] 4.28 113 [108,] 4.32 147 [109,] 4.36 125 [110,] 4.40 125 [111,] 4.44 134 [112,] 4.48 113 [113,] 4.52 116 [114,] 4.56 117 [115,] 4.60 129 [116,] 4.64 143 [117,] 4.68 114 [118,] 4.72 105 [119,] 4.76 110 [120,] 4.80 119 [121,] 4.84 104 [122,] 4.88 121 [123,] 4.92 120 [124,] 4.96 114 [125,] 5.00 99 [126,] 5.04 103 [127,] 5.08 127 [128,] 5.12 91 [129,] 5.16 114 [130,] 5.20 116 [131,] 5.24 103 [132,] 5.28 104 [133,] 5.32 112 [134,] 5.36 115 [135,] 5.40 122 [136,] 5.44 110 [137,] 5.48 83 [138,] 5.52 118 [139,] 5.56 132 [140,] 5.60 112 [141,] 5.64 133 [142,] 5.68 107 [143,] 5.72 110 [144,] 5.76 96 [145,] 5.80 122 [146,] 5.84 88 [147,] 5.88 106 [148,] 5.92 104 [149,] 5.96 92 [150,] 6.00 108 [151,] 6.04 100 [152,] 6.08 111 [153,] 6.12 97 [154,] 6.16 106 [155,] 6.20 95 [156,] 6.24 89 [157,] 6.28 96 [158,] 6.32 119 [159,] 6.36 92 [160,] 6.40 99 [161,] 6.44 99 [162,] 6.48 110 [163,] 6.52 126 [164,] 6.56 88 [165,] 6.60 120 [166,] 6.64 92 [167,] 6.68 88 [168,] 6.72 100 [169,] 6.76 119 [170,] 6.80 89 [171,] 6.84 92 [172,] 6.88 96 [173,] 6.92 107 [174,] 6.96 101 [175,] 7.00 116 [176,] 7.04 101 [177,] 7.08 98 [178,] 7.12 110 [179,] 7.16 102 [180,] 7.20 103 [181,] 7.24 101 [182,] 7.28 93 [183,] 7.32 122 [184,] 7.36 78 [185,] 7.40 134 [186,] 7.44 101 [187,] 7.48 91 [188,] 7.52 94 [189,] 7.56 106 [190,] 7.60 98 [191,] 7.64 105 [192,] 7.68 109 [193,] 7.72 102 [194,] 7.76 103 [195,] 7.80 119 [196,] 7.84 85 [197,] 7.88 99 [198,] 7.92 86 [199,] 7.96 85 [200,] 8.00 96 [201,] 8.04 88 [202,] 8.08 92 [203,] 8.12 87 [204,] 8.16 121 [205,] 8.20 103 [206,] 8.24 90 [207,] 8.28 90 [208,] 8.32 107 [209,] 8.36 101 [210,] 8.40 87 [211,] 8.44 93 [212,] 8.48 90 [213,] 8.52 91 [214,] 8.56 78 [215,] 8.60 81 [216,] 8.64 122 [217,] 8.68 100 [218,] 8.72 84 [219,] 8.76 86 [220,] 8.80 96 [221,] 8.84 91 [222,] 8.88 77 [223,] 8.92 94 [224,] 8.96 82 [225,] 9.00 86 [226,] 9.04 85 [227,] 9.08 90 [228,] 9.12 95 [229,] 9.16 78 [230,] 9.20 96 [231,] 9.24 82 [232,] 9.28 70 [233,] 9.32 93 [234,] 9.36 83 [235,] 9.40 91 [236,] 9.44 125 [237,] 9.48 86 [238,] 9.52 105 [239,] 9.56 93 [240,] 9.60 95 [241,] 9.64 98 [242,] 9.68 83 [243,] 9.72 86 [244,] 9.76 88 [245,] 9.80 95 [246,] 9.84 102 [247,] 9.88 108 [248,] 9.92 87 [249,] 9.96 83 [250,] 10.00 97 [251,] 10.04 83 [252,] 10.08 84 [253,] 10.12 75 [254,] 10.16 104 [255,] 10.20 83 [256,] 10.24 95 [257,] 10.28 86 [258,] 10.32 89 [259,] 10.36 92 [260,] 10.40 91 [261,] 10.44 89 [262,] 10.48 84 [263,] 10.52 84 [264,] 10.56 83 [265,] 10.60 83 [266,] 10.64 75 [267,] 10.68 87 [268,] 10.72 104 [269,] 10.76 98 [270,] 10.80 101 [271,] 10.84 78 [272,] 10.88 103 [273,] 10.92 82 [274,] 10.96 107 [275,] 11.00 90 [276,] 11.04 108 [277,] 11.08 74 [278,] 11.12 81 [279,] 11.16 75 [280,] 11.20 81 [281,] 11.24 80 [282,] 11.28 79 [283,] 11.32 87 [284,] 11.36 73 [285,] 11.40 79 [286,] 11.44 69 [287,] 11.48 83 [288,] 11.52 68 [289,] 11.56 85 [290,] 11.60 104 [291,] 11.64 98 [292,] 11.68 78 [293,] 11.72 83 [294,] 11.76 78 [295,] 11.80 81 [296,] 11.84 81 [297,] 11.88 69 [298,] 11.92 72 [299,] 11.96 80 [300,] 12.00 103 [301,] 12.04 81 [302,] 12.08 80 [303,] 12.12 72 [304,] 12.16 69 [305,] 12.20 85 [306,] 12.24 89 [307,] 12.28 101 [308,] 12.32 76 [309,] 12.36 79 [310,] 12.40 93 [311,] 12.44 94 [312,] 12.48 84 [313,] 12.52 69 [314,] 12.56 78 [315,] 12.60 80 [316,] 12.64 101 [317,] 12.68 81 [318,] 12.72 89 [319,] 12.76 71 [320,] 12.80 71 [321,] 12.84 72 [322,] 12.88 90 [323,] 12.92 81 [324,] 12.96 81 [325,] 13.00 75 [326,] 13.04 63 [327,] 13.08 78 [328,] 13.12 74 [329,] 13.16 86 [330,] 13.20 83 [331,] 13.24 84 [332,] 13.28 90 [333,] 13.32 63 [334,] 13.36 80 [335,] 13.40 87 [336,] 13.44 88 [337,] 13.48 65 [338,] 13.52 69 [339,] 13.56 83 [340,] 13.60 82 [341,] 13.64 61 [342,] 13.68 84 [343,] 13.72 77 [344,] 13.76 79 [345,] 13.80 85 [346,] 13.84 70 [347,] 13.88 96 [348,] 13.92 103 [349,] 13.96 59 [350,] 14.00 77 [351,] 14.04 81 [352,] 14.08 61 [353,] 14.12 72 [354,] 14.16 98 [355,] 14.20 89 [356,] 14.24 69 [357,] 14.28 83 [358,] 14.32 71 [359,] 14.36 84 [360,] 14.40 79 [361,] 14.44 92 [362,] 14.48 78 [363,] 14.52 60 [364,] 14.56 63 [365,] 14.60 59 [366,] 14.64 79 [367,] 14.68 83 [368,] 14.72 80 [369,] 14.76 78 [370,] 14.80 74 [371,] 14.84 93 [372,] 14.88 86 [373,] 14.92 72 [374,] 14.96 92 [375,] 15.00 84 [376,] 15.04 103 [377,] 15.08 85 [378,] 15.12 60 [379,] 15.16 91 [380,] 15.20 60 [381,] 15.24 76 [382,] 15.28 94 [383,] 15.32 72 [384,] 15.36 83 [385,] 15.40 77 [386,] 15.44 62 [387,] 15.48 87 [388,] 15.52 87 [389,] 15.56 56 [390,] 15.60 87 [391,] 15.64 68 [392,] 15.68 86 [393,] 15.72 70 [394,] 15.76 80 [395,] 15.80 87 [396,] 15.84 81 [397,] 15.88 78 [398,] 15.92 94 [399,] 15.96 69 [400,] 16.00 72 [401,] 16.04 70 [402,] 16.08 81 [403,] 16.12 78 [404,] 16.16 72 [405,] 16.20 84 [406,] 16.24 83 [407,] 16.28 79 [408,] 16.32 76 [409,] 16.36 89 [410,] 16.40 64 [411,] 16.44 68 [412,] 16.48 92 [413,] 16.52 66 [414,] 16.56 81 [415,] 16.60 72 [416,] 16.64 81 [417,] 16.68 74 [418,] 16.72 64 [419,] 16.76 71 [420,] 16.80 70 [421,] 16.84 90 [422,] 16.88 67 [423,] 16.92 73 [424,] 16.96 80 [425,] 17.00 66 [426,] 17.04 74 [427,] 17.08 75 [428,] 17.12 71 [429,] 17.16 78 [430,] 17.20 83 [431,] 17.24 72 [432,] 17.28 78 [433,] 17.32 74 [434,] 17.36 75 [435,] 17.40 86 [436,] 17.44 66 [437,] 17.48 76 [438,] 17.52 82 [439,] 17.56 81 [440,] 17.60 60 [441,] 17.64 88 [442,] 17.68 82 [443,] 17.72 85 [444,] 17.76 77 [445,] 17.80 70 [446,] 17.84 74 [447,] 17.88 99 [448,] 17.92 88 [449,] 17.96 74 [450,] 18.00 65 [451,] 18.04 80 [452,] 18.08 72 [453,] 18.12 73 [454,] 18.16 59 [455,] 18.20 87 [456,] 18.24 79 [457,] 18.28 92 [458,] 18.32 58 [459,] 18.36 75 [460,] 18.40 66 [461,] 18.44 58 [462,] 18.48 74 [463,] 18.52 75 [464,] 18.56 75 [465,] 18.60 79 [466,] 18.64 60 [467,] 18.68 84 [468,] 18.72 80 [469,] 18.76 68 [470,] 18.80 76 [471,] 18.84 64 [472,] 18.88 70 [473,] 18.92 85 [474,] 18.96 66 [475,] 19.00 69 [476,] 19.04 71 [477,] 19.08 68 [478,] 19.12 61 [479,] 19.16 88 [480,] 19.20 59 [481,] 19.24 83 [482,] 19.28 54 [483,] 19.32 58 [484,] 19.36 69 [485,] 19.40 53 [486,] 19.44 78 [487,] 19.48 79 [488,] 19.52 59 [489,] 19.56 76 [490,] 19.60 75 [491,] 19.64 91 [492,] 19.68 78 [493,] 19.72 65 [494,] 19.76 81 [495,] 19.80 66 [496,] 19.84 68 [497,] 19.88 55 [498,] 19.92 74 [499,] 19.96 77 [500,] 20.00 62 [501,] 20.04 87 [502,] 20.08 66 [503,] 20.12 63 [504,] 20.16 75 [505,] 20.20 91 [506,] 20.24 51 [507,] 20.28 66 [508,] 20.32 82 [509,] 20.36 73 [510,] 20.40 63 [511,] 20.44 68 [512,] 20.48 63 [513,] 20.52 61 [514,] 20.56 92 [515,] 20.60 81 [516,] 20.64 62 [517,] 20.68 70 [518,] 20.72 79 [519,] 20.76 75 [520,] 20.80 95 [521,] 20.84 79 [522,] 20.88 73 [523,] 20.92 54 [524,] 20.96 75 [525,] 21.00 87 [526,] 21.04 64 [527,] 21.08 72 [528,] 21.12 80 [529,] 21.16 57 [530,] 21.20 56 [531,] 21.24 79 [532,] 21.28 78 [533,] 21.32 80 [534,] 21.36 68 [535,] 21.40 79 [536,] 21.44 49 [537,] 21.48 57 [538,] 21.52 79 [539,] 21.56 71 [540,] 21.60 81 [541,] 21.64 77 [542,] 21.68 60 [543,] 21.72 67 [544,] 21.76 61 [545,] 21.80 70 [546,] 21.84 73 [547,] 21.88 63 [548,] 21.92 65 [549,] 21.96 69 [550,] 22.00 62 [551,] 22.04 78 [552,] 22.08 73 [553,] 22.12 80 [554,] 22.16 71 [555,] 22.20 64 [556,] 22.24 71 [557,] 22.28 68 [558,] 22.32 80 [559,] 22.36 61 [560,] 22.40 74 [561,] 22.44 58 [562,] 22.48 68 [563,] 22.52 75 [564,] 22.56 87 [565,] 22.60 64 [566,] 22.64 76 [567,] 22.68 61 [568,] 22.72 66 [569,] 22.76 58 [570,] 22.80 71 [571,] 22.84 59 [572,] 22.88 66 [573,] 22.92 93 [574,] 22.96 63 [575,] 23.00 68 [576,] 23.04 82 [577,] 23.08 89 [578,] 23.12 52 [579,] 23.16 63 [580,] 23.20 51 [581,] 23.24 67 [582,] 23.28 72 [583,] 23.32 76 [584,] 23.36 71 [585,] 23.40 69 [586,] 23.44 59 [587,] 23.48 75 [588,] 23.52 83 [589,] 23.56 67 [590,] 23.60 84 [591,] 23.64 84 [592,] 23.68 75 [593,] 23.72 66 [594,] 23.76 61 [595,] 23.80 60 [596,] 23.84 76 [597,] 23.88 75 [598,] 23.92 72 [599,] 23.96 79 [600,] 24.00 71 [601,] 24.04 75 [602,] 24.08 80 [603,] 24.12 85 [604,] 24.16 66 [605,] 24.20 65 [606,] 24.24 62 [607,] 24.28 76 [608,] 24.32 56 [609,] 24.36 55 [610,] 24.40 68 [611,] 24.44 69 [612,] 24.48 78 [613,] 24.52 81 [614,] 24.56 67 [615,] 24.60 75 [616,] 24.64 58 [617,] 24.68 67 [618,] 24.72 67 [619,] 24.76 57 [620,] 24.80 55 [621,] 24.84 58 [622,] 24.88 63 [623,] 24.92 74 [624,] 24.96 53 [625,] 25.00 67 [626,] 25.04 76 [627,] 25.08 73 [628,] 25.12 62 [629,] 25.16 70 [630,] 25.20 64 [631,] 25.24 87 [632,] 25.28 70 [633,] 25.32 69 [634,] 25.36 73 [635,] 25.40 66 [636,] 25.44 56 [637,] 25.48 71 [638,] 25.52 80 [639,] 25.56 80 [640,] 25.60 58 [641,] 25.64 86 [642,] 25.68 58 [643,] 25.72 64 [644,] 25.76 65 [645,] 25.80 67 [646,] 25.84 83 [647,] 25.88 47 [648,] 25.92 54 [649,] 25.96 59 [650,] 26.00 62 [651,] 26.04 77 [652,] 26.08 70 [653,] 26.12 55 [654,] 26.16 83 [655,] 26.20 71 [656,] 26.24 59 [657,] 26.28 66 [658,] 26.32 66 [659,] 26.36 68 [660,] 26.40 54 [661,] 26.44 68 [662,] 26.48 84 [663,] 26.52 59 [664,] 26.56 49 [665,] 26.60 77 [666,] 26.64 70 [667,] 26.68 58 [668,] 26.72 56 [669,] 26.76 59 [670,] 26.80 78 [671,] 26.84 52 [672,] 26.88 65 [673,] 26.92 82 [674,] 26.96 59 [675,] 27.00 71 [676,] 27.04 68 [677,] 27.08 72 [678,] 27.12 84 [679,] 27.16 71 [680,] 27.20 73 [681,] 27.24 60 [682,] 27.28 73 [683,] 27.32 64 [684,] 27.36 71 [685,] 27.40 75 [686,] 27.44 68 [687,] 27.48 68 [688,] 27.52 84 [689,] 27.56 73 [690,] 27.60 72 [691,] 27.64 67 [692,] 27.68 74 [693,] 27.72 64 [694,] 27.76 63 [695,] 27.80 54 [696,] 27.84 70 [697,] 27.88 60 [698,] 27.92 62 [699,] 27.96 62 [700,] 28.00 50 [701,] 28.04 60 [702,] 28.08 77 [703,] 28.12 68 [704,] 28.16 70 [705,] 28.20 65 [706,] 28.24 58 [707,] 28.28 55 [708,] 28.32 76 [709,] 28.36 60 [710,] 28.40 65 [711,] 28.44 64 [712,] 28.48 63 [713,] 28.52 55 [714,] 28.56 97 [715,] 28.60 49 [716,] 28.64 74 [717,] 28.68 49 [718,] 28.72 66 [719,] 28.76 51 [720,] 28.80 72 [721,] 28.84 67 [722,] 28.88 86 [723,] 28.92 51 [724,] 28.96 71 [725,] 29.00 70 [726,] 29.04 74 [727,] 29.08 76 [728,] 29.12 72 [729,] 29.16 59 [730,] 29.20 52 [731,] 29.24 75 [732,] 29.28 81 [733,] 29.32 65 [734,] 29.36 70 [735,] 29.40 71 [736,] 29.44 64 [737,] 29.48 51 [738,] 29.52 57 [739,] 29.56 61 [740,] 29.60 72 [741,] 29.64 54 [742,] 29.68 61 [743,] 29.72 63 [744,] 29.76 60 [745,] 29.80 69 [746,] 29.84 64 [747,] 29.88 55 [748,] 29.92 64 [749,] 29.96 46 [750,] 30.00 56 [751,] 30.04 64 [752,] 30.08 61 [753,] 30.12 64 [754,] 30.16 80 [755,] 30.20 69 [756,] 30.24 71 [757,] 30.28 66 [758,] 30.32 72 [759,] 30.36 60 [760,] 30.40 80 [761,] 30.44 56 [762,] 30.48 52 [763,] 30.52 75 [764,] 30.56 72 [765,] 30.60 63 [766,] 30.64 63 [767,] 30.68 69 [768,] 30.72 62 [769,] 30.76 74 [770,] 30.80 69 [771,] 30.84 55 [772,] 30.88 73 [773,] 30.92 68 [774,] 30.96 69 [775,] 31.00 61 [776,] 31.04 78 [777,] 31.08 62 [778,] 31.12 51 [779,] 31.16 74 [780,] 31.20 79 [781,] 31.24 67 [782,] 31.28 64 [783,] 31.32 57 [784,] 31.36 76 [785,] 31.40 83 [786,] 31.44 66 [787,] 31.48 59 [788,] 31.52 59 [789,] 31.56 69 [790,] 31.60 45 [791,] 31.64 52 [792,] 31.68 72 [793,] 31.72 69 [794,] 31.76 67 [795,] 31.80 79 [796,] 31.84 52 [797,] 31.88 84 [798,] 31.92 46 [799,] 31.96 56 [800,] 32.00 68 [801,] 32.04 56 [802,] 32.08 69 [803,] 32.12 64 [804,] 32.16 63 [805,] 32.20 69 [806,] 32.24 54 [807,] 32.28 52 [808,] 32.32 57 [809,] 32.36 79 [810,] 32.40 73 [811,] 32.44 72 [812,] 32.48 74 [813,] 32.52 64 [814,] 32.56 67 [815,] 32.60 69 [816,] 32.64 74 [817,] 32.68 80 [818,] 32.72 77 [819,] 32.76 62 [820,] 32.80 63 [821,] 32.84 69 [822,] 32.88 76 [823,] 32.92 65 [824,] 32.96 48 [825,] 33.00 81 [826,] 33.04 62 [827,] 33.08 51 [828,] 33.12 52 [829,] 33.16 62 [830,] 33.20 59 [831,] 33.24 75 [832,] 33.28 51 [833,] 33.32 57 [834,] 33.36 75 [835,] 33.40 67 [836,] 33.44 63 [837,] 33.48 68 [838,] 33.52 57 [839,] 33.56 47 [840,] 33.60 58 [841,] 33.64 66 [842,] 33.68 61 [843,] 33.72 51 [844,] 33.76 56 [845,] 33.80 76 [846,] 33.84 68 [847,] 33.88 44 [848,] 33.92 50 [849,] 33.96 45 [850,] 34.00 46 [851,] 34.04 54 [852,] 34.08 73 [853,] 34.12 67 [854,] 34.16 63 [855,] 34.20 65 [856,] 34.24 60 [857,] 34.28 53 [858,] 34.32 59 [859,] 34.36 67 [860,] 34.40 58 [861,] 34.44 57 [862,] 34.48 51 [863,] 34.52 54 [864,] 34.56 56 [865,] 34.60 71 [866,] 34.64 61 [867,] 34.68 60 [868,] 34.72 63 [869,] 34.76 60 [870,] 34.80 65 [871,] 34.84 56 [872,] 34.88 54 [873,] 34.92 57 [874,] 34.96 70 [875,] 35.00 64 [876,] 35.04 61 [877,] 35.08 60 [878,] 35.12 61 [879,] 35.16 51 [880,] 35.20 60 [881,] 35.24 46 [882,] 35.28 52 [883,] 35.32 51 [884,] 35.36 49 [885,] 35.40 70 [886,] 35.44 55 [887,] 35.48 65 [888,] 35.52 50 [889,] 35.56 53 [890,] 35.60 61 [891,] 35.64 66 [892,] 35.68 53 [893,] 35.72 48 [894,] 35.76 51 [895,] 35.80 48 [896,] 35.84 53 [897,] 35.88 58 [898,] 35.92 52 [899,] 35.96 48 [900,] 36.00 61 [901,] 36.04 57 [902,] 36.08 74 [903,] 36.12 58 [904,] 36.16 53 [905,] 36.20 49 [906,] 36.24 65 [907,] 36.28 81 [908,] 36.32 40 [909,] 36.36 57 [910,] 36.40 60 [911,] 36.44 54 [912,] 36.48 63 [913,] 36.52 68 [914,] 36.56 53 [915,] 36.60 67 [916,] 36.64 67 [917,] 36.68 76 [918,] 36.72 43 [919,] 36.76 60 [920,] 36.80 55 [921,] 36.84 55 [922,] 36.88 65 [923,] 36.92 55 [924,] 36.96 68 [925,] 37.00 62 [926,] 37.04 74 [927,] 37.08 68 [928,] 37.12 68 [929,] 37.16 68 [930,] 37.20 69 [931,] 37.24 81 [932,] 37.28 53 [933,] 37.32 56 [934,] 37.36 62 [935,] 37.40 71 [936,] 37.44 66 [937,] 37.48 59 [938,] 37.52 54 [939,] 37.56 48 [940,] 37.60 79 [941,] 37.64 68 [942,] 37.68 60 [943,] 37.72 81 [944,] 37.76 65 [945,] 37.80 65 [946,] 37.84 52 [947,] 37.88 46 [948,] 37.92 57 [949,] 37.96 74 [950,] 38.00 58 [951,] 38.04 68 [952,] 38.08 74 [953,] 38.12 55 [954,] 38.16 47 [955,] 38.20 53 [956,] 38.24 56 [957,] 38.28 45 [958,] 38.32 47 [959,] 38.36 56 [960,] 38.40 45 [961,] 38.44 57 [962,] 38.48 65 [963,] 38.52 62 [964,] 38.56 60 [965,] 38.60 62 [966,] 38.64 50 [967,] 38.68 49 [968,] 38.72 50 [969,] 38.76 61 [970,] 38.80 53 [971,] 38.84 71 [972,] 38.88 60 [973,] 38.92 60 [974,] 38.96 48 [975,] 39.00 51 [976,] 39.04 48 [977,] 39.08 55 [978,] 39.12 60 [979,] 39.16 66 [980,] 39.20 55 [981,] 39.24 59 [982,] 39.28 45 [983,] 39.32 61 [984,] 39.36 65 [985,] 39.40 51 [986,] 39.44 51 [987,] 39.48 60 [988,] 39.52 50 [989,] 39.56 50 [990,] 39.60 43 [991,] 39.64 52 [992,] 39.68 59 [993,] 39.72 71 [994,] 39.76 74 [995,] 39.80 44 [996,] 39.84 52 [997,] 39.88 71 [998,] 39.92 66 [999,] 39.96 45 [1000,] 40.00 58 $`15_TL (PMT)` [,1] [,2] [1,] 0.64 2 [2,] 1.28 1 [3,] 1.92 5 [4,] 2.56 1 [5,] 3.20 1 [6,] 3.84 3 [7,] 4.48 1 [8,] 5.12 0 [9,] 5.76 1 [10,] 6.40 10 [11,] 7.04 1 [12,] 7.68 2 [13,] 8.32 2 [14,] 8.96 2 [15,] 9.60 6 [16,] 10.24 2 [17,] 10.88 0 [18,] 11.52 0 [19,] 12.16 4 [20,] 12.80 3 [21,] 13.44 2 [22,] 14.08 8 [23,] 14.72 3 [24,] 15.36 5 [25,] 16.00 2 [26,] 16.64 4 [27,] 17.28 3 [28,] 17.92 4 [29,] 18.56 1 [30,] 19.20 5 [31,] 19.84 0 [32,] 20.48 5 [33,] 21.12 3 [34,] 21.76 6 [35,] 22.40 3 [36,] 23.04 10 [37,] 23.68 0 [38,] 24.32 3 [39,] 24.96 3 [40,] 25.60 6 [41,] 26.24 2 [42,] 26.88 1 [43,] 27.52 4 [44,] 28.16 0 [45,] 28.80 4 [46,] 29.44 1 [47,] 30.08 6 [48,] 30.72 6 [49,] 31.36 0 [50,] 32.00 1 [51,] 32.64 7 [52,] 33.28 3 [53,] 33.92 4 [54,] 34.56 8 [55,] 35.20 1 [56,] 35.84 7 [57,] 36.48 4 [58,] 37.12 12 [59,] 37.76 3 [60,] 38.40 3 [61,] 39.04 8 [62,] 39.68 4 [63,] 40.32 3 [64,] 40.96 8 [65,] 41.60 4 [66,] 42.24 5 [67,] 42.88 3 [68,] 43.52 5 [69,] 44.16 6 [70,] 44.80 1 [71,] 45.44 3 [72,] 46.08 2 [73,] 46.72 8 [74,] 47.36 4 [75,] 48.00 10 [76,] 48.64 6 [77,] 49.28 10 [78,] 49.92 3 [79,] 50.56 28 [80,] 51.20 6 [81,] 51.84 10 [82,] 52.48 7 [83,] 53.12 3 [84,] 53.76 12 [85,] 54.40 4 [86,] 55.04 10 [87,] 55.68 14 [88,] 56.32 7 [89,] 56.96 3 [90,] 57.60 11 [91,] 58.24 20 [92,] 58.88 16 [93,] 59.52 16 [94,] 60.16 20 [95,] 60.80 21 [96,] 61.44 13 [97,] 62.08 15 [98,] 62.72 20 [99,] 63.36 20 [100,] 64.00 20 [101,] 64.64 23 [102,] 65.28 17 [103,] 65.92 25 [104,] 66.56 18 [105,] 67.20 25 [106,] 67.84 25 [107,] 68.48 26 [108,] 69.12 32 [109,] 69.76 22 [110,] 70.40 33 [111,] 71.04 26 [112,] 71.68 23 [113,] 72.32 49 [114,] 72.96 39 [115,] 73.60 29 [116,] 74.24 44 [117,] 74.88 44 [118,] 75.52 51 [119,] 76.16 57 [120,] 76.80 66 [121,] 77.44 61 [122,] 78.08 62 [123,] 78.72 75 [124,] 79.36 78 [125,] 80.00 73 [126,] 80.64 84 [127,] 81.28 86 [128,] 81.92 86 [129,] 82.56 99 [130,] 83.20 107 [131,] 83.84 125 [132,] 84.48 112 [133,] 85.12 129 [134,] 85.76 111 [135,] 86.40 127 [136,] 87.04 116 [137,] 87.68 140 [138,] 88.32 146 [139,] 88.96 159 [140,] 89.60 146 [141,] 90.24 150 [142,] 90.88 188 [143,] 91.52 179 [144,] 92.16 176 [145,] 92.80 194 [146,] 93.44 189 [147,] 94.08 199 [148,] 94.72 189 [149,] 95.36 189 [150,] 96.00 195 [151,] 96.64 259 [152,] 97.28 213 [153,] 97.92 239 [154,] 98.56 238 [155,] 99.20 244 [156,] 99.84 236 [157,] 100.48 290 [158,] 101.12 253 [159,] 101.76 282 [160,] 102.40 259 [161,] 103.04 250 [162,] 103.68 282 [163,] 104.32 289 [164,] 104.96 264 [165,] 105.60 263 [166,] 106.24 299 [167,] 106.88 243 [168,] 107.52 282 [169,] 108.16 255 [170,] 108.80 282 [171,] 109.44 284 [172,] 110.08 267 [173,] 110.72 295 [174,] 111.36 265 [175,] 112.00 237 [176,] 112.64 208 [177,] 113.28 183 [178,] 113.92 238 [179,] 114.56 213 [180,] 115.20 198 [181,] 115.84 195 [182,] 116.48 224 [183,] 117.12 210 [184,] 117.76 191 [185,] 118.40 138 [186,] 119.04 152 [187,] 119.68 138 [188,] 120.32 140 [189,] 120.96 129 [190,] 121.60 136 [191,] 122.24 117 [192,] 122.88 116 [193,] 123.52 94 [194,] 124.16 82 [195,] 124.80 89 [196,] 125.44 79 [197,] 126.08 97 [198,] 126.72 85 [199,] 127.36 66 [200,] 128.00 75 [201,] 128.64 91 [202,] 129.28 67 [203,] 129.92 92 [204,] 130.56 76 [205,] 131.20 78 [206,] 131.84 71 [207,] 132.48 86 [208,] 133.12 84 [209,] 133.76 78 [210,] 134.40 74 [211,] 135.04 80 [212,] 135.68 73 [213,] 136.32 75 [214,] 136.96 88 [215,] 137.60 80 [216,] 138.24 85 [217,] 138.88 81 [218,] 139.52 98 [219,] 140.16 82 [220,] 140.80 89 [221,] 141.44 83 [222,] 142.08 97 [223,] 142.72 79 [224,] 143.36 85 [225,] 144.00 82 [226,] 144.64 78 [227,] 145.28 100 [228,] 145.92 90 [229,] 146.56 97 [230,] 147.20 95 [231,] 147.84 72 [232,] 148.48 78 [233,] 149.12 100 [234,] 149.76 61 [235,] 150.40 69 [236,] 151.04 90 [237,] 151.68 74 [238,] 152.32 79 [239,] 152.96 82 [240,] 153.60 76 [241,] 154.24 64 [242,] 154.88 72 [243,] 155.52 76 [244,] 156.16 73 [245,] 156.80 75 [246,] 157.44 75 [247,] 158.08 90 [248,] 158.72 84 [249,] 159.36 82 [250,] 160.00 70 $`16_OSL (PMT)` [,1] [,2] [1,] 0.04 2660 [2,] 0.08 2404 [3,] 0.12 2054 [4,] 0.16 1845 [5,] 0.20 1610 [6,] 0.24 1391 [7,] 0.28 1160 [8,] 0.32 1020 [9,] 0.36 986 [10,] 0.40 878 [11,] 0.44 731 [12,] 0.48 658 [13,] 0.52 600 [14,] 0.56 570 [15,] 0.60 498 [16,] 0.64 465 [17,] 0.68 435 [18,] 0.72 394 [19,] 0.76 305 [20,] 0.80 320 [21,] 0.84 289 [22,] 0.88 266 [23,] 0.92 227 [24,] 0.96 265 [25,] 1.00 236 [26,] 1.04 251 [27,] 1.08 240 [28,] 1.12 188 [29,] 1.16 186 [30,] 1.20 199 [31,] 1.24 200 [32,] 1.28 177 [33,] 1.32 197 [34,] 1.36 183 [35,] 1.40 167 [36,] 1.44 140 [37,] 1.48 174 [38,] 1.52 138 [39,] 1.56 163 [40,] 1.60 164 [41,] 1.64 136 [42,] 1.68 156 [43,] 1.72 163 [44,] 1.76 120 [45,] 1.80 157 [46,] 1.84 132 [47,] 1.88 124 [48,] 1.92 143 [49,] 1.96 127 [50,] 2.00 118 [51,] 2.04 154 [52,] 2.08 130 [53,] 2.12 110 [54,] 2.16 121 [55,] 2.20 118 [56,] 2.24 114 [57,] 2.28 130 [58,] 2.32 111 [59,] 2.36 145 [60,] 2.40 132 [61,] 2.44 114 [62,] 2.48 106 [63,] 2.52 95 [64,] 2.56 130 [65,] 2.60 115 [66,] 2.64 114 [67,] 2.68 125 [68,] 2.72 118 [69,] 2.76 122 [70,] 2.80 108 [71,] 2.84 111 [72,] 2.88 110 [73,] 2.92 109 [74,] 2.96 112 [75,] 3.00 107 [76,] 3.04 119 [77,] 3.08 101 [78,] 3.12 88 [79,] 3.16 107 [80,] 3.20 99 [81,] 3.24 132 [82,] 3.28 107 [83,] 3.32 98 [84,] 3.36 79 [85,] 3.40 88 [86,] 3.44 102 [87,] 3.48 105 [88,] 3.52 94 [89,] 3.56 89 [90,] 3.60 95 [91,] 3.64 96 [92,] 3.68 103 [93,] 3.72 97 [94,] 3.76 100 [95,] 3.80 87 [96,] 3.84 97 [97,] 3.88 107 [98,] 3.92 105 [99,] 3.96 99 [100,] 4.00 110 [101,] 4.04 98 [102,] 4.08 96 [103,] 4.12 88 [104,] 4.16 84 [105,] 4.20 91 [106,] 4.24 64 [107,] 4.28 89 [108,] 4.32 86 [109,] 4.36 94 [110,] 4.40 107 [111,] 4.44 93 [112,] 4.48 82 [113,] 4.52 98 [114,] 4.56 84 [115,] 4.60 97 [116,] 4.64 89 [117,] 4.68 84 [118,] 4.72 94 [119,] 4.76 85 [120,] 4.80 87 [121,] 4.84 74 [122,] 4.88 100 [123,] 4.92 101 [124,] 4.96 96 [125,] 5.00 111 [126,] 5.04 95 [127,] 5.08 87 [128,] 5.12 93 [129,] 5.16 87 [130,] 5.20 127 [131,] 5.24 91 [132,] 5.28 93 [133,] 5.32 82 [134,] 5.36 104 [135,] 5.40 112 [136,] 5.44 88 [137,] 5.48 103 [138,] 5.52 95 [139,] 5.56 91 [140,] 5.60 95 [141,] 5.64 111 [142,] 5.68 86 [143,] 5.72 73 [144,] 5.76 77 [145,] 5.80 88 [146,] 5.84 65 [147,] 5.88 79 [148,] 5.92 110 [149,] 5.96 89 [150,] 6.00 80 [151,] 6.04 84 [152,] 6.08 77 [153,] 6.12 87 [154,] 6.16 101 [155,] 6.20 84 [156,] 6.24 83 [157,] 6.28 84 [158,] 6.32 89 [159,] 6.36 68 [160,] 6.40 86 [161,] 6.44 87 [162,] 6.48 80 [163,] 6.52 68 [164,] 6.56 70 [165,] 6.60 77 [166,] 6.64 82 [167,] 6.68 83 [168,] 6.72 94 [169,] 6.76 93 [170,] 6.80 86 [171,] 6.84 95 [172,] 6.88 100 [173,] 6.92 90 [174,] 6.96 95 [175,] 7.00 76 [176,] 7.04 80 [177,] 7.08 89 [178,] 7.12 95 [179,] 7.16 57 [180,] 7.20 82 [181,] 7.24 90 [182,] 7.28 95 [183,] 7.32 86 [184,] 7.36 84 [185,] 7.40 84 [186,] 7.44 69 [187,] 7.48 74 [188,] 7.52 68 [189,] 7.56 90 [190,] 7.60 77 [191,] 7.64 73 [192,] 7.68 75 [193,] 7.72 77 [194,] 7.76 73 [195,] 7.80 75 [196,] 7.84 93 [197,] 7.88 96 [198,] 7.92 82 [199,] 7.96 92 [200,] 8.00 98 [201,] 8.04 82 [202,] 8.08 83 [203,] 8.12 92 [204,] 8.16 85 [205,] 8.20 83 [206,] 8.24 81 [207,] 8.28 67 [208,] 8.32 75 [209,] 8.36 82 [210,] 8.40 65 [211,] 8.44 82 [212,] 8.48 85 [213,] 8.52 68 [214,] 8.56 72 [215,] 8.60 90 [216,] 8.64 71 [217,] 8.68 89 [218,] 8.72 70 [219,] 8.76 80 [220,] 8.80 85 [221,] 8.84 61 [222,] 8.88 89 [223,] 8.92 79 [224,] 8.96 64 [225,] 9.00 81 [226,] 9.04 81 [227,] 9.08 64 [228,] 9.12 79 [229,] 9.16 91 [230,] 9.20 87 [231,] 9.24 95 [232,] 9.28 78 [233,] 9.32 72 [234,] 9.36 70 [235,] 9.40 56 [236,] 9.44 91 [237,] 9.48 80 [238,] 9.52 62 [239,] 9.56 86 [240,] 9.60 56 [241,] 9.64 70 [242,] 9.68 67 [243,] 9.72 87 [244,] 9.76 90 [245,] 9.80 74 [246,] 9.84 77 [247,] 9.88 65 [248,] 9.92 55 [249,] 9.96 70 [250,] 10.00 63 [251,] 10.04 70 [252,] 10.08 80 [253,] 10.12 77 [254,] 10.16 84 [255,] 10.20 89 [256,] 10.24 85 [257,] 10.28 85 [258,] 10.32 67 [259,] 10.36 70 [260,] 10.40 80 [261,] 10.44 70 [262,] 10.48 71 [263,] 10.52 79 [264,] 10.56 80 [265,] 10.60 74 [266,] 10.64 77 [267,] 10.68 78 [268,] 10.72 77 [269,] 10.76 62 [270,] 10.80 68 [271,] 10.84 73 [272,] 10.88 86 [273,] 10.92 85 [274,] 10.96 66 [275,] 11.00 50 [276,] 11.04 66 [277,] 11.08 70 [278,] 11.12 82 [279,] 11.16 73 [280,] 11.20 68 [281,] 11.24 76 [282,] 11.28 77 [283,] 11.32 80 [284,] 11.36 68 [285,] 11.40 83 [286,] 11.44 82 [287,] 11.48 72 [288,] 11.52 69 [289,] 11.56 84 [290,] 11.60 57 [291,] 11.64 87 [292,] 11.68 72 [293,] 11.72 75 [294,] 11.76 62 [295,] 11.80 69 [296,] 11.84 68 [297,] 11.88 67 [298,] 11.92 65 [299,] 11.96 68 [300,] 12.00 84 [301,] 12.04 77 [302,] 12.08 66 [303,] 12.12 72 [304,] 12.16 70 [305,] 12.20 106 [306,] 12.24 77 [307,] 12.28 59 [308,] 12.32 66 [309,] 12.36 67 [310,] 12.40 66 [311,] 12.44 51 [312,] 12.48 72 [313,] 12.52 89 [314,] 12.56 76 [315,] 12.60 83 [316,] 12.64 83 [317,] 12.68 62 [318,] 12.72 74 [319,] 12.76 65 [320,] 12.80 72 [321,] 12.84 64 [322,] 12.88 69 [323,] 12.92 75 [324,] 12.96 80 [325,] 13.00 106 [326,] 13.04 88 [327,] 13.08 62 [328,] 13.12 70 [329,] 13.16 71 [330,] 13.20 77 [331,] 13.24 71 [332,] 13.28 107 [333,] 13.32 68 [334,] 13.36 78 [335,] 13.40 77 [336,] 13.44 75 [337,] 13.48 73 [338,] 13.52 49 [339,] 13.56 66 [340,] 13.60 82 [341,] 13.64 82 [342,] 13.68 85 [343,] 13.72 87 [344,] 13.76 73 [345,] 13.80 72 [346,] 13.84 67 [347,] 13.88 77 [348,] 13.92 72 [349,] 13.96 76 [350,] 14.00 89 [351,] 14.04 59 [352,] 14.08 75 [353,] 14.12 70 [354,] 14.16 77 [355,] 14.20 72 [356,] 14.24 77 [357,] 14.28 66 [358,] 14.32 78 [359,] 14.36 58 [360,] 14.40 83 [361,] 14.44 77 [362,] 14.48 63 [363,] 14.52 71 [364,] 14.56 75 [365,] 14.60 65 [366,] 14.64 64 [367,] 14.68 46 [368,] 14.72 54 [369,] 14.76 66 [370,] 14.80 86 [371,] 14.84 70 [372,] 14.88 52 [373,] 14.92 63 [374,] 14.96 76 [375,] 15.00 58 [376,] 15.04 68 [377,] 15.08 78 [378,] 15.12 68 [379,] 15.16 78 [380,] 15.20 59 [381,] 15.24 78 [382,] 15.28 72 [383,] 15.32 75 [384,] 15.36 68 [385,] 15.40 71 [386,] 15.44 74 [387,] 15.48 70 [388,] 15.52 72 [389,] 15.56 66 [390,] 15.60 70 [391,] 15.64 69 [392,] 15.68 58 [393,] 15.72 71 [394,] 15.76 75 [395,] 15.80 77 [396,] 15.84 58 [397,] 15.88 92 [398,] 15.92 94 [399,] 15.96 65 [400,] 16.00 65 [401,] 16.04 71 [402,] 16.08 78 [403,] 16.12 76 [404,] 16.16 83 [405,] 16.20 73 [406,] 16.24 76 [407,] 16.28 86 [408,] 16.32 76 [409,] 16.36 71 [410,] 16.40 56 [411,] 16.44 68 [412,] 16.48 61 [413,] 16.52 68 [414,] 16.56 57 [415,] 16.60 85 [416,] 16.64 71 [417,] 16.68 81 [418,] 16.72 76 [419,] 16.76 66 [420,] 16.80 76 [421,] 16.84 73 [422,] 16.88 55 [423,] 16.92 63 [424,] 16.96 68 [425,] 17.00 63 [426,] 17.04 66 [427,] 17.08 67 [428,] 17.12 81 [429,] 17.16 34 [430,] 17.20 78 [431,] 17.24 71 [432,] 17.28 59 [433,] 17.32 64 [434,] 17.36 66 [435,] 17.40 76 [436,] 17.44 52 [437,] 17.48 70 [438,] 17.52 59 [439,] 17.56 55 [440,] 17.60 66 [441,] 17.64 71 [442,] 17.68 60 [443,] 17.72 83 [444,] 17.76 70 [445,] 17.80 64 [446,] 17.84 102 [447,] 17.88 46 [448,] 17.92 68 [449,] 17.96 64 [450,] 18.00 92 [451,] 18.04 79 [452,] 18.08 74 [453,] 18.12 67 [454,] 18.16 57 [455,] 18.20 65 [456,] 18.24 76 [457,] 18.28 67 [458,] 18.32 75 [459,] 18.36 59 [460,] 18.40 65 [461,] 18.44 74 [462,] 18.48 54 [463,] 18.52 79 [464,] 18.56 55 [465,] 18.60 91 [466,] 18.64 65 [467,] 18.68 69 [468,] 18.72 82 [469,] 18.76 70 [470,] 18.80 64 [471,] 18.84 71 [472,] 18.88 71 [473,] 18.92 87 [474,] 18.96 68 [475,] 19.00 68 [476,] 19.04 64 [477,] 19.08 73 [478,] 19.12 60 [479,] 19.16 75 [480,] 19.20 52 [481,] 19.24 74 [482,] 19.28 47 [483,] 19.32 63 [484,] 19.36 70 [485,] 19.40 53 [486,] 19.44 95 [487,] 19.48 66 [488,] 19.52 71 [489,] 19.56 69 [490,] 19.60 56 [491,] 19.64 70 [492,] 19.68 70 [493,] 19.72 76 [494,] 19.76 82 [495,] 19.80 85 [496,] 19.84 71 [497,] 19.88 61 [498,] 19.92 69 [499,] 19.96 54 [500,] 20.00 58 [501,] 20.04 43 [502,] 20.08 80 [503,] 20.12 54 [504,] 20.16 84 [505,] 20.20 89 [506,] 20.24 77 [507,] 20.28 64 [508,] 20.32 71 [509,] 20.36 69 [510,] 20.40 63 [511,] 20.44 60 [512,] 20.48 68 [513,] 20.52 75 [514,] 20.56 64 [515,] 20.60 66 [516,] 20.64 73 [517,] 20.68 59 [518,] 20.72 58 [519,] 20.76 63 [520,] 20.80 78 [521,] 20.84 49 [522,] 20.88 51 [523,] 20.92 68 [524,] 20.96 59 [525,] 21.00 77 [526,] 21.04 73 [527,] 21.08 56 [528,] 21.12 73 [529,] 21.16 68 [530,] 21.20 68 [531,] 21.24 73 [532,] 21.28 70 [533,] 21.32 65 [534,] 21.36 68 [535,] 21.40 65 [536,] 21.44 72 [537,] 21.48 65 [538,] 21.52 69 [539,] 21.56 71 [540,] 21.60 65 [541,] 21.64 74 [542,] 21.68 65 [543,] 21.72 70 [544,] 21.76 72 [545,] 21.80 54 [546,] 21.84 71 [547,] 21.88 53 [548,] 21.92 88 [549,] 21.96 69 [550,] 22.00 80 [551,] 22.04 80 [552,] 22.08 75 [553,] 22.12 70 [554,] 22.16 69 [555,] 22.20 59 [556,] 22.24 70 [557,] 22.28 62 [558,] 22.32 69 [559,] 22.36 71 [560,] 22.40 50 [561,] 22.44 69 [562,] 22.48 62 [563,] 22.52 88 [564,] 22.56 77 [565,] 22.60 53 [566,] 22.64 59 [567,] 22.68 68 [568,] 22.72 61 [569,] 22.76 64 [570,] 22.80 66 [571,] 22.84 58 [572,] 22.88 77 [573,] 22.92 78 [574,] 22.96 45 [575,] 23.00 64 [576,] 23.04 58 [577,] 23.08 70 [578,] 23.12 66 [579,] 23.16 55 [580,] 23.20 61 [581,] 23.24 68 [582,] 23.28 70 [583,] 23.32 77 [584,] 23.36 66 [585,] 23.40 62 [586,] 23.44 67 [587,] 23.48 67 [588,] 23.52 78 [589,] 23.56 66 [590,] 23.60 66 [591,] 23.64 57 [592,] 23.68 58 [593,] 23.72 42 [594,] 23.76 89 [595,] 23.80 64 [596,] 23.84 58 [597,] 23.88 68 [598,] 23.92 65 [599,] 23.96 57 [600,] 24.00 64 [601,] 24.04 75 [602,] 24.08 65 [603,] 24.12 58 [604,] 24.16 72 [605,] 24.20 63 [606,] 24.24 66 [607,] 24.28 70 [608,] 24.32 66 [609,] 24.36 70 [610,] 24.40 71 [611,] 24.44 71 [612,] 24.48 58 [613,] 24.52 77 [614,] 24.56 66 [615,] 24.60 61 [616,] 24.64 65 [617,] 24.68 66 [618,] 24.72 76 [619,] 24.76 64 [620,] 24.80 69 [621,] 24.84 73 [622,] 24.88 63 [623,] 24.92 51 [624,] 24.96 80 [625,] 25.00 61 [626,] 25.04 62 [627,] 25.08 71 [628,] 25.12 55 [629,] 25.16 98 [630,] 25.20 59 [631,] 25.24 60 [632,] 25.28 54 [633,] 25.32 74 [634,] 25.36 70 [635,] 25.40 56 [636,] 25.44 61 [637,] 25.48 76 [638,] 25.52 65 [639,] 25.56 43 [640,] 25.60 57 [641,] 25.64 67 [642,] 25.68 70 [643,] 25.72 61 [644,] 25.76 60 [645,] 25.80 70 [646,] 25.84 60 [647,] 25.88 48 [648,] 25.92 64 [649,] 25.96 51 [650,] 26.00 73 [651,] 26.04 60 [652,] 26.08 70 [653,] 26.12 54 [654,] 26.16 59 [655,] 26.20 60 [656,] 26.24 53 [657,] 26.28 56 [658,] 26.32 54 [659,] 26.36 68 [660,] 26.40 86 [661,] 26.44 73 [662,] 26.48 49 [663,] 26.52 58 [664,] 26.56 63 [665,] 26.60 48 [666,] 26.64 68 [667,] 26.68 68 [668,] 26.72 59 [669,] 26.76 48 [670,] 26.80 62 [671,] 26.84 73 [672,] 26.88 58 [673,] 26.92 58 [674,] 26.96 59 [675,] 27.00 52 [676,] 27.04 58 [677,] 27.08 72 [678,] 27.12 93 [679,] 27.16 62 [680,] 27.20 79 [681,] 27.24 49 [682,] 27.28 61 [683,] 27.32 56 [684,] 27.36 86 [685,] 27.40 58 [686,] 27.44 56 [687,] 27.48 70 [688,] 27.52 50 [689,] 27.56 66 [690,] 27.60 62 [691,] 27.64 61 [692,] 27.68 68 [693,] 27.72 65 [694,] 27.76 64 [695,] 27.80 85 [696,] 27.84 55 [697,] 27.88 56 [698,] 27.92 59 [699,] 27.96 55 [700,] 28.00 63 [701,] 28.04 73 [702,] 28.08 70 [703,] 28.12 59 [704,] 28.16 59 [705,] 28.20 51 [706,] 28.24 66 [707,] 28.28 51 [708,] 28.32 66 [709,] 28.36 50 [710,] 28.40 85 [711,] 28.44 77 [712,] 28.48 80 [713,] 28.52 75 [714,] 28.56 66 [715,] 28.60 50 [716,] 28.64 66 [717,] 28.68 59 [718,] 28.72 56 [719,] 28.76 63 [720,] 28.80 59 [721,] 28.84 49 [722,] 28.88 56 [723,] 28.92 67 [724,] 28.96 66 [725,] 29.00 52 [726,] 29.04 41 [727,] 29.08 74 [728,] 29.12 54 [729,] 29.16 62 [730,] 29.20 64 [731,] 29.24 50 [732,] 29.28 58 [733,] 29.32 67 [734,] 29.36 43 [735,] 29.40 58 [736,] 29.44 61 [737,] 29.48 59 [738,] 29.52 54 [739,] 29.56 54 [740,] 29.60 67 [741,] 29.64 65 [742,] 29.68 61 [743,] 29.72 52 [744,] 29.76 46 [745,] 29.80 57 [746,] 29.84 67 [747,] 29.88 67 [748,] 29.92 53 [749,] 29.96 54 [750,] 30.00 66 [751,] 30.04 52 [752,] 30.08 45 [753,] 30.12 59 [754,] 30.16 48 [755,] 30.20 68 [756,] 30.24 67 [757,] 30.28 72 [758,] 30.32 51 [759,] 30.36 53 [760,] 30.40 55 [761,] 30.44 58 [762,] 30.48 62 [763,] 30.52 60 [764,] 30.56 52 [765,] 30.60 58 [766,] 30.64 52 [767,] 30.68 50 [768,] 30.72 56 [769,] 30.76 69 [770,] 30.80 79 [771,] 30.84 47 [772,] 30.88 54 [773,] 30.92 62 [774,] 30.96 76 [775,] 31.00 54 [776,] 31.04 54 [777,] 31.08 60 [778,] 31.12 61 [779,] 31.16 66 [780,] 31.20 56 [781,] 31.24 59 [782,] 31.28 57 [783,] 31.32 51 [784,] 31.36 65 [785,] 31.40 55 [786,] 31.44 83 [787,] 31.48 78 [788,] 31.52 67 [789,] 31.56 74 [790,] 31.60 80 [791,] 31.64 58 [792,] 31.68 65 [793,] 31.72 59 [794,] 31.76 65 [795,] 31.80 52 [796,] 31.84 68 [797,] 31.88 48 [798,] 31.92 83 [799,] 31.96 41 [800,] 32.00 55 [801,] 32.04 54 [802,] 32.08 65 [803,] 32.12 52 [804,] 32.16 60 [805,] 32.20 47 [806,] 32.24 57 [807,] 32.28 52 [808,] 32.32 70 [809,] 32.36 93 [810,] 32.40 63 [811,] 32.44 64 [812,] 32.48 54 [813,] 32.52 64 [814,] 32.56 74 [815,] 32.60 54 [816,] 32.64 69 [817,] 32.68 60 [818,] 32.72 52 [819,] 32.76 56 [820,] 32.80 62 [821,] 32.84 53 [822,] 32.88 63 [823,] 32.92 50 [824,] 32.96 54 [825,] 33.00 59 [826,] 33.04 59 [827,] 33.08 53 [828,] 33.12 60 [829,] 33.16 66 [830,] 33.20 52 [831,] 33.24 68 [832,] 33.28 63 [833,] 33.32 46 [834,] 33.36 53 [835,] 33.40 62 [836,] 33.44 61 [837,] 33.48 64 [838,] 33.52 64 [839,] 33.56 50 [840,] 33.60 56 [841,] 33.64 66 [842,] 33.68 65 [843,] 33.72 58 [844,] 33.76 63 [845,] 33.80 81 [846,] 33.84 46 [847,] 33.88 60 [848,] 33.92 69 [849,] 33.96 50 [850,] 34.00 64 [851,] 34.04 46 [852,] 34.08 72 [853,] 34.12 72 [854,] 34.16 46 [855,] 34.20 64 [856,] 34.24 56 [857,] 34.28 70 [858,] 34.32 76 [859,] 34.36 51 [860,] 34.40 65 [861,] 34.44 62 [862,] 34.48 66 [863,] 34.52 64 [864,] 34.56 78 [865,] 34.60 51 [866,] 34.64 58 [867,] 34.68 42 [868,] 34.72 59 [869,] 34.76 64 [870,] 34.80 59 [871,] 34.84 75 [872,] 34.88 58 [873,] 34.92 65 [874,] 34.96 48 [875,] 35.00 64 [876,] 35.04 44 [877,] 35.08 64 [878,] 35.12 62 [879,] 35.16 54 [880,] 35.20 58 [881,] 35.24 40 [882,] 35.28 63 [883,] 35.32 54 [884,] 35.36 68 [885,] 35.40 74 [886,] 35.44 62 [887,] 35.48 48 [888,] 35.52 49 [889,] 35.56 63 [890,] 35.60 56 [891,] 35.64 63 [892,] 35.68 57 [893,] 35.72 41 [894,] 35.76 59 [895,] 35.80 47 [896,] 35.84 61 [897,] 35.88 61 [898,] 35.92 64 [899,] 35.96 57 [900,] 36.00 69 [901,] 36.04 74 [902,] 36.08 59 [903,] 36.12 47 [904,] 36.16 56 [905,] 36.20 64 [906,] 36.24 60 [907,] 36.28 52 [908,] 36.32 42 [909,] 36.36 60 [910,] 36.40 67 [911,] 36.44 66 [912,] 36.48 47 [913,] 36.52 65 [914,] 36.56 80 [915,] 36.60 50 [916,] 36.64 61 [917,] 36.68 66 [918,] 36.72 50 [919,] 36.76 73 [920,] 36.80 62 [921,] 36.84 66 [922,] 36.88 69 [923,] 36.92 75 [924,] 36.96 69 [925,] 37.00 67 [926,] 37.04 74 [927,] 37.08 71 [928,] 37.12 64 [929,] 37.16 58 [930,] 37.20 57 [931,] 37.24 57 [932,] 37.28 50 [933,] 37.32 51 [934,] 37.36 63 [935,] 37.40 83 [936,] 37.44 60 [937,] 37.48 66 [938,] 37.52 42 [939,] 37.56 47 [940,] 37.60 48 [941,] 37.64 67 [942,] 37.68 56 [943,] 37.72 64 [944,] 37.76 50 [945,] 37.80 62 [946,] 37.84 58 [947,] 37.88 53 [948,] 37.92 53 [949,] 37.96 69 [950,] 38.00 58 [951,] 38.04 77 [952,] 38.08 78 [953,] 38.12 46 [954,] 38.16 45 [955,] 38.20 41 [956,] 38.24 57 [957,] 38.28 65 [958,] 38.32 67 [959,] 38.36 50 [960,] 38.40 70 [961,] 38.44 57 [962,] 38.48 77 [963,] 38.52 52 [964,] 38.56 65 [965,] 38.60 43 [966,] 38.64 64 [967,] 38.68 62 [968,] 38.72 47 [969,] 38.76 64 [970,] 38.80 61 [971,] 38.84 74 [972,] 38.88 61 [973,] 38.92 65 [974,] 38.96 56 [975,] 39.00 63 [976,] 39.04 56 [977,] 39.08 58 [978,] 39.12 60 [979,] 39.16 62 [980,] 39.20 74 [981,] 39.24 71 [982,] 39.28 72 [983,] 39.32 59 [984,] 39.36 55 [985,] 39.40 55 [986,] 39.44 50 [987,] 39.48 53 [988,] 39.52 68 [989,] 39.56 52 [990,] 39.60 57 [991,] 39.64 64 [992,] 39.68 63 [993,] 39.72 73 [994,] 39.76 51 [995,] 39.80 60 [996,] 39.84 68 [997,] 39.88 55 [998,] 39.92 49 [999,] 39.96 66 [1000,] 40.00 59 $`17_TL (PMT)` [,1] [,2] [1,] 0.884 20 [2,] 1.768 3 [3,] 2.652 4 [4,] 3.536 1 [5,] 4.420 6 [6,] 5.304 22 [7,] 6.188 1 [8,] 7.072 10 [9,] 7.956 5 [10,] 8.840 10 [11,] 9.724 2 [12,] 10.608 13 [13,] 11.492 8 [14,] 12.376 2 [15,] 13.260 4 [16,] 14.144 8 [17,] 15.028 3 [18,] 15.912 4 [19,] 16.796 7 [20,] 17.680 3 [21,] 18.564 9 [22,] 19.448 1 [23,] 20.332 1 [24,] 21.216 5 [25,] 22.100 8 [26,] 22.984 6 [27,] 23.868 4 [28,] 24.752 7 [29,] 25.636 6 [30,] 26.520 2 [31,] 27.404 14 [32,] 28.288 4 [33,] 29.172 17 [34,] 30.056 3 [35,] 30.940 4 [36,] 31.824 2 [37,] 32.708 3 [38,] 33.592 5 [39,] 34.476 2 [40,] 35.360 1 [41,] 36.244 4 [42,] 37.128 4 [43,] 38.012 4 [44,] 38.896 6 [45,] 39.780 7 [46,] 40.664 4 [47,] 41.548 4 [48,] 42.432 3 [49,] 43.316 4 [50,] 44.200 3 [51,] 45.084 8 [52,] 45.968 1 [53,] 46.852 6 [54,] 47.736 0 [55,] 48.620 1 [56,] 49.504 1 [57,] 50.388 6 [58,] 51.272 3 [59,] 52.156 1 [60,] 53.040 3 [61,] 53.924 9 [62,] 54.808 3 [63,] 55.692 0 [64,] 56.576 8 [65,] 57.460 6 [66,] 58.344 8 [67,] 59.228 7 [68,] 60.112 1 [69,] 60.996 15 [70,] 61.880 3 [71,] 62.764 18 [72,] 63.648 2 [73,] 64.532 8 [74,] 65.416 6 [75,] 66.300 5 [76,] 67.184 6 [77,] 68.068 5 [78,] 68.952 6 [79,] 69.836 7 [80,] 70.720 7 [81,] 71.604 10 [82,] 72.488 18 [83,] 73.372 25 [84,] 74.256 9 [85,] 75.140 13 [86,] 76.024 9 [87,] 76.908 15 [88,] 77.792 14 [89,] 78.676 21 [90,] 79.560 9 [91,] 80.444 24 [92,] 81.328 9 [93,] 82.212 10 [94,] 83.096 7 [95,] 83.980 16 [96,] 84.864 16 [97,] 85.748 18 [98,] 86.632 23 [99,] 87.516 18 [100,] 88.400 39 [101,] 89.284 26 [102,] 90.168 16 [103,] 91.052 35 [104,] 91.936 31 [105,] 92.820 27 [106,] 93.704 26 [107,] 94.588 34 [108,] 95.472 38 [109,] 96.356 56 [110,] 97.240 44 [111,] 98.124 36 [112,] 99.008 59 [113,] 99.892 67 [114,] 100.776 58 [115,] 101.660 75 [116,] 102.544 55 [117,] 103.428 92 [118,] 104.312 55 [119,] 105.196 63 [120,] 106.080 88 [121,] 106.964 117 [122,] 107.848 95 [123,] 108.732 105 [124,] 109.616 140 [125,] 110.500 154 [126,] 111.384 115 [127,] 112.268 147 [128,] 113.152 182 [129,] 114.036 149 [130,] 114.920 157 [131,] 115.804 180 [132,] 116.688 206 [133,] 117.572 195 [134,] 118.456 213 [135,] 119.340 219 [136,] 120.224 230 [137,] 121.108 259 [138,] 121.992 267 [139,] 122.876 283 [140,] 123.760 308 [141,] 124.644 356 [142,] 125.528 346 [143,] 126.412 317 [144,] 127.296 363 [145,] 128.180 420 [146,] 129.064 394 [147,] 129.948 447 [148,] 130.832 478 [149,] 131.716 440 [150,] 132.600 460 [151,] 133.484 541 [152,] 134.368 518 [153,] 135.252 530 [154,] 136.136 567 [155,] 137.020 555 [156,] 137.904 574 [157,] 138.788 577 [158,] 139.672 584 [159,] 140.556 626 [160,] 141.440 673 [161,] 142.324 618 [162,] 143.208 617 [163,] 144.092 631 [164,] 144.976 699 [165,] 145.860 667 [166,] 146.744 673 [167,] 147.628 620 [168,] 148.512 653 [169,] 149.396 583 [170,] 150.280 672 [171,] 151.164 606 [172,] 152.048 661 [173,] 152.932 605 [174,] 153.816 608 [175,] 154.700 638 [176,] 155.584 616 [177,] 156.468 559 [178,] 157.352 573 [179,] 158.236 596 [180,] 159.120 635 [181,] 160.004 646 [182,] 160.888 634 [183,] 161.772 650 [184,] 162.656 593 [185,] 163.540 584 [186,] 164.424 658 [187,] 165.308 570 [188,] 166.192 620 [189,] 167.076 648 [190,] 167.960 670 [191,] 168.844 638 [192,] 169.728 668 [193,] 170.612 661 [194,] 171.496 646 [195,] 172.380 644 [196,] 173.264 655 [197,] 174.148 671 [198,] 175.032 671 [199,] 175.916 691 [200,] 176.800 640 [201,] 177.684 715 [202,] 178.568 653 [203,] 179.452 649 [204,] 180.336 715 [205,] 181.220 686 [206,] 182.104 625 [207,] 182.988 708 [208,] 183.872 644 [209,] 184.756 735 [210,] 185.640 725 [211,] 186.524 730 [212,] 187.408 668 [213,] 188.292 709 [214,] 189.176 699 [215,] 190.060 728 [216,] 190.944 701 [217,] 191.828 752 [218,] 192.712 775 [219,] 193.596 772 [220,] 194.480 748 [221,] 195.364 783 [222,] 196.248 752 [223,] 197.132 788 [224,] 198.016 822 [225,] 198.900 825 [226,] 199.784 784 [227,] 200.668 854 [228,] 201.552 733 [229,] 202.436 879 [230,] 203.320 848 [231,] 204.204 853 [232,] 205.088 808 [233,] 205.972 855 [234,] 206.856 919 [235,] 207.740 913 [236,] 208.624 770 [237,] 209.508 839 [238,] 210.392 817 [239,] 211.276 960 [240,] 212.160 897 [241,] 213.044 879 [242,] 213.928 859 [243,] 214.812 849 [244,] 215.696 837 [245,] 216.580 907 [246,] 217.464 854 [247,] 218.348 895 [248,] 219.232 873 [249,] 220.116 832 [250,] 221.000 266 $`18_OSL (PMT)` [,1] [,2] [1,] 0.04 16684 [2,] 0.08 14410 [3,] 0.12 11961 [4,] 0.16 10396 [5,] 0.20 8549 [6,] 0.24 7578 [7,] 0.28 6513 [8,] 0.32 5633 [9,] 0.36 5106 [10,] 0.40 4259 [11,] 0.44 3758 [12,] 0.48 3379 [13,] 0.52 2941 [14,] 0.56 2653 [15,] 0.60 2286 [16,] 0.64 2111 [17,] 0.68 1816 [18,] 0.72 1628 [19,] 0.76 1605 [20,] 0.80 1337 [21,] 0.84 1310 [22,] 0.88 1090 [23,] 0.92 1044 [24,] 0.96 922 [25,] 1.00 897 [26,] 1.04 864 [27,] 1.08 756 [28,] 1.12 672 [29,] 1.16 688 [30,] 1.20 580 [31,] 1.24 573 [32,] 1.28 603 [33,] 1.32 517 [34,] 1.36 501 [35,] 1.40 517 [36,] 1.44 404 [37,] 1.48 446 [38,] 1.52 404 [39,] 1.56 418 [40,] 1.60 362 [41,] 1.64 378 [42,] 1.68 372 [43,] 1.72 353 [44,] 1.76 290 [45,] 1.80 291 [46,] 1.84 307 [47,] 1.88 280 [48,] 1.92 319 [49,] 1.96 291 [50,] 2.00 299 [51,] 2.04 301 [52,] 2.08 276 [53,] 2.12 301 [54,] 2.16 267 [55,] 2.20 285 [56,] 2.24 245 [57,] 2.28 233 [58,] 2.32 257 [59,] 2.36 227 [60,] 2.40 231 [61,] 2.44 248 [62,] 2.48 253 [63,] 2.52 242 [64,] 2.56 238 [65,] 2.60 270 [66,] 2.64 209 [67,] 2.68 215 [68,] 2.72 223 [69,] 2.76 251 [70,] 2.80 198 [71,] 2.84 214 [72,] 2.88 233 [73,] 2.92 229 [74,] 2.96 239 [75,] 3.00 210 [76,] 3.04 196 [77,] 3.08 208 [78,] 3.12 216 [79,] 3.16 180 [80,] 3.20 206 [81,] 3.24 180 [82,] 3.28 231 [83,] 3.32 229 [84,] 3.36 200 [85,] 3.40 166 [86,] 3.44 212 [87,] 3.48 221 [88,] 3.52 193 [89,] 3.56 178 [90,] 3.60 177 [91,] 3.64 194 [92,] 3.68 198 [93,] 3.72 169 [94,] 3.76 179 [95,] 3.80 193 [96,] 3.84 169 [97,] 3.88 153 [98,] 3.92 183 [99,] 3.96 161 [100,] 4.00 185 [101,] 4.04 151 [102,] 4.08 161 [103,] 4.12 185 [104,] 4.16 183 [105,] 4.20 175 [106,] 4.24 163 [107,] 4.28 171 [108,] 4.32 157 [109,] 4.36 193 [110,] 4.40 164 [111,] 4.44 179 [112,] 4.48 167 [113,] 4.52 219 [114,] 4.56 176 [115,] 4.60 155 [116,] 4.64 176 [117,] 4.68 151 [118,] 4.72 175 [119,] 4.76 151 [120,] 4.80 173 [121,] 4.84 142 [122,] 4.88 145 [123,] 4.92 146 [124,] 4.96 172 [125,] 5.00 142 [126,] 5.04 136 [127,] 5.08 141 [128,] 5.12 183 [129,] 5.16 164 [130,] 5.20 147 [131,] 5.24 161 [132,] 5.28 171 [133,] 5.32 135 [134,] 5.36 137 [135,] 5.40 164 [136,] 5.44 179 [137,] 5.48 154 [138,] 5.52 168 [139,] 5.56 159 [140,] 5.60 161 [141,] 5.64 167 [142,] 5.68 145 [143,] 5.72 151 [144,] 5.76 139 [145,] 5.80 169 [146,] 5.84 176 [147,] 5.88 136 [148,] 5.92 167 [149,] 5.96 143 [150,] 6.00 150 [151,] 6.04 149 [152,] 6.08 149 [153,] 6.12 149 [154,] 6.16 135 [155,] 6.20 132 [156,] 6.24 151 [157,] 6.28 152 [158,] 6.32 142 [159,] 6.36 142 [160,] 6.40 134 [161,] 6.44 134 [162,] 6.48 132 [163,] 6.52 142 [164,] 6.56 133 [165,] 6.60 114 [166,] 6.64 154 [167,] 6.68 119 [168,] 6.72 117 [169,] 6.76 132 [170,] 6.80 133 [171,] 6.84 122 [172,] 6.88 119 [173,] 6.92 135 [174,] 6.96 144 [175,] 7.00 130 [176,] 7.04 145 [177,] 7.08 121 [178,] 7.12 109 [179,] 7.16 135 [180,] 7.20 124 [181,] 7.24 142 [182,] 7.28 121 [183,] 7.32 123 [184,] 7.36 150 [185,] 7.40 134 [186,] 7.44 129 [187,] 7.48 144 [188,] 7.52 131 [189,] 7.56 143 [190,] 7.60 132 [191,] 7.64 142 [192,] 7.68 136 [193,] 7.72 119 [194,] 7.76 115 [195,] 7.80 107 [196,] 7.84 115 [197,] 7.88 145 [198,] 7.92 146 [199,] 7.96 113 [200,] 8.00 146 [201,] 8.04 127 [202,] 8.08 123 [203,] 8.12 147 [204,] 8.16 131 [205,] 8.20 136 [206,] 8.24 166 [207,] 8.28 139 [208,] 8.32 133 [209,] 8.36 133 [210,] 8.40 140 [211,] 8.44 113 [212,] 8.48 107 [213,] 8.52 135 [214,] 8.56 128 [215,] 8.60 123 [216,] 8.64 113 [217,] 8.68 116 [218,] 8.72 109 [219,] 8.76 125 [220,] 8.80 123 [221,] 8.84 128 [222,] 8.88 128 [223,] 8.92 123 [224,] 8.96 91 [225,] 9.00 123 [226,] 9.04 114 [227,] 9.08 124 [228,] 9.12 127 [229,] 9.16 122 [230,] 9.20 105 [231,] 9.24 112 [232,] 9.28 101 [233,] 9.32 132 [234,] 9.36 122 [235,] 9.40 120 [236,] 9.44 113 [237,] 9.48 118 [238,] 9.52 104 [239,] 9.56 139 [240,] 9.60 122 [241,] 9.64 110 [242,] 9.68 91 [243,] 9.72 122 [244,] 9.76 124 [245,] 9.80 125 [246,] 9.84 98 [247,] 9.88 130 [248,] 9.92 106 [249,] 9.96 118 [250,] 10.00 122 [251,] 10.04 117 [252,] 10.08 119 [253,] 10.12 111 [254,] 10.16 96 [255,] 10.20 112 [256,] 10.24 112 [257,] 10.28 136 [258,] 10.32 99 [259,] 10.36 133 [260,] 10.40 115 [261,] 10.44 118 [262,] 10.48 115 [263,] 10.52 112 [264,] 10.56 121 [265,] 10.60 110 [266,] 10.64 128 [267,] 10.68 120 [268,] 10.72 110 [269,] 10.76 88 [270,] 10.80 112 [271,] 10.84 112 [272,] 10.88 115 [273,] 10.92 141 [274,] 10.96 97 [275,] 11.00 110 [276,] 11.04 117 [277,] 11.08 109 [278,] 11.12 111 [279,] 11.16 116 [280,] 11.20 124 [281,] 11.24 123 [282,] 11.28 118 [283,] 11.32 119 [284,] 11.36 99 [285,] 11.40 124 [286,] 11.44 101 [287,] 11.48 111 [288,] 11.52 103 [289,] 11.56 92 [290,] 11.60 103 [291,] 11.64 91 [292,] 11.68 103 [293,] 11.72 123 [294,] 11.76 123 [295,] 11.80 80 [296,] 11.84 125 [297,] 11.88 101 [298,] 11.92 100 [299,] 11.96 99 [300,] 12.00 117 [301,] 12.04 107 [302,] 12.08 98 [303,] 12.12 122 [304,] 12.16 105 [305,] 12.20 115 [306,] 12.24 106 [307,] 12.28 97 [308,] 12.32 99 [309,] 12.36 107 [310,] 12.40 108 [311,] 12.44 93 [312,] 12.48 89 [313,] 12.52 109 [314,] 12.56 113 [315,] 12.60 124 [316,] 12.64 103 [317,] 12.68 111 [318,] 12.72 138 [319,] 12.76 113 [320,] 12.80 81 [321,] 12.84 105 [322,] 12.88 125 [323,] 12.92 116 [324,] 12.96 132 [325,] 13.00 118 [326,] 13.04 111 [327,] 13.08 102 [328,] 13.12 102 [329,] 13.16 90 [330,] 13.20 99 [331,] 13.24 110 [332,] 13.28 106 [333,] 13.32 95 [334,] 13.36 126 [335,] 13.40 84 [336,] 13.44 101 [337,] 13.48 117 [338,] 13.52 119 [339,] 13.56 131 [340,] 13.60 107 [341,] 13.64 110 [342,] 13.68 83 [343,] 13.72 101 [344,] 13.76 102 [345,] 13.80 102 [346,] 13.84 112 [347,] 13.88 115 [348,] 13.92 88 [349,] 13.96 127 [350,] 14.00 105 [351,] 14.04 110 [352,] 14.08 108 [353,] 14.12 105 [354,] 14.16 96 [355,] 14.20 94 [356,] 14.24 103 [357,] 14.28 111 [358,] 14.32 98 [359,] 14.36 102 [360,] 14.40 106 [361,] 14.44 105 [362,] 14.48 101 [363,] 14.52 114 [364,] 14.56 103 [365,] 14.60 89 [366,] 14.64 97 [367,] 14.68 110 [368,] 14.72 102 [369,] 14.76 86 [370,] 14.80 122 [371,] 14.84 110 [372,] 14.88 99 [373,] 14.92 133 [374,] 14.96 102 [375,] 15.00 101 [376,] 15.04 129 [377,] 15.08 96 [378,] 15.12 89 [379,] 15.16 108 [380,] 15.20 105 [381,] 15.24 104 [382,] 15.28 96 [383,] 15.32 95 [384,] 15.36 120 [385,] 15.40 101 [386,] 15.44 99 [387,] 15.48 106 [388,] 15.52 90 [389,] 15.56 80 [390,] 15.60 90 [391,] 15.64 98 [392,] 15.68 91 [393,] 15.72 103 [394,] 15.76 101 [395,] 15.80 85 [396,] 15.84 87 [397,] 15.88 95 [398,] 15.92 105 [399,] 15.96 113 [400,] 16.00 103 [401,] 16.04 83 [402,] 16.08 101 [403,] 16.12 111 [404,] 16.16 110 [405,] 16.20 110 [406,] 16.24 89 [407,] 16.28 89 [408,] 16.32 95 [409,] 16.36 120 [410,] 16.40 94 [411,] 16.44 99 [412,] 16.48 117 [413,] 16.52 83 [414,] 16.56 98 [415,] 16.60 99 [416,] 16.64 84 [417,] 16.68 92 [418,] 16.72 76 [419,] 16.76 92 [420,] 16.80 119 [421,] 16.84 100 [422,] 16.88 87 [423,] 16.92 109 [424,] 16.96 99 [425,] 17.00 118 [426,] 17.04 114 [427,] 17.08 104 [428,] 17.12 83 [429,] 17.16 96 [430,] 17.20 102 [431,] 17.24 113 [432,] 17.28 98 [433,] 17.32 91 [434,] 17.36 97 [435,] 17.40 126 [436,] 17.44 104 [437,] 17.48 90 [438,] 17.52 91 [439,] 17.56 98 [440,] 17.60 88 [441,] 17.64 86 [442,] 17.68 105 [443,] 17.72 99 [444,] 17.76 89 [445,] 17.80 100 [446,] 17.84 104 [447,] 17.88 97 [448,] 17.92 106 [449,] 17.96 96 [450,] 18.00 91 [451,] 18.04 111 [452,] 18.08 88 [453,] 18.12 92 [454,] 18.16 113 [455,] 18.20 102 [456,] 18.24 101 [457,] 18.28 92 [458,] 18.32 84 [459,] 18.36 99 [460,] 18.40 102 [461,] 18.44 121 [462,] 18.48 111 [463,] 18.52 98 [464,] 18.56 98 [465,] 18.60 106 [466,] 18.64 100 [467,] 18.68 115 [468,] 18.72 122 [469,] 18.76 84 [470,] 18.80 86 [471,] 18.84 97 [472,] 18.88 90 [473,] 18.92 100 [474,] 18.96 91 [475,] 19.00 90 [476,] 19.04 114 [477,] 19.08 115 [478,] 19.12 71 [479,] 19.16 105 [480,] 19.20 104 [481,] 19.24 88 [482,] 19.28 92 [483,] 19.32 91 [484,] 19.36 85 [485,] 19.40 102 [486,] 19.44 94 [487,] 19.48 79 [488,] 19.52 112 [489,] 19.56 93 [490,] 19.60 82 [491,] 19.64 111 [492,] 19.68 119 [493,] 19.72 117 [494,] 19.76 114 [495,] 19.80 116 [496,] 19.84 80 [497,] 19.88 90 [498,] 19.92 91 [499,] 19.96 79 [500,] 20.00 110 [501,] 20.04 85 [502,] 20.08 105 [503,] 20.12 92 [504,] 20.16 97 [505,] 20.20 100 [506,] 20.24 88 [507,] 20.28 110 [508,] 20.32 94 [509,] 20.36 86 [510,] 20.40 81 [511,] 20.44 89 [512,] 20.48 76 [513,] 20.52 87 [514,] 20.56 90 [515,] 20.60 123 [516,] 20.64 66 [517,] 20.68 79 [518,] 20.72 94 [519,] 20.76 90 [520,] 20.80 95 [521,] 20.84 109 [522,] 20.88 111 [523,] 20.92 76 [524,] 20.96 85 [525,] 21.00 96 [526,] 21.04 86 [527,] 21.08 89 [528,] 21.12 97 [529,] 21.16 102 [530,] 21.20 93 [531,] 21.24 92 [532,] 21.28 84 [533,] 21.32 91 [534,] 21.36 86 [535,] 21.40 83 [536,] 21.44 82 [537,] 21.48 73 [538,] 21.52 110 [539,] 21.56 84 [540,] 21.60 90 [541,] 21.64 91 [542,] 21.68 89 [543,] 21.72 108 [544,] 21.76 91 [545,] 21.80 123 [546,] 21.84 93 [547,] 21.88 68 [548,] 21.92 99 [549,] 21.96 77 [550,] 22.00 80 [551,] 22.04 90 [552,] 22.08 70 [553,] 22.12 98 [554,] 22.16 111 [555,] 22.20 83 [556,] 22.24 83 [557,] 22.28 122 [558,] 22.32 85 [559,] 22.36 98 [560,] 22.40 82 [561,] 22.44 86 [562,] 22.48 95 [563,] 22.52 77 [564,] 22.56 93 [565,] 22.60 69 [566,] 22.64 97 [567,] 22.68 97 [568,] 22.72 95 [569,] 22.76 67 [570,] 22.80 87 [571,] 22.84 91 [572,] 22.88 89 [573,] 22.92 103 [574,] 22.96 91 [575,] 23.00 95 [576,] 23.04 92 [577,] 23.08 68 [578,] 23.12 59 [579,] 23.16 90 [580,] 23.20 86 [581,] 23.24 98 [582,] 23.28 72 [583,] 23.32 85 [584,] 23.36 105 [585,] 23.40 94 [586,] 23.44 91 [587,] 23.48 91 [588,] 23.52 71 [589,] 23.56 89 [590,] 23.60 90 [591,] 23.64 102 [592,] 23.68 82 [593,] 23.72 91 [594,] 23.76 85 [595,] 23.80 92 [596,] 23.84 92 [597,] 23.88 82 [598,] 23.92 91 [599,] 23.96 114 [600,] 24.00 91 [601,] 24.04 70 [602,] 24.08 79 [603,] 24.12 91 [604,] 24.16 98 [605,] 24.20 120 [606,] 24.24 92 [607,] 24.28 101 [608,] 24.32 84 [609,] 24.36 104 [610,] 24.40 84 [611,] 24.44 100 [612,] 24.48 89 [613,] 24.52 86 [614,] 24.56 79 [615,] 24.60 109 [616,] 24.64 97 [617,] 24.68 80 [618,] 24.72 85 [619,] 24.76 87 [620,] 24.80 119 [621,] 24.84 96 [622,] 24.88 86 [623,] 24.92 91 [624,] 24.96 93 [625,] 25.00 75 [626,] 25.04 73 [627,] 25.08 89 [628,] 25.12 90 [629,] 25.16 107 [630,] 25.20 98 [631,] 25.24 74 [632,] 25.28 81 [633,] 25.32 68 [634,] 25.36 91 [635,] 25.40 98 [636,] 25.44 82 [637,] 25.48 90 [638,] 25.52 82 [639,] 25.56 93 [640,] 25.60 94 [641,] 25.64 113 [642,] 25.68 82 [643,] 25.72 109 [644,] 25.76 89 [645,] 25.80 84 [646,] 25.84 91 [647,] 25.88 92 [648,] 25.92 93 [649,] 25.96 71 [650,] 26.00 75 [651,] 26.04 89 [652,] 26.08 78 [653,] 26.12 79 [654,] 26.16 97 [655,] 26.20 76 [656,] 26.24 89 [657,] 26.28 83 [658,] 26.32 101 [659,] 26.36 85 [660,] 26.40 94 [661,] 26.44 97 [662,] 26.48 90 [663,] 26.52 90 [664,] 26.56 77 [665,] 26.60 83 [666,] 26.64 96 [667,] 26.68 89 [668,] 26.72 101 [669,] 26.76 66 [670,] 26.80 80 [671,] 26.84 93 [672,] 26.88 101 [673,] 26.92 51 [674,] 26.96 91 [675,] 27.00 111 [676,] 27.04 71 [677,] 27.08 81 [678,] 27.12 98 [679,] 27.16 79 [680,] 27.20 88 [681,] 27.24 90 [682,] 27.28 88 [683,] 27.32 102 [684,] 27.36 81 [685,] 27.40 110 [686,] 27.44 92 [687,] 27.48 74 [688,] 27.52 84 [689,] 27.56 98 [690,] 27.60 73 [691,] 27.64 79 [692,] 27.68 81 [693,] 27.72 87 [694,] 27.76 82 [695,] 27.80 112 [696,] 27.84 96 [697,] 27.88 99 [698,] 27.92 98 [699,] 27.96 100 [700,] 28.00 59 [701,] 28.04 94 [702,] 28.08 86 [703,] 28.12 92 [704,] 28.16 72 [705,] 28.20 72 [706,] 28.24 90 [707,] 28.28 89 [708,] 28.32 74 [709,] 28.36 89 [710,] 28.40 82 [711,] 28.44 74 [712,] 28.48 113 [713,] 28.52 81 [714,] 28.56 91 [715,] 28.60 84 [716,] 28.64 81 [717,] 28.68 71 [718,] 28.72 96 [719,] 28.76 72 [720,] 28.80 103 [721,] 28.84 80 [722,] 28.88 82 [723,] 28.92 92 [724,] 28.96 80 [725,] 29.00 85 [726,] 29.04 85 [727,] 29.08 88 [728,] 29.12 87 [729,] 29.16 94 [730,] 29.20 85 [731,] 29.24 73 [732,] 29.28 88 [733,] 29.32 69 [734,] 29.36 81 [735,] 29.40 92 [736,] 29.44 78 [737,] 29.48 100 [738,] 29.52 87 [739,] 29.56 114 [740,] 29.60 66 [741,] 29.64 103 [742,] 29.68 82 [743,] 29.72 83 [744,] 29.76 71 [745,] 29.80 87 [746,] 29.84 77 [747,] 29.88 97 [748,] 29.92 73 [749,] 29.96 84 [750,] 30.00 91 [751,] 30.04 84 [752,] 30.08 74 [753,] 30.12 81 [754,] 30.16 74 [755,] 30.20 77 [756,] 30.24 91 [757,] 30.28 78 [758,] 30.32 85 [759,] 30.36 84 [760,] 30.40 77 [761,] 30.44 53 [762,] 30.48 77 [763,] 30.52 64 [764,] 30.56 80 [765,] 30.60 75 [766,] 30.64 87 [767,] 30.68 97 [768,] 30.72 72 [769,] 30.76 90 [770,] 30.80 85 [771,] 30.84 83 [772,] 30.88 79 [773,] 30.92 81 [774,] 30.96 68 [775,] 31.00 73 [776,] 31.04 73 [777,] 31.08 106 [778,] 31.12 88 [779,] 31.16 65 [780,] 31.20 85 [781,] 31.24 89 [782,] 31.28 81 [783,] 31.32 92 [784,] 31.36 85 [785,] 31.40 90 [786,] 31.44 90 [787,] 31.48 85 [788,] 31.52 91 [789,] 31.56 81 [790,] 31.60 87 [791,] 31.64 69 [792,] 31.68 78 [793,] 31.72 87 [794,] 31.76 106 [795,] 31.80 68 [796,] 31.84 68 [797,] 31.88 71 [798,] 31.92 70 [799,] 31.96 87 [800,] 32.00 81 [801,] 32.04 92 [802,] 32.08 64 [803,] 32.12 94 [804,] 32.16 80 [805,] 32.20 83 [806,] 32.24 73 [807,] 32.28 104 [808,] 32.32 64 [809,] 32.36 69 [810,] 32.40 82 [811,] 32.44 73 [812,] 32.48 79 [813,] 32.52 76 [814,] 32.56 77 [815,] 32.60 77 [816,] 32.64 99 [817,] 32.68 90 [818,] 32.72 78 [819,] 32.76 79 [820,] 32.80 79 [821,] 32.84 93 [822,] 32.88 83 [823,] 32.92 76 [824,] 32.96 70 [825,] 33.00 67 [826,] 33.04 83 [827,] 33.08 88 [828,] 33.12 85 [829,] 33.16 85 [830,] 33.20 80 [831,] 33.24 86 [832,] 33.28 97 [833,] 33.32 71 [834,] 33.36 106 [835,] 33.40 75 [836,] 33.44 86 [837,] 33.48 101 [838,] 33.52 80 [839,] 33.56 77 [840,] 33.60 80 [841,] 33.64 72 [842,] 33.68 113 [843,] 33.72 85 [844,] 33.76 92 [845,] 33.80 87 [846,] 33.84 61 [847,] 33.88 76 [848,] 33.92 76 [849,] 33.96 103 [850,] 34.00 83 [851,] 34.04 66 [852,] 34.08 78 [853,] 34.12 77 [854,] 34.16 94 [855,] 34.20 81 [856,] 34.24 89 [857,] 34.28 89 [858,] 34.32 58 [859,] 34.36 97 [860,] 34.40 70 [861,] 34.44 101 [862,] 34.48 92 [863,] 34.52 81 [864,] 34.56 82 [865,] 34.60 92 [866,] 34.64 77 [867,] 34.68 93 [868,] 34.72 84 [869,] 34.76 78 [870,] 34.80 81 [871,] 34.84 77 [872,] 34.88 111 [873,] 34.92 79 [874,] 34.96 89 [875,] 35.00 85 [876,] 35.04 88 [877,] 35.08 81 [878,] 35.12 76 [879,] 35.16 102 [880,] 35.20 65 [881,] 35.24 65 [882,] 35.28 79 [883,] 35.32 82 [884,] 35.36 82 [885,] 35.40 82 [886,] 35.44 66 [887,] 35.48 74 [888,] 35.52 79 [889,] 35.56 81 [890,] 35.60 60 [891,] 35.64 79 [892,] 35.68 94 [893,] 35.72 82 [894,] 35.76 104 [895,] 35.80 75 [896,] 35.84 86 [897,] 35.88 87 [898,] 35.92 90 [899,] 35.96 67 [900,] 36.00 94 [901,] 36.04 87 [902,] 36.08 95 [903,] 36.12 73 [904,] 36.16 81 [905,] 36.20 81 [906,] 36.24 74 [907,] 36.28 66 [908,] 36.32 89 [909,] 36.36 68 [910,] 36.40 59 [911,] 36.44 81 [912,] 36.48 73 [913,] 36.52 58 [914,] 36.56 77 [915,] 36.60 82 [916,] 36.64 87 [917,] 36.68 86 [918,] 36.72 85 [919,] 36.76 79 [920,] 36.80 91 [921,] 36.84 66 [922,] 36.88 83 [923,] 36.92 81 [924,] 36.96 87 [925,] 37.00 68 [926,] 37.04 71 [927,] 37.08 89 [928,] 37.12 77 [929,] 37.16 75 [930,] 37.20 79 [931,] 37.24 75 [932,] 37.28 89 [933,] 37.32 83 [934,] 37.36 67 [935,] 37.40 80 [936,] 37.44 79 [937,] 37.48 79 [938,] 37.52 69 [939,] 37.56 82 [940,] 37.60 70 [941,] 37.64 76 [942,] 37.68 65 [943,] 37.72 90 [944,] 37.76 93 [945,] 37.80 61 [946,] 37.84 81 [947,] 37.88 87 [948,] 37.92 75 [949,] 37.96 86 [950,] 38.00 76 [951,] 38.04 79 [952,] 38.08 59 [953,] 38.12 61 [954,] 38.16 88 [955,] 38.20 91 [956,] 38.24 69 [957,] 38.28 80 [958,] 38.32 73 [959,] 38.36 66 [960,] 38.40 81 [961,] 38.44 74 [962,] 38.48 62 [963,] 38.52 88 [964,] 38.56 74 [965,] 38.60 76 [966,] 38.64 82 [967,] 38.68 77 [968,] 38.72 59 [969,] 38.76 69 [970,] 38.80 79 [971,] 38.84 87 [972,] 38.88 69 [973,] 38.92 85 [974,] 38.96 86 [975,] 39.00 82 [976,] 39.04 70 [977,] 39.08 79 [978,] 39.12 92 [979,] 39.16 84 [980,] 39.20 83 [981,] 39.24 69 [982,] 39.28 87 [983,] 39.32 78 [984,] 39.36 84 [985,] 39.40 71 [986,] 39.44 83 [987,] 39.48 79 [988,] 39.52 99 [989,] 39.56 82 [990,] 39.60 74 [991,] 39.64 74 [992,] 39.68 64 [993,] 39.72 75 [994,] 39.76 103 [995,] 39.80 75 [996,] 39.84 75 [997,] 39.88 68 [998,] 39.92 87 [999,] 39.96 75 [1000,] 40.00 63 $`19_TL (PMT)` [,1] [,2] [1,] 0.64 2 [2,] 1.28 8 [3,] 1.92 0 [4,] 2.56 1 [5,] 3.20 10 [6,] 3.84 5 [7,] 4.48 2 [8,] 5.12 11 [9,] 5.76 4 [10,] 6.40 19 [11,] 7.04 5 [12,] 7.68 9 [13,] 8.32 7 [14,] 8.96 5 [15,] 9.60 9 [16,] 10.24 3 [17,] 10.88 7 [18,] 11.52 5 [19,] 12.16 6 [20,] 12.80 7 [21,] 13.44 1 [22,] 14.08 3 [23,] 14.72 7 [24,] 15.36 2 [25,] 16.00 5 [26,] 16.64 2 [27,] 17.28 2 [28,] 17.92 1 [29,] 18.56 0 [30,] 19.20 3 [31,] 19.84 3 [32,] 20.48 1 [33,] 21.12 1 [34,] 21.76 6 [35,] 22.40 9 [36,] 23.04 3 [37,] 23.68 7 [38,] 24.32 4 [39,] 24.96 5 [40,] 25.60 3 [41,] 26.24 10 [42,] 26.88 1 [43,] 27.52 3 [44,] 28.16 0 [45,] 28.80 1 [46,] 29.44 1 [47,] 30.08 2 [48,] 30.72 2 [49,] 31.36 5 [50,] 32.00 0 [51,] 32.64 3 [52,] 33.28 3 [53,] 33.92 4 [54,] 34.56 1 [55,] 35.20 12 [56,] 35.84 4 [57,] 36.48 1 [58,] 37.12 5 [59,] 37.76 4 [60,] 38.40 2 [61,] 39.04 2 [62,] 39.68 8 [63,] 40.32 4 [64,] 40.96 7 [65,] 41.60 10 [66,] 42.24 3 [67,] 42.88 13 [68,] 43.52 13 [69,] 44.16 5 [70,] 44.80 6 [71,] 45.44 4 [72,] 46.08 6 [73,] 46.72 11 [74,] 47.36 0 [75,] 48.00 9 [76,] 48.64 1 [77,] 49.28 5 [78,] 49.92 5 [79,] 50.56 7 [80,] 51.20 5 [81,] 51.84 11 [82,] 52.48 4 [83,] 53.12 4 [84,] 53.76 12 [85,] 54.40 6 [86,] 55.04 5 [87,] 55.68 6 [88,] 56.32 11 [89,] 56.96 12 [90,] 57.60 13 [91,] 58.24 16 [92,] 58.88 19 [93,] 59.52 6 [94,] 60.16 16 [95,] 60.80 12 [96,] 61.44 15 [97,] 62.08 16 [98,] 62.72 16 [99,] 63.36 19 [100,] 64.00 18 [101,] 64.64 16 [102,] 65.28 26 [103,] 65.92 19 [104,] 66.56 18 [105,] 67.20 20 [106,] 67.84 22 [107,] 68.48 23 [108,] 69.12 28 [109,] 69.76 33 [110,] 70.40 43 [111,] 71.04 34 [112,] 71.68 30 [113,] 72.32 25 [114,] 72.96 61 [115,] 73.60 40 [116,] 74.24 41 [117,] 74.88 62 [118,] 75.52 72 [119,] 76.16 48 [120,] 76.80 47 [121,] 77.44 54 [122,] 78.08 60 [123,] 78.72 60 [124,] 79.36 74 [125,] 80.00 68 [126,] 80.64 74 [127,] 81.28 88 [128,] 81.92 85 [129,] 82.56 88 [130,] 83.20 106 [131,] 83.84 103 [132,] 84.48 120 [133,] 85.12 132 [134,] 85.76 107 [135,] 86.40 146 [136,] 87.04 157 [137,] 87.68 131 [138,] 88.32 145 [139,] 88.96 150 [140,] 89.60 121 [141,] 90.24 157 [142,] 90.88 165 [143,] 91.52 160 [144,] 92.16 189 [145,] 92.80 216 [146,] 93.44 222 [147,] 94.08 234 [148,] 94.72 202 [149,] 95.36 174 [150,] 96.00 187 [151,] 96.64 214 [152,] 97.28 220 [153,] 97.92 277 [154,] 98.56 251 [155,] 99.20 265 [156,] 99.84 254 [157,] 100.48 262 [158,] 101.12 245 [159,] 101.76 302 [160,] 102.40 296 [161,] 103.04 287 [162,] 103.68 310 [163,] 104.32 299 [164,] 104.96 312 [165,] 105.60 292 [166,] 106.24 291 [167,] 106.88 330 [168,] 107.52 301 [169,] 108.16 295 [170,] 108.80 285 [171,] 109.44 284 [172,] 110.08 272 [173,] 110.72 282 [174,] 111.36 270 [175,] 112.00 279 [176,] 112.64 255 [177,] 113.28 199 [178,] 113.92 245 [179,] 114.56 195 [180,] 115.20 214 [181,] 115.84 172 [182,] 116.48 210 [183,] 117.12 208 [184,] 117.76 181 [185,] 118.40 178 [186,] 119.04 155 [187,] 119.68 159 [188,] 120.32 136 [189,] 120.96 145 [190,] 121.60 121 [191,] 122.24 141 [192,] 122.88 132 [193,] 123.52 97 [194,] 124.16 105 [195,] 124.80 94 [196,] 125.44 106 [197,] 126.08 75 [198,] 126.72 71 [199,] 127.36 96 [200,] 128.00 75 [201,] 128.64 105 [202,] 129.28 111 [203,] 129.92 76 [204,] 130.56 91 [205,] 131.20 74 [206,] 131.84 75 [207,] 132.48 87 [208,] 133.12 66 [209,] 133.76 75 [210,] 134.40 88 [211,] 135.04 84 [212,] 135.68 86 [213,] 136.32 98 [214,] 136.96 82 [215,] 137.60 111 [216,] 138.24 101 [217,] 138.88 97 [218,] 139.52 104 [219,] 140.16 93 [220,] 140.80 91 [221,] 141.44 89 [222,] 142.08 98 [223,] 142.72 87 [224,] 143.36 99 [225,] 144.00 134 [226,] 144.64 85 [227,] 145.28 95 [228,] 145.92 68 [229,] 146.56 105 [230,] 147.20 83 [231,] 147.84 104 [232,] 148.48 110 [233,] 149.12 70 [234,] 149.76 94 [235,] 150.40 91 [236,] 151.04 97 [237,] 151.68 113 [238,] 152.32 83 [239,] 152.96 95 [240,] 153.60 90 [241,] 154.24 100 [242,] 154.88 76 [243,] 155.52 97 [244,] 156.16 92 [245,] 156.80 107 [246,] 157.44 82 [247,] 158.08 101 [248,] 158.72 91 [249,] 159.36 75 [250,] 160.00 74 $`20_OSL (PMT)` [,1] [,2] [1,] 0.04 3102 [2,] 0.08 2613 [3,] 0.12 2358 [4,] 0.16 2071 [5,] 0.20 1823 [6,] 0.24 1609 [7,] 0.28 1341 [8,] 0.32 1236 [9,] 0.36 1049 [10,] 0.40 921 [11,] 0.44 851 [12,] 0.48 725 [13,] 0.52 744 [14,] 0.56 581 [15,] 0.60 541 [16,] 0.64 590 [17,] 0.68 474 [18,] 0.72 475 [19,] 0.76 377 [20,] 0.80 368 [21,] 0.84 361 [22,] 0.88 325 [23,] 0.92 338 [24,] 0.96 308 [25,] 1.00 301 [26,] 1.04 283 [27,] 1.08 280 [28,] 1.12 240 [29,] 1.16 254 [30,] 1.20 246 [31,] 1.24 222 [32,] 1.28 220 [33,] 1.32 184 [34,] 1.36 185 [35,] 1.40 160 [36,] 1.44 204 [37,] 1.48 160 [38,] 1.52 230 [39,] 1.56 183 [40,] 1.60 162 [41,] 1.64 147 [42,] 1.68 180 [43,] 1.72 172 [44,] 1.76 176 [45,] 1.80 163 [46,] 1.84 157 [47,] 1.88 166 [48,] 1.92 173 [49,] 1.96 148 [50,] 2.00 145 [51,] 2.04 140 [52,] 2.08 140 [53,] 2.12 132 [54,] 2.16 124 [55,] 2.20 137 [56,] 2.24 139 [57,] 2.28 144 [58,] 2.32 134 [59,] 2.36 131 [60,] 2.40 145 [61,] 2.44 144 [62,] 2.48 127 [63,] 2.52 136 [64,] 2.56 107 [65,] 2.60 136 [66,] 2.64 123 [67,] 2.68 116 [68,] 2.72 145 [69,] 2.76 117 [70,] 2.80 129 [71,] 2.84 131 [72,] 2.88 137 [73,] 2.92 115 [74,] 2.96 124 [75,] 3.00 135 [76,] 3.04 144 [77,] 3.08 128 [78,] 3.12 119 [79,] 3.16 137 [80,] 3.20 120 [81,] 3.24 124 [82,] 3.28 120 [83,] 3.32 133 [84,] 3.36 107 [85,] 3.40 143 [86,] 3.44 122 [87,] 3.48 132 [88,] 3.52 146 [89,] 3.56 125 [90,] 3.60 130 [91,] 3.64 130 [92,] 3.68 109 [93,] 3.72 109 [94,] 3.76 125 [95,] 3.80 124 [96,] 3.84 115 [97,] 3.88 118 [98,] 3.92 109 [99,] 3.96 115 [100,] 4.00 104 [101,] 4.04 115 [102,] 4.08 148 [103,] 4.12 97 [104,] 4.16 111 [105,] 4.20 111 [106,] 4.24 124 [107,] 4.28 105 [108,] 4.32 114 [109,] 4.36 99 [110,] 4.40 111 [111,] 4.44 110 [112,] 4.48 94 [113,] 4.52 131 [114,] 4.56 82 [115,] 4.60 92 [116,] 4.64 109 [117,] 4.68 133 [118,] 4.72 134 [119,] 4.76 128 [120,] 4.80 113 [121,] 4.84 128 [122,] 4.88 96 [123,] 4.92 117 [124,] 4.96 141 [125,] 5.00 128 [126,] 5.04 115 [127,] 5.08 117 [128,] 5.12 138 [129,] 5.16 116 [130,] 5.20 121 [131,] 5.24 104 [132,] 5.28 120 [133,] 5.32 98 [134,] 5.36 102 [135,] 5.40 127 [136,] 5.44 108 [137,] 5.48 125 [138,] 5.52 92 [139,] 5.56 106 [140,] 5.60 119 [141,] 5.64 100 [142,] 5.68 124 [143,] 5.72 112 [144,] 5.76 80 [145,] 5.80 114 [146,] 5.84 78 [147,] 5.88 123 [148,] 5.92 105 [149,] 5.96 88 [150,] 6.00 94 [151,] 6.04 120 [152,] 6.08 84 [153,] 6.12 96 [154,] 6.16 85 [155,] 6.20 95 [156,] 6.24 102 [157,] 6.28 109 [158,] 6.32 102 [159,] 6.36 101 [160,] 6.40 114 [161,] 6.44 130 [162,] 6.48 99 [163,] 6.52 105 [164,] 6.56 86 [165,] 6.60 105 [166,] 6.64 97 [167,] 6.68 95 [168,] 6.72 109 [169,] 6.76 99 [170,] 6.80 132 [171,] 6.84 106 [172,] 6.88 132 [173,] 6.92 97 [174,] 6.96 96 [175,] 7.00 89 [176,] 7.04 83 [177,] 7.08 132 [178,] 7.12 113 [179,] 7.16 119 [180,] 7.20 78 [181,] 7.24 112 [182,] 7.28 92 [183,] 7.32 98 [184,] 7.36 89 [185,] 7.40 97 [186,] 7.44 116 [187,] 7.48 81 [188,] 7.52 86 [189,] 7.56 99 [190,] 7.60 88 [191,] 7.64 94 [192,] 7.68 104 [193,] 7.72 105 [194,] 7.76 90 [195,] 7.80 102 [196,] 7.84 97 [197,] 7.88 102 [198,] 7.92 88 [199,] 7.96 94 [200,] 8.00 127 [201,] 8.04 107 [202,] 8.08 79 [203,] 8.12 80 [204,] 8.16 136 [205,] 8.20 90 [206,] 8.24 83 [207,] 8.28 97 [208,] 8.32 113 [209,] 8.36 84 [210,] 8.40 106 [211,] 8.44 101 [212,] 8.48 110 [213,] 8.52 96 [214,] 8.56 83 [215,] 8.60 101 [216,] 8.64 91 [217,] 8.68 108 [218,] 8.72 89 [219,] 8.76 125 [220,] 8.80 85 [221,] 8.84 102 [222,] 8.88 88 [223,] 8.92 108 [224,] 8.96 100 [225,] 9.00 98 [226,] 9.04 99 [227,] 9.08 104 [228,] 9.12 96 [229,] 9.16 99 [230,] 9.20 63 [231,] 9.24 96 [232,] 9.28 102 [233,] 9.32 92 [234,] 9.36 82 [235,] 9.40 114 [236,] 9.44 100 [237,] 9.48 108 [238,] 9.52 91 [239,] 9.56 88 [240,] 9.60 85 [241,] 9.64 67 [242,] 9.68 92 [243,] 9.72 81 [244,] 9.76 88 [245,] 9.80 88 [246,] 9.84 124 [247,] 9.88 81 [248,] 9.92 90 [249,] 9.96 101 [250,] 10.00 81 [251,] 10.04 88 [252,] 10.08 76 [253,] 10.12 93 [254,] 10.16 100 [255,] 10.20 67 [256,] 10.24 117 [257,] 10.28 93 [258,] 10.32 78 [259,] 10.36 81 [260,] 10.40 96 [261,] 10.44 85 [262,] 10.48 120 [263,] 10.52 117 [264,] 10.56 89 [265,] 10.60 111 [266,] 10.64 91 [267,] 10.68 95 [268,] 10.72 108 [269,] 10.76 103 [270,] 10.80 122 [271,] 10.84 81 [272,] 10.88 94 [273,] 10.92 73 [274,] 10.96 92 [275,] 11.00 90 [276,] 11.04 98 [277,] 11.08 89 [278,] 11.12 105 [279,] 11.16 104 [280,] 11.20 105 [281,] 11.24 84 [282,] 11.28 100 [283,] 11.32 64 [284,] 11.36 97 [285,] 11.40 95 [286,] 11.44 85 [287,] 11.48 79 [288,] 11.52 98 [289,] 11.56 83 [290,] 11.60 104 [291,] 11.64 80 [292,] 11.68 92 [293,] 11.72 93 [294,] 11.76 91 [295,] 11.80 76 [296,] 11.84 80 [297,] 11.88 82 [298,] 11.92 87 [299,] 11.96 94 [300,] 12.00 92 [301,] 12.04 88 [302,] 12.08 87 [303,] 12.12 84 [304,] 12.16 88 [305,] 12.20 88 [306,] 12.24 98 [307,] 12.28 82 [308,] 12.32 107 [309,] 12.36 91 [310,] 12.40 84 [311,] 12.44 69 [312,] 12.48 79 [313,] 12.52 80 [314,] 12.56 103 [315,] 12.60 81 [316,] 12.64 94 [317,] 12.68 91 [318,] 12.72 97 [319,] 12.76 91 [320,] 12.80 108 [321,] 12.84 97 [322,] 12.88 85 [323,] 12.92 78 [324,] 12.96 75 [325,] 13.00 64 [326,] 13.04 106 [327,] 13.08 84 [328,] 13.12 88 [329,] 13.16 75 [330,] 13.20 83 [331,] 13.24 88 [332,] 13.28 83 [333,] 13.32 105 [334,] 13.36 83 [335,] 13.40 84 [336,] 13.44 84 [337,] 13.48 82 [338,] 13.52 82 [339,] 13.56 99 [340,] 13.60 91 [341,] 13.64 85 [342,] 13.68 106 [343,] 13.72 89 [344,] 13.76 91 [345,] 13.80 79 [346,] 13.84 86 [347,] 13.88 79 [348,] 13.92 81 [349,] 13.96 90 [350,] 14.00 109 [351,] 14.04 87 [352,] 14.08 92 [353,] 14.12 87 [354,] 14.16 94 [355,] 14.20 77 [356,] 14.24 83 [357,] 14.28 98 [358,] 14.32 91 [359,] 14.36 79 [360,] 14.40 82 [361,] 14.44 72 [362,] 14.48 86 [363,] 14.52 88 [364,] 14.56 75 [365,] 14.60 72 [366,] 14.64 97 [367,] 14.68 105 [368,] 14.72 96 [369,] 14.76 91 [370,] 14.80 101 [371,] 14.84 75 [372,] 14.88 86 [373,] 14.92 88 [374,] 14.96 81 [375,] 15.00 92 [376,] 15.04 92 [377,] 15.08 68 [378,] 15.12 79 [379,] 15.16 92 [380,] 15.20 85 [381,] 15.24 76 [382,] 15.28 93 [383,] 15.32 79 [384,] 15.36 65 [385,] 15.40 84 [386,] 15.44 86 [387,] 15.48 91 [388,] 15.52 76 [389,] 15.56 98 [390,] 15.60 84 [391,] 15.64 90 [392,] 15.68 112 [393,] 15.72 89 [394,] 15.76 95 [395,] 15.80 96 [396,] 15.84 64 [397,] 15.88 80 [398,] 15.92 66 [399,] 15.96 80 [400,] 16.00 88 [401,] 16.04 95 [402,] 16.08 90 [403,] 16.12 69 [404,] 16.16 82 [405,] 16.20 89 [406,] 16.24 102 [407,] 16.28 83 [408,] 16.32 82 [409,] 16.36 82 [410,] 16.40 82 [411,] 16.44 88 [412,] 16.48 71 [413,] 16.52 109 [414,] 16.56 76 [415,] 16.60 69 [416,] 16.64 93 [417,] 16.68 85 [418,] 16.72 89 [419,] 16.76 67 [420,] 16.80 72 [421,] 16.84 75 [422,] 16.88 66 [423,] 16.92 73 [424,] 16.96 85 [425,] 17.00 86 [426,] 17.04 64 [427,] 17.08 82 [428,] 17.12 85 [429,] 17.16 101 [430,] 17.20 82 [431,] 17.24 69 [432,] 17.28 88 [433,] 17.32 90 [434,] 17.36 86 [435,] 17.40 78 [436,] 17.44 80 [437,] 17.48 85 [438,] 17.52 87 [439,] 17.56 98 [440,] 17.60 93 [441,] 17.64 73 [442,] 17.68 113 [443,] 17.72 83 [444,] 17.76 94 [445,] 17.80 80 [446,] 17.84 76 [447,] 17.88 82 [448,] 17.92 100 [449,] 17.96 71 [450,] 18.00 89 [451,] 18.04 82 [452,] 18.08 88 [453,] 18.12 69 [454,] 18.16 95 [455,] 18.20 79 [456,] 18.24 90 [457,] 18.28 92 [458,] 18.32 79 [459,] 18.36 77 [460,] 18.40 87 [461,] 18.44 75 [462,] 18.48 97 [463,] 18.52 71 [464,] 18.56 92 [465,] 18.60 92 [466,] 18.64 68 [467,] 18.68 71 [468,] 18.72 92 [469,] 18.76 96 [470,] 18.80 71 [471,] 18.84 78 [472,] 18.88 79 [473,] 18.92 72 [474,] 18.96 76 [475,] 19.00 93 [476,] 19.04 65 [477,] 19.08 63 [478,] 19.12 79 [479,] 19.16 97 [480,] 19.20 73 [481,] 19.24 77 [482,] 19.28 83 [483,] 19.32 72 [484,] 19.36 76 [485,] 19.40 81 [486,] 19.44 111 [487,] 19.48 85 [488,] 19.52 71 [489,] 19.56 80 [490,] 19.60 85 [491,] 19.64 89 [492,] 19.68 93 [493,] 19.72 98 [494,] 19.76 90 [495,] 19.80 109 [496,] 19.84 66 [497,] 19.88 76 [498,] 19.92 72 [499,] 19.96 77 [500,] 20.00 83 [501,] 20.04 73 [502,] 20.08 95 [503,] 20.12 74 [504,] 20.16 80 [505,] 20.20 94 [506,] 20.24 80 [507,] 20.28 86 [508,] 20.32 79 [509,] 20.36 93 [510,] 20.40 75 [511,] 20.44 78 [512,] 20.48 66 [513,] 20.52 73 [514,] 20.56 83 [515,] 20.60 88 [516,] 20.64 70 [517,] 20.68 73 [518,] 20.72 107 [519,] 20.76 85 [520,] 20.80 71 [521,] 20.84 81 [522,] 20.88 86 [523,] 20.92 95 [524,] 20.96 87 [525,] 21.00 88 [526,] 21.04 79 [527,] 21.08 76 [528,] 21.12 69 [529,] 21.16 82 [530,] 21.20 86 [531,] 21.24 68 [532,] 21.28 81 [533,] 21.32 83 [534,] 21.36 79 [535,] 21.40 89 [536,] 21.44 89 [537,] 21.48 93 [538,] 21.52 73 [539,] 21.56 77 [540,] 21.60 83 [541,] 21.64 78 [542,] 21.68 78 [543,] 21.72 81 [544,] 21.76 62 [545,] 21.80 82 [546,] 21.84 80 [547,] 21.88 75 [548,] 21.92 84 [549,] 21.96 75 [550,] 22.00 74 [551,] 22.04 91 [552,] 22.08 80 [553,] 22.12 82 [554,] 22.16 88 [555,] 22.20 79 [556,] 22.24 104 [557,] 22.28 96 [558,] 22.32 57 [559,] 22.36 76 [560,] 22.40 83 [561,] 22.44 73 [562,] 22.48 82 [563,] 22.52 87 [564,] 22.56 87 [565,] 22.60 74 [566,] 22.64 73 [567,] 22.68 69 [568,] 22.72 108 [569,] 22.76 88 [570,] 22.80 103 [571,] 22.84 90 [572,] 22.88 85 [573,] 22.92 83 [574,] 22.96 91 [575,] 23.00 85 [576,] 23.04 75 [577,] 23.08 83 [578,] 23.12 76 [579,] 23.16 86 [580,] 23.20 71 [581,] 23.24 70 [582,] 23.28 72 [583,] 23.32 54 [584,] 23.36 68 [585,] 23.40 77 [586,] 23.44 70 [587,] 23.48 69 [588,] 23.52 68 [589,] 23.56 73 [590,] 23.60 100 [591,] 23.64 89 [592,] 23.68 84 [593,] 23.72 85 [594,] 23.76 69 [595,] 23.80 93 [596,] 23.84 70 [597,] 23.88 94 [598,] 23.92 67 [599,] 23.96 93 [600,] 24.00 79 [601,] 24.04 81 [602,] 24.08 64 [603,] 24.12 81 [604,] 24.16 72 [605,] 24.20 69 [606,] 24.24 73 [607,] 24.28 80 [608,] 24.32 75 [609,] 24.36 63 [610,] 24.40 74 [611,] 24.44 58 [612,] 24.48 97 [613,] 24.52 69 [614,] 24.56 72 [615,] 24.60 95 [616,] 24.64 68 [617,] 24.68 75 [618,] 24.72 80 [619,] 24.76 69 [620,] 24.80 98 [621,] 24.84 64 [622,] 24.88 77 [623,] 24.92 74 [624,] 24.96 80 [625,] 25.00 53 [626,] 25.04 73 [627,] 25.08 82 [628,] 25.12 78 [629,] 25.16 80 [630,] 25.20 96 [631,] 25.24 67 [632,] 25.28 73 [633,] 25.32 89 [634,] 25.36 79 [635,] 25.40 92 [636,] 25.44 69 [637,] 25.48 69 [638,] 25.52 66 [639,] 25.56 69 [640,] 25.60 83 [641,] 25.64 92 [642,] 25.68 94 [643,] 25.72 84 [644,] 25.76 78 [645,] 25.80 90 [646,] 25.84 84 [647,] 25.88 74 [648,] 25.92 84 [649,] 25.96 74 [650,] 26.00 81 [651,] 26.04 63 [652,] 26.08 66 [653,] 26.12 69 [654,] 26.16 81 [655,] 26.20 91 [656,] 26.24 59 [657,] 26.28 88 [658,] 26.32 83 [659,] 26.36 67 [660,] 26.40 66 [661,] 26.44 68 [662,] 26.48 74 [663,] 26.52 72 [664,] 26.56 54 [665,] 26.60 80 [666,] 26.64 64 [667,] 26.68 77 [668,] 26.72 81 [669,] 26.76 94 [670,] 26.80 94 [671,] 26.84 57 [672,] 26.88 61 [673,] 26.92 88 [674,] 26.96 75 [675,] 27.00 80 [676,] 27.04 86 [677,] 27.08 62 [678,] 27.12 74 [679,] 27.16 74 [680,] 27.20 80 [681,] 27.24 57 [682,] 27.28 62 [683,] 27.32 75 [684,] 27.36 79 [685,] 27.40 90 [686,] 27.44 98 [687,] 27.48 75 [688,] 27.52 74 [689,] 27.56 90 [690,] 27.60 70 [691,] 27.64 92 [692,] 27.68 80 [693,] 27.72 64 [694,] 27.76 46 [695,] 27.80 84 [696,] 27.84 83 [697,] 27.88 59 [698,] 27.92 82 [699,] 27.96 85 [700,] 28.00 97 [701,] 28.04 83 [702,] 28.08 80 [703,] 28.12 54 [704,] 28.16 85 [705,] 28.20 92 [706,] 28.24 82 [707,] 28.28 71 [708,] 28.32 72 [709,] 28.36 85 [710,] 28.40 74 [711,] 28.44 85 [712,] 28.48 82 [713,] 28.52 65 [714,] 28.56 69 [715,] 28.60 80 [716,] 28.64 65 [717,] 28.68 45 [718,] 28.72 80 [719,] 28.76 86 [720,] 28.80 57 [721,] 28.84 60 [722,] 28.88 73 [723,] 28.92 71 [724,] 28.96 87 [725,] 29.00 95 [726,] 29.04 88 [727,] 29.08 92 [728,] 29.12 72 [729,] 29.16 66 [730,] 29.20 98 [731,] 29.24 91 [732,] 29.28 61 [733,] 29.32 72 [734,] 29.36 95 [735,] 29.40 87 [736,] 29.44 77 [737,] 29.48 86 [738,] 29.52 91 [739,] 29.56 65 [740,] 29.60 77 [741,] 29.64 77 [742,] 29.68 82 [743,] 29.72 69 [744,] 29.76 77 [745,] 29.80 62 [746,] 29.84 68 [747,] 29.88 74 [748,] 29.92 93 [749,] 29.96 75 [750,] 30.00 81 [751,] 30.04 58 [752,] 30.08 80 [753,] 30.12 96 [754,] 30.16 74 [755,] 30.20 57 [756,] 30.24 67 [757,] 30.28 78 [758,] 30.32 65 [759,] 30.36 64 [760,] 30.40 57 [761,] 30.44 73 [762,] 30.48 90 [763,] 30.52 85 [764,] 30.56 61 [765,] 30.60 82 [766,] 30.64 82 [767,] 30.68 77 [768,] 30.72 68 [769,] 30.76 69 [770,] 30.80 74 [771,] 30.84 58 [772,] 30.88 65 [773,] 30.92 93 [774,] 30.96 87 [775,] 31.00 79 [776,] 31.04 81 [777,] 31.08 96 [778,] 31.12 73 [779,] 31.16 64 [780,] 31.20 74 [781,] 31.24 79 [782,] 31.28 66 [783,] 31.32 81 [784,] 31.36 85 [785,] 31.40 65 [786,] 31.44 66 [787,] 31.48 63 [788,] 31.52 97 [789,] 31.56 75 [790,] 31.60 70 [791,] 31.64 71 [792,] 31.68 91 [793,] 31.72 81 [794,] 31.76 70 [795,] 31.80 67 [796,] 31.84 88 [797,] 31.88 96 [798,] 31.92 92 [799,] 31.96 91 [800,] 32.00 81 [801,] 32.04 69 [802,] 32.08 72 [803,] 32.12 83 [804,] 32.16 91 [805,] 32.20 62 [806,] 32.24 77 [807,] 32.28 78 [808,] 32.32 65 [809,] 32.36 81 [810,] 32.40 65 [811,] 32.44 85 [812,] 32.48 79 [813,] 32.52 61 [814,] 32.56 55 [815,] 32.60 75 [816,] 32.64 63 [817,] 32.68 79 [818,] 32.72 83 [819,] 32.76 86 [820,] 32.80 66 [821,] 32.84 78 [822,] 32.88 62 [823,] 32.92 64 [824,] 32.96 78 [825,] 33.00 68 [826,] 33.04 91 [827,] 33.08 83 [828,] 33.12 89 [829,] 33.16 82 [830,] 33.20 61 [831,] 33.24 64 [832,] 33.28 68 [833,] 33.32 60 [834,] 33.36 94 [835,] 33.40 76 [836,] 33.44 74 [837,] 33.48 75 [838,] 33.52 69 [839,] 33.56 70 [840,] 33.60 63 [841,] 33.64 61 [842,] 33.68 72 [843,] 33.72 68 [844,] 33.76 78 [845,] 33.80 72 [846,] 33.84 76 [847,] 33.88 77 [848,] 33.92 81 [849,] 33.96 79 [850,] 34.00 77 [851,] 34.04 72 [852,] 34.08 59 [853,] 34.12 75 [854,] 34.16 80 [855,] 34.20 59 [856,] 34.24 71 [857,] 34.28 71 [858,] 34.32 78 [859,] 34.36 82 [860,] 34.40 73 [861,] 34.44 69 [862,] 34.48 73 [863,] 34.52 59 [864,] 34.56 82 [865,] 34.60 79 [866,] 34.64 79 [867,] 34.68 70 [868,] 34.72 80 [869,] 34.76 73 [870,] 34.80 64 [871,] 34.84 70 [872,] 34.88 84 [873,] 34.92 85 [874,] 34.96 55 [875,] 35.00 73 [876,] 35.04 71 [877,] 35.08 67 [878,] 35.12 81 [879,] 35.16 67 [880,] 35.20 66 [881,] 35.24 75 [882,] 35.28 72 [883,] 35.32 56 [884,] 35.36 68 [885,] 35.40 101 [886,] 35.44 80 [887,] 35.48 77 [888,] 35.52 62 [889,] 35.56 71 [890,] 35.60 76 [891,] 35.64 65 [892,] 35.68 71 [893,] 35.72 75 [894,] 35.76 64 [895,] 35.80 72 [896,] 35.84 59 [897,] 35.88 64 [898,] 35.92 64 [899,] 35.96 78 [900,] 36.00 75 [901,] 36.04 65 [902,] 36.08 74 [903,] 36.12 62 [904,] 36.16 54 [905,] 36.20 71 [906,] 36.24 72 [907,] 36.28 83 [908,] 36.32 85 [909,] 36.36 72 [910,] 36.40 82 [911,] 36.44 78 [912,] 36.48 79 [913,] 36.52 77 [914,] 36.56 56 [915,] 36.60 76 [916,] 36.64 74 [917,] 36.68 57 [918,] 36.72 84 [919,] 36.76 66 [920,] 36.80 80 [921,] 36.84 61 [922,] 36.88 60 [923,] 36.92 63 [924,] 36.96 84 [925,] 37.00 62 [926,] 37.04 89 [927,] 37.08 69 [928,] 37.12 70 [929,] 37.16 59 [930,] 37.20 76 [931,] 37.24 79 [932,] 37.28 59 [933,] 37.32 91 [934,] 37.36 81 [935,] 37.40 77 [936,] 37.44 69 [937,] 37.48 73 [938,] 37.52 59 [939,] 37.56 89 [940,] 37.60 82 [941,] 37.64 86 [942,] 37.68 85 [943,] 37.72 80 [944,] 37.76 63 [945,] 37.80 89 [946,] 37.84 58 [947,] 37.88 69 [948,] 37.92 67 [949,] 37.96 77 [950,] 38.00 65 [951,] 38.04 73 [952,] 38.08 67 [953,] 38.12 50 [954,] 38.16 88 [955,] 38.20 84 [956,] 38.24 72 [957,] 38.28 67 [958,] 38.32 59 [959,] 38.36 90 [960,] 38.40 83 [961,] 38.44 58 [962,] 38.48 58 [963,] 38.52 85 [964,] 38.56 60 [965,] 38.60 72 [966,] 38.64 69 [967,] 38.68 90 [968,] 38.72 72 [969,] 38.76 76 [970,] 38.80 75 [971,] 38.84 77 [972,] 38.88 72 [973,] 38.92 77 [974,] 38.96 81 [975,] 39.00 81 [976,] 39.04 67 [977,] 39.08 71 [978,] 39.12 62 [979,] 39.16 83 [980,] 39.20 71 [981,] 39.24 61 [982,] 39.28 70 [983,] 39.32 74 [984,] 39.36 75 [985,] 39.40 63 [986,] 39.44 60 [987,] 39.48 73 [988,] 39.52 77 [989,] 39.56 78 [990,] 39.60 69 [991,] 39.64 73 [992,] 39.68 78 [993,] 39.72 86 [994,] 39.76 88 [995,] 39.80 68 [996,] 39.84 63 [997,] 39.88 68 [998,] 39.92 69 [999,] 39.96 67 [1000,] 40.00 102 $`21_TL (PMT)` [,1] [,2] [1,] 0.884 7 [2,] 1.768 4 [3,] 2.652 1 [4,] 3.536 5 [5,] 4.420 2 [6,] 5.304 9 [7,] 6.188 2 [8,] 7.072 7 [9,] 7.956 4 [10,] 8.840 5 [11,] 9.724 5 [12,] 10.608 4 [13,] 11.492 1 [14,] 12.376 0 [15,] 13.260 4 [16,] 14.144 9 [17,] 15.028 8 [18,] 15.912 3 [19,] 16.796 2 [20,] 17.680 1 [21,] 18.564 2 [22,] 19.448 4 [23,] 20.332 5 [24,] 21.216 7 [25,] 22.100 3 [26,] 22.984 2 [27,] 23.868 13 [28,] 24.752 9 [29,] 25.636 6 [30,] 26.520 8 [31,] 27.404 3 [32,] 28.288 2 [33,] 29.172 6 [34,] 30.056 2 [35,] 30.940 7 [36,] 31.824 2 [37,] 32.708 4 [38,] 33.592 6 [39,] 34.476 3 [40,] 35.360 5 [41,] 36.244 4 [42,] 37.128 10 [43,] 38.012 2 [44,] 38.896 9 [45,] 39.780 19 [46,] 40.664 9 [47,] 41.548 10 [48,] 42.432 6 [49,] 43.316 2 [50,] 44.200 1 [51,] 45.084 5 [52,] 45.968 7 [53,] 46.852 7 [54,] 47.736 7 [55,] 48.620 10 [56,] 49.504 9 [57,] 50.388 5 [58,] 51.272 22 [59,] 52.156 7 [60,] 53.040 7 [61,] 53.924 8 [62,] 54.808 11 [63,] 55.692 10 [64,] 56.576 12 [65,] 57.460 13 [66,] 58.344 15 [67,] 59.228 19 [68,] 60.112 12 [69,] 60.996 19 [70,] 61.880 12 [71,] 62.764 15 [72,] 63.648 14 [73,] 64.532 11 [74,] 65.416 17 [75,] 66.300 14 [76,] 67.184 12 [77,] 68.068 20 [78,] 68.952 21 [79,] 69.836 30 [80,] 70.720 27 [81,] 71.604 36 [82,] 72.488 21 [83,] 73.372 23 [84,] 74.256 38 [85,] 75.140 41 [86,] 76.024 45 [87,] 76.908 37 [88,] 77.792 41 [89,] 78.676 65 [90,] 79.560 49 [91,] 80.444 46 [92,] 81.328 58 [93,] 82.212 55 [94,] 83.096 72 [95,] 83.980 65 [96,] 84.864 88 [97,] 85.748 78 [98,] 86.632 102 [99,] 87.516 82 [100,] 88.400 114 [101,] 89.284 102 [102,] 90.168 122 [103,] 91.052 124 [104,] 91.936 133 [105,] 92.820 161 [106,] 93.704 147 [107,] 94.588 175 [108,] 95.472 183 [109,] 96.356 181 [110,] 97.240 164 [111,] 98.124 145 [112,] 99.008 220 [113,] 99.892 220 [114,] 100.776 194 [115,] 101.660 215 [116,] 102.544 232 [117,] 103.428 228 [118,] 104.312 248 [119,] 105.196 266 [120,] 106.080 238 [121,] 106.964 245 [122,] 107.848 236 [123,] 108.732 241 [124,] 109.616 241 [125,] 110.500 231 [126,] 111.384 217 [127,] 112.268 245 [128,] 113.152 247 [129,] 114.036 238 [130,] 114.920 210 [131,] 115.804 226 [132,] 116.688 210 [133,] 117.572 169 [134,] 118.456 207 [135,] 119.340 186 [136,] 120.224 193 [137,] 121.108 224 [138,] 121.992 154 [139,] 122.876 174 [140,] 123.760 188 [141,] 124.644 174 [142,] 125.528 177 [143,] 126.412 134 [144,] 127.296 176 [145,] 128.180 149 [146,] 129.064 156 [147,] 129.948 171 [148,] 130.832 187 [149,] 131.716 144 [150,] 132.600 177 [151,] 133.484 183 [152,] 134.368 167 [153,] 135.252 175 [154,] 136.136 167 [155,] 137.020 198 [156,] 137.904 193 [157,] 138.788 198 [158,] 139.672 186 [159,] 140.556 191 [160,] 141.440 181 [161,] 142.324 195 [162,] 143.208 162 [163,] 144.092 192 [164,] 144.976 187 [165,] 145.860 176 [166,] 146.744 184 [167,] 147.628 202 [168,] 148.512 167 [169,] 149.396 153 [170,] 150.280 189 [171,] 151.164 189 [172,] 152.048 196 [173,] 152.932 192 [174,] 153.816 171 [175,] 154.700 184 [176,] 155.584 187 [177,] 156.468 176 [178,] 157.352 179 [179,] 158.236 201 [180,] 159.120 186 [181,] 160.004 230 [182,] 160.888 191 [183,] 161.772 162 [184,] 162.656 180 [185,] 163.540 160 [186,] 164.424 170 [187,] 165.308 140 [188,] 166.192 172 [189,] 167.076 182 [190,] 167.960 192 [191,] 168.844 183 [192,] 169.728 143 [193,] 170.612 155 [194,] 171.496 170 [195,] 172.380 190 [196,] 173.264 160 [197,] 174.148 175 [198,] 175.032 166 [199,] 175.916 175 [200,] 176.800 159 [201,] 177.684 184 [202,] 178.568 163 [203,] 179.452 174 [204,] 180.336 166 [205,] 181.220 181 [206,] 182.104 165 [207,] 182.988 170 [208,] 183.872 170 [209,] 184.756 164 [210,] 185.640 192 [211,] 186.524 170 [212,] 187.408 204 [213,] 188.292 181 [214,] 189.176 158 [215,] 190.060 180 [216,] 190.944 191 [217,] 191.828 198 [218,] 192.712 178 [219,] 193.596 196 [220,] 194.480 189 [221,] 195.364 198 [222,] 196.248 228 [223,] 197.132 236 [224,] 198.016 219 [225,] 198.900 228 [226,] 199.784 196 [227,] 200.668 206 [228,] 201.552 208 [229,] 202.436 255 [230,] 203.320 257 [231,] 204.204 249 [232,] 205.088 243 [233,] 205.972 225 [234,] 206.856 242 [235,] 207.740 228 [236,] 208.624 260 [237,] 209.508 256 [238,] 210.392 261 [239,] 211.276 269 [240,] 212.160 243 [241,] 213.044 304 [242,] 213.928 241 [243,] 214.812 279 [244,] 215.696 285 [245,] 216.580 263 [246,] 217.464 305 [247,] 218.348 316 [248,] 219.232 244 [249,] 220.116 310 [250,] 221.000 148 $`22_OSL (PMT)` [,1] [,2] [1,] 0.04 4993 [2,] 0.08 4383 [3,] 0.12 3681 [4,] 0.16 3106 [5,] 0.20 2877 [6,] 0.24 2452 [7,] 0.28 2173 [8,] 0.32 1856 [9,] 0.36 1620 [10,] 0.40 1479 [11,] 0.44 1351 [12,] 0.48 1123 [13,] 0.52 1021 [14,] 0.56 838 [15,] 0.60 776 [16,] 0.64 726 [17,] 0.68 663 [18,] 0.72 590 [19,] 0.76 526 [20,] 0.80 499 [21,] 0.84 468 [22,] 0.88 402 [23,] 0.92 448 [24,] 0.96 340 [25,] 1.00 325 [26,] 1.04 269 [27,] 1.08 288 [28,] 1.12 273 [29,] 1.16 265 [30,] 1.20 245 [31,] 1.24 250 [32,] 1.28 210 [33,] 1.32 199 [34,] 1.36 206 [35,] 1.40 183 [36,] 1.44 163 [37,] 1.48 215 [38,] 1.52 178 [39,] 1.56 159 [40,] 1.60 164 [41,] 1.64 128 [42,] 1.68 165 [43,] 1.72 146 [44,] 1.76 169 [45,] 1.80 155 [46,] 1.84 118 [47,] 1.88 143 [48,] 1.92 164 [49,] 1.96 115 [50,] 2.00 120 [51,] 2.04 161 [52,] 2.08 122 [53,] 2.12 137 [54,] 2.16 119 [55,] 2.20 119 [56,] 2.24 133 [57,] 2.28 130 [58,] 2.32 137 [59,] 2.36 113 [60,] 2.40 125 [61,] 2.44 134 [62,] 2.48 95 [63,] 2.52 124 [64,] 2.56 117 [65,] 2.60 136 [66,] 2.64 111 [67,] 2.68 104 [68,] 2.72 121 [69,] 2.76 132 [70,] 2.80 112 [71,] 2.84 117 [72,] 2.88 91 [73,] 2.92 113 [74,] 2.96 109 [75,] 3.00 86 [76,] 3.04 98 [77,] 3.08 99 [78,] 3.12 111 [79,] 3.16 90 [80,] 3.20 84 [81,] 3.24 107 [82,] 3.28 112 [83,] 3.32 110 [84,] 3.36 96 [85,] 3.40 83 [86,] 3.44 92 [87,] 3.48 79 [88,] 3.52 98 [89,] 3.56 97 [90,] 3.60 105 [91,] 3.64 108 [92,] 3.68 104 [93,] 3.72 108 [94,] 3.76 69 [95,] 3.80 99 [96,] 3.84 105 [97,] 3.88 98 [98,] 3.92 98 [99,] 3.96 84 [100,] 4.00 130 [101,] 4.04 88 [102,] 4.08 110 [103,] 4.12 82 [104,] 4.16 91 [105,] 4.20 97 [106,] 4.24 99 [107,] 4.28 80 [108,] 4.32 90 [109,] 4.36 93 [110,] 4.40 80 [111,] 4.44 83 [112,] 4.48 83 [113,] 4.52 96 [114,] 4.56 96 [115,] 4.60 100 [116,] 4.64 86 [117,] 4.68 82 [118,] 4.72 86 [119,] 4.76 86 [120,] 4.80 109 [121,] 4.84 77 [122,] 4.88 114 [123,] 4.92 97 [124,] 4.96 92 [125,] 5.00 62 [126,] 5.04 83 [127,] 5.08 93 [128,] 5.12 116 [129,] 5.16 91 [130,] 5.20 91 [131,] 5.24 83 [132,] 5.28 85 [133,] 5.32 85 [134,] 5.36 97 [135,] 5.40 89 [136,] 5.44 81 [137,] 5.48 78 [138,] 5.52 69 [139,] 5.56 84 [140,] 5.60 86 [141,] 5.64 69 [142,] 5.68 95 [143,] 5.72 89 [144,] 5.76 87 [145,] 5.80 71 [146,] 5.84 64 [147,] 5.88 78 [148,] 5.92 94 [149,] 5.96 63 [150,] 6.00 79 [151,] 6.04 74 [152,] 6.08 82 [153,] 6.12 82 [154,] 6.16 71 [155,] 6.20 72 [156,] 6.24 97 [157,] 6.28 91 [158,] 6.32 76 [159,] 6.36 85 [160,] 6.40 81 [161,] 6.44 88 [162,] 6.48 86 [163,] 6.52 67 [164,] 6.56 94 [165,] 6.60 95 [166,] 6.64 81 [167,] 6.68 76 [168,] 6.72 70 [169,] 6.76 81 [170,] 6.80 76 [171,] 6.84 76 [172,] 6.88 77 [173,] 6.92 69 [174,] 6.96 85 [175,] 7.00 98 [176,] 7.04 73 [177,] 7.08 93 [178,] 7.12 78 [179,] 7.16 95 [180,] 7.20 62 [181,] 7.24 81 [182,] 7.28 78 [183,] 7.32 84 [184,] 7.36 73 [185,] 7.40 84 [186,] 7.44 84 [187,] 7.48 66 [188,] 7.52 77 [189,] 7.56 76 [190,] 7.60 75 [191,] 7.64 88 [192,] 7.68 76 [193,] 7.72 95 [194,] 7.76 74 [195,] 7.80 85 [196,] 7.84 67 [197,] 7.88 78 [198,] 7.92 82 [199,] 7.96 108 [200,] 8.00 78 [201,] 8.04 56 [202,] 8.08 97 [203,] 8.12 93 [204,] 8.16 79 [205,] 8.20 88 [206,] 8.24 92 [207,] 8.28 60 [208,] 8.32 79 [209,] 8.36 76 [210,] 8.40 70 [211,] 8.44 73 [212,] 8.48 56 [213,] 8.52 65 [214,] 8.56 76 [215,] 8.60 86 [216,] 8.64 82 [217,] 8.68 75 [218,] 8.72 73 [219,] 8.76 79 [220,] 8.80 63 [221,] 8.84 86 [222,] 8.88 79 [223,] 8.92 89 [224,] 8.96 69 [225,] 9.00 74 [226,] 9.04 71 [227,] 9.08 56 [228,] 9.12 83 [229,] 9.16 83 [230,] 9.20 64 [231,] 9.24 83 [232,] 9.28 91 [233,] 9.32 97 [234,] 9.36 73 [235,] 9.40 87 [236,] 9.44 63 [237,] 9.48 56 [238,] 9.52 68 [239,] 9.56 69 [240,] 9.60 70 [241,] 9.64 66 [242,] 9.68 84 [243,] 9.72 98 [244,] 9.76 73 [245,] 9.80 68 [246,] 9.84 107 [247,] 9.88 68 [248,] 9.92 70 [249,] 9.96 78 [250,] 10.00 60 [251,] 10.04 92 [252,] 10.08 59 [253,] 10.12 77 [254,] 10.16 66 [255,] 10.20 61 [256,] 10.24 56 [257,] 10.28 89 [258,] 10.32 87 [259,] 10.36 90 [260,] 10.40 83 [261,] 10.44 97 [262,] 10.48 71 [263,] 10.52 49 [264,] 10.56 88 [265,] 10.60 92 [266,] 10.64 76 [267,] 10.68 97 [268,] 10.72 81 [269,] 10.76 78 [270,] 10.80 76 [271,] 10.84 73 [272,] 10.88 67 [273,] 10.92 90 [274,] 10.96 83 [275,] 11.00 68 [276,] 11.04 70 [277,] 11.08 69 [278,] 11.12 78 [279,] 11.16 83 [280,] 11.20 65 [281,] 11.24 96 [282,] 11.28 100 [283,] 11.32 74 [284,] 11.36 68 [285,] 11.40 86 [286,] 11.44 70 [287,] 11.48 66 [288,] 11.52 77 [289,] 11.56 63 [290,] 11.60 84 [291,] 11.64 72 [292,] 11.68 96 [293,] 11.72 58 [294,] 11.76 66 [295,] 11.80 69 [296,] 11.84 72 [297,] 11.88 70 [298,] 11.92 69 [299,] 11.96 66 [300,] 12.00 74 [301,] 12.04 76 [302,] 12.08 55 [303,] 12.12 68 [304,] 12.16 73 [305,] 12.20 116 [306,] 12.24 65 [307,] 12.28 80 [308,] 12.32 76 [309,] 12.36 88 [310,] 12.40 75 [311,] 12.44 60 [312,] 12.48 95 [313,] 12.52 82 [314,] 12.56 71 [315,] 12.60 79 [316,] 12.64 73 [317,] 12.68 90 [318,] 12.72 62 [319,] 12.76 78 [320,] 12.80 72 [321,] 12.84 63 [322,] 12.88 74 [323,] 12.92 72 [324,] 12.96 89 [325,] 13.00 83 [326,] 13.04 73 [327,] 13.08 62 [328,] 13.12 72 [329,] 13.16 57 [330,] 13.20 59 [331,] 13.24 93 [332,] 13.28 77 [333,] 13.32 76 [334,] 13.36 70 [335,] 13.40 66 [336,] 13.44 80 [337,] 13.48 89 [338,] 13.52 64 [339,] 13.56 86 [340,] 13.60 63 [341,] 13.64 65 [342,] 13.68 78 [343,] 13.72 70 [344,] 13.76 65 [345,] 13.80 74 [346,] 13.84 72 [347,] 13.88 65 [348,] 13.92 83 [349,] 13.96 70 [350,] 14.00 83 [351,] 14.04 80 [352,] 14.08 93 [353,] 14.12 89 [354,] 14.16 76 [355,] 14.20 83 [356,] 14.24 93 [357,] 14.28 82 [358,] 14.32 74 [359,] 14.36 79 [360,] 14.40 64 [361,] 14.44 71 [362,] 14.48 105 [363,] 14.52 75 [364,] 14.56 79 [365,] 14.60 63 [366,] 14.64 72 [367,] 14.68 83 [368,] 14.72 61 [369,] 14.76 64 [370,] 14.80 74 [371,] 14.84 65 [372,] 14.88 73 [373,] 14.92 58 [374,] 14.96 89 [375,] 15.00 64 [376,] 15.04 74 [377,] 15.08 73 [378,] 15.12 86 [379,] 15.16 67 [380,] 15.20 74 [381,] 15.24 82 [382,] 15.28 67 [383,] 15.32 69 [384,] 15.36 91 [385,] 15.40 58 [386,] 15.44 68 [387,] 15.48 81 [388,] 15.52 86 [389,] 15.56 47 [390,] 15.60 70 [391,] 15.64 68 [392,] 15.68 75 [393,] 15.72 55 [394,] 15.76 65 [395,] 15.80 77 [396,] 15.84 78 [397,] 15.88 72 [398,] 15.92 59 [399,] 15.96 60 [400,] 16.00 64 [401,] 16.04 47 [402,] 16.08 60 [403,] 16.12 71 [404,] 16.16 67 [405,] 16.20 61 [406,] 16.24 69 [407,] 16.28 61 [408,] 16.32 65 [409,] 16.36 66 [410,] 16.40 80 [411,] 16.44 77 [412,] 16.48 66 [413,] 16.52 63 [414,] 16.56 76 [415,] 16.60 80 [416,] 16.64 90 [417,] 16.68 81 [418,] 16.72 66 [419,] 16.76 71 [420,] 16.80 75 [421,] 16.84 73 [422,] 16.88 75 [423,] 16.92 61 [424,] 16.96 68 [425,] 17.00 50 [426,] 17.04 62 [427,] 17.08 68 [428,] 17.12 89 [429,] 17.16 77 [430,] 17.20 72 [431,] 17.24 75 [432,] 17.28 58 [433,] 17.32 65 [434,] 17.36 69 [435,] 17.40 60 [436,] 17.44 72 [437,] 17.48 56 [438,] 17.52 63 [439,] 17.56 79 [440,] 17.60 66 [441,] 17.64 73 [442,] 17.68 90 [443,] 17.72 64 [444,] 17.76 73 [445,] 17.80 68 [446,] 17.84 71 [447,] 17.88 61 [448,] 17.92 50 [449,] 17.96 75 [450,] 18.00 76 [451,] 18.04 66 [452,] 18.08 73 [453,] 18.12 64 [454,] 18.16 52 [455,] 18.20 80 [456,] 18.24 65 [457,] 18.28 84 [458,] 18.32 90 [459,] 18.36 75 [460,] 18.40 77 [461,] 18.44 46 [462,] 18.48 77 [463,] 18.52 70 [464,] 18.56 78 [465,] 18.60 52 [466,] 18.64 56 [467,] 18.68 51 [468,] 18.72 72 [469,] 18.76 64 [470,] 18.80 65 [471,] 18.84 59 [472,] 18.88 73 [473,] 18.92 54 [474,] 18.96 70 [475,] 19.00 81 [476,] 19.04 61 [477,] 19.08 69 [478,] 19.12 75 [479,] 19.16 71 [480,] 19.20 68 [481,] 19.24 85 [482,] 19.28 71 [483,] 19.32 57 [484,] 19.36 74 [485,] 19.40 67 [486,] 19.44 76 [487,] 19.48 83 [488,] 19.52 76 [489,] 19.56 99 [490,] 19.60 80 [491,] 19.64 66 [492,] 19.68 54 [493,] 19.72 76 [494,] 19.76 75 [495,] 19.80 76 [496,] 19.84 81 [497,] 19.88 71 [498,] 19.92 53 [499,] 19.96 65 [500,] 20.00 60 [501,] 20.04 65 [502,] 20.08 68 [503,] 20.12 66 [504,] 20.16 65 [505,] 20.20 91 [506,] 20.24 65 [507,] 20.28 72 [508,] 20.32 73 [509,] 20.36 78 [510,] 20.40 70 [511,] 20.44 70 [512,] 20.48 71 [513,] 20.52 66 [514,] 20.56 52 [515,] 20.60 68 [516,] 20.64 58 [517,] 20.68 85 [518,] 20.72 56 [519,] 20.76 68 [520,] 20.80 71 [521,] 20.84 80 [522,] 20.88 59 [523,] 20.92 63 [524,] 20.96 59 [525,] 21.00 70 [526,] 21.04 60 [527,] 21.08 64 [528,] 21.12 64 [529,] 21.16 72 [530,] 21.20 83 [531,] 21.24 69 [532,] 21.28 66 [533,] 21.32 67 [534,] 21.36 75 [535,] 21.40 63 [536,] 21.44 79 [537,] 21.48 64 [538,] 21.52 73 [539,] 21.56 60 [540,] 21.60 65 [541,] 21.64 71 [542,] 21.68 57 [543,] 21.72 58 [544,] 21.76 70 [545,] 21.80 78 [546,] 21.84 70 [547,] 21.88 75 [548,] 21.92 62 [549,] 21.96 62 [550,] 22.00 68 [551,] 22.04 79 [552,] 22.08 51 [553,] 22.12 76 [554,] 22.16 71 [555,] 22.20 55 [556,] 22.24 73 [557,] 22.28 90 [558,] 22.32 92 [559,] 22.36 76 [560,] 22.40 54 [561,] 22.44 68 [562,] 22.48 64 [563,] 22.52 69 [564,] 22.56 41 [565,] 22.60 52 [566,] 22.64 70 [567,] 22.68 70 [568,] 22.72 75 [569,] 22.76 63 [570,] 22.80 74 [571,] 22.84 64 [572,] 22.88 74 [573,] 22.92 73 [574,] 22.96 69 [575,] 23.00 60 [576,] 23.04 73 [577,] 23.08 83 [578,] 23.12 59 [579,] 23.16 66 [580,] 23.20 63 [581,] 23.24 61 [582,] 23.28 68 [583,] 23.32 90 [584,] 23.36 64 [585,] 23.40 70 [586,] 23.44 55 [587,] 23.48 62 [588,] 23.52 67 [589,] 23.56 60 [590,] 23.60 68 [591,] 23.64 73 [592,] 23.68 73 [593,] 23.72 71 [594,] 23.76 69 [595,] 23.80 73 [596,] 23.84 63 [597,] 23.88 63 [598,] 23.92 71 [599,] 23.96 58 [600,] 24.00 49 [601,] 24.04 62 [602,] 24.08 70 [603,] 24.12 56 [604,] 24.16 78 [605,] 24.20 74 [606,] 24.24 63 [607,] 24.28 68 [608,] 24.32 57 [609,] 24.36 51 [610,] 24.40 61 [611,] 24.44 77 [612,] 24.48 62 [613,] 24.52 62 [614,] 24.56 61 [615,] 24.60 66 [616,] 24.64 71 [617,] 24.68 73 [618,] 24.72 63 [619,] 24.76 48 [620,] 24.80 80 [621,] 24.84 52 [622,] 24.88 69 [623,] 24.92 71 [624,] 24.96 54 [625,] 25.00 63 [626,] 25.04 68 [627,] 25.08 62 [628,] 25.12 63 [629,] 25.16 55 [630,] 25.20 59 [631,] 25.24 84 [632,] 25.28 64 [633,] 25.32 56 [634,] 25.36 64 [635,] 25.40 64 [636,] 25.44 61 [637,] 25.48 63 [638,] 25.52 72 [639,] 25.56 55 [640,] 25.60 58 [641,] 25.64 66 [642,] 25.68 75 [643,] 25.72 72 [644,] 25.76 44 [645,] 25.80 58 [646,] 25.84 68 [647,] 25.88 67 [648,] 25.92 64 [649,] 25.96 69 [650,] 26.00 60 [651,] 26.04 65 [652,] 26.08 65 [653,] 26.12 69 [654,] 26.16 60 [655,] 26.20 62 [656,] 26.24 64 [657,] 26.28 72 [658,] 26.32 76 [659,] 26.36 60 [660,] 26.40 74 [661,] 26.44 86 [662,] 26.48 50 [663,] 26.52 65 [664,] 26.56 61 [665,] 26.60 76 [666,] 26.64 74 [667,] 26.68 72 [668,] 26.72 70 [669,] 26.76 65 [670,] 26.80 56 [671,] 26.84 62 [672,] 26.88 55 [673,] 26.92 39 [674,] 26.96 74 [675,] 27.00 59 [676,] 27.04 82 [677,] 27.08 61 [678,] 27.12 63 [679,] 27.16 68 [680,] 27.20 51 [681,] 27.24 80 [682,] 27.28 50 [683,] 27.32 69 [684,] 27.36 69 [685,] 27.40 51 [686,] 27.44 65 [687,] 27.48 89 [688,] 27.52 70 [689,] 27.56 54 [690,] 27.60 66 [691,] 27.64 66 [692,] 27.68 74 [693,] 27.72 73 [694,] 27.76 59 [695,] 27.80 64 [696,] 27.84 89 [697,] 27.88 65 [698,] 27.92 79 [699,] 27.96 63 [700,] 28.00 60 [701,] 28.04 63 [702,] 28.08 66 [703,] 28.12 60 [704,] 28.16 58 [705,] 28.20 91 [706,] 28.24 60 [707,] 28.28 64 [708,] 28.32 79 [709,] 28.36 43 [710,] 28.40 50 [711,] 28.44 63 [712,] 28.48 66 [713,] 28.52 53 [714,] 28.56 68 [715,] 28.60 69 [716,] 28.64 69 [717,] 28.68 62 [718,] 28.72 89 [719,] 28.76 63 [720,] 28.80 77 [721,] 28.84 77 [722,] 28.88 68 [723,] 28.92 66 [724,] 28.96 45 [725,] 29.00 49 [726,] 29.04 60 [727,] 29.08 71 [728,] 29.12 77 [729,] 29.16 57 [730,] 29.20 66 [731,] 29.24 67 [732,] 29.28 53 [733,] 29.32 63 [734,] 29.36 57 [735,] 29.40 81 [736,] 29.44 69 [737,] 29.48 65 [738,] 29.52 62 [739,] 29.56 73 [740,] 29.60 61 [741,] 29.64 61 [742,] 29.68 77 [743,] 29.72 78 [744,] 29.76 60 [745,] 29.80 78 [746,] 29.84 63 [747,] 29.88 68 [748,] 29.92 56 [749,] 29.96 61 [750,] 30.00 59 [751,] 30.04 84 [752,] 30.08 65 [753,] 30.12 61 [754,] 30.16 58 [755,] 30.20 57 [756,] 30.24 73 [757,] 30.28 65 [758,] 30.32 65 [759,] 30.36 65 [760,] 30.40 64 [761,] 30.44 90 [762,] 30.48 77 [763,] 30.52 58 [764,] 30.56 60 [765,] 30.60 78 [766,] 30.64 73 [767,] 30.68 78 [768,] 30.72 57 [769,] 30.76 53 [770,] 30.80 52 [771,] 30.84 70 [772,] 30.88 63 [773,] 30.92 55 [774,] 30.96 65 [775,] 31.00 80 [776,] 31.04 64 [777,] 31.08 48 [778,] 31.12 77 [779,] 31.16 67 [780,] 31.20 65 [781,] 31.24 67 [782,] 31.28 46 [783,] 31.32 67 [784,] 31.36 73 [785,] 31.40 64 [786,] 31.44 69 [787,] 31.48 60 [788,] 31.52 59 [789,] 31.56 56 [790,] 31.60 43 [791,] 31.64 79 [792,] 31.68 55 [793,] 31.72 83 [794,] 31.76 73 [795,] 31.80 74 [796,] 31.84 59 [797,] 31.88 75 [798,] 31.92 88 [799,] 31.96 63 [800,] 32.00 58 [801,] 32.04 56 [802,] 32.08 53 [803,] 32.12 76 [804,] 32.16 86 [805,] 32.20 58 [806,] 32.24 55 [807,] 32.28 64 [808,] 32.32 59 [809,] 32.36 68 [810,] 32.40 65 [811,] 32.44 61 [812,] 32.48 58 [813,] 32.52 53 [814,] 32.56 61 [815,] 32.60 65 [816,] 32.64 54 [817,] 32.68 67 [818,] 32.72 71 [819,] 32.76 77 [820,] 32.80 77 [821,] 32.84 58 [822,] 32.88 67 [823,] 32.92 61 [824,] 32.96 85 [825,] 33.00 49 [826,] 33.04 75 [827,] 33.08 66 [828,] 33.12 72 [829,] 33.16 64 [830,] 33.20 53 [831,] 33.24 59 [832,] 33.28 73 [833,] 33.32 62 [834,] 33.36 63 [835,] 33.40 63 [836,] 33.44 64 [837,] 33.48 54 [838,] 33.52 53 [839,] 33.56 52 [840,] 33.60 51 [841,] 33.64 64 [842,] 33.68 74 [843,] 33.72 54 [844,] 33.76 53 [845,] 33.80 59 [846,] 33.84 63 [847,] 33.88 63 [848,] 33.92 57 [849,] 33.96 57 [850,] 34.00 77 [851,] 34.04 66 [852,] 34.08 53 [853,] 34.12 72 [854,] 34.16 63 [855,] 34.20 66 [856,] 34.24 88 [857,] 34.28 54 [858,] 34.32 57 [859,] 34.36 71 [860,] 34.40 58 [861,] 34.44 71 [862,] 34.48 60 [863,] 34.52 68 [864,] 34.56 65 [865,] 34.60 58 [866,] 34.64 57 [867,] 34.68 58 [868,] 34.72 67 [869,] 34.76 66 [870,] 34.80 53 [871,] 34.84 75 [872,] 34.88 77 [873,] 34.92 51 [874,] 34.96 63 [875,] 35.00 53 [876,] 35.04 59 [877,] 35.08 63 [878,] 35.12 63 [879,] 35.16 63 [880,] 35.20 65 [881,] 35.24 72 [882,] 35.28 75 [883,] 35.32 60 [884,] 35.36 62 [885,] 35.40 63 [886,] 35.44 61 [887,] 35.48 58 [888,] 35.52 70 [889,] 35.56 49 [890,] 35.60 58 [891,] 35.64 50 [892,] 35.68 50 [893,] 35.72 53 [894,] 35.76 62 [895,] 35.80 61 [896,] 35.84 78 [897,] 35.88 61 [898,] 35.92 67 [899,] 35.96 54 [900,] 36.00 55 [901,] 36.04 56 [902,] 36.08 49 [903,] 36.12 52 [904,] 36.16 60 [905,] 36.20 50 [906,] 36.24 72 [907,] 36.28 60 [908,] 36.32 63 [909,] 36.36 56 [910,] 36.40 56 [911,] 36.44 50 [912,] 36.48 65 [913,] 36.52 59 [914,] 36.56 70 [915,] 36.60 68 [916,] 36.64 72 [917,] 36.68 81 [918,] 36.72 65 [919,] 36.76 65 [920,] 36.80 60 [921,] 36.84 69 [922,] 36.88 54 [923,] 36.92 75 [924,] 36.96 49 [925,] 37.00 64 [926,] 37.04 54 [927,] 37.08 39 [928,] 37.12 58 [929,] 37.16 58 [930,] 37.20 59 [931,] 37.24 52 [932,] 37.28 56 [933,] 37.32 62 [934,] 37.36 76 [935,] 37.40 56 [936,] 37.44 58 [937,] 37.48 52 [938,] 37.52 57 [939,] 37.56 69 [940,] 37.60 48 [941,] 37.64 60 [942,] 37.68 61 [943,] 37.72 54 [944,] 37.76 73 [945,] 37.80 64 [946,] 37.84 53 [947,] 37.88 57 [948,] 37.92 67 [949,] 37.96 57 [950,] 38.00 67 [951,] 38.04 60 [952,] 38.08 44 [953,] 38.12 53 [954,] 38.16 70 [955,] 38.20 61 [956,] 38.24 69 [957,] 38.28 63 [958,] 38.32 73 [959,] 38.36 78 [960,] 38.40 74 [961,] 38.44 78 [962,] 38.48 56 [963,] 38.52 77 [964,] 38.56 59 [965,] 38.60 75 [966,] 38.64 52 [967,] 38.68 46 [968,] 38.72 62 [969,] 38.76 78 [970,] 38.80 66 [971,] 38.84 71 [972,] 38.88 40 [973,] 38.92 64 [974,] 38.96 49 [975,] 39.00 72 [976,] 39.04 55 [977,] 39.08 62 [978,] 39.12 60 [979,] 39.16 68 [980,] 39.20 63 [981,] 39.24 66 [982,] 39.28 63 [983,] 39.32 53 [984,] 39.36 65 [985,] 39.40 48 [986,] 39.44 60 [987,] 39.48 58 [988,] 39.52 52 [989,] 39.56 71 [990,] 39.60 60 [991,] 39.64 56 [992,] 39.68 57 [993,] 39.72 71 [994,] 39.76 80 [995,] 39.80 60 [996,] 39.84 75 [997,] 39.88 74 [998,] 39.92 60 [999,] 39.96 46 [1000,] 40.00 45 $`23_TL (PMT)` [,1] [,2] [1,] 0.64 22 [2,] 1.28 2 [3,] 1.92 2 [4,] 2.56 5 [5,] 3.20 6 [6,] 3.84 5 [7,] 4.48 2 [8,] 5.12 6 [9,] 5.76 5 [10,] 6.40 4 [11,] 7.04 2 [12,] 7.68 15 [13,] 8.32 5 [14,] 8.96 10 [15,] 9.60 7 [16,] 10.24 4 [17,] 10.88 1 [18,] 11.52 9 [19,] 12.16 4 [20,] 12.80 3 [21,] 13.44 3 [22,] 14.08 2 [23,] 14.72 10 [24,] 15.36 4 [25,] 16.00 3 [26,] 16.64 2 [27,] 17.28 5 [28,] 17.92 6 [29,] 18.56 6 [30,] 19.20 10 [31,] 19.84 6 [32,] 20.48 3 [33,] 21.12 10 [34,] 21.76 8 [35,] 22.40 1 [36,] 23.04 9 [37,] 23.68 0 [38,] 24.32 10 [39,] 24.96 4 [40,] 25.60 4 [41,] 26.24 8 [42,] 26.88 2 [43,] 27.52 6 [44,] 28.16 0 [45,] 28.80 4 [46,] 29.44 10 [47,] 30.08 9 [48,] 30.72 0 [49,] 31.36 5 [50,] 32.00 7 [51,] 32.64 7 [52,] 33.28 4 [53,] 33.92 6 [54,] 34.56 5 [55,] 35.20 2 [56,] 35.84 10 [57,] 36.48 5 [58,] 37.12 5 [59,] 37.76 9 [60,] 38.40 5 [61,] 39.04 3 [62,] 39.68 1 [63,] 40.32 0 [64,] 40.96 4 [65,] 41.60 1 [66,] 42.24 5 [67,] 42.88 5 [68,] 43.52 34 [69,] 44.16 3 [70,] 44.80 11 [71,] 45.44 6 [72,] 46.08 6 [73,] 46.72 6 [74,] 47.36 5 [75,] 48.00 3 [76,] 48.64 14 [77,] 49.28 2 [78,] 49.92 7 [79,] 50.56 11 [80,] 51.20 1 [81,] 51.84 7 [82,] 52.48 3 [83,] 53.12 3 [84,] 53.76 8 [85,] 54.40 4 [86,] 55.04 9 [87,] 55.68 19 [88,] 56.32 8 [89,] 56.96 9 [90,] 57.60 12 [91,] 58.24 12 [92,] 58.88 14 [93,] 59.52 12 [94,] 60.16 7 [95,] 60.80 14 [96,] 61.44 21 [97,] 62.08 14 [98,] 62.72 30 [99,] 63.36 16 [100,] 64.00 17 [101,] 64.64 8 [102,] 65.28 33 [103,] 65.92 20 [104,] 66.56 35 [105,] 67.20 35 [106,] 67.84 22 [107,] 68.48 25 [108,] 69.12 21 [109,] 69.76 42 [110,] 70.40 22 [111,] 71.04 31 [112,] 71.68 31 [113,] 72.32 29 [114,] 72.96 29 [115,] 73.60 44 [116,] 74.24 42 [117,] 74.88 47 [118,] 75.52 58 [119,] 76.16 40 [120,] 76.80 51 [121,] 77.44 58 [122,] 78.08 74 [123,] 78.72 55 [124,] 79.36 68 [125,] 80.00 55 [126,] 80.64 76 [127,] 81.28 74 [128,] 81.92 88 [129,] 82.56 80 [130,] 83.20 98 [131,] 83.84 95 [132,] 84.48 99 [133,] 85.12 109 [134,] 85.76 104 [135,] 86.40 136 [136,] 87.04 114 [137,] 87.68 132 [138,] 88.32 159 [139,] 88.96 119 [140,] 89.60 165 [141,] 90.24 160 [142,] 90.88 162 [143,] 91.52 168 [144,] 92.16 123 [145,] 92.80 170 [146,] 93.44 165 [147,] 94.08 193 [148,] 94.72 159 [149,] 95.36 191 [150,] 96.00 206 [151,] 96.64 231 [152,] 97.28 229 [153,] 97.92 225 [154,] 98.56 239 [155,] 99.20 248 [156,] 99.84 240 [157,] 100.48 267 [158,] 101.12 238 [159,] 101.76 270 [160,] 102.40 270 [161,] 103.04 256 [162,] 103.68 272 [163,] 104.32 237 [164,] 104.96 273 [165,] 105.60 238 [166,] 106.24 251 [167,] 106.88 270 [168,] 107.52 258 [169,] 108.16 252 [170,] 108.80 239 [171,] 109.44 244 [172,] 110.08 245 [173,] 110.72 233 [174,] 111.36 235 [175,] 112.00 238 [176,] 112.64 222 [177,] 113.28 208 [178,] 113.92 219 [179,] 114.56 227 [180,] 115.20 185 [181,] 115.84 196 [182,] 116.48 162 [183,] 117.12 155 [184,] 117.76 155 [185,] 118.40 136 [186,] 119.04 133 [187,] 119.68 120 [188,] 120.32 150 [189,] 120.96 126 [190,] 121.60 115 [191,] 122.24 126 [192,] 122.88 108 [193,] 123.52 102 [194,] 124.16 107 [195,] 124.80 106 [196,] 125.44 113 [197,] 126.08 97 [198,] 126.72 94 [199,] 127.36 92 [200,] 128.00 78 [201,] 128.64 92 [202,] 129.28 76 [203,] 129.92 80 [204,] 130.56 81 [205,] 131.20 90 [206,] 131.84 90 [207,] 132.48 98 [208,] 133.12 65 [209,] 133.76 95 [210,] 134.40 108 [211,] 135.04 100 [212,] 135.68 77 [213,] 136.32 87 [214,] 136.96 89 [215,] 137.60 110 [216,] 138.24 68 [217,] 138.88 75 [218,] 139.52 89 [219,] 140.16 90 [220,] 140.80 91 [221,] 141.44 88 [222,] 142.08 100 [223,] 142.72 84 [224,] 143.36 100 [225,] 144.00 114 [226,] 144.64 97 [227,] 145.28 94 [228,] 145.92 95 [229,] 146.56 87 [230,] 147.20 95 [231,] 147.84 93 [232,] 148.48 84 [233,] 149.12 91 [234,] 149.76 88 [235,] 150.40 83 [236,] 151.04 102 [237,] 151.68 91 [238,] 152.32 89 [239,] 152.96 89 [240,] 153.60 109 [241,] 154.24 99 [242,] 154.88 103 [243,] 155.52 76 [244,] 156.16 84 [245,] 156.80 85 [246,] 157.44 79 [247,] 158.08 88 [248,] 158.72 80 [249,] 159.36 80 [250,] 160.00 87 $`24_OSL (PMT)` [,1] [,2] [1,] 0.04 3179 [2,] 0.08 2681 [3,] 0.12 2278 [4,] 0.16 2056 [5,] 0.20 1749 [6,] 0.24 1564 [7,] 0.28 1299 [8,] 0.32 1280 [9,] 0.36 1088 [10,] 0.40 1041 [11,] 0.44 824 [12,] 0.48 745 [13,] 0.52 677 [14,] 0.56 653 [15,] 0.60 536 [16,] 0.64 483 [17,] 0.68 446 [18,] 0.72 404 [19,] 0.76 398 [20,] 0.80 360 [21,] 0.84 338 [22,] 0.88 322 [23,] 0.92 296 [24,] 0.96 270 [25,] 1.00 271 [26,] 1.04 223 [27,] 1.08 256 [28,] 1.12 236 [29,] 1.16 272 [30,] 1.20 236 [31,] 1.24 222 [32,] 1.28 205 [33,] 1.32 204 [34,] 1.36 202 [35,] 1.40 171 [36,] 1.44 170 [37,] 1.48 164 [38,] 1.52 163 [39,] 1.56 188 [40,] 1.60 165 [41,] 1.64 134 [42,] 1.68 130 [43,] 1.72 146 [44,] 1.76 130 [45,] 1.80 144 [46,] 1.84 144 [47,] 1.88 122 [48,] 1.92 155 [49,] 1.96 142 [50,] 2.00 143 [51,] 2.04 116 [52,] 2.08 121 [53,] 2.12 134 [54,] 2.16 102 [55,] 2.20 136 [56,] 2.24 128 [57,] 2.28 111 [58,] 2.32 108 [59,] 2.36 113 [60,] 2.40 115 [61,] 2.44 134 [62,] 2.48 135 [63,] 2.52 109 [64,] 2.56 113 [65,] 2.60 113 [66,] 2.64 120 [67,] 2.68 102 [68,] 2.72 116 [69,] 2.76 116 [70,] 2.80 126 [71,] 2.84 114 [72,] 2.88 106 [73,] 2.92 114 [74,] 2.96 95 [75,] 3.00 127 [76,] 3.04 103 [77,] 3.08 87 [78,] 3.12 127 [79,] 3.16 93 [80,] 3.20 98 [81,] 3.24 123 [82,] 3.28 130 [83,] 3.32 104 [84,] 3.36 106 [85,] 3.40 103 [86,] 3.44 93 [87,] 3.48 107 [88,] 3.52 89 [89,] 3.56 114 [90,] 3.60 125 [91,] 3.64 103 [92,] 3.68 95 [93,] 3.72 88 [94,] 3.76 122 [95,] 3.80 97 [96,] 3.84 108 [97,] 3.88 123 [98,] 3.92 118 [99,] 3.96 97 [100,] 4.00 120 [101,] 4.04 102 [102,] 4.08 117 [103,] 4.12 107 [104,] 4.16 98 [105,] 4.20 134 [106,] 4.24 122 [107,] 4.28 97 [108,] 4.32 118 [109,] 4.36 79 [110,] 4.40 100 [111,] 4.44 106 [112,] 4.48 93 [113,] 4.52 97 [114,] 4.56 90 [115,] 4.60 109 [116,] 4.64 85 [117,] 4.68 97 [118,] 4.72 94 [119,] 4.76 100 [120,] 4.80 104 [121,] 4.84 112 [122,] 4.88 95 [123,] 4.92 86 [124,] 4.96 98 [125,] 5.00 85 [126,] 5.04 108 [127,] 5.08 87 [128,] 5.12 75 [129,] 5.16 85 [130,] 5.20 75 [131,] 5.24 84 [132,] 5.28 92 [133,] 5.32 101 [134,] 5.36 105 [135,] 5.40 84 [136,] 5.44 94 [137,] 5.48 95 [138,] 5.52 84 [139,] 5.56 101 [140,] 5.60 90 [141,] 5.64 75 [142,] 5.68 91 [143,] 5.72 92 [144,] 5.76 97 [145,] 5.80 94 [146,] 5.84 91 [147,] 5.88 86 [148,] 5.92 91 [149,] 5.96 113 [150,] 6.00 70 [151,] 6.04 85 [152,] 6.08 81 [153,] 6.12 97 [154,] 6.16 74 [155,] 6.20 93 [156,] 6.24 72 [157,] 6.28 86 [158,] 6.32 105 [159,] 6.36 107 [160,] 6.40 105 [161,] 6.44 92 [162,] 6.48 104 [163,] 6.52 92 [164,] 6.56 91 [165,] 6.60 78 [166,] 6.64 83 [167,] 6.68 103 [168,] 6.72 70 [169,] 6.76 82 [170,] 6.80 86 [171,] 6.84 108 [172,] 6.88 88 [173,] 6.92 97 [174,] 6.96 90 [175,] 7.00 76 [176,] 7.04 94 [177,] 7.08 92 [178,] 7.12 88 [179,] 7.16 93 [180,] 7.20 81 [181,] 7.24 88 [182,] 7.28 86 [183,] 7.32 88 [184,] 7.36 75 [185,] 7.40 88 [186,] 7.44 89 [187,] 7.48 75 [188,] 7.52 82 [189,] 7.56 70 [190,] 7.60 91 [191,] 7.64 62 [192,] 7.68 75 [193,] 7.72 96 [194,] 7.76 67 [195,] 7.80 82 [196,] 7.84 87 [197,] 7.88 88 [198,] 7.92 102 [199,] 7.96 80 [200,] 8.00 73 [201,] 8.04 77 [202,] 8.08 82 [203,] 8.12 88 [204,] 8.16 61 [205,] 8.20 76 [206,] 8.24 90 [207,] 8.28 86 [208,] 8.32 81 [209,] 8.36 79 [210,] 8.40 106 [211,] 8.44 81 [212,] 8.48 107 [213,] 8.52 84 [214,] 8.56 83 [215,] 8.60 75 [216,] 8.64 79 [217,] 8.68 72 [218,] 8.72 71 [219,] 8.76 82 [220,] 8.80 72 [221,] 8.84 93 [222,] 8.88 90 [223,] 8.92 78 [224,] 8.96 88 [225,] 9.00 108 [226,] 9.04 79 [227,] 9.08 68 [228,] 9.12 96 [229,] 9.16 113 [230,] 9.20 87 [231,] 9.24 84 [232,] 9.28 83 [233,] 9.32 90 [234,] 9.36 85 [235,] 9.40 80 [236,] 9.44 109 [237,] 9.48 86 [238,] 9.52 88 [239,] 9.56 77 [240,] 9.60 84 [241,] 9.64 83 [242,] 9.68 94 [243,] 9.72 85 [244,] 9.76 93 [245,] 9.80 93 [246,] 9.84 71 [247,] 9.88 80 [248,] 9.92 90 [249,] 9.96 78 [250,] 10.00 78 [251,] 10.04 83 [252,] 10.08 81 [253,] 10.12 89 [254,] 10.16 89 [255,] 10.20 77 [256,] 10.24 92 [257,] 10.28 76 [258,] 10.32 68 [259,] 10.36 77 [260,] 10.40 100 [261,] 10.44 57 [262,] 10.48 90 [263,] 10.52 82 [264,] 10.56 77 [265,] 10.60 85 [266,] 10.64 90 [267,] 10.68 81 [268,] 10.72 86 [269,] 10.76 82 [270,] 10.80 74 [271,] 10.84 72 [272,] 10.88 71 [273,] 10.92 81 [274,] 10.96 90 [275,] 11.00 78 [276,] 11.04 74 [277,] 11.08 67 [278,] 11.12 73 [279,] 11.16 83 [280,] 11.20 78 [281,] 11.24 92 [282,] 11.28 66 [283,] 11.32 80 [284,] 11.36 74 [285,] 11.40 70 [286,] 11.44 73 [287,] 11.48 81 [288,] 11.52 82 [289,] 11.56 77 [290,] 11.60 64 [291,] 11.64 66 [292,] 11.68 56 [293,] 11.72 68 [294,] 11.76 79 [295,] 11.80 84 [296,] 11.84 89 [297,] 11.88 73 [298,] 11.92 83 [299,] 11.96 85 [300,] 12.00 77 [301,] 12.04 81 [302,] 12.08 92 [303,] 12.12 75 [304,] 12.16 77 [305,] 12.20 83 [306,] 12.24 73 [307,] 12.28 108 [308,] 12.32 86 [309,] 12.36 74 [310,] 12.40 99 [311,] 12.44 73 [312,] 12.48 59 [313,] 12.52 77 [314,] 12.56 94 [315,] 12.60 79 [316,] 12.64 80 [317,] 12.68 77 [318,] 12.72 66 [319,] 12.76 81 [320,] 12.80 87 [321,] 12.84 69 [322,] 12.88 89 [323,] 12.92 96 [324,] 12.96 89 [325,] 13.00 81 [326,] 13.04 83 [327,] 13.08 84 [328,] 13.12 70 [329,] 13.16 68 [330,] 13.20 81 [331,] 13.24 82 [332,] 13.28 85 [333,] 13.32 96 [334,] 13.36 80 [335,] 13.40 64 [336,] 13.44 71 [337,] 13.48 83 [338,] 13.52 80 [339,] 13.56 74 [340,] 13.60 88 [341,] 13.64 70 [342,] 13.68 69 [343,] 13.72 85 [344,] 13.76 79 [345,] 13.80 65 [346,] 13.84 72 [347,] 13.88 61 [348,] 13.92 102 [349,] 13.96 87 [350,] 14.00 70 [351,] 14.04 71 [352,] 14.08 71 [353,] 14.12 75 [354,] 14.16 82 [355,] 14.20 79 [356,] 14.24 80 [357,] 14.28 79 [358,] 14.32 96 [359,] 14.36 70 [360,] 14.40 97 [361,] 14.44 74 [362,] 14.48 58 [363,] 14.52 93 [364,] 14.56 83 [365,] 14.60 72 [366,] 14.64 90 [367,] 14.68 77 [368,] 14.72 73 [369,] 14.76 81 [370,] 14.80 78 [371,] 14.84 90 [372,] 14.88 65 [373,] 14.92 86 [374,] 14.96 78 [375,] 15.00 69 [376,] 15.04 79 [377,] 15.08 59 [378,] 15.12 65 [379,] 15.16 61 [380,] 15.20 66 [381,] 15.24 81 [382,] 15.28 77 [383,] 15.32 93 [384,] 15.36 67 [385,] 15.40 68 [386,] 15.44 86 [387,] 15.48 78 [388,] 15.52 62 [389,] 15.56 64 [390,] 15.60 64 [391,] 15.64 73 [392,] 15.68 70 [393,] 15.72 65 [394,] 15.76 101 [395,] 15.80 79 [396,] 15.84 63 [397,] 15.88 70 [398,] 15.92 94 [399,] 15.96 74 [400,] 16.00 67 [401,] 16.04 71 [402,] 16.08 68 [403,] 16.12 86 [404,] 16.16 59 [405,] 16.20 62 [406,] 16.24 107 [407,] 16.28 84 [408,] 16.32 74 [409,] 16.36 76 [410,] 16.40 83 [411,] 16.44 59 [412,] 16.48 81 [413,] 16.52 83 [414,] 16.56 56 [415,] 16.60 81 [416,] 16.64 81 [417,] 16.68 62 [418,] 16.72 69 [419,] 16.76 72 [420,] 16.80 72 [421,] 16.84 68 [422,] 16.88 85 [423,] 16.92 71 [424,] 16.96 84 [425,] 17.00 77 [426,] 17.04 57 [427,] 17.08 82 [428,] 17.12 81 [429,] 17.16 74 [430,] 17.20 68 [431,] 17.24 70 [432,] 17.28 67 [433,] 17.32 68 [434,] 17.36 79 [435,] 17.40 61 [436,] 17.44 66 [437,] 17.48 63 [438,] 17.52 76 [439,] 17.56 68 [440,] 17.60 58 [441,] 17.64 73 [442,] 17.68 94 [443,] 17.72 65 [444,] 17.76 63 [445,] 17.80 69 [446,] 17.84 70 [447,] 17.88 71 [448,] 17.92 54 [449,] 17.96 58 [450,] 18.00 71 [451,] 18.04 78 [452,] 18.08 70 [453,] 18.12 68 [454,] 18.16 72 [455,] 18.20 92 [456,] 18.24 68 [457,] 18.28 64 [458,] 18.32 69 [459,] 18.36 74 [460,] 18.40 71 [461,] 18.44 89 [462,] 18.48 62 [463,] 18.52 61 [464,] 18.56 63 [465,] 18.60 63 [466,] 18.64 93 [467,] 18.68 68 [468,] 18.72 73 [469,] 18.76 82 [470,] 18.80 70 [471,] 18.84 72 [472,] 18.88 92 [473,] 18.92 62 [474,] 18.96 70 [475,] 19.00 66 [476,] 19.04 84 [477,] 19.08 77 [478,] 19.12 71 [479,] 19.16 86 [480,] 19.20 80 [481,] 19.24 78 [482,] 19.28 83 [483,] 19.32 67 [484,] 19.36 72 [485,] 19.40 65 [486,] 19.44 68 [487,] 19.48 66 [488,] 19.52 57 [489,] 19.56 70 [490,] 19.60 83 [491,] 19.64 62 [492,] 19.68 90 [493,] 19.72 70 [494,] 19.76 95 [495,] 19.80 56 [496,] 19.84 71 [497,] 19.88 60 [498,] 19.92 71 [499,] 19.96 70 [500,] 20.00 65 [501,] 20.04 78 [502,] 20.08 85 [503,] 20.12 60 [504,] 20.16 69 [505,] 20.20 58 [506,] 20.24 73 [507,] 20.28 74 [508,] 20.32 70 [509,] 20.36 70 [510,] 20.40 65 [511,] 20.44 62 [512,] 20.48 68 [513,] 20.52 72 [514,] 20.56 73 [515,] 20.60 64 [516,] 20.64 72 [517,] 20.68 82 [518,] 20.72 68 [519,] 20.76 60 [520,] 20.80 67 [521,] 20.84 55 [522,] 20.88 75 [523,] 20.92 75 [524,] 20.96 81 [525,] 21.00 68 [526,] 21.04 62 [527,] 21.08 60 [528,] 21.12 72 [529,] 21.16 66 [530,] 21.20 67 [531,] 21.24 72 [532,] 21.28 66 [533,] 21.32 68 [534,] 21.36 82 [535,] 21.40 64 [536,] 21.44 75 [537,] 21.48 80 [538,] 21.52 83 [539,] 21.56 77 [540,] 21.60 59 [541,] 21.64 66 [542,] 21.68 86 [543,] 21.72 75 [544,] 21.76 61 [545,] 21.80 74 [546,] 21.84 62 [547,] 21.88 69 [548,] 21.92 61 [549,] 21.96 82 [550,] 22.00 79 [551,] 22.04 73 [552,] 22.08 58 [553,] 22.12 63 [554,] 22.16 75 [555,] 22.20 69 [556,] 22.24 67 [557,] 22.28 53 [558,] 22.32 94 [559,] 22.36 85 [560,] 22.40 59 [561,] 22.44 76 [562,] 22.48 73 [563,] 22.52 48 [564,] 22.56 56 [565,] 22.60 79 [566,] 22.64 90 [567,] 22.68 63 [568,] 22.72 70 [569,] 22.76 73 [570,] 22.80 57 [571,] 22.84 57 [572,] 22.88 66 [573,] 22.92 70 [574,] 22.96 88 [575,] 23.00 60 [576,] 23.04 64 [577,] 23.08 74 [578,] 23.12 93 [579,] 23.16 74 [580,] 23.20 77 [581,] 23.24 79 [582,] 23.28 82 [583,] 23.32 75 [584,] 23.36 80 [585,] 23.40 77 [586,] 23.44 97 [587,] 23.48 64 [588,] 23.52 88 [589,] 23.56 78 [590,] 23.60 74 [591,] 23.64 95 [592,] 23.68 61 [593,] 23.72 71 [594,] 23.76 59 [595,] 23.80 78 [596,] 23.84 79 [597,] 23.88 89 [598,] 23.92 59 [599,] 23.96 69 [600,] 24.00 76 [601,] 24.04 52 [602,] 24.08 76 [603,] 24.12 69 [604,] 24.16 76 [605,] 24.20 80 [606,] 24.24 86 [607,] 24.28 76 [608,] 24.32 51 [609,] 24.36 63 [610,] 24.40 63 [611,] 24.44 74 [612,] 24.48 64 [613,] 24.52 59 [614,] 24.56 63 [615,] 24.60 49 [616,] 24.64 55 [617,] 24.68 69 [618,] 24.72 55 [619,] 24.76 72 [620,] 24.80 77 [621,] 24.84 77 [622,] 24.88 57 [623,] 24.92 49 [624,] 24.96 62 [625,] 25.00 65 [626,] 25.04 60 [627,] 25.08 51 [628,] 25.12 59 [629,] 25.16 70 [630,] 25.20 50 [631,] 25.24 76 [632,] 25.28 77 [633,] 25.32 67 [634,] 25.36 69 [635,] 25.40 64 [636,] 25.44 61 [637,] 25.48 73 [638,] 25.52 50 [639,] 25.56 64 [640,] 25.60 75 [641,] 25.64 60 [642,] 25.68 66 [643,] 25.72 61 [644,] 25.76 68 [645,] 25.80 61 [646,] 25.84 55 [647,] 25.88 61 [648,] 25.92 66 [649,] 25.96 50 [650,] 26.00 73 [651,] 26.04 62 [652,] 26.08 61 [653,] 26.12 63 [654,] 26.16 53 [655,] 26.20 80 [656,] 26.24 75 [657,] 26.28 78 [658,] 26.32 65 [659,] 26.36 65 [660,] 26.40 66 [661,] 26.44 58 [662,] 26.48 62 [663,] 26.52 78 [664,] 26.56 54 [665,] 26.60 58 [666,] 26.64 68 [667,] 26.68 84 [668,] 26.72 67 [669,] 26.76 80 [670,] 26.80 69 [671,] 26.84 73 [672,] 26.88 64 [673,] 26.92 72 [674,] 26.96 77 [675,] 27.00 56 [676,] 27.04 76 [677,] 27.08 71 [678,] 27.12 70 [679,] 27.16 56 [680,] 27.20 72 [681,] 27.24 67 [682,] 27.28 74 [683,] 27.32 68 [684,] 27.36 77 [685,] 27.40 53 [686,] 27.44 70 [687,] 27.48 67 [688,] 27.52 49 [689,] 27.56 91 [690,] 27.60 74 [691,] 27.64 81 [692,] 27.68 70 [693,] 27.72 53 [694,] 27.76 63 [695,] 27.80 59 [696,] 27.84 61 [697,] 27.88 82 [698,] 27.92 72 [699,] 27.96 66 [700,] 28.00 67 [701,] 28.04 80 [702,] 28.08 55 [703,] 28.12 73 [704,] 28.16 73 [705,] 28.20 64 [706,] 28.24 65 [707,] 28.28 61 [708,] 28.32 71 [709,] 28.36 52 [710,] 28.40 74 [711,] 28.44 70 [712,] 28.48 63 [713,] 28.52 73 [714,] 28.56 72 [715,] 28.60 47 [716,] 28.64 73 [717,] 28.68 65 [718,] 28.72 83 [719,] 28.76 74 [720,] 28.80 72 [721,] 28.84 63 [722,] 28.88 65 [723,] 28.92 69 [724,] 28.96 70 [725,] 29.00 83 [726,] 29.04 67 [727,] 29.08 52 [728,] 29.12 67 [729,] 29.16 79 [730,] 29.20 56 [731,] 29.24 72 [732,] 29.28 75 [733,] 29.32 46 [734,] 29.36 57 [735,] 29.40 57 [736,] 29.44 70 [737,] 29.48 89 [738,] 29.52 82 [739,] 29.56 64 [740,] 29.60 59 [741,] 29.64 65 [742,] 29.68 62 [743,] 29.72 61 [744,] 29.76 69 [745,] 29.80 58 [746,] 29.84 70 [747,] 29.88 61 [748,] 29.92 70 [749,] 29.96 63 [750,] 30.00 60 [751,] 30.04 47 [752,] 30.08 67 [753,] 30.12 75 [754,] 30.16 73 [755,] 30.20 58 [756,] 30.24 65 [757,] 30.28 58 [758,] 30.32 51 [759,] 30.36 56 [760,] 30.40 64 [761,] 30.44 72 [762,] 30.48 77 [763,] 30.52 71 [764,] 30.56 76 [765,] 30.60 46 [766,] 30.64 87 [767,] 30.68 68 [768,] 30.72 69 [769,] 30.76 69 [770,] 30.80 78 [771,] 30.84 71 [772,] 30.88 83 [773,] 30.92 63 [774,] 30.96 70 [775,] 31.00 65 [776,] 31.04 66 [777,] 31.08 56 [778,] 31.12 74 [779,] 31.16 54 [780,] 31.20 71 [781,] 31.24 103 [782,] 31.28 69 [783,] 31.32 56 [784,] 31.36 62 [785,] 31.40 59 [786,] 31.44 73 [787,] 31.48 45 [788,] 31.52 96 [789,] 31.56 74 [790,] 31.60 77 [791,] 31.64 46 [792,] 31.68 49 [793,] 31.72 72 [794,] 31.76 86 [795,] 31.80 58 [796,] 31.84 70 [797,] 31.88 46 [798,] 31.92 63 [799,] 31.96 74 [800,] 32.00 71 [801,] 32.04 56 [802,] 32.08 64 [803,] 32.12 51 [804,] 32.16 76 [805,] 32.20 73 [806,] 32.24 66 [807,] 32.28 71 [808,] 32.32 69 [809,] 32.36 57 [810,] 32.40 52 [811,] 32.44 55 [812,] 32.48 56 [813,] 32.52 71 [814,] 32.56 81 [815,] 32.60 58 [816,] 32.64 76 [817,] 32.68 56 [818,] 32.72 61 [819,] 32.76 61 [820,] 32.80 50 [821,] 32.84 51 [822,] 32.88 47 [823,] 32.92 66 [824,] 32.96 71 [825,] 33.00 57 [826,] 33.04 62 [827,] 33.08 71 [828,] 33.12 61 [829,] 33.16 58 [830,] 33.20 45 [831,] 33.24 80 [832,] 33.28 64 [833,] 33.32 65 [834,] 33.36 76 [835,] 33.40 62 [836,] 33.44 53 [837,] 33.48 64 [838,] 33.52 72 [839,] 33.56 65 [840,] 33.60 73 [841,] 33.64 49 [842,] 33.68 79 [843,] 33.72 79 [844,] 33.76 94 [845,] 33.80 49 [846,] 33.84 70 [847,] 33.88 55 [848,] 33.92 58 [849,] 33.96 88 [850,] 34.00 74 [851,] 34.04 63 [852,] 34.08 64 [853,] 34.12 50 [854,] 34.16 62 [855,] 34.20 67 [856,] 34.24 87 [857,] 34.28 56 [858,] 34.32 63 [859,] 34.36 56 [860,] 34.40 55 [861,] 34.44 57 [862,] 34.48 69 [863,] 34.52 82 [864,] 34.56 46 [865,] 34.60 85 [866,] 34.64 54 [867,] 34.68 61 [868,] 34.72 55 [869,] 34.76 71 [870,] 34.80 62 [871,] 34.84 64 [872,] 34.88 68 [873,] 34.92 61 [874,] 34.96 50 [875,] 35.00 68 [876,] 35.04 62 [877,] 35.08 64 [878,] 35.12 53 [879,] 35.16 47 [880,] 35.20 61 [881,] 35.24 73 [882,] 35.28 60 [883,] 35.32 62 [884,] 35.36 65 [885,] 35.40 66 [886,] 35.44 58 [887,] 35.48 85 [888,] 35.52 75 [889,] 35.56 52 [890,] 35.60 70 [891,] 35.64 62 [892,] 35.68 64 [893,] 35.72 57 [894,] 35.76 56 [895,] 35.80 49 [896,] 35.84 71 [897,] 35.88 75 [898,] 35.92 63 [899,] 35.96 53 [900,] 36.00 57 [901,] 36.04 67 [902,] 36.08 73 [903,] 36.12 87 [904,] 36.16 65 [905,] 36.20 58 [906,] 36.24 49 [907,] 36.28 78 [908,] 36.32 60 [909,] 36.36 65 [910,] 36.40 70 [911,] 36.44 54 [912,] 36.48 47 [913,] 36.52 71 [914,] 36.56 51 [915,] 36.60 65 [916,] 36.64 58 [917,] 36.68 51 [918,] 36.72 81 [919,] 36.76 56 [920,] 36.80 68 [921,] 36.84 70 [922,] 36.88 58 [923,] 36.92 53 [924,] 36.96 88 [925,] 37.00 68 [926,] 37.04 61 [927,] 37.08 59 [928,] 37.12 58 [929,] 37.16 62 [930,] 37.20 66 [931,] 37.24 61 [932,] 37.28 69 [933,] 37.32 57 [934,] 37.36 62 [935,] 37.40 57 [936,] 37.44 45 [937,] 37.48 68 [938,] 37.52 80 [939,] 37.56 52 [940,] 37.60 49 [941,] 37.64 58 [942,] 37.68 51 [943,] 37.72 89 [944,] 37.76 67 [945,] 37.80 54 [946,] 37.84 58 [947,] 37.88 57 [948,] 37.92 72 [949,] 37.96 72 [950,] 38.00 64 [951,] 38.04 53 [952,] 38.08 61 [953,] 38.12 62 [954,] 38.16 56 [955,] 38.20 58 [956,] 38.24 82 [957,] 38.28 70 [958,] 38.32 68 [959,] 38.36 80 [960,] 38.40 72 [961,] 38.44 58 [962,] 38.48 95 [963,] 38.52 62 [964,] 38.56 59 [965,] 38.60 66 [966,] 38.64 64 [967,] 38.68 63 [968,] 38.72 63 [969,] 38.76 59 [970,] 38.80 78 [971,] 38.84 75 [972,] 38.88 52 [973,] 38.92 57 [974,] 38.96 72 [975,] 39.00 69 [976,] 39.04 62 [977,] 39.08 54 [978,] 39.12 62 [979,] 39.16 62 [980,] 39.20 53 [981,] 39.24 54 [982,] 39.28 68 [983,] 39.32 50 [984,] 39.36 45 [985,] 39.40 73 [986,] 39.44 65 [987,] 39.48 82 [988,] 39.52 72 [989,] 39.56 61 [990,] 39.60 55 [991,] 39.64 74 [992,] 39.68 72 [993,] 39.72 76 [994,] 39.76 74 [995,] 39.80 56 [996,] 39.84 49 [997,] 39.88 56 [998,] 39.92 55 [999,] 39.96 69 [1000,] 40.00 75 $`25_TL (PMT)` [,1] [,2] [1,] 0.884 1 [2,] 1.768 3 [3,] 2.652 3 [4,] 3.536 3 [5,] 4.420 1 [6,] 5.304 8 [7,] 6.188 11 [8,] 7.072 5 [9,] 7.956 9 [10,] 8.840 5 [11,] 9.724 6 [12,] 10.608 1 [13,] 11.492 3 [14,] 12.376 4 [15,] 13.260 4 [16,] 14.144 10 [17,] 15.028 8 [18,] 15.912 7 [19,] 16.796 3 [20,] 17.680 2 [21,] 18.564 3 [22,] 19.448 2 [23,] 20.332 12 [24,] 21.216 4 [25,] 22.100 2 [26,] 22.984 7 [27,] 23.868 1 [28,] 24.752 4 [29,] 25.636 11 [30,] 26.520 2 [31,] 27.404 1 [32,] 28.288 3 [33,] 29.172 4 [34,] 30.056 4 [35,] 30.940 3 [36,] 31.824 11 [37,] 32.708 9 [38,] 33.592 9 [39,] 34.476 15 [40,] 35.360 3 [41,] 36.244 1 [42,] 37.128 3 [43,] 38.012 6 [44,] 38.896 2 [45,] 39.780 4 [46,] 40.664 8 [47,] 41.548 1 [48,] 42.432 9 [49,] 43.316 3 [50,] 44.200 4 [51,] 45.084 6 [52,] 45.968 5 [53,] 46.852 2 [54,] 47.736 9 [55,] 48.620 9 [56,] 49.504 7 [57,] 50.388 3 [58,] 51.272 6 [59,] 52.156 2 [60,] 53.040 6 [61,] 53.924 2 [62,] 54.808 18 [63,] 55.692 10 [64,] 56.576 7 [65,] 57.460 3 [66,] 58.344 5 [67,] 59.228 9 [68,] 60.112 2 [69,] 60.996 1 [70,] 61.880 11 [71,] 62.764 2 [72,] 63.648 4 [73,] 64.532 7 [74,] 65.416 4 [75,] 66.300 7 [76,] 67.184 2 [77,] 68.068 1 [78,] 68.952 5 [79,] 69.836 3 [80,] 70.720 4 [81,] 71.604 8 [82,] 72.488 11 [83,] 73.372 7 [84,] 74.256 3 [85,] 75.140 0 [86,] 76.024 11 [87,] 76.908 5 [88,] 77.792 8 [89,] 78.676 4 [90,] 79.560 2 [91,] 80.444 13 [92,] 81.328 0 [93,] 82.212 2 [94,] 83.096 4 [95,] 83.980 6 [96,] 84.864 6 [97,] 85.748 16 [98,] 86.632 2 [99,] 87.516 2 [100,] 88.400 3 [101,] 89.284 9 [102,] 90.168 5 [103,] 91.052 2 [104,] 91.936 2 [105,] 92.820 5 [106,] 93.704 13 [107,] 94.588 9 [108,] 95.472 4 [109,] 96.356 9 [110,] 97.240 11 [111,] 98.124 1 [112,] 99.008 7 [113,] 99.892 14 [114,] 100.776 5 [115,] 101.660 5 [116,] 102.544 4 [117,] 103.428 4 [118,] 104.312 2 [119,] 105.196 3 [120,] 106.080 4 [121,] 106.964 6 [122,] 107.848 0 [123,] 108.732 3 [124,] 109.616 2 [125,] 110.500 2 [126,] 111.384 13 [127,] 112.268 4 [128,] 113.152 1 [129,] 114.036 9 [130,] 114.920 3 [131,] 115.804 11 [132,] 116.688 7 [133,] 117.572 5 [134,] 118.456 9 [135,] 119.340 6 [136,] 120.224 11 [137,] 121.108 5 [138,] 121.992 2 [139,] 122.876 12 [140,] 123.760 5 [141,] 124.644 6 [142,] 125.528 8 [143,] 126.412 4 [144,] 127.296 9 [145,] 128.180 13 [146,] 129.064 2 [147,] 129.948 6 [148,] 130.832 5 [149,] 131.716 3 [150,] 132.600 8 [151,] 133.484 6 [152,] 134.368 8 [153,] 135.252 6 [154,] 136.136 8 [155,] 137.020 12 [156,] 137.904 7 [157,] 138.788 7 [158,] 139.672 10 [159,] 140.556 11 [160,] 141.440 22 [161,] 142.324 6 [162,] 143.208 4 [163,] 144.092 19 [164,] 144.976 10 [165,] 145.860 8 [166,] 146.744 7 [167,] 147.628 13 [168,] 148.512 8 [169,] 149.396 8 [170,] 150.280 21 [171,] 151.164 20 [172,] 152.048 3 [173,] 152.932 11 [174,] 153.816 14 [175,] 154.700 16 [176,] 155.584 7 [177,] 156.468 24 [178,] 157.352 24 [179,] 158.236 24 [180,] 159.120 30 [181,] 160.004 20 [182,] 160.888 19 [183,] 161.772 25 [184,] 162.656 16 [185,] 163.540 16 [186,] 164.424 28 [187,] 165.308 35 [188,] 166.192 21 [189,] 167.076 19 [190,] 167.960 27 [191,] 168.844 19 [192,] 169.728 27 [193,] 170.612 27 [194,] 171.496 23 [195,] 172.380 33 [196,] 173.264 27 [197,] 174.148 38 [198,] 175.032 30 [199,] 175.916 34 [200,] 176.800 35 [201,] 177.684 24 [202,] 178.568 29 [203,] 179.452 55 [204,] 180.336 27 [205,] 181.220 30 [206,] 182.104 27 [207,] 182.988 31 [208,] 183.872 38 [209,] 184.756 29 [210,] 185.640 47 [211,] 186.524 53 [212,] 187.408 58 [213,] 188.292 43 [214,] 189.176 55 [215,] 190.060 41 [216,] 190.944 38 [217,] 191.828 73 [218,] 192.712 55 [219,] 193.596 52 [220,] 194.480 46 [221,] 195.364 47 [222,] 196.248 55 [223,] 197.132 54 [224,] 198.016 59 [225,] 198.900 57 [226,] 199.784 82 [227,] 200.668 79 [228,] 201.552 73 [229,] 202.436 72 [230,] 203.320 69 [231,] 204.204 86 [232,] 205.088 87 [233,] 205.972 78 [234,] 206.856 75 [235,] 207.740 108 [236,] 208.624 86 [237,] 209.508 91 [238,] 210.392 78 [239,] 211.276 127 [240,] 212.160 97 [241,] 213.044 124 [242,] 213.928 108 [243,] 214.812 98 [244,] 215.696 119 [245,] 216.580 103 [246,] 217.464 119 [247,] 218.348 125 [248,] 219.232 131 [249,] 220.116 108 [250,] 221.000 135 $`26_OSL (PMT)` [,1] [,2] [1,] 0.04 85 [2,] 0.08 107 [3,] 0.12 79 [4,] 0.16 74 [5,] 0.20 98 [6,] 0.24 90 [7,] 0.28 68 [8,] 0.32 93 [9,] 0.36 77 [10,] 0.40 69 [11,] 0.44 72 [12,] 0.48 60 [13,] 0.52 55 [14,] 0.56 64 [15,] 0.60 78 [16,] 0.64 71 [17,] 0.68 69 [18,] 0.72 70 [19,] 0.76 70 [20,] 0.80 54 [21,] 0.84 59 [22,] 0.88 60 [23,] 0.92 71 [24,] 0.96 58 [25,] 1.00 83 [26,] 1.04 72 [27,] 1.08 59 [28,] 1.12 53 [29,] 1.16 59 [30,] 1.20 61 [31,] 1.24 74 [32,] 1.28 57 [33,] 1.32 53 [34,] 1.36 66 [35,] 1.40 78 [36,] 1.44 65 [37,] 1.48 64 [38,] 1.52 65 [39,] 1.56 70 [40,] 1.60 51 [41,] 1.64 65 [42,] 1.68 59 [43,] 1.72 76 [44,] 1.76 52 [45,] 1.80 78 [46,] 1.84 50 [47,] 1.88 68 [48,] 1.92 59 [49,] 1.96 68 [50,] 2.00 83 [51,] 2.04 64 [52,] 2.08 44 [53,] 2.12 82 [54,] 2.16 57 [55,] 2.20 60 [56,] 2.24 65 [57,] 2.28 56 [58,] 2.32 69 [59,] 2.36 60 [60,] 2.40 78 [61,] 2.44 81 [62,] 2.48 71 [63,] 2.52 68 [64,] 2.56 50 [65,] 2.60 59 [66,] 2.64 59 [67,] 2.68 52 [68,] 2.72 53 [69,] 2.76 61 [70,] 2.80 63 [71,] 2.84 79 [72,] 2.88 58 [73,] 2.92 58 [74,] 2.96 70 [75,] 3.00 69 [76,] 3.04 77 [77,] 3.08 53 [78,] 3.12 63 [79,] 3.16 53 [80,] 3.20 72 [81,] 3.24 69 [82,] 3.28 42 [83,] 3.32 60 [84,] 3.36 62 [85,] 3.40 41 [86,] 3.44 58 [87,] 3.48 47 [88,] 3.52 61 [89,] 3.56 59 [90,] 3.60 71 [91,] 3.64 63 [92,] 3.68 65 [93,] 3.72 60 [94,] 3.76 73 [95,] 3.80 84 [96,] 3.84 49 [97,] 3.88 52 [98,] 3.92 56 [99,] 3.96 50 [100,] 4.00 46 [101,] 4.04 45 [102,] 4.08 69 [103,] 4.12 66 [104,] 4.16 73 [105,] 4.20 70 [106,] 4.24 55 [107,] 4.28 73 [108,] 4.32 60 [109,] 4.36 61 [110,] 4.40 60 [111,] 4.44 74 [112,] 4.48 63 [113,] 4.52 49 [114,] 4.56 47 [115,] 4.60 63 [116,] 4.64 50 [117,] 4.68 62 [118,] 4.72 48 [119,] 4.76 70 [120,] 4.80 49 [121,] 4.84 61 [122,] 4.88 64 [123,] 4.92 60 [124,] 4.96 52 [125,] 5.00 51 [126,] 5.04 59 [127,] 5.08 60 [128,] 5.12 69 [129,] 5.16 71 [130,] 5.20 67 [131,] 5.24 63 [132,] 5.28 59 [133,] 5.32 44 [134,] 5.36 48 [135,] 5.40 47 [136,] 5.44 71 [137,] 5.48 50 [138,] 5.52 75 [139,] 5.56 63 [140,] 5.60 51 [141,] 5.64 57 [142,] 5.68 48 [143,] 5.72 63 [144,] 5.76 60 [145,] 5.80 50 [146,] 5.84 74 [147,] 5.88 64 [148,] 5.92 47 [149,] 5.96 54 [150,] 6.00 57 [151,] 6.04 69 [152,] 6.08 48 [153,] 6.12 66 [154,] 6.16 77 [155,] 6.20 41 [156,] 6.24 47 [157,] 6.28 47 [158,] 6.32 51 [159,] 6.36 73 [160,] 6.40 71 [161,] 6.44 61 [162,] 6.48 64 [163,] 6.52 45 [164,] 6.56 44 [165,] 6.60 62 [166,] 6.64 51 [167,] 6.68 52 [168,] 6.72 66 [169,] 6.76 62 [170,] 6.80 43 [171,] 6.84 59 [172,] 6.88 57 [173,] 6.92 48 [174,] 6.96 50 [175,] 7.00 55 [176,] 7.04 52 [177,] 7.08 55 [178,] 7.12 61 [179,] 7.16 54 [180,] 7.20 70 [181,] 7.24 41 [182,] 7.28 54 [183,] 7.32 75 [184,] 7.36 65 [185,] 7.40 61 [186,] 7.44 49 [187,] 7.48 51 [188,] 7.52 59 [189,] 7.56 64 [190,] 7.60 71 [191,] 7.64 55 [192,] 7.68 46 [193,] 7.72 47 [194,] 7.76 54 [195,] 7.80 72 [196,] 7.84 36 [197,] 7.88 36 [198,] 7.92 48 [199,] 7.96 58 [200,] 8.00 51 [201,] 8.04 61 [202,] 8.08 43 [203,] 8.12 54 [204,] 8.16 53 [205,] 8.20 36 [206,] 8.24 57 [207,] 8.28 71 [208,] 8.32 57 [209,] 8.36 54 [210,] 8.40 42 [211,] 8.44 39 [212,] 8.48 50 [213,] 8.52 58 [214,] 8.56 46 [215,] 8.60 43 [216,] 8.64 70 [217,] 8.68 37 [218,] 8.72 63 [219,] 8.76 59 [220,] 8.80 59 [221,] 8.84 58 [222,] 8.88 62 [223,] 8.92 62 [224,] 8.96 63 [225,] 9.00 52 [226,] 9.04 65 [227,] 9.08 66 [228,] 9.12 62 [229,] 9.16 55 [230,] 9.20 48 [231,] 9.24 42 [232,] 9.28 55 [233,] 9.32 66 [234,] 9.36 64 [235,] 9.40 43 [236,] 9.44 50 [237,] 9.48 57 [238,] 9.52 63 [239,] 9.56 62 [240,] 9.60 44 [241,] 9.64 50 [242,] 9.68 61 [243,] 9.72 47 [244,] 9.76 52 [245,] 9.80 46 [246,] 9.84 49 [247,] 9.88 50 [248,] 9.92 66 [249,] 9.96 57 [250,] 10.00 50 [251,] 10.04 42 [252,] 10.08 67 [253,] 10.12 51 [254,] 10.16 46 [255,] 10.20 47 [256,] 10.24 48 [257,] 10.28 34 [258,] 10.32 45 [259,] 10.36 44 [260,] 10.40 60 [261,] 10.44 54 [262,] 10.48 53 [263,] 10.52 48 [264,] 10.56 47 [265,] 10.60 54 [266,] 10.64 56 [267,] 10.68 60 [268,] 10.72 56 [269,] 10.76 58 [270,] 10.80 71 [271,] 10.84 49 [272,] 10.88 52 [273,] 10.92 59 [274,] 10.96 48 [275,] 11.00 41 [276,] 11.04 43 [277,] 11.08 44 [278,] 11.12 54 [279,] 11.16 49 [280,] 11.20 51 [281,] 11.24 65 [282,] 11.28 62 [283,] 11.32 57 [284,] 11.36 53 [285,] 11.40 43 [286,] 11.44 69 [287,] 11.48 47 [288,] 11.52 53 [289,] 11.56 47 [290,] 11.60 59 [291,] 11.64 58 [292,] 11.68 37 [293,] 11.72 57 [294,] 11.76 57 [295,] 11.80 60 [296,] 11.84 56 [297,] 11.88 57 [298,] 11.92 58 [299,] 11.96 53 [300,] 12.00 68 [301,] 12.04 38 [302,] 12.08 44 [303,] 12.12 48 [304,] 12.16 53 [305,] 12.20 60 [306,] 12.24 64 [307,] 12.28 45 [308,] 12.32 54 [309,] 12.36 58 [310,] 12.40 48 [311,] 12.44 49 [312,] 12.48 61 [313,] 12.52 54 [314,] 12.56 54 [315,] 12.60 55 [316,] 12.64 57 [317,] 12.68 55 [318,] 12.72 69 [319,] 12.76 45 [320,] 12.80 56 [321,] 12.84 48 [322,] 12.88 61 [323,] 12.92 55 [324,] 12.96 58 [325,] 13.00 55 [326,] 13.04 56 [327,] 13.08 64 [328,] 13.12 47 [329,] 13.16 56 [330,] 13.20 57 [331,] 13.24 41 [332,] 13.28 57 [333,] 13.32 28 [334,] 13.36 47 [335,] 13.40 44 [336,] 13.44 55 [337,] 13.48 63 [338,] 13.52 54 [339,] 13.56 65 [340,] 13.60 57 [341,] 13.64 66 [342,] 13.68 57 [343,] 13.72 56 [344,] 13.76 51 [345,] 13.80 40 [346,] 13.84 71 [347,] 13.88 48 [348,] 13.92 53 [349,] 13.96 50 [350,] 14.00 56 [351,] 14.04 53 [352,] 14.08 44 [353,] 14.12 44 [354,] 14.16 59 [355,] 14.20 70 [356,] 14.24 46 [357,] 14.28 41 [358,] 14.32 46 [359,] 14.36 60 [360,] 14.40 57 [361,] 14.44 49 [362,] 14.48 55 [363,] 14.52 61 [364,] 14.56 58 [365,] 14.60 59 [366,] 14.64 43 [367,] 14.68 43 [368,] 14.72 42 [369,] 14.76 68 [370,] 14.80 48 [371,] 14.84 54 [372,] 14.88 62 [373,] 14.92 57 [374,] 14.96 41 [375,] 15.00 44 [376,] 15.04 55 [377,] 15.08 62 [378,] 15.12 57 [379,] 15.16 64 [380,] 15.20 39 [381,] 15.24 44 [382,] 15.28 53 [383,] 15.32 44 [384,] 15.36 55 [385,] 15.40 54 [386,] 15.44 51 [387,] 15.48 57 [388,] 15.52 56 [389,] 15.56 62 [390,] 15.60 50 [391,] 15.64 52 [392,] 15.68 57 [393,] 15.72 65 [394,] 15.76 54 [395,] 15.80 57 [396,] 15.84 49 [397,] 15.88 48 [398,] 15.92 55 [399,] 15.96 50 [400,] 16.00 49 [401,] 16.04 60 [402,] 16.08 51 [403,] 16.12 45 [404,] 16.16 63 [405,] 16.20 64 [406,] 16.24 51 [407,] 16.28 53 [408,] 16.32 41 [409,] 16.36 49 [410,] 16.40 42 [411,] 16.44 58 [412,] 16.48 48 [413,] 16.52 43 [414,] 16.56 51 [415,] 16.60 50 [416,] 16.64 50 [417,] 16.68 63 [418,] 16.72 50 [419,] 16.76 49 [420,] 16.80 39 [421,] 16.84 46 [422,] 16.88 59 [423,] 16.92 39 [424,] 16.96 42 [425,] 17.00 50 [426,] 17.04 50 [427,] 17.08 55 [428,] 17.12 49 [429,] 17.16 48 [430,] 17.20 45 [431,] 17.24 67 [432,] 17.28 62 [433,] 17.32 39 [434,] 17.36 36 [435,] 17.40 53 [436,] 17.44 37 [437,] 17.48 28 [438,] 17.52 46 [439,] 17.56 53 [440,] 17.60 48 [441,] 17.64 58 [442,] 17.68 57 [443,] 17.72 38 [444,] 17.76 44 [445,] 17.80 50 [446,] 17.84 46 [447,] 17.88 46 [448,] 17.92 48 [449,] 17.96 47 [450,] 18.00 50 [451,] 18.04 56 [452,] 18.08 46 [453,] 18.12 47 [454,] 18.16 42 [455,] 18.20 53 [456,] 18.24 55 [457,] 18.28 61 [458,] 18.32 48 [459,] 18.36 47 [460,] 18.40 40 [461,] 18.44 49 [462,] 18.48 68 [463,] 18.52 52 [464,] 18.56 57 [465,] 18.60 57 [466,] 18.64 63 [467,] 18.68 42 [468,] 18.72 58 [469,] 18.76 60 [470,] 18.80 58 [471,] 18.84 52 [472,] 18.88 52 [473,] 18.92 48 [474,] 18.96 46 [475,] 19.00 52 [476,] 19.04 48 [477,] 19.08 50 [478,] 19.12 45 [479,] 19.16 49 [480,] 19.20 61 [481,] 19.24 56 [482,] 19.28 58 [483,] 19.32 51 [484,] 19.36 59 [485,] 19.40 60 [486,] 19.44 49 [487,] 19.48 50 [488,] 19.52 56 [489,] 19.56 58 [490,] 19.60 73 [491,] 19.64 42 [492,] 19.68 52 [493,] 19.72 49 [494,] 19.76 45 [495,] 19.80 55 [496,] 19.84 52 [497,] 19.88 60 [498,] 19.92 55 [499,] 19.96 45 [500,] 20.00 47 [501,] 20.04 49 [502,] 20.08 53 [503,] 20.12 53 [504,] 20.16 52 [505,] 20.20 60 [506,] 20.24 51 [507,] 20.28 69 [508,] 20.32 45 [509,] 20.36 42 [510,] 20.40 61 [511,] 20.44 65 [512,] 20.48 51 [513,] 20.52 58 [514,] 20.56 55 [515,] 20.60 43 [516,] 20.64 55 [517,] 20.68 46 [518,] 20.72 46 [519,] 20.76 54 [520,] 20.80 46 [521,] 20.84 43 [522,] 20.88 44 [523,] 20.92 46 [524,] 20.96 56 [525,] 21.00 34 [526,] 21.04 48 [527,] 21.08 55 [528,] 21.12 42 [529,] 21.16 40 [530,] 21.20 56 [531,] 21.24 49 [532,] 21.28 40 [533,] 21.32 59 [534,] 21.36 49 [535,] 21.40 42 [536,] 21.44 44 [537,] 21.48 29 [538,] 21.52 42 [539,] 21.56 57 [540,] 21.60 50 [541,] 21.64 57 [542,] 21.68 49 [543,] 21.72 48 [544,] 21.76 48 [545,] 21.80 39 [546,] 21.84 59 [547,] 21.88 57 [548,] 21.92 57 [549,] 21.96 55 [550,] 22.00 57 [551,] 22.04 46 [552,] 22.08 48 [553,] 22.12 61 [554,] 22.16 59 [555,] 22.20 42 [556,] 22.24 60 [557,] 22.28 44 [558,] 22.32 59 [559,] 22.36 57 [560,] 22.40 40 [561,] 22.44 50 [562,] 22.48 39 [563,] 22.52 64 [564,] 22.56 49 [565,] 22.60 65 [566,] 22.64 55 [567,] 22.68 50 [568,] 22.72 43 [569,] 22.76 54 [570,] 22.80 71 [571,] 22.84 51 [572,] 22.88 56 [573,] 22.92 32 [574,] 22.96 35 [575,] 23.00 52 [576,] 23.04 56 [577,] 23.08 61 [578,] 23.12 35 [579,] 23.16 60 [580,] 23.20 45 [581,] 23.24 35 [582,] 23.28 52 [583,] 23.32 48 [584,] 23.36 46 [585,] 23.40 52 [586,] 23.44 70 [587,] 23.48 47 [588,] 23.52 69 [589,] 23.56 46 [590,] 23.60 61 [591,] 23.64 52 [592,] 23.68 46 [593,] 23.72 35 [594,] 23.76 47 [595,] 23.80 41 [596,] 23.84 63 [597,] 23.88 58 [598,] 23.92 46 [599,] 23.96 42 [600,] 24.00 44 [601,] 24.04 59 [602,] 24.08 56 [603,] 24.12 45 [604,] 24.16 41 [605,] 24.20 46 [606,] 24.24 49 [607,] 24.28 55 [608,] 24.32 53 [609,] 24.36 45 [610,] 24.40 55 [611,] 24.44 51 [612,] 24.48 57 [613,] 24.52 52 [614,] 24.56 56 [615,] 24.60 55 [616,] 24.64 56 [617,] 24.68 51 [618,] 24.72 65 [619,] 24.76 58 [620,] 24.80 58 [621,] 24.84 45 [622,] 24.88 51 [623,] 24.92 42 [624,] 24.96 56 [625,] 25.00 62 [626,] 25.04 69 [627,] 25.08 49 [628,] 25.12 65 [629,] 25.16 36 [630,] 25.20 59 [631,] 25.24 56 [632,] 25.28 45 [633,] 25.32 54 [634,] 25.36 49 [635,] 25.40 62 [636,] 25.44 52 [637,] 25.48 52 [638,] 25.52 48 [639,] 25.56 43 [640,] 25.60 47 [641,] 25.64 64 [642,] 25.68 43 [643,] 25.72 47 [644,] 25.76 62 [645,] 25.80 51 [646,] 25.84 54 [647,] 25.88 51 [648,] 25.92 48 [649,] 25.96 63 [650,] 26.00 49 [651,] 26.04 41 [652,] 26.08 51 [653,] 26.12 53 [654,] 26.16 47 [655,] 26.20 64 [656,] 26.24 51 [657,] 26.28 27 [658,] 26.32 35 [659,] 26.36 48 [660,] 26.40 59 [661,] 26.44 44 [662,] 26.48 65 [663,] 26.52 51 [664,] 26.56 41 [665,] 26.60 55 [666,] 26.64 46 [667,] 26.68 53 [668,] 26.72 49 [669,] 26.76 60 [670,] 26.80 52 [671,] 26.84 57 [672,] 26.88 32 [673,] 26.92 39 [674,] 26.96 44 [675,] 27.00 57 [676,] 27.04 44 [677,] 27.08 62 [678,] 27.12 42 [679,] 27.16 43 [680,] 27.20 43 [681,] 27.24 41 [682,] 27.28 54 [683,] 27.32 35 [684,] 27.36 65 [685,] 27.40 44 [686,] 27.44 41 [687,] 27.48 47 [688,] 27.52 48 [689,] 27.56 47 [690,] 27.60 48 [691,] 27.64 57 [692,] 27.68 57 [693,] 27.72 59 [694,] 27.76 63 [695,] 27.80 47 [696,] 27.84 55 [697,] 27.88 51 [698,] 27.92 45 [699,] 27.96 63 [700,] 28.00 46 [701,] 28.04 50 [702,] 28.08 45 [703,] 28.12 37 [704,] 28.16 55 [705,] 28.20 59 [706,] 28.24 46 [707,] 28.28 53 [708,] 28.32 43 [709,] 28.36 29 [710,] 28.40 49 [711,] 28.44 55 [712,] 28.48 46 [713,] 28.52 51 [714,] 28.56 49 [715,] 28.60 49 [716,] 28.64 40 [717,] 28.68 47 [718,] 28.72 36 [719,] 28.76 46 [720,] 28.80 54 [721,] 28.84 46 [722,] 28.88 70 [723,] 28.92 47 [724,] 28.96 49 [725,] 29.00 44 [726,] 29.04 36 [727,] 29.08 41 [728,] 29.12 52 [729,] 29.16 52 [730,] 29.20 51 [731,] 29.24 44 [732,] 29.28 45 [733,] 29.32 46 [734,] 29.36 45 [735,] 29.40 56 [736,] 29.44 46 [737,] 29.48 41 [738,] 29.52 50 [739,] 29.56 53 [740,] 29.60 48 [741,] 29.64 46 [742,] 29.68 52 [743,] 29.72 51 [744,] 29.76 50 [745,] 29.80 50 [746,] 29.84 45 [747,] 29.88 44 [748,] 29.92 56 [749,] 29.96 55 [750,] 30.00 36 [751,] 30.04 51 [752,] 30.08 41 [753,] 30.12 53 [754,] 30.16 56 [755,] 30.20 45 [756,] 30.24 64 [757,] 30.28 40 [758,] 30.32 46 [759,] 30.36 52 [760,] 30.40 55 [761,] 30.44 52 [762,] 30.48 34 [763,] 30.52 42 [764,] 30.56 57 [765,] 30.60 51 [766,] 30.64 49 [767,] 30.68 43 [768,] 30.72 57 [769,] 30.76 47 [770,] 30.80 54 [771,] 30.84 67 [772,] 30.88 48 [773,] 30.92 32 [774,] 30.96 61 [775,] 31.00 49 [776,] 31.04 43 [777,] 31.08 55 [778,] 31.12 38 [779,] 31.16 47 [780,] 31.20 42 [781,] 31.24 52 [782,] 31.28 69 [783,] 31.32 57 [784,] 31.36 48 [785,] 31.40 44 [786,] 31.44 60 [787,] 31.48 45 [788,] 31.52 48 [789,] 31.56 58 [790,] 31.60 45 [791,] 31.64 60 [792,] 31.68 43 [793,] 31.72 38 [794,] 31.76 61 [795,] 31.80 35 [796,] 31.84 67 [797,] 31.88 67 [798,] 31.92 51 [799,] 31.96 55 [800,] 32.00 45 [801,] 32.04 44 [802,] 32.08 43 [803,] 32.12 49 [804,] 32.16 55 [805,] 32.20 43 [806,] 32.24 49 [807,] 32.28 48 [808,] 32.32 42 [809,] 32.36 47 [810,] 32.40 42 [811,] 32.44 47 [812,] 32.48 48 [813,] 32.52 44 [814,] 32.56 42 [815,] 32.60 40 [816,] 32.64 55 [817,] 32.68 69 [818,] 32.72 40 [819,] 32.76 45 [820,] 32.80 38 [821,] 32.84 31 [822,] 32.88 48 [823,] 32.92 53 [824,] 32.96 44 [825,] 33.00 56 [826,] 33.04 44 [827,] 33.08 46 [828,] 33.12 48 [829,] 33.16 43 [830,] 33.20 43 [831,] 33.24 67 [832,] 33.28 44 [833,] 33.32 61 [834,] 33.36 39 [835,] 33.40 59 [836,] 33.44 27 [837,] 33.48 49 [838,] 33.52 51 [839,] 33.56 42 [840,] 33.60 48 [841,] 33.64 36 [842,] 33.68 44 [843,] 33.72 38 [844,] 33.76 39 [845,] 33.80 52 [846,] 33.84 48 [847,] 33.88 53 [848,] 33.92 53 [849,] 33.96 40 [850,] 34.00 41 [851,] 34.04 51 [852,] 34.08 46 [853,] 34.12 45 [854,] 34.16 59 [855,] 34.20 36 [856,] 34.24 49 [857,] 34.28 48 [858,] 34.32 42 [859,] 34.36 45 [860,] 34.40 52 [861,] 34.44 41 [862,] 34.48 36 [863,] 34.52 39 [864,] 34.56 34 [865,] 34.60 49 [866,] 34.64 57 [867,] 34.68 50 [868,] 34.72 51 [869,] 34.76 36 [870,] 34.80 43 [871,] 34.84 31 [872,] 34.88 34 [873,] 34.92 51 [874,] 34.96 47 [875,] 35.00 69 [876,] 35.04 48 [877,] 35.08 41 [878,] 35.12 59 [879,] 35.16 55 [880,] 35.20 39 [881,] 35.24 54 [882,] 35.28 38 [883,] 35.32 58 [884,] 35.36 44 [885,] 35.40 52 [886,] 35.44 47 [887,] 35.48 47 [888,] 35.52 54 [889,] 35.56 40 [890,] 35.60 42 [891,] 35.64 40 [892,] 35.68 47 [893,] 35.72 55 [894,] 35.76 63 [895,] 35.80 30 [896,] 35.84 44 [897,] 35.88 42 [898,] 35.92 45 [899,] 35.96 54 [900,] 36.00 39 [901,] 36.04 47 [902,] 36.08 41 [903,] 36.12 58 [904,] 36.16 53 [905,] 36.20 56 [906,] 36.24 62 [907,] 36.28 37 [908,] 36.32 53 [909,] 36.36 52 [910,] 36.40 57 [911,] 36.44 49 [912,] 36.48 40 [913,] 36.52 45 [914,] 36.56 43 [915,] 36.60 57 [916,] 36.64 44 [917,] 36.68 46 [918,] 36.72 43 [919,] 36.76 59 [920,] 36.80 45 [921,] 36.84 52 [922,] 36.88 55 [923,] 36.92 44 [924,] 36.96 46 [925,] 37.00 47 [926,] 37.04 50 [927,] 37.08 55 [928,] 37.12 41 [929,] 37.16 32 [930,] 37.20 43 [931,] 37.24 42 [932,] 37.28 41 [933,] 37.32 54 [934,] 37.36 54 [935,] 37.40 51 [936,] 37.44 58 [937,] 37.48 48 [938,] 37.52 48 [939,] 37.56 37 [940,] 37.60 47 [941,] 37.64 55 [942,] 37.68 39 [943,] 37.72 57 [944,] 37.76 48 [945,] 37.80 42 [946,] 37.84 51 [947,] 37.88 35 [948,] 37.92 42 [949,] 37.96 37 [950,] 38.00 45 [951,] 38.04 41 [952,] 38.08 39 [953,] 38.12 44 [954,] 38.16 37 [955,] 38.20 47 [956,] 38.24 50 [957,] 38.28 54 [958,] 38.32 47 [959,] 38.36 35 [960,] 38.40 43 [961,] 38.44 60 [962,] 38.48 43 [963,] 38.52 35 [964,] 38.56 47 [965,] 38.60 59 [966,] 38.64 43 [967,] 38.68 54 [968,] 38.72 45 [969,] 38.76 62 [970,] 38.80 38 [971,] 38.84 54 [972,] 38.88 61 [973,] 38.92 49 [974,] 38.96 50 [975,] 39.00 50 [976,] 39.04 41 [977,] 39.08 41 [978,] 39.12 36 [979,] 39.16 42 [980,] 39.20 59 [981,] 39.24 51 [982,] 39.28 49 [983,] 39.32 48 [984,] 39.36 39 [985,] 39.40 47 [986,] 39.44 54 [987,] 39.48 42 [988,] 39.52 40 [989,] 39.56 43 [990,] 39.60 47 [991,] 39.64 52 [992,] 39.68 33 [993,] 39.72 54 [994,] 39.76 34 [995,] 39.80 54 [996,] 39.84 50 [997,] 39.88 54 [998,] 39.92 54 [999,] 39.96 46 [1000,] 40.00 48 $`27_TL (PMT)` [,1] [,2] [1,] 0.64 0 [2,] 1.28 5 [3,] 1.92 1 [4,] 2.56 2 [5,] 3.20 4 [6,] 3.84 2 [7,] 4.48 4 [8,] 5.12 3 [9,] 5.76 3 [10,] 6.40 4 [11,] 7.04 14 [12,] 7.68 5 [13,] 8.32 7 [14,] 8.96 10 [15,] 9.60 5 [16,] 10.24 5 [17,] 10.88 11 [18,] 11.52 1 [19,] 12.16 0 [20,] 12.80 6 [21,] 13.44 6 [22,] 14.08 7 [23,] 14.72 3 [24,] 15.36 4 [25,] 16.00 2 [26,] 16.64 2 [27,] 17.28 9 [28,] 17.92 5 [29,] 18.56 3 [30,] 19.20 0 [31,] 19.84 7 [32,] 20.48 5 [33,] 21.12 5 [34,] 21.76 0 [35,] 22.40 4 [36,] 23.04 7 [37,] 23.68 3 [38,] 24.32 6 [39,] 24.96 3 [40,] 25.60 9 [41,] 26.24 3 [42,] 26.88 2 [43,] 27.52 4 [44,] 28.16 4 [45,] 28.80 1 [46,] 29.44 2 [47,] 30.08 29 [48,] 30.72 5 [49,] 31.36 5 [50,] 32.00 1 [51,] 32.64 5 [52,] 33.28 5 [53,] 33.92 3 [54,] 34.56 3 [55,] 35.20 3 [56,] 35.84 0 [57,] 36.48 3 [58,] 37.12 2 [59,] 37.76 2 [60,] 38.40 3 [61,] 39.04 6 [62,] 39.68 0 [63,] 40.32 11 [64,] 40.96 8 [65,] 41.60 9 [66,] 42.24 1 [67,] 42.88 1 [68,] 43.52 7 [69,] 44.16 14 [70,] 44.80 9 [71,] 45.44 3 [72,] 46.08 0 [73,] 46.72 3 [74,] 47.36 2 [75,] 48.00 1 [76,] 48.64 4 [77,] 49.28 8 [78,] 49.92 3 [79,] 50.56 12 [80,] 51.20 9 [81,] 51.84 5 [82,] 52.48 4 [83,] 53.12 9 [84,] 53.76 4 [85,] 54.40 6 [86,] 55.04 8 [87,] 55.68 8 [88,] 56.32 14 [89,] 56.96 8 [90,] 57.60 6 [91,] 58.24 3 [92,] 58.88 11 [93,] 59.52 12 [94,] 60.16 9 [95,] 60.80 9 [96,] 61.44 16 [97,] 62.08 23 [98,] 62.72 13 [99,] 63.36 16 [100,] 64.00 19 [101,] 64.64 22 [102,] 65.28 20 [103,] 65.92 17 [104,] 66.56 19 [105,] 67.20 32 [106,] 67.84 25 [107,] 68.48 23 [108,] 69.12 23 [109,] 69.76 21 [110,] 70.40 29 [111,] 71.04 31 [112,] 71.68 46 [113,] 72.32 50 [114,] 72.96 23 [115,] 73.60 35 [116,] 74.24 31 [117,] 74.88 52 [118,] 75.52 37 [119,] 76.16 38 [120,] 76.80 54 [121,] 77.44 41 [122,] 78.08 57 [123,] 78.72 56 [124,] 79.36 67 [125,] 80.00 75 [126,] 80.64 57 [127,] 81.28 80 [128,] 81.92 94 [129,] 82.56 76 [130,] 83.20 68 [131,] 83.84 110 [132,] 84.48 86 [133,] 85.12 95 [134,] 85.76 105 [135,] 86.40 121 [136,] 87.04 114 [137,] 87.68 130 [138,] 88.32 129 [139,] 88.96 141 [140,] 89.60 136 [141,] 90.24 148 [142,] 90.88 141 [143,] 91.52 155 [144,] 92.16 153 [145,] 92.80 154 [146,] 93.44 145 [147,] 94.08 176 [148,] 94.72 181 [149,] 95.36 198 [150,] 96.00 199 [151,] 96.64 204 [152,] 97.28 217 [153,] 97.92 203 [154,] 98.56 245 [155,] 99.20 190 [156,] 99.84 240 [157,] 100.48 215 [158,] 101.12 251 [159,] 101.76 233 [160,] 102.40 246 [161,] 103.04 263 [162,] 103.68 257 [163,] 104.32 266 [164,] 104.96 300 [165,] 105.60 268 [166,] 106.24 245 [167,] 106.88 264 [168,] 107.52 242 [169,] 108.16 264 [170,] 108.80 238 [171,] 109.44 269 [172,] 110.08 256 [173,] 110.72 232 [174,] 111.36 219 [175,] 112.00 235 [176,] 112.64 218 [177,] 113.28 201 [178,] 113.92 205 [179,] 114.56 178 [180,] 115.20 185 [181,] 115.84 172 [182,] 116.48 201 [183,] 117.12 147 [184,] 117.76 173 [185,] 118.40 158 [186,] 119.04 172 [187,] 119.68 155 [188,] 120.32 117 [189,] 120.96 141 [190,] 121.60 79 [191,] 122.24 111 [192,] 122.88 104 [193,] 123.52 94 [194,] 124.16 105 [195,] 124.80 89 [196,] 125.44 76 [197,] 126.08 87 [198,] 126.72 86 [199,] 127.36 87 [200,] 128.00 82 [201,] 128.64 92 [202,] 129.28 74 [203,] 129.92 88 [204,] 130.56 111 [205,] 131.20 71 [206,] 131.84 98 [207,] 132.48 71 [208,] 133.12 80 [209,] 133.76 80 [210,] 134.40 92 [211,] 135.04 78 [212,] 135.68 101 [213,] 136.32 93 [214,] 136.96 93 [215,] 137.60 76 [216,] 138.24 75 [217,] 138.88 84 [218,] 139.52 82 [219,] 140.16 94 [220,] 140.80 92 [221,] 141.44 93 [222,] 142.08 89 [223,] 142.72 95 [224,] 143.36 101 [225,] 144.00 87 [226,] 144.64 80 [227,] 145.28 114 [228,] 145.92 96 [229,] 146.56 78 [230,] 147.20 91 [231,] 147.84 120 [232,] 148.48 95 [233,] 149.12 81 [234,] 149.76 82 [235,] 150.40 75 [236,] 151.04 69 [237,] 151.68 82 [238,] 152.32 92 [239,] 152.96 89 [240,] 153.60 102 [241,] 154.24 75 [242,] 154.88 90 [243,] 155.52 64 [244,] 156.16 80 [245,] 156.80 74 [246,] 157.44 70 [247,] 158.08 84 [248,] 158.72 96 [249,] 159.36 91 [250,] 160.00 68 $`28_OSL (PMT)` [,1] [,2] [1,] 0.04 3334 [2,] 0.08 2773 [3,] 0.12 2460 [4,] 0.16 2209 [5,] 0.20 1924 [6,] 0.24 1594 [7,] 0.28 1450 [8,] 0.32 1260 [9,] 0.36 1116 [10,] 0.40 1029 [11,] 0.44 962 [12,] 0.48 759 [13,] 0.52 717 [14,] 0.56 666 [15,] 0.60 592 [16,] 0.64 488 [17,] 0.68 485 [18,] 0.72 431 [19,] 0.76 423 [20,] 0.80 384 [21,] 0.84 380 [22,] 0.88 345 [23,] 0.92 300 [24,] 0.96 282 [25,] 1.00 236 [26,] 1.04 229 [27,] 1.08 248 [28,] 1.12 211 [29,] 1.16 203 [30,] 1.20 215 [31,] 1.24 212 [32,] 1.28 189 [33,] 1.32 185 [34,] 1.36 199 [35,] 1.40 170 [36,] 1.44 171 [37,] 1.48 137 [38,] 1.52 154 [39,] 1.56 189 [40,] 1.60 150 [41,] 1.64 150 [42,] 1.68 166 [43,] 1.72 145 [44,] 1.76 129 [45,] 1.80 153 [46,] 1.84 116 [47,] 1.88 134 [48,] 1.92 151 [49,] 1.96 149 [50,] 2.00 121 [51,] 2.04 136 [52,] 2.08 119 [53,] 2.12 128 [54,] 2.16 139 [55,] 2.20 112 [56,] 2.24 125 [57,] 2.28 125 [58,] 2.32 140 [59,] 2.36 112 [60,] 2.40 107 [61,] 2.44 120 [62,] 2.48 96 [63,] 2.52 112 [64,] 2.56 104 [65,] 2.60 137 [66,] 2.64 98 [67,] 2.68 107 [68,] 2.72 109 [69,] 2.76 101 [70,] 2.80 99 [71,] 2.84 101 [72,] 2.88 108 [73,] 2.92 111 [74,] 2.96 117 [75,] 3.00 117 [76,] 3.04 98 [77,] 3.08 107 [78,] 3.12 98 [79,] 3.16 105 [80,] 3.20 108 [81,] 3.24 90 [82,] 3.28 111 [83,] 3.32 94 [84,] 3.36 105 [85,] 3.40 103 [86,] 3.44 118 [87,] 3.48 83 [88,] 3.52 96 [89,] 3.56 128 [90,] 3.60 104 [91,] 3.64 97 [92,] 3.68 91 [93,] 3.72 84 [94,] 3.76 103 [95,] 3.80 81 [96,] 3.84 93 [97,] 3.88 88 [98,] 3.92 105 [99,] 3.96 71 [100,] 4.00 98 [101,] 4.04 109 [102,] 4.08 74 [103,] 4.12 119 [104,] 4.16 106 [105,] 4.20 117 [106,] 4.24 101 [107,] 4.28 87 [108,] 4.32 90 [109,] 4.36 84 [110,] 4.40 83 [111,] 4.44 86 [112,] 4.48 98 [113,] 4.52 99 [114,] 4.56 90 [115,] 4.60 81 [116,] 4.64 92 [117,] 4.68 91 [118,] 4.72 81 [119,] 4.76 77 [120,] 4.80 108 [121,] 4.84 86 [122,] 4.88 93 [123,] 4.92 96 [124,] 4.96 99 [125,] 5.00 106 [126,] 5.04 83 [127,] 5.08 91 [128,] 5.12 81 [129,] 5.16 95 [130,] 5.20 98 [131,] 5.24 70 [132,] 5.28 104 [133,] 5.32 78 [134,] 5.36 85 [135,] 5.40 83 [136,] 5.44 75 [137,] 5.48 82 [138,] 5.52 57 [139,] 5.56 83 [140,] 5.60 82 [141,] 5.64 82 [142,] 5.68 70 [143,] 5.72 81 [144,] 5.76 88 [145,] 5.80 90 [146,] 5.84 98 [147,] 5.88 85 [148,] 5.92 80 [149,] 5.96 94 [150,] 6.00 94 [151,] 6.04 86 [152,] 6.08 72 [153,] 6.12 90 [154,] 6.16 87 [155,] 6.20 81 [156,] 6.24 85 [157,] 6.28 76 [158,] 6.32 66 [159,] 6.36 80 [160,] 6.40 77 [161,] 6.44 84 [162,] 6.48 100 [163,] 6.52 85 [164,] 6.56 81 [165,] 6.60 79 [166,] 6.64 81 [167,] 6.68 79 [168,] 6.72 85 [169,] 6.76 72 [170,] 6.80 82 [171,] 6.84 78 [172,] 6.88 69 [173,] 6.92 73 [174,] 6.96 62 [175,] 7.00 79 [176,] 7.04 62 [177,] 7.08 97 [178,] 7.12 89 [179,] 7.16 97 [180,] 7.20 71 [181,] 7.24 73 [182,] 7.28 92 [183,] 7.32 89 [184,] 7.36 78 [185,] 7.40 65 [186,] 7.44 93 [187,] 7.48 96 [188,] 7.52 75 [189,] 7.56 83 [190,] 7.60 83 [191,] 7.64 107 [192,] 7.68 98 [193,] 7.72 67 [194,] 7.76 63 [195,] 7.80 84 [196,] 7.84 78 [197,] 7.88 93 [198,] 7.92 70 [199,] 7.96 84 [200,] 8.00 64 [201,] 8.04 80 [202,] 8.08 97 [203,] 8.12 92 [204,] 8.16 84 [205,] 8.20 72 [206,] 8.24 82 [207,] 8.28 63 [208,] 8.32 76 [209,] 8.36 99 [210,] 8.40 74 [211,] 8.44 107 [212,] 8.48 75 [213,] 8.52 90 [214,] 8.56 70 [215,] 8.60 71 [216,] 8.64 71 [217,] 8.68 75 [218,] 8.72 76 [219,] 8.76 87 [220,] 8.80 71 [221,] 8.84 76 [222,] 8.88 68 [223,] 8.92 90 [224,] 8.96 85 [225,] 9.00 88 [226,] 9.04 83 [227,] 9.08 78 [228,] 9.12 76 [229,] 9.16 80 [230,] 9.20 60 [231,] 9.24 85 [232,] 9.28 65 [233,] 9.32 76 [234,] 9.36 56 [235,] 9.40 68 [236,] 9.44 92 [237,] 9.48 80 [238,] 9.52 77 [239,] 9.56 81 [240,] 9.60 62 [241,] 9.64 68 [242,] 9.68 57 [243,] 9.72 77 [244,] 9.76 86 [245,] 9.80 77 [246,] 9.84 61 [247,] 9.88 68 [248,] 9.92 88 [249,] 9.96 62 [250,] 10.00 73 [251,] 10.04 78 [252,] 10.08 71 [253,] 10.12 89 [254,] 10.16 81 [255,] 10.20 68 [256,] 10.24 68 [257,] 10.28 71 [258,] 10.32 61 [259,] 10.36 66 [260,] 10.40 77 [261,] 10.44 65 [262,] 10.48 75 [263,] 10.52 80 [264,] 10.56 67 [265,] 10.60 68 [266,] 10.64 61 [267,] 10.68 66 [268,] 10.72 77 [269,] 10.76 66 [270,] 10.80 69 [271,] 10.84 86 [272,] 10.88 78 [273,] 10.92 62 [274,] 10.96 52 [275,] 11.00 60 [276,] 11.04 63 [277,] 11.08 76 [278,] 11.12 67 [279,] 11.16 85 [280,] 11.20 64 [281,] 11.24 69 [282,] 11.28 67 [283,] 11.32 71 [284,] 11.36 61 [285,] 11.40 60 [286,] 11.44 78 [287,] 11.48 59 [288,] 11.52 72 [289,] 11.56 72 [290,] 11.60 82 [291,] 11.64 78 [292,] 11.68 78 [293,] 11.72 84 [294,] 11.76 78 [295,] 11.80 61 [296,] 11.84 59 [297,] 11.88 53 [298,] 11.92 71 [299,] 11.96 64 [300,] 12.00 69 [301,] 12.04 65 [302,] 12.08 72 [303,] 12.12 81 [304,] 12.16 64 [305,] 12.20 67 [306,] 12.24 77 [307,] 12.28 71 [308,] 12.32 61 [309,] 12.36 53 [310,] 12.40 85 [311,] 12.44 78 [312,] 12.48 66 [313,] 12.52 60 [314,] 12.56 56 [315,] 12.60 59 [316,] 12.64 74 [317,] 12.68 75 [318,] 12.72 82 [319,] 12.76 79 [320,] 12.80 76 [321,] 12.84 82 [322,] 12.88 53 [323,] 12.92 71 [324,] 12.96 68 [325,] 13.00 74 [326,] 13.04 56 [327,] 13.08 74 [328,] 13.12 77 [329,] 13.16 66 [330,] 13.20 51 [331,] 13.24 61 [332,] 13.28 83 [333,] 13.32 79 [334,] 13.36 72 [335,] 13.40 57 [336,] 13.44 58 [337,] 13.48 60 [338,] 13.52 74 [339,] 13.56 89 [340,] 13.60 57 [341,] 13.64 99 [342,] 13.68 76 [343,] 13.72 64 [344,] 13.76 63 [345,] 13.80 67 [346,] 13.84 64 [347,] 13.88 60 [348,] 13.92 68 [349,] 13.96 81 [350,] 14.00 75 [351,] 14.04 74 [352,] 14.08 53 [353,] 14.12 63 [354,] 14.16 70 [355,] 14.20 71 [356,] 14.24 72 [357,] 14.28 73 [358,] 14.32 63 [359,] 14.36 70 [360,] 14.40 72 [361,] 14.44 78 [362,] 14.48 65 [363,] 14.52 72 [364,] 14.56 74 [365,] 14.60 83 [366,] 14.64 65 [367,] 14.68 66 [368,] 14.72 59 [369,] 14.76 77 [370,] 14.80 50 [371,] 14.84 57 [372,] 14.88 81 [373,] 14.92 61 [374,] 14.96 63 [375,] 15.00 75 [376,] 15.04 76 [377,] 15.08 57 [378,] 15.12 73 [379,] 15.16 70 [380,] 15.20 54 [381,] 15.24 85 [382,] 15.28 74 [383,] 15.32 63 [384,] 15.36 74 [385,] 15.40 85 [386,] 15.44 93 [387,] 15.48 60 [388,] 15.52 62 [389,] 15.56 61 [390,] 15.60 74 [391,] 15.64 64 [392,] 15.68 72 [393,] 15.72 62 [394,] 15.76 53 [395,] 15.80 74 [396,] 15.84 84 [397,] 15.88 58 [398,] 15.92 58 [399,] 15.96 75 [400,] 16.00 66 [401,] 16.04 70 [402,] 16.08 60 [403,] 16.12 68 [404,] 16.16 69 [405,] 16.20 80 [406,] 16.24 56 [407,] 16.28 72 [408,] 16.32 52 [409,] 16.36 65 [410,] 16.40 63 [411,] 16.44 56 [412,] 16.48 65 [413,] 16.52 88 [414,] 16.56 73 [415,] 16.60 83 [416,] 16.64 79 [417,] 16.68 77 [418,] 16.72 76 [419,] 16.76 69 [420,] 16.80 62 [421,] 16.84 62 [422,] 16.88 78 [423,] 16.92 56 [424,] 16.96 58 [425,] 17.00 74 [426,] 17.04 77 [427,] 17.08 73 [428,] 17.12 60 [429,] 17.16 68 [430,] 17.20 63 [431,] 17.24 77 [432,] 17.28 68 [433,] 17.32 86 [434,] 17.36 55 [435,] 17.40 69 [436,] 17.44 70 [437,] 17.48 55 [438,] 17.52 58 [439,] 17.56 55 [440,] 17.60 58 [441,] 17.64 80 [442,] 17.68 82 [443,] 17.72 59 [444,] 17.76 53 [445,] 17.80 56 [446,] 17.84 74 [447,] 17.88 48 [448,] 17.92 52 [449,] 17.96 85 [450,] 18.00 51 [451,] 18.04 76 [452,] 18.08 66 [453,] 18.12 63 [454,] 18.16 63 [455,] 18.20 64 [456,] 18.24 73 [457,] 18.28 66 [458,] 18.32 59 [459,] 18.36 51 [460,] 18.40 60 [461,] 18.44 55 [462,] 18.48 62 [463,] 18.52 53 [464,] 18.56 62 [465,] 18.60 51 [466,] 18.64 69 [467,] 18.68 72 [468,] 18.72 47 [469,] 18.76 62 [470,] 18.80 51 [471,] 18.84 54 [472,] 18.88 86 [473,] 18.92 59 [474,] 18.96 64 [475,] 19.00 70 [476,] 19.04 75 [477,] 19.08 69 [478,] 19.12 81 [479,] 19.16 62 [480,] 19.20 70 [481,] 19.24 69 [482,] 19.28 52 [483,] 19.32 87 [484,] 19.36 52 [485,] 19.40 74 [486,] 19.44 74 [487,] 19.48 54 [488,] 19.52 53 [489,] 19.56 72 [490,] 19.60 48 [491,] 19.64 60 [492,] 19.68 62 [493,] 19.72 76 [494,] 19.76 67 [495,] 19.80 43 [496,] 19.84 66 [497,] 19.88 61 [498,] 19.92 62 [499,] 19.96 45 [500,] 20.00 58 [501,] 20.04 66 [502,] 20.08 55 [503,] 20.12 56 [504,] 20.16 75 [505,] 20.20 59 [506,] 20.24 59 [507,] 20.28 62 [508,] 20.32 49 [509,] 20.36 57 [510,] 20.40 63 [511,] 20.44 85 [512,] 20.48 51 [513,] 20.52 45 [514,] 20.56 57 [515,] 20.60 55 [516,] 20.64 59 [517,] 20.68 64 [518,] 20.72 58 [519,] 20.76 68 [520,] 20.80 66 [521,] 20.84 62 [522,] 20.88 62 [523,] 20.92 71 [524,] 20.96 54 [525,] 21.00 71 [526,] 21.04 56 [527,] 21.08 70 [528,] 21.12 53 [529,] 21.16 67 [530,] 21.20 65 [531,] 21.24 66 [532,] 21.28 49 [533,] 21.32 63 [534,] 21.36 57 [535,] 21.40 44 [536,] 21.44 71 [537,] 21.48 60 [538,] 21.52 87 [539,] 21.56 65 [540,] 21.60 57 [541,] 21.64 53 [542,] 21.68 64 [543,] 21.72 57 [544,] 21.76 72 [545,] 21.80 48 [546,] 21.84 55 [547,] 21.88 70 [548,] 21.92 59 [549,] 21.96 51 [550,] 22.00 75 [551,] 22.04 68 [552,] 22.08 59 [553,] 22.12 52 [554,] 22.16 82 [555,] 22.20 57 [556,] 22.24 77 [557,] 22.28 62 [558,] 22.32 70 [559,] 22.36 56 [560,] 22.40 106 [561,] 22.44 65 [562,] 22.48 42 [563,] 22.52 59 [564,] 22.56 64 [565,] 22.60 46 [566,] 22.64 58 [567,] 22.68 84 [568,] 22.72 57 [569,] 22.76 72 [570,] 22.80 62 [571,] 22.84 69 [572,] 22.88 67 [573,] 22.92 58 [574,] 22.96 67 [575,] 23.00 48 [576,] 23.04 64 [577,] 23.08 50 [578,] 23.12 63 [579,] 23.16 66 [580,] 23.20 55 [581,] 23.24 66 [582,] 23.28 64 [583,] 23.32 69 [584,] 23.36 52 [585,] 23.40 90 [586,] 23.44 52 [587,] 23.48 65 [588,] 23.52 62 [589,] 23.56 56 [590,] 23.60 60 [591,] 23.64 51 [592,] 23.68 61 [593,] 23.72 63 [594,] 23.76 52 [595,] 23.80 59 [596,] 23.84 59 [597,] 23.88 70 [598,] 23.92 68 [599,] 23.96 64 [600,] 24.00 60 [601,] 24.04 60 [602,] 24.08 66 [603,] 24.12 65 [604,] 24.16 53 [605,] 24.20 67 [606,] 24.24 48 [607,] 24.28 49 [608,] 24.32 51 [609,] 24.36 60 [610,] 24.40 46 [611,] 24.44 56 [612,] 24.48 63 [613,] 24.52 59 [614,] 24.56 57 [615,] 24.60 47 [616,] 24.64 49 [617,] 24.68 46 [618,] 24.72 58 [619,] 24.76 66 [620,] 24.80 80 [621,] 24.84 52 [622,] 24.88 60 [623,] 24.92 66 [624,] 24.96 62 [625,] 25.00 51 [626,] 25.04 81 [627,] 25.08 58 [628,] 25.12 64 [629,] 25.16 70 [630,] 25.20 67 [631,] 25.24 74 [632,] 25.28 53 [633,] 25.32 58 [634,] 25.36 70 [635,] 25.40 48 [636,] 25.44 64 [637,] 25.48 55 [638,] 25.52 66 [639,] 25.56 63 [640,] 25.60 47 [641,] 25.64 52 [642,] 25.68 78 [643,] 25.72 67 [644,] 25.76 68 [645,] 25.80 61 [646,] 25.84 70 [647,] 25.88 62 [648,] 25.92 53 [649,] 25.96 60 [650,] 26.00 46 [651,] 26.04 71 [652,] 26.08 49 [653,] 26.12 79 [654,] 26.16 66 [655,] 26.20 56 [656,] 26.24 76 [657,] 26.28 56 [658,] 26.32 60 [659,] 26.36 53 [660,] 26.40 70 [661,] 26.44 53 [662,] 26.48 62 [663,] 26.52 48 [664,] 26.56 46 [665,] 26.60 61 [666,] 26.64 57 [667,] 26.68 53 [668,] 26.72 59 [669,] 26.76 58 [670,] 26.80 66 [671,] 26.84 48 [672,] 26.88 69 [673,] 26.92 59 [674,] 26.96 58 [675,] 27.00 73 [676,] 27.04 64 [677,] 27.08 56 [678,] 27.12 43 [679,] 27.16 51 [680,] 27.20 58 [681,] 27.24 43 [682,] 27.28 70 [683,] 27.32 56 [684,] 27.36 66 [685,] 27.40 63 [686,] 27.44 59 [687,] 27.48 62 [688,] 27.52 76 [689,] 27.56 70 [690,] 27.60 62 [691,] 27.64 59 [692,] 27.68 61 [693,] 27.72 58 [694,] 27.76 46 [695,] 27.80 51 [696,] 27.84 59 [697,] 27.88 57 [698,] 27.92 47 [699,] 27.96 61 [700,] 28.00 54 [701,] 28.04 66 [702,] 28.08 56 [703,] 28.12 56 [704,] 28.16 68 [705,] 28.20 57 [706,] 28.24 52 [707,] 28.28 69 [708,] 28.32 37 [709,] 28.36 73 [710,] 28.40 77 [711,] 28.44 68 [712,] 28.48 64 [713,] 28.52 59 [714,] 28.56 58 [715,] 28.60 43 [716,] 28.64 58 [717,] 28.68 55 [718,] 28.72 50 [719,] 28.76 56 [720,] 28.80 55 [721,] 28.84 53 [722,] 28.88 69 [723,] 28.92 83 [724,] 28.96 55 [725,] 29.00 72 [726,] 29.04 59 [727,] 29.08 62 [728,] 29.12 54 [729,] 29.16 77 [730,] 29.20 43 [731,] 29.24 54 [732,] 29.28 65 [733,] 29.32 61 [734,] 29.36 45 [735,] 29.40 37 [736,] 29.44 73 [737,] 29.48 44 [738,] 29.52 52 [739,] 29.56 46 [740,] 29.60 60 [741,] 29.64 66 [742,] 29.68 65 [743,] 29.72 47 [744,] 29.76 64 [745,] 29.80 48 [746,] 29.84 57 [747,] 29.88 47 [748,] 29.92 44 [749,] 29.96 57 [750,] 30.00 55 [751,] 30.04 68 [752,] 30.08 44 [753,] 30.12 54 [754,] 30.16 54 [755,] 30.20 64 [756,] 30.24 71 [757,] 30.28 64 [758,] 30.32 59 [759,] 30.36 62 [760,] 30.40 56 [761,] 30.44 65 [762,] 30.48 70 [763,] 30.52 36 [764,] 30.56 73 [765,] 30.60 71 [766,] 30.64 50 [767,] 30.68 67 [768,] 30.72 73 [769,] 30.76 56 [770,] 30.80 65 [771,] 30.84 45 [772,] 30.88 57 [773,] 30.92 70 [774,] 30.96 56 [775,] 31.00 74 [776,] 31.04 51 [777,] 31.08 60 [778,] 31.12 59 [779,] 31.16 48 [780,] 31.20 52 [781,] 31.24 58 [782,] 31.28 63 [783,] 31.32 51 [784,] 31.36 55 [785,] 31.40 51 [786,] 31.44 51 [787,] 31.48 54 [788,] 31.52 54 [789,] 31.56 50 [790,] 31.60 52 [791,] 31.64 57 [792,] 31.68 55 [793,] 31.72 63 [794,] 31.76 64 [795,] 31.80 63 [796,] 31.84 61 [797,] 31.88 48 [798,] 31.92 79 [799,] 31.96 50 [800,] 32.00 56 [801,] 32.04 49 [802,] 32.08 60 [803,] 32.12 65 [804,] 32.16 49 [805,] 32.20 51 [806,] 32.24 60 [807,] 32.28 49 [808,] 32.32 55 [809,] 32.36 45 [810,] 32.40 63 [811,] 32.44 57 [812,] 32.48 81 [813,] 32.52 47 [814,] 32.56 56 [815,] 32.60 51 [816,] 32.64 49 [817,] 32.68 66 [818,] 32.72 69 [819,] 32.76 46 [820,] 32.80 63 [821,] 32.84 59 [822,] 32.88 65 [823,] 32.92 61 [824,] 32.96 62 [825,] 33.00 53 [826,] 33.04 63 [827,] 33.08 57 [828,] 33.12 76 [829,] 33.16 73 [830,] 33.20 61 [831,] 33.24 48 [832,] 33.28 71 [833,] 33.32 59 [834,] 33.36 41 [835,] 33.40 44 [836,] 33.44 52 [837,] 33.48 57 [838,] 33.52 76 [839,] 33.56 56 [840,] 33.60 65 [841,] 33.64 71 [842,] 33.68 56 [843,] 33.72 47 [844,] 33.76 70 [845,] 33.80 56 [846,] 33.84 59 [847,] 33.88 68 [848,] 33.92 70 [849,] 33.96 58 [850,] 34.00 33 [851,] 34.04 59 [852,] 34.08 56 [853,] 34.12 52 [854,] 34.16 63 [855,] 34.20 57 [856,] 34.24 62 [857,] 34.28 60 [858,] 34.32 64 [859,] 34.36 58 [860,] 34.40 42 [861,] 34.44 66 [862,] 34.48 78 [863,] 34.52 56 [864,] 34.56 61 [865,] 34.60 74 [866,] 34.64 62 [867,] 34.68 47 [868,] 34.72 78 [869,] 34.76 61 [870,] 34.80 60 [871,] 34.84 77 [872,] 34.88 52 [873,] 34.92 56 [874,] 34.96 67 [875,] 35.00 92 [876,] 35.04 52 [877,] 35.08 63 [878,] 35.12 50 [879,] 35.16 46 [880,] 35.20 62 [881,] 35.24 65 [882,] 35.28 58 [883,] 35.32 66 [884,] 35.36 59 [885,] 35.40 50 [886,] 35.44 51 [887,] 35.48 37 [888,] 35.52 68 [889,] 35.56 42 [890,] 35.60 70 [891,] 35.64 64 [892,] 35.68 52 [893,] 35.72 57 [894,] 35.76 77 [895,] 35.80 49 [896,] 35.84 57 [897,] 35.88 75 [898,] 35.92 51 [899,] 35.96 63 [900,] 36.00 51 [901,] 36.04 58 [902,] 36.08 55 [903,] 36.12 57 [904,] 36.16 46 [905,] 36.20 56 [906,] 36.24 57 [907,] 36.28 66 [908,] 36.32 57 [909,] 36.36 58 [910,] 36.40 50 [911,] 36.44 48 [912,] 36.48 52 [913,] 36.52 56 [914,] 36.56 59 [915,] 36.60 49 [916,] 36.64 55 [917,] 36.68 61 [918,] 36.72 66 [919,] 36.76 51 [920,] 36.80 66 [921,] 36.84 61 [922,] 36.88 52 [923,] 36.92 55 [924,] 36.96 54 [925,] 37.00 62 [926,] 37.04 53 [927,] 37.08 57 [928,] 37.12 57 [929,] 37.16 40 [930,] 37.20 58 [931,] 37.24 52 [932,] 37.28 66 [933,] 37.32 63 [934,] 37.36 66 [935,] 37.40 61 [936,] 37.44 49 [937,] 37.48 70 [938,] 37.52 63 [939,] 37.56 60 [940,] 37.60 52 [941,] 37.64 61 [942,] 37.68 72 [943,] 37.72 60 [944,] 37.76 50 [945,] 37.80 58 [946,] 37.84 64 [947,] 37.88 63 [948,] 37.92 70 [949,] 37.96 41 [950,] 38.00 74 [951,] 38.04 54 [952,] 38.08 54 [953,] 38.12 51 [954,] 38.16 68 [955,] 38.20 63 [956,] 38.24 50 [957,] 38.28 52 [958,] 38.32 82 [959,] 38.36 53 [960,] 38.40 59 [961,] 38.44 56 [962,] 38.48 45 [963,] 38.52 47 [964,] 38.56 52 [965,] 38.60 62 [966,] 38.64 62 [967,] 38.68 65 [968,] 38.72 78 [969,] 38.76 64 [970,] 38.80 64 [971,] 38.84 49 [972,] 38.88 54 [973,] 38.92 40 [974,] 38.96 74 [975,] 39.00 71 [976,] 39.04 62 [977,] 39.08 64 [978,] 39.12 72 [979,] 39.16 69 [980,] 39.20 78 [981,] 39.24 64 [982,] 39.28 83 [983,] 39.32 57 [984,] 39.36 54 [985,] 39.40 53 [986,] 39.44 69 [987,] 39.48 68 [988,] 39.52 40 [989,] 39.56 59 [990,] 39.60 56 [991,] 39.64 54 [992,] 39.68 50 [993,] 39.72 64 [994,] 39.76 63 [995,] 39.80 53 [996,] 39.84 55 [997,] 39.88 63 [998,] 39.92 65 [999,] 39.96 60 [1000,] 40.00 59 $`29_TL (PMT)` [,1] [,2] [1,] 0.884 4 [2,] 1.768 4 [3,] 2.652 7 [4,] 3.536 1 [5,] 4.420 10 [6,] 5.304 8 [7,] 6.188 3 [8,] 7.072 6 [9,] 7.956 5 [10,] 8.840 4 [11,] 9.724 5 [12,] 10.608 0 [13,] 11.492 5 [14,] 12.376 4 [15,] 13.260 6 [16,] 14.144 4 [17,] 15.028 3 [18,] 15.912 7 [19,] 16.796 1 [20,] 17.680 3 [21,] 18.564 0 [22,] 19.448 7 [23,] 20.332 6 [24,] 21.216 5 [25,] 22.100 6 [26,] 22.984 1 [27,] 23.868 14 [28,] 24.752 4 [29,] 25.636 1 [30,] 26.520 3 [31,] 27.404 1 [32,] 28.288 4 [33,] 29.172 4 [34,] 30.056 2 [35,] 30.940 7 [36,] 31.824 8 [37,] 32.708 4 [38,] 33.592 22 [39,] 34.476 4 [40,] 35.360 2 [41,] 36.244 9 [42,] 37.128 5 [43,] 38.012 10 [44,] 38.896 6 [45,] 39.780 7 [46,] 40.664 3 [47,] 41.548 1 [48,] 42.432 4 [49,] 43.316 11 [50,] 44.200 11 [51,] 45.084 19 [52,] 45.968 0 [53,] 46.852 12 [54,] 47.736 16 [55,] 48.620 6 [56,] 49.504 8 [57,] 50.388 2 [58,] 51.272 3 [59,] 52.156 5 [60,] 53.040 10 [61,] 53.924 5 [62,] 54.808 20 [63,] 55.692 6 [64,] 56.576 13 [65,] 57.460 7 [66,] 58.344 14 [67,] 59.228 7 [68,] 60.112 8 [69,] 60.996 18 [70,] 61.880 9 [71,] 62.764 13 [72,] 63.648 13 [73,] 64.532 7 [74,] 65.416 15 [75,] 66.300 17 [76,] 67.184 19 [77,] 68.068 26 [78,] 68.952 17 [79,] 69.836 18 [80,] 70.720 37 [81,] 71.604 47 [82,] 72.488 34 [83,] 73.372 26 [84,] 74.256 34 [85,] 75.140 42 [86,] 76.024 36 [87,] 76.908 39 [88,] 77.792 40 [89,] 78.676 46 [90,] 79.560 56 [91,] 80.444 49 [92,] 81.328 61 [93,] 82.212 61 [94,] 83.096 81 [95,] 83.980 70 [96,] 84.864 74 [97,] 85.748 88 [98,] 86.632 65 [99,] 87.516 103 [100,] 88.400 94 [101,] 89.284 120 [102,] 90.168 122 [103,] 91.052 110 [104,] 91.936 138 [105,] 92.820 146 [106,] 93.704 143 [107,] 94.588 118 [108,] 95.472 178 [109,] 96.356 168 [110,] 97.240 199 [111,] 98.124 209 [112,] 99.008 182 [113,] 99.892 160 [114,] 100.776 195 [115,] 101.660 174 [116,] 102.544 199 [117,] 103.428 222 [118,] 104.312 172 [119,] 105.196 245 [120,] 106.080 220 [121,] 106.964 256 [122,] 107.848 229 [123,] 108.732 217 [124,] 109.616 217 [125,] 110.500 263 [126,] 111.384 226 [127,] 112.268 188 [128,] 113.152 233 [129,] 114.036 258 [130,] 114.920 180 [131,] 115.804 168 [132,] 116.688 227 [133,] 117.572 177 [134,] 118.456 177 [135,] 119.340 157 [136,] 120.224 144 [137,] 121.108 165 [138,] 121.992 162 [139,] 122.876 116 [140,] 123.760 142 [141,] 124.644 151 [142,] 125.528 149 [143,] 126.412 139 [144,] 127.296 149 [145,] 128.180 121 [146,] 129.064 145 [147,] 129.948 175 [148,] 130.832 163 [149,] 131.716 144 [150,] 132.600 139 [151,] 133.484 189 [152,] 134.368 176 [153,] 135.252 175 [154,] 136.136 169 [155,] 137.020 178 [156,] 137.904 187 [157,] 138.788 149 [158,] 139.672 154 [159,] 140.556 157 [160,] 141.440 201 [161,] 142.324 205 [162,] 143.208 158 [163,] 144.092 184 [164,] 144.976 176 [165,] 145.860 183 [166,] 146.744 189 [167,] 147.628 185 [168,] 148.512 175 [169,] 149.396 170 [170,] 150.280 197 [171,] 151.164 163 [172,] 152.048 163 [173,] 152.932 158 [174,] 153.816 149 [175,] 154.700 167 [176,] 155.584 184 [177,] 156.468 157 [178,] 157.352 158 [179,] 158.236 201 [180,] 159.120 155 [181,] 160.004 143 [182,] 160.888 179 [183,] 161.772 132 [184,] 162.656 165 [185,] 163.540 162 [186,] 164.424 164 [187,] 165.308 183 [188,] 166.192 177 [189,] 167.076 180 [190,] 167.960 178 [191,] 168.844 155 [192,] 169.728 171 [193,] 170.612 165 [194,] 171.496 168 [195,] 172.380 155 [196,] 173.264 175 [197,] 174.148 152 [198,] 175.032 199 [199,] 175.916 162 [200,] 176.800 147 [201,] 177.684 194 [202,] 178.568 166 [203,] 179.452 152 [204,] 180.336 149 [205,] 181.220 153 [206,] 182.104 159 [207,] 182.988 163 [208,] 183.872 154 [209,] 184.756 183 [210,] 185.640 167 [211,] 186.524 154 [212,] 187.408 167 [213,] 188.292 148 [214,] 189.176 146 [215,] 190.060 154 [216,] 190.944 171 [217,] 191.828 164 [218,] 192.712 155 [219,] 193.596 162 [220,] 194.480 195 [221,] 195.364 210 [222,] 196.248 192 [223,] 197.132 212 [224,] 198.016 174 [225,] 198.900 185 [226,] 199.784 198 [227,] 200.668 192 [228,] 201.552 189 [229,] 202.436 197 [230,] 203.320 249 [231,] 204.204 192 [232,] 205.088 206 [233,] 205.972 219 [234,] 206.856 223 [235,] 207.740 268 [236,] 208.624 225 [237,] 209.508 244 [238,] 210.392 240 [239,] 211.276 187 [240,] 212.160 211 [241,] 213.044 214 [242,] 213.928 223 [243,] 214.812 245 [244,] 215.696 222 [245,] 216.580 242 [246,] 217.464 277 [247,] 218.348 236 [248,] 219.232 233 [249,] 220.116 246 [250,] 221.000 121 $`30_IRSL (PMT)` [,1] [,2] [1,] 0.04 34 [2,] 0.08 42 [3,] 0.12 28 [4,] 0.16 29 [5,] 0.20 35 [6,] 0.24 41 [7,] 0.28 30 [8,] 0.32 31 [9,] 0.36 36 [10,] 0.40 41 [11,] 0.44 30 [12,] 0.48 28 [13,] 0.52 34 [14,] 0.56 31 [15,] 0.60 46 [16,] 0.64 25 [17,] 0.68 20 [18,] 0.72 20 [19,] 0.76 25 [20,] 0.80 21 [21,] 0.84 28 [22,] 0.88 14 [23,] 0.92 19 [24,] 0.96 21 [25,] 1.00 22 [26,] 1.04 32 [27,] 1.08 27 [28,] 1.12 23 [29,] 1.16 21 [30,] 1.20 23 [31,] 1.24 30 [32,] 1.28 21 [33,] 1.32 18 [34,] 1.36 27 [35,] 1.40 29 [36,] 1.44 17 [37,] 1.48 21 [38,] 1.52 28 [39,] 1.56 19 [40,] 1.60 17 [41,] 1.64 24 [42,] 1.68 21 [43,] 1.72 11 [44,] 1.76 27 [45,] 1.80 14 [46,] 1.84 11 [47,] 1.88 24 [48,] 1.92 17 [49,] 1.96 17 [50,] 2.00 14 [51,] 2.04 12 [52,] 2.08 18 [53,] 2.12 18 [54,] 2.16 23 [55,] 2.20 19 [56,] 2.24 14 [57,] 2.28 15 [58,] 2.32 17 [59,] 2.36 16 [60,] 2.40 14 [61,] 2.44 19 [62,] 2.48 7 [63,] 2.52 13 [64,] 2.56 11 [65,] 2.60 13 [66,] 2.64 11 [67,] 2.68 15 [68,] 2.72 15 [69,] 2.76 15 [70,] 2.80 17 [71,] 2.84 12 [72,] 2.88 11 [73,] 2.92 10 [74,] 2.96 14 [75,] 3.00 9 [76,] 3.04 13 [77,] 3.08 13 [78,] 3.12 14 [79,] 3.16 10 [80,] 3.20 7 [81,] 3.24 5 [82,] 3.28 13 [83,] 3.32 9 [84,] 3.36 22 [85,] 3.40 11 [86,] 3.44 10 [87,] 3.48 14 [88,] 3.52 16 [89,] 3.56 7 [90,] 3.60 16 [91,] 3.64 16 [92,] 3.68 15 [93,] 3.72 12 [94,] 3.76 6 [95,] 3.80 13 [96,] 3.84 12 [97,] 3.88 7 [98,] 3.92 9 [99,] 3.96 11 [100,] 4.00 8 [101,] 4.04 12 [102,] 4.08 11 [103,] 4.12 7 [104,] 4.16 13 [105,] 4.20 5 [106,] 4.24 12 [107,] 4.28 6 [108,] 4.32 9 [109,] 4.36 12 [110,] 4.40 12 [111,] 4.44 9 [112,] 4.48 10 [113,] 4.52 14 [114,] 4.56 7 [115,] 4.60 6 [116,] 4.64 9 [117,] 4.68 7 [118,] 4.72 9 [119,] 4.76 4 [120,] 4.80 11 [121,] 4.84 7 [122,] 4.88 15 [123,] 4.92 11 [124,] 4.96 9 [125,] 5.00 13 [126,] 5.04 13 [127,] 5.08 8 [128,] 5.12 11 [129,] 5.16 7 [130,] 5.20 13 [131,] 5.24 10 [132,] 5.28 6 [133,] 5.32 11 [134,] 5.36 6 [135,] 5.40 2 [136,] 5.44 8 [137,] 5.48 7 [138,] 5.52 8 [139,] 5.56 9 [140,] 5.60 4 [141,] 5.64 6 [142,] 5.68 4 [143,] 5.72 8 [144,] 5.76 15 [145,] 5.80 11 [146,] 5.84 8 [147,] 5.88 5 [148,] 5.92 4 [149,] 5.96 13 [150,] 6.00 3 [151,] 6.04 8 [152,] 6.08 7 [153,] 6.12 15 [154,] 6.16 4 [155,] 6.20 11 [156,] 6.24 3 [157,] 6.28 1 [158,] 6.32 3 [159,] 6.36 7 [160,] 6.40 15 [161,] 6.44 6 [162,] 6.48 2 [163,] 6.52 7 [164,] 6.56 7 [165,] 6.60 2 [166,] 6.64 5 [167,] 6.68 2 [168,] 6.72 4 [169,] 6.76 10 [170,] 6.80 7 [171,] 6.84 10 [172,] 6.88 3 [173,] 6.92 9 [174,] 6.96 5 [175,] 7.00 5 [176,] 7.04 1 [177,] 7.08 5 [178,] 7.12 2 [179,] 7.16 4 [180,] 7.20 9 [181,] 7.24 3 [182,] 7.28 5 [183,] 7.32 4 [184,] 7.36 6 [185,] 7.40 8 [186,] 7.44 8 [187,] 7.48 8 [188,] 7.52 5 [189,] 7.56 9 [190,] 7.60 13 [191,] 7.64 1 [192,] 7.68 16 [193,] 7.72 6 [194,] 7.76 4 [195,] 7.80 7 [196,] 7.84 3 [197,] 7.88 9 [198,] 7.92 5 [199,] 7.96 6 [200,] 8.00 12 [201,] 8.04 10 [202,] 8.08 4 [203,] 8.12 9 [204,] 8.16 7 [205,] 8.20 7 [206,] 8.24 0 [207,] 8.28 3 [208,] 8.32 5 [209,] 8.36 8 [210,] 8.40 8 [211,] 8.44 6 [212,] 8.48 7 [213,] 8.52 4 [214,] 8.56 2 [215,] 8.60 10 [216,] 8.64 5 [217,] 8.68 5 [218,] 8.72 6 [219,] 8.76 5 [220,] 8.80 6 [221,] 8.84 9 [222,] 8.88 6 [223,] 8.92 9 [224,] 8.96 1 [225,] 9.00 7 [226,] 9.04 4 [227,] 9.08 4 [228,] 9.12 4 [229,] 9.16 2 [230,] 9.20 10 [231,] 9.24 4 [232,] 9.28 5 [233,] 9.32 5 [234,] 9.36 7 [235,] 9.40 8 [236,] 9.44 2 [237,] 9.48 5 [238,] 9.52 2 [239,] 9.56 4 [240,] 9.60 4 [241,] 9.64 10 [242,] 9.68 8 [243,] 9.72 5 [244,] 9.76 4 [245,] 9.80 5 [246,] 9.84 10 [247,] 9.88 5 [248,] 9.92 3 [249,] 9.96 4 [250,] 10.00 6 [251,] 10.04 3 [252,] 10.08 1 [253,] 10.12 4 [254,] 10.16 6 [255,] 10.20 5 [256,] 10.24 4 [257,] 10.28 4 [258,] 10.32 8 [259,] 10.36 3 [260,] 10.40 6 [261,] 10.44 3 [262,] 10.48 9 [263,] 10.52 8 [264,] 10.56 3 [265,] 10.60 10 [266,] 10.64 11 [267,] 10.68 3 [268,] 10.72 7 [269,] 10.76 4 [270,] 10.80 3 [271,] 10.84 6 [272,] 10.88 3 [273,] 10.92 7 [274,] 10.96 4 [275,] 11.00 3 [276,] 11.04 2 [277,] 11.08 0 [278,] 11.12 8 [279,] 11.16 0 [280,] 11.20 3 [281,] 11.24 7 [282,] 11.28 4 [283,] 11.32 8 [284,] 11.36 3 [285,] 11.40 7 [286,] 11.44 1 [287,] 11.48 7 [288,] 11.52 2 [289,] 11.56 4 [290,] 11.60 5 [291,] 11.64 1 [292,] 11.68 5 [293,] 11.72 4 [294,] 11.76 4 [295,] 11.80 9 [296,] 11.84 2 [297,] 11.88 12 [298,] 11.92 5 [299,] 11.96 2 [300,] 12.00 3 [301,] 12.04 6 [302,] 12.08 13 [303,] 12.12 12 [304,] 12.16 3 [305,] 12.20 2 [306,] 12.24 3 [307,] 12.28 4 [308,] 12.32 4 [309,] 12.36 3 [310,] 12.40 5 [311,] 12.44 3 [312,] 12.48 5 [313,] 12.52 1 [314,] 12.56 2 [315,] 12.60 4 [316,] 12.64 6 [317,] 12.68 8 [318,] 12.72 5 [319,] 12.76 1 [320,] 12.80 9 [321,] 12.84 2 [322,] 12.88 9 [323,] 12.92 7 [324,] 12.96 17 [325,] 13.00 3 [326,] 13.04 5 [327,] 13.08 1 [328,] 13.12 5 [329,] 13.16 8 [330,] 13.20 3 [331,] 13.24 2 [332,] 13.28 2 [333,] 13.32 4 [334,] 13.36 5 [335,] 13.40 6 [336,] 13.44 5 [337,] 13.48 5 [338,] 13.52 8 [339,] 13.56 5 [340,] 13.60 5 [341,] 13.64 3 [342,] 13.68 3 [343,] 13.72 6 [344,] 13.76 3 [345,] 13.80 1 [346,] 13.84 1 [347,] 13.88 1 [348,] 13.92 3 [349,] 13.96 1 [350,] 14.00 7 [351,] 14.04 20 [352,] 14.08 1 [353,] 14.12 1 [354,] 14.16 3 [355,] 14.20 6 [356,] 14.24 5 [357,] 14.28 5 [358,] 14.32 2 [359,] 14.36 3 [360,] 14.40 0 [361,] 14.44 0 [362,] 14.48 2 [363,] 14.52 0 [364,] 14.56 9 [365,] 14.60 5 [366,] 14.64 2 [367,] 14.68 2 [368,] 14.72 2 [369,] 14.76 1 [370,] 14.80 9 [371,] 14.84 7 [372,] 14.88 4 [373,] 14.92 7 [374,] 14.96 8 [375,] 15.00 7 [376,] 15.04 7 [377,] 15.08 7 [378,] 15.12 3 [379,] 15.16 2 [380,] 15.20 8 [381,] 15.24 6 [382,] 15.28 6 [383,] 15.32 2 [384,] 15.36 2 [385,] 15.40 2 [386,] 15.44 6 [387,] 15.48 3 [388,] 15.52 6 [389,] 15.56 2 [390,] 15.60 2 [391,] 15.64 1 [392,] 15.68 9 [393,] 15.72 5 [394,] 15.76 7 [395,] 15.80 1 [396,] 15.84 7 [397,] 15.88 2 [398,] 15.92 4 [399,] 15.96 7 [400,] 16.00 1 [401,] 16.04 6 [402,] 16.08 2 [403,] 16.12 0 [404,] 16.16 2 [405,] 16.20 3 [406,] 16.24 7 [407,] 16.28 6 [408,] 16.32 5 [409,] 16.36 2 [410,] 16.40 8 [411,] 16.44 9 [412,] 16.48 4 [413,] 16.52 2 [414,] 16.56 5 [415,] 16.60 1 [416,] 16.64 5 [417,] 16.68 2 [418,] 16.72 6 [419,] 16.76 1 [420,] 16.80 3 [421,] 16.84 0 [422,] 16.88 4 [423,] 16.92 2 [424,] 16.96 6 [425,] 17.00 4 [426,] 17.04 4 [427,] 17.08 3 [428,] 17.12 1 [429,] 17.16 9 [430,] 17.20 4 [431,] 17.24 5 [432,] 17.28 2 [433,] 17.32 3 [434,] 17.36 3 [435,] 17.40 2 [436,] 17.44 0 [437,] 17.48 1 [438,] 17.52 3 [439,] 17.56 1 [440,] 17.60 1 [441,] 17.64 8 [442,] 17.68 2 [443,] 17.72 3 [444,] 17.76 6 [445,] 17.80 1 [446,] 17.84 1 [447,] 17.88 3 [448,] 17.92 14 [449,] 17.96 7 [450,] 18.00 3 [451,] 18.04 5 [452,] 18.08 3 [453,] 18.12 2 [454,] 18.16 4 [455,] 18.20 4 [456,] 18.24 2 [457,] 18.28 2 [458,] 18.32 4 [459,] 18.36 4 [460,] 18.40 3 [461,] 18.44 5 [462,] 18.48 4 [463,] 18.52 7 [464,] 18.56 3 [465,] 18.60 2 [466,] 18.64 3 [467,] 18.68 1 [468,] 18.72 3 [469,] 18.76 6 [470,] 18.80 2 [471,] 18.84 0 [472,] 18.88 2 [473,] 18.92 6 [474,] 18.96 2 [475,] 19.00 4 [476,] 19.04 0 [477,] 19.08 2 [478,] 19.12 8 [479,] 19.16 0 [480,] 19.20 9 [481,] 19.24 3 [482,] 19.28 2 [483,] 19.32 6 [484,] 19.36 5 [485,] 19.40 4 [486,] 19.44 3 [487,] 19.48 5 [488,] 19.52 0 [489,] 19.56 3 [490,] 19.60 5 [491,] 19.64 2 [492,] 19.68 3 [493,] 19.72 7 [494,] 19.76 1 [495,] 19.80 4 [496,] 19.84 3 [497,] 19.88 7 [498,] 19.92 3 [499,] 19.96 2 [500,] 20.00 2 [501,] 20.04 5 [502,] 20.08 3 [503,] 20.12 1 [504,] 20.16 4 [505,] 20.20 1 [506,] 20.24 4 [507,] 20.28 0 [508,] 20.32 1 [509,] 20.36 1 [510,] 20.40 6 [511,] 20.44 3 [512,] 20.48 0 [513,] 20.52 4 [514,] 20.56 5 [515,] 20.60 6 [516,] 20.64 2 [517,] 20.68 6 [518,] 20.72 2 [519,] 20.76 2 [520,] 20.80 2 [521,] 20.84 0 [522,] 20.88 4 [523,] 20.92 8 [524,] 20.96 8 [525,] 21.00 7 [526,] 21.04 2 [527,] 21.08 0 [528,] 21.12 2 [529,] 21.16 3 [530,] 21.20 1 [531,] 21.24 3 [532,] 21.28 3 [533,] 21.32 5 [534,] 21.36 4 [535,] 21.40 4 [536,] 21.44 6 [537,] 21.48 4 [538,] 21.52 4 [539,] 21.56 7 [540,] 21.60 5 [541,] 21.64 4 [542,] 21.68 5 [543,] 21.72 3 [544,] 21.76 0 [545,] 21.80 5 [546,] 21.84 6 [547,] 21.88 3 [548,] 21.92 3 [549,] 21.96 3 [550,] 22.00 3 [551,] 22.04 3 [552,] 22.08 2 [553,] 22.12 6 [554,] 22.16 2 [555,] 22.20 1 [556,] 22.24 3 [557,] 22.28 2 [558,] 22.32 1 [559,] 22.36 6 [560,] 22.40 2 [561,] 22.44 0 [562,] 22.48 5 [563,] 22.52 4 [564,] 22.56 4 [565,] 22.60 2 [566,] 22.64 3 [567,] 22.68 3 [568,] 22.72 3 [569,] 22.76 3 [570,] 22.80 4 [571,] 22.84 3 [572,] 22.88 1 [573,] 22.92 5 [574,] 22.96 1 [575,] 23.00 7 [576,] 23.04 4 [577,] 23.08 1 [578,] 23.12 0 [579,] 23.16 3 [580,] 23.20 7 [581,] 23.24 4 [582,] 23.28 3 [583,] 23.32 5 [584,] 23.36 0 [585,] 23.40 7 [586,] 23.44 4 [587,] 23.48 1 [588,] 23.52 3 [589,] 23.56 3 [590,] 23.60 7 [591,] 23.64 4 [592,] 23.68 0 [593,] 23.72 1 [594,] 23.76 6 [595,] 23.80 4 [596,] 23.84 4 [597,] 23.88 0 [598,] 23.92 4 [599,] 23.96 3 [600,] 24.00 3 [601,] 24.04 7 [602,] 24.08 1 [603,] 24.12 0 [604,] 24.16 3 [605,] 24.20 3 [606,] 24.24 4 [607,] 24.28 3 [608,] 24.32 3 [609,] 24.36 5 [610,] 24.40 9 [611,] 24.44 6 [612,] 24.48 5 [613,] 24.52 4 [614,] 24.56 3 [615,] 24.60 1 [616,] 24.64 1 [617,] 24.68 9 [618,] 24.72 0 [619,] 24.76 0 [620,] 24.80 4 [621,] 24.84 3 [622,] 24.88 4 [623,] 24.92 2 [624,] 24.96 2 [625,] 25.00 1 [626,] 25.04 0 [627,] 25.08 2 [628,] 25.12 4 [629,] 25.16 6 [630,] 25.20 3 [631,] 25.24 5 [632,] 25.28 3 [633,] 25.32 2 [634,] 25.36 3 [635,] 25.40 2 [636,] 25.44 0 [637,] 25.48 4 [638,] 25.52 2 [639,] 25.56 2 [640,] 25.60 4 [641,] 25.64 1 [642,] 25.68 2 [643,] 25.72 2 [644,] 25.76 3 [645,] 25.80 2 [646,] 25.84 2 [647,] 25.88 3 [648,] 25.92 3 [649,] 25.96 1 [650,] 26.00 1 [651,] 26.04 4 [652,] 26.08 5 [653,] 26.12 3 [654,] 26.16 3 [655,] 26.20 9 [656,] 26.24 5 [657,] 26.28 6 [658,] 26.32 2 [659,] 26.36 11 [660,] 26.40 2 [661,] 26.44 2 [662,] 26.48 3 [663,] 26.52 1 [664,] 26.56 0 [665,] 26.60 1 [666,] 26.64 5 [667,] 26.68 3 [668,] 26.72 1 [669,] 26.76 2 [670,] 26.80 1 [671,] 26.84 0 [672,] 26.88 0 [673,] 26.92 0 [674,] 26.96 2 [675,] 27.00 0 [676,] 27.04 4 [677,] 27.08 7 [678,] 27.12 3 [679,] 27.16 1 [680,] 27.20 5 [681,] 27.24 0 [682,] 27.28 2 [683,] 27.32 9 [684,] 27.36 4 [685,] 27.40 0 [686,] 27.44 3 [687,] 27.48 10 [688,] 27.52 9 [689,] 27.56 2 [690,] 27.60 6 [691,] 27.64 0 [692,] 27.68 3 [693,] 27.72 5 [694,] 27.76 1 [695,] 27.80 9 [696,] 27.84 1 [697,] 27.88 0 [698,] 27.92 2 [699,] 27.96 5 [700,] 28.00 2 [701,] 28.04 6 [702,] 28.08 2 [703,] 28.12 2 [704,] 28.16 3 [705,] 28.20 1 [706,] 28.24 1 [707,] 28.28 2 [708,] 28.32 0 [709,] 28.36 3 [710,] 28.40 4 [711,] 28.44 5 [712,] 28.48 3 [713,] 28.52 2 [714,] 28.56 6 [715,] 28.60 1 [716,] 28.64 2 [717,] 28.68 6 [718,] 28.72 1 [719,] 28.76 3 [720,] 28.80 2 [721,] 28.84 2 [722,] 28.88 3 [723,] 28.92 7 [724,] 28.96 7 [725,] 29.00 2 [726,] 29.04 6 [727,] 29.08 6 [728,] 29.12 4 [729,] 29.16 0 [730,] 29.20 2 [731,] 29.24 2 [732,] 29.28 5 [733,] 29.32 1 [734,] 29.36 0 [735,] 29.40 2 [736,] 29.44 3 [737,] 29.48 3 [738,] 29.52 5 [739,] 29.56 5 [740,] 29.60 3 [741,] 29.64 0 [742,] 29.68 0 [743,] 29.72 2 [744,] 29.76 0 [745,] 29.80 2 [746,] 29.84 5 [747,] 29.88 6 [748,] 29.92 4 [749,] 29.96 2 [750,] 30.00 1 [751,] 30.04 1 [752,] 30.08 3 [753,] 30.12 3 [754,] 30.16 2 [755,] 30.20 3 [756,] 30.24 6 [757,] 30.28 5 [758,] 30.32 5 [759,] 30.36 2 [760,] 30.40 2 [761,] 30.44 3 [762,] 30.48 1 [763,] 30.52 4 [764,] 30.56 0 [765,] 30.60 1 [766,] 30.64 3 [767,] 30.68 3 [768,] 30.72 6 [769,] 30.76 8 [770,] 30.80 1 [771,] 30.84 9 [772,] 30.88 0 [773,] 30.92 4 [774,] 30.96 7 [775,] 31.00 1 [776,] 31.04 15 [777,] 31.08 4 [778,] 31.12 2 [779,] 31.16 1 [780,] 31.20 2 [781,] 31.24 2 [782,] 31.28 6 [783,] 31.32 0 [784,] 31.36 1 [785,] 31.40 3 [786,] 31.44 0 [787,] 31.48 7 [788,] 31.52 5 [789,] 31.56 3 [790,] 31.60 2 [791,] 31.64 3 [792,] 31.68 2 [793,] 31.72 3 [794,] 31.76 2 [795,] 31.80 1 [796,] 31.84 2 [797,] 31.88 5 [798,] 31.92 5 [799,] 31.96 2 [800,] 32.00 1 [801,] 32.04 0 [802,] 32.08 3 [803,] 32.12 0 [804,] 32.16 5 [805,] 32.20 10 [806,] 32.24 1 [807,] 32.28 1 [808,] 32.32 2 [809,] 32.36 1 [810,] 32.40 7 [811,] 32.44 4 [812,] 32.48 1 [813,] 32.52 5 [814,] 32.56 3 [815,] 32.60 0 [816,] 32.64 1 [817,] 32.68 0 [818,] 32.72 1 [819,] 32.76 2 [820,] 32.80 3 [821,] 32.84 1 [822,] 32.88 5 [823,] 32.92 3 [824,] 32.96 4 [825,] 33.00 3 [826,] 33.04 3 [827,] 33.08 5 [828,] 33.12 2 [829,] 33.16 2 [830,] 33.20 2 [831,] 33.24 0 [832,] 33.28 2 [833,] 33.32 3 [834,] 33.36 0 [835,] 33.40 4 [836,] 33.44 2 [837,] 33.48 1 [838,] 33.52 4 [839,] 33.56 5 [840,] 33.60 4 [841,] 33.64 1 [842,] 33.68 6 [843,] 33.72 0 [844,] 33.76 1 [845,] 33.80 9 [846,] 33.84 5 [847,] 33.88 10 [848,] 33.92 2 [849,] 33.96 4 [850,] 34.00 1 [851,] 34.04 1 [852,] 34.08 2 [853,] 34.12 2 [854,] 34.16 3 [855,] 34.20 8 [856,] 34.24 4 [857,] 34.28 4 [858,] 34.32 2 [859,] 34.36 2 [860,] 34.40 0 [861,] 34.44 1 [862,] 34.48 3 [863,] 34.52 1 [864,] 34.56 1 [865,] 34.60 3 [866,] 34.64 7 [867,] 34.68 1 [868,] 34.72 1 [869,] 34.76 6 [870,] 34.80 7 [871,] 34.84 4 [872,] 34.88 7 [873,] 34.92 0 [874,] 34.96 5 [875,] 35.00 1 [876,] 35.04 6 [877,] 35.08 5 [878,] 35.12 2 [879,] 35.16 0 [880,] 35.20 4 [881,] 35.24 4 [882,] 35.28 1 [883,] 35.32 1 [884,] 35.36 4 [885,] 35.40 5 [886,] 35.44 2 [887,] 35.48 3 [888,] 35.52 5 [889,] 35.56 4 [890,] 35.60 4 [891,] 35.64 5 [892,] 35.68 2 [893,] 35.72 5 [894,] 35.76 4 [895,] 35.80 1 [896,] 35.84 3 [897,] 35.88 2 [898,] 35.92 0 [899,] 35.96 0 [900,] 36.00 2 [901,] 36.04 6 [902,] 36.08 3 [903,] 36.12 5 [904,] 36.16 0 [905,] 36.20 4 [906,] 36.24 0 [907,] 36.28 1 [908,] 36.32 1 [909,] 36.36 3 [910,] 36.40 1 [911,] 36.44 3 [912,] 36.48 3 [913,] 36.52 3 [914,] 36.56 1 [915,] 36.60 4 [916,] 36.64 2 [917,] 36.68 4 [918,] 36.72 0 [919,] 36.76 3 [920,] 36.80 3 [921,] 36.84 1 [922,] 36.88 5 [923,] 36.92 2 [924,] 36.96 3 [925,] 37.00 3 [926,] 37.04 1 [927,] 37.08 1 [928,] 37.12 4 [929,] 37.16 1 [930,] 37.20 4 [931,] 37.24 4 [932,] 37.28 3 [933,] 37.32 3 [934,] 37.36 2 [935,] 37.40 7 [936,] 37.44 2 [937,] 37.48 1 [938,] 37.52 1 [939,] 37.56 6 [940,] 37.60 1 [941,] 37.64 0 [942,] 37.68 6 [943,] 37.72 3 [944,] 37.76 7 [945,] 37.80 2 [946,] 37.84 4 [947,] 37.88 1 [948,] 37.92 7 [949,] 37.96 8 [950,] 38.00 3 [951,] 38.04 3 [952,] 38.08 1 [953,] 38.12 3 [954,] 38.16 3 [955,] 38.20 0 [956,] 38.24 4 [957,] 38.28 6 [958,] 38.32 0 [959,] 38.36 2 [960,] 38.40 1 [961,] 38.44 2 [962,] 38.48 2 [963,] 38.52 1 [964,] 38.56 0 [965,] 38.60 1 [966,] 38.64 1 [967,] 38.68 2 [968,] 38.72 3 [969,] 38.76 0 [970,] 38.80 2 [971,] 38.84 14 [972,] 38.88 3 [973,] 38.92 0 [974,] 38.96 4 [975,] 39.00 0 [976,] 39.04 6 [977,] 39.08 3 [978,] 39.12 5 [979,] 39.16 5 [980,] 39.20 2 [981,] 39.24 8 [982,] 39.28 5 [983,] 39.32 1 [984,] 39.36 3 [985,] 39.40 1 [986,] 39.44 2 [987,] 39.48 2 [988,] 39.52 2 [989,] 39.56 1 [990,] 39.60 0 [991,] 39.64 3 [992,] 39.68 4 [993,] 39.72 1 [994,] 39.76 6 [995,] 39.80 2 [996,] 39.84 1 [997,] 39.88 0 [998,] 39.92 6 [999,] 39.96 2 [1000,] 40.00 2 > > ## Not run: > ##D ##select your BIN-file > ##D file <- file.choose() > ##D > ##D ##convert > ##D convert_BIN2CSV(file) > ##D > ## End(Not run) > > > > > cleanEx() > nameEx("convert_CW2pHMi") > ### * convert_CW2pHMi > > flush(stderr()); flush(stdout()) > > ### Name: convert_CW2pHMi > ### Title: Transform a CW-OSL curve into a pHM-OSL curve via interpolation > ### under hyperbolic modulation conditions > ### Aliases: convert_CW2pHMi > ### Keywords: manip > > ### ** Examples > > > ##(1) - simple transformation > > ##load CW-OSL curve data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ##transform values > values.transformed <- convert_CW2pHMi(ExampleData.CW_OSL_Curve) > > ##plot > plot(values.transformed$x, values.transformed$y.t, log = "x") > > ##(2) - load CW-OSL curve from BIN-file and plot transformed values > > ##load BINfile > #BINfileData<-readBIN2R("[path to BIN-file]") > data(ExampleData.BINfileData, envir = environment()) > > ##grep first CW-OSL curve from ALQ 1 > curve.ID<-CWOSL.SAR.Data@METADATA[CWOSL.SAR.Data@METADATA[,"LTYPE"]=="OSL" & + CWOSL.SAR.Data@METADATA[,"POSITION"]==1 + ,"ID"] > > curve.HIGH<-CWOSL.SAR.Data@METADATA[CWOSL.SAR.Data@METADATA[,"ID"]==curve.ID[1] + ,"HIGH"] > > curve.NPOINTS<-CWOSL.SAR.Data@METADATA[CWOSL.SAR.Data@METADATA[,"ID"]==curve.ID[1] + ,"NPOINTS"] > > ##combine curve to data set > curve<-data.frame(x = seq(curve.HIGH/curve.NPOINTS,curve.HIGH, + by = curve.HIGH/curve.NPOINTS), + y=unlist(CWOSL.SAR.Data@DATA[curve.ID[1]])) > > ##transform values > curve.transformed <- convert_CW2pHMi(curve) > > ##plot curve > plot(curve.transformed$x, curve.transformed$y.t, log = "x") > > ##(3) - produce Fig. 4 from Bos & Wallinga (2012) > > ##load data > data(ExampleData.CW_OSL_Curve, envir = environment()) > values <- CW_Curve.BosWallinga2012 > > ##open plot area > plot(NA, NA, + xlim=c(0.001,10), + ylim=c(0,8000), + ylab="pseudo OSL (cts/0.01 s)", + xlab="t [s]", + log="x", + main="Fig. 4 - Bos & Wallinga (2012)") > > values.t <- convert_CW2pLMi(values, P = 1/20) > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col="red" ,lwd=1.3) > text(0.03,4500,"LM", col="red" ,cex=.8) > > values.t <- convert_CW2pHMi(values, delta = 40) Warning: [convert_CW2pHMi()] 56 invalid values found, replaced by the mean of the nearest values > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col="black", lwd=1.3) > text(0.005,3000,"HM", cex=.8) > > values.t <- convert_CW2pPMi(values, P = 1/10) Warning: [convert_CW2pPMi()] t' is beyond the time resolution and more than two data points have been extrapolated > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col="blue", lwd=1.3) > text(0.5,6500,"PM", col="blue" ,cex=.8) > > > > > cleanEx() > nameEx("convert_CW2pLM") > ### * convert_CW2pLM > > flush(stderr()); flush(stdout()) > > ### Name: convert_CW2pLM > ### Title: Transform a CW-OSL curve into a pLM-OSL curve > ### Aliases: convert_CW2pLM > ### Keywords: manip > > ### ** Examples > > > ##read curve from CWOSL.SAR.Data transform curve and plot values > data(ExampleData.BINfileData, envir = environment()) > > ##read id for the 1st OSL curve > id.OSL <- CWOSL.SAR.Data@METADATA[CWOSL.SAR.Data@METADATA[,"LTYPE"] == "OSL","ID"] > > ##produce x and y (time and count data for the data set) > x<-seq(CWOSL.SAR.Data@METADATA[id.OSL[1],"HIGH"]/CWOSL.SAR.Data@METADATA[id.OSL[1],"NPOINTS"], + CWOSL.SAR.Data@METADATA[id.OSL[1],"HIGH"], + by = CWOSL.SAR.Data@METADATA[id.OSL[1],"HIGH"]/CWOSL.SAR.Data@METADATA[id.OSL[1],"NPOINTS"]) > y <- unlist(CWOSL.SAR.Data@DATA[id.OSL[1]]) > values <- data.frame(x,y) > > ##transform values > values.transformed <- convert_CW2pLM(values) > > ##plot > plot(values.transformed) > > > > > cleanEx() > nameEx("convert_CW2pLMi") > ### * convert_CW2pLMi > > flush(stderr()); flush(stdout()) > > ### Name: convert_CW2pLMi > ### Title: Transform a CW-OSL curve into a pLM-OSL curve via interpolation > ### under linear modulation conditions > ### Aliases: convert_CW2pLMi > ### Keywords: manip > > ### ** Examples > > > ##(1) > ##load CW-OSL curve data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ##transform values > values.transformed <- convert_CW2pLMi(ExampleData.CW_OSL_Curve) > > ##plot > plot(values.transformed$x, values.transformed$y.t, log = "x") > > ##(2) - produce Fig. 4 from Bos & Wallinga (2012) > ##load data > data(ExampleData.CW_OSL_Curve, envir = environment()) > values <- CW_Curve.BosWallinga2012 > > ##open plot area > plot(NA, NA, + xlim = c(0.001,10), + ylim = c(0,8000), + ylab = "pseudo OSL (cts/0.01 s)", + xlab = "t [s]", + log = "x", + main = "Fig. 4 - Bos & Wallinga (2012)") > > > values.t <- convert_CW2pLMi(values, P = 1/20) > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col = "red", lwd = 1.3) > text(0.03,4500,"LM", col = "red", cex = .8) > > values.t <- convert_CW2pHMi(values, delta = 40) Warning: [convert_CW2pHMi()] 56 invalid values found, replaced by the mean of the nearest values > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col = "black", lwd = 1.3) > text(0.005,3000,"HM", cex =.8) > > values.t <- convert_CW2pPMi(values, P = 1/10) Warning: [convert_CW2pPMi()] t' is beyond the time resolution and more than two data points have been extrapolated > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col = "blue", lwd = 1.3) > text(0.5,6500,"PM", col = "blue", cex = .8) > > > > > cleanEx() > nameEx("convert_CW2pPMi") > ### * convert_CW2pPMi > > flush(stderr()); flush(stdout()) > > ### Name: convert_CW2pPMi > ### Title: Transform a CW-OSL curve into a pPM-OSL curve via interpolation > ### under parabolic modulation conditions > ### Aliases: convert_CW2pPMi > ### Keywords: manip > > ### ** Examples > > > ##(1) > ##load CW-OSL curve data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ##transform values > values.transformed <- convert_CW2pPMi(ExampleData.CW_OSL_Curve) > > ##plot > plot(values.transformed$x,values.transformed$y.t, log = "x") > > ##(2) - produce Fig. 4 from Bos & Wallinga (2012) > > ##load data > data(ExampleData.CW_OSL_Curve, envir = environment()) > values <- CW_Curve.BosWallinga2012 > > ##open plot area > plot(NA, NA, + xlim = c(0.001,10), + ylim = c(0,8000), + ylab = "pseudo OSL (cts/0.01 s)", + xlab = "t [s]", + log = "x", + main = "Fig. 4 - Bos & Wallinga (2012)") > > values.t <- convert_CW2pLMi(values, P = 1/20) > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col = "red",lwd = 1.3) > text(0.03,4500,"LM", col = "red", cex = .8) > > values.t <- convert_CW2pHMi(values, delta = 40) Warning: [convert_CW2pHMi()] 56 invalid values found, replaced by the mean of the nearest values > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col = "black", lwd = 1.3) > text(0.005,3000,"HM", cex = .8) > > values.t <- convert_CW2pPMi(values, P = 1/10) Warning: [convert_CW2pPMi()] t' is beyond the time resolution and more than two data points have been extrapolated > lines(values[1:length(values.t[, 1]), 1], values.t[, 2], + col = "blue", lwd = 1.3) > text(0.5,6500,"PM", col = "blue", cex = .8) > > > > > cleanEx() > nameEx("convert_Concentration2DoseRate") > ### * convert_Concentration2DoseRate > > flush(stderr()); flush(stdout()) > > ### Name: convert_Concentration2DoseRate > ### Title: Dose-rate conversion function > ### Aliases: convert_Concentration2DoseRate > ### Keywords: datagen > > ### ** Examples > > > ## create input template > input <- convert_Concentration2DoseRate() [convert_Concentration2DoseRate()] Input template returned, please fill this data frame and use it as input to the function > > ## fill input > input$Mineral <- "FS" > input$K <- 2.13 > input$K_SE <- 0.07 > input$Th <- 9.76 > input$Th_SE <- 0.32 > input$U <- 2.24 > input$U_SE <- 0.12 > input$GrainSize <- 200 > input$WaterContent <- 30 > input$WaterContent_SE <- 5 > > ## convert > convert_Concentration2DoseRate(input) [RLum.Results-class] originator: convert_Concentration2DoseRate() data: 2 .. $InfDRG : matrix .. $input_data : data.frame additional info elements: 1 > > > > > cleanEx() > nameEx("convert_Daybreak2CSV") > ### * convert_Daybreak2CSV > > flush(stderr()); flush(stdout()) > > ### Name: convert_Daybreak2CSV > ### Title: Export measurement data produced by a Daybreak luminescence > ### reader to CSV-files > ### Aliases: convert_Daybreak2CSV > ### Keywords: IO > > ### ** Examples > > > ## Not run: > ##D ##select your BIN-file > ##D file <- file.choose() > ##D > ##D ##convert > ##D convert_Daybreak2CSV(file) > ## End(Not run) > > > > > cleanEx() > nameEx("convert_PSL2CSV") > ### * convert_PSL2CSV > > flush(stderr()); flush(stdout()) > > ### Name: convert_PSL2CSV > ### Title: Export PSL-file(s) to CSV-files > ### Aliases: convert_PSL2CSV > ### Keywords: IO > > ### ** Examples > > > ## export into single data.frame > file <- system.file("extdata/DorNie_0016.psl", package="Luminescence") > convert_PSL2CSV(file, export = FALSE, single_table = TRUE) [read_PSL2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: DorNie_0016.psl $conv_ALU0016_psl 1_USER (PMT)_t 1_USER (PMT)_cts 2_IRSL (PMT)_t 2_IRSL (PMT)_cts 1 1 0 1 16660 2 2 -2 2 16129 3 3 14 3 15860 4 4 7 4 15773 5 5 6 5 13509 6 6 -7 6 15171 7 7 -1 7 15025 8 8 6 8 14753 9 9 -8 9 14438 10 10 3 10 14205 11 11 -2 11 14048 12 12 6 12 13886 13 13 0 13 13769 14 14 6 14 13619 15 15 -3 15 13365 16 NA NA 16 12847 17 NA NA 17 12967 18 NA NA 18 12693 19 NA NA 19 12726 20 NA NA 20 12663 21 NA NA 21 12740 22 NA NA 22 12394 23 NA NA 23 12142 24 NA NA 24 12139 25 NA NA 25 11967 26 NA NA 26 11870 27 NA NA 27 11836 28 NA NA 28 11673 29 NA NA 29 11539 30 NA NA 30 11513 31 NA NA 31 11443 32 NA NA 32 11391 33 NA NA 33 11263 34 NA NA 34 11128 35 NA NA 35 11026 36 NA NA 36 10991 37 NA NA 37 10798 38 NA NA 38 10781 39 NA NA 39 10754 40 NA NA 40 10455 41 NA NA 41 10705 42 NA NA 42 10457 43 NA NA 43 10358 44 NA NA 44 10578 45 NA NA 45 10543 46 NA NA 46 10260 47 NA NA 47 10263 48 NA NA 48 10209 49 NA NA 49 9936 50 NA NA 50 9943 51 NA NA 51 9782 52 NA NA 52 9836 53 NA NA 53 9876 54 NA NA 54 8814 55 NA NA 55 9854 56 NA NA 56 9571 57 NA NA 57 9581 58 NA NA 58 9433 59 NA NA 59 9568 60 NA NA 60 9466 61 NA NA 61 9362 62 NA NA 62 9267 63 NA NA 63 9240 64 NA NA 64 9425 65 NA NA 65 9129 66 NA NA 66 9132 67 NA NA 67 9036 68 NA NA 68 9166 69 NA NA 69 8859 70 NA NA 70 8973 71 NA NA 71 8914 72 NA NA 72 8921 73 NA NA 73 8819 74 NA NA 74 8935 75 NA NA 75 8711 76 NA NA 76 8862 77 NA NA 77 8847 78 NA NA 78 8611 79 NA NA 79 8785 80 NA NA 80 8583 81 NA NA 81 8340 82 NA NA 82 8481 83 NA NA 83 8525 84 NA NA 84 8286 85 NA NA 85 8547 86 NA NA 86 8292 87 NA NA 87 8415 88 NA NA 88 8231 89 NA NA 89 8054 90 NA NA 90 8489 91 NA NA 91 8075 92 NA NA 92 8076 93 NA NA 93 8048 94 NA NA 94 7913 95 NA NA 95 7952 96 NA NA 96 7993 97 NA NA 97 7914 98 NA NA 98 7909 99 NA NA 99 7863 100 NA NA 100 7966 3_USER (PMT)_t 3_USER (PMT)_cts 4_OSL (PMT)_t 4_OSL (PMT)_cts 1 1 4 1 88023 2 2 10 2 85585 3 3 -5 3 83394 4 4 -1 4 80840 5 5 -8 5 78826 6 6 -6 6 76523 7 7 13 7 74442 8 8 5 8 72370 9 9 -24 9 70429 10 10 11 10 69502 11 11 9 11 67389 12 12 7 12 65571 13 13 -8 13 64550 14 14 -12 14 62602 15 15 -7 15 61530 16 NA NA 16 59973 17 NA NA 17 58776 18 NA NA 18 56702 19 NA NA 19 56463 20 NA NA 20 55544 21 NA NA 21 54560 22 NA NA 22 53655 23 NA NA 23 51510 24 NA NA 24 51533 25 NA NA 25 50612 26 NA NA 26 49634 27 NA NA 27 48865 28 NA NA 28 47477 29 NA NA 29 47611 30 NA NA 30 46493 31 NA NA 31 46228 32 NA NA 32 45406 33 NA NA 33 44412 34 NA NA 34 43986 35 NA NA 35 42660 36 NA NA 36 42668 37 NA NA 37 42134 38 NA NA 38 41714 39 NA NA 39 41122 40 NA NA 40 40480 41 NA NA 41 39864 42 NA NA 42 39509 43 NA NA 43 38667 44 NA NA 44 34400 45 NA NA 45 37490 46 NA NA 46 37932 47 NA NA 47 37080 48 NA NA 48 36770 49 NA NA 49 35939 50 NA NA 50 35905 51 NA NA 51 35136 52 NA NA 52 34799 53 NA NA 53 34099 54 NA NA 54 33965 55 NA NA 55 33632 56 NA NA 56 33346 57 NA NA 57 32733 58 NA NA 58 32818 59 NA NA 59 31939 60 NA NA 60 31811 61 NA NA 61 31846 62 NA NA 62 31014 63 NA NA 63 31358 64 NA NA 64 30640 65 NA NA 65 30371 66 NA NA 66 30182 67 NA NA 67 29531 68 NA NA 68 29751 69 NA NA 69 29212 70 NA NA 70 28599 71 NA NA 71 28182 72 NA NA 72 28644 73 NA NA 73 28154 74 NA NA 74 27587 75 NA NA 75 27537 76 NA NA 76 27275 77 NA NA 77 27064 78 NA NA 78 27142 79 NA NA 79 26655 80 NA NA 80 26503 81 NA NA 81 26296 82 NA NA 82 25213 83 NA NA 83 25774 84 NA NA 84 24724 85 NA NA 85 25337 86 NA NA 86 25361 87 NA NA 87 24962 88 NA NA 88 24411 89 NA NA 89 24427 90 NA NA 90 24599 91 NA NA 91 24128 92 NA NA 92 23943 93 NA NA 93 21914 94 NA NA 94 23812 95 NA NA 95 23516 96 NA NA 96 23346 97 NA NA 97 22965 98 NA NA 98 22955 99 NA NA 99 22828 100 NA NA 100 22552 5_USER (PMT)_t 5_USER (PMT)_cts 1 1 -22 2 2 -1 3 3 25 4 4 0 5 5 12 6 6 4 7 7 12 8 8 -13 9 9 26 10 10 -16 11 11 -26 12 12 -12 13 13 28 14 14 -8 15 15 -10 16 NA NA 17 NA NA 18 NA NA 19 NA NA 20 NA NA 21 NA NA 22 NA NA 23 NA NA 24 NA NA 25 NA NA 26 NA NA 27 NA NA 28 NA NA 29 NA NA 30 NA NA 31 NA NA 32 NA NA 33 NA NA 34 NA NA 35 NA NA 36 NA NA 37 NA NA 38 NA NA 39 NA NA 40 NA NA 41 NA NA 42 NA NA 43 NA NA 44 NA NA 45 NA NA 46 NA NA 47 NA NA 48 NA NA 49 NA NA 50 NA NA 51 NA NA 52 NA NA 53 NA NA 54 NA NA 55 NA NA 56 NA NA 57 NA NA 58 NA NA 59 NA NA 60 NA NA 61 NA NA 62 NA NA 63 NA NA 64 NA NA 65 NA NA 66 NA NA 67 NA NA 68 NA NA 69 NA NA 70 NA NA 71 NA NA 72 NA NA 73 NA NA 74 NA NA 75 NA NA 76 NA NA 77 NA NA 78 NA NA 79 NA NA 80 NA NA 81 NA NA 82 NA NA 83 NA NA 84 NA NA 85 NA NA 86 NA NA 87 NA NA 88 NA NA 89 NA NA 90 NA NA 91 NA NA 92 NA NA 93 NA NA 94 NA NA 95 NA NA 96 NA NA 97 NA NA 98 NA NA 99 NA NA 100 NA NA > > ## Not run: > ##D ##select your BIN-file > ##D file <- file.choose() > ##D > ##D ##convert > ##D convert_PSL2CSV(file) > ## End(Not run) > > > > > cleanEx() > nameEx("convert_PSL2Risoe.BINfileData") > ### * convert_PSL2Risoe.BINfileData > > flush(stderr()); flush(stdout()) > > ### Name: convert_PSL2Risoe.BINfileData > ### Title: Convert portable OSL data to a Risoe.BINfileData object > ### Aliases: convert_PSL2Risoe.BINfileData > ### Keywords: IO > > ### ** Examples > > > # (1) load and plot example data set > data("ExampleData.portableOSL", envir = environment()) > plot_RLum(ExampleData.portableOSL) > > # (2) merge all RLum.Analysis objects into one > merged <- merge_RLum(ExampleData.portableOSL) > merged [RLum.Analysis-class] originator: merge_RLum.Analysis() protocol: portable OSL additional info elements: 196 number of records: 70 .. : RLum.Data.Curve : 70 .. .. : #1 USER (PMT) | #2 IRSL (PMT) | #3 USER (PMT) | #4 OSL (PMT) | #5 USER (PMT) | #6 USER (PMT) | #7 IRSL (PMT) .. .. : #8 USER (PMT) | #9 OSL (PMT) | #10 USER (PMT) | #11 USER (PMT) | #12 IRSL (PMT) | #13 USER (PMT) | #14 OSL (PMT) .. .. : #15 USER (PMT) | #16 USER (PMT) | #17 IRSL (PMT) | #18 USER (PMT) | #19 OSL (PMT) | #20 USER (PMT) | #21 USER (PMT) .. .. : #22 IRSL (PMT) | #23 USER (PMT) | #24 OSL (PMT) | #25 USER (PMT) | #26 USER (PMT) | #27 IRSL (PMT) | #28 USER (PMT) .. .. : #29 OSL (PMT) | #30 USER (PMT) | #31 USER (PMT) | #32 IRSL (PMT) | #33 USER (PMT) | #34 OSL (PMT) | #35 USER (PMT) .. .. : #36 USER (PMT) | #37 IRSL (PMT) | #38 USER (PMT) | #39 OSL (PMT) | #40 USER (PMT) | #41 USER (PMT) | #42 IRSL (PMT) .. .. : #43 USER (PMT) | #44 OSL (PMT) | #45 USER (PMT) | #46 USER (PMT) | #47 IRSL (PMT) | #48 USER (PMT) | #49 OSL (PMT) .. .. : #50 USER (PMT) | #51 USER (PMT) | #52 IRSL (PMT) | #53 USER (PMT) | #54 OSL (PMT) | #55 USER (PMT) | #56 USER (PMT) .. .. : #57 IRSL (PMT) | #58 USER (PMT) | #59 OSL (PMT) | #60 USER (PMT) | #61 USER (PMT) | #62 IRSL (PMT) | #63 USER (PMT) .. .. : #64 OSL (PMT) | #65 USER (PMT) | #66 USER (PMT) | #67 IRSL (PMT) | #68 USER (PMT) | #69 OSL (PMT) | #70 USER (PMT) > > # (3) convert to RisoeBINfile object > bin <- convert_PSL2Risoe.BINfileData(merged) > bin [Risoe.BINfileData object] BIN/BINX version: 7 File name: Praktikum2016 Object date: 190516 User: RLum System ID: 0 (unknown) Overall records: 70 Records type: IRSL (n = 14) OSL (n = 14) USER (n = 42) Position range: 1 : 1 Run range: 1 : 70 Set range: 1 : 1 > > # (4) write Risoe BIN file > ## Not run: > ##D write_R2BIN(bin, "~/portableOSL.binx") > ## End(Not run) > > > > > cleanEx() > nameEx("convert_RLum2Risoe.BINfileData") > ### * convert_RLum2Risoe.BINfileData > > flush(stderr()); flush(stdout()) > > ### Name: convert_RLum2Risoe.BINfileData > ### Title: Converts RLum.Analysis and RLum.Data.Curve objects to > ### RLum2Risoe.BINfileData objects > ### Aliases: convert_RLum2Risoe.BINfileData > ### Keywords: IO > > ### ** Examples > > > ##simple conversion using the example dataset > data(ExampleData.RLum.Analysis, envir = environment()) > convert_RLum2Risoe.BINfileData(IRSAR.RF.Data) [Risoe.BINfileData object] BIN/BINX version: 0 Object date: 20260312 User: 0 System ID: 0 (unknown) Overall records: 2 Records type: RL (n = 2) Position range: 0 : 0 Run range: 1 : 2 Set range: 0 : 0 > > > > > cleanEx() > nameEx("convert_SG2MG") > ### * convert_SG2MG > > flush(stderr()); flush(stdout()) > > ### Name: convert_SG2MG > ### Title: Converts Single-Grain Data to Multiple-Grain Data > ### Aliases: convert_SG2MG > ### Keywords: IO > > ### ** Examples > > ## simple run > ## (please not that the example is not using SG data) > data(ExampleData.BINfileData, envir = environment()) > convert_SG2MG(CWOSL.SAR.Data) [Risoe.BINfileData object] BIN/BINX version: 03 Object date: 060920, 070920, 080920, 090920, 100920 User: Default System ID: 0 (unknown) Overall records: 720 Records type: IRSL (n = 24) OSL (n = 336) TL (n = 360) Position range: 1 : 24 Run range: 1 : 8 Set range: 2 : 6 > > > > > cleanEx() > nameEx("convert_Second2Gray") > ### * convert_Second2Gray > > flush(stderr()); flush(stdout()) > > ### Name: convert_Second2Gray > ### Title: Converting equivalent dose values from seconds (s) to Gray (Gy) > ### Aliases: convert_Second2Gray > ### Keywords: manip > > ### ** Examples > > > ##(A) for known source dose rate at date of measurement > ## - load De data from the example data help file > data(ExampleData.DeValues, envir = environment()) > ## - convert De(s) to De(Gy) > convert_Second2Gray(ExampleData.DeValues$BT998, c(0.0438,0.0019)) De De.error 1 151.48 5.334 2 152.08 5.144 3 165.80 6.805 4 136.15 4.608 5 144.42 4.642 6 123.44 4.471 7 123.64 4.227 8 127.07 4.396 9 125.06 4.630 10 124.45 4.256 11 118.60 4.049 12 128.08 4.408 13 110.78 3.701 14 121.02 4.187 15 124.09 4.129 16 124.70 4.043 17 123.68 4.262 18 126.34 4.228 19 128.59 4.254 20 131.46 4.448 21 127.77 4.330 22 131.05 5.023 23 126.34 4.317 24 115.49 3.479 25 119.58 3.815 > > > ##(B) for source dose rate calibration data > ## - calculate source dose rate first > dose.rate <- calc_SourceDoseRate(measurement.date = "2012-01-27", + calib.date = "2014-12-19", + calib.dose.rate = 0.0438, + calib.error = 0.0019) > # read example data > data(ExampleData.DeValues, envir = environment()) > > # apply dose.rate to convert De(s) to De(Gy) > convert_Second2Gray(ExampleData.DeValues$BT998, dose.rate) De De.error 1 162.37 5.717 2 163.01 5.514 3 177.72 7.294 4 145.93 4.939 5 154.80 4.976 6 132.31 4.792 7 132.53 4.531 8 136.21 4.712 9 134.04 4.962 10 133.39 4.561 11 127.12 4.340 12 137.29 4.724 13 118.74 3.967 14 129.71 4.488 15 133.01 4.426 16 133.66 4.334 17 132.57 4.568 18 135.42 4.531 19 137.83 4.560 20 140.91 4.768 21 136.96 4.641 22 140.47 5.384 23 135.42 4.628 24 123.79 3.729 25 128.18 4.090 > > > > > cleanEx() > nameEx("convert_Wavelength2Energy") > ### * convert_Wavelength2Energy > > flush(stderr()); flush(stdout()) > > ### Name: convert_Wavelength2Energy > ### Title: Emission Spectra Conversion from Wavelength to Energy Scales > ### (Jacobian Conversion) > ### Aliases: convert_Wavelength2Energy > ### Keywords: IO > > ### ** Examples > > > ##=====================## > ##(1) Literature example after Mooney et al. (2013) > ##(1.1) create matrix > m <- matrix( + data = c(seq(400, 800, 50), rep(1, 9)), ncol = 2) > > ##(1.2) set plot function to reproduce the literature figure > p <- function(m) { + plot(x = m[, 1], y = m[, 2]) + polygon( + x = c(m[, 1], rev(m[, 1])), + y = c(m[, 2], rep(0, nrow(m)))) + for (i in 1:nrow(m)) { + lines(x = rep(m[i, 1], 2), y = c(0, m[i, 2])) + } + } > > ##(1.3) plot curves > par(mfrow = c(1,2)) > p(m) > p(convert_Wavelength2Energy(m)) > > ##=====================## > ##(2) Another example using density curves > ##create dataset > xy <- density( + c(rnorm(n = 100, mean = 500, sd = 20), + rnorm(n = 100, mean = 800, sd = 20))) > xy <- data.frame(xy$x, xy$y) > > ##plot > par(mfrow = c(1,2)) > plot( + xy, + type = "l", + xlim = c(150, 1000), + xlab = "Wavelength [nm]", + ylab = "Luminescence [a.u.]" + ) > plot( + convert_Wavelength2Energy(xy), + xy$y, + type = "l", + xlim = c(1.23, 8.3), + xlab = "Energy [eV]", + ylab = "Luminescence [a.u.]" + ) > > > > > graphics::par(get("par.postscript", pos = 'CheckExEnv')) > cleanEx() > nameEx("convert_XSYG2CSV") > ### * convert_XSYG2CSV > > flush(stderr()); flush(stdout()) > > ### Name: convert_XSYG2CSV > ### Title: Export XSYG-file(s) to CSV-files > ### Aliases: convert_XSYG2CSV > ### Keywords: IO > > ### ** Examples > > > ##transform XSYG-file values to a list > data(ExampleData.XSYG, envir = environment()) > convert_XSYG2CSV(OSL.SARMeasurement$Sequence.Object[1:10], export = FALSE) $`1_TL (UVVIS)` [,1] [,2] [1,] 0.1 9 [2,] 0.2 7 [3,] 0.3 7 [4,] 0.4 9 [5,] 0.5 20 [6,] 0.6 12 [7,] 0.7 13 [8,] 0.8 17 [9,] 0.9 10 [10,] 1.0 11 [11,] 1.1 13 [12,] 1.2 13 [13,] 1.3 10 [14,] 1.4 3 [15,] 1.5 12 [16,] 1.6 18 [17,] 1.7 11 [18,] 1.8 11 [19,] 1.9 12 [20,] 2.0 9 [21,] 2.1 10 [22,] 2.2 0 [23,] 2.3 15 [24,] 2.4 14 [25,] 2.5 14 [26,] 2.6 14 [27,] 2.7 14 [28,] 2.8 7 [29,] 2.9 18 [30,] 3.0 16 [31,] 3.1 10 [32,] 3.2 14 [33,] 3.3 10 [34,] 3.4 10 [35,] 3.5 5 [36,] 3.6 11 [37,] 3.7 17 [38,] 3.8 18 [39,] 3.9 11 [40,] 4.0 4 [41,] 4.1 11 [42,] 4.2 12 [43,] 4.3 21 [44,] 4.4 7 [45,] 4.5 18 [46,] 4.6 8 [47,] 4.7 19 [48,] 4.8 9 [49,] 4.9 14 [50,] 5.0 22 [51,] 5.1 12 [52,] 5.2 20 [53,] 5.3 16 [54,] 5.4 19 [55,] 5.5 10 [56,] 5.6 18 [57,] 5.7 20 [58,] 5.8 18 [59,] 5.9 14 [60,] 6.0 9 [61,] 6.1 9 [62,] 6.2 17 [63,] 6.3 26 [64,] 6.4 12 [65,] 6.5 13 [66,] 6.6 10 [67,] 6.7 12 [68,] 6.8 8 [69,] 6.9 12 [70,] 7.0 16 [71,] 7.1 9 [72,] 7.2 11 [73,] 7.3 18 [74,] 7.4 5 [75,] 7.5 9 [76,] 7.6 6 [77,] 7.7 8 [78,] 7.8 17 [79,] 7.9 18 [80,] 8.0 18 [81,] 8.1 11 [82,] 8.2 10 [83,] 8.3 16 [84,] 8.4 11 [85,] 8.5 14 [86,] 8.6 10 [87,] 8.7 10 [88,] 8.8 8 [89,] 8.9 15 [90,] 9.0 7 [91,] 9.1 11 [92,] 9.2 11 [93,] 9.3 16 [94,] 9.4 10 [95,] 9.5 14 [96,] 9.6 13 [97,] 9.7 11 [98,] 9.8 10 [99,] 9.9 8 [100,] 10.0 10 [101,] 10.1 9 [102,] 10.2 10 [103,] 10.3 13 [104,] 10.4 12 [105,] 10.5 15 [106,] 10.6 12 [107,] 10.7 6 [108,] 10.8 13 [109,] 10.9 10 [110,] 11.0 15 [111,] 11.1 14 [112,] 11.2 9 [113,] 11.3 4 [114,] 11.4 14 [115,] 11.5 15 [116,] 11.6 0 [117,] 11.7 19 [118,] 11.8 12 [119,] 11.9 10 [120,] 12.0 4 [121,] 12.1 16 [122,] 12.2 11 [123,] 12.3 19 [124,] 12.4 18 [125,] 12.5 3 [126,] 12.6 13 [127,] 12.7 15 [128,] 12.8 4 [129,] 12.9 13 [130,] 13.0 0 [131,] 13.1 10 [132,] 13.2 13 [133,] 13.3 12 [134,] 13.4 9 [135,] 13.5 12 [136,] 13.6 8 [137,] 13.7 10 [138,] 13.8 14 [139,] 13.9 14 [140,] 14.0 15 [141,] 14.1 12 [142,] 14.2 7 [143,] 14.3 14 [144,] 14.4 8 [145,] 14.5 22 [146,] 14.6 12 [147,] 14.7 14 [148,] 14.8 19 [149,] 14.9 13 [150,] 15.0 9 [151,] 15.1 19 [152,] 15.2 13 [153,] 15.3 14 [154,] 15.4 23 [155,] 15.5 15 [156,] 15.6 10 [157,] 15.7 15 [158,] 15.8 20 [159,] 15.9 19 [160,] 16.0 11 [161,] 16.1 11 [162,] 16.2 7 [163,] 16.3 9 [164,] 16.4 0 [165,] 16.5 10 [166,] 16.6 10 [167,] 16.7 8 [168,] 16.8 14 [169,] 16.9 10 [170,] 17.0 7 [171,] 17.1 10 [172,] 17.2 8 [173,] 17.3 9 [174,] 17.4 9 [175,] 17.5 10 [176,] 17.6 22 [177,] 17.7 14 [178,] 17.8 11 [179,] 17.9 17 [180,] 18.0 14 [181,] 18.1 8 [182,] 18.2 8 [183,] 18.3 15 [184,] 18.4 9 [185,] 18.5 13 [186,] 18.6 10 [187,] 18.7 12 [188,] 18.8 9 [189,] 18.9 20 [190,] 19.0 10 [191,] 19.1 9 [192,] 19.2 7 [193,] 19.3 8 [194,] 19.4 23 [195,] 19.5 16 [196,] 19.6 17 [197,] 19.7 11 [198,] 19.8 13 [199,] 19.9 17 [200,] 20.0 24 [201,] 20.1 14 [202,] 20.2 19 [203,] 20.3 11 [204,] 20.4 9 [205,] 20.5 13 [206,] 20.6 23 [207,] 20.7 10 [208,] 20.8 12 [209,] 20.9 22 [210,] 21.0 5 [211,] 21.1 11 [212,] 21.2 16 [213,] 21.3 17 [214,] 21.4 11 [215,] 21.5 16 [216,] 21.6 11 [217,] 21.7 9 [218,] 21.8 13 [219,] 21.9 12 [220,] 22.0 7 [221,] 22.1 13 [222,] 22.2 14 [223,] 22.3 21 [224,] 22.4 8 [225,] 22.5 4 [226,] 22.6 17 [227,] 22.7 19 [228,] 22.8 8 [229,] 22.9 13 [230,] 23.0 14 [231,] 23.1 11 [232,] 23.2 14 [233,] 23.3 15 [234,] 23.4 13 [235,] 23.5 15 [236,] 23.6 9 [237,] 23.7 17 [238,] 23.8 10 [239,] 23.9 16 [240,] 24.0 8 [241,] 24.1 8 [242,] 24.2 17 [243,] 24.3 8 [244,] 24.4 7 [245,] 24.5 19 [246,] 24.6 14 [247,] 24.7 17 [248,] 24.8 7 [249,] 24.9 14 [250,] 25.0 12 [251,] 25.1 11 [252,] 25.2 11 [253,] 25.3 15 [254,] 25.4 11 [255,] 25.5 18 [256,] 25.6 21 [257,] 25.7 13 [258,] 25.8 11 [259,] 25.9 13 [260,] 26.0 14 [261,] 26.1 10 [262,] 26.2 19 [263,] 26.3 13 [264,] 26.4 9 [265,] 26.5 8 [266,] 26.6 7 [267,] 26.7 19 [268,] 26.8 19 [269,] 26.9 10 [270,] 27.0 25 [271,] 27.1 13 [272,] 27.2 12 [273,] 27.3 8 [274,] 27.4 14 [275,] 27.5 18 [276,] 27.6 19 [277,] 27.7 6 [278,] 27.8 11 [279,] 27.9 9 [280,] 28.0 22 [281,] 28.1 18 [282,] 28.2 11 [283,] 28.3 14 [284,] 28.4 20 [285,] 28.5 12 [286,] 28.6 17 [287,] 28.7 9 [288,] 28.8 0 [289,] 28.9 9 [290,] 29.0 7 [291,] 29.1 5 [292,] 29.2 8 [293,] 29.3 11 [294,] 29.4 21 [295,] 29.5 35 [296,] 29.6 9 [297,] 29.7 12 [298,] 29.8 20 [299,] 29.9 10 [300,] 30.0 16 [301,] 30.1 13 [302,] 30.2 9 [303,] 30.3 14 [304,] 30.4 10 [305,] 30.5 13 [306,] 30.6 15 [307,] 30.7 0 [308,] 30.8 8 [309,] 30.9 6 [310,] 31.0 14 [311,] 31.1 19 [312,] 31.2 27 [313,] 31.3 12 [314,] 31.4 15 [315,] 31.5 8 [316,] 31.6 11 [317,] 31.7 13 [318,] 31.8 11 [319,] 31.9 7 [320,] 32.0 13 [321,] 32.1 15 [322,] 32.2 7 [323,] 32.3 16 [324,] 32.4 5 [325,] 32.5 7 [326,] 32.6 11 [327,] 32.7 15 [328,] 32.8 10 [329,] 32.9 9 [330,] 33.0 15 [331,] 33.1 14 [332,] 33.2 13 [333,] 33.3 8 [334,] 33.4 22 [335,] 33.5 15 [336,] 33.6 16 [337,] 33.7 11 [338,] 33.8 15 [339,] 33.9 7 [340,] 34.0 2 [341,] 34.1 9 [342,] 34.2 14 [343,] 34.3 10 [344,] 34.4 12 [345,] 34.5 12 [346,] 34.6 9 [347,] 34.7 16 [348,] 34.8 12 [349,] 34.9 15 [350,] 35.0 16 [351,] 35.1 13 [352,] 35.2 16 [353,] 35.3 15 [354,] 35.4 16 [355,] 35.5 8 [356,] 35.6 12 [357,] 35.7 17 [358,] 35.8 18 [359,] 35.9 9 [360,] 36.0 8 [361,] 36.1 16 [362,] 36.2 17 [363,] 36.3 19 [364,] 36.4 9 [365,] 36.5 6 [366,] 36.6 15 [367,] 36.7 4 [368,] 36.8 16 [369,] 36.9 6 [370,] 37.0 9 [371,] 37.1 8 [372,] 37.2 9 [373,] 37.3 10 [374,] 37.4 12 [375,] 37.5 18 [376,] 37.6 10 [377,] 37.7 11 [378,] 37.8 11 [379,] 37.9 16 [380,] 38.0 15 [381,] 38.1 9 [382,] 38.2 11 [383,] 38.3 11 [384,] 38.4 14 [385,] 38.5 9 [386,] 38.6 13 [387,] 38.7 9 [388,] 38.8 10 [389,] 38.9 14 [390,] 39.0 7 [391,] 39.1 10 [392,] 39.2 14 [393,] 39.3 20 [394,] 39.4 11 [395,] 39.5 14 [396,] 39.6 8 [397,] 39.7 14 [398,] 39.8 9 [399,] 39.9 9 [400,] 40.0 7 [401,] 40.1 21 [402,] 40.2 16 [403,] 40.3 11 [404,] 40.4 19 [405,] 40.5 14 [406,] 40.6 6 [407,] 40.7 11 [408,] 40.8 11 [409,] 40.9 7 [410,] 41.0 17 [411,] 41.1 14 [412,] 41.2 16 [413,] 41.3 8 [414,] 41.4 8 [415,] 41.5 14 [416,] 41.6 15 [417,] 41.7 9 [418,] 41.8 7 [419,] 41.9 11 [420,] 42.0 11 [421,] 42.1 7 [422,] 42.2 0 [423,] 42.3 10 [424,] 42.4 10 [425,] 42.5 15 [426,] 42.6 11 [427,] 42.7 15 [428,] 42.8 9 [429,] 42.9 12 [430,] 43.0 14 [431,] 43.1 7 [432,] 43.2 6 [433,] 43.3 15 [434,] 43.4 11 [435,] 43.5 11 [436,] 43.6 9 [437,] 43.7 4 [438,] 43.8 5 [439,] 43.9 11 [440,] 44.0 13 [441,] 44.1 10 [442,] 44.2 11 [443,] 44.3 14 [444,] 44.4 10 [445,] 44.5 13 [446,] 44.6 10 [447,] 44.7 11 [448,] 44.8 5 [449,] 44.9 12 [450,] 45.0 15 [451,] 45.1 12 [452,] 45.2 7 [453,] 45.3 15 [454,] 45.4 15 [455,] 45.5 15 [456,] 45.6 21 [457,] 45.7 22 [458,] 45.8 9 [459,] 45.9 11 [460,] 46.0 15 [461,] 46.1 10 [462,] 46.2 16 [463,] 46.3 13 [464,] 46.4 9 [465,] 46.5 12 [466,] 46.6 5 [467,] 46.7 9 [468,] 46.8 12 [469,] 46.9 6 [470,] 47.0 12 [471,] 47.1 17 [472,] 47.2 15 [473,] 47.3 11 [474,] 47.4 6 [475,] 47.5 15 [476,] 47.6 8 [477,] 47.7 4 [478,] 47.8 13 [479,] 47.9 20 [480,] 48.0 11 [481,] 48.1 11 [482,] 48.2 9 [483,] 48.3 8 [484,] 48.4 11 [485,] 48.5 20 [486,] 48.6 10 [487,] 48.7 11 [488,] 48.8 10 [489,] 48.9 13 [490,] 49.0 19 [491,] 49.1 16 [492,] 49.2 17 [493,] 49.3 10 [494,] 49.4 16 [495,] 49.5 13 [496,] 49.6 9 [497,] 49.7 15 [498,] 49.8 14 [499,] 49.9 8 [500,] 50.0 11 [501,] 50.1 15 [502,] 50.2 13 [503,] 50.3 21 [504,] 50.4 9 [505,] 50.5 15 [506,] 50.6 15 [507,] 50.7 8 [508,] 50.8 13 [509,] 50.9 11 [510,] 51.0 13 [511,] 51.1 11 [512,] 51.2 15 [513,] 51.3 11 [514,] 51.4 14 [515,] 51.5 15 [516,] 51.6 10 [517,] 51.7 25 [518,] 51.8 13 [519,] 51.9 14 [520,] 52.0 14 [521,] 52.1 14 [522,] 52.2 14 [523,] 52.3 4 [524,] 52.4 13 [525,] 52.5 10 [526,] 52.6 19 [527,] 52.7 12 [528,] 52.8 8 [529,] 52.9 11 [530,] 53.0 9 [531,] 53.1 10 [532,] 53.2 10 [533,] 53.3 10 [534,] 53.4 8 [535,] 53.5 10 [536,] 53.6 12 [537,] 53.7 10 [538,] 53.8 12 [539,] 53.9 18 [540,] 54.0 13 [541,] 54.1 12 [542,] 54.2 8 [543,] 54.3 11 [544,] 54.4 8 [545,] 54.5 11 [546,] 54.6 8 [547,] 54.7 15 [548,] 54.8 18 [549,] 54.9 8 [550,] 55.0 16 [551,] 55.1 8 [552,] 55.2 15 [553,] 55.3 16 [554,] 55.4 17 [555,] 55.5 6 [556,] 55.6 14 [557,] 55.7 20 [558,] 55.8 13 [559,] 55.9 9 [560,] 56.0 13 [561,] 56.1 9 [562,] 56.2 10 [563,] 56.3 8 [564,] 56.4 16 [565,] 56.5 11 [566,] 56.6 4 [567,] 56.7 6 [568,] 56.8 16 [569,] 56.9 18 [570,] 57.0 14 [571,] 57.1 15 [572,] 57.2 5 [573,] 57.3 6 [574,] 57.4 15 [575,] 57.5 16 [576,] 57.6 16 [577,] 57.7 6 [578,] 57.8 6 [579,] 57.9 5 [580,] 58.0 17 [581,] 58.1 7 [582,] 58.2 12 [583,] 58.3 21 [584,] 58.4 22 [585,] 58.5 12 [586,] 58.6 12 [587,] 58.7 15 [588,] 58.8 15 [589,] 58.9 17 [590,] 59.0 15 [591,] 59.1 14 [592,] 59.2 8 [593,] 59.3 12 [594,] 59.4 8 [595,] 59.5 9 [596,] 59.6 16 [597,] 59.7 14 [598,] 59.8 9 [599,] 59.9 19 [600,] 60.0 11 [601,] 60.1 26 [602,] 60.2 25 [603,] 60.3 12 [604,] 60.4 6 [605,] 60.5 20 [606,] 60.6 16 [607,] 60.7 6 [608,] 60.8 15 [609,] 60.9 0 [610,] 61.0 16 [611,] 61.1 7 [612,] 61.2 13 [613,] 61.3 18 [614,] 61.4 14 [615,] 61.5 30 [616,] 61.6 11 [617,] 61.7 19 [618,] 61.8 11 [619,] 61.9 21 [620,] 62.0 11 [621,] 62.1 10 [622,] 62.2 15 [623,] 62.3 7 [624,] 62.4 13 [625,] 62.5 12 [626,] 62.6 13 [627,] 62.7 15 [628,] 62.8 6 [629,] 62.9 15 [630,] 63.0 15 [631,] 63.1 17 [632,] 63.2 12 [633,] 63.3 12 [634,] 63.4 10 [635,] 63.5 14 [636,] 63.6 12 [637,] 63.7 9 [638,] 63.8 17 [639,] 63.9 22 [640,] 64.0 12 [641,] 64.1 10 [642,] 64.2 18 [643,] 64.3 27 [644,] 64.4 14 [645,] 64.5 18 [646,] 64.6 21 [647,] 64.7 18 [648,] 64.8 21 [649,] 64.9 21 [650,] 65.0 17 [651,] 65.1 16 [652,] 65.2 27 [653,] 65.3 29 [654,] 65.4 19 [655,] 65.5 23 [656,] 65.6 12 [657,] 65.7 17 [658,] 65.8 13 [659,] 65.9 18 [660,] 66.0 20 [661,] 66.1 19 [662,] 66.2 19 [663,] 66.3 22 [664,] 66.4 16 [665,] 66.5 16 [666,] 66.6 21 [667,] 66.7 13 [668,] 66.8 24 [669,] 66.9 25 [670,] 67.0 18 [671,] 67.1 22 [672,] 67.2 21 [673,] 67.3 23 [674,] 67.4 23 [675,] 67.5 19 [676,] 67.6 25 [677,] 67.7 15 [678,] 67.8 17 [679,] 67.9 19 [680,] 68.0 16 [681,] 68.1 22 [682,] 68.2 24 [683,] 68.3 26 [684,] 68.4 12 [685,] 68.5 26 [686,] 68.6 21 [687,] 68.7 19 [688,] 68.8 26 [689,] 68.9 15 [690,] 69.0 16 [691,] 69.1 24 [692,] 69.2 28 [693,] 69.3 16 [694,] 69.4 27 [695,] 69.5 30 [696,] 69.6 23 [697,] 69.7 28 [698,] 69.8 24 [699,] 69.9 28 [700,] 70.0 25 [701,] 70.1 31 [702,] 70.2 18 [703,] 70.3 16 [704,] 70.4 23 [705,] 70.5 13 [706,] 70.6 24 [707,] 70.7 17 [708,] 70.8 17 [709,] 70.9 38 [710,] 71.0 18 [711,] 71.1 42 [712,] 71.2 13 [713,] 71.3 18 [714,] 71.4 24 [715,] 71.5 31 [716,] 71.6 29 [717,] 71.7 31 [718,] 71.8 22 [719,] 71.9 33 [720,] 72.0 29 [721,] 72.1 24 [722,] 72.2 33 [723,] 72.3 28 [724,] 72.4 33 [725,] 72.5 39 [726,] 72.6 24 [727,] 72.7 34 [728,] 72.8 29 [729,] 72.9 25 [730,] 73.0 22 [731,] 73.1 24 [732,] 73.2 23 [733,] 73.3 30 [734,] 73.4 24 [735,] 73.5 52 [736,] 73.6 27 [737,] 73.7 29 [738,] 73.8 32 [739,] 73.9 35 [740,] 74.0 35 [741,] 74.1 30 [742,] 74.2 35 [743,] 74.3 41 [744,] 74.4 28 [745,] 74.5 40 [746,] 74.6 37 [747,] 74.7 35 [748,] 74.8 30 [749,] 74.9 31 [750,] 75.0 49 [751,] 75.1 35 [752,] 75.2 38 [753,] 75.3 26 [754,] 75.4 31 [755,] 75.5 23 [756,] 75.6 39 [757,] 75.7 30 [758,] 75.8 24 [759,] 75.9 39 [760,] 76.0 29 [761,] 76.1 31 [762,] 76.2 35 [763,] 76.3 42 [764,] 76.4 51 [765,] 76.5 38 [766,] 76.6 33 [767,] 76.7 42 [768,] 76.8 37 [769,] 76.9 39 [770,] 77.0 30 [771,] 77.1 46 [772,] 77.2 39 [773,] 77.3 46 [774,] 77.4 45 [775,] 77.5 40 [776,] 77.6 36 [777,] 77.7 34 [778,] 77.8 48 [779,] 77.9 42 [780,] 78.0 47 [781,] 78.1 36 [782,] 78.2 57 [783,] 78.3 50 [784,] 78.4 32 [785,] 78.5 41 [786,] 78.6 44 [787,] 78.7 39 [788,] 78.8 37 [789,] 78.9 47 [790,] 79.0 45 [791,] 79.1 52 [792,] 79.2 45 [793,] 79.3 60 [794,] 79.4 46 [795,] 79.5 44 [796,] 79.6 36 [797,] 79.7 43 [798,] 79.8 54 [799,] 79.9 41 [800,] 80.0 58 [801,] 80.1 47 [802,] 80.2 53 [803,] 80.3 40 [804,] 80.4 52 [805,] 80.5 47 [806,] 80.6 35 [807,] 80.7 58 [808,] 80.8 38 [809,] 80.9 44 [810,] 81.0 46 [811,] 81.1 51 [812,] 81.2 54 [813,] 81.3 52 [814,] 81.4 59 [815,] 81.5 61 [816,] 81.6 43 [817,] 81.7 50 [818,] 81.8 48 [819,] 81.9 57 [820,] 82.0 48 [821,] 82.1 51 [822,] 82.2 63 [823,] 82.3 48 [824,] 82.4 45 [825,] 82.5 60 [826,] 82.6 59 [827,] 82.7 51 [828,] 82.8 56 [829,] 82.9 54 [830,] 83.0 60 [831,] 83.1 70 [832,] 83.2 61 [833,] 83.3 63 [834,] 83.4 49 [835,] 83.5 55 [836,] 83.6 59 [837,] 83.7 51 [838,] 83.8 58 [839,] 83.9 62 [840,] 84.0 50 [841,] 84.1 59 [842,] 84.2 55 [843,] 84.3 53 [844,] 84.4 58 [845,] 84.5 73 [846,] 84.6 70 [847,] 84.7 59 [848,] 84.8 61 [849,] 84.9 46 [850,] 85.0 75 [851,] 85.1 58 [852,] 85.2 60 [853,] 85.3 61 [854,] 85.4 60 [855,] 85.5 62 [856,] 85.6 62 [857,] 85.7 47 [858,] 85.8 54 [859,] 85.9 49 [860,] 86.0 60 [861,] 86.1 69 [862,] 86.2 64 [863,] 86.3 58 [864,] 86.4 61 [865,] 86.5 65 [866,] 86.6 72 [867,] 86.7 62 [868,] 86.8 65 [869,] 86.9 62 [870,] 87.0 57 [871,] 87.1 57 [872,] 87.2 69 [873,] 87.3 70 [874,] 87.4 71 [875,] 87.5 53 [876,] 87.6 57 [877,] 87.7 57 [878,] 87.8 57 [879,] 87.9 82 [880,] 88.0 58 [881,] 88.1 54 [882,] 88.2 62 [883,] 88.3 64 [884,] 88.4 65 [885,] 88.5 52 [886,] 88.6 55 [887,] 88.7 46 [888,] 88.8 66 [889,] 88.9 60 [890,] 89.0 61 [891,] 89.1 49 [892,] 89.2 68 [893,] 89.3 57 [894,] 89.4 67 [895,] 89.5 60 [896,] 89.6 70 [897,] 89.7 54 [898,] 89.8 57 [899,] 89.9 71 [900,] 90.0 60 [901,] 90.1 58 [902,] 90.2 45 [903,] 90.3 45 [904,] 90.4 53 [905,] 90.5 49 [906,] 90.6 66 [907,] 90.7 50 [908,] 90.8 58 [909,] 90.9 43 [910,] 91.0 63 [911,] 91.1 42 [912,] 91.2 70 [913,] 91.3 52 [914,] 91.4 48 [915,] 91.5 60 [916,] 91.6 53 [917,] 91.7 52 [918,] 91.8 50 [919,] 91.9 56 [920,] 92.0 42 [921,] 92.1 53 [922,] 92.2 54 [923,] 92.3 35 [924,] 92.4 57 [925,] 92.5 46 [926,] 92.6 53 [927,] 92.7 50 [928,] 92.8 44 [929,] 92.9 61 [930,] 93.0 65 [931,] 93.1 50 [932,] 93.2 50 [933,] 93.3 39 [934,] 93.4 41 [935,] 93.5 49 [936,] 93.6 43 [937,] 93.7 48 [938,] 93.8 51 [939,] 93.9 56 [940,] 94.0 51 [941,] 94.1 42 [942,] 94.2 46 [943,] 94.3 64 [944,] 94.4 49 [945,] 94.5 49 [946,] 94.6 39 [947,] 94.7 54 [948,] 94.8 41 [949,] 94.9 49 [950,] 95.0 39 [951,] 95.1 46 [952,] 95.2 38 [953,] 95.3 36 [954,] 95.4 36 [955,] 95.5 38 [956,] 95.6 59 [957,] 95.7 34 [958,] 95.8 42 [959,] 95.9 38 [960,] 96.0 40 [961,] 96.1 34 [962,] 96.2 46 [963,] 96.3 37 [964,] 96.4 35 [965,] 96.5 44 [966,] 96.6 34 [967,] 96.7 30 [968,] 96.8 44 [969,] 96.9 32 [970,] 97.0 23 [971,] 97.1 34 [972,] 97.2 45 [973,] 97.3 27 [974,] 97.4 31 [975,] 97.5 33 [976,] 97.6 39 [977,] 97.7 27 [978,] 97.8 32 [979,] 97.9 42 [980,] 98.0 44 [981,] 98.1 37 [982,] 98.2 24 [983,] 98.3 35 [984,] 98.4 39 [985,] 98.5 27 [986,] 98.6 26 [987,] 98.7 34 [988,] 98.8 25 [989,] 98.9 35 [990,] 99.0 27 [991,] 99.1 34 [992,] 99.2 34 [993,] 99.3 33 [994,] 99.4 32 [995,] 99.5 30 [996,] 99.6 35 [997,] 99.7 44 [998,] 99.8 20 [999,] 99.9 30 [1000,] 100.0 27 [1001,] 100.1 30 [1002,] 100.2 30 [1003,] 100.3 25 [1004,] 100.4 25 [1005,] 100.5 32 [1006,] 100.6 38 [1007,] 100.7 27 [1008,] 100.8 36 [1009,] 100.9 27 [1010,] 101.0 37 [1011,] 101.1 27 [1012,] 101.2 27 [1013,] 101.3 29 [1014,] 101.4 46 [1015,] 101.5 26 [1016,] 101.6 13 [1017,] 101.7 44 [1018,] 101.8 34 [1019,] 101.9 29 [1020,] 102.0 41 [1021,] 102.1 36 [1022,] 102.2 24 [1023,] 102.3 21 [1024,] 102.4 26 [1025,] 102.5 28 [1026,] 102.6 29 [1027,] 102.7 40 [1028,] 102.8 27 [1029,] 102.9 22 [1030,] 103.0 25 [1031,] 103.1 31 [1032,] 103.2 23 [1033,] 103.3 24 [1034,] 103.4 28 [1035,] 103.5 27 [1036,] 103.6 29 [1037,] 103.7 33 [1038,] 103.8 32 [1039,] 103.9 20 [1040,] 104.0 31 [1041,] 104.1 28 [1042,] 104.2 30 [1043,] 104.3 32 [1044,] 104.4 30 [1045,] 104.5 22 [1046,] 104.6 30 [1047,] 104.7 30 [1048,] 104.8 19 [1049,] 104.9 27 [1050,] 105.0 13 [1051,] 105.1 25 [1052,] 105.2 31 [1053,] 105.3 34 [1054,] 105.4 50 [1055,] 105.5 34 [1056,] 105.6 24 [1057,] 105.7 27 [1058,] 105.8 31 [1059,] 105.9 31 [1060,] 106.0 31 [1061,] 106.1 21 [1062,] 106.2 34 [1063,] 106.3 43 [1064,] 106.4 27 [1065,] 106.5 44 [1066,] 106.6 23 [1067,] 106.7 22 [1068,] 106.8 27 [1069,] 106.9 43 [1070,] 107.0 22 [1071,] 107.1 27 [1072,] 107.2 24 [1073,] 107.3 25 [1074,] 107.4 27 [1075,] 107.5 29 [1076,] 107.6 24 [1077,] 107.7 31 [1078,] 107.8 25 [1079,] 107.9 32 [1080,] 108.0 27 [1081,] 108.1 27 [1082,] 108.2 26 [1083,] 108.3 31 [1084,] 108.4 27 [1085,] 108.5 27 [1086,] 108.6 33 [1087,] 108.7 21 [1088,] 108.8 16 [1089,] 108.9 37 [1090,] 109.0 28 [1091,] 109.1 31 [1092,] 109.2 28 [1093,] 109.3 35 [1094,] 109.4 28 [1095,] 109.5 34 [1096,] 109.6 27 [1097,] 109.7 40 [1098,] 109.8 23 [1099,] 109.9 19 [1100,] 110.0 32 [1101,] 110.1 31 [1102,] 110.2 28 [1103,] 110.3 47 [1104,] 110.4 38 [1105,] 110.5 28 [1106,] 110.6 20 [1107,] 110.7 28 [1108,] 110.8 31 [1109,] 110.9 24 [1110,] 111.0 36 [1111,] 111.1 29 [1112,] 111.2 22 [1113,] 111.3 38 [1114,] 111.4 31 [1115,] 111.5 21 [1116,] 111.6 14 [1117,] 111.7 33 [1118,] 111.8 32 [1119,] 111.9 31 [1120,] 112.0 43 [1121,] 112.1 29 [1122,] 112.2 26 [1123,] 112.3 31 [1124,] 112.4 26 [1125,] 112.5 36 [1126,] 112.6 33 [1127,] 112.7 30 [1128,] 112.8 35 [1129,] 112.9 32 [1130,] 113.0 24 [1131,] 113.1 43 [1132,] 113.2 41 [1133,] 113.3 33 [1134,] 113.4 26 [1135,] 113.5 24 [1136,] 113.6 34 [1137,] 113.7 41 [1138,] 113.8 33 [1139,] 113.9 25 [1140,] 114.0 33 [1141,] 114.1 35 [1142,] 114.2 34 [1143,] 114.3 32 [1144,] 114.4 39 [1145,] 114.5 17 [1146,] 114.6 32 [1147,] 114.7 29 [1148,] 114.8 22 [1149,] 114.9 34 [1150,] 115.0 30 [1151,] 115.1 39 [1152,] 115.2 35 [1153,] 115.3 24 [1154,] 115.4 21 [1155,] 115.5 23 [1156,] 115.6 29 [1157,] 115.7 39 [1158,] 115.8 24 [1159,] 115.9 33 [1160,] 116.0 23 [1161,] 116.1 28 [1162,] 116.2 20 [1163,] 116.3 37 [1164,] 116.4 23 [1165,] 116.5 20 [1166,] 116.6 20 [1167,] 116.7 36 [1168,] 116.8 24 [1169,] 116.9 21 [1170,] 117.0 32 [1171,] 117.1 34 [1172,] 117.2 32 [1173,] 117.3 25 [1174,] 117.4 24 [1175,] 117.5 27 [1176,] 117.6 35 [1177,] 117.7 33 [1178,] 117.8 26 [1179,] 117.9 33 [1180,] 118.0 27 $`2__TL (NA)` [,1] [,2] [1,] 0 25 [2,] 118 260 [3,] 128 260 [4,] 148 60 [5,] 268 60 $`3__TL (NA)` [,1] [,2] [1,] 0.0 26 [2,] 0.1 27 [3,] 0.2 26 [4,] 0.3 29 [5,] 0.4 29 [6,] 0.5 28 [7,] 0.6 28 [8,] 0.7 28 [9,] 0.8 27 [10,] 0.9 27 [11,] 1.0 27 [12,] 1.1 27 [13,] 1.2 27 [14,] 1.3 26 [15,] 1.4 26 [16,] 1.5 26 [17,] 1.6 26 [18,] 1.7 26 [19,] 1.8 26 [20,] 1.9 26 [21,] 2.0 26 [22,] 2.1 26 [23,] 2.2 26 [24,] 2.3 26 [25,] 2.4 26 [26,] 2.5 26 [27,] 2.6 26 [28,] 2.7 26 [29,] 2.8 27 [30,] 2.9 27 [31,] 3.0 27 [32,] 3.1 27 [33,] 3.2 27 [34,] 3.3 26 [35,] 3.4 26 [36,] 3.5 26 [37,] 3.6 27 [38,] 3.7 27 [39,] 3.8 26 [40,] 3.9 26 [41,] 4.0 26 [42,] 4.1 26 [43,] 4.2 26 [44,] 4.3 27 [45,] 4.4 27 [46,] 4.5 27 [47,] 4.6 27 [48,] 4.7 27 [49,] 4.8 26 [50,] 4.9 26 [51,] 5.0 26 [52,] 5.1 26 [53,] 5.2 27 [54,] 5.3 27 [55,] 5.4 27 [56,] 5.5 27 [57,] 5.6 27 [58,] 5.7 26 [59,] 5.8 27 [60,] 5.9 27 [61,] 6.0 27 [62,] 6.1 27 [63,] 6.2 26 [64,] 6.3 26 [65,] 6.4 27 [66,] 6.5 27 [67,] 6.6 27 [68,] 6.7 27 [69,] 6.8 28 [70,] 6.9 28 [71,] 7.0 28 [72,] 7.1 29 [73,] 7.2 29 [74,] 7.3 29 [75,] 7.4 30 [76,] 7.5 30 [77,] 7.6 31 [78,] 7.7 31 [79,] 7.8 31 [80,] 7.9 31 [81,] 8.0 32 [82,] 8.1 32 [83,] 8.2 32 [84,] 8.3 33 [85,] 8.4 33 [86,] 8.5 33 [87,] 8.6 33 [88,] 8.7 33 [89,] 8.8 34 [90,] 8.9 34 [91,] 9.0 34 [92,] 9.1 35 [93,] 9.2 35 [94,] 9.3 35 [95,] 9.4 35 [96,] 9.5 36 [97,] 9.6 36 [98,] 9.7 37 [99,] 9.8 37 [100,] 9.9 37 [101,] 10.0 37 [102,] 10.1 38 [103,] 10.2 38 [104,] 10.3 38 [105,] 10.4 39 [106,] 10.5 39 [107,] 10.6 39 [108,] 10.7 39 [109,] 10.8 40 [110,] 10.9 40 [111,] 11.0 41 [112,] 11.1 41 [113,] 11.2 41 [114,] 11.3 41 [115,] 11.4 42 [116,] 11.5 42 [117,] 11.6 42 [118,] 11.7 43 [119,] 11.8 43 [120,] 11.9 43 [121,] 12.0 43 [122,] 12.1 43 [123,] 12.2 44 [124,] 12.3 44 [125,] 12.4 44 [126,] 12.5 44 [127,] 12.6 45 [128,] 12.7 45 [129,] 12.8 45 [130,] 12.9 45 [131,] 13.0 46 [132,] 13.1 46 [133,] 13.2 47 [134,] 13.3 47 [135,] 13.4 47 [136,] 13.5 48 [137,] 13.6 48 [138,] 13.7 48 [139,] 13.8 48 [140,] 13.9 49 [141,] 14.0 49 [142,] 14.1 49 [143,] 14.2 49 [144,] 14.3 49 [145,] 14.4 49 [146,] 14.5 50 [147,] 14.6 50 [148,] 14.7 51 [149,] 14.8 51 [150,] 14.9 51 [151,] 15.0 51 [152,] 15.1 51 [153,] 15.2 51 [154,] 15.3 51 [155,] 15.4 52 [156,] 15.5 52 [157,] 15.6 52 [158,] 15.7 52 [159,] 15.8 53 [160,] 15.9 53 [161,] 16.0 54 [162,] 16.1 54 [163,] 16.2 54 [164,] 16.3 54 [165,] 16.4 55 [166,] 16.5 55 [167,] 16.6 55 [168,] 16.7 55 [169,] 16.8 55 [170,] 16.9 55 [171,] 17.0 55 [172,] 17.1 55 [173,] 17.2 55 [174,] 17.3 55 [175,] 17.4 55 [176,] 17.5 55 [177,] 17.6 55 [178,] 17.7 56 [179,] 17.8 57 [180,] 17.9 57 [181,] 18.0 58 [182,] 18.1 59 [183,] 18.2 60 [184,] 18.3 61 [185,] 18.4 62 [186,] 18.5 62 [187,] 18.6 63 [188,] 18.7 63 [189,] 18.8 63 [190,] 18.9 63 [191,] 19.0 63 [192,] 19.1 62 [193,] 19.2 62 [194,] 19.3 61 [195,] 19.4 61 [196,] 19.5 62 [197,] 19.6 62 [198,] 19.7 63 [199,] 19.8 63 [200,] 19.9 63 [201,] 20.0 63 [202,] 20.1 64 [203,] 20.2 64 [204,] 20.3 64 [205,] 20.4 64 [206,] 20.5 65 [207,] 20.6 65 [208,] 20.7 64 [209,] 20.8 64 [210,] 20.9 64 [211,] 21.0 65 [212,] 21.1 65 [213,] 21.2 65 [214,] 21.3 65 [215,] 21.4 65 [216,] 21.5 65 [217,] 21.6 66 [218,] 21.7 66 [219,] 21.8 66 [220,] 21.9 66 [221,] 22.0 67 [222,] 22.1 67 [223,] 22.2 67 [224,] 22.3 67 [225,] 22.4 68 [226,] 22.5 68 [227,] 22.6 68 [228,] 22.7 68 [229,] 22.8 68 [230,] 22.9 69 [231,] 23.0 69 [232,] 23.1 69 [233,] 23.2 69 [234,] 23.3 70 [235,] 23.4 69 [236,] 23.5 69 [237,] 23.6 70 [238,] 23.7 70 [239,] 23.8 70 [240,] 23.9 70 [241,] 24.0 71 [242,] 24.1 71 [243,] 24.2 71 [244,] 24.3 71 [245,] 24.4 72 [246,] 24.5 72 [247,] 24.6 72 [248,] 24.7 72 [249,] 24.8 72 [250,] 24.9 72 [251,] 25.0 73 [252,] 25.1 73 [253,] 25.2 73 [254,] 25.3 73 [255,] 25.4 74 [256,] 25.5 74 [257,] 25.6 74 [258,] 25.7 74 [259,] 25.8 75 [260,] 25.9 75 [261,] 26.0 75 [262,] 26.1 75 [263,] 26.2 75 [264,] 26.3 75 [265,] 26.4 76 [266,] 26.5 77 [267,] 26.6 77 [268,] 26.7 77 [269,] 26.8 77 [270,] 26.9 77 [271,] 27.0 77 [272,] 27.1 78 [273,] 27.2 78 [274,] 27.3 78 [275,] 27.4 78 [276,] 27.5 78 [277,] 27.6 79 [278,] 27.7 79 [279,] 27.8 79 [280,] 27.9 79 [281,] 28.0 79 [282,] 28.1 79 [283,] 28.2 80 [284,] 28.3 80 [285,] 28.4 80 [286,] 28.5 81 [287,] 28.6 80 [288,] 28.7 80 [289,] 28.8 81 [290,] 28.9 81 [291,] 29.0 81 [292,] 29.1 81 [293,] 29.2 81 [294,] 29.3 82 [295,] 29.4 82 [296,] 29.5 82 [297,] 29.6 83 [298,] 29.7 83 [299,] 29.8 83 [300,] 29.9 83 [301,] 30.0 83 [302,] 30.1 84 [303,] 30.2 84 [304,] 30.3 85 [305,] 30.4 86 [306,] 30.5 86 [307,] 30.6 86 [308,] 30.7 86 [309,] 30.8 86 [310,] 30.9 87 [311,] 31.0 87 [312,] 31.1 87 [313,] 31.2 87 [314,] 31.3 86 [315,] 31.4 86 [316,] 31.5 86 [317,] 31.6 87 [318,] 31.7 87 [319,] 31.8 87 [320,] 31.9 87 [321,] 32.0 88 [322,] 32.1 88 [323,] 32.2 88 [324,] 32.3 88 [325,] 32.4 89 [326,] 32.5 89 [327,] 32.6 90 [328,] 32.7 90 [329,] 32.8 90 [330,] 32.9 90 [331,] 33.0 90 [332,] 33.1 90 [333,] 33.2 90 [334,] 33.3 91 [335,] 33.4 90 [336,] 33.5 90 [337,] 33.6 90 [338,] 33.7 91 [339,] 33.8 91 [340,] 33.9 91 [341,] 34.0 91 [342,] 34.1 91 [343,] 34.2 92 [344,] 34.3 92 [345,] 34.4 92 [346,] 34.5 92 [347,] 34.6 93 [348,] 34.7 93 [349,] 34.8 93 [350,] 34.9 93 [351,] 35.0 93 [352,] 35.1 94 [353,] 35.2 94 [354,] 35.3 94 [355,] 35.4 94 [356,] 35.5 94 [357,] 35.6 94 [358,] 35.7 95 [359,] 35.8 95 [360,] 35.9 95 [361,] 36.0 95 [362,] 36.1 95 [363,] 36.2 96 [364,] 36.3 96 [365,] 36.4 96 [366,] 36.5 96 [367,] 36.6 97 [368,] 36.7 97 [369,] 36.8 97 [370,] 36.9 97 [371,] 37.0 98 [372,] 37.1 98 [373,] 37.2 97 [374,] 37.3 98 [375,] 37.4 98 [376,] 37.5 98 [377,] 37.6 99 [378,] 37.7 99 [379,] 37.8 99 [380,] 37.9 99 [381,] 38.0 99 [382,] 38.1 100 [383,] 38.2 101 [384,] 38.3 101 [385,] 38.4 101 [386,] 38.5 101 [387,] 38.6 101 [388,] 38.7 101 [389,] 38.8 101 [390,] 38.9 101 [391,] 39.0 101 [392,] 39.1 101 [393,] 39.2 102 [394,] 39.3 102 [395,] 39.4 102 [396,] 39.5 102 [397,] 39.6 102 [398,] 39.7 103 [399,] 39.8 103 [400,] 39.9 103 [401,] 40.0 103 [402,] 40.1 103 [403,] 40.2 104 [404,] 40.3 104 [405,] 40.4 104 [406,] 40.5 105 [407,] 40.6 105 [408,] 40.7 105 [409,] 40.8 105 [410,] 40.9 105 [411,] 41.0 105 [412,] 41.1 106 [413,] 41.2 106 [414,] 41.3 106 [415,] 41.4 107 [416,] 41.5 106 [417,] 41.6 107 [418,] 41.7 107 [419,] 41.8 107 [420,] 41.9 107 [421,] 42.0 108 [422,] 42.1 108 [423,] 42.2 108 [424,] 42.3 108 [425,] 42.4 108 [426,] 42.5 109 [427,] 42.6 109 [428,] 42.7 109 [429,] 42.8 109 [430,] 42.9 109 [431,] 43.0 110 [432,] 43.1 110 [433,] 43.2 110 [434,] 43.3 110 [435,] 43.4 111 [436,] 43.5 111 [437,] 43.6 111 [438,] 43.7 111 [439,] 43.8 112 [440,] 43.9 111 [441,] 44.0 111 [442,] 44.1 111 [443,] 44.2 111 [444,] 44.3 111 [445,] 44.4 111 [446,] 44.5 111 [447,] 44.6 112 [448,] 44.7 112 [449,] 44.8 112 [450,] 44.9 113 [451,] 45.0 113 [452,] 45.1 114 [453,] 45.2 114 [454,] 45.3 114 [455,] 45.4 115 [456,] 45.5 115 [457,] 45.6 115 [458,] 45.7 115 [459,] 45.8 115 [460,] 45.9 115 [461,] 46.0 115 [462,] 46.1 115 [463,] 46.2 115 [464,] 46.3 115 [465,] 46.4 115 [466,] 46.5 116 [467,] 46.6 116 [468,] 46.7 116 [469,] 46.8 116 [470,] 46.9 117 [471,] 47.0 117 [472,] 47.1 117 [473,] 47.2 118 [474,] 47.3 118 [475,] 47.4 118 [476,] 47.5 118 [477,] 47.6 118 [478,] 47.7 119 [479,] 47.8 119 [480,] 47.9 119 [481,] 48.0 119 [482,] 48.1 120 [483,] 48.2 120 [484,] 48.3 120 [485,] 48.4 120 [486,] 48.5 120 [487,] 48.6 121 [488,] 48.7 121 [489,] 48.8 121 [490,] 48.9 121 [491,] 49.0 121 [492,] 49.1 122 [493,] 49.2 122 [494,] 49.3 122 [495,] 49.4 123 [496,] 49.5 123 [497,] 49.6 123 [498,] 49.7 123 [499,] 49.8 124 [500,] 49.9 124 [501,] 50.0 124 [502,] 50.1 124 [503,] 50.2 124 [504,] 50.3 124 [505,] 50.4 125 [506,] 50.5 125 [507,] 50.6 126 [508,] 50.7 126 [509,] 50.8 126 [510,] 50.9 126 [511,] 51.0 126 [512,] 51.1 127 [513,] 51.2 127 [514,] 51.3 127 [515,] 51.4 127 [516,] 51.5 127 [517,] 51.6 127 [518,] 51.7 127 [519,] 51.8 127 [520,] 51.9 128 [521,] 52.0 128 [522,] 52.1 128 [523,] 52.2 128 [524,] 52.3 128 [525,] 52.4 129 [526,] 52.5 129 [527,] 52.6 129 [528,] 52.7 129 [529,] 52.8 129 [530,] 52.9 129 [531,] 53.0 129 [532,] 53.1 129 [533,] 53.2 130 [534,] 53.3 130 [535,] 53.4 130 [536,] 53.5 130 [537,] 53.6 131 [538,] 53.7 131 [539,] 53.8 131 [540,] 53.9 131 [541,] 54.0 131 [542,] 54.1 131 [543,] 54.2 132 [544,] 54.3 132 [545,] 54.4 132 [546,] 54.5 132 [547,] 54.6 132 [548,] 54.7 133 [549,] 54.8 133 [550,] 54.9 133 [551,] 55.0 133 [552,] 55.1 133 [553,] 55.2 134 [554,] 55.3 134 [555,] 55.4 134 [556,] 55.5 134 [557,] 55.6 135 [558,] 55.7 135 [559,] 55.8 135 [560,] 55.9 135 [561,] 56.0 135 [562,] 56.1 136 [563,] 56.2 136 [564,] 56.3 136 [565,] 56.4 137 [566,] 56.5 137 [567,] 56.6 137 [568,] 56.7 137 [569,] 56.8 137 [570,] 56.9 137 [571,] 57.0 138 [572,] 57.1 137 [573,] 57.2 138 [574,] 57.3 138 [575,] 57.4 138 [576,] 57.5 138 [577,] 57.6 139 [578,] 57.7 139 [579,] 57.8 139 [580,] 57.9 140 [581,] 58.0 140 [582,] 58.1 140 [583,] 58.2 140 [584,] 58.3 141 [585,] 58.4 141 [586,] 58.5 141 [587,] 58.6 141 [588,] 58.7 141 [589,] 58.8 141 [590,] 58.9 141 [591,] 59.0 141 [592,] 59.1 141 [593,] 59.2 142 [594,] 59.3 142 [595,] 59.4 142 [596,] 59.5 142 [597,] 59.6 143 [598,] 59.7 143 [599,] 59.8 143 [600,] 59.9 143 [601,] 60.0 143 [602,] 60.1 144 [603,] 60.2 144 [604,] 60.3 144 [605,] 60.4 144 [606,] 60.5 144 [607,] 60.6 144 [608,] 60.7 144 [609,] 60.8 144 [610,] 60.9 145 [611,] 61.0 145 [612,] 61.1 146 [613,] 61.2 146 [614,] 61.3 147 [615,] 61.4 147 [616,] 61.5 148 [617,] 61.6 148 [618,] 61.7 148 [619,] 61.8 149 [620,] 61.9 149 [621,] 62.0 149 [622,] 62.1 149 [623,] 62.2 149 [624,] 62.3 149 [625,] 62.4 149 [626,] 62.5 149 [627,] 62.6 149 [628,] 62.7 149 [629,] 62.8 149 [630,] 62.9 149 [631,] 63.0 149 [632,] 63.1 149 [633,] 63.2 150 [634,] 63.3 151 [635,] 63.4 151 [636,] 63.5 151 [637,] 63.6 151 [638,] 63.7 151 [639,] 63.8 152 [640,] 63.9 152 [641,] 64.0 152 [642,] 64.1 153 [643,] 64.2 153 [644,] 64.3 153 [645,] 64.4 154 [646,] 64.5 154 [647,] 64.6 154 [648,] 64.7 154 [649,] 64.8 154 [650,] 64.9 154 [651,] 65.0 154 [652,] 65.1 154 [653,] 65.2 154 [654,] 65.3 154 [655,] 65.4 154 [656,] 65.5 154 [657,] 65.6 155 [658,] 65.7 155 [659,] 65.8 155 [660,] 65.9 155 [661,] 66.0 156 [662,] 66.1 156 [663,] 66.2 156 [664,] 66.3 156 [665,] 66.4 156 [666,] 66.5 157 [667,] 66.6 157 [668,] 66.7 157 [669,] 66.8 157 [670,] 66.9 157 [671,] 67.0 157 [672,] 67.1 157 [673,] 67.2 157 [674,] 67.3 157 [675,] 67.4 157 [676,] 67.5 158 [677,] 67.6 158 [678,] 67.7 159 [679,] 67.8 159 [680,] 67.9 159 [681,] 68.0 159 [682,] 68.1 159 [683,] 68.2 160 [684,] 68.3 160 [685,] 68.4 160 [686,] 68.5 160 [687,] 68.6 161 [688,] 68.7 160 [689,] 68.8 160 [690,] 68.9 160 [691,] 69.0 160 [692,] 69.1 161 [693,] 69.2 161 [694,] 69.3 161 [695,] 69.4 162 [696,] 69.5 162 [697,] 69.6 162 [698,] 69.7 162 [699,] 69.8 163 [700,] 69.9 163 [701,] 70.0 163 [702,] 70.1 163 [703,] 70.2 164 [704,] 70.3 164 [705,] 70.4 164 [706,] 70.5 164 [707,] 70.6 165 [708,] 70.7 165 [709,] 70.8 165 [710,] 70.9 165 [711,] 71.0 165 [712,] 71.1 166 [713,] 71.2 166 [714,] 71.3 166 [715,] 71.4 166 [716,] 71.5 167 [717,] 71.6 167 [718,] 71.7 167 [719,] 71.8 167 [720,] 71.9 167 [721,] 72.0 167 [722,] 72.1 167 [723,] 72.2 168 [724,] 72.3 168 [725,] 72.4 168 [726,] 72.5 168 [727,] 72.6 168 [728,] 72.7 169 [729,] 72.8 169 [730,] 72.9 169 [731,] 73.0 169 [732,] 73.1 169 [733,] 73.2 170 [734,] 73.3 170 [735,] 73.4 170 [736,] 73.5 170 [737,] 73.6 170 [738,] 73.7 171 [739,] 73.8 171 [740,] 73.9 171 [741,] 74.0 171 [742,] 74.1 171 [743,] 74.2 171 [744,] 74.3 172 [745,] 74.4 172 [746,] 74.5 172 [747,] 74.6 173 [748,] 74.7 173 [749,] 74.8 173 [750,] 74.9 173 [751,] 75.0 174 [752,] 75.1 174 [753,] 75.2 174 [754,] 75.3 174 [755,] 75.4 174 [756,] 75.5 174 [757,] 75.6 175 [758,] 75.7 175 [759,] 75.8 175 [760,] 75.9 175 [761,] 76.0 175 [762,] 76.1 176 [763,] 76.2 176 [764,] 76.3 176 [765,] 76.4 176 [766,] 76.5 177 [767,] 76.6 177 [768,] 76.7 177 [769,] 76.8 177 [770,] 76.9 178 [771,] 77.0 178 [772,] 77.1 178 [773,] 77.2 178 [774,] 77.3 178 [775,] 77.4 178 [776,] 77.5 178 [777,] 77.6 180 [778,] 77.7 180 [779,] 77.8 180 [780,] 77.9 180 [781,] 78.0 181 [782,] 78.1 181 [783,] 78.2 181 [784,] 78.3 181 [785,] 78.4 181 [786,] 78.5 182 [787,] 78.6 180 [788,] 78.7 180 [789,] 78.8 181 [790,] 78.9 181 [791,] 79.0 181 [792,] 79.1 181 [793,] 79.2 181 [794,] 79.3 182 [795,] 79.4 182 [796,] 79.5 182 [797,] 79.6 182 [798,] 79.7 182 [799,] 79.8 183 [800,] 79.9 183 [801,] 80.0 183 [802,] 80.1 183 [803,] 80.2 183 [804,] 80.3 183 [805,] 80.4 184 [806,] 80.5 184 [807,] 80.6 184 [808,] 80.7 184 [809,] 80.8 185 [810,] 80.9 185 [811,] 81.0 185 [812,] 81.1 185 [813,] 81.2 186 [814,] 81.3 186 [815,] 81.4 186 [816,] 81.5 187 [817,] 81.6 187 [818,] 81.7 187 [819,] 81.8 187 [820,] 81.9 187 [821,] 82.0 187 [822,] 82.1 188 [823,] 82.2 188 [824,] 82.3 188 [825,] 82.4 188 [826,] 82.5 188 [827,] 82.6 188 [828,] 82.7 188 [829,] 82.8 188 [830,] 82.9 189 [831,] 83.0 189 [832,] 83.1 189 [833,] 83.2 189 [834,] 83.3 189 [835,] 83.4 190 [836,] 83.5 190 [837,] 83.6 190 [838,] 83.7 190 [839,] 83.8 191 [840,] 83.9 191 [841,] 84.0 191 [842,] 84.1 191 [843,] 84.2 192 [844,] 84.3 192 [845,] 84.4 192 [846,] 84.5 193 [847,] 84.6 193 [848,] 84.7 193 [849,] 84.8 193 [850,] 84.9 193 [851,] 85.0 193 [852,] 85.1 194 [853,] 85.2 194 [854,] 85.3 194 [855,] 85.4 194 [856,] 85.5 194 [857,] 85.6 194 [858,] 85.7 195 [859,] 85.8 195 [860,] 85.9 195 [861,] 86.0 195 [862,] 86.1 196 [863,] 86.2 196 [864,] 86.3 196 [865,] 86.4 196 [866,] 86.5 197 [867,] 86.6 197 [868,] 86.7 197 [869,] 86.8 197 [870,] 86.9 198 [871,] 87.0 198 [872,] 87.1 198 [873,] 87.2 198 [874,] 87.3 198 [875,] 87.4 199 [876,] 87.5 199 [877,] 87.6 199 [878,] 87.7 199 [879,] 87.8 199 [880,] 87.9 199 [881,] 88.0 198 [882,] 88.1 198 [883,] 88.2 199 [884,] 88.3 199 [885,] 88.4 199 [886,] 88.5 199 [887,] 88.6 200 [888,] 88.7 200 [889,] 88.8 200 [890,] 88.9 201 [891,] 89.0 201 [892,] 89.1 201 [893,] 89.2 201 [894,] 89.3 202 [895,] 89.4 202 [896,] 89.5 203 [897,] 89.6 203 [898,] 89.7 203 [899,] 89.8 203 [900,] 89.9 203 [901,] 90.0 203 [902,] 90.1 203 [903,] 90.2 203 [904,] 90.3 204 [905,] 90.4 204 [906,] 90.5 204 [907,] 90.6 205 [908,] 90.7 205 [909,] 90.8 205 [910,] 90.9 206 [911,] 91.0 206 [912,] 91.1 206 [913,] 91.2 207 [914,] 91.3 207 [915,] 91.4 207 [916,] 91.5 207 [917,] 91.6 207 [918,] 91.7 207 [919,] 91.8 207 [920,] 91.9 208 [921,] 92.0 208 [922,] 92.1 208 [923,] 92.2 208 [924,] 92.3 208 [925,] 92.4 208 [926,] 92.5 208 [927,] 92.6 208 [928,] 92.7 208 [929,] 92.8 209 [930,] 92.9 209 [931,] 93.0 209 [932,] 93.1 209 [933,] 93.2 209 [934,] 93.3 209 [935,] 93.4 210 [936,] 93.5 210 [937,] 93.6 210 [938,] 93.7 210 [939,] 93.8 211 [940,] 93.9 211 [941,] 94.0 211 [942,] 94.1 211 [943,] 94.2 211 [944,] 94.3 212 [945,] 94.4 212 [946,] 94.5 212 [947,] 94.6 213 [948,] 94.7 213 [949,] 94.8 213 [950,] 94.9 213 [951,] 95.0 213 [952,] 95.1 214 [953,] 95.2 214 [954,] 95.3 214 [955,] 95.4 214 [956,] 95.5 214 [957,] 95.6 213 [958,] 95.7 214 [959,] 95.8 214 [960,] 95.9 214 [961,] 96.0 214 [962,] 96.1 214 [963,] 96.2 214 [964,] 96.3 214 [965,] 96.4 215 [966,] 96.5 215 [967,] 96.6 216 [968,] 96.7 216 [969,] 96.8 217 [970,] 96.9 217 [971,] 97.0 217 [972,] 97.1 217 [973,] 97.2 218 [974,] 97.3 218 [975,] 97.4 218 [976,] 97.5 218 [977,] 97.6 218 [978,] 97.7 219 [979,] 97.8 219 [980,] 97.9 219 [981,] 98.0 219 [982,] 98.1 220 [983,] 98.2 220 [984,] 98.3 220 [985,] 98.4 221 [986,] 98.5 221 [987,] 98.6 221 [988,] 98.7 221 [989,] 98.8 221 [990,] 98.9 221 [991,] 99.0 223 [992,] 99.1 222 [993,] 99.2 223 [994,] 99.3 223 [995,] 99.4 223 [996,] 99.5 223 [997,] 99.6 224 [998,] 99.7 224 [999,] 99.8 224 [1000,] 99.9 224 [1001,] 100.0 224 [1002,] 100.1 224 [1003,] 100.2 224 [1004,] 100.3 224 [1005,] 100.4 224 [1006,] 100.5 224 [1007,] 100.6 224 [1008,] 100.7 224 [1009,] 100.8 225 [1010,] 100.9 224 [1011,] 101.0 224 [1012,] 101.1 225 [1013,] 101.2 225 [1014,] 101.3 225 [1015,] 101.4 225 [1016,] 101.5 226 [1017,] 101.6 226 [1018,] 101.7 226 [1019,] 101.8 226 [1020,] 101.9 227 [1021,] 102.0 227 [1022,] 102.1 228 [1023,] 102.2 228 [1024,] 102.3 228 [1025,] 102.4 228 [1026,] 102.5 229 [1027,] 102.6 229 [1028,] 102.7 229 [1029,] 102.8 229 [1030,] 102.9 229 [1031,] 103.0 229 [1032,] 103.1 230 [1033,] 103.2 230 [1034,] 103.3 230 [1035,] 103.4 230 [1036,] 103.5 230 [1037,] 103.6 230 [1038,] 103.7 231 [1039,] 103.8 231 [1040,] 103.9 231 [1041,] 104.0 231 [1042,] 104.1 231 [1043,] 104.2 232 [1044,] 104.3 232 [1045,] 104.4 232 [1046,] 104.5 232 [1047,] 104.6 232 [1048,] 104.7 233 [1049,] 104.8 233 [1050,] 104.9 233 [1051,] 105.0 233 [1052,] 105.1 233 [1053,] 105.2 233 [1054,] 105.3 233 [1055,] 105.4 234 [1056,] 105.5 234 [1057,] 105.6 234 [1058,] 105.7 234 [1059,] 105.8 235 [1060,] 105.9 235 [1061,] 106.0 235 [1062,] 106.1 235 [1063,] 106.2 235 [1064,] 106.3 235 [1065,] 106.4 235 [1066,] 106.5 236 [1067,] 106.6 236 [1068,] 106.7 236 [1069,] 106.8 236 [1070,] 106.9 237 [1071,] 107.0 237 [1072,] 107.1 237 [1073,] 107.2 237 [1074,] 107.3 237 [1075,] 107.4 238 [1076,] 107.5 238 [1077,] 107.6 238 [1078,] 107.7 238 [1079,] 107.8 238 [1080,] 107.9 238 [1081,] 108.0 239 [1082,] 108.1 239 [1083,] 108.2 239 [1084,] 108.3 239 [1085,] 108.4 239 [1086,] 108.5 240 [1087,] 108.6 240 [1088,] 108.7 240 [1089,] 108.8 241 [1090,] 108.9 241 [1091,] 109.0 241 [1092,] 109.1 241 [1093,] 109.2 242 [1094,] 109.3 242 [1095,] 109.4 242 [1096,] 109.5 243 [1097,] 109.6 243 [1098,] 109.7 243 [1099,] 109.8 243 [1100,] 109.9 244 [1101,] 110.0 244 [1102,] 110.1 244 [1103,] 110.2 244 [1104,] 110.3 245 [1105,] 110.4 245 [1106,] 110.5 245 [1107,] 110.6 245 [1108,] 110.7 245 [1109,] 110.8 246 [1110,] 110.9 245 [1111,] 111.0 245 [1112,] 111.1 246 [1113,] 111.2 246 [1114,] 111.3 245 [1115,] 111.4 246 [1116,] 111.5 246 [1117,] 111.6 246 [1118,] 111.7 246 [1119,] 111.8 246 [1120,] 111.9 247 [1121,] 112.0 247 [1122,] 112.1 247 [1123,] 112.2 247 [1124,] 112.3 247 [1125,] 112.4 248 [1126,] 112.5 248 [1127,] 112.6 248 [1128,] 112.7 249 [1129,] 112.8 249 [1130,] 112.9 249 [1131,] 113.0 250 [1132,] 113.1 250 [1133,] 113.2 250 [1134,] 113.3 250 [1135,] 113.4 250 [1136,] 113.5 250 [1137,] 113.6 250 [1138,] 113.7 251 [1139,] 113.8 251 [1140,] 113.9 251 [1141,] 114.0 251 [1142,] 114.1 251 [1143,] 114.2 252 [1144,] 114.3 252 [1145,] 114.4 252 [1146,] 114.5 252 [1147,] 114.6 252 [1148,] 114.7 252 [1149,] 114.8 252 [1150,] 114.9 253 [1151,] 115.0 253 [1152,] 115.1 253 [1153,] 115.2 253 [1154,] 115.3 253 [1155,] 115.4 254 [1156,] 115.5 254 [1157,] 115.6 254 [1158,] 115.7 254 [1159,] 115.8 254 [1160,] 115.9 255 [1161,] 116.0 255 [1162,] 116.1 255 [1163,] 116.2 256 [1164,] 116.3 256 [1165,] 116.4 256 [1166,] 116.5 256 [1167,] 116.6 257 [1168,] 116.7 257 [1169,] 116.8 257 [1170,] 116.9 257 [1171,] 117.0 257 [1172,] 117.1 256 [1173,] 117.2 257 [1174,] 117.3 257 [1175,] 117.4 257 [1176,] 117.5 257 [1177,] 117.6 257 [1178,] 117.7 257 [1179,] 117.8 257 [1180,] 117.9 258 [1181,] 118.0 258 [1182,] 118.1 259 [1183,] 118.2 259 [1184,] 118.3 260 [1185,] 118.4 260 [1186,] 118.5 261 [1187,] 118.6 261 [1188,] 118.7 261 [1189,] 118.8 261 [1190,] 118.9 262 [1191,] 119.0 262 [1192,] 119.1 261 [1193,] 119.2 261 [1194,] 119.3 261 [1195,] 119.4 261 [1196,] 119.5 261 [1197,] 119.6 261 [1198,] 119.7 261 [1199,] 119.8 261 [1200,] 119.9 261 [1201,] 120.0 261 [1202,] 120.1 261 [1203,] 120.2 261 [1204,] 120.3 261 [1205,] 120.4 261 [1206,] 120.5 261 [1207,] 120.6 261 [1208,] 120.7 261 [1209,] 120.8 261 [1210,] 120.9 261 [1211,] 121.0 261 [1212,] 121.1 261 [1213,] 121.2 261 [1214,] 121.3 261 [1215,] 121.4 260 [1216,] 121.5 260 [1217,] 121.6 260 [1218,] 121.7 260 [1219,] 121.8 260 [1220,] 121.9 260 [1221,] 122.0 260 [1222,] 122.1 260 [1223,] 122.2 260 [1224,] 122.3 260 [1225,] 122.4 260 [1226,] 122.5 261 [1227,] 122.6 261 [1228,] 122.7 261 [1229,] 122.8 261 [1230,] 122.9 261 [1231,] 123.0 261 [1232,] 123.1 261 [1233,] 123.2 261 [1234,] 123.3 262 [1235,] 123.4 261 [1236,] 123.5 261 [1237,] 123.6 261 [1238,] 123.7 261 [1239,] 123.8 261 [1240,] 123.9 261 [1241,] 124.0 261 [1242,] 124.1 261 [1243,] 124.2 261 [1244,] 124.3 261 [1245,] 124.4 261 [1246,] 124.5 261 [1247,] 124.6 261 [1248,] 124.7 261 [1249,] 124.8 261 [1250,] 124.9 261 [1251,] 125.0 261 [1252,] 125.1 260 [1253,] 125.2 261 [1254,] 125.3 260 [1255,] 125.4 260 [1256,] 125.5 260 [1257,] 125.6 260 [1258,] 125.7 260 [1259,] 125.8 260 [1260,] 125.9 260 [1261,] 126.0 260 [1262,] 126.1 260 [1263,] 126.2 260 [1264,] 126.3 260 [1265,] 126.4 260 [1266,] 126.5 260 [1267,] 126.6 260 [1268,] 126.7 260 [1269,] 126.8 260 [1270,] 126.9 260 [1271,] 127.0 260 [1272,] 127.1 260 [1273,] 127.2 260 [1274,] 127.3 260 [1275,] 127.4 260 [1276,] 127.5 260 [1277,] 127.6 260 [1278,] 127.7 260 [1279,] 127.8 260 [1280,] 127.9 260 [1281,] 128.0 260 [1282,] 128.1 260 [1283,] 128.2 260 [1284,] 128.3 260 [1285,] 128.4 260 [1286,] 128.5 260 [1287,] 128.6 260 [1288,] 128.7 260 [1289,] 128.8 261 [1290,] 128.9 261 [1291,] 129.0 260 [1292,] 129.1 260 [1293,] 129.2 260 [1294,] 129.3 259 [1295,] 129.4 258 [1296,] 129.5 258 [1297,] 129.6 257 [1298,] 129.7 257 [1299,] 129.8 255 [1300,] 129.9 254 [1301,] 130.0 254 [1302,] 130.1 254 [1303,] 130.2 253 [1304,] 130.3 253 [1305,] 130.4 253 [1306,] 130.5 253 [1307,] 130.6 252 [1308,] 130.7 251 [1309,] 130.8 251 [1310,] 130.9 250 [1311,] 131.0 249 [1312,] 131.1 249 [1313,] 131.2 248 [1314,] 131.3 247 [1315,] 131.4 246 [1316,] 131.5 245 [1317,] 131.6 245 [1318,] 131.7 244 [1319,] 131.8 243 [1320,] 131.9 242 [1321,] 132.0 241 [1322,] 132.1 240 [1323,] 132.2 239 [1324,] 132.3 239 [1325,] 132.4 238 [1326,] 132.5 237 [1327,] 132.6 236 [1328,] 132.7 235 [1329,] 132.8 234 [1330,] 132.9 233 [1331,] 133.0 233 [1332,] 133.1 232 [1333,] 133.2 231 [1334,] 133.3 230 [1335,] 133.4 229 [1336,] 133.5 229 [1337,] 133.6 228 [1338,] 133.7 227 [1339,] 133.8 227 [1340,] 133.9 226 [1341,] 134.0 225 [1342,] 134.1 224 [1343,] 134.2 223 [1344,] 134.3 223 [1345,] 134.4 222 [1346,] 134.5 221 [1347,] 134.6 220 [1348,] 134.7 219 [1349,] 134.8 218 [1350,] 134.9 217 [1351,] 135.0 216 [1352,] 135.1 215 [1353,] 135.2 215 [1354,] 135.3 214 [1355,] 135.4 213 [1356,] 135.5 213 [1357,] 135.6 212 [1358,] 135.7 211 [1359,] 135.8 211 [1360,] 135.9 210 [1361,] 136.0 209 [1362,] 136.1 208 [1363,] 136.2 207 [1364,] 136.3 207 [1365,] 136.4 206 [1366,] 136.5 205 [1367,] 136.6 204 [1368,] 136.7 203 [1369,] 136.8 202 [1370,] 136.9 202 [1371,] 137.0 201 [1372,] 137.1 200 [1373,] 137.2 199 [1374,] 137.3 199 [1375,] 137.4 198 [1376,] 137.5 197 [1377,] 137.6 197 [1378,] 137.7 197 [1379,] 137.8 196 [1380,] 137.9 195 [1381,] 138.0 194 [1382,] 138.1 194 [1383,] 138.2 193 [1384,] 138.3 192 [1385,] 138.4 192 [1386,] 138.5 191 [1387,] 138.6 190 [1388,] 138.7 189 [1389,] 138.8 189 [1390,] 138.9 188 [1391,] 139.0 187 [1392,] 139.1 186 [1393,] 139.2 186 [1394,] 139.3 185 [1395,] 139.4 185 [1396,] 139.5 184 [1397,] 139.6 183 [1398,] 139.7 183 [1399,] 139.8 182 [1400,] 139.9 181 [1401,] 140.0 181 [1402,] 140.1 180 [1403,] 140.2 179 [1404,] 140.3 179 [1405,] 140.4 178 [1406,] 140.5 177 [1407,] 140.6 177 [1408,] 140.7 176 [1409,] 140.8 175 [1410,] 140.9 175 [1411,] 141.0 174 [1412,] 141.1 173 [1413,] 141.2 173 [1414,] 141.3 172 [1415,] 141.4 172 [1416,] 141.5 171 [1417,] 141.6 171 [1418,] 141.7 170 [1419,] 141.8 169 [1420,] 141.9 169 [1421,] 142.0 168 [1422,] 142.1 167 [1423,] 142.2 167 [1424,] 142.3 166 [1425,] 142.4 165 [1426,] 142.5 165 [1427,] 142.6 164 [1428,] 142.7 164 [1429,] 142.8 163 [1430,] 142.9 163 [1431,] 143.0 162 [1432,] 143.1 161 [1433,] 143.2 161 [1434,] 143.3 160 [1435,] 143.4 160 [1436,] 143.5 159 [1437,] 143.6 158 [1438,] 143.7 158 [1439,] 143.8 157 [1440,] 143.9 157 [1441,] 144.0 156 [1442,] 144.1 155 [1443,] 144.2 155 [1444,] 144.3 154 [1445,] 144.4 153 [1446,] 144.5 153 [1447,] 144.6 152 [1448,] 144.7 152 [1449,] 144.8 151 [1450,] 144.9 151 [1451,] 145.0 150 [1452,] 145.1 149 [1453,] 145.2 149 [1454,] 145.3 148 [1455,] 145.4 147 [1456,] 145.5 147 [1457,] 145.6 146 [1458,] 145.7 145 [1459,] 145.8 145 [1460,] 145.9 145 [1461,] 146.0 144 [1462,] 146.1 144 [1463,] 146.2 144 [1464,] 146.3 144 [1465,] 146.4 143 [1466,] 146.5 143 [1467,] 146.6 143 [1468,] 146.7 142 [1469,] 146.8 142 [1470,] 146.9 141 [1471,] 147.0 141 [1472,] 147.1 140 [1473,] 147.2 140 [1474,] 147.3 139 [1475,] 147.4 139 [1476,] 147.5 138 [1477,] 147.6 138 [1478,] 147.7 137 [1479,] 147.8 137 [1480,] 147.9 136 [1481,] 148.0 136 [1482,] 148.1 135 [1483,] 148.2 135 [1484,] 148.3 134 [1485,] 148.4 134 [1486,] 148.5 133 [1487,] 148.6 133 [1488,] 148.7 133 [1489,] 148.8 132 [1490,] 148.9 132 [1491,] 149.0 131 [1492,] 149.1 131 [1493,] 149.2 131 [1494,] 149.3 130 [1495,] 149.4 130 [1496,] 149.5 129 [1497,] 149.6 129 [1498,] 149.7 128 [1499,] 149.8 128 [1500,] 149.9 127 [1501,] 150.0 127 [1502,] 150.1 126 [1503,] 150.2 126 [1504,] 150.3 125 [1505,] 150.4 125 [1506,] 150.5 125 [1507,] 150.6 124 [1508,] 150.7 124 [1509,] 150.8 123 [1510,] 150.9 123 [1511,] 151.0 123 [1512,] 151.1 123 [1513,] 151.2 122 [1514,] 151.3 122 [1515,] 151.4 121 [1516,] 151.5 121 [1517,] 151.6 120 [1518,] 151.7 120 [1519,] 151.8 120 [1520,] 151.9 119 [1521,] 152.0 119 [1522,] 152.1 118 [1523,] 152.2 118 [1524,] 152.3 117 [1525,] 152.4 117 [1526,] 152.5 117 [1527,] 152.6 116 [1528,] 152.7 116 [1529,] 152.8 115 [1530,] 152.9 115 [1531,] 153.0 114 [1532,] 153.1 114 [1533,] 153.2 114 [1534,] 153.3 113 [1535,] 153.4 113 [1536,] 153.5 112 [1537,] 153.6 112 [1538,] 153.7 112 [1539,] 153.8 111 [1540,] 153.9 111 [1541,] 154.0 111 [1542,] 154.1 111 [1543,] 154.2 111 [1544,] 154.3 110 [1545,] 154.4 110 [1546,] 154.5 109 [1547,] 154.6 109 [1548,] 154.7 109 [1549,] 154.8 108 [1550,] 154.9 108 [1551,] 155.0 107 [1552,] 155.1 107 [1553,] 155.2 107 [1554,] 155.3 106 [1555,] 155.4 106 [1556,] 155.5 105 [1557,] 155.6 105 [1558,] 155.7 105 [1559,] 155.8 104 [1560,] 155.9 104 [1561,] 156.0 104 [1562,] 156.1 104 [1563,] 156.2 103 [1564,] 156.3 103 [1565,] 156.4 102 [1566,] 156.5 102 [1567,] 156.6 102 [1568,] 156.7 102 [1569,] 156.8 101 [1570,] 156.9 101 [1571,] 157.0 101 [1572,] 157.1 100 [1573,] 157.2 100 [1574,] 157.3 101 [1575,] 157.4 101 [1576,] 157.5 101 [1577,] 157.6 100 [1578,] 157.7 100 [1579,] 157.8 99 [1580,] 157.9 99 [1581,] 158.0 99 [1582,] 158.1 98 [1583,] 158.2 98 [1584,] 158.3 97 [1585,] 158.4 96 [1586,] 158.5 96 [1587,] 158.6 96 [1588,] 158.7 96 [1589,] 158.8 95 [1590,] 158.9 95 [1591,] 159.0 95 [1592,] 159.1 95 [1593,] 159.2 94 [1594,] 159.3 94 [1595,] 159.4 94 [1596,] 159.5 93 [1597,] 159.6 93 [1598,] 159.7 93 [1599,] 159.8 93 [1600,] 159.9 92 [1601,] 160.0 92 [1602,] 160.1 92 [1603,] 160.2 91 [1604,] 160.3 91 [1605,] 160.4 91 [1606,] 160.5 90 [1607,] 160.6 89 [1608,] 160.7 89 [1609,] 160.8 89 [1610,] 160.9 88 [1611,] 161.0 88 [1612,] 161.1 88 [1613,] 161.2 87 [1614,] 161.3 87 [1615,] 161.4 87 [1616,] 161.5 87 [1617,] 161.6 88 [1618,] 161.7 87 [1619,] 161.8 87 [1620,] 161.9 87 [1621,] 162.0 87 [1622,] 162.1 87 [1623,] 162.2 86 [1624,] 162.3 86 [1625,] 162.4 86 [1626,] 162.5 85 [1627,] 162.6 85 [1628,] 162.7 85 [1629,] 162.8 85 [1630,] 162.9 84 [1631,] 163.0 84 [1632,] 163.1 84 [1633,] 163.2 83 [1634,] 163.3 83 [1635,] 163.4 83 [1636,] 163.5 83 [1637,] 163.6 83 [1638,] 163.7 82 [1639,] 163.8 82 [1640,] 163.9 82 [1641,] 164.0 82 [1642,] 164.1 81 [1643,] 164.2 81 [1644,] 164.3 81 [1645,] 164.4 80 [1646,] 164.5 80 [1647,] 164.6 80 [1648,] 164.7 80 [1649,] 164.8 80 [1650,] 164.9 79 [1651,] 165.0 79 [1652,] 165.1 79 [1653,] 165.2 79 [1654,] 165.3 79 [1655,] 165.4 78 [1656,] 165.5 78 [1657,] 165.6 77 [1658,] 165.7 77 [1659,] 165.8 77 [1660,] 165.9 77 [1661,] 166.0 77 [1662,] 166.1 76 [1663,] 166.2 76 [1664,] 166.3 76 [1665,] 166.4 76 [1666,] 166.5 76 [1667,] 166.6 76 [1668,] 166.7 75 [1669,] 166.8 75 [1670,] 166.9 75 [1671,] 167.0 75 [1672,] 167.1 74 [1673,] 167.2 74 [1674,] 167.3 73 [1675,] 167.4 73 [1676,] 167.5 73 [1677,] 167.6 73 [1678,] 167.7 73 [1679,] 167.8 72 [1680,] 167.9 72 [1681,] 168.0 72 [1682,] 168.1 72 [1683,] 168.2 72 [1684,] 168.3 72 [1685,] 168.4 72 [1686,] 168.5 71 [1687,] 168.6 71 [1688,] 168.7 71 [1689,] 168.8 71 [1690,] 168.9 71 [1691,] 169.0 71 [1692,] 169.1 71 [1693,] 169.2 71 [1694,] 169.3 70 [1695,] 169.4 70 [1696,] 169.5 70 [1697,] 169.6 70 [1698,] 169.7 70 [1699,] 169.8 69 [1700,] 169.9 69 [1701,] 170.0 69 [1702,] 170.1 69 [1703,] 170.2 69 [1704,] 170.3 68 [1705,] 170.4 68 [1706,] 170.5 68 [1707,] 170.6 68 [1708,] 170.7 67 [1709,] 170.8 67 [1710,] 170.9 67 [1711,] 171.0 67 [1712,] 171.1 67 [1713,] 171.2 66 [1714,] 171.3 66 [1715,] 171.4 66 [1716,] 171.5 66 [1717,] 171.6 67 [1718,] 171.7 66 [1719,] 171.8 66 [1720,] 171.9 66 [1721,] 172.0 66 [1722,] 172.1 66 [1723,] 172.2 66 [1724,] 172.3 66 [1725,] 172.4 66 [1726,] 172.5 66 [1727,] 172.6 65 [1728,] 172.7 65 [1729,] 172.8 65 [1730,] 172.9 65 [1731,] 173.0 65 [1732,] 173.1 64 [1733,] 173.2 64 [1734,] 173.3 64 [1735,] 173.4 64 [1736,] 173.5 63 [1737,] 173.6 63 [1738,] 173.7 62 [1739,] 173.8 61 [1740,] 173.9 60 $`4_OSL (UVVIS)` [,1] [,2] [1,] 0.1 891 [2,] 0.2 775 [3,] 0.3 655 [4,] 0.4 497 [5,] 0.5 424 [6,] 0.6 328 [7,] 0.7 293 [8,] 0.8 199 [9,] 0.9 204 [10,] 1.0 157 [11,] 1.1 125 [12,] 1.2 108 [13,] 1.3 94 [14,] 1.4 85 [15,] 1.5 77 [16,] 1.6 61 [17,] 1.7 73 [18,] 1.8 50 [19,] 1.9 42 [20,] 2.0 41 [21,] 2.1 32 [22,] 2.2 42 [23,] 2.3 34 [24,] 2.4 43 [25,] 2.5 26 [26,] 2.6 41 [27,] 2.7 28 [28,] 2.8 29 [29,] 2.9 34 [30,] 3.0 35 [31,] 3.1 19 [32,] 3.2 18 [33,] 3.3 17 [34,] 3.4 33 [35,] 3.5 18 [36,] 3.6 18 [37,] 3.7 15 [38,] 3.8 31 [39,] 3.9 15 [40,] 4.0 14 [41,] 4.1 12 [42,] 4.2 16 [43,] 4.3 18 [44,] 4.4 12 [45,] 4.5 16 [46,] 4.6 15 [47,] 4.7 9 [48,] 4.8 21 [49,] 4.9 16 [50,] 5.0 17 [51,] 5.1 18 [52,] 5.2 17 [53,] 5.3 18 [54,] 5.4 13 [55,] 5.5 19 [56,] 5.6 12 [57,] 5.7 11 [58,] 5.8 11 [59,] 5.9 16 [60,] 6.0 9 [61,] 6.1 11 [62,] 6.2 15 [63,] 6.3 9 [64,] 6.4 12 [65,] 6.5 13 [66,] 6.6 16 [67,] 6.7 8 [68,] 6.8 16 [69,] 6.9 12 [70,] 7.0 16 [71,] 7.1 8 [72,] 7.2 15 [73,] 7.3 9 [74,] 7.4 7 [75,] 7.5 11 [76,] 7.6 15 [77,] 7.7 19 [78,] 7.8 14 [79,] 7.9 13 [80,] 8.0 18 [81,] 8.1 10 [82,] 8.2 16 [83,] 8.3 7 [84,] 8.4 14 [85,] 8.5 15 [86,] 8.6 11 [87,] 8.7 11 [88,] 8.8 14 [89,] 8.9 20 [90,] 9.0 12 [91,] 9.1 10 [92,] 9.2 16 [93,] 9.3 5 [94,] 9.4 11 [95,] 9.5 9 [96,] 9.6 15 [97,] 9.7 16 [98,] 9.8 15 [99,] 9.9 11 [100,] 10.0 14 [101,] 10.1 11 [102,] 10.2 12 [103,] 10.3 12 [104,] 10.4 12 [105,] 10.5 16 [106,] 10.6 9 [107,] 10.7 13 [108,] 10.8 19 [109,] 10.9 10 [110,] 11.0 8 [111,] 11.1 2 [112,] 11.2 4 [113,] 11.3 9 [114,] 11.4 11 [115,] 11.5 12 [116,] 11.6 14 [117,] 11.7 13 [118,] 11.8 8 [119,] 11.9 15 [120,] 12.0 4 [121,] 12.1 16 [122,] 12.2 28 [123,] 12.3 5 [124,] 12.4 16 [125,] 12.5 15 [126,] 12.6 14 [127,] 12.7 10 [128,] 12.8 13 [129,] 12.9 13 [130,] 13.0 14 [131,] 13.1 12 [132,] 13.2 14 [133,] 13.3 19 [134,] 13.4 16 [135,] 13.5 13 [136,] 13.6 14 [137,] 13.7 10 [138,] 13.8 11 [139,] 13.9 9 [140,] 14.0 20 [141,] 14.1 14 [142,] 14.2 13 [143,] 14.3 15 [144,] 14.4 20 [145,] 14.5 9 [146,] 14.6 17 [147,] 14.7 10 [148,] 14.8 13 [149,] 14.9 8 [150,] 15.0 15 [151,] 15.1 14 [152,] 15.2 9 [153,] 15.3 19 [154,] 15.4 14 [155,] 15.5 9 [156,] 15.6 11 [157,] 15.7 7 [158,] 15.8 14 [159,] 15.9 11 [160,] 16.0 18 [161,] 16.1 8 [162,] 16.2 8 [163,] 16.3 15 [164,] 16.4 15 [165,] 16.5 8 [166,] 16.6 0 [167,] 16.7 17 [168,] 16.8 16 [169,] 16.9 14 [170,] 17.0 12 [171,] 17.1 5 [172,] 17.2 12 [173,] 17.3 11 [174,] 17.4 16 [175,] 17.5 6 [176,] 17.6 13 [177,] 17.7 12 [178,] 17.8 9 [179,] 17.9 3 [180,] 18.0 13 [181,] 18.1 20 [182,] 18.2 12 [183,] 18.3 21 [184,] 18.4 4 [185,] 18.5 8 [186,] 18.6 9 [187,] 18.7 11 [188,] 18.8 20 [189,] 18.9 11 [190,] 19.0 12 [191,] 19.1 6 [192,] 19.2 11 [193,] 19.3 21 [194,] 19.4 16 [195,] 19.5 13 [196,] 19.6 7 [197,] 19.7 16 [198,] 19.8 9 [199,] 19.9 10 [200,] 20.0 15 [201,] 20.1 12 [202,] 20.2 8 [203,] 20.3 9 [204,] 20.4 16 [205,] 20.5 11 [206,] 20.6 17 [207,] 20.7 18 [208,] 20.8 10 [209,] 20.9 15 [210,] 21.0 9 [211,] 21.1 13 [212,] 21.2 7 [213,] 21.3 17 [214,] 21.4 12 [215,] 21.5 29 [216,] 21.6 15 [217,] 21.7 10 [218,] 21.8 11 [219,] 21.9 10 [220,] 22.0 21 [221,] 22.1 12 [222,] 22.2 5 [223,] 22.3 7 [224,] 22.4 14 [225,] 22.5 10 [226,] 22.6 14 [227,] 22.7 4 [228,] 22.8 16 [229,] 22.9 12 [230,] 23.0 15 [231,] 23.1 9 [232,] 23.2 16 [233,] 23.3 6 [234,] 23.4 13 [235,] 23.5 13 [236,] 23.6 18 [237,] 23.7 7 [238,] 23.8 13 [239,] 23.9 13 [240,] 24.0 10 [241,] 24.1 4 [242,] 24.2 22 [243,] 24.3 9 [244,] 24.4 16 [245,] 24.5 4 [246,] 24.6 12 [247,] 24.7 9 [248,] 24.8 29 [249,] 24.9 10 [250,] 25.0 19 [251,] 25.1 9 [252,] 25.2 20 [253,] 25.3 18 [254,] 25.4 14 [255,] 25.5 14 [256,] 25.6 12 [257,] 25.7 24 [258,] 25.8 8 [259,] 25.9 16 [260,] 26.0 7 [261,] 26.1 17 [262,] 26.2 9 [263,] 26.3 15 [264,] 26.4 11 [265,] 26.5 11 [266,] 26.6 16 [267,] 26.7 9 [268,] 26.8 18 [269,] 26.9 21 [270,] 27.0 6 [271,] 27.1 10 [272,] 27.2 6 [273,] 27.3 11 [274,] 27.4 12 [275,] 27.5 16 [276,] 27.6 14 [277,] 27.7 15 [278,] 27.8 17 [279,] 27.9 13 [280,] 28.0 9 [281,] 28.1 16 [282,] 28.2 15 [283,] 28.3 6 [284,] 28.4 12 [285,] 28.5 11 [286,] 28.6 19 [287,] 28.7 7 [288,] 28.8 10 [289,] 28.9 11 [290,] 29.0 7 [291,] 29.1 14 [292,] 29.2 17 [293,] 29.3 25 [294,] 29.4 18 [295,] 29.5 13 [296,] 29.6 18 [297,] 29.7 10 [298,] 29.8 21 [299,] 29.9 11 [300,] 30.0 10 [301,] 30.1 18 [302,] 30.2 9 [303,] 30.3 9 [304,] 30.4 8 [305,] 30.5 7 [306,] 30.6 15 [307,] 30.7 7 [308,] 30.8 19 [309,] 30.9 22 [310,] 31.0 6 [311,] 31.1 19 [312,] 31.2 15 [313,] 31.3 10 [314,] 31.4 12 [315,] 31.5 20 [316,] 31.6 12 [317,] 31.7 17 [318,] 31.8 12 [319,] 31.9 16 [320,] 32.0 15 [321,] 32.1 13 [322,] 32.2 19 [323,] 32.3 12 [324,] 32.4 20 [325,] 32.5 10 [326,] 32.6 15 [327,] 32.7 17 [328,] 32.8 18 [329,] 32.9 21 [330,] 33.0 9 [331,] 33.1 17 [332,] 33.2 10 [333,] 33.3 15 [334,] 33.4 8 [335,] 33.5 9 [336,] 33.6 11 [337,] 33.7 8 [338,] 33.8 2 [339,] 33.9 18 [340,] 34.0 8 [341,] 34.1 19 [342,] 34.2 24 [343,] 34.3 8 [344,] 34.4 11 [345,] 34.5 11 [346,] 34.6 11 [347,] 34.7 12 [348,] 34.8 16 [349,] 34.9 9 [350,] 35.0 13 [351,] 35.1 8 [352,] 35.2 12 [353,] 35.3 14 [354,] 35.4 9 [355,] 35.5 19 [356,] 35.6 19 [357,] 35.7 12 [358,] 35.8 7 [359,] 35.9 13 [360,] 36.0 11 [361,] 36.1 12 [362,] 36.2 13 [363,] 36.3 16 [364,] 36.4 16 [365,] 36.5 21 [366,] 36.6 5 [367,] 36.7 7 [368,] 36.8 14 [369,] 36.9 12 [370,] 37.0 20 [371,] 37.1 11 [372,] 37.2 15 [373,] 37.3 17 [374,] 37.4 11 [375,] 37.5 8 [376,] 37.6 10 [377,] 37.7 14 [378,] 37.8 11 [379,] 37.9 11 [380,] 38.0 10 [381,] 38.1 19 [382,] 38.2 23 [383,] 38.3 17 [384,] 38.4 6 [385,] 38.5 15 [386,] 38.6 9 [387,] 38.7 7 [388,] 38.8 8 [389,] 38.9 16 [390,] 39.0 12 [391,] 39.1 8 [392,] 39.2 12 [393,] 39.3 15 [394,] 39.4 15 [395,] 39.5 6 [396,] 39.6 10 [397,] 39.7 22 [398,] 39.8 16 [399,] 39.9 9 [400,] 40.0 11 [401,] 40.1 10 [402,] 40.2 17 [403,] 40.3 9 [404,] 40.4 10 [405,] 40.5 10 [406,] 40.6 13 [407,] 40.7 14 [408,] 40.8 9 [409,] 40.9 17 [410,] 41.0 20 [411,] 41.1 8 [412,] 41.2 13 [413,] 41.3 13 [414,] 41.4 5 [415,] 41.5 16 [416,] 41.6 15 [417,] 41.7 18 [418,] 41.8 12 [419,] 41.9 17 [420,] 42.0 11 [421,] 42.1 23 [422,] 42.2 17 [423,] 42.3 10 [424,] 42.4 11 [425,] 42.5 12 [426,] 42.6 11 [427,] 42.7 22 [428,] 42.8 9 [429,] 42.9 18 [430,] 43.0 12 [431,] 43.1 16 [432,] 43.2 11 [433,] 43.3 15 [434,] 43.4 16 [435,] 43.5 7 [436,] 43.6 13 [437,] 43.7 20 [438,] 43.8 9 [439,] 43.9 20 [440,] 44.0 15 [441,] 44.1 10 [442,] 44.2 10 [443,] 44.3 14 [444,] 44.4 14 [445,] 44.5 4 [446,] 44.6 12 [447,] 44.7 5 [448,] 44.8 15 [449,] 44.9 6 [450,] 45.0 14 [451,] 45.1 15 [452,] 45.2 11 [453,] 45.3 12 [454,] 45.4 14 [455,] 45.5 12 [456,] 45.6 8 [457,] 45.7 16 [458,] 45.8 7 [459,] 45.9 9 [460,] 46.0 10 [461,] 46.1 15 [462,] 46.2 12 [463,] 46.3 5 [464,] 46.4 11 [465,] 46.5 23 [466,] 46.6 5 [467,] 46.7 10 [468,] 46.8 16 [469,] 46.9 18 [470,] 47.0 12 [471,] 47.1 16 [472,] 47.2 16 [473,] 47.3 8 [474,] 47.4 17 [475,] 47.5 8 [476,] 47.6 12 [477,] 47.7 10 [478,] 47.8 14 [479,] 47.9 8 [480,] 48.0 10 [481,] 48.1 11 [482,] 48.2 19 [483,] 48.3 12 [484,] 48.4 9 [485,] 48.5 13 [486,] 48.6 20 [487,] 48.7 9 [488,] 48.8 13 [489,] 48.9 7 [490,] 49.0 16 [491,] 49.1 10 [492,] 49.2 14 [493,] 49.3 12 [494,] 49.4 12 [495,] 49.5 10 [496,] 49.6 7 [497,] 49.7 8 [498,] 49.8 12 [499,] 49.9 19 [500,] 50.0 16 $`5__OSL (NA)` [,1] [,2] [1,] 0 25 [2,] 20 125 [3,] 90 125 [4,] 96 60 [5,] 216 60 $`6__OSL (NA)` [,1] [,2] [1,] 0.0 50 [2,] 0.1 49 [3,] 0.2 48 [4,] 0.3 48 [5,] 0.4 48 [6,] 0.5 48 [7,] 0.6 48 [8,] 0.7 48 [9,] 0.8 48 [10,] 0.9 48 [11,] 1.0 47 [12,] 1.1 47 [13,] 1.2 47 [14,] 1.3 47 [15,] 1.4 47 [16,] 1.5 47 [17,] 1.6 47 [18,] 1.7 47 [19,] 1.8 47 [20,] 1.9 47 [21,] 2.0 47 [22,] 2.1 47 [23,] 2.2 47 [24,] 2.3 47 [25,] 2.4 46 [26,] 2.5 46 [27,] 2.6 46 [28,] 2.7 46 [29,] 2.8 46 [30,] 2.9 46 [31,] 3.0 46 [32,] 3.1 46 [33,] 3.2 46 [34,] 3.3 46 [35,] 3.4 46 [36,] 3.5 46 [37,] 3.6 46 [38,] 3.7 46 [39,] 3.8 46 [40,] 3.9 46 [41,] 4.0 46 [42,] 4.1 45 [43,] 4.2 45 [44,] 4.3 45 [45,] 4.4 45 [46,] 4.5 45 [47,] 4.6 45 [48,] 4.7 45 [49,] 4.8 44 [50,] 4.9 43 [51,] 5.0 43 [52,] 5.1 43 [53,] 5.2 44 [54,] 5.3 44 [55,] 5.4 43 [56,] 5.5 43 [57,] 5.6 43 [58,] 5.7 43 [59,] 5.8 43 [60,] 5.9 44 [61,] 6.0 44 [62,] 6.1 44 [63,] 6.2 44 [64,] 6.3 44 [65,] 6.4 44 [66,] 6.5 43 [67,] 6.6 43 [68,] 6.7 44 [69,] 6.8 44 [70,] 6.9 44 [71,] 7.0 44 [72,] 7.1 43 [73,] 7.2 43 [74,] 7.3 43 [75,] 7.4 43 [76,] 7.5 43 [77,] 7.6 43 [78,] 7.7 43 [79,] 7.8 44 [80,] 7.9 44 [81,] 8.0 44 [82,] 8.1 45 [83,] 8.2 45 [84,] 8.3 46 [85,] 8.4 47 [86,] 8.5 47 [87,] 8.6 48 [88,] 8.7 49 [89,] 8.8 49 [90,] 8.9 50 [91,] 9.0 50 [92,] 9.1 51 [93,] 9.2 51 [94,] 9.3 52 [95,] 9.4 53 [96,] 9.5 53 [97,] 9.6 54 [98,] 9.7 54 [99,] 9.8 55 [100,] 9.9 56 [101,] 10.0 58 [102,] 10.1 59 [103,] 10.2 59 [104,] 10.3 60 [105,] 10.4 61 [106,] 10.5 62 [107,] 10.6 64 [108,] 10.7 65 [109,] 10.8 65 [110,] 10.9 65 [111,] 11.0 66 [112,] 11.1 66 [113,] 11.2 67 [114,] 11.3 67 [115,] 11.4 68 [116,] 11.5 69 [117,] 11.6 69 [118,] 11.7 70 [119,] 11.8 70 [120,] 11.9 71 [121,] 12.0 71 [122,] 12.1 72 [123,] 12.2 73 [124,] 12.3 73 [125,] 12.4 74 [126,] 12.5 75 [127,] 12.6 75 [128,] 12.7 76 [129,] 12.8 77 [130,] 12.9 78 [131,] 13.0 78 [132,] 13.1 79 [133,] 13.2 79 [134,] 13.3 80 [135,] 13.4 81 [136,] 13.5 82 [137,] 13.6 82 [138,] 13.7 83 [139,] 13.8 84 [140,] 13.9 85 [141,] 14.0 86 [142,] 14.1 86 [143,] 14.2 87 [144,] 14.3 87 [145,] 14.4 89 [146,] 14.5 89 [147,] 14.6 90 [148,] 14.7 90 [149,] 14.8 91 [150,] 14.9 90 [151,] 15.0 90 [152,] 15.1 91 [153,] 15.2 91 [154,] 15.3 92 [155,] 15.4 92 [156,] 15.5 92 [157,] 15.6 93 [158,] 15.7 93 [159,] 15.8 94 [160,] 15.9 95 [161,] 16.0 97 [162,] 16.1 97 [163,] 16.2 98 [164,] 16.3 98 [165,] 16.4 99 [166,] 16.5 100 [167,] 16.6 100 [168,] 16.7 101 [169,] 16.8 102 [170,] 16.9 103 [171,] 17.0 103 [172,] 17.1 103 [173,] 17.2 104 [174,] 17.3 105 [175,] 17.4 105 [176,] 17.5 106 [177,] 17.6 106 [178,] 17.7 107 [179,] 17.8 107 [180,] 17.9 107 [181,] 18.0 108 [182,] 18.1 109 [183,] 18.2 110 [184,] 18.3 110 [185,] 18.4 111 [186,] 18.5 111 [187,] 18.6 111 [188,] 18.7 112 [189,] 18.8 113 [190,] 18.9 113 [191,] 19.0 114 [192,] 19.1 114 [193,] 19.2 116 [194,] 19.3 116 [195,] 19.4 117 [196,] 19.5 117 [197,] 19.6 118 [198,] 19.7 119 [199,] 19.8 119 [200,] 19.9 119 [201,] 20.0 120 [202,] 20.1 121 [203,] 20.2 120 [204,] 20.3 121 [205,] 20.4 121 [206,] 20.5 122 [207,] 20.6 122 [208,] 20.7 123 [209,] 20.8 123 [210,] 20.9 123 [211,] 21.0 124 [212,] 21.1 124 [213,] 21.2 124 [214,] 21.3 124 [215,] 21.4 124 [216,] 21.5 124 [217,] 21.6 124 [218,] 21.7 124 [219,] 21.8 124 [220,] 21.9 124 [221,] 22.0 124 [222,] 22.1 124 [223,] 22.2 124 [224,] 22.3 124 [225,] 22.4 124 [226,] 22.5 124 [227,] 22.6 124 [228,] 22.7 124 [229,] 22.8 123 [230,] 22.9 123 [231,] 23.0 124 [232,] 23.1 124 [233,] 23.2 124 [234,] 23.3 123 [235,] 23.4 124 [236,] 23.5 124 [237,] 23.6 124 [238,] 23.7 125 [239,] 23.8 125 [240,] 23.9 125 [241,] 24.0 125 [242,] 24.1 125 [243,] 24.2 125 [244,] 24.3 126 [245,] 24.4 126 [246,] 24.5 126 [247,] 24.6 127 [248,] 24.7 126 [249,] 24.8 126 [250,] 24.9 126 [251,] 25.0 126 [252,] 25.1 126 [253,] 25.2 126 [254,] 25.3 126 [255,] 25.4 126 [256,] 25.5 126 [257,] 25.6 125 [258,] 25.7 125 [259,] 25.8 125 [260,] 25.9 125 [261,] 26.0 125 [262,] 26.1 125 [263,] 26.2 125 [264,] 26.3 125 [265,] 26.4 124 [266,] 26.5 124 [267,] 26.6 124 [268,] 26.7 124 [269,] 26.8 124 [270,] 26.9 124 [271,] 27.0 124 [272,] 27.1 124 [273,] 27.2 124 [274,] 27.3 124 [275,] 27.4 125 [276,] 27.5 125 [277,] 27.6 125 [278,] 27.7 125 [279,] 27.8 125 [280,] 27.9 125 [281,] 28.0 125 [282,] 28.1 125 [283,] 28.2 125 [284,] 28.3 125 [285,] 28.4 125 [286,] 28.5 125 [287,] 28.6 125 [288,] 28.7 125 [289,] 28.8 125 [290,] 28.9 125 [291,] 29.0 125 [292,] 29.1 125 [293,] 29.2 125 [294,] 29.3 125 [295,] 29.4 125 [296,] 29.5 125 [297,] 29.6 125 [298,] 29.7 125 [299,] 29.8 125 [300,] 29.9 125 [301,] 30.0 125 [302,] 30.1 125 [303,] 30.2 125 [304,] 30.3 125 [305,] 30.4 125 [306,] 30.5 125 [307,] 30.6 125 [308,] 30.7 125 [309,] 30.8 126 [310,] 30.9 126 [311,] 31.0 126 [312,] 31.1 126 [313,] 31.2 126 [314,] 31.3 126 [315,] 31.4 126 [316,] 31.5 126 [317,] 31.6 127 [318,] 31.7 127 [319,] 31.8 126 [320,] 31.9 126 [321,] 32.0 126 [322,] 32.1 126 [323,] 32.2 126 [324,] 32.3 126 [325,] 32.4 126 [326,] 32.5 126 [327,] 32.6 127 [328,] 32.7 126 [329,] 32.8 126 [330,] 32.9 126 [331,] 33.0 126 [332,] 33.1 126 [333,] 33.2 127 [334,] 33.3 127 [335,] 33.4 127 [336,] 33.5 127 [337,] 33.6 126 [338,] 33.7 126 [339,] 33.8 126 [340,] 33.9 126 [341,] 34.0 126 [342,] 34.1 126 [343,] 34.2 126 [344,] 34.3 126 [345,] 34.4 126 [346,] 34.5 126 [347,] 34.6 126 [348,] 34.7 126 [349,] 34.8 126 [350,] 34.9 126 [351,] 35.0 126 [352,] 35.1 126 [353,] 35.2 126 [354,] 35.3 126 [355,] 35.4 126 [356,] 35.5 126 [357,] 35.6 126 [358,] 35.7 126 [359,] 35.8 125 [360,] 35.9 125 [361,] 36.0 125 [362,] 36.1 125 [363,] 36.2 125 [364,] 36.3 125 [365,] 36.4 125 [366,] 36.5 125 [367,] 36.6 125 [368,] 36.7 125 [369,] 36.8 125 [370,] 36.9 125 [371,] 37.0 125 [372,] 37.1 125 [373,] 37.2 125 [374,] 37.3 125 [375,] 37.4 125 [376,] 37.5 125 [377,] 37.6 125 [378,] 37.7 125 [379,] 37.8 125 [380,] 37.9 126 [381,] 38.0 126 [382,] 38.1 126 [383,] 38.2 125 [384,] 38.3 126 [385,] 38.4 126 [386,] 38.5 126 [387,] 38.6 126 [388,] 38.7 126 [389,] 38.8 125 [390,] 38.9 125 [391,] 39.0 125 [392,] 39.1 125 [393,] 39.2 125 [394,] 39.3 125 [395,] 39.4 125 [396,] 39.5 125 [397,] 39.6 125 [398,] 39.7 125 [399,] 39.8 125 [400,] 39.9 125 [401,] 40.0 125 [402,] 40.1 125 [403,] 40.2 125 [404,] 40.3 125 [405,] 40.4 125 [406,] 40.5 126 [407,] 40.6 126 [408,] 40.7 126 [409,] 40.8 126 [410,] 40.9 126 [411,] 41.0 126 [412,] 41.1 126 [413,] 41.2 126 [414,] 41.3 126 [415,] 41.4 126 [416,] 41.5 126 [417,] 41.6 126 [418,] 41.7 125 [419,] 41.8 125 [420,] 41.9 125 [421,] 42.0 125 [422,] 42.1 125 [423,] 42.2 125 [424,] 42.3 125 [425,] 42.4 125 [426,] 42.5 125 [427,] 42.6 125 [428,] 42.7 125 [429,] 42.8 125 [430,] 42.9 126 [431,] 43.0 126 [432,] 43.1 126 [433,] 43.2 126 [434,] 43.3 125 [435,] 43.4 126 [436,] 43.5 126 [437,] 43.6 126 [438,] 43.7 126 [439,] 43.8 126 [440,] 43.9 126 [441,] 44.0 125 [442,] 44.1 126 [443,] 44.2 125 [444,] 44.3 125 [445,] 44.4 125 [446,] 44.5 126 [447,] 44.6 126 [448,] 44.7 126 [449,] 44.8 126 [450,] 44.9 126 [451,] 45.0 126 [452,] 45.1 126 [453,] 45.2 126 [454,] 45.3 126 [455,] 45.4 126 [456,] 45.5 126 [457,] 45.6 126 [458,] 45.7 126 [459,] 45.8 126 [460,] 45.9 126 [461,] 46.0 127 [462,] 46.1 126 [463,] 46.2 126 [464,] 46.3 126 [465,] 46.4 127 [466,] 46.5 127 [467,] 46.6 127 [468,] 46.7 127 [469,] 46.8 127 [470,] 46.9 127 [471,] 47.0 127 [472,] 47.1 127 [473,] 47.2 127 [474,] 47.3 127 [475,] 47.4 126 [476,] 47.5 126 [477,] 47.6 126 [478,] 47.7 126 [479,] 47.8 126 [480,] 47.9 125 [481,] 48.0 125 [482,] 48.1 125 [483,] 48.2 125 [484,] 48.3 125 [485,] 48.4 125 [486,] 48.5 125 [487,] 48.6 125 [488,] 48.7 124 [489,] 48.8 124 [490,] 48.9 124 [491,] 49.0 124 [492,] 49.1 124 [493,] 49.2 124 [494,] 49.3 124 [495,] 49.4 124 [496,] 49.5 124 [497,] 49.6 124 [498,] 49.7 125 [499,] 49.8 125 [500,] 49.9 125 [501,] 50.0 125 [502,] 50.1 125 [503,] 50.2 126 [504,] 50.3 125 [505,] 50.4 125 [506,] 50.5 125 [507,] 50.6 125 [508,] 50.7 125 [509,] 50.8 125 [510,] 50.9 125 [511,] 51.0 125 [512,] 51.1 125 [513,] 51.2 125 [514,] 51.3 125 [515,] 51.4 126 [516,] 51.5 125 [517,] 51.6 125 [518,] 51.7 125 [519,] 51.8 125 [520,] 51.9 125 [521,] 52.0 125 [522,] 52.1 125 [523,] 52.2 125 [524,] 52.3 125 [525,] 52.4 125 [526,] 52.5 125 [527,] 52.6 125 [528,] 52.7 125 [529,] 52.8 125 [530,] 52.9 125 [531,] 53.0 125 [532,] 53.1 125 [533,] 53.2 125 [534,] 53.3 125 [535,] 53.4 125 [536,] 53.5 125 [537,] 53.6 125 [538,] 53.7 125 [539,] 53.8 125 [540,] 53.9 125 [541,] 54.0 125 [542,] 54.1 125 [543,] 54.2 125 [544,] 54.3 125 [545,] 54.4 125 [546,] 54.5 125 [547,] 54.6 125 [548,] 54.7 125 [549,] 54.8 125 [550,] 54.9 125 [551,] 55.0 124 [552,] 55.1 124 [553,] 55.2 124 [554,] 55.3 124 [555,] 55.4 124 [556,] 55.5 124 [557,] 55.6 124 [558,] 55.7 124 [559,] 55.8 124 [560,] 55.9 124 [561,] 56.0 125 [562,] 56.1 125 [563,] 56.2 126 [564,] 56.3 126 [565,] 56.4 126 [566,] 56.5 126 [567,] 56.6 125 [568,] 56.7 125 [569,] 56.8 125 [570,] 56.9 125 [571,] 57.0 125 [572,] 57.1 125 [573,] 57.2 125 [574,] 57.3 125 [575,] 57.4 125 [576,] 57.5 125 [577,] 57.6 125 [578,] 57.7 125 [579,] 57.8 125 [580,] 57.9 125 [581,] 58.0 125 [582,] 58.1 125 [583,] 58.2 125 [584,] 58.3 125 [585,] 58.4 125 [586,] 58.5 125 [587,] 58.6 125 [588,] 58.7 125 [589,] 58.8 125 [590,] 58.9 125 [591,] 59.0 124 [592,] 59.1 124 [593,] 59.2 123 [594,] 59.3 123 [595,] 59.4 123 [596,] 59.5 123 [597,] 59.6 123 [598,] 59.7 124 [599,] 59.8 124 [600,] 59.9 124 [601,] 60.0 124 [602,] 60.1 124 [603,] 60.2 125 [604,] 60.3 125 [605,] 60.4 125 [606,] 60.5 125 [607,] 60.6 125 [608,] 60.7 125 [609,] 60.8 125 [610,] 60.9 125 [611,] 61.0 124 [612,] 61.1 124 [613,] 61.2 124 [614,] 61.3 125 [615,] 61.4 125 [616,] 61.5 126 [617,] 61.6 125 [618,] 61.7 125 [619,] 61.8 126 [620,] 61.9 126 [621,] 62.0 126 [622,] 62.1 126 [623,] 62.2 126 [624,] 62.3 125 [625,] 62.4 125 [626,] 62.5 125 [627,] 62.6 126 [628,] 62.7 126 [629,] 62.8 125 [630,] 62.9 126 [631,] 63.0 126 [632,] 63.1 126 [633,] 63.2 126 [634,] 63.3 125 [635,] 63.4 125 [636,] 63.5 125 [637,] 63.6 125 [638,] 63.7 125 [639,] 63.8 125 [640,] 63.9 125 [641,] 64.0 125 [642,] 64.1 125 [643,] 64.2 125 [644,] 64.3 125 [645,] 64.4 125 [646,] 64.5 125 [647,] 64.6 125 [648,] 64.7 125 [649,] 64.8 125 [650,] 64.9 125 [651,] 65.0 125 [652,] 65.1 125 [653,] 65.2 125 [654,] 65.3 125 [655,] 65.4 125 [656,] 65.5 125 [657,] 65.6 126 [658,] 65.7 126 [659,] 65.8 125 [660,] 65.9 125 [661,] 66.0 126 [662,] 66.1 126 [663,] 66.2 126 [664,] 66.3 125 [665,] 66.4 125 [666,] 66.5 126 [667,] 66.6 126 [668,] 66.7 125 [669,] 66.8 126 [670,] 66.9 126 [671,] 67.0 126 [672,] 67.1 126 [673,] 67.2 126 [674,] 67.3 126 [675,] 67.4 126 [676,] 67.5 126 [677,] 67.6 126 [678,] 67.7 125 [679,] 67.8 125 [680,] 67.9 125 [681,] 68.0 125 [682,] 68.1 125 [683,] 68.2 125 [684,] 68.3 125 [685,] 68.4 125 [686,] 68.5 125 [687,] 68.6 125 [688,] 68.7 125 [689,] 68.8 125 [690,] 68.9 125 [691,] 69.0 125 [692,] 69.1 125 [693,] 69.2 124 [694,] 69.3 124 [695,] 69.4 125 [696,] 69.5 124 [697,] 69.6 124 [698,] 69.7 125 [699,] 69.8 125 [700,] 69.9 125 [701,] 70.0 124 [702,] 70.1 124 [703,] 70.2 124 [704,] 70.3 124 [705,] 70.4 124 [706,] 70.5 124 [707,] 70.6 124 [708,] 70.7 124 [709,] 70.8 124 [710,] 70.9 124 [711,] 71.0 124 [712,] 71.1 124 [713,] 71.2 125 [714,] 71.3 125 [715,] 71.4 125 [716,] 71.5 125 [717,] 71.6 125 [718,] 71.7 125 [719,] 71.8 125 [720,] 71.9 124 [721,] 72.0 125 [722,] 72.1 125 [723,] 72.2 124 [724,] 72.3 124 [725,] 72.4 125 [726,] 72.5 125 [727,] 72.6 125 [728,] 72.7 125 [729,] 72.8 125 [730,] 72.9 125 [731,] 73.0 125 [732,] 73.1 125 [733,] 73.2 125 [734,] 73.3 125 [735,] 73.4 124 [736,] 73.5 124 [737,] 73.6 124 [738,] 73.7 124 [739,] 73.8 125 [740,] 73.9 125 [741,] 74.0 125 [742,] 74.1 125 [743,] 74.2 125 [744,] 74.3 126 [745,] 74.4 126 [746,] 74.5 126 [747,] 74.6 126 [748,] 74.7 126 [749,] 74.8 126 [750,] 74.9 126 [751,] 75.0 125 [752,] 75.1 125 [753,] 75.2 125 [754,] 75.3 125 [755,] 75.4 125 [756,] 75.5 125 [757,] 75.6 125 [758,] 75.7 125 [759,] 75.8 125 [760,] 75.9 125 [761,] 76.0 125 [762,] 76.1 125 [763,] 76.2 126 [764,] 76.3 125 [765,] 76.4 125 [766,] 76.5 125 [767,] 76.6 125 [768,] 76.7 125 [769,] 76.8 125 [770,] 76.9 125 [771,] 77.0 126 [772,] 77.1 126 [773,] 77.2 126 [774,] 77.3 126 [775,] 77.4 127 [776,] 77.5 127 [777,] 77.6 127 [778,] 77.7 127 [779,] 77.8 127 [780,] 77.9 127 [781,] 78.0 126 [782,] 78.1 126 [783,] 78.2 126 [784,] 78.3 126 [785,] 78.4 125 [786,] 78.5 125 [787,] 78.6 124 [788,] 78.7 124 [789,] 78.8 124 [790,] 78.9 125 [791,] 79.0 125 [792,] 79.1 125 [793,] 79.2 125 [794,] 79.3 125 [795,] 79.4 125 [796,] 79.5 124 [797,] 79.6 124 [798,] 79.7 125 [799,] 79.8 125 [800,] 79.9 125 [801,] 80.0 125 [802,] 80.1 125 [803,] 80.2 125 [804,] 80.3 125 [805,] 80.4 125 [806,] 80.5 125 [807,] 80.6 125 [808,] 80.7 125 [809,] 80.8 125 [810,] 80.9 126 [811,] 81.0 125 [812,] 81.1 126 [813,] 81.2 127 [814,] 81.3 127 [815,] 81.4 127 [816,] 81.5 127 [817,] 81.6 127 [818,] 81.7 127 [819,] 81.8 127 [820,] 81.9 126 [821,] 82.0 126 [822,] 82.1 125 [823,] 82.2 125 [824,] 82.3 124 [825,] 82.4 125 [826,] 82.5 124 [827,] 82.6 124 [828,] 82.7 124 [829,] 82.8 124 [830,] 82.9 124 [831,] 83.0 125 [832,] 83.1 125 [833,] 83.2 125 [834,] 83.3 125 [835,] 83.4 125 [836,] 83.5 125 [837,] 83.6 125 [838,] 83.7 125 [839,] 83.8 125 [840,] 83.9 125 [841,] 84.0 125 [842,] 84.1 125 [843,] 84.2 124 [844,] 84.3 125 [845,] 84.4 125 [846,] 84.5 125 [847,] 84.6 125 [848,] 84.7 125 [849,] 84.8 125 [850,] 84.9 125 [851,] 85.0 125 [852,] 85.1 126 [853,] 85.2 126 [854,] 85.3 126 [855,] 85.4 126 [856,] 85.5 126 [857,] 85.6 126 [858,] 85.7 126 [859,] 85.8 126 [860,] 85.9 127 [861,] 86.0 127 [862,] 86.1 127 [863,] 86.2 127 [864,] 86.3 127 [865,] 86.4 127 [866,] 86.5 126 [867,] 86.6 127 [868,] 86.7 127 [869,] 86.8 127 [870,] 86.9 125 [871,] 87.0 125 [872,] 87.1 126 [873,] 87.2 126 [874,] 87.3 126 [875,] 87.4 127 [876,] 87.5 127 [877,] 87.6 127 [878,] 87.7 127 [879,] 87.8 127 [880,] 87.9 127 [881,] 88.0 127 [882,] 88.1 126 [883,] 88.2 126 [884,] 88.3 126 [885,] 88.4 126 [886,] 88.5 125 [887,] 88.6 125 [888,] 88.7 125 [889,] 88.8 125 [890,] 88.9 125 [891,] 89.0 125 [892,] 89.1 125 [893,] 89.2 125 [894,] 89.3 125 [895,] 89.4 125 [896,] 89.5 125 [897,] 89.6 125 [898,] 89.7 125 [899,] 89.8 125 [900,] 89.9 125 [901,] 90.0 125 [902,] 90.1 125 [903,] 90.2 125 [904,] 90.3 125 [905,] 90.4 125 [906,] 90.5 125 [907,] 90.6 125 [908,] 90.7 124 [909,] 90.8 124 [910,] 90.9 124 [911,] 91.0 124 [912,] 91.1 124 [913,] 91.2 123 [914,] 91.3 123 [915,] 91.4 123 [916,] 91.5 123 [917,] 91.6 123 [918,] 91.7 123 [919,] 91.8 123 [920,] 91.9 123 [921,] 92.0 122 [922,] 92.1 122 [923,] 92.2 122 [924,] 92.3 121 [925,] 92.4 121 [926,] 92.5 121 [927,] 92.6 121 [928,] 92.7 120 [929,] 92.8 119 [930,] 92.9 119 [931,] 93.0 119 [932,] 93.1 118 [933,] 93.2 118 [934,] 93.3 118 [935,] 93.4 118 [936,] 93.5 117 [937,] 93.6 117 [938,] 93.7 117 [939,] 93.8 117 [940,] 93.9 116 [941,] 94.0 116 [942,] 94.1 116 [943,] 94.2 115 [944,] 94.3 115 [945,] 94.4 114 [946,] 94.5 114 [947,] 94.6 114 [948,] 94.7 113 [949,] 94.8 113 [950,] 94.9 113 [951,] 95.0 113 [952,] 95.1 112 [953,] 95.2 112 [954,] 95.3 112 [955,] 95.4 111 [956,] 95.5 111 [957,] 95.6 111 [958,] 95.7 110 [959,] 95.8 110 [960,] 95.9 109 [961,] 96.0 109 [962,] 96.1 109 [963,] 96.2 108 [964,] 96.3 108 [965,] 96.4 108 [966,] 96.5 108 [967,] 96.6 107 [968,] 96.7 107 [969,] 96.8 107 [970,] 96.9 106 [971,] 97.0 105 [972,] 97.1 105 [973,] 97.2 105 [974,] 97.3 105 [975,] 97.4 104 [976,] 97.5 104 [977,] 97.6 104 [978,] 97.7 103 [979,] 97.8 103 [980,] 97.9 103 [981,] 98.0 103 [982,] 98.1 102 [983,] 98.2 102 [984,] 98.3 102 [985,] 98.4 101 [986,] 98.5 101 [987,] 98.6 100 [988,] 98.7 100 [989,] 98.8 99 [990,] 98.9 99 [991,] 99.0 99 [992,] 99.1 98 [993,] 99.2 98 [994,] 99.3 97 [995,] 99.4 97 [996,] 99.5 97 [997,] 99.6 96 [998,] 99.7 96 [999,] 99.8 96 [1000,] 99.9 95 [1001,] 100.0 95 [1002,] 100.1 95 [1003,] 100.2 95 [1004,] 100.3 95 [1005,] 100.4 94 [1006,] 100.5 94 [1007,] 100.6 94 [1008,] 100.7 93 [1009,] 100.8 93 [1010,] 100.9 93 [1011,] 101.0 93 [1012,] 101.1 92 [1013,] 101.2 92 [1014,] 101.3 91 [1015,] 101.4 91 [1016,] 101.5 92 [1017,] 101.6 92 [1018,] 101.7 91 [1019,] 101.8 91 [1020,] 101.9 91 [1021,] 102.0 91 [1022,] 102.1 90 [1023,] 102.2 90 [1024,] 102.3 90 [1025,] 102.4 89 [1026,] 102.5 89 [1027,] 102.6 89 [1028,] 102.7 88 [1029,] 102.8 88 [1030,] 102.9 88 [1031,] 103.0 87 [1032,] 103.1 87 [1033,] 103.2 87 [1034,] 103.3 86 [1035,] 103.4 86 [1036,] 103.5 86 [1037,] 103.6 86 [1038,] 103.7 86 [1039,] 103.8 86 [1040,] 103.9 85 [1041,] 104.0 85 [1042,] 104.1 85 [1043,] 104.2 85 [1044,] 104.3 85 [1045,] 104.4 84 [1046,] 104.5 84 [1047,] 104.6 84 [1048,] 104.7 83 [1049,] 104.8 82 [1050,] 104.9 82 [1051,] 105.0 82 [1052,] 105.1 82 [1053,] 105.2 81 [1054,] 105.3 81 [1055,] 105.4 80 [1056,] 105.5 80 [1057,] 105.6 80 [1058,] 105.7 80 [1059,] 105.8 80 [1060,] 105.9 80 [1061,] 106.0 79 [1062,] 106.1 79 [1063,] 106.2 79 [1064,] 106.3 79 [1065,] 106.4 79 [1066,] 106.5 79 [1067,] 106.6 79 [1068,] 106.7 79 [1069,] 106.8 78 [1070,] 106.9 78 [1071,] 107.0 78 [1072,] 107.1 77 [1073,] 107.2 77 [1074,] 107.3 77 [1075,] 107.4 77 [1076,] 107.5 76 [1077,] 107.6 76 [1078,] 107.7 75 [1079,] 107.8 75 [1080,] 107.9 75 [1081,] 108.0 75 [1082,] 108.1 75 [1083,] 108.2 74 [1084,] 108.3 74 [1085,] 108.4 74 [1086,] 108.5 74 [1087,] 108.6 74 [1088,] 108.7 74 [1089,] 108.8 73 [1090,] 108.9 73 [1091,] 109.0 73 [1092,] 109.1 73 [1093,] 109.2 73 [1094,] 109.3 72 [1095,] 109.4 72 [1096,] 109.5 72 [1097,] 109.6 72 [1098,] 109.7 72 [1099,] 109.8 72 [1100,] 109.9 71 [1101,] 110.0 71 [1102,] 110.1 71 [1103,] 110.2 71 [1104,] 110.3 70 [1105,] 110.4 71 [1106,] 110.5 71 [1107,] 110.6 70 [1108,] 110.7 70 [1109,] 110.8 70 [1110,] 110.9 70 [1111,] 111.0 70 [1112,] 111.1 70 [1113,] 111.2 70 [1114,] 111.3 70 [1115,] 111.4 69 [1116,] 111.5 68 [1117,] 111.6 68 [1118,] 111.7 68 [1119,] 111.8 68 [1120,] 111.9 67 [1121,] 112.0 67 [1122,] 112.1 67 [1123,] 112.2 67 [1124,] 112.3 67 [1125,] 112.4 67 [1126,] 112.5 67 [1127,] 112.6 67 [1128,] 112.7 66 [1129,] 112.8 66 [1130,] 112.9 66 [1131,] 113.0 65 [1132,] 113.1 65 [1133,] 113.2 65 [1134,] 113.3 65 [1135,] 113.4 65 [1136,] 113.5 65 [1137,] 113.6 65 [1138,] 113.7 65 [1139,] 113.8 64 [1140,] 113.9 64 [1141,] 114.0 64 [1142,] 114.1 64 [1143,] 114.2 63 [1144,] 114.3 63 [1145,] 114.4 62 [1146,] 114.5 62 [1147,] 114.6 61 [1148,] 114.7 60 [1149,] 114.8 59 [1150,] 114.9 59 $`7__OSL (NA)` [,1] [,2] [1,] 0 40 [2,] 50 40 $`8__OSL (NA)` [,1] [,2] [1,] 0.497 39.8 [2,] 0.997 39.8 [3,] 1.497 40.0 [4,] 1.997 40.1 [5,] 2.497 40.0 [6,] 2.997 40.0 [7,] 3.497 40.0 [8,] 3.997 40.1 [9,] 4.497 39.9 [10,] 4.997 40.0 [11,] 5.497 40.2 [12,] 5.997 40.0 [13,] 6.497 39.9 [14,] 6.997 40.1 [15,] 7.497 40.1 [16,] 7.997 39.9 [17,] 8.497 40.1 [18,] 8.997 40.1 [19,] 9.497 40.0 [20,] 9.997 40.0 [21,] 10.497 40.0 [22,] 10.997 40.0 [23,] 11.497 40.0 [24,] 11.997 39.9 [25,] 12.497 39.9 [26,] 12.997 40.0 [27,] 13.497 39.9 [28,] 13.997 40.0 [29,] 14.497 40.0 [30,] 14.997 40.0 [31,] 15.497 40.0 [32,] 15.997 40.0 [33,] 16.497 40.0 [34,] 16.997 40.0 [35,] 17.497 40.0 [36,] 17.997 40.0 [37,] 18.497 39.9 [38,] 18.997 40.0 [39,] 19.497 40.0 [40,] 19.997 40.0 [41,] 20.497 40.0 [42,] 20.997 40.1 [43,] 21.497 40.0 [44,] 21.997 39.9 [45,] 22.497 40.0 [46,] 22.997 40.1 [47,] 23.497 40.0 [48,] 23.997 40.0 [49,] 24.497 40.0 [50,] 24.997 39.9 [51,] 25.497 40.0 [52,] 25.997 40.0 [53,] 26.497 39.9 [54,] 26.997 39.9 [55,] 27.497 40.0 [56,] 27.997 40.0 [57,] 28.497 40.0 [58,] 28.997 39.9 [59,] 29.497 40.0 [60,] 29.997 40.0 [61,] 30.497 39.9 [62,] 30.997 40.0 [63,] 31.497 39.9 [64,] 31.997 40.0 [65,] 32.497 40.0 [66,] 32.997 40.0 [67,] 33.497 40.1 [68,] 33.997 40.1 [69,] 34.497 40.0 [70,] 34.997 40.0 [71,] 35.497 40.1 [72,] 35.997 40.0 [73,] 36.497 40.1 [74,] 36.997 40.1 [75,] 37.497 39.9 [76,] 37.997 39.9 [77,] 38.497 40.1 [78,] 38.997 40.1 [79,] 39.497 40.0 [80,] 39.997 40.0 [81,] 40.497 40.0 [82,] 40.997 40.0 [83,] 41.497 39.9 [84,] 41.997 39.9 [85,] 42.497 40.0 [86,] 42.997 40.0 [87,] 43.497 39.9 [88,] 43.997 39.9 [89,] 44.497 39.9 [90,] 44.997 39.9 [91,] 45.497 40.0 [92,] 45.997 40.0 [93,] 46.497 40.0 [94,] 46.997 40.1 [95,] 47.497 40.1 [96,] 47.997 40.0 [97,] 48.497 40.0 [98,] 48.997 40.0 [99,] 49.497 39.9 [100,] 49.997 39.9 [101,] 50.497 40.0 [102,] 50.997 20.0 [103,] 51.497 0.0 [104,] 51.997 0.0 [105,] 52.497 0.0 [106,] 52.997 0.0 [107,] 53.497 0.0 [108,] 53.997 0.0 [109,] 54.497 0.0 [110,] 54.997 0.0 [111,] 55.497 0.0 [112,] 55.997 0.0 [113,] 56.497 0.0 [114,] 56.997 0.0 [115,] 57.497 0.0 [116,] 57.997 0.0 [117,] 58.497 0.0 [118,] 58.997 0.0 [119,] 59.497 0.0 [120,] 59.997 0.0 [121,] 60.497 0.0 [122,] 60.997 0.0 [123,] 61.497 0.0 [124,] 61.997 0.0 [125,] 62.497 0.0 [126,] 62.997 0.0 [127,] 63.497 0.0 [128,] 63.997 0.0 [129,] 64.497 0.0 [130,] 64.997 0.0 [131,] 65.497 0.0 [132,] 65.997 0.0 [133,] 66.497 0.0 [134,] 66.997 0.0 [135,] 67.497 0.0 [136,] 67.997 0.0 [137,] 68.497 0.0 [138,] 68.997 0.0 [139,] 69.497 0.0 [140,] 69.997 0.0 [141,] 70.497 0.0 [142,] 70.997 0.0 [143,] 71.497 0.0 [144,] 71.997 0.0 [145,] 72.497 0.0 [146,] 72.997 0.0 [147,] 73.497 0.0 [148,] 73.997 0.0 [149,] 74.497 0.0 [150,] 74.997 0.0 $`9_irradiation (NA)` [,1] [,2] [1,] 0 1 [2,] 15 1 $`10_TL (UVVIS)` [,1] [,2] [1,] 0.1 46 [2,] 0.2 47 [3,] 0.3 35 [4,] 0.4 34 [5,] 0.5 30 [6,] 0.6 36 [7,] 0.7 40 [8,] 0.8 39 [9,] 0.9 37 [10,] 1.0 27 [11,] 1.1 36 [12,] 1.2 38 [13,] 1.3 35 [14,] 1.4 39 [15,] 1.5 34 [16,] 1.6 41 [17,] 1.7 31 [18,] 1.8 36 [19,] 1.9 43 [20,] 2.0 26 [21,] 2.1 32 [22,] 2.2 36 [23,] 2.3 46 [24,] 2.4 32 [25,] 2.5 31 [26,] 2.6 53 [27,] 2.7 35 [28,] 2.8 24 [29,] 2.9 26 [30,] 3.0 40 [31,] 3.1 35 [32,] 3.2 40 [33,] 3.3 42 [34,] 3.4 30 [35,] 3.5 49 [36,] 3.6 38 [37,] 3.7 34 [38,] 3.8 40 [39,] 3.9 26 [40,] 4.0 27 [41,] 4.1 42 [42,] 4.2 23 [43,] 4.3 32 [44,] 4.4 25 [45,] 4.5 35 [46,] 4.6 40 [47,] 4.7 41 [48,] 4.8 42 [49,] 4.9 34 [50,] 5.0 32 [51,] 5.1 44 [52,] 5.2 36 [53,] 5.3 32 [54,] 5.4 26 [55,] 5.5 27 [56,] 5.6 33 [57,] 5.7 48 [58,] 5.8 35 [59,] 5.9 30 [60,] 6.0 33 [61,] 6.1 34 [62,] 6.2 36 [63,] 6.3 27 [64,] 6.4 32 [65,] 6.5 42 [66,] 6.6 26 [67,] 6.7 35 [68,] 6.8 28 [69,] 6.9 32 [70,] 7.0 21 [71,] 7.1 27 [72,] 7.2 27 [73,] 7.3 25 [74,] 7.4 32 [75,] 7.5 34 [76,] 7.6 28 [77,] 7.7 18 [78,] 7.8 20 [79,] 7.9 20 [80,] 8.0 36 [81,] 8.1 29 [82,] 8.2 26 [83,] 8.3 30 [84,] 8.4 31 [85,] 8.5 30 [86,] 8.6 20 [87,] 8.7 25 [88,] 8.8 23 [89,] 8.9 28 [90,] 9.0 24 [91,] 9.1 26 [92,] 9.2 25 [93,] 9.3 23 [94,] 9.4 19 [95,] 9.5 24 [96,] 9.6 22 [97,] 9.7 20 [98,] 9.8 28 [99,] 9.9 23 [100,] 10.0 24 [101,] 10.1 20 [102,] 10.2 26 [103,] 10.3 24 [104,] 10.4 35 [105,] 10.5 31 [106,] 10.6 29 [107,] 10.7 23 [108,] 10.8 29 [109,] 10.9 24 [110,] 11.0 18 [111,] 11.1 34 [112,] 11.2 12 [113,] 11.3 23 [114,] 11.4 19 [115,] 11.5 33 [116,] 11.6 32 [117,] 11.7 30 [118,] 11.8 22 [119,] 11.9 24 [120,] 12.0 29 [121,] 12.1 33 [122,] 12.2 37 [123,] 12.3 30 [124,] 12.4 30 [125,] 12.5 25 [126,] 12.6 33 [127,] 12.7 21 [128,] 12.8 28 [129,] 12.9 19 [130,] 13.0 25 [131,] 13.1 28 [132,] 13.2 29 [133,] 13.3 22 [134,] 13.4 29 [135,] 13.5 19 [136,] 13.6 13 [137,] 13.7 28 [138,] 13.8 18 [139,] 13.9 24 [140,] 14.0 20 [141,] 14.1 30 [142,] 14.2 37 [143,] 14.3 19 [144,] 14.4 23 [145,] 14.5 21 [146,] 14.6 27 [147,] 14.7 20 [148,] 14.8 21 [149,] 14.9 25 [150,] 15.0 29 [151,] 15.1 28 [152,] 15.2 38 [153,] 15.3 27 [154,] 15.4 36 [155,] 15.5 31 [156,] 15.6 25 [157,] 15.7 19 [158,] 15.8 29 [159,] 15.9 24 [160,] 16.0 17 [161,] 16.1 19 [162,] 16.2 37 [163,] 16.3 33 [164,] 16.4 30 [165,] 16.5 31 [166,] 16.6 34 [167,] 16.7 39 [168,] 16.8 35 [169,] 16.9 20 [170,] 17.0 42 [171,] 17.1 27 [172,] 17.2 30 [173,] 17.3 28 [174,] 17.4 25 [175,] 17.5 21 [176,] 17.6 17 [177,] 17.7 35 [178,] 17.8 34 [179,] 17.9 24 [180,] 18.0 27 [181,] 18.1 29 [182,] 18.2 38 [183,] 18.3 32 [184,] 18.4 40 [185,] 18.5 37 [186,] 18.6 27 [187,] 18.7 36 [188,] 18.8 41 [189,] 18.9 45 [190,] 19.0 53 [191,] 19.1 41 [192,] 19.2 51 [193,] 19.3 49 [194,] 19.4 48 [195,] 19.5 43 [196,] 19.6 40 [197,] 19.7 41 [198,] 19.8 47 [199,] 19.9 44 [200,] 20.0 44 [201,] 20.1 41 [202,] 20.2 43 [203,] 20.3 44 [204,] 20.4 50 [205,] 20.5 46 [206,] 20.6 45 [207,] 20.7 61 [208,] 20.8 43 [209,] 20.9 62 [210,] 21.0 50 [211,] 21.1 48 [212,] 21.2 39 [213,] 21.3 44 [214,] 21.4 68 [215,] 21.5 56 [216,] 21.6 60 [217,] 21.7 56 [218,] 21.8 64 [219,] 21.9 60 [220,] 22.0 65 [221,] 22.1 54 [222,] 22.2 52 [223,] 22.3 58 [224,] 22.4 51 [225,] 22.5 58 [226,] 22.6 55 [227,] 22.7 57 [228,] 22.8 50 [229,] 22.9 59 [230,] 23.0 73 [231,] 23.1 65 [232,] 23.2 69 [233,] 23.3 72 [234,] 23.4 66 [235,] 23.5 63 [236,] 23.6 71 [237,] 23.7 76 [238,] 23.8 76 [239,] 23.9 64 [240,] 24.0 76 [241,] 24.1 78 [242,] 24.2 78 [243,] 24.3 68 [244,] 24.4 76 [245,] 24.5 77 [246,] 24.6 79 [247,] 24.7 86 [248,] 24.8 78 [249,] 24.9 80 [250,] 25.0 97 [251,] 25.1 74 [252,] 25.2 108 [253,] 25.3 76 [254,] 25.4 81 [255,] 25.5 100 [256,] 25.6 101 [257,] 25.7 106 [258,] 25.8 112 [259,] 25.9 92 [260,] 26.0 129 [261,] 26.1 105 [262,] 26.2 121 [263,] 26.3 99 [264,] 26.4 109 [265,] 26.5 129 [266,] 26.6 127 [267,] 26.7 117 [268,] 26.8 119 [269,] 26.9 143 [270,] 27.0 152 [271,] 27.1 143 [272,] 27.2 122 [273,] 27.3 122 [274,] 27.4 128 [275,] 27.5 155 [276,] 27.6 156 [277,] 27.7 140 [278,] 27.8 163 [279,] 27.9 158 [280,] 28.0 172 [281,] 28.1 154 [282,] 28.2 163 [283,] 28.3 161 [284,] 28.4 168 [285,] 28.5 172 [286,] 28.6 184 [287,] 28.7 195 [288,] 28.8 179 [289,] 28.9 181 [290,] 29.0 224 [291,] 29.1 214 [292,] 29.2 187 [293,] 29.3 209 [294,] 29.4 200 [295,] 29.5 211 [296,] 29.6 202 [297,] 29.7 202 [298,] 29.8 210 [299,] 29.9 226 [300,] 30.0 222 [301,] 30.1 243 [302,] 30.2 227 [303,] 30.3 218 [304,] 30.4 229 [305,] 30.5 259 [306,] 30.6 222 [307,] 30.7 269 [308,] 30.8 257 [309,] 30.9 267 [310,] 31.0 244 [311,] 31.1 265 [312,] 31.2 260 [313,] 31.3 301 [314,] 31.4 245 [315,] 31.5 296 [316,] 31.6 280 [317,] 31.7 277 [318,] 31.8 296 [319,] 31.9 308 [320,] 32.0 303 [321,] 32.1 277 [322,] 32.2 304 [323,] 32.3 312 [324,] 32.4 342 [325,] 32.5 282 [326,] 32.6 324 [327,] 32.7 367 [328,] 32.8 336 [329,] 32.9 339 [330,] 33.0 356 [331,] 33.1 355 [332,] 33.2 392 [333,] 33.3 322 [334,] 33.4 323 [335,] 33.5 362 [336,] 33.6 380 [337,] 33.7 403 [338,] 33.8 400 [339,] 33.9 400 [340,] 34.0 416 [341,] 34.1 400 [342,] 34.2 422 [343,] 34.3 439 [344,] 34.4 464 [345,] 34.5 435 [346,] 34.6 432 [347,] 34.7 436 [348,] 34.8 408 [349,] 34.9 406 [350,] 35.0 446 [351,] 35.1 498 [352,] 35.2 414 [353,] 35.3 418 [354,] 35.4 428 [355,] 35.5 462 [356,] 35.6 445 [357,] 35.7 493 [358,] 35.8 446 [359,] 35.9 456 [360,] 36.0 416 [361,] 36.1 457 [362,] 36.2 517 [363,] 36.3 491 [364,] 36.4 463 [365,] 36.5 450 [366,] 36.6 495 [367,] 36.7 447 [368,] 36.8 484 [369,] 36.9 488 [370,] 37.0 498 [371,] 37.1 518 [372,] 37.2 467 [373,] 37.3 506 [374,] 37.4 502 [375,] 37.5 469 [376,] 37.6 530 [377,] 37.7 542 [378,] 37.8 522 [379,] 37.9 482 [380,] 38.0 465 [381,] 38.1 452 [382,] 38.2 469 [383,] 38.3 497 [384,] 38.4 478 [385,] 38.5 469 [386,] 38.6 523 [387,] 38.7 484 [388,] 38.8 468 [389,] 38.9 488 [390,] 39.0 555 [391,] 39.1 469 [392,] 39.2 455 [393,] 39.3 484 [394,] 39.4 493 [395,] 39.5 440 [396,] 39.6 430 [397,] 39.7 464 [398,] 39.8 438 [399,] 39.9 462 [400,] 40.0 427 [401,] 40.1 415 [402,] 40.2 395 [403,] 40.3 439 [404,] 40.4 424 [405,] 40.5 401 [406,] 40.6 421 [407,] 40.7 390 [408,] 40.8 396 [409,] 40.9 404 [410,] 41.0 363 [411,] 41.1 326 [412,] 41.2 344 [413,] 41.3 372 [414,] 41.4 342 [415,] 41.5 370 [416,] 41.6 358 [417,] 41.7 339 [418,] 41.8 326 [419,] 41.9 310 [420,] 42.0 271 [421,] 42.1 281 [422,] 42.2 297 [423,] 42.3 318 [424,] 42.4 311 [425,] 42.5 245 [426,] 42.6 267 [427,] 42.7 227 [428,] 42.8 226 [429,] 42.9 225 [430,] 43.0 192 [431,] 43.1 218 [432,] 43.2 226 [433,] 43.3 217 [434,] 43.4 200 [435,] 43.5 200 [436,] 43.6 194 [437,] 43.7 181 [438,] 43.8 180 [439,] 43.9 152 [440,] 44.0 187 [441,] 44.1 152 [442,] 44.2 158 [443,] 44.3 162 [444,] 44.4 131 [445,] 44.5 149 [446,] 44.6 115 [447,] 44.7 119 [448,] 44.8 112 [449,] 44.9 105 [450,] 45.0 107 [451,] 45.1 82 [452,] 45.2 114 [453,] 45.3 87 [454,] 45.4 87 [455,] 45.5 98 [456,] 45.6 76 [457,] 45.7 94 [458,] 45.8 80 [459,] 45.9 85 [460,] 46.0 65 [461,] 46.1 76 [462,] 46.2 71 [463,] 46.3 54 [464,] 46.4 53 [465,] 46.5 57 [466,] 46.6 49 [467,] 46.7 46 [468,] 46.8 35 [469,] 46.9 39 [470,] 47.0 37 [471,] 47.1 36 [472,] 47.2 41 [473,] 47.3 36 [474,] 47.4 25 [475,] 47.5 35 [476,] 47.6 28 [477,] 47.7 46 [478,] 47.8 27 [479,] 47.9 26 [480,] 48.0 25 [481,] 48.1 20 [482,] 48.2 25 [483,] 48.3 31 [484,] 48.4 29 [485,] 48.5 32 [486,] 48.6 38 [487,] 48.7 26 [488,] 48.8 19 [489,] 48.9 28 [490,] 49.0 24 [491,] 49.1 27 [492,] 49.2 32 [493,] 49.3 19 [494,] 49.4 11 [495,] 49.5 23 [496,] 49.6 14 [497,] 49.7 27 [498,] 49.8 25 [499,] 49.9 14 [500,] 50.0 17 [501,] 50.1 17 [502,] 50.2 19 [503,] 50.3 20 [504,] 50.4 19 [505,] 50.5 27 [506,] 50.6 26 [507,] 50.7 23 [508,] 50.8 28 [509,] 50.9 18 [510,] 51.0 25 [511,] 51.1 22 [512,] 51.2 18 [513,] 51.3 21 [514,] 51.4 17 [515,] 51.5 19 [516,] 51.6 11 [517,] 51.7 21 [518,] 51.8 20 [519,] 51.9 17 [520,] 52.0 20 [521,] 52.1 28 [522,] 52.2 10 [523,] 52.3 21 [524,] 52.4 16 [525,] 52.5 21 [526,] 52.6 29 [527,] 52.7 25 [528,] 52.8 17 [529,] 52.9 17 [530,] 53.0 24 [531,] 53.1 13 [532,] 53.2 23 [533,] 53.3 26 [534,] 53.4 27 [535,] 53.5 20 [536,] 53.6 31 [537,] 53.7 18 [538,] 53.8 23 [539,] 53.9 16 [540,] 54.0 15 [541,] 54.1 33 [542,] 54.2 9 [543,] 54.3 24 [544,] 54.4 26 [545,] 54.5 30 [546,] 54.6 23 [547,] 54.7 17 [548,] 54.8 10 [549,] 54.9 20 [550,] 55.0 15 [551,] 55.1 18 [552,] 55.2 14 [553,] 55.3 19 [554,] 55.4 24 [555,] 55.5 21 [556,] 55.6 15 [557,] 55.7 20 [558,] 55.8 21 [559,] 55.9 14 [560,] 56.0 22 [561,] 56.1 26 [562,] 56.2 18 [563,] 56.3 25 [564,] 56.4 17 [565,] 56.5 22 [566,] 56.6 20 [567,] 56.7 14 [568,] 56.8 16 [569,] 56.9 20 [570,] 57.0 15 [571,] 57.1 23 [572,] 57.2 15 [573,] 57.3 14 [574,] 57.4 27 [575,] 57.5 14 [576,] 57.6 17 [577,] 57.7 17 [578,] 57.8 23 [579,] 57.9 23 [580,] 58.0 26 [581,] 58.1 27 [582,] 58.2 25 [583,] 58.3 18 [584,] 58.4 17 [585,] 58.5 21 [586,] 58.6 24 [587,] 58.7 16 [588,] 58.8 18 [589,] 58.9 16 [590,] 59.0 23 [591,] 59.1 17 [592,] 59.2 25 [593,] 59.3 17 [594,] 59.4 17 [595,] 59.5 21 [596,] 59.6 22 [597,] 59.7 17 [598,] 59.8 20 [599,] 59.9 13 [600,] 60.0 34 [601,] 60.1 30 [602,] 60.2 6 [603,] 60.3 20 [604,] 60.4 12 [605,] 60.5 14 [606,] 60.6 16 [607,] 60.7 20 [608,] 60.8 20 [609,] 60.9 21 [610,] 61.0 29 [611,] 61.1 11 [612,] 61.2 13 [613,] 61.3 13 [614,] 61.4 20 [615,] 61.5 27 [616,] 61.6 4 [617,] 61.7 22 [618,] 61.8 18 [619,] 61.9 20 [620,] 62.0 21 [621,] 62.1 20 [622,] 62.2 14 [623,] 62.3 17 [624,] 62.4 23 [625,] 62.5 22 [626,] 62.6 13 [627,] 62.7 12 [628,] 62.8 26 [629,] 62.9 14 [630,] 63.0 22 [631,] 63.1 30 [632,] 63.2 18 [633,] 63.3 18 [634,] 63.4 16 [635,] 63.5 12 [636,] 63.6 18 [637,] 63.7 14 [638,] 63.8 31 [639,] 63.9 11 [640,] 64.0 19 [641,] 64.1 14 [642,] 64.2 25 [643,] 64.3 15 [644,] 64.4 17 [645,] 64.5 12 [646,] 64.6 14 [647,] 64.7 10 [648,] 64.8 14 [649,] 64.9 14 [650,] 65.0 19 [651,] 65.1 27 [652,] 65.2 16 [653,] 65.3 16 [654,] 65.4 20 [655,] 65.5 17 [656,] 65.6 16 [657,] 65.7 18 [658,] 65.8 25 [659,] 65.9 10 [660,] 66.0 16 [661,] 66.1 31 [662,] 66.2 12 [663,] 66.3 19 [664,] 66.4 14 [665,] 66.5 10 [666,] 66.6 11 [667,] 66.7 12 [668,] 66.8 11 [669,] 66.9 30 [670,] 67.0 16 [671,] 67.1 11 [672,] 67.2 15 [673,] 67.3 12 [674,] 67.4 13 [675,] 67.5 26 [676,] 67.6 7 [677,] 67.7 10 [678,] 67.8 18 [679,] 67.9 18 [680,] 68.0 22 > > ## Not run: > ##D ##select your BIN-file > ##D file <- file.choose() > ##D > ##D ##convert > ##D convert_XSYG2CSV(file) > ##D > ## End(Not run) > > > > > cleanEx() > nameEx("correct_PMTLinearity") > ### * correct_PMTLinearity > > flush(stderr()); flush(stdout()) > > ### Name: correct_PMTLinearity > ### Title: Dead-time (linearity) Correction for Photomultiplier tubes (PMT) > ### Aliases: correct_PMTLinearity > ### Keywords: manip > > ### ** Examples > > o <- set_RLum("RLum.Data.Curve") > correct_PMTLinearity(o, PMT_pulse_pair_resolution = 10) [RLum.Data.Curve-class] recordType: NA curveType: NA measured values: 1 .. range of x-values: 0 0 .. range of y-values: 0 0 additional info elements: 0 > > > > > cleanEx() > nameEx("dot-as.latex.table") > ### * dot-as.latex.table > > flush(stderr()); flush(stdout()) > > ### Name: .as.latex.table > ### Title: Create LaTeX tables from data.frames and RLum objects > ### Aliases: .as.latex.table > ### Keywords: internal > > ### ** Examples > > df <- data.frame(x = 1:10, y = letters[1:10]) > .as.latex.table(df) % add usepackage{adjustbox} to latex preamble \begin{table}[ht] \centering \begin{adjustbox}{max width=\textwidth} \begin{tabular}{cc} \hline \multicolumn{1}{p{2cm}}{\centering x } & \multicolumn{1}{p{2cm}}{\centering y }\\ \hline 1.000 & a \\ 2.000 & b \\ 3.000 & c \\ 4.000 & d \\ 5.000 & e \\ 6.000 & f \\ 7.000 & g \\ 8.000 & h \\ 9.000 & i \\ 10.000 & j \\ \hline \end{tabular} \end{adjustbox} \end{table}> .as.latex.table(df, pos = "lr") % add usepackage{adjustbox} to latex preamble \begin{table}[ht] \centering \begin{adjustbox}{max width=\textwidth} \begin{tabular}{lr} \hline \multicolumn{1}{p{2cm}}{\centering x } & \multicolumn{1}{p{2cm}}{\centering y }\\ \hline 1.000 & a \\ 2.000 & b \\ 3.000 & c \\ 4.000 & d \\ 5.000 & e \\ 6.000 & f \\ 7.000 & g \\ 8.000 & h \\ 9.000 & i \\ 10.000 & j \\ \hline \end{tabular} \end{adjustbox} \end{table}> .as.latex.table(df, select = "y", pos = "r") % add usepackage{adjustbox} to latex preamble \begin{table}[ht] \centering \begin{adjustbox}{max width=\textwidth} \begin{tabular}{r} \hline \multicolumn{1}{p{2cm}}{\centering y }\\ \hline a \\ b \\ c \\ d \\ e \\ f \\ g \\ h \\ i \\ j \\ \hline \end{tabular} \end{adjustbox} \end{table}> > > > > cleanEx() > nameEx("extract_IrradiationTimes") > ### * extract_IrradiationTimes > > flush(stderr()); flush(stdout()) > > ### Name: extract_IrradiationTimes > ### Title: Extract Irradiation Times from an XSYG-file or 'RLum.Analysis' > ### object > ### Aliases: extract_IrradiationTimes > ### Keywords: IO manip > > ### ** Examples > > ## take system file > xsyg <- system.file("extdata/XSYG_file.xsyg", package="Luminescence") > > ## the import is automatically > ## but you can import it before > irr_times <- extract_IrradiationTimes(xsyg) [read_XSYG2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: XSYG_file.xsyg | | | 0% | |======================================================================| 100% >> 1 of 1 sequence(s) loaded successfully > irr_times$irr.times POSITION STEP START DURATION.STEP 1 1 TL (UVVIS) 2016-02-24 15:51:23 57.0 2 1 OSL (UVVIS) 2016-02-24 15:53:24 129.9 3 1 irradiation (NA) 2016-02-24 15:57:45 80.0 4 1 TL (UVVIS) 2016-02-24 15:58:02 37.0 END IRR_TIME TIMESINCEIRR TIMESINCELAST.STEP 1 2016-02-24 15:52:20 0 -1 0.0 2 2016-02-24 15:55:33 0 -1 64.0 3 2016-02-24 15:59:05 0 -1 131.1 4 2016-02-24 15:58:39 80 -63 -63.0 > > ## Not run: > ##D # (1) - example for your own data > ##D > ##D # set files and run function > ##D file.XSYG <- file.choose() > ##D file.BINX <- file.choose() > ##D > ##D extract_IrradiationTimes(file.XSYG = file.XSYG, file.BINX = file.BINX) > ##D > ##D # export results additionally to a CSV-file in the same directory as the XSYG-file > ##D write.table(x = get_RLum(output), > ##D file = paste0(file.BINX,"_extract_IrradiationTimes.csv"), > ##D sep = ";", > ##D row.names = FALSE) > ## End(Not run) > > > > > cleanEx() > nameEx("extract_ROI") > ### * extract_ROI > > flush(stderr()); flush(stdout()) > > ### Name: extract_ROI > ### Title: Extract Pixel Values through Circular Region-of-Interests (ROI) > ### from an Image > ### Aliases: extract_ROI > ### Keywords: manip > > ### ** Examples > > > m <- matrix(runif(100,0,255), ncol = 10, nrow = 10) > roi <- matrix(c(2.,4,2,5,6,7,3,1,1), ncol = 3) > extract_ROI(object = m, roi = roi, plot = TRUE) [RLum.Results-class] originator: extract_ROI() data: 3 .. $roi_signals : list .. $roi_summary : matrix .. $roi_coord : matrix additional info elements: 1 > > > > > cleanEx() > nameEx("fit_CWCurve") > ### * fit_CWCurve > > flush(stderr()); flush(stdout()) > > ### Name: fit_CWCurve > ### Title: Non-linear Least Squares Fit for CW-OSL curves -beta version- > ### Aliases: fit_CWCurve > ### Keywords: dplot models > > ### ** Examples > > > ##load data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ##fit data > fit <- fit_CWCurve(ExampleData.CW_OSL_Curve, + main = "CW Curve Fit", + n.components.max = 4, + log = "x") [fit_CWCurve()] Fitting was finally done using a 3-component function (max=4): ------------------------------------------------------------------------------ y ~ I0.1 * lambda.1 * exp(-lambda.1 * x) + I0.2 * lambda.2 * exp(-lambda.2 * x) + I0.3 * lambda.3 * exp(-lambda.3 * x) I0 I0.error lambda lambda.error cs cs.rel c1 2387.608 NA 4.5905460 NA 5.389404e-17 1.0000 c2 1053.500 NA 1.9593744 NA 2.300349e-17 0.4268 c3 2816.625 NA 0.0205474 NA 2.412310e-19 0.0045 ------------------------------------------------------------------------------ pseudo-R^2 = 0.9995 > > > > > cleanEx() > nameEx("fit_DoseResponseCurve") > ### * fit_DoseResponseCurve > > flush(stderr()); flush(stdout()) > > ### Name: fit_DoseResponseCurve > ### Title: Fit a dose-response curve for luminescence data (Lx/Tx against > ### dose) > ### Aliases: fit_DoseResponseCurve > > ### ** Examples > > > ##(1) fit growth curve for a dummy data.set and show De value > data(ExampleData.LxTxData, envir = environment()) > temp <- fit_DoseResponseCurve(LxTxData) [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07 > get_RLum(temp) De De.Error D01 D01.ERROR D02 D02.ERROR R R.ERROR Dc D63 1 1737.881 59.68123 1766.074 92.38736 NA NA NA NA NA NA n_N De.MC Fit Mode HPDI68_L HPDI68_U HPDI95_L HPDI95_U 1 0.5271352 1738.478 EXP interpolation 1674.495 1795.255 1622.275 1872.77 .De.plot .De.raw 1 1737.881 1737.881 > > ##(1b) to access the fitting value try > get_RLum(temp, data.object = "Fit") Nonlinear regression model model: y ~ a * (1 - exp(-(x + c)/b)) data: data a b c 6.806 1766.074 5.051 weighted residual sum-of-squares: 0.0004268 Number of iterations to convergence: 4 Achieved convergence tolerance: 1.49e-08 > > ##(2) fit using the 'extrapolation' mode > LxTxData[1,2:3] <- c(0.5, 0.001) > print(fit_DoseResponseCurve(LxTxData, mode = "extrapolation")) [fit_DoseResponseCurve()] Fit: EXP (extrapolation) | De = 109.74 | D01 = 2624.06 [RLum.Results-class] originator: fit_DoseResponseCurve() data: 5 .. $De : data.frame .. $De.MC : numeric .. $Fit : nls .. $Fit.Args : list .. $Formula : expression additional info elements: 2 > > ##(3) fit using the 'alternate' mode > LxTxData[1,2:3] <- c(0.5, 0.001) > print(fit_DoseResponseCurve(LxTxData, mode = "alternate")) [fit_DoseResponseCurve()] Fit: EXP (alternate) | De = NA | D01 = 2624.06 [RLum.Results-class] originator: fit_DoseResponseCurve() data: 5 .. $De : data.frame .. $De.MC : numeric .. $Fit : nls .. $Fit.Args : list .. $Formula : expression additional info elements: 2 > > ##(4) import and fit test data set by Berger & Huntley 1989 > QNL84_2_unbleached <- + read.table(system.file("extdata/QNL84_2_unbleached.txt", package = "Luminescence")) > > results <- fit_DoseResponseCurve( + QNL84_2_unbleached, + mode = "extrapolation", + verbose = FALSE) Warning: [fit_DoseResponseCurve()] Error column invalid or 0, 'fit.weights' ignored > > #calculate confidence interval for the parameters > #as alternative error estimation > confint(results$Fit, level = 0.68) Waiting for profiling to be done... 16% 84% a 140543.3024 146731.8471 b 374.0861 425.5679 c 116.3499 133.3474 > > ## Not run: > ##D ##(5) special case the OTORX model with test dose column > ##D df <- cbind(LxTxData, Test_Dose = 15) > ##D fit_DoseResponseCurve(object = df, fit.method = "OTORX", n.MC = 10) |> > ##D plot_DoseResponseCurve() > ##D > ##D QNL84_2_bleached <- > ##D read.table(system.file("extdata/QNL84_2_bleached.txt", package = "Luminescence")) > ##D STRB87_1_unbleached <- > ##D read.table(system.file("extdata/STRB87_1_unbleached.txt", package = "Luminescence")) > ##D STRB87_1_bleached <- > ##D read.table(system.file("extdata/STRB87_1_bleached.txt", package = "Luminescence")) > ##D > ##D print( > ##D fit_DoseResponseCurve( > ##D QNL84_2_bleached, > ##D mode = "alternate", > ##D verbose = FALSE)$Fit) > ##D > ##D print( > ##D fit_DoseResponseCurve( > ##D STRB87_1_unbleached, > ##D mode = "alternate", > ##D verbose = FALSE)$Fit) > ##D > ##D print( > ##D fit_DoseResponseCurve( > ##D STRB87_1_bleached, > ##D mode = "alternate", > ##D verbose = FALSE)$Fit) > ##D > ## End(Not run) > > > > > cleanEx() > nameEx("fit_EmissionSpectra") > ### * fit_EmissionSpectra > > flush(stderr()); flush(stdout()) > > ### Name: fit_EmissionSpectra > ### Title: Luminescence Emission Spectra Deconvolution > ### Aliases: fit_EmissionSpectra > ### Keywords: datagen > > ### ** Examples > > > ##load example data > data(ExampleData.XSYG, envir = environment()) > > ##subtract background > TL.Spectrum@data <- TL.Spectrum@data[] - TL.Spectrum@data[,15] > > results <- fit_EmissionSpectra( + object = TL.Spectrum, + frame = 5, + method_control = list(max.runs = 10) + ) [fit_EmissionSpectra()] >> Treating dataset >> 5 << >> Wavelength scale detected ... >> Wavelength to energy scale conversion ... [OK] >> Searching components ... [-] >> Searching components ... [\] >> Searching components ... [/] >> Searching components ... [/] >> Searching components ... [-] >> Searching components ... [-] >> Searching components ... [-] >> Searching components ... [-] >> Searching components ... [-] >> Searching components ... [-] >> Searching components ... [OK] >> Fitting results (1 component model): ------------------------------------------------------------------------- mu SE(mu) sigma SE(sigma) C SE(C) [1,] 2.578402 0.006163982 0.3748339 0.005834778 0.7750762 0.01085087 ------------------------------------------------------------------------- SE: standard error | SSR: 2.164e+01| R^2: 0.807 | R^2_adj: 0.1938 (use the output in $fit for a more detailed analysis) > > ##deconvolution of a TL spectrum > ## Not run: > ##D > ##D ##load example data > ##D > ##D ##replace 0 values > ##D results <- fit_EmissionSpectra( > ##D object = TL.Spectrum, > ##D frame = 5, main = "TL spectrum" > ##D ) > ##D > ## End(Not run) > > > > > cleanEx() > nameEx("fit_LMCurve") > ### * fit_LMCurve > > flush(stderr()); flush(stdout()) > > ### Name: fit_LMCurve > ### Title: Non-linear Least Squares Fit for LM-OSL curves > ### Aliases: fit_LMCurve > ### Keywords: dplot models > > ### ** Examples > > > ##(1) fit LM data without background subtraction > data(ExampleData.FittingLM, envir = environment()) > fit_LMCurve(values.curve, n.components = 3, log = "x") [fit_LMCurve()] Fitting was done using a 3-component function: xm.1 xm.2 xm.3 Im.1 Im.2 Im.3 56.18245 1449.72373 7878.17725 202.76713 367.30182 639.20926 (equation used for fitting according to Kitis & Pagonis, 2008) ------------------------------------------------------------------------------ (1) Corresponding values according to the equation in Bulur, 1996 for b and n0: b1 = 1.267239e+00 ± NA n01 = 1.878216e+04 ± NA b2 = 1.903222e-03 ± NA n02 = 8.779213e+05 ± NA b3 = 6.444786e-05 ± NA n03 = 8.302637e+06 ± NA cs from component.1 = 1.488e-17 cm^2 >> relative: 1 cs from component.2 = 2.234e-20 cm^2 >> relative: 0.0015 cs from component.3 = 7.566e-22 cm^2 >> relative: 1e-04 (stimulation intensity value used for calculation: 8.517725e+16 1/s 1/cm^2) (errors quoted as 1-sigma uncertainties) ------------------------------------------------------------------------------ pseudo-R^2 = 0.9557 [RLum.Results-class] originator: fit_LMCurve() data: 4 .. $data : data.frame .. $fit : nls .. $component_matrix : matrix .. $component.contribution.matrix : list additional info elements: 1 > > ##(2) fit LM data with background subtraction and export as JPEG > ## -alter file path for your preferred system > ##jpeg(file = "~/Desktop/Fit_Output%03d.jpg", quality = 100, > ## height = 3000, width = 3000, res = 300) > data(ExampleData.FittingLM, envir = environment()) > fit_LMCurve(values.curve, object.bg = values.curveBG, + n.components = 2, log = "x", plot.BG = TRUE) [fit_LMCurve()] >> Background subtracted (method = 'polynomial') [fit_LMCurve()] Fitting was done using a 2-component function: xm.1 xm.2 Im.1 Im.2 53.32213 1587.57212 176.74173 406.89921 (equation used for fitting according to Kitis & Pagonis, 2008) ------------------------------------------------------------------------------ (1) Corresponding values according to the equation in Bulur, 1996 for b and n0: b1 = 1.406841e+00 ± NA n01 = 1.553795e+04 ± NA b2 = 1.587059e-03 ± NA n02 = 1.065044e+06 ± NA cs from component.1 = 1.652e-17 cm^2 >> relative: 1 cs from component.2 = 1.863e-20 cm^2 >> relative: 0.0011 (stimulation intensity value used for calculation: 8.517725e+16 1/s 1/cm^2) (errors quoted as 1-sigma uncertainties) ------------------------------------------------------------------------------ pseudo-R^2 = 0.9417 [RLum.Results-class] originator: fit_LMCurve() data: 4 .. $data : data.frame .. $fit : nls .. $component_matrix : matrix .. $component.contribution.matrix : list additional info elements: 1 > ##dev.off() > > ##(3) fit LM data with manual start parameters > data(ExampleData.FittingLM, envir = environment()) > fit_LMCurve(values.curve, + object.bg = values.curveBG, + n.components = 3, + log = "x", + start_values = data.frame(Im = c(170,25,400), xm = c(56,200,1500))) [fit_LMCurve()] >> Background subtracted (method = 'polynomial') [fit_LMCurve()] Fitting was done using a 3-component function: xm.1 xm.2 xm.3 Im.1 Im.2 Im.3 49.00545 204.36331 1591.66339 169.43746 23.01060 405.46209 (equation used for fitting according to Kitis & Pagonis, 2008) ------------------------------------------------------------------------------ (1) Corresponding values according to the equation in Bulur, 1996 for b and n0: b1 = 1.665602e+00 ± NA n01 = 1.368992e+04 ± NA b2 = 9.577543e-02 ± NA n02 = 7.753149e+03 ± NA b3 = 1.578911e-03 ± NA n03 = 1.064017e+06 ± NA cs from component.1 = 1.955e-17 cm^2 >> relative: 1 cs from component.2 = 1.124e-18 cm^2 >> relative: 0.0575 cs from component.3 = 1.854e-20 cm^2 >> relative: 9e-04 (stimulation intensity value used for calculation: 8.517725e+16 1/s 1/cm^2) (errors quoted as 1-sigma uncertainties) ------------------------------------------------------------------------------ pseudo-R^2 = 0.9437 [RLum.Results-class] originator: fit_LMCurve() data: 4 .. $data : data.frame .. $fit : nls .. $component_matrix : matrix .. $component.contribution.matrix : list additional info elements: 1 > > > > > cleanEx() > nameEx("fit_OSLLifeTimes") > ### * fit_OSLLifeTimes > > flush(stderr()); flush(stdout()) > > ### Name: fit_OSLLifeTimes > ### Title: Fitting and Deconvolution of OSL Lifetime Components > ### Aliases: fit_OSLLifeTimes > > ### ** Examples > > > ##load example data > data(ExampleData.TR_OSL, envir = environment()) > > ##fit lifetimes (short run) > fit_OSLLifeTimes( + object = ExampleData.TR_OSL, + n.components = 1) [fit_OSLLifeTime()] (1) Start parameter and component adapation ---------------------(start adaption)------------------------------------ >> + adaption for 1 comp. : Inf (calc.) <> 3 (ref.) >> [add comp.] >> [forced stop] ---------------------(end adaption)-------------------------------------- >> Applied component matrix A tau Comp.1 2.118737e+12 87.9146 (2) Fitting results (sorted by ascending tau) ------------------------------------------------------------------------- Estimate Std. Error t value Pr(>|t|) A.1 2.118737e+10 9.710554e+07 218.18915 0.000000e+00 tau.1 8.791461e+01 3.167935e+00 27.75139 1.196541e-143 ------------------------------------------------------------------------- (3) Further information ------------------------------------------------------------------------- Photon count sum: 3.831e+13 Durbin-Watson residual statistic: 0.77 [ <> ] [RLum.Results-class] originator: fit_OSLLifeTimes() data: 4 .. $data : matrix .. $start_matrix : matrix .. $total_counts : numeric .. $fit : nls additional info elements: 1 > > ##long example > ## Not run: > ##D fit_OSLLifeTimes( > ##D object = ExampleData.TR_OSL) > ## End(Not run) > > > > > cleanEx() > nameEx("fit_SurfaceExposure") > ### * fit_SurfaceExposure > > flush(stderr()); flush(stdout()) > > ### Name: fit_SurfaceExposure > ### Title: Nonlinear Least Squares Fit for OSL surface exposure data > ### Aliases: fit_SurfaceExposure > ### Keywords: datagen > > ### ** Examples > > > ## Load example data > data("ExampleData.SurfaceExposure") > > ## Example 1 - Single sample > # Known parameters: 10000 a, mu = 0.9, sigmaphi = 5e-10 > sample_1 <- ExampleData.SurfaceExposure$sample_1 > head(sample_1) depth intensity error 1 0.0 0.05487370 0.08018774 2 0.1 -0.06055516 0.17745452 3 0.2 0.09560277 0.12385804 4 0.3 -0.05973453 0.05593426 5 0.4 -0.02775111 0.19830218 6 0.5 0.04852239 0.06168570 > results <- fit_SurfaceExposure( + data = sample_1, + mu = 0.9, + sigmaphi = 5e-10) [fit_SurfaceExposure()] Estimated parameter(s): --------------------- age (a): 9890 ± 369 Fixed parameter(s): ------------------- sigmaphi: 5e-10 mu: 0.9 > get_RLum(results) age age_error sigmaphi sigmaphi_error mu mu_error 1 9892.927 369.0142 5e-10 NA 0.9 NA > > ## Example 2 - Single sample and considering dose rate > # Known parameters: 10000 a, mu = 0.9, sigmaphi = 5e-10, > # dose rate = 2.5 Gy/ka, D0 = 40 Gy > sample_2 <- ExampleData.SurfaceExposure$sample_2 > head(sample_2) depth intensity error 1 0.0 0.05881908 0.08018774 2 0.1 -0.05623983 0.17745452 3 0.2 0.10032258 0.12385804 4 0.3 -0.05457253 0.05593426 5 0.4 -0.02210573 0.19830218 6 0.5 0.05469614 0.06168570 > results <- fit_SurfaceExposure( + data = sample_2, + mu = 0.9, + sigmaphi = 5e-10, + Ddot = 2.5, + D0 = 40) [fit_SurfaceExposure()] Estimated parameter(s): --------------------- age (a): 9800 ± 675 Fixed parameter(s): ------------------- sigmaphi: 5e-10 mu: 0.9 > get_RLum(results) age age_error sigmaphi sigmaphi_error mu mu_error 1 9803.815 674.8718 5e-10 NA 0.9 NA > > ## Example 3 - Multiple samples (global fit) to better constrain 'mu' > # Known parameters: ages = 1e3, 1e4, 1e5, 1e6 a, mu = 0.9, sigmaphi = 5e-10 > set_1 <- ExampleData.SurfaceExposure$set_1 > str(set_1, max.level = 2) List of 4 $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] 0.0274 -0.0303 0.0478 -0.0298 -0.0134 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] 0.00714 -0.04511 0.04804 0.04145 0.0266 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] -0.0284 0.00732 -0.04984 0.02182 -0.02349 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] -0.0122 -0.0189 0.0358 -0.0314 -0.0454 ... > results <- fit_SurfaceExposure( + data = set_1, + age = c(1e3, 1e4, 1e5, 1e6), + sigmaphi = 5e-10) [fit_SurfaceExposure()] Shared estimated parameter(s): --------------------- mu: 0.901 ± 0.00161 Fixed parameter(s): ------------------- age (a): 1000, 10000, 1e+05, 1e+06 sigmaphi: 5e-10 To apply the estimated parameters to a sample of unknown age run: fit_SurfaceExposure(data = set_1, sigmaphi = 5e-10, mu = c(0.901, 0.901, 0.901, 0.901)) > get_RLum(results) age age_error sigmaphi sigmaphi_error mu mu_error 1 1e+03 NA 5e-10 NA 0.9009494 0.001612274 2 1e+04 NA 5e-10 NA 0.9009494 0.001612274 3 1e+05 NA 5e-10 NA 0.9009494 0.001612274 4 1e+06 NA 5e-10 NA 0.9009494 0.001612274 > > ## Example 4 - Multiple samples (global fit) and considering dose rate > # Known parameters: ages = 1e2, 1e3, 1e4, 1e5, 1e6 a, mu = 0.9, sigmaphi = 5e-10, > # dose rate = 1.0 Ga/ka, D0 = 40 Gy > set_2 <- ExampleData.SurfaceExposure$set_2 > str(set_2, max.level = 2) List of 5 $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] 0.235 0.238 0.381 0.369 0.451 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] 0.00872 -0.04321 0.05032 0.04426 0.03029 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] -0.02682 0.00921 -0.04757 0.02453 -0.02024 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] -0.0106 -0.0171 0.0381 -0.0287 -0.0422 ... $ :'data.frame': 76 obs. of 2 variables: ..$ depth : num [1:76] 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ... ..$ intensity: num [1:76] -0.00358 0.03918 0.00275 0.04301 -0.04237 ... > results <- fit_SurfaceExposure( + data = set_2, + age = c(1e2, 1e3, 1e4, 1e5, 1e6), + sigmaphi = 5e-10, + Ddot = 1, + D0 = 40) [fit_SurfaceExposure()] Shared estimated parameter(s): --------------------- mu: 0.899 ± 0.00232 Fixed parameter(s): ------------------- age (a): 100, 1000, 10000, 1e+05, 1e+06 sigmaphi: 5e-10 To apply the estimated parameters to a sample of unknown age run: fit_SurfaceExposure(data = set_2, sigmaphi = 5e-10, mu = c(0.899, 0.899, 0.899, 0.899, 0.899)) > get_RLum(results) age age_error sigmaphi sigmaphi_error mu mu_error 1 1e+02 NA 5e-10 NA 0.8986586 0.002323745 2 1e+03 NA 5e-10 NA 0.8986586 0.002323745 3 1e+04 NA 5e-10 NA 0.8986586 0.002323745 4 1e+05 NA 5e-10 NA 0.8986586 0.002323745 5 1e+06 NA 5e-10 NA 0.8986586 0.002323745 > > > > > cleanEx() > nameEx("fit_ThermalQuenching") > ### * fit_ThermalQuenching > > flush(stderr()); flush(stdout()) > > ### Name: fit_ThermalQuenching > ### Title: Fitting Thermal Quenching Data > ### Aliases: fit_ThermalQuenching > > ### ** Examples > > > ##create short example dataset > data <- data.frame( + T = c(25, 40, 50, 60, 70, 80, 90, 100, 110), + V = c(0.06, 0.058, 0.052, 0.051, 0.041, 0.034, 0.035, 0.033, 0.032), + V_X = c(0.012, 0.009, 0.008, 0.008, 0.007, 0.006, 0.005, 0.005, 0.004)) > > ##fit > fit_ThermalQuenching( + data = data, + n.MC = NULL) [fit_ThermalQuenching()] A = 0.02853867 ± NA C = 3.8315e+14 ± NA W = 0.9749455 ± NA eV c = 0.03139589 ± NA -------------------------------- [RLum.Results-class] originator: fit_ThermalQuenching() data: 2 .. $data : data.frame .. $fit : nls additional info elements: 1 > > > > > cleanEx() > nameEx("get_Layout") > ### * get_Layout > > flush(stderr()); flush(stdout()) > > ### Name: get_Layout > ### Title: Collection of layout definitions > ### Aliases: get_Layout > > ### ** Examples > > > ## read example data set > data(ExampleData.DeValues, envir = environment()) > > ## show structure of the default layout definition > layout.default <- get_Layout(layout = "default") > str(layout.default) List of 2 $ abanico:List of 5 ..$ font.type:List of 14 .. ..$ main : chr "" .. ..$ xlab1 : chr "" .. ..$ xlab2 : chr "" .. ..$ ylab : chr "" .. ..$ zlab : chr "" .. ..$ xtck1 : chr "" .. ..$ xtck2 : chr "" .. ..$ xtck3 : chr "" .. ..$ ytck : chr "" .. ..$ ztck : chr "" .. ..$ mtext : chr "" .. ..$ summary: chr "" .. ..$ stats : chr "" .. ..$ legend : chr "" ..$ font.size:List of 15 .. ..$ main : num 12 .. ..$ xlab1 : num 12 .. ..$ xlab2 : num 12 .. ..$ xlab3 : num 12 .. ..$ ylab : num 12 .. ..$ zlab : num 12 .. ..$ xtck1 : num 12 .. ..$ xtck2 : num 12 .. ..$ xtck3 : num 12 .. ..$ ytck : num 12 .. ..$ ztck : num 12 .. ..$ mtext : num 10 .. ..$ summary: num 10 .. ..$ stats : num 10 .. ..$ legend : num 10 ..$ font.deco:List of 15 .. ..$ main : chr "bold" .. ..$ xlab1 : chr "normal" .. ..$ xlab2 : chr "normal" .. ..$ xlab3 : chr "normal" .. ..$ ylab : chr "normal" .. ..$ zlab : chr "normal" .. ..$ xtck1 : chr "normal" .. ..$ xtck2 : chr "normal" .. ..$ xtck3 : chr "normal" .. ..$ ytck : chr "normal" .. ..$ ztck : chr "normal" .. ..$ mtext : chr "normal" .. ..$ summary: chr "normal" .. ..$ stats : chr "normal" .. ..$ legend : chr "normal" ..$ colour :List of 29 .. ..$ main : num 1 .. ..$ xlab1 : num 1 .. ..$ xlab2 : num 1 .. ..$ xlab3 : num 1 .. ..$ ylab : num 1 .. ..$ zlab : num 1 .. ..$ xtck1 : num 1 .. ..$ xtck2 : num 1 .. ..$ xtck3 : num 1 .. ..$ ytck : num 1 .. ..$ ztck : num 1 .. ..$ mtext : num 1 .. ..$ summary : num 1 .. ..$ stats : num 1 .. ..$ legend : num 1 .. ..$ centrality: num 1 .. ..$ value.dot : num 1 .. ..$ value.bar : num 1 .. ..$ value.rug : num 1 .. ..$ poly.line : logi NA .. ..$ poly.fill : chr "#BFBFBF99" .. ..$ bar.line : logi NA .. ..$ bar.fill : chr "grey60" .. ..$ kde.line : num 1 .. ..$ kde.fill : logi NA .. ..$ grid.major: chr "grey80" .. ..$ grid.minor: chr "none" .. ..$ border : num 1 .. ..$ background: logi NA ..$ dimension:List of 22 .. ..$ figure.width : chr "auto" .. ..$ figure.height: chr "auto" .. ..$ margin : num [1:4] 10 10 10 10 .. ..$ main.line : num 100 .. ..$ xlab1.line : num 90 .. ..$ xlab2.line : num 90 .. ..$ xlab3.line : num 90 .. ..$ ylab.line : num 100 .. ..$ zlab.line : num 70 .. ..$ xtck1.line : num 100 .. ..$ xtck2.line : num 100 .. ..$ xtck3.line : num 100 .. ..$ ytck.line : num 100 .. ..$ ztck.line : num 100 .. ..$ xtcl1 : num 100 .. ..$ xtcl2 : num 100 .. ..$ xtcl3 : num 100 .. ..$ ytcl : num 100 .. ..$ ztcl : num 100 .. ..$ rugl : num 100 .. ..$ mtext : num 100 .. ..$ summary.line : num 100 $ kde :List of 5 ..$ font.type:List of 9 .. ..$ main : chr "" .. ..$ xlab : chr "" .. ..$ ylab1 : chr "" .. ..$ ylab2 : chr "" .. ..$ xtck : chr "" .. ..$ ytck1 : chr "" .. ..$ ytck2 : chr "" .. ..$ stats : chr "" .. ..$ legend: chr "" ..$ font.size:List of 10 .. ..$ main : num 14 .. ..$ xlab : num 12 .. ..$ ylab1 : num 12 .. ..$ ylab2 : num 12 .. ..$ xtck : num 12 .. ..$ ytck1 : num 12 .. ..$ ytck2 : num 12 .. ..$ mtext : num 10 .. ..$ stats : num 12 .. ..$ legend: num 12 ..$ font.deco:List of 9 .. ..$ main : chr "bold" .. ..$ xlab : chr "normal" .. ..$ ylab1 : chr "normal" .. ..$ ylab2 : chr "normal" .. ..$ xtck : chr "normal" .. ..$ ytck1 : chr "normal" .. ..$ ytck2 : chr "normal" .. ..$ stats : chr "normal" .. ..$ legend: chr "normal" ..$ colour :List of 20 .. ..$ main : num 1 .. ..$ xlab : num 1 .. ..$ ylab1 : num 1 .. ..$ ylab2 : num 1 .. ..$ xtck : num 1 .. ..$ ytck1 : num 1 .. ..$ ytck2 : num 1 .. ..$ box : num 1 .. ..$ mtext : num 2 .. ..$ stats : num 1 .. ..$ kde.line : num 1 .. ..$ kde.fill : NULL .. ..$ value.dot : num 1 .. ..$ value.bar : num 1 .. ..$ value.rug : num 1 .. ..$ boxplot.line: num 1 .. ..$ boxplot.fill: NULL .. ..$ mean.point : num 1 .. ..$ sd.line : num 1 .. ..$ background : logi NA ..$ dimension:List of 14 .. ..$ figure.width : chr "auto" .. ..$ figure.height: chr "auto" .. ..$ margin : num [1:4] 10 10 10 10 .. ..$ main.line : num 100 .. ..$ xlab.line : num 100 .. ..$ ylab1.line : num 100 .. ..$ ylab2.line : num 100 .. ..$ xtck.line : num 100 .. ..$ ytck1.line : num 100 .. ..$ ytck2.line : num 100 .. ..$ xtcl : num 100 .. ..$ ytcl1 : num 100 .. ..$ ytcl2 : num 100 .. ..$ stats.line : num 100 > > ## show colour definitions for Abanico plot, only > layout.default$abanico$colour $main [1] 1 $xlab1 [1] 1 $xlab2 [1] 1 $xlab3 [1] 1 $ylab [1] 1 $zlab [1] 1 $xtck1 [1] 1 $xtck2 [1] 1 $xtck3 [1] 1 $ytck [1] 1 $ztck [1] 1 $mtext [1] 1 $summary [1] 1 $stats [1] 1 $legend [1] 1 $centrality [1] 1 $value.dot [1] 1 $value.bar [1] 1 $value.rug [1] 1 $poly.line [1] NA $poly.fill [1] "#BFBFBF99" $bar.line [1] NA $bar.fill [1] "grey60" $kde.line [1] 1 $kde.fill [1] NA $grid.major [1] "grey80" $grid.minor [1] "none" $border [1] 1 $background [1] NA > > ## set Abanico plot title colour to orange > layout.default$abanico$colour$main <- "orange" > > ## create Abanico plot with modofied layout definition > plot_AbanicoPlot(data = ExampleData.DeValues, + layout = layout.default) > > ## create Abanico plot with predefined layout "journal" > plot_AbanicoPlot(data = ExampleData.DeValues, + layout = "journal") > > > > > cleanEx() > nameEx("get_RLum") > ### * get_RLum > > flush(stderr()); flush(stdout()) > > ### Name: get_RLum > ### Title: General accessor function for RLum-class objects > ### Aliases: get_RLum get_RLum,list-method get_RLum,NULL-method > ### get_RLum,RLum.Analysis-method get_RLum,RLum.Data.Curve-method > ### get_RLum,RLum.Data.Image-method get_RLum,RLum.Data.Spectrum-method > ### get_RLum,RLum.Results-method > ### Keywords: utilities > > ### ** Examples > > > ## Example based using data and from the calc_CentralDose() function > > ## load example data > data(ExampleData.DeValues, envir = environment()) > > ## apply the central dose model 1st time > temp1 <- calc_CentralDose(ExampleData.DeValues$CA1) [calc_CentralDose] ----------- meta data ---------------- n: 62 log: TRUE ----------- dose estimate ------------ abs. central dose: 65.71 abs. SE: 3.05 rel. SE [%]: 4.65 ----------- overdispersion ----------- abs. OD: 22.79 abs. SE: 2.27 OD [%]: 34.69 SE [%]: 3.46 ------------------------------------- > > ## get results and store them in a new object > temp.get <- get_RLum(object = temp1) > > > > > cleanEx() > nameEx("get_rightAnswer") > ### * get_rightAnswer > > flush(stderr()); flush(stdout()) > > ### Name: get_rightAnswer > ### Title: Function to get the right answer > ### Aliases: get_rightAnswer > > ### ** Examples > > > ## you really want to know? > get_rightAnswer() [1] 46 > > > > > cleanEx() > nameEx("import_Data") > ### * import_Data > > flush(stderr()); flush(stdout()) > > ### Name: import_Data > ### Title: Import Luminescence Data into R > ### Aliases: import_Data > ### Keywords: datagen > > ### ** Examples > > > ## import BINX/BIN > file <- system.file("extdata/BINfile_V8.binx", package = "Luminescence") > temp <- import_Data(file) > > ## RF data > file <- system.file("extdata", "RF_file.rf", package = "Luminescence") > temp <- import_Data(file) > > > > > cleanEx() > nameEx("melt_RLum") > ### * melt_RLum > > flush(stderr()); flush(stdout()) > > ### Name: melt_RLum > ### Title: Melt RLum-class objects into a flat data.frame > ### Aliases: melt_RLum melt_RLum,list-method melt_RLum,RLum.Analysis-method > ### melt_RLum,RLum.Data.Curve-method > ### Keywords: utilities > > ### ** Examples > > data(ExampleData.XSYG, envir = environment()) > melt_RLum(OSL.SARMeasurement[[2]][[1]]) X Y TYPE UID 1 0.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 2 0.2 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 3 0.3 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 4 0.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 5 0.5 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 6 0.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 7 0.7 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 8 0.8 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 9 0.9 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 10 1.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 11 1.1 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 12 1.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 13 1.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 14 1.4 3 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 15 1.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 16 1.6 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 17 1.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 18 1.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 19 1.9 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 20 2.0 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 21 2.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 22 2.2 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 23 2.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 24 2.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 25 2.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 26 2.6 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 27 2.7 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 28 2.8 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 29 2.9 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 30 3.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 31 3.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 32 3.2 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 33 3.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 34 3.4 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 35 3.5 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 36 3.6 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 37 3.7 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 38 3.8 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 39 3.9 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 40 4.0 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 41 4.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 42 4.2 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 43 4.3 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 44 4.4 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 45 4.5 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 46 4.6 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 47 4.7 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 48 4.8 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 49 4.9 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 50 5.0 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 51 5.1 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 52 5.2 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 53 5.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 54 5.4 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 55 5.5 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 56 5.6 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 57 5.7 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 58 5.8 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 59 5.9 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 60 6.0 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 61 6.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 62 6.2 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 63 6.3 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 64 6.4 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 65 6.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 66 6.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 67 6.7 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 68 6.8 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 69 6.9 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 70 7.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 71 7.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 72 7.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 73 7.3 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 74 7.4 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 75 7.5 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 76 7.6 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 77 7.7 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 78 7.8 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 79 7.9 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 80 8.0 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 81 8.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 82 8.2 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 83 8.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 84 8.4 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 85 8.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 86 8.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 87 8.7 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 88 8.8 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 89 8.9 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 90 9.0 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 91 9.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 92 9.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 93 9.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 94 9.4 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 95 9.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 96 9.6 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 97 9.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 98 9.8 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 99 9.9 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 100 10.0 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 101 10.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 102 10.2 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 103 10.3 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 104 10.4 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 105 10.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 106 10.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 107 10.7 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 108 10.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 109 10.9 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 110 11.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 111 11.1 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 112 11.2 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 113 11.3 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 114 11.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 115 11.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 116 11.6 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 117 11.7 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 118 11.8 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 119 11.9 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 120 12.0 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 121 12.1 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 122 12.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 123 12.3 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 124 12.4 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 125 12.5 3 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 126 12.6 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 127 12.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 128 12.8 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 129 12.9 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 130 13.0 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 131 13.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 132 13.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 133 13.3 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 134 13.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 135 13.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 136 13.6 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 137 13.7 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 138 13.8 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 139 13.9 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 140 14.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 141 14.1 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 142 14.2 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 143 14.3 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 144 14.4 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 145 14.5 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 146 14.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 147 14.7 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 148 14.8 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 149 14.9 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 150 15.0 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 151 15.1 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 152 15.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 153 15.3 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 154 15.4 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 155 15.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 156 15.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 157 15.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 158 15.8 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 159 15.9 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 160 16.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 161 16.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 162 16.2 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 163 16.3 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 164 16.4 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 165 16.5 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 166 16.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 167 16.7 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 168 16.8 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 169 16.9 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 170 17.0 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 171 17.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 172 17.2 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 173 17.3 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 174 17.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 175 17.5 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 176 17.6 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 177 17.7 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 178 17.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 179 17.9 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 180 18.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 181 18.1 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 182 18.2 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 183 18.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 184 18.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 185 18.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 186 18.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 187 18.7 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 188 18.8 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 189 18.9 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 190 19.0 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 191 19.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 192 19.2 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 193 19.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 194 19.4 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 195 19.5 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 196 19.6 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 197 19.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 198 19.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 199 19.9 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 200 20.0 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 201 20.1 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 202 20.2 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 203 20.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 204 20.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 205 20.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 206 20.6 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 207 20.7 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 208 20.8 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 209 20.9 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 210 21.0 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 211 21.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 212 21.2 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 213 21.3 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 214 21.4 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 215 21.5 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 216 21.6 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 217 21.7 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 218 21.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 219 21.9 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 220 22.0 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 221 22.1 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 222 22.2 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 223 22.3 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 224 22.4 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 225 22.5 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 226 22.6 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 227 22.7 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 228 22.8 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 229 22.9 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 230 23.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 231 23.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 232 23.2 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 233 23.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 234 23.4 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 235 23.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 236 23.6 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 237 23.7 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 238 23.8 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 239 23.9 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 240 24.0 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 241 24.1 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 242 24.2 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 243 24.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 244 24.4 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 245 24.5 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 246 24.6 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 247 24.7 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 248 24.8 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 249 24.9 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 250 25.0 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 251 25.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 252 25.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 253 25.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 254 25.4 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 255 25.5 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 256 25.6 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 257 25.7 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 258 25.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 259 25.9 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 260 26.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 261 26.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 262 26.2 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 263 26.3 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 264 26.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 265 26.5 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 266 26.6 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 267 26.7 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 268 26.8 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 269 26.9 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 270 27.0 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 271 27.1 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 272 27.2 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 273 27.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 274 27.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 275 27.5 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 276 27.6 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 277 27.7 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 278 27.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 279 27.9 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 280 28.0 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 281 28.1 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 282 28.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 283 28.3 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 284 28.4 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 285 28.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 286 28.6 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 287 28.7 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 288 28.8 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 289 28.9 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 290 29.0 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 291 29.1 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 292 29.2 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 293 29.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 294 29.4 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 295 29.5 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 296 29.6 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 297 29.7 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 298 29.8 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 299 29.9 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 300 30.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 301 30.1 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 302 30.2 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 303 30.3 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 304 30.4 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 305 30.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 306 30.6 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 307 30.7 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 308 30.8 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 309 30.9 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 310 31.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 311 31.1 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 312 31.2 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 313 31.3 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 314 31.4 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 315 31.5 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 316 31.6 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 317 31.7 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 318 31.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 319 31.9 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 320 32.0 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 321 32.1 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 322 32.2 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 323 32.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 324 32.4 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 325 32.5 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 326 32.6 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 327 32.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 328 32.8 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 329 32.9 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 330 33.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 331 33.1 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 332 33.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 333 33.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 334 33.4 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 335 33.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 336 33.6 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 337 33.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 338 33.8 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 339 33.9 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 340 34.0 2 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 341 34.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 342 34.2 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 343 34.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 344 34.4 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 345 34.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 346 34.6 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 347 34.7 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 348 34.8 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 349 34.9 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 350 35.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 351 35.1 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 352 35.2 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 353 35.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 354 35.4 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 355 35.5 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 356 35.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 357 35.7 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 358 35.8 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 359 35.9 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 360 36.0 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 361 36.1 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 362 36.2 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 363 36.3 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 364 36.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 365 36.5 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 366 36.6 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 367 36.7 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 368 36.8 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 369 36.9 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 370 37.0 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 371 37.1 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 372 37.2 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 373 37.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 374 37.4 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 375 37.5 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 376 37.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 377 37.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 378 37.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 379 37.9 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 380 38.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 381 38.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 382 38.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 383 38.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 384 38.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 385 38.5 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 386 38.6 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 387 38.7 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 388 38.8 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 389 38.9 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 390 39.0 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 391 39.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 392 39.2 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 393 39.3 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 394 39.4 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 395 39.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 396 39.6 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 397 39.7 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 398 39.8 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 399 39.9 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 400 40.0 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 401 40.1 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 402 40.2 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 403 40.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 404 40.4 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 405 40.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 406 40.6 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 407 40.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 408 40.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 409 40.9 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 410 41.0 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 411 41.1 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 412 41.2 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 413 41.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 414 41.4 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 415 41.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 416 41.6 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 417 41.7 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 418 41.8 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 419 41.9 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 420 42.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 421 42.1 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 422 42.2 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 423 42.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 424 42.4 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 425 42.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 426 42.6 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 427 42.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 428 42.8 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 429 42.9 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 430 43.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 431 43.1 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 432 43.2 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 433 43.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 434 43.4 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 435 43.5 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 436 43.6 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 437 43.7 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 438 43.8 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 439 43.9 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 440 44.0 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 441 44.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 442 44.2 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 443 44.3 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 444 44.4 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 445 44.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 446 44.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 447 44.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 448 44.8 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 449 44.9 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 450 45.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 451 45.1 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 452 45.2 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 453 45.3 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 454 45.4 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 455 45.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 456 45.6 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 457 45.7 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 458 45.8 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 459 45.9 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 460 46.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 461 46.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 462 46.2 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 463 46.3 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 464 46.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 465 46.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 466 46.6 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 467 46.7 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 468 46.8 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 469 46.9 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 470 47.0 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 471 47.1 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 472 47.2 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 473 47.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 474 47.4 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 475 47.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 476 47.6 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 477 47.7 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 478 47.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 479 47.9 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 480 48.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 481 48.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 482 48.2 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 483 48.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 484 48.4 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 485 48.5 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 486 48.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 487 48.7 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 488 48.8 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 489 48.9 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 490 49.0 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 491 49.1 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 492 49.2 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 493 49.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 494 49.4 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 495 49.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 496 49.6 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 497 49.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 498 49.8 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 499 49.9 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 500 50.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 501 50.1 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 502 50.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 503 50.3 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 504 50.4 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 505 50.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 506 50.6 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 507 50.7 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 508 50.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 509 50.9 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 510 51.0 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 511 51.1 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 512 51.2 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 513 51.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 514 51.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 515 51.5 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 516 51.6 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 517 51.7 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 518 51.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 519 51.9 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 520 52.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 521 52.1 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 522 52.2 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 523 52.3 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 524 52.4 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 525 52.5 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 526 52.6 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 527 52.7 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 528 52.8 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 529 52.9 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 530 53.0 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 531 53.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 532 53.2 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 533 53.3 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 534 53.4 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 535 53.5 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 536 53.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 537 53.7 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 538 53.8 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 539 53.9 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 540 54.0 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 541 54.1 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 542 54.2 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 543 54.3 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 544 54.4 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 545 54.5 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 546 54.6 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 547 54.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 548 54.8 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 549 54.9 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 550 55.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 551 55.1 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 552 55.2 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 553 55.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 554 55.4 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 555 55.5 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 556 55.6 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 557 55.7 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 558 55.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 559 55.9 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 560 56.0 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 561 56.1 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 562 56.2 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 563 56.3 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 564 56.4 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 565 56.5 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 566 56.6 4 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 567 56.7 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 568 56.8 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 569 56.9 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 570 57.0 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 571 57.1 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 572 57.2 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 573 57.3 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 574 57.4 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 575 57.5 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 576 57.6 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 577 57.7 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 578 57.8 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 579 57.9 5 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 580 58.0 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 581 58.1 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 582 58.2 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 583 58.3 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 584 58.4 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 585 58.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 586 58.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 587 58.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 588 58.8 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 589 58.9 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 590 59.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 591 59.1 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 592 59.2 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 593 59.3 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 594 59.4 8 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 595 59.5 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 596 59.6 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 597 59.7 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 598 59.8 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 599 59.9 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 600 60.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 601 60.1 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 602 60.2 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 603 60.3 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 604 60.4 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 605 60.5 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 606 60.6 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 607 60.7 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 608 60.8 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 609 60.9 0 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 610 61.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 611 61.1 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 612 61.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 613 61.3 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 614 61.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 615 61.5 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 616 61.6 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 617 61.7 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 618 61.8 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 619 61.9 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 620 62.0 11 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 621 62.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 622 62.2 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 623 62.3 7 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 624 62.4 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 625 62.5 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 626 62.6 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 627 62.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 628 62.8 6 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 629 62.9 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 630 63.0 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 631 63.1 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 632 63.2 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 633 63.3 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 634 63.4 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 635 63.5 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 636 63.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 637 63.7 9 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 638 63.8 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 639 63.9 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 640 64.0 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 641 64.1 10 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 642 64.2 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 643 64.3 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 644 64.4 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 645 64.5 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 646 64.6 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 647 64.7 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 648 64.8 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 649 64.9 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 650 65.0 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 651 65.1 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 652 65.2 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 653 65.3 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 654 65.4 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 655 65.5 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 656 65.6 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 657 65.7 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 658 65.8 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 659 65.9 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 660 66.0 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 661 66.1 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 662 66.2 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 663 66.3 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 664 66.4 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 665 66.5 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 666 66.6 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 667 66.7 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 668 66.8 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 669 66.9 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 670 67.0 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 671 67.1 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 672 67.2 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 673 67.3 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 674 67.4 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 675 67.5 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 676 67.6 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 677 67.7 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 678 67.8 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 679 67.9 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 680 68.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 681 68.1 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 682 68.2 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 683 68.3 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 684 68.4 12 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 685 68.5 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 686 68.6 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 687 68.7 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 688 68.8 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 689 68.9 15 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 690 69.0 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 691 69.1 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 692 69.2 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 693 69.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 694 69.4 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 695 69.5 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 696 69.6 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 697 69.7 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 698 69.8 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 699 69.9 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 700 70.0 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 701 70.1 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 702 70.2 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 703 70.3 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 704 70.4 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 705 70.5 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 706 70.6 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 707 70.7 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 708 70.8 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 709 70.9 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 710 71.0 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 711 71.1 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 712 71.2 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 713 71.3 18 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 714 71.4 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 715 71.5 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 716 71.6 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 717 71.7 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 718 71.8 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 719 71.9 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 720 72.0 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 721 72.1 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 722 72.2 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 723 72.3 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 724 72.4 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 725 72.5 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 726 72.6 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 727 72.7 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 728 72.8 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 729 72.9 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 730 73.0 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 731 73.1 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 732 73.2 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 733 73.3 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 734 73.4 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 735 73.5 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 736 73.6 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 737 73.7 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 738 73.8 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 739 73.9 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 740 74.0 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 741 74.1 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 742 74.2 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 743 74.3 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 744 74.4 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 745 74.5 40 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 746 74.6 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 747 74.7 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 748 74.8 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 749 74.9 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 750 75.0 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 751 75.1 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 752 75.2 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 753 75.3 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 754 75.4 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 755 75.5 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 756 75.6 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 757 75.7 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 758 75.8 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 759 75.9 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 760 76.0 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 761 76.1 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 762 76.2 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 763 76.3 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 764 76.4 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 765 76.5 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 766 76.6 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 767 76.7 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 768 76.8 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 769 76.9 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 770 77.0 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 771 77.1 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 772 77.2 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 773 77.3 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 774 77.4 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 775 77.5 40 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 776 77.6 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 777 77.7 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 778 77.8 48 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 779 77.9 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 780 78.0 47 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 781 78.1 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 782 78.2 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 783 78.3 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 784 78.4 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 785 78.5 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 786 78.6 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 787 78.7 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 788 78.8 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 789 78.9 47 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 790 79.0 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 791 79.1 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 792 79.2 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 793 79.3 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 794 79.4 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 795 79.5 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 796 79.6 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 797 79.7 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 798 79.8 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 799 79.9 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 800 80.0 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 801 80.1 47 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 802 80.2 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 803 80.3 40 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 804 80.4 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 805 80.5 47 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 806 80.6 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 807 80.7 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 808 80.8 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 809 80.9 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 810 81.0 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 811 81.1 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 812 81.2 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 813 81.3 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 814 81.4 59 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 815 81.5 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 816 81.6 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 817 81.7 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 818 81.8 48 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 819 81.9 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 820 82.0 48 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 821 82.1 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 822 82.2 63 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 823 82.3 48 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 824 82.4 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 825 82.5 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 826 82.6 59 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 827 82.7 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 828 82.8 56 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 829 82.9 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 830 83.0 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 831 83.1 70 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 832 83.2 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 833 83.3 63 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 834 83.4 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 835 83.5 55 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 836 83.6 59 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 837 83.7 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 838 83.8 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 839 83.9 62 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 840 84.0 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 841 84.1 59 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 842 84.2 55 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 843 84.3 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 844 84.4 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 845 84.5 73 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 846 84.6 70 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 847 84.7 59 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 848 84.8 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 849 84.9 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 850 85.0 75 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 851 85.1 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 852 85.2 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 853 85.3 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 854 85.4 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 855 85.5 62 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 856 85.6 62 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 857 85.7 47 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 858 85.8 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 859 85.9 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 860 86.0 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 861 86.1 69 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 862 86.2 64 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 863 86.3 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 864 86.4 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 865 86.5 65 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 866 86.6 72 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 867 86.7 62 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 868 86.8 65 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 869 86.9 62 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 870 87.0 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 871 87.1 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 872 87.2 69 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 873 87.3 70 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 874 87.4 71 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 875 87.5 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 876 87.6 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 877 87.7 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 878 87.8 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 879 87.9 82 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 880 88.0 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 881 88.1 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 882 88.2 62 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 883 88.3 64 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 884 88.4 65 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 885 88.5 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 886 88.6 55 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 887 88.7 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 888 88.8 66 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 889 88.9 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 890 89.0 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 891 89.1 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 892 89.2 68 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 893 89.3 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 894 89.4 67 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 895 89.5 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 896 89.6 70 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 897 89.7 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 898 89.8 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 899 89.9 71 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 900 90.0 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 901 90.1 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 902 90.2 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 903 90.3 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 904 90.4 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 905 90.5 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 906 90.6 66 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 907 90.7 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 908 90.8 58 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 909 90.9 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 910 91.0 63 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 911 91.1 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 912 91.2 70 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 913 91.3 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 914 91.4 48 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 915 91.5 60 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 916 91.6 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 917 91.7 52 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 918 91.8 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 919 91.9 56 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 920 92.0 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 921 92.1 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 922 92.2 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 923 92.3 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 924 92.4 57 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 925 92.5 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 926 92.6 53 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 927 92.7 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 928 92.8 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 929 92.9 61 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 930 93.0 65 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 931 93.1 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 932 93.2 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 933 93.3 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 934 93.4 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 935 93.5 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 936 93.6 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 937 93.7 48 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 938 93.8 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 939 93.9 56 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 940 94.0 51 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 941 94.1 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 942 94.2 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 943 94.3 64 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 944 94.4 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 945 94.5 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 946 94.6 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 947 94.7 54 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 948 94.8 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 949 94.9 49 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 950 95.0 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 951 95.1 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 952 95.2 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 953 95.3 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 954 95.4 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 955 95.5 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 956 95.6 59 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 957 95.7 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 958 95.8 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 959 95.9 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 960 96.0 40 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 961 96.1 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 962 96.2 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 963 96.3 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 964 96.4 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 965 96.5 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 966 96.6 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 967 96.7 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 968 96.8 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 969 96.9 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 970 97.0 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 971 97.1 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 972 97.2 45 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 973 97.3 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 974 97.4 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 975 97.5 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 976 97.6 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 977 97.7 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 978 97.8 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 979 97.9 42 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 980 98.0 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 981 98.1 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 982 98.2 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 983 98.3 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 984 98.4 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 985 98.5 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 986 98.6 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 987 98.7 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 988 98.8 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 989 98.9 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 990 99.0 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 991 99.1 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 992 99.2 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 993 99.3 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 994 99.4 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 995 99.5 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 996 99.6 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 997 99.7 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 998 99.8 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 999 99.9 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1000 100.0 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1001 100.1 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1002 100.2 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1003 100.3 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1004 100.4 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1005 100.5 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1006 100.6 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1007 100.7 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1008 100.8 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1009 100.9 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1010 101.0 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1011 101.1 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1012 101.2 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1013 101.3 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1014 101.4 46 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1015 101.5 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1016 101.6 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1017 101.7 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1018 101.8 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1019 101.9 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1020 102.0 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1021 102.1 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1022 102.2 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1023 102.3 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1024 102.4 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1025 102.5 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1026 102.6 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1027 102.7 40 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1028 102.8 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1029 102.9 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1030 103.0 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1031 103.1 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1032 103.2 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1033 103.3 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1034 103.4 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1035 103.5 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1036 103.6 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1037 103.7 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1038 103.8 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1039 103.9 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1040 104.0 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1041 104.1 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1042 104.2 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1043 104.3 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1044 104.4 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1045 104.5 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1046 104.6 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1047 104.7 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1048 104.8 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1049 104.9 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1050 105.0 13 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1051 105.1 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1052 105.2 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1053 105.3 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1054 105.4 50 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1055 105.5 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1056 105.6 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1057 105.7 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1058 105.8 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1059 105.9 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1060 106.0 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1061 106.1 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1062 106.2 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1063 106.3 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1064 106.4 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1065 106.5 44 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1066 106.6 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1067 106.7 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1068 106.8 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1069 106.9 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1070 107.0 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1071 107.1 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1072 107.2 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1073 107.3 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1074 107.4 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1075 107.5 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1076 107.6 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1077 107.7 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1078 107.8 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1079 107.9 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1080 108.0 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1081 108.1 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1082 108.2 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1083 108.3 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1084 108.4 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1085 108.5 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1086 108.6 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1087 108.7 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1088 108.8 16 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1089 108.9 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1090 109.0 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1091 109.1 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1092 109.2 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1093 109.3 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1094 109.4 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1095 109.5 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1096 109.6 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1097 109.7 40 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1098 109.8 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1099 109.9 19 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1100 110.0 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1101 110.1 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1102 110.2 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1103 110.3 47 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1104 110.4 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1105 110.5 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1106 110.6 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1107 110.7 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1108 110.8 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1109 110.9 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1110 111.0 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1111 111.1 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1112 111.2 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1113 111.3 38 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1114 111.4 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1115 111.5 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1116 111.6 14 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1117 111.7 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1118 111.8 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1119 111.9 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1120 112.0 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1121 112.1 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1122 112.2 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1123 112.3 31 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1124 112.4 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1125 112.5 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1126 112.6 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1127 112.7 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1128 112.8 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1129 112.9 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1130 113.0 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1131 113.1 43 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1132 113.2 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1133 113.3 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1134 113.4 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1135 113.5 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1136 113.6 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1137 113.7 41 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1138 113.8 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1139 113.9 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1140 114.0 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1141 114.1 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1142 114.2 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1143 114.3 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1144 114.4 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1145 114.5 17 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1146 114.6 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1147 114.7 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1148 114.8 22 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1149 114.9 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1150 115.0 30 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1151 115.1 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1152 115.2 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1153 115.3 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1154 115.4 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1155 115.5 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1156 115.6 29 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1157 115.7 39 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1158 115.8 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1159 115.9 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1160 116.0 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1161 116.1 28 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1162 116.2 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1163 116.3 37 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1164 116.4 23 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1165 116.5 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1166 116.6 20 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1167 116.7 36 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1168 116.8 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1169 116.9 21 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1170 117.0 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1171 117.1 34 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1172 117.2 32 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1173 117.3 25 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1174 117.4 24 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1175 117.5 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1176 117.6 35 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1177 117.7 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1178 117.8 26 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1179 117.9 33 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 1180 118.0 27 TL (UVVIS) 2016-01-30-10:54.0.226260372670367 > > > > > cleanEx() > nameEx("merge_RLum.Analysis") > ### * merge_RLum.Analysis > > flush(stderr()); flush(stdout()) > > ### Name: merge_RLum.Analysis > ### Title: Merge function for RLum.Analysis S4 class objects > ### Aliases: merge_RLum.Analysis > ### Keywords: internal utilities > > ### ** Examples > > > ##merge different RLum objects from the example data > data(ExampleData.RLum.Analysis, envir = environment()) > data(ExampleData.BINfileData, envir = environment()) > > object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > curve <- get_RLum(object)[[2]] > > temp.merged <- merge_RLum.Analysis(list(curve, IRSAR.RF.Data, IRSAR.RF.Data)) > > > > > cleanEx() > nameEx("merge_RLum.Data.Curve") > ### * merge_RLum.Data.Curve > > flush(stderr()); flush(stdout()) > > ### Name: merge_RLum.Data.Curve > ### Title: Merge function for RLum.Data.Curve S4 class objects > ### Aliases: merge_RLum.Data.Curve > ### Keywords: internal utilities > > ### ** Examples > > > ##load example data > data(ExampleData.XSYG, envir = environment()) > > ##grep first and 3d TL curves > TL.curves <- get_RLum(OSL.SARMeasurement$Sequence.Object, recordType = "TL (UVVIS)") > TL.curve.1 <- TL.curves[[1]] > TL.curve.3 <- TL.curves[[3]] > > ##plot single curves > plot_RLum(TL.curve.1) > plot_RLum(TL.curve.3) > > ##subtract the 1st curve from the 2nd and plot > TL.curve.merged <- merge_RLum.Data.Curve(list(TL.curve.3, TL.curve.1), merge.method = "/") Warning: [merge_RLum.Data.Curve()] 8 'Inf' values replaced by 0 in the matrix > plot_RLum(TL.curve.merged) > > > > > cleanEx() > nameEx("merge_RLum.Data.Spectrum") > ### * merge_RLum.Data.Spectrum > > flush(stderr()); flush(stdout()) > > ### Name: merge_RLum.Data.Spectrum > ### Title: Merge function for RLum.Data.Spectrum S4 class objects > ### Aliases: merge_RLum.Data.Spectrum > ### Keywords: internal utilities > > ### ** Examples > > > ## load example data > data(ExampleData.XSYG, envir = environment()) > > ## plot single curve > plot_RLum(TL.Spectrum) > > ## sum two copies of the same curve > merged <- merge_RLum.Data.Spectrum(list(TL.Spectrum, TL.Spectrum), + merge.method = "sum") > plot_RLum(merged) > > > > > cleanEx() > nameEx("merge_RLum") > ### * merge_RLum > > flush(stderr()); flush(stdout()) > > ### Name: merge_RLum > ### Title: General merge function for RLum-class objects > ### Aliases: merge_RLum > ### Keywords: utilities > > ### ** Examples > > > ##Example based using data and from the calc_CentralDose() function > > ##load example data > data(ExampleData.DeValues, envir = environment()) > > ##apply the central dose model 1st time > temp1 <- calc_CentralDose(ExampleData.DeValues$CA1) [calc_CentralDose] ----------- meta data ---------------- n: 62 log: TRUE ----------- dose estimate ------------ abs. central dose: 65.71 abs. SE: 3.05 rel. SE [%]: 4.65 ----------- overdispersion ----------- abs. OD: 22.79 abs. SE: 2.27 OD [%]: 34.69 SE [%]: 3.46 ------------------------------------- > > ##apply the central dose model 2nd time > temp2 <- calc_CentralDose(ExampleData.DeValues$CA1) [calc_CentralDose] ----------- meta data ---------------- n: 62 log: TRUE ----------- dose estimate ------------ abs. central dose: 65.71 abs. SE: 3.05 rel. SE [%]: 4.65 ----------- overdispersion ----------- abs. OD: 22.79 abs. SE: 2.27 OD [%]: 34.69 SE [%]: 3.46 ------------------------------------- > > ##merge the results and store them in a new object > temp.merged <- get_RLum(merge_RLum(objects = list(temp1, temp2))) > > > > > cleanEx() > nameEx("merge_Risoe.BINfileData") > ### * merge_Risoe.BINfileData > > flush(stderr()); flush(stdout()) > > ### Name: merge_Risoe.BINfileData > ### Title: Merge Risoe.BINfileData objects or Risoe BIN-files > ### Aliases: merge_Risoe.BINfileData > ### Keywords: IO manip > > ### ** Examples > > > ##merge two objects > data(ExampleData.BINfileData, envir = environment()) > > object1 <- CWOSL.SAR.Data > object2 <- CWOSL.SAR.Data > > object.new <- merge_Risoe.BINfileData(c(object1, object2)) > > > > > cleanEx() > nameEx("metadata") > ### * metadata > > flush(stderr()); flush(stdout()) > > ### Name: add_metadata<- > ### Title: Safe manipulation of object metadata > ### Aliases: add_metadata<- rename_metadata<- replace_metadata<- > ### add_metadata<-,RLum.Analysis-method > ### rename_metadata<-,RLum.Analysis-method > ### replace_metadata<-,RLum.Analysis-method > ### add_metadata<-,RLum.Data-method rename_metadata<-,RLum.Data-method > ### replace_metadata<-,RLum.Data-method > ### add_metadata<-,Risoe.BINfileData-method > ### rename_metadata<-,Risoe.BINfileData-method > ### replace_metadata<-,Risoe.BINfileData-method > ### Keywords: utilities > > ### ** Examples > > > ## load example data > data(ExampleData.BINfileData, envir = environment()) > > ## show data > CWOSL.SAR.Data [Risoe.BINfileData object] BIN/BINX version: 03 Object date: 060920, 070920, 080920, 090920, 100920 User: Default System ID: 0 (unknown) Overall records: 720 Records type: IRSL (n = 24) OSL (n = 336) TL (n = 360) Position range: 1 : 24 Run range: 1 : 8 Set range: 2 : 6 > > ## add a new field > add_metadata(CWOSL.SAR.Data, + info_element = "INSTITUTE") <- "Heidelberg University" > > ## rename a field > rename_metadata(CWOSL.SAR.Data, + info_element = "INSTITUTE") <- "INSTITUTION" > > ## replace all LTYPE to RSL > ## but only for the first position > replace_metadata( + object = CWOSL.SAR.Data, + info_element = "LTYPE", + subset = (POSITION == 1)) <- "RSL" > > ## replacing a field with NULL allows to remove that field > replace_metadata(CWOSL.SAR.Data, + info_element = "PREVIOUS") <- NULL > > ## show the modified data > CWOSL.SAR.Data [Risoe.BINfileData object] BIN/BINX version: 03 Object date: 060920, 070920, 080920, 090920, 100920 User: Default System ID: 0 (unknown) Overall records: 720 Records type: IRSL (n = 23) OSL (n = 322) RSL (n = 30) TL (n = 345) Position range: 1 : 24 Run range: 1 : 8 Set range: 2 : 6 > > > > > cleanEx() > nameEx("methods_RLum") > ### * methods_RLum > > flush(stderr()); flush(stdout()) > > ### Name: methods_RLum > ### Title: methods_RLum > ### Aliases: methods_RLum plot.list plot.RLum.Results plot.RLum.Analysis > ### plot.RLum.Data.Curve plot.RLum.Data.Spectrum plot.RLum.Data.Image > ### plot.Risoe.BINfileData hist.RLum.Results hist.RLum.Data.Image > ### hist.RLum.Data.Curve hist.RLum.Analysis summary.RLum.Results > ### summary.RLum.Analysis summary.RLum.Data.Image summary.RLum.Data.Curve > ### subset.Risoe.BINfileData subset.RLum.Analysis bin bin.RLum.Data.Curve > ### bin.RLum.Data.Spectrum length.RLum.Results length.RLum.Analysis > ### length.RLum.Data.Curve length.Risoe.BINfileData dim.RLum.Data.Curve > ### dim.RLum.Data.Spectrum rep.RLum names.RLum.Data.Curve > ### names.RLum.Data.Spectrum names.RLum.Data.Image names.RLum.Analysis > ### names.RLum.Results names.Risoe.BINfileData > ### row.names.RLum.Data.Spectrum as.data.frame.RLum.Data.Curve > ### as.data.frame.RLum.Data.Spectrum as.data.frame.Risoe.BINfileData > ### as.list.RLum.Results as.list.RLum.Data.Curve as.list.RLum.Data.Image > ### as.list.RLum.Data.Spectrum as.list.RLum.Analysis > ### as.matrix.RLum.Data.Curve as.matrix.RLum.Data.Spectrum > ### as.matrix.RLum.Data.Image merge.RLum unlist.RLum.Analysis > ### +.RLum.Data.Curve +.RLum.Data.Spectrum -.RLum.Data.Curve > ### -.RLum.Data.Spectrum *.RLum.Data.Curve *.RLum.Data.Spectrum > ### /.RLum.Data.Curve /.RLum.Data.Spectrum [.RLum.Data.Curve > ### [.RLum.Data.Spectrum [.RLum.Data.Image [.RLum.Analysis [.RLum.Results > ### [<-.RLum.Data.Curve [[.RLum.Analysis [[.RLum.Results > ### $.RLum.Data.Curve $.RLum.Analysis $.RLum.Results > ### Keywords: internal > > ### ** Examples > > > ##load example data > data(ExampleData.RLum.Analysis, envir = environment()) > > > ##combine curve is various ways > curve1 <- IRSAR.RF.Data[[1]] > curve2 <- IRSAR.RF.Data[[1]] > curve1 + curve2 [RLum.Data.Curve-class] recordType: RF (NA) curveType: merged measured values: 5 .. range of x-values: 0.1747448 6.311132 .. range of y-values: 2846.3 2875.6 additional info elements: 0 > curve1 - curve2 [RLum.Data.Curve-class] recordType: RF (NA) curveType: merged measured values: 5 .. range of x-values: 0.1747448 6.311132 .. range of y-values: 0 0 additional info elements: 0 > curve1 / curve2 [RLum.Data.Curve-class] recordType: RF (NA) curveType: merged measured values: 5 .. range of x-values: 0.1747448 6.311132 .. range of y-values: 1 1 additional info elements: 0 > curve1 * curve2 [RLum.Data.Curve-class] recordType: RF (NA) curveType: merged measured values: 5 .. range of x-values: 0.1747448 6.311132 .. range of y-values: 2025356 2067269 additional info elements: 0 > > > ##`$` access curves > IRSAR.RF.Data$RF [[1]] [RLum.Data.Curve-class] recordType: RF (NA) curveType: NA measured values: 5 .. range of x-values: 0.1747448 6.311132 .. range of y-values: 1423.15 1437.8 additional info elements: 0 [[2]] [RLum.Data.Curve-class] recordType: RF (NA) curveType: NA measured values: 524 .. range of x-values: 0.3768403 715.4821 .. range of y-values: 1379.947 2103.4 additional info elements: 0 > > > > > cleanEx() > nameEx("normalise_RLum") > ### * normalise_RLum > > flush(stderr()); flush(stdout()) > > ### Name: normalise_RLum > ### Title: Normalisation of RLum-class objects > ### Aliases: normalise_RLum normalise_RLum,list-method > ### normalise_RLum,RLum.Analysis-method > ### normalise_RLum,RLum.Data.Curve-method > ### normalise_RLum,RLum.Data.Image-method > ### normalise_RLum,RLum.Data.Spectrum-method > ### Keywords: utilities > > ### ** Examples > > > ## load example data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ## create RLum.Data.Curve object from this example > curve <- + set_RLum( + class = "RLum.Data.Curve", + recordType = "OSL", + data = as.matrix(ExampleData.CW_OSL_Curve) + ) > > ## plot data without and with smoothing > plot_RLum(curve) > plot_RLum(normalise_RLum(curve)) > > > > > cleanEx() > nameEx("plot_AbanicoPlot") > ### * plot_AbanicoPlot > > flush(stderr()); flush(stdout()) > > ### Name: plot_AbanicoPlot > ### Title: Function to create an Abanico Plot. > ### Aliases: plot_AbanicoPlot > > ### ** Examples > > > ## load example data and recalculate to Gray > data(ExampleData.DeValues, envir = environment()) > ExampleData.DeValues <- ExampleData.DeValues$CA1 > > ## plot the example data straightforward > plot_AbanicoPlot(data = ExampleData.DeValues) > > ## now with linear z-scale > plot_AbanicoPlot(data = ExampleData.DeValues, + log.z = FALSE) > > ## now with output of the plot parameters > plot1 <- plot_AbanicoPlot(data = ExampleData.DeValues) > str(plot1) List of 10 $ xlim : num [1:2] 0 16.1 $ ylim : num [1:2] -36.8 15.9 $ zlim : num [1:2] 17.4 132.9 $ polar.box : num [1:4] 0 16.1 -20.5 12.2 $ cartesian.box: num [1:4] 16.6 20.4 -20.5 12.2 $ plot.ratio : num 0.788 $ data :List of 1 ..$ :'data.frame': 62 obs. of 10 variables: .. ..$ De : num [1:62] 19.7 26.2 31.5 31.9 36.2 ... .. ..$ error : num [1:62] 2.14 2.04 2.34 2.34 2.95 3.15 8.22 3.23 4.43 4.43 ... .. ..$ z : num [1:62] 2.98 3.27 3.45 3.46 3.59 ... .. ..$ se : num [1:62] 0.1086 0.0779 0.0743 0.0732 0.0816 ... .. ..$ z.central : num [1:62] 4.13 4.13 4.13 4.13 4.13 ... .. ..$ precision : num [1:62] 9.21 12.84 13.45 13.65 12.26 ... .. ..$ std.estimate : num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ... .. ..$ std.estimate.plot: num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ... .. ..$ weights : num [1:62] 0.0161 0.0161 0.0161 0.0161 0.0161 ... .. ..$ data.in.2s : logi [1:62] FALSE FALSE FALSE FALSE FALSE FALSE ... $ data.global :'data.frame': 62 obs. of 10 variables: ..$ De : num [1:62] 19.7 26.2 31.5 31.9 36.2 ... ..$ error : num [1:62] 2.14 2.04 2.34 2.34 2.95 3.15 8.22 3.23 4.43 4.43 ... ..$ z : num [1:62] 2.98 3.27 3.45 3.46 3.59 ... ..$ se : num [1:62] 0.1086 0.0779 0.0743 0.0732 0.0816 ... ..$ z.central : num [1:62] 4.13 4.13 4.13 4.13 4.13 ... ..$ precision : num [1:62] 9.21 12.84 13.45 13.65 12.26 ... ..$ std.estimate : num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ... ..$ std.estimate.plot: num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ... ..$ weights : num [1:62] 0.0161 0.0161 0.0161 0.0161 0.0161 ... ..$ data set : num [1:62] 1 1 1 1 1 1 1 1 1 1 ... $ KDE :List of 1 ..$ : num [1:514, 1:2] 2.86 2.86 2.86 2.87 2.87 ... $ par :List of 66 ..$ xlog : logi FALSE ..$ ylog : logi FALSE ..$ adj : num 0.5 ..$ ann : logi TRUE ..$ ask : logi FALSE ..$ bg : chr "transparent" ..$ bty : chr "o" ..$ cex : num 1 ..$ cex.axis : num 1 ..$ cex.lab : num 1 ..$ cex.main : num 1.2 ..$ cex.sub : num 1 ..$ col : chr "black" ..$ col.axis : chr "black" ..$ col.lab : chr "black" ..$ col.main : chr "black" ..$ col.sub : chr "black" ..$ crt : num 0 ..$ err : int 0 ..$ family : chr "" ..$ fg : chr "black" ..$ fig : num [1:4] 0 1 0 1 ..$ fin : num [1:2] 7 7 ..$ font : int 1 ..$ font.axis: int 1 ..$ font.lab : int 1 ..$ font.main: int 2 ..$ font.sub : int 1 ..$ lab : int [1:3] 5 5 7 ..$ las : int 0 ..$ lend : chr "round" ..$ lheight : num 1 ..$ ljoin : chr "round" ..$ lmitre : num 10 ..$ lty : chr "solid" ..$ lwd : num 1 ..$ mai : num [1:4] 0.9 0.9 0.7 1.4 ..$ mar : num [1:4] 4.5 4.5 3.5 7 ..$ mex : num 1 ..$ mfcol : int [1:2] 1 1 ..$ mfg : int [1:4] 1 1 1 1 ..$ mfrow : int [1:2] 1 1 ..$ mgp : num [1:3] 3 1 0 ..$ mkh : num 0.001 ..$ new : logi FALSE ..$ oma : num [1:4] 0 0 0 0 ..$ omd : num [1:4] 0 1 0 1 ..$ omi : num [1:4] 0 0 0 0 ..$ pch : int 1 ..$ pin : num [1:2] 4.7 5.4 ..$ plt : num [1:4] 0.129 0.8 0.129 0.9 ..$ ps : int 12 ..$ pty : chr "m" ..$ smo : num 1 ..$ srt : num 0 ..$ tck : num NA ..$ tcl : num -0.5 ..$ usr : num [1:4] 0 20.4 -36.8 15.9 ..$ xaxp : num [1:3] 0 20 4 ..$ xaxs : chr "r" ..$ xaxt : chr "s" ..$ xpd : logi TRUE ..$ yaxp : num [1:3] -30 10 4 ..$ yaxs : chr "r" ..$ yaxt : chr "s" ..$ ylbias : num 0.2 > plot1$zlim [1] 17.41711 132.85700 > > ## now with adjusted z-scale limits > plot_AbanicoPlot(data = ExampleData.DeValues, + zlim = c(10, 200)) > > ## now with adjusted x-scale limits > plot_AbanicoPlot(data = ExampleData.DeValues, + xlim = c(0, 20)) > > ## now with rug to indicate individual values in KDE part > plot_AbanicoPlot(data = ExampleData.DeValues, + rug = TRUE) > > ## now with a smaller bandwidth for the KDE plot > plot_AbanicoPlot(data = ExampleData.DeValues, + bw = 0.04) > > ## now with a histogram instead of the KDE plot > plot_AbanicoPlot(data = ExampleData.DeValues, + hist = TRUE, + kde = FALSE) > > ## now with a KDE plot and histogram with manual number of bins > plot_AbanicoPlot(data = ExampleData.DeValues, + hist = TRUE, + breaks = 20) > > ## now with a KDE plot and a dot plot > plot_AbanicoPlot(data = ExampleData.DeValues, + dots = TRUE) > > ## now with user-defined plot ratio > plot_AbanicoPlot(data = ExampleData.DeValues, + plot.ratio = 0.5) > ## now with user-defined central value > plot_AbanicoPlot(data = ExampleData.DeValues, + z.0 = 70) > > ## now with median as central value > plot_AbanicoPlot(data = ExampleData.DeValues, + z.0 = "median") > > ## now with the 17-83 percentile range as definition of scatter > plot_AbanicoPlot(data = ExampleData.DeValues, + z.0 = "median", + dispersion = "p17") > > ## now with user-defined green line for minimum age model > CAM <- calc_CentralDose(ExampleData.DeValues, + plot = FALSE) [calc_CentralDose] ----------- meta data ---------------- n: 62 log: TRUE ----------- dose estimate ------------ abs. central dose: 65.71 abs. SE: 3.05 rel. SE [%]: 4.65 ----------- overdispersion ----------- abs. OD: 22.79 abs. SE: 2.27 OD [%]: 34.69 SE [%]: 3.46 ------------------------------------- > plot_AbanicoPlot(data = CAM, + line.col = "darkseagreen") > > ## now create plot with legend, colour, different points and smaller scale > plot_AbanicoPlot(data = ExampleData.DeValues, + legend = "Sample 1", + col = "tomato4", + bar.col = "peachpuff", + pch = "R", + cex = 0.8) > > ## now without 2-sigma bar, polygon, grid lines and central value line > plot_AbanicoPlot(data = ExampleData.DeValues, + bar.col = FALSE, + polygon.col = FALSE, + grid.col = FALSE, + y.axis = FALSE, + lwd = 0) > > ## now with direct display of De errors, without 2-sigma bar > plot_AbanicoPlot(data = ExampleData.DeValues, + bar.col = FALSE, + ylab = "", + y.axis = FALSE, + error.bars = TRUE) > > ## now with user-defined axes labels > plot_AbanicoPlot(data = ExampleData.DeValues, + xlab = c("Data error (%)", + "Data precision"), + ylab = "Scatter", + zlab = "Equivalent dose [Gy]") > > ## now with minimum, maximum and median value indicated > plot_AbanicoPlot(data = ExampleData.DeValues, + stats = c("min", "max", "median")) > > ## now with a brief statistical summary as subheader > plot_AbanicoPlot(data = ExampleData.DeValues, + summary = c("n", "in.2s")) > > ## now with another statistical summary > plot_AbanicoPlot(data = ExampleData.DeValues, + summary = c("mean.weighted", "median"), + summary.pos = "topleft") > > ## now a plot with two 2-sigma bars for one data set > plot_AbanicoPlot(data = ExampleData.DeValues, + bar = c(30, 100)) > > ## now the data set is split into sub-groups, one is manipulated > data.1 <- ExampleData.DeValues[1:30,] > data.2 <- ExampleData.DeValues[31:62,] * 1.3 > > ## now a common dataset is created from the two subgroups > data.3 <- list(data.1, data.2) > > ## now the two data sets are plotted in one plot > plot_AbanicoPlot(data = data.3) > > ## now with some graphical modification > plot_AbanicoPlot(data = data.3, + z.0 = "median", + col = c("steelblue4", "orange4"), + bar.col = c("steelblue3", "orange3"), + polygon.col = c("steelblue1", "orange1"), + pch = c(2, 6), + angle = c(30, 50), + summary = c("n", "in.2s", "median")) > > ## create Abanico plot with predefined layout definition > plot_AbanicoPlot(data = ExampleData.DeValues, + layout = "journal") > > ## now with predefined layout definition and further modifications > plot_AbanicoPlot( + data = data.3, + z.0 = "median", + layout = "journal", + col = c("steelblue4", "orange4"), + bar.col = adjustcolor(c("steelblue3", "orange3"), + alpha.f = 0.5), + polygon.col = c("steelblue3", "orange3")) > > ## for further information on layout definitions see documentation > ## of function get_Layout() > > ## now with manually added plot content > ## create empty plot with numeric output > AP <- plot_AbanicoPlot(data = ExampleData.DeValues, + pch = NA) > > ## identify data in 2 sigma range > in_2sigma <- AP$data[[1]]$data.in.2s > > ## restore function-internal plot parameters > par(AP$par) > > ## add points inside 2-sigma range > points(x = AP$data[[1]]$precision[in_2sigma], + y = AP$data[[1]]$std.estimate.plot[in_2sigma], + pch = 16) > > ## add points outside 2-sigma range > points(x = AP$data[[1]]$precision[!in_2sigma], + y = AP$data[[1]]$std.estimate.plot[!in_2sigma], + pch = 1) > > > > > graphics::par(get("par.postscript", pos = 'CheckExEnv')) > cleanEx() > nameEx("plot_DRCSummary") > ### * plot_DRCSummary > > flush(stderr()); flush(stdout()) > > ### Name: plot_DRCSummary > ### Title: Create a Dose-Response Curve Summary Plot > ### Aliases: plot_DRCSummary > > ### ** Examples > > > #load data example data > data(ExampleData.BINfileData, envir = environment()) > > #transform the values from the first position in a RLum.Analysis object > object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > > ## perform SAR analysis > results <- analyse_SAR.CWOSL( + object, + signal_integral = 1:2, + background_integral = 900:1000, + plot = FALSE + ) [analyse_SAR.CWOSL()] Fit: EXP (interpolation) | De = 1668.25 | D01 = 1982.76 > > ##plot only DRC > plot_DRCSummary(results) [RLum.Results-class] originator: plot_DRCSummary() data: 2 .. $results : data.frame .. $data : RLum.Results additional info elements: 2 > > > > > cleanEx() > nameEx("plot_DRTResults") > ### * plot_DRTResults > > flush(stderr()); flush(stdout()) > > ### Name: plot_DRTResults > ### Title: Visualise dose recovery test results > ### Aliases: plot_DRTResults > ### Keywords: dplot > > ### ** Examples > > > ## read example data set and misapply them for this plot type > data(ExampleData.DeValues, envir = environment()) > > ## plot values > plot_DRTResults( + ExampleData.DeValues$BT998[7:11,], + given.dose = 2800, + mtext = "Example data") > > ## plot values with legend > plot_DRTResults( + ExampleData.DeValues$BT998[7:11,], + given.dose = 2800, + legend = "Test data set") > > ## create and plot two subsets with randomised values > x.1 <- ExampleData.DeValues$BT998[7:11,] > x.2 <- ExampleData.DeValues$BT998[7:11,] * c(runif(5, 0.9, 1.1), 1) > > plot_DRTResults( + list(x.1, x.2), + given.dose = 2800) > > ## some more user-defined plot parameters > plot_DRTResults( + list(x.1, x.2), + given.dose = 2800, + pch = c(2, 5), + col = c("orange", "blue"), + xlim = c(0, 8), + ylim = c(0.85, 1.15), + xlab = "Sample aliquot") > > ## plot the data with user-defined statistical measures as legend > plot_DRTResults( + list(x.1, x.2), + given.dose = 2800, + summary = c("n", "weighted$mean", "sd.abs")) > > ## plot the data with user-defined statistical measures as sub-header > plot_DRTResults( + list(x.1, x.2), + given.dose = 2800, + summary = c("n", "weighted$mean", "sd.abs"), + summary.pos = "sub") > > ## plot the data grouped by preheat temperatures > plot_DRTResults( + ExampleData.DeValues$BT998[7:11,], + given.dose = 2800, + preheat = c(200, 200, 200, 240, 240)) > > ## read example data set and misapply them for this plot type > data(ExampleData.DeValues, envir = environment()) > > ## plot values > plot_DRTResults( + ExampleData.DeValues$BT998[7:11,], + given.dose = 2800, + mtext = "Example data") > > ## plot two data sets grouped by preheat temperatures > plot_DRTResults( + list(x.1, x.2), + given.dose = 2800, + preheat = c(200, 200, 200, 240, 240)) > > ## plot the data grouped by preheat temperatures as boxplots > plot_DRTResults( + ExampleData.DeValues$BT998[7:11,], + given.dose = 2800, + preheat = c(200, 200, 200, 240, 240), + boxplot = TRUE) > > > > > cleanEx() > nameEx("plot_DetPlot") > ### * plot_DetPlot > > flush(stderr()); flush(stdout()) > > ### Name: plot_DetPlot > ### Title: Create De(t) plot > ### Aliases: plot_DetPlot > > ### ** Examples > > > ## Not run: > ##D ##load data > ##D ##ExampleData.BINfileData contains two BINfileData objects > ##D ##CWOSL.SAR.Data and TL.SAR.Data > ##D data(ExampleData.BINfileData, envir = environment()) > ##D > ##D ##transform the values from the first position in a RLum.Analysis object > ##D object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > ##D > ##D plot_DetPlot( > ##D object, > ##D signal_integral = 1:3, > ##D background_integral = 900:1000, > ##D n.channels = 5) > ## End(Not run) > > > > > cleanEx() > nameEx("plot_DoseResponseCurve") > ### * plot_DoseResponseCurve > > flush(stderr()); flush(stdout()) > > ### Name: plot_DoseResponseCurve > ### Title: Plot a dose-response curve for luminescence data (Lx/Tx against > ### dose) > ### Aliases: plot_DoseResponseCurve > > ### ** Examples > > > ##(1) plot dose-response curve for a dummy dataset > data(ExampleData.LxTxData, envir = environment()) > fit <- fit_DoseResponseCurve(LxTxData) [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07 > plot_DoseResponseCurve(fit) > > ##(1b) horizontal plot arrangement > layout(mat = matrix(c(1,1,2,3), ncol = 2)) > plot_DoseResponseCurve(fit, plot_singlePanels = TRUE) > > ##(2) plot the dose-response curve with pdf output - uncomment to use > ##pdf(file = "~/Dose_Response_Curve_Dummy.pdf", paper = "special") > plot_DoseResponseCurve(fit) > ##dev.off() > > ##(3) plot the growth curve with pdf output - uncomment to use, single output > ##pdf(file = "~/Dose_Response_Curve_Dummy.pdf", paper = "special") > plot_DoseResponseCurve(fit, plot_singlePanels = TRUE) > ##dev.off() > > ##(4) plot resulting function for given interval x > x <- seq(1,10000, by = 100) > plot( + x = x, + y = eval(fit$Formula), + type = "l" + ) > > > > > cleanEx() > nameEx("plot_FilterCombinations") > ### * plot_FilterCombinations > > flush(stderr()); flush(stdout()) > > ### Name: plot_FilterCombinations > ### Title: Plot filter combinations along with the (optional) net > ### transmission window > ### Aliases: plot_FilterCombinations > ### Keywords: aplot datagen > > ### ** Examples > > > ## (For legal reasons no real filter data are provided) > > ## Create filter sets > filter1 <- density(rnorm(100, mean = 450, sd = 20)) > filter1 <- matrix(c(filter1$x, filter1$y/max(filter1$y)), ncol = 2) > filter2 <- matrix(c(200:799,rep(c(0,0.8,0),each = 200)), ncol = 2) > > ## Example 1 (standard) > plot_FilterCombinations(filters = list(filter1, filter2)) > > ## Example 2 (with d and P value and name for filter 2) > results <- plot_FilterCombinations( + filters = list(filter_1 = filter1, Rectangle = list(filter2, d = 2, P = 0.6))) > results [RLum.Results-class] originator: plot_FilterCombinations() data: 3 .. $net_transmission_window : matrix .. $OD_total : matrix .. $filter_matrix : matrix additional info elements: 1 > > ## Example 3 show optical density > plot(results$OD_total) > > ## Not run: > ##D ##Example 4 > ##D ##show the filters using the interactive mode > ##D plot_FilterCombinations(filters = list(filter1, filter2), interactive = TRUE) > ## End(Not run) > > > > > cleanEx() > nameEx("plot_GrowthCurve") > ### * plot_GrowthCurve > > flush(stderr()); flush(stdout()) > > ### Name: plot_GrowthCurve > ### Title: Fit and plot a dose-response curve for luminescence data (Lx/Tx > ### against dose) > ### Aliases: plot_GrowthCurve > > ### ** Examples > > > ##(1) plot growth curve for a dummy dataset > data(ExampleData.LxTxData, envir = environment()) > plot_GrowthCurve(LxTxData) [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07 > > ##(1b) horizontal plot arrangement > layout(mat = matrix(c(1,1,2,3), ncol = 2)) > plot_GrowthCurve(LxTxData, plot_singlePanels = TRUE) [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07 > > ##(2) plot the growth curve with pdf output - uncomment to use > ##pdf(file = "~/Desktop/Growth_Curve_Dummy.pdf", paper = "special") > plot_GrowthCurve(LxTxData) [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07 > ##dev.off() > > ##(3) plot the growth curve with pdf output - uncomment to use, single output > ##pdf(file = "~/Desktop/Growth_Curve_Dummy.pdf", paper = "special") > temp <- plot_GrowthCurve(LxTxData, plot_singlePanels = TRUE) [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07 > ##dev.off() > > ##(4) plot resulting function for given interval x > x <- seq(1,10000, by = 100) > plot( + x = x, + y = eval(temp$Formula), + type = "l" + ) > > ##(5) plot using the 'extrapolation' mode > LxTxData[1,2:3] <- c(0.5, 0.001) > print(plot_GrowthCurve(LxTxData, mode = "extrapolation")) [fit_DoseResponseCurve()] Fit: EXP (extrapolation) | De = 109.74 | D01 = 2624.06 [RLum.Results-class] originator: fit_DoseResponseCurve() data: 5 .. $De : data.frame .. $De.MC : numeric .. $Fit : nls .. $Fit.Args : list .. $Formula : expression additional info elements: 2 > > ##(6) plot using the 'alternate' mode > LxTxData[1,2:3] <- c(0.5, 0.001) > print(plot_GrowthCurve(LxTxData, mode = "alternate")) [fit_DoseResponseCurve()] Fit: EXP (alternate) | De = NA | D01 = 2624.06 [RLum.Results-class] originator: fit_DoseResponseCurve() data: 5 .. $De : data.frame .. $De.MC : numeric .. $Fit : nls .. $Fit.Args : list .. $Formula : expression additional info elements: 2 > > > > > cleanEx() > nameEx("plot_Histogram") > ### * plot_Histogram > > flush(stderr()); flush(stdout()) > > ### Name: plot_Histogram > ### Title: Plot a histogram with separate error plot > ### Aliases: plot_Histogram > > ### ** Examples > > > ## load data > data(ExampleData.DeValues, envir = environment()) > ExampleData.DeValues <- convert_Second2Gray(ExampleData.DeValues$BT998, + dose.rate = c(0.0438,0.0019)) > > ## plot histogram the easiest way > plot_Histogram(ExampleData.DeValues) > > ## plot histogram with some more modifications > plot_Histogram(ExampleData.DeValues, + rug = TRUE, + normal_curve = TRUE, + cex.global = 0.9, + pch = 2, + colour = c("grey", "black", "blue", "green"), + summary = c("n", "mean", "sdrel"), + summary.pos = "topleft", + main = "Histogram of De-values", + mtext = "Example data set", + ylab = c(expression(paste(D[e], " distribution")), + "Standard error"), + xlim = c(100, 250), + ylim = c(0, 0.1, 5, 20)) > > > > > cleanEx() > nameEx("plot_KDE") > ### * plot_KDE > > flush(stderr()); flush(stdout()) > > ### Name: plot_KDE > ### Title: Plot kernel density estimate with statistics > ### Aliases: plot_KDE > > ### ** Examples > > > ## read example data set > data(ExampleData.DeValues, envir = environment()) > ExampleData.DeValues <- + convert_Second2Gray(ExampleData.DeValues$BT998, c(0.0438,0.0019)) > > ## create plot straightforward > plot_KDE(data = ExampleData.DeValues) > > ## create plot with logarithmic x-axis > plot_KDE(data = ExampleData.DeValues, + log = "x") > > ## create plot with user-defined labels and axes limits > plot_KDE(data = ExampleData.DeValues, + main = "Dose distribution", + xlab = "Dose (s)", + ylab = c("KDE estimate", "Cumulative dose value"), + xlim = c(100, 250), + ylim = c(0, 0.08, 0, 30)) > > ## create plot with boxplot option > plot_KDE(data = ExampleData.DeValues, + boxplot = TRUE) > > ## create plot with statistical summary below header > plot_KDE(data = ExampleData.DeValues, + summary = c("n", "median", "skewness", "in.2s")) > > ## create plot with statistical summary as legend > plot_KDE(data = ExampleData.DeValues, + summary = c("n", "mean", "sd.rel", "se.abs"), + summary.pos = "topleft") > > ## split data set into sub-groups, one is manipulated, and merge again > data.1 <- ExampleData.DeValues[1:15,] > data.2 <- ExampleData.DeValues[16:25,] * 1.3 > data.3 <- list(data.1, data.2) > > ## create plot with two subsets straightforward > plot_KDE(data = data.3) > > ## create plot with two subsets and summary legend at user coordinates > plot_KDE(data = data.3, + summary = c("n", "median", "skewness"), + summary.pos = c(110, 0.07), + col = c("blue", "orange")) > > ## example of how to use the numerical output of the function > ## return plot output to draw a thicker KDE line > KDE_out <- plot_KDE(data = ExampleData.DeValues) > > > > > cleanEx() > nameEx("plot_MoranScatterplot") > ### * plot_MoranScatterplot > > flush(stderr()); flush(stdout()) > > ### Name: plot_MoranScatterplot > ### Title: Moran Scatter Plot: Visualizing Spatial Dependency > ### Aliases: plot_MoranScatterplot > > ### ** Examples > > plot_MoranScatterplot(1:100) > > > > > cleanEx() > nameEx("plot_NRt") > ### * plot_NRt > > flush(stderr()); flush(stdout()) > > ### Name: plot_NRt > ### Title: Visualise natural/regenerated signal ratios > ### Aliases: plot_NRt > > ### ** Examples > > > ## load example data > data("ExampleData.BINfileData", envir = environment()) > > ## EXAMPLE 1 > > ## convert Risoe.BINfileData object to RLum.Analysis object > data <- Risoe.BINfileData2RLum.Analysis(object = CWOSL.SAR.Data, pos = 8, ltype = "OSL") > > ## extract all OSL curves > allCurves <- get_RLum(data) > > ## keep only the natural and regenerated signal curves > pos <- seq(1, 9, 2) > curves <- allCurves[pos] > > ## plot a standard NR(t) plot > plot_NRt(curves) > > ## re-plot with rolling mean data smoothing > plot_NRt(curves, smooth = "rmean", k = 10) > > ## re-plot with a logarithmic x-axis > plot_NRt(curves, log = "x", smooth = "rmean", k = 5) > > ## re-plot with custom axes ranges > plot_NRt(curves, smooth = "rmean", k = 5, + xlim = c(0.1, 5), ylim = c(0.4, 1.6), + legend.pos = "bottomleft") > > ## re-plot with smoothing spline on log scale > plot_NRt(curves, smooth = "spline", log = "x", + legend.pos = "top") > > ## EXAMPLE 2 > > # you may also use this function to check whether all > # TD curves follow the same shape (making it a TnTx(t) plot). > posTD <- seq(2, 14, 2) > curves <- allCurves[posTD] > > plot_NRt(curves, main = "TnTx(t) Plot", + smooth = "rmean", k = 20, + ylab = "TD natural / TD regenerated", + xlim = c(0, 20), legend = FALSE) > > ## EXAMPLE 3 > > # extract data from all positions > data <- lapply(1:24, FUN = function(pos) { + Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos = pos, ltype = "OSL") + }) > > # get individual curve data from each aliquot > aliquot <- lapply(data, get_RLum) > > # set graphical parameters > par(mfrow = c(2, 2)) > > # create NR(t) plots for all aliquots > for (i in 1:length(aliquot)) { + plot_NRt(aliquot[[i]][pos], + main = paste0("Aliquot #", i), + smooth = "rmean", k = 20, + xlim = c(0, 10), + cex = 0.6, legend.pos = "bottomleft") + } > > # reset graphical parameters > par(mfrow = c(1, 1)) > > > > > graphics::par(get("par.postscript", pos = 'CheckExEnv')) > cleanEx() > nameEx("plot_OSLAgeSummary") > ### * plot_OSLAgeSummary > > flush(stderr()); flush(stdout()) > > ### Name: plot_OSLAgeSummary > ### Title: Plot Posterior OSL-Age Summary > ### Aliases: plot_OSLAgeSummary > ### Keywords: dplot hplot > > ### ** Examples > > ##generate random data > set.seed(1234) > object <- rnorm(1000, 100, 10) > plot_OSLAgeSummary(object) [plot_OSLAgeSummary()] Credible Interval (95 %): 80.5 : 120.6 Bayes estimate (posterior mean ± sd): 99.7 ± 10 [RLum.Results-class] originator: plot_OSLAgeSummary() data: 3 .. $Estimate : numeric .. $Credible_Interval : matrix .. $level : numeric additional info elements: 1 > > > > > cleanEx() > nameEx("plot_RLum.Analysis") > ### * plot_RLum.Analysis > > flush(stderr()); flush(stdout()) > > ### Name: plot_RLum.Analysis > ### Title: Plot function for an 'RLum.Analysis' S4 class object > ### Aliases: plot_RLum.Analysis > ### Keywords: aplot > > ### ** Examples > > > ##load data > data(ExampleData.BINfileData, envir = environment()) > > ##convert values for position 1 > temp <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos=1) > > ##(1) plot (combine) TL curves in one plot > plot_RLum.Analysis( + temp, + subset = list(recordType = "TL"), + combine = TRUE, + norm = TRUE, + abline = list(v = c(110)) + ) > > ##(2) same as example (1) but using > ## the argument smooth = TRUE > plot_RLum.Analysis( + temp, + subset = list(recordType = "TL"), + combine = TRUE, + norm = TRUE, + smooth = TRUE, + abline = list(v = c(110)) + ) > > > > > cleanEx() > nameEx("plot_RLum.Data.Curve") > ### * plot_RLum.Data.Curve > > flush(stderr()); flush(stdout()) > > ### Name: plot_RLum.Data.Curve > ### Title: Plot function for an RLum.Data.Curve S4 class object > ### Aliases: plot_RLum.Data.Curve > ### Keywords: aplot > > ### ** Examples > > > ##plot curve data > > #load Example data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > #transform data.frame to RLum.Data.Curve object > temp <- as(ExampleData.CW_OSL_Curve, "RLum.Data.Curve") > > #plot RLum.Data.Curve object > plot_RLum.Data.Curve(temp) > > > > > cleanEx() > nameEx("plot_RLum.Data.Image") > ### * plot_RLum.Data.Image > > flush(stderr()); flush(stdout()) > > ### Name: plot_RLum.Data.Image > ### Title: Plot function for an 'RLum.Data.Image' S4 class object > ### Aliases: plot_RLum.Data.Image > ### Keywords: aplot > > ### ** Examples > > > ##load data > data(ExampleData.RLum.Data.Image, envir = environment()) > > ##plot data > plot_RLum.Data.Image(ExampleData.RLum.Data.Image) > > > > > cleanEx() > nameEx("plot_RLum.Data.Spectrum") > ### * plot_RLum.Data.Spectrum > > flush(stderr()); flush(stdout()) > > ### Name: plot_RLum.Data.Spectrum > ### Title: Plot function for an RLum.Data.Spectrum S4 class object > ### Aliases: plot_RLum.Data.Spectrum > ### Keywords: aplot > > ### ** Examples > > > ##load example data > data(ExampleData.XSYG, envir = environment()) > > ##(1)plot simple spectrum (2D) - image > plot_RLum.Data.Spectrum( + TL.Spectrum, + plot.type="image", + xlim = c(310,750), + ylim = c(0,300), + bin.rows=10, + bin.cols = 1) Warning: [plot_RLum.Data.Spectrum()] 6 channels removed due to row (wavelength) binning > > ##(2) plot spectrum (3D) > plot_RLum.Data.Spectrum( + TL.Spectrum, + plot.type="persp", + xlim = c(310,750), + ylim = c(0,100), + bin.rows=10, + bin.cols = 1) Warning: [plot_RLum.Data.Spectrum()] 6 channels removed due to row (wavelength) binning > > ##(3) plot spectrum on energy axis > ##please note the background subtraction > plot_RLum.Data.Spectrum(TL.Spectrum, + plot.type="persp", + ylim = c(0,200), + bin.rows=10, + bg.channels = 10, + bin.cols = 1, + xaxis.energy = TRUE) Warning: [plot_RLum.Data.Spectrum()] 3 channels removed due to row (wavelength) binning > > ##(4) plot multiple lines (2D) - multiple.lines (with ylim) > plot_RLum.Data.Spectrum( + TL.Spectrum, + plot.type="multiple.lines", + xlim = c(310,750), + ylim = c(0,100), + bin.rows=10, + bin.cols = 1) Warning: [plot_RLum.Data.Spectrum()] 6 channels removed due to row (wavelength) binning > > ## Not run: > ##D ##(4) interactive plot using the package plotly ("surface") > ##D plot_RLum.Data.Spectrum(TL.Spectrum, plot.type="interactive", > ##D xlim = c(310,750), ylim = c(0,300), bin.rows=10, > ##D bin.cols = 1) > ##D > ##D ##(5) interactive plot using the package plotly ("contour") > ##D plot_RLum.Data.Spectrum(TL.Spectrum, plot.type="interactive", > ##D xlim = c(310,750), ylim = c(0,300), bin.rows=10, > ##D bin.cols = 1, > ##D type = "contour", > ##D showscale = TRUE) > ##D > ##D ##(6) interactive plot using the package plotly ("heatmap") > ##D plot_RLum.Data.Spectrum(TL.Spectrum, plot.type="interactive", > ##D xlim = c(310,750), ylim = c(0,300), bin.rows=10, > ##D bin.cols = 1, > ##D type = "heatmap", > ##D showscale = TRUE) > ## End(Not run) > > > > > cleanEx() > nameEx("plot_RLum") > ### * plot_RLum > > flush(stderr()); flush(stdout()) > > ### Name: plot_RLum > ### Title: General plot function for RLum S4 class objects > ### Aliases: plot_RLum > ### Keywords: dplot > > ### ** Examples > > #load Example data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > #transform data.frame to RLum.Data.Curve object > temp <- as(ExampleData.CW_OSL_Curve, "RLum.Data.Curve") > > #plot RLum object > plot_RLum(temp) > > > > > cleanEx() > nameEx("plot_RLum.Results") > ### * plot_RLum.Results > > flush(stderr()); flush(stdout()) > > ### Name: plot_RLum.Results > ### Title: Plot function for an RLum.Results S4 class object > ### Aliases: plot_RLum.Results > ### Keywords: aplot > > ### ** Examples > > > > ###load data > data(ExampleData.DeValues, envir = environment()) > > # apply the un-logged minimum age model > mam <- calc_MinDose(data = ExampleData.DeValues$CA1, sigmab = 0.2, log = TRUE, plot = FALSE) ----------- Meta data ----------- n par sigmab logged Lmax BIC 62 3 0.2 TRUE -32.43138 84.14389 --- Final parameter estimates --- gamma sigma p0 Estimate 45.64 1.56 0.02 ------ Confidence intervals ----- 2.5 % 97.5 % gamma 38.61 53.65 sigma 1.33 1.89 p0 NA 0.28 ------ De (asymmetric error) ----- De lower upper 45.64 38.61 53.65 ------ De (symmetric error) ----- De error 45.64 3.84 > > ##plot > plot_RLum.Results(mam) > > # estimate the number of grains on an aliquot > grains<- calc_AliquotSize(grain.size = c(100,150), sample.diameter = 1, plot = FALSE, MC.iter = 100) [calc_AliquotSize] --------------------------------------------------------- mean grain size (microns) : 125 sample diameter (mm) : 1 packing density : 0.65 number of grains : 42 --------------- Monte Carlo Estimates ------------------- number of iterations (n) : 100 median : 36 mean : 42 standard deviation (mean) : 20 standard error (mean) : 2 95% CI from t-test (mean) : 38 - 46 standard error from CI (mean): 2 --------------------------------------------------------- > > ##plot > plot_RLum.Results(grains) > > > > > > cleanEx() > nameEx("plot_ROI") > ### * plot_ROI > > flush(stderr()); flush(stdout()) > > ### Name: plot_ROI > ### Title: Create Regions of Interest (ROI) Graphic > ### Aliases: plot_ROI > ### Keywords: datagen plot > > ### ** Examples > > > ## simple example > file <- system.file("extdata", "RF_file.rf", package = "Luminescence") > temp <- read_RF2R(file) [read_RF2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: RF_file.rf > plot_ROI(temp) > > ## in combination with extract_ROI() > m <- matrix(runif(100,0,255), ncol = 10, nrow = 10) > roi <- matrix(c(2.,4,2,5,6,7,3,1,1), ncol = 3) > t <- extract_ROI(object = m, roi = roi) > plot_ROI(t, bg_image = m) > > > > > cleanEx() > nameEx("plot_RadialPlot") > ### * plot_RadialPlot > > flush(stderr()); flush(stdout()) > > ### Name: plot_RadialPlot > ### Title: Function to create a Radial Plot > ### Aliases: plot_RadialPlot > > ### ** Examples > > > ## load example data > data(ExampleData.DeValues, envir = environment()) > ExampleData.DeValues <- convert_Second2Gray( + ExampleData.DeValues$BT998, c(0.0438,0.0019)) > > ## plot the example data straightforward > plot_RadialPlot(data = ExampleData.DeValues) > > ## now with linear z-scale > plot_RadialPlot( + data = ExampleData.DeValues, + log.z = FALSE) > > ## store the the plot parameters > plot1 <- plot_RadialPlot( + data = ExampleData.DeValues, + log.z = FALSE) > plot1 $data $data[[1]] De error z se z.central precision std.estimate std.estimate.plot 1 151.48 5.334 151.48 5.334 126.8469 0.1874766 4.61813168 4.61813168 2 152.08 5.144 152.08 5.144 126.8469 0.1944012 4.90534883 4.90534883 3 165.80 6.805 165.80 6.805 126.8469 0.1469508 5.72419021 5.72419021 4 136.15 4.608 136.15 4.608 126.8469 0.2170139 2.01890503 2.01890503 5 144.42 4.642 144.42 4.642 126.8469 0.2154244 3.78567738 3.78567738 6 123.44 4.471 123.44 4.471 126.8469 0.2236636 -0.76199634 -0.76199634 7 123.64 4.227 123.64 4.227 126.8469 0.2365744 -0.75866705 -0.75866705 8 127.07 4.396 127.07 4.396 126.8469 0.2274795 0.05075395 0.05075395 9 125.06 4.630 125.06 4.630 126.8469 0.2159827 -0.38593642 -0.38593642 10 124.45 4.256 124.45 4.256 126.8469 0.2349624 -0.56317801 -0.56317801 11 118.60 4.049 118.60 4.049 126.8469 0.2469746 -2.03677096 -2.03677096 12 128.08 4.408 128.08 4.408 126.8469 0.2268603 0.27974464 0.27974464 13 110.78 3.701 110.78 3.701 126.8469 0.2701972 -4.34122821 -4.34122821 14 121.02 4.187 121.02 4.187 126.8469 0.2388345 -1.39166124 -1.39166124 15 124.09 4.129 124.09 4.129 126.8469 0.2421894 -0.66768845 -0.66768845 16 124.70 4.043 124.70 4.043 126.8469 0.2473411 -0.53101302 -0.53101302 17 123.68 4.262 123.68 4.262 126.8469 0.2346316 -0.74305153 -0.74305153 18 126.34 4.228 126.34 4.228 126.8469 0.2365184 -0.11988780 -0.11988780 19 128.59 4.254 128.59 4.254 126.8469 0.2350729 0.40975890 0.40975890 20 131.46 4.448 131.46 4.448 126.8469 0.2248201 1.03712104 1.03712104 21 127.77 4.330 127.77 4.330 126.8469 0.2309469 0.21319039 0.21319039 22 131.05 5.023 131.05 5.023 126.8469 0.1990842 0.83677372 0.83677372 23 126.34 4.317 126.34 4.317 126.8469 0.2316423 -0.11741617 -0.11741617 24 115.49 3.479 115.49 3.479 126.8469 0.2874389 -3.26441093 -3.26441093 25 119.58 3.815 119.58 3.815 126.8469 0.2621232 -1.90481930 -1.90481930 .id 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 11 1 12 1 13 1 14 1 15 1 16 1 17 1 18 1 19 1 20 1 21 1 22 1 23 1 24 1 25 1 $data.global De error z se z.central precision std.estimate std.estimate.plot 1 151.48 5.334 151.48 5.334 126.8469 0.1874766 4.61813168 4.61813168 2 152.08 5.144 152.08 5.144 126.8469 0.1944012 4.90534883 4.90534883 3 165.80 6.805 165.80 6.805 126.8469 0.1469508 5.72419021 5.72419021 4 136.15 4.608 136.15 4.608 126.8469 0.2170139 2.01890503 2.01890503 5 144.42 4.642 144.42 4.642 126.8469 0.2154244 3.78567738 3.78567738 6 123.44 4.471 123.44 4.471 126.8469 0.2236636 -0.76199634 -0.76199634 7 123.64 4.227 123.64 4.227 126.8469 0.2365744 -0.75866705 -0.75866705 8 127.07 4.396 127.07 4.396 126.8469 0.2274795 0.05075395 0.05075395 9 125.06 4.630 125.06 4.630 126.8469 0.2159827 -0.38593642 -0.38593642 10 124.45 4.256 124.45 4.256 126.8469 0.2349624 -0.56317801 -0.56317801 11 118.60 4.049 118.60 4.049 126.8469 0.2469746 -2.03677096 -2.03677096 12 128.08 4.408 128.08 4.408 126.8469 0.2268603 0.27974464 0.27974464 13 110.78 3.701 110.78 3.701 126.8469 0.2701972 -4.34122821 -4.34122821 14 121.02 4.187 121.02 4.187 126.8469 0.2388345 -1.39166124 -1.39166124 15 124.09 4.129 124.09 4.129 126.8469 0.2421894 -0.66768845 -0.66768845 16 124.70 4.043 124.70 4.043 126.8469 0.2473411 -0.53101302 -0.53101302 17 123.68 4.262 123.68 4.262 126.8469 0.2346316 -0.74305153 -0.74305153 18 126.34 4.228 126.34 4.228 126.8469 0.2365184 -0.11988780 -0.11988780 19 128.59 4.254 128.59 4.254 126.8469 0.2350729 0.40975890 0.40975890 20 131.46 4.448 131.46 4.448 126.8469 0.2248201 1.03712104 1.03712104 21 127.77 4.330 127.77 4.330 126.8469 0.2309469 0.21319039 0.21319039 22 131.05 5.023 131.05 5.023 126.8469 0.1990842 0.83677372 0.83677372 23 126.34 4.317 126.34 4.317 126.8469 0.2316423 -0.11741617 -0.11741617 24 115.49 3.479 115.49 3.479 126.8469 0.2874389 -3.26441093 -3.26441093 25 119.58 3.815 119.58 3.815 126.8469 0.2621232 -1.90481930 -1.90481930 .id 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 11 1 12 1 13 1 14 1 15 1 16 1 17 1 18 1 19 1 20 1 21 1 22 1 23 1 24 1 25 1 $xlim [1] 0.0000000 0.2874389 $ylim [1] -16.89314 20.48852 $zlim [1] 93.89862 191.06569 $r [1] 0.3043386 $plot.ratio [1] 0.8181818 $ticks.major tick.x1.major tick.x2.major tick.y1.major tick.y2.major [1,] 0.2848427 0.2891153 -9.385079 -9.525855 [2,] 0.2454161 0.2490973 15.760403 15.996809 [3,] 0.2909708 0.2953353 -7.811659 -7.928834 [4,] 0.3034125 0.3079637 -2.077431 -2.108592 [5,] 0.3009624 0.3054768 3.958593 4.017971 [6,] 0.2846227 0.2888920 9.436128 9.577670 [7,] 0.2601617 0.2640641 13.828402 14.035828 $ticks.minor tick.x1.minor tick.x2.minor tick.y1.minor tick.y2.minor [1,] 0.2860110 0.2880130 -9.1085584 -9.1723183 [2,] 0.2909708 0.2930076 -7.8116592 -7.8663408 [3,] 0.2952874 0.2973544 -6.4511101 -6.4962679 [4,] 0.2988580 0.3009500 -5.0348264 -5.0700701 [5,] 0.3015911 0.3037022 -3.5729147 -3.5979251 [6,] 0.3034125 0.3055364 -2.0774306 -2.0919726 [7,] 0.3042709 0.3064008 -0.5619535 -0.5658872 [8,] 0.3041414 0.3062704 0.9589928 0.9657057 [9,] 0.3030279 0.3051491 2.4706214 2.4879158 [10,] 0.3009624 0.3030691 3.9585925 3.9863027 [11,] 0.2980026 0.3000886 5.4096745 5.4475422 [12,] 0.2942277 0.2962873 6.8122870 6.8599730 [13,] 0.2897328 0.2917609 8.1568798 8.2139780 [14,] 0.2846227 0.2866150 9.4361279 9.5021808 [15,] 0.2790061 0.2809591 10.6449512 10.7194659 [16,] 0.2729905 0.2749014 11.7803885 11.8628512 [17,] 0.2666778 0.2685445 12.8413657 12.9312553 [18,] 0.2601617 0.2619828 13.8284022 13.9252010 [19,] 0.2535254 0.2553001 14.7432926 14.8464957 [20,] 0.2468413 0.2485692 15.5887963 15.6979178 $labels label.x label.y label.z.text [1,] 0.2933880 -9.666631 93.9 [2,] 0.2527785 16.233215 191.0 [3,] 0.2996999 -8.046009 100.0 [4,] 0.3125149 -2.139754 120.0 [5,] 0.3099912 4.077350 140.0 [6,] 0.2931614 9.719212 160.0 [7,] 0.2679665 14.243254 180.0 $polygons [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 0 0 0.2874389 0.2874389 -2 2 2 -2 $ellipse.lims [,1] [,2] [1,] 0.2848427 0.2454161 [2,] -9.3850787 15.7604025 > plot1$zlim [1] 93.89862 191.06569 > > ## now with adjusted z-scale limits > plot_RadialPlot( + data = ExampleData.DeValues, + log.z = FALSE, + xlim = c(0, 5), + zlim = c(100, 200)) > > ## now the two plots with serious but seasonally changing fun > #plot_RadialPlot(data = data.3, fun = TRUE) > > ## now with user-defined central value, in log-scale again > plot_RadialPlot( + data = ExampleData.DeValues, + central.value = 150) > > ## now with a rug, indicating individual De values at the z-scale > plot_RadialPlot( + data = ExampleData.DeValues, + rug = TRUE) > > ## now with legend, colour, different points and smaller scale > plot_RadialPlot( + data = ExampleData.DeValues, + legend = "Sample 1", + col = "tomato4", + bar.col = "peachpuff", + pch = "R", + cex = 0.8) > > ## now without 2-sigma bar, y-axis, grid lines and central value line > plot_RadialPlot( + data = ExampleData.DeValues, + bar.col = "none", + grid.col = "none", + y.ticks = FALSE, + lwd = 0) > > ## now with user-defined axes labels > plot_RadialPlot( + data = ExampleData.DeValues, + xlab = c("Data error (%)", "Data precision"), + ylab = "Scatter", + zlab = "Equivalent dose [Gy]") > > ## now with minimum, maximum and median value indicated > plot_RadialPlot( + data = ExampleData.DeValues, + central.value = 150, + stats = c("min", "max", "median")) > > ## now with a brief statistical summary > plot_RadialPlot( + data = ExampleData.DeValues, + summary = c("n", "in.2s")) > > ## now with another statistical summary as subheader > plot_RadialPlot( + data = ExampleData.DeValues, + summary = c("mean.weighted", "median"), + summary.pos = "sub") > > ## now the data set is split into sub-groups, one is manipulated > data.1 <- ExampleData.DeValues[1:15,] > data.2 <- ExampleData.DeValues[16:25,] * 1.3 > > ## now a common dataset is created from the two subgroups > data.3 <- list(data.1, data.2) > > ## now the two data sets are plotted in one plot > plot_RadialPlot(data = data.3) > > ## now with some graphical modification > plot_RadialPlot( + data = data.3, + col = c("darkblue", "darkgreen"), + bar.col = c("lightblue", "lightgreen"), + pch = c(2, 6), + summary = c("n", "in.2s"), + summary.pos = "sub", + legend = c("Sample 1", "Sample 2")) > > > > > cleanEx() > nameEx("plot_Risoe.BINfileData") > ### * plot_Risoe.BINfileData > > flush(stderr()); flush(stdout()) > > ### Name: plot_Risoe.BINfileData > ### Title: Plot Single Luminescence Curves from a Risoe.BINfileData-class > ### object > ### Aliases: plot_Risoe.BINfileData > ### Keywords: dplot > > ### ** Examples > > > ##load data > data(ExampleData.BINfileData, envir = environment()) > > ##plot all curves from the first position to the desktop > #pdf(file = "~/Desktop/CurveOutput.pdf", paper = "a4", height = 11, onefile = TRUE) > > ##example - load from *.bin file > #BINfile<- file.choose() > #BINfileData<-read_BIN2R(BINfile) > > #par(mfrow = c(4,3), oma = c(0.5,1,0.5,1)) > #plot_Risoe.BINfileData(CWOSL.SAR.Data,position = 1) > #mtext(side = 4, BINfile, outer = TRUE, col = "blue", cex = .7) > #dev.off() > > > > > cleanEx() > nameEx("plot_SingleGrainDisc") > ### * plot_SingleGrainDisc > > flush(stderr()); flush(stdout()) > > ### Name: plot_SingleGrainDisc > ### Title: Plot a disc with its values > ### Aliases: plot_SingleGrainDisc > > ### ** Examples > > > plot_SingleGrainDisc(1:100) > > > > > cleanEx() > nameEx("plot_ViolinPlot") > ### * plot_ViolinPlot > > flush(stderr()); flush(stdout()) > > ### Name: plot_ViolinPlot > ### Title: Create a violin plot > ### Aliases: plot_ViolinPlot > > ### ** Examples > > > ## read example data set > data(ExampleData.DeValues, envir = environment()) > ExampleData.DeValues <- convert_Second2Gray(ExampleData.DeValues$BT998, + c(0.0438,0.0019)) > > ## create plot straightforward > plot_ViolinPlot(data = ExampleData.DeValues) > > > > > cleanEx() > nameEx("read_BIN2R") > ### * read_BIN2R > > flush(stderr()); flush(stdout()) > > ### Name: read_BIN2R > ### Title: Import Risø BIN/BINX-files into R > ### Aliases: read_BIN2R > ### Keywords: IO > > ### ** Examples > > > file <- system.file("extdata/BINfile_V8.binx", package = "Luminescence") > temp <- read_BIN2R(file) [read_BIN2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: BINfile_V8.binx n_rec: 2 | | | 0% | |=================================== | 50% | |======================================================================| 100% >> 2 records read successfully > temp [Risoe.BINfileData object] BIN/BINX version: 8 File name: ExampleData.BINfileData Object date: 060920 User: Default System ID: 0 (unknown) Overall records: 2 Records type: TL (n = 2) Position range: 1 : 2 Run range: 1 : 1 Set range: 2 : 2 > > > > > cleanEx() > nameEx("read_BINXLOG2R") > ### * read_BINXLOG2R > > flush(stderr()); flush(stdout()) > > ### Name: read_BINXLOG2R > ### Title: Import Risø BINX-data from the BINX Log File > ### Aliases: read_BINXLOG2R > ### Keywords: IO > > ### ** Examples > > ## read log file (RLum.Analysis) > file <- system.file("extdata/BINX_IRSL_LOG.TXT", package = "Luminescence") > object <- read_BINXLOG2R(file = file) [read_BINXLOG2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: BINX_IRSL_LOG.TXT size: 13.39 kB > > ## convert to RisoeBINFile-class object > object <- convert_RLum2Risoe.BINfileData(object) > > ## export as BINX > ## Not run: > ##D write_R2BIN(t, file = tempfile(), version = "04") > ## End(Not run) > > > > > cleanEx() > nameEx("read_Daybreak2R") > ### * read_Daybreak2R > > flush(stderr()); flush(stdout()) > > ### Name: read_Daybreak2R > ### Title: Import measurement data produced by a Daybreak TL/OSL reader > ### into R > ### Aliases: read_Daybreak2R > ### Keywords: IO > > ### ** Examples > > > ## Not run: > ##D file <- system.file("extdata/Daybreak_TestFile.txt", package = "Luminescence") > ##D temp <- read_Daybreak2R(file) > ## End(Not run) > > > > > cleanEx() > nameEx("read_HeliosOSL2R") > ### * read_HeliosOSL2R > > flush(stderr()); flush(stdout()) > > ### Name: read_HeliosOSL2R > ### Title: Import Luminescence Data from Helios Luminescence Reader > ### Aliases: read_HeliosOSL2R > ### Keywords: IO > > ### ** Examples > > file <- system.file("extdata/HeliosOSL_Example.osl", package = "Luminescence") > read_HeliosOSL2R(file) [read_HeliosOSL2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: HeliosOSL_Example.osl [RLum.Analysis-class] originator: read_HeliosOSL2R() protocol: NA additional info elements: 0 number of records: 6 .. : RLum.Data.Curve : 6 .. .. : #1 OSL (J) <> #2 OSL (Jcorr) <> #3 OSL (Jphd) <> #4 OSL (dt.s.) <> #5 OSL (T.K.) <> #6 OSL (ILed.A.) > > > > > cleanEx() > nameEx("read_PSL2R") > ### * read_PSL2R > > flush(stderr()); flush(stdout()) > > ### Name: read_PSL2R > ### Title: Import SUERC portable OSL Reader PSL files into R > ### Aliases: read_PSL2R > ### Keywords: IO > > ### ** Examples > > > # (1) Import PSL file to R > > file <- system.file("extdata", "DorNie_0016.psl", package = "Luminescence") > psl <- read_PSL2R(file, drop_bg = FALSE, as_decay_curve = TRUE, smooth = TRUE, merge = FALSE) [read_PSL2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: DorNie_0016.psl > print(str(psl, max.level = 3)) Formal class 'RLum.Analysis' [package "Luminescence"] with 6 slots ..@ protocol : chr "portable OSL" ..@ records :List of 5 .. ..$ :Formal class 'RLum.Data.Curve' [package "Luminescence"] with 7 slots .. ..$ :Formal class 'RLum.Data.Curve' [package "Luminescence"] with 7 slots .. ..$ :Formal class 'RLum.Data.Curve' [package "Luminescence"] with 7 slots .. ..$ :Formal class 'RLum.Data.Curve' [package "Luminescence"] with 7 slots .. ..$ :Formal class 'RLum.Data.Curve' [package "Luminescence"] with 7 slots ..@ originator: chr "read_PSL2R" ..@ info :List of 15 .. ..$ Run_Name : chr "ALU" .. ..$ Sample_no : chr "0016" .. ..$ Sequence_Name : chr "Praktikum2016" .. ..$ Filename : chr "Praktikum2016" .. ..$ Dark_Count : chr "15 c/s" .. ..$ Light_Count : chr "0 c/s" .. ..$ Dark_Count_Correction: chr "OFF" .. ..$ Offset_Subtract : chr "ON" .. ..$ Datafile_Path : chr "D:\\Results\\DORNIE\\ALU\\ALU0016.psl" .. ..$ Summary_Path : chr "D:\\Results\\DORNIE\\ALU\\summary\\ALU.sum" .. ..$ Run_Sequence : chr "Praktikum2016" .. ..$ Date : Date[1:1], format: "2016-05-19" .. ..$ Time : chr "4:45:12" .. ..$ Sample : chr "L11" .. ..$ Sequence :'data.frame': 5 obs. of 5 variables: ..@ .uid : chr "cec381a6b74bff81" ..@ .pid : chr NA NULL > plot(psl, combine = TRUE) > > > > > cleanEx() > nameEx("read_RF2R") > ### * read_RF2R > > flush(stderr()); flush(stdout()) > > ### Name: read_RF2R > ### Title: Import RF-files to R > ### Aliases: read_RF2R > ### Keywords: IO > > ### ** Examples > > > ##Import > file <- system.file("extdata", "RF_file.rf", package = "Luminescence") > temp <- read_RF2R(file) [read_RF2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: RF_file.rf > > > > > cleanEx() > nameEx("read_SPE2R") > ### * read_SPE2R > > flush(stderr()); flush(stdout()) > > ### Name: read_SPE2R > ### Title: Import Princeton Instruments (TM) SPE-file into R > ### Aliases: read_SPE2R > ### Keywords: IO > > ### ** Examples > > > ## to run examples uncomment lines and run the code > > ##(1) Import data as RLum.Data.Spectrum object > #file <- file.choose() > #temp <- read_SPE2R(file) > #temp > > ##(2) Import data as RLum.Data.Image object > #file <- file.choose() > #temp <- read_SPE2R(file, output.object = "RLum.Data.Image") > #temp > > ##(3) Import data as matrix object > #file <- file.choose() > #temp <- read_SPE2R(file, output.object = "matrix") > #temp > > ##(4) Export raw data to csv, if temp is a RLum.Data.Spectrum object > # write.table(x = get_RLum(temp), > # file = "[your path and filename]", > # sep = ";", row.names = FALSE) > > > > > cleanEx() > nameEx("read_TIFF2R") > ### * read_TIFF2R > > flush(stderr()); flush(stdout()) > > ### Name: read_TIFF2R > ### Title: Import TIFF Image Data into R > ### Aliases: read_TIFF2R > ### Keywords: IO > > ### ** Examples > > > ## use system file > file <- system.file("extdata", "TIFFfile.tif", package = "Luminescence") > > ## import image > image <- read_TIFF2R(file) [read_TIFF2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: TIFFfile.tif > > > > > cleanEx() > nameEx("read_XSYG2R") > ### * read_XSYG2R > > flush(stderr()); flush(stdout()) > > ### Name: read_XSYG2R > ### Title: Import XSYG files into R > ### Aliases: read_XSYG2R > ### Keywords: IO > > ### ** Examples > > > ##(1) import XSYG file to R (uncomment for usage) > > #FILE <- file.choose() > #temp <- read_XSYG2R(FILE) > > ##(2) additional examples for pure XML import using the package XML > ## (uncomment for usage) > > ##import entire XML file > #FILE <- file.choose() > #temp <- XML::xmlRoot(XML::xmlTreeParse(FILE)) > > ##search for specific subnodes with curves containing 'OSL' > #getNodeSet(temp, "//Sample/Sequence/Record[@recordType = 'OSL']/Curve") > > ##(2) How to extract single curves ... after import > data(ExampleData.XSYG, envir = environment()) > > ##grep one OSL curves and plot the first curve > OSLcurve <- get_RLum(OSL.SARMeasurement$Sequence.Object, recordType="OSL")[[1]] > > ##(3) How to see the structure of an object? > structure_RLum(OSL.SARMeasurement$Sequence.Object) id recordType curveType protocol.step n.channels x.min x.max 1 1 TL (UVVIS) measured 1180 0.100 118.000 2 2 _TL (NA) predefined 5 0.000 268.000 3 3 _TL (NA) measured 1740 0.000 173.900 4 4 OSL (UVVIS) measured 500 0.100 50.000 5 5 _OSL (NA) predefined 5 0.000 216.000 6 6 _OSL (NA) measured 1150 0.000 114.900 7 7 _OSL (NA) predefined 2 0.000 50.000 8 8 _OSL (NA) measured 150 0.497 74.997 9 9 irradiation (NA) predefined 2 0.000 15.000 10 10 TL (UVVIS) measured 680 0.100 68.000 11 11 _TL (NA) predefined 4 0.000 198.000 12 12 _TL (NA) measured 990 0.000 98.900 13 13 OSL (UVVIS) measured 500 0.100 50.000 14 14 _OSL (NA) predefined 5 0.000 216.000 15 15 _OSL (NA) measured 1150 0.000 114.900 16 16 _OSL (NA) predefined 2 0.000 50.000 17 17 _OSL (NA) measured 151 0.012 75.012 18 18 irradiation (NA) predefined 2 0.000 60.000 19 19 TL (UVVIS) measured 1180 0.100 118.000 20 20 _TL (NA) predefined 5 0.000 268.000 21 21 _TL (NA) measured 1730 0.000 172.900 22 22 OSL (UVVIS) measured 500 0.100 50.000 23 23 _OSL (NA) predefined 5 0.000 216.000 24 24 _OSL (NA) measured 1160 0.000 115.900 25 25 _OSL (NA) predefined 2 0.000 50.000 26 26 _OSL (NA) measured 153 0.012 76.012 27 27 irradiation (NA) predefined 2 0.000 15.000 28 28 TL (UVVIS) measured 680 0.100 68.000 29 29 _TL (NA) predefined 4 0.000 198.000 30 30 _TL (NA) measured 1000 0.000 99.900 31 31 OSL (UVVIS) measured 500 0.100 50.000 32 32 _OSL (NA) predefined 5 0.000 216.000 33 33 _OSL (NA) measured 1150 0.000 114.900 34 34 _OSL (NA) predefined 2 0.000 50.000 35 35 _OSL (NA) measured 151 0.014 75.014 36 36 irradiation (NA) predefined 2 0.000 130.000 37 37 TL (UVVIS) measured 1180 0.100 118.000 38 38 _TL (NA) predefined 5 0.000 268.000 39 39 _TL (NA) measured 1740 0.000 173.900 40 40 OSL (UVVIS) measured 500 0.100 50.000 41 41 _OSL (NA) predefined 5 0.000 216.000 42 42 _OSL (NA) measured 1150 0.000 114.900 43 43 _OSL (NA) predefined 2 0.000 50.000 44 44 _OSL (NA) measured 151 0.012 75.012 45 45 irradiation (NA) predefined 2 0.000 15.000 46 46 TL (UVVIS) measured 680 0.100 68.000 47 47 _TL (NA) predefined 4 0.000 198.000 48 48 _TL (NA) measured 990 0.000 98.900 49 49 OSL (UVVIS) measured 500 0.100 50.000 50 50 _OSL (NA) predefined 5 0.000 216.000 51 51 _OSL (NA) measured 1130 0.000 112.900 52 52 _OSL (NA) predefined 2 0.000 50.000 53 53 _OSL (NA) measured 147 0.012 73.012 54 54 irradiation (NA) predefined 2 0.000 230.000 55 55 TL (UVVIS) measured 1180 0.100 118.000 56 56 _TL (NA) predefined 5 0.000 268.000 57 57 _TL (NA) measured 1740 0.000 173.900 58 58 OSL (UVVIS) measured 500 0.100 50.000 59 59 _OSL (NA) predefined 5 0.000 216.000 60 60 _OSL (NA) measured 1150 0.000 114.900 61 61 _OSL (NA) predefined 2 0.000 50.000 62 62 _OSL (NA) measured 151 0.012 75.012 63 63 irradiation (NA) predefined 2 0.000 15.000 64 64 TL (UVVIS) measured 680 0.100 68.000 65 65 _TL (NA) predefined 4 0.000 198.000 66 66 _TL (NA) measured 990 0.000 98.900 67 67 OSL (UVVIS) measured 500 0.100 50.000 68 68 _OSL (NA) predefined 5 0.000 216.000 69 69 _OSL (NA) measured 1150 0.000 114.900 70 70 _OSL (NA) predefined 2 0.000 50.000 71 71 _OSL (NA) measured 151 0.012 75.012 72 72 irradiation (NA) predefined 2 0.000 300.000 73 73 TL (UVVIS) measured 1180 0.100 118.000 74 74 _TL (NA) predefined 5 0.000 268.000 75 75 _TL (NA) measured 1750 0.000 174.900 76 76 OSL (UVVIS) measured 500 0.100 50.000 77 77 _OSL (NA) predefined 5 0.000 216.000 78 78 _OSL (NA) measured 1160 0.000 115.900 79 79 _OSL (NA) predefined 2 0.000 50.000 80 80 _OSL (NA) measured 152 0.481 75.981 81 81 irradiation (NA) predefined 2 0.000 15.000 82 82 TL (UVVIS) measured 680 0.100 68.000 83 83 _TL (NA) predefined 4 0.000 198.000 84 84 _TL (NA) measured 990 0.000 98.900 85 85 OSL (UVVIS) measured 500 0.100 50.000 86 86 _OSL (NA) predefined 5 0.000 216.000 87 87 _OSL (NA) measured 1130 0.000 112.900 88 88 _OSL (NA) predefined 2 0.000 50.000 89 89 _OSL (NA) measured 147 0.012 73.012 90 90 TL (UVVIS) measured 1180 0.100 118.000 91 91 _TL (NA) predefined 5 0.000 268.000 92 92 _TL (NA) measured 1740 0.000 173.900 93 93 OSL (UVVIS) measured 500 0.100 50.000 94 94 _OSL (NA) predefined 5 0.000 216.000 95 95 _OSL (NA) measured 1140 0.000 113.900 96 96 _OSL (NA) predefined 2 0.000 50.000 97 97 _OSL (NA) measured 149 0.012 74.012 98 98 irradiation (NA) predefined 2 0.000 15.000 99 99 TL (UVVIS) measured 680 0.100 68.000 100 100 _TL (NA) predefined 4 0.000 198.000 101 101 _TL (NA) measured 990 0.000 98.900 102 102 OSL (UVVIS) measured 500 0.100 50.000 103 103 _OSL (NA) predefined 5 0.000 216.000 104 104 _OSL (NA) measured 1150 0.000 114.900 105 105 _OSL (NA) predefined 2 0.000 50.000 106 106 _OSL (NA) measured 151 0.012 75.012 107 107 irradiation (NA) predefined 2 0.000 60.000 108 108 TL (UVVIS) measured 1180 0.100 118.000 109 109 _TL (NA) predefined 5 0.000 268.000 110 110 _TL (NA) measured 1740 0.000 173.900 111 111 OSL (UVVIS) measured 500 0.100 50.000 112 112 _OSL (NA) predefined 5 0.000 216.000 113 113 _OSL (NA) measured 1150 0.000 114.900 114 114 _OSL (NA) predefined 2 0.000 50.000 115 115 _OSL (NA) measured 151 0.020 75.020 116 116 irradiation (NA) predefined 2 0.000 15.000 117 117 TL (UVVIS) measured 680 0.100 68.000 118 118 _TL (NA) predefined 4 0.000 198.000 119 119 _TL (NA) measured 980 0.000 97.900 120 120 OSL (UVVIS) measured 500 0.100 50.000 121 121 _OSL (NA) predefined 5 0.000 216.000 122 122 _OSL (NA) measured 1140 0.000 113.900 123 123 _OSL (NA) predefined 2 0.000 50.000 124 124 _OSL (NA) measured 149 0.012 74.012 y.min y.max originator .uid 1 0 82.0 read_XSYG2R() 2016-01-30-10:54.0.226260372670367 2 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.77414278825745 3 26 262.0 read_XSYG2R() 2016-01-30-10:54.0.429038936737925 4 0 891.0 read_XSYG2R() 2016-01-30-10:54.0.336071660276502 5 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.832267640857026 6 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.339185907738283 7 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.517060354584828 8 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.537775189615786 9 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.20047601335682 10 4 555.0 read_XSYG2R() 2016-01-30-10:54.0.868833578424528 11 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.742296873126179 12 34 160.0 read_XSYG2R() 2016-01-30-10:54.0.589681873098016 13 0 122.0 read_XSYG2R() 2016-01-30-10:54.0.630885894177482 14 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.663541194982827 15 42 127.0 read_XSYG2R() 2016-01-30-10:54.0.905940495431423 16 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.381334827048704 17 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.328897463157773 18 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.870911038015038 19 11 1591.0 read_XSYG2R() 2016-01-30-10:54.0.932349309092388 20 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.297850674483925 21 33 262.0 read_XSYG2R() 2016-01-30-10:54.0.605329250684008 22 0 473.0 read_XSYG2R() 2016-01-30-10:54.0.289562621153891 23 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.925942022586241 24 43 128.0 read_XSYG2R() 2016-01-30-10:54.0.291019570548087 25 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.320679558906704 26 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.968130854191259 27 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.0512687624432147 28 3 736.0 read_XSYG2R() 2016-01-30-10:54.0.42879255511798 29 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.0236395532265306 30 33 160.0 read_XSYG2R() 2016-01-30-10:54.0.585047567961738 31 0 149.0 read_XSYG2R() 2016-01-30-10:54.0.522002540295944 32 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.454029348213226 33 42 127.0 read_XSYG2R() 2016-01-30-10:54.0.710487167816609 34 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.830461921636015 35 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.0631769173778594 36 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.593671935843304 37 13 3495.0 read_XSYG2R() 2016-01-30-10:54.0.229677951894701 38 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.921212903689593 39 27 263.0 read_XSYG2R() 2016-01-30-10:54.0.462135725654662 40 0 1152.0 read_XSYG2R() 2016-01-30-10:54.0.173798899399117 41 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.905658074887469 42 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.341222140239552 43 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.4814964144025 44 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.0450054712127894 45 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.268596603535116 46 9 912.0 read_XSYG2R() 2016-01-30-10:54.0.370865847915411 47 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.512568636797369 48 33 160.0 read_XSYG2R() 2016-01-30-10:54.0.869454299798235 49 0 215.0 read_XSYG2R() 2016-01-30-10:54.0.186754534952343 50 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.931624148506671 51 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.561583923641592 52 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.465734504396096 53 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.929129796102643 54 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.29691950744018 55 25 5564.0 read_XSYG2R() 2016-01-30-10:54.0.534651084803045 56 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.792043952038512 57 27 262.0 read_XSYG2R() 2016-01-30-10:54.0.208661240758374 58 0 2346.0 read_XSYG2R() 2016-01-30-10:54.0.937022477388382 59 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.633003524737433 60 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.744804858230054 61 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.451362358173355 62 0 40.3 read_XSYG2R() 2016-01-30-10:54.0.91636705910787 63 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.0463254018686712 64 12 1146.0 read_XSYG2R() 2016-01-30-10:54.0.528479704400524 65 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.478199049830437 66 34 160.0 read_XSYG2R() 2016-01-30-10:54.0.122971840202808 67 0 292.0 read_XSYG2R() 2016-01-30-10:54.0.879391883034259 68 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.242106179939583 69 42 128.0 read_XSYG2R() 2016-01-30-10:54.0.482210234506056 70 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.936310092685744 71 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.58761327737011 72 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.662958577508107 73 47 7423.0 read_XSYG2R() 2016-01-30-10:54.0.349518121918663 74 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.395675572101027 75 25 261.0 read_XSYG2R() 2016-01-30-10:54.0.832506845006719 76 0 3505.0 read_XSYG2R() 2016-01-30-10:54.0.673705363180488 77 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.836654497077689 78 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.655996734043583 79 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.762605228461325 80 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.723475385224447 81 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.953630778472871 82 15 1414.0 read_XSYG2R() 2016-01-30-10:54.0.372155147604644 83 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.212284204317257 84 34 161.0 read_XSYG2R() 2016-01-30-10:54.0.78430981375277 85 0 388.0 read_XSYG2R() 2016-01-30-10:54.0.858382838079706 86 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.0998988668434322 87 42 128.0 read_XSYG2R() 2016-01-30-10:54.0.619967711856589 88 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.079608827130869 89 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.850248564733192 90 0 40.0 read_XSYG2R() 2016-01-30-10:54.0.123581775929779 91 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.0850816639140248 92 38 261.0 read_XSYG2R() 2016-01-30-10:54.0.185026297112927 93 0 27.0 read_XSYG2R() 2016-01-30-10:54.0.738029998959973 94 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.906962538138032 95 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.196863719262183 96 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.223747788928449 97 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.452920723007992 98 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.588007028913125 99 17 1505.0 read_XSYG2R() 2016-01-30-10:54.0.202315265778452 100 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.568469027988613 101 34 160.0 read_XSYG2R() 2016-01-30-10:54.0.770061913877726 102 2 371.0 read_XSYG2R() 2016-01-30-10:54.0.194079604931176 103 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.159584373235703 104 42 127.0 read_XSYG2R() 2016-01-30-10:54.0.883203205419704 105 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.194686755770817 106 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.57188334944658 107 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.310936602763832 108 12 4354.0 read_XSYG2R() 2016-01-30-10:54.0.00642073270864785 109 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.673262577038258 110 32 262.0 read_XSYG2R() 2016-01-30-10:54.0.945887796580791 111 0 1150.0 read_XSYG2R() 2016-01-30-10:54.0.931073016719893 112 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.524589899694547 113 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.901807451387867 114 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.473460933892056 115 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.0573154254816473 116 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.314163006609306 117 10 1540.0 read_XSYG2R() 2016-01-30-10:54.0.891242811921984 118 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.495065419003367 119 33 160.0 read_XSYG2R() 2016-01-30-10:54.0.0757919212337583 120 0 372.0 read_XSYG2R() 2016-01-30-10:54.0.193264133529738 121 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.787167773349211 122 43 126.0 read_XSYG2R() 2016-01-30-10:54.0.778637015959248 123 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.902725383639336 124 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.911328677553684 .pid info 1 2016-01-.... state, p.... 2 2016-01-.... state, p.... 3 2016-01-.... state, p.... 4 2016-01-.... state, p.... 5 2016-01-.... state, p.... 6 2016-01-.... state, p.... 7 2016-01-.... state, p.... 8 2016-01-.... state, p.... 9 2016-01-.... state, p.... 10 2016-01-.... state, p.... 11 2016-01-.... state, p.... 12 2016-01-.... state, p.... 13 2016-01-.... state, p.... 14 2016-01-.... state, p.... 15 2016-01-.... state, p.... 16 2016-01-.... state, p.... 17 2016-01-.... state, p.... 18 2016-01-.... state, p.... 19 2016-01-.... state, p.... 20 2016-01-.... state, p.... 21 2016-01-.... state, p.... 22 2016-01-.... state, p.... 23 2016-01-.... state, p.... 24 2016-01-.... state, p.... 25 2016-01-.... state, p.... 26 2016-01-.... state, p.... 27 2016-01-.... state, p.... 28 2016-01-.... state, p.... 29 2016-01-.... state, p.... 30 2016-01-.... state, p.... 31 2016-01-.... state, p.... 32 2016-01-.... state, p.... 33 2016-01-.... state, p.... 34 2016-01-.... state, p.... 35 2016-01-.... state, p.... 36 2016-01-.... state, p.... 37 2016-01-.... state, p.... 38 2016-01-.... state, p.... 39 2016-01-.... state, p.... 40 2016-01-.... state, p.... 41 2016-01-.... state, p.... 42 2016-01-.... state, p.... 43 2016-01-.... state, p.... 44 2016-01-.... state, p.... 45 2016-01-.... state, p.... 46 2016-01-.... state, p.... 47 2016-01-.... state, p.... 48 2016-01-.... state, p.... 49 2016-01-.... state, p.... 50 2016-01-.... state, p.... 51 2016-01-.... state, p.... 52 2016-01-.... state, p.... 53 2016-01-.... state, p.... 54 2016-01-.... state, p.... 55 2016-01-.... state, p.... 56 2016-01-.... state, p.... 57 2016-01-.... state, p.... 58 2016-01-.... state, p.... 59 2016-01-.... state, p.... 60 2016-01-.... state, p.... 61 2016-01-.... state, p.... 62 2016-01-.... state, p.... 63 2016-01-.... state, p.... 64 2016-01-.... state, p.... 65 2016-01-.... state, p.... 66 2016-01-.... state, p.... 67 2016-01-.... state, p.... 68 2016-01-.... state, p.... 69 2016-01-.... state, p.... 70 2016-01-.... state, p.... 71 2016-01-.... state, p.... 72 2016-01-.... state, p.... 73 2016-01-.... state, p.... 74 2016-01-.... state, p.... 75 2016-01-.... state, p.... 76 2016-01-.... state, p.... 77 2016-01-.... state, p.... 78 2016-01-.... state, p.... 79 2016-01-.... state, p.... 80 2016-01-.... state, p.... 81 2016-01-.... state, p.... 82 2016-01-.... state, p.... 83 2016-01-.... state, p.... 84 2016-01-.... state, p.... 85 2016-01-.... state, p.... 86 2016-01-.... state, p.... 87 2016-01-.... state, p.... 88 2016-01-.... state, p.... 89 2016-01-.... state, p.... 90 2016-01-.... state, p.... 91 2016-01-.... state, p.... 92 2016-01-.... state, p.... 93 2016-01-.... state, p.... 94 2016-01-.... state, p.... 95 2016-01-.... state, p.... 96 2016-01-.... state, p.... 97 2016-01-.... state, p.... 98 2016-01-.... state, p.... 99 2016-01-.... state, p.... 100 2016-01-.... state, p.... 101 2016-01-.... state, p.... 102 2016-01-.... state, p.... 103 2016-01-.... state, p.... 104 2016-01-.... state, p.... 105 2016-01-.... state, p.... 106 2016-01-.... state, p.... 107 2016-01-.... state, p.... 108 2016-01-.... state, p.... 109 2016-01-.... state, p.... 110 2016-01-.... state, p.... 111 2016-01-.... state, p.... 112 2016-01-.... state, p.... 113 2016-01-.... state, p.... 114 2016-01-.... state, p.... 115 2016-01-.... state, p.... 116 2016-01-.... state, p.... 117 2016-01-.... state, p.... 118 2016-01-.... state, p.... 119 2016-01-.... state, p.... 120 2016-01-.... state, p.... 121 2016-01-.... state, p.... 122 2016-01-.... state, p.... 123 2016-01-.... state, p.... 124 2016-01-.... state, p.... > > > > > cleanEx() > nameEx("remove_RLum") > ### * remove_RLum > > flush(stderr()); flush(stdout()) > > ### Name: remove_RLum > ### Title: Strips records from RLum-class objects > ### Aliases: remove_RLum remove_RLum,list-method > ### remove_RLum,RLum.Analysis-method > ### Keywords: utilities > > ### ** Examples > > ## load example data > data(ExampleData.XSYG, envir = environment()) > sar <- OSL.SARMeasurement$Sequence.Object[1:9] > > ## strop only OSL curves > sar <- remove_RLum(sar, recordType = "OSL") > sar [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 0 number of records: 4 .. : RLum.Data.Curve : 4 .. .. : #1 TL (UVVIS) <> #2 _TL (NA) <> #3 _TL (NA) .. .. : #4 irradiation (NA) > > > > > cleanEx() > nameEx("remove_SignalBackground") > ### * remove_SignalBackground > > flush(stderr()); flush(stdout()) > > ### Name: remove_SignalBackground > ### Title: Remove Signal Background from 'RLum.Data.Curve' Objects > ### Aliases: remove_SignalBackground > ### Keywords: datagen > > ### ** Examples > > > ## load example dataset > xsyg <- read_XSYG2R( + system.file("extdata/XSYG_file.xsyg", package = "Luminescence"), + fastForward = TRUE, + verbose = FALSE) > > ## remove constant background from OSL curves > remove_SignalBackground( + object = xsyg, + object_bg = 100, + recordType = "OSL (UVVIS)") [[1]] [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 1 number of records: 12 .. : RLum.Data.Curve : 12 .. .. : #1 TL (UVVIS) <> #2 _TL (NA) <> #3 _TL (NA) .. .. : #4 OSL (UVVIS) <> #5 _OSL (NA) <> #6 _OSL (NA) <> #7 _OSL (NA) <> #8 _OSL (NA) .. .. : #9 irradiation (NA) .. .. : #10 TL (UVVIS) <> #11 _TL (NA) <> #12 _TL (NA) > > ## use a more elaborate examples > ## with two TL curves (2nd is background) > xsyg_v1 <- set_RLum("RLum.Analysis", records = c( + rep(xsyg[[1]]@records[[1]], 2), + xsyg[[1]]@records[[4]], + xsyg[[1]]@records[[4]], + rep(xsyg[[1]]@records[[10]], 2), + xsyg[[1]]@records[[4]], + xsyg[[1]]@records[[4]])) > > ## remove background and strip background > ## curves from the object > o <- remove_SignalBackground( + object = xsyg_v1, + recordType = "TL (UVVIS)") > > > > > cleanEx() > nameEx("report_RLum") > ### * report_RLum > > flush(stderr()); flush(stdout()) > > ### Name: report_RLum > ### Title: Create a HTML-report for (RLum) objects > ### Aliases: report_RLum > > ### ** Examples > > > ## Not run: > ##D ## Example: RLum.Results ---- > ##D > ##D # load example data > ##D data("ExampleData.DeValues") > ##D > ##D # apply the MAM-3 age model and save results > ##D mam <- calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.2) > ##D > ##D # create the HTML report > ##D report_RLum(object = mam, file = "~/CA1_MAM.Rmd", > ##D timestamp = FALSE, > ##D title = "MAM-3 for sample CA1") > ##D > ##D # when creating a report the input file is automatically saved to a > ##D # .Rds file (see saveRDS()). > ##D mam_report <- readRDS("~/CA1_MAM.Rds") > ##D all.equal(mam, mam_report) > ##D > ##D > ##D ## Example: Temporary file & Viewer/Browser ---- > ##D > ##D # (a) > ##D # Specifying a filename is not necessarily required. If no filename is provided, > ##D # the report is rendered in a temporary file. If you use the RStudio IDE, the > ##D # temporary report is shown in the interactive Viewer pane. > ##D report_RLum(object = mam) > ##D > ##D # (b) > ##D # Additionally, you can view the HTML report in your system's default web browser. > ##D report_RLum(object = mam, launch.browser = TRUE) > ##D > ##D > ##D ## Example: RLum.Analysis ---- > ##D > ##D data("ExampleData.RLum.Analysis") > ##D > ##D # create the HTML report (note that specifying a file > ##D # extension is not necessary) > ##D report_RLum(object = IRSAR.RF.Data, file = "~/IRSAR_RF") > ##D > ##D > ##D ## Example: RLum.Data.Curve ---- > ##D > ##D data.curve <- get_RLum(IRSAR.RF.Data)[[1]] > ##D > ##D # create the HTML report > ##D report_RLum(object = data.curve, file = "~/Data_Curve") > ##D > ##D ## Example: Any other object ---- > ##D x <- list(x = 1:10, > ##D y = runif(10, -5, 5), > ##D z = data.frame(a = LETTERS[1:20], b = dnorm(0:9)), > ##D NA) > ##D > ##D report_RLum(object = x, file = "~/arbitray_list") > ## End(Not run) > > > > > cleanEx() > nameEx("sTeve") > ### * sTeve > > flush(stderr()); flush(stdout()) > > ### Name: sTeve > ### Title: sTeve - sophisticated tool for efficient data validation and > ### evaluation > ### Aliases: sTeve > ### Keywords: manip > > ### ** Examples > > > ##no example available > > > > > cleanEx() > nameEx("scale_GammaDose") > ### * scale_GammaDose > > flush(stderr()); flush(stdout()) > > ### Name: scale_GammaDose > ### Title: Calculate the gamma dose deposited within a sample taking > ### layer-to-layer variations in radioactivity into account (according to > ### Aitken, 1985) > ### Aliases: scale_GammaDose > ### Keywords: datagen > > ### ** Examples > > > # Load example data > data("ExampleData.ScaleGammaDose", envir = environment()) > x <- ExampleData.ScaleGammaDose > > # Scale gamma dose rate > results <- scale_GammaDose(data = x, + conversion_factors = "Cresswelletal2018", + fractional_gamma_dose = "Aitken1985", + verbose = TRUE, + plot = TRUE) [scale_GammaDose()] ---- Conversion factors: Cresswelletal2018 Gamma dose fractions: Aitken1985 Target layer: A ---- Infinite matrix gamma dose rate per layer ---- ID K (Gy/ka) Th (Gy/ka) U (Gy/ka) Total (Gy/ka) 1 E_upper 0.399±0.199 0.409±0.156 0.164±0.056 0.973 2 D_upper 0.358±0.175 0.171±0.058 0.112±0.033 0.641 3 C_upper 0.319±0.138 0.256±0.086 0.156±0.062 0.730 4 B_upper 0.467±0.295 0.437±0.248 0.191±0.115 1.094 5 A 0.369±0.254 0.332±0.203 0.216±0.133 0.917 6 B_lower 0.469±0.285 0.439±0.238 0.190±0.125 1.097 7 C_lower 0.466±0.265 0.317±0.150 0.224±0.124 1.006 8 D_lower 0.274±0.129 0.194±0.048 0.129±0.057 0.597 9 E_lower 0.431±0.193 0.437±0.161 0.181±0.088 1.049 ---- Scaled gamma dose rate for target layer: A ---- ID K (Gy/ka) Th (Gy/ka) U (Gy/ka) Contribution (%) 1 E_upper 0.001±0.000 0.001±0.000 0.000±0.000 0.2 2 D_upper 0.005±0.003 0.002±0.001 0.001±0.000 1.0 3 C_upper 0.033±0.014 0.025±0.008 0.015±0.006 7.9 4 B_upper 0.043±0.027 0.040±0.023 0.017±0.010 10.8 5 A 0.207±0.143 0.193±0.118 0.129±0.079 57.1 6 B_lower 0.068±0.041 0.062±0.033 0.026±0.017 16.8 7 C_lower 0.014±0.008 0.009±0.004 0.006±0.003 3.1 8 D_lower 0.007±0.003 0.004±0.001 0.003±0.001 1.5 9 E_lower 0.006±0.003 0.006±0.002 0.002±0.001 1.6 10 TOTAL 0.385±0.152 0.342±0.125 0.200±0.082 100.0 ---- Infinite matrix gamma dose rate: 0.917 ± 0.351 Gy/ka Scaled gamma dose rate: 0.927 ± 0.214 Gy/ka > > get_RLum(results) id dose_rate_K dose_rate_K_err dose_rate_Th dose_rate_Th_err dose_rate_U 1 A 0.3854764 0.1521888 0.3419409 0.1252244 0.1999792 dose_rate_U_err dose_rate_total dose_rate_total_err 1 0.08217342 0.9273965 0.21353 > > > > > cleanEx() > nameEx("set_RLum") > ### * set_RLum > > flush(stderr()); flush(stdout()) > > ### Name: set_RLum > ### Title: General setter function for RLum-class objects > ### Aliases: set_RLum set_RLum,RLum.Analysis-method > ### set_RLum,RLum.Data.Curve-method set_RLum,RLum.Data.Image-method > ### set_RLum,RLum.Data.Spectrum-method set_RLum,RLum.Results-method > ### Keywords: utilities > > ### ** Examples > > > ## produce empty objects from each class > set_RLum(class = "RLum.Data.Curve") [RLum.Data.Curve-class] recordType: NA curveType: NA measured values: 1 .. range of x-values: 0 0 .. range of y-values: 0 0 additional info elements: 0 > set_RLum(class = "RLum.Data.Spectrum") [RLum.Data.Spectrum-class] recordType: Spectrum curveType: NA .. recorded frames: 1 .. .. measured values per frame: 1 .. .. range wavelength/pixel: Inf -Inf .. .. range time/temp.: Inf -Inf .. .. range count values: NA NA additional info elements: 0 > set_RLum(class = "RLum.Data.Spectrum") [RLum.Data.Spectrum-class] recordType: Spectrum curveType: NA .. recorded frames: 1 .. .. measured values per frame: 1 .. .. range wavelength/pixel: Inf -Inf .. .. range time/temp.: Inf -Inf .. .. range count values: NA NA additional info elements: 0 > set_RLum(class = "RLum.Analysis") [RLum.Analysis-class] originator: NA() protocol: NA additional info elements: 0 number of records: 0 >> This is an empty object, which cannot be used for further analysis! << > set_RLum(class = "RLum.Results") [RLum.Results-class] originator: NA() data: 0 .. $ : list additional info elements: 0 > > ## produce a curve object with arbitrary curve values > object <- set_RLum( + class = "RLum.Data.Curve", + curveType = "arbitrary", + recordType = "OSL", + data = matrix(c(1:100,exp(-c(1:100))),ncol = 2)) > > ## plot this curve object > plot_RLum(object) > > > > > cleanEx() > nameEx("smooth_RLum") > ### * smooth_RLum > > flush(stderr()); flush(stdout()) > > ### Name: smooth_RLum > ### Title: Smoothing of data for RLum-class objects > ### Aliases: smooth_RLum smooth_RLum,list-method > ### smooth_RLum,RLum.Analysis-method smooth_RLum,RLum.Data.Curve-method > ### Keywords: utilities > > ### ** Examples > > > ## load example data > data(ExampleData.CW_OSL_Curve, envir = environment()) > > ## create RLum.Data.Curve object from this example > curve <- + set_RLum( + class = "RLum.Data.Curve", + recordType = "OSL", + data = as.matrix(ExampleData.CW_OSL_Curve) + ) > > ## plot data without and with smoothing > plot_RLum(curve) > plot_RLum(smooth_RLum(curve)) > > > > > cleanEx() > nameEx("sort_RLum") > ### * sort_RLum > > flush(stderr()); flush(stdout()) > > ### Name: sort_RLum > ### Title: Sort data for RLum-class and Risoe.BINfileData-class objects > ### Aliases: sort_RLum sort_RLum,list-method sort_RLum,RLum.Analysis-method > ### sort_RLum,Risoe.BINfileData-method > ### Keywords: utilities > > ### ** Examples > > > ## load example data > data(ExampleData.XSYG, envir = environment()) > obj <- OSL.SARMeasurement$Sequence.Object[1:9] > > sort_RLum(obj, slot = "recordType") [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 0 number of records: 9 .. : RLum.Data.Curve : 9 .. .. : #1 OSL (UVVIS) .. .. : #2 TL (UVVIS) .. .. : #3 _OSL (NA) <> #4 _OSL (NA) <> #5 _OSL (NA) <> #6 _OSL (NA) .. .. : #7 _TL (NA) <> #8 _TL (NA) .. .. : #9 irradiation (NA) > sort_RLum(obj, info_element = "curveDescripter") [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 0 number of records: 9 .. : RLum.Data.Curve : 9 .. .. : #1 _TL (NA) <> #2 _TL (NA) .. .. : #3 _OSL (NA) <> #4 _OSL (NA) .. .. : #5 TL (UVVIS) .. .. : #6 OSL (UVVIS) <> #7 _OSL (NA) <> #8 _OSL (NA) .. .. : #9 irradiation (NA) > > data(ExampleData.XSYG, envir = environment()) > sar <- OSL.SARMeasurement$Sequence.Object[1:5] > sort_RLum(sar, solt = "recordType", info_element = c("startDate")) [RLum.Analysis-class] originator: read_XSYG2R() protocol: SAR additional info elements: 0 number of records: 5 .. : RLum.Data.Curve : 5 .. .. : #1 TL (UVVIS) <> #2 _TL (NA) <> #3 _TL (NA) .. .. : #4 OSL (UVVIS) <> #5 _OSL (NA) > > > > > cleanEx() > nameEx("structure_RLum") > ### * structure_RLum > > flush(stderr()); flush(stdout()) > > ### Name: structure_RLum > ### Title: General structure function for RLum-class objects > ### Aliases: structure_RLum structure_RLum,list-method > ### structure_RLum,RLum.Analysis-method > ### Keywords: utilities > > ### ** Examples > > > ## load example data > data(ExampleData.XSYG, envir = environment()) > > ## show structure > structure_RLum(OSL.SARMeasurement$Sequence.Object) id recordType curveType protocol.step n.channels x.min x.max 1 1 TL (UVVIS) measured 1180 0.100 118.000 2 2 _TL (NA) predefined 5 0.000 268.000 3 3 _TL (NA) measured 1740 0.000 173.900 4 4 OSL (UVVIS) measured 500 0.100 50.000 5 5 _OSL (NA) predefined 5 0.000 216.000 6 6 _OSL (NA) measured 1150 0.000 114.900 7 7 _OSL (NA) predefined 2 0.000 50.000 8 8 _OSL (NA) measured 150 0.497 74.997 9 9 irradiation (NA) predefined 2 0.000 15.000 10 10 TL (UVVIS) measured 680 0.100 68.000 11 11 _TL (NA) predefined 4 0.000 198.000 12 12 _TL (NA) measured 990 0.000 98.900 13 13 OSL (UVVIS) measured 500 0.100 50.000 14 14 _OSL (NA) predefined 5 0.000 216.000 15 15 _OSL (NA) measured 1150 0.000 114.900 16 16 _OSL (NA) predefined 2 0.000 50.000 17 17 _OSL (NA) measured 151 0.012 75.012 18 18 irradiation (NA) predefined 2 0.000 60.000 19 19 TL (UVVIS) measured 1180 0.100 118.000 20 20 _TL (NA) predefined 5 0.000 268.000 21 21 _TL (NA) measured 1730 0.000 172.900 22 22 OSL (UVVIS) measured 500 0.100 50.000 23 23 _OSL (NA) predefined 5 0.000 216.000 24 24 _OSL (NA) measured 1160 0.000 115.900 25 25 _OSL (NA) predefined 2 0.000 50.000 26 26 _OSL (NA) measured 153 0.012 76.012 27 27 irradiation (NA) predefined 2 0.000 15.000 28 28 TL (UVVIS) measured 680 0.100 68.000 29 29 _TL (NA) predefined 4 0.000 198.000 30 30 _TL (NA) measured 1000 0.000 99.900 31 31 OSL (UVVIS) measured 500 0.100 50.000 32 32 _OSL (NA) predefined 5 0.000 216.000 33 33 _OSL (NA) measured 1150 0.000 114.900 34 34 _OSL (NA) predefined 2 0.000 50.000 35 35 _OSL (NA) measured 151 0.014 75.014 36 36 irradiation (NA) predefined 2 0.000 130.000 37 37 TL (UVVIS) measured 1180 0.100 118.000 38 38 _TL (NA) predefined 5 0.000 268.000 39 39 _TL (NA) measured 1740 0.000 173.900 40 40 OSL (UVVIS) measured 500 0.100 50.000 41 41 _OSL (NA) predefined 5 0.000 216.000 42 42 _OSL (NA) measured 1150 0.000 114.900 43 43 _OSL (NA) predefined 2 0.000 50.000 44 44 _OSL (NA) measured 151 0.012 75.012 45 45 irradiation (NA) predefined 2 0.000 15.000 46 46 TL (UVVIS) measured 680 0.100 68.000 47 47 _TL (NA) predefined 4 0.000 198.000 48 48 _TL (NA) measured 990 0.000 98.900 49 49 OSL (UVVIS) measured 500 0.100 50.000 50 50 _OSL (NA) predefined 5 0.000 216.000 51 51 _OSL (NA) measured 1130 0.000 112.900 52 52 _OSL (NA) predefined 2 0.000 50.000 53 53 _OSL (NA) measured 147 0.012 73.012 54 54 irradiation (NA) predefined 2 0.000 230.000 55 55 TL (UVVIS) measured 1180 0.100 118.000 56 56 _TL (NA) predefined 5 0.000 268.000 57 57 _TL (NA) measured 1740 0.000 173.900 58 58 OSL (UVVIS) measured 500 0.100 50.000 59 59 _OSL (NA) predefined 5 0.000 216.000 60 60 _OSL (NA) measured 1150 0.000 114.900 61 61 _OSL (NA) predefined 2 0.000 50.000 62 62 _OSL (NA) measured 151 0.012 75.012 63 63 irradiation (NA) predefined 2 0.000 15.000 64 64 TL (UVVIS) measured 680 0.100 68.000 65 65 _TL (NA) predefined 4 0.000 198.000 66 66 _TL (NA) measured 990 0.000 98.900 67 67 OSL (UVVIS) measured 500 0.100 50.000 68 68 _OSL (NA) predefined 5 0.000 216.000 69 69 _OSL (NA) measured 1150 0.000 114.900 70 70 _OSL (NA) predefined 2 0.000 50.000 71 71 _OSL (NA) measured 151 0.012 75.012 72 72 irradiation (NA) predefined 2 0.000 300.000 73 73 TL (UVVIS) measured 1180 0.100 118.000 74 74 _TL (NA) predefined 5 0.000 268.000 75 75 _TL (NA) measured 1750 0.000 174.900 76 76 OSL (UVVIS) measured 500 0.100 50.000 77 77 _OSL (NA) predefined 5 0.000 216.000 78 78 _OSL (NA) measured 1160 0.000 115.900 79 79 _OSL (NA) predefined 2 0.000 50.000 80 80 _OSL (NA) measured 152 0.481 75.981 81 81 irradiation (NA) predefined 2 0.000 15.000 82 82 TL (UVVIS) measured 680 0.100 68.000 83 83 _TL (NA) predefined 4 0.000 198.000 84 84 _TL (NA) measured 990 0.000 98.900 85 85 OSL (UVVIS) measured 500 0.100 50.000 86 86 _OSL (NA) predefined 5 0.000 216.000 87 87 _OSL (NA) measured 1130 0.000 112.900 88 88 _OSL (NA) predefined 2 0.000 50.000 89 89 _OSL (NA) measured 147 0.012 73.012 90 90 TL (UVVIS) measured 1180 0.100 118.000 91 91 _TL (NA) predefined 5 0.000 268.000 92 92 _TL (NA) measured 1740 0.000 173.900 93 93 OSL (UVVIS) measured 500 0.100 50.000 94 94 _OSL (NA) predefined 5 0.000 216.000 95 95 _OSL (NA) measured 1140 0.000 113.900 96 96 _OSL (NA) predefined 2 0.000 50.000 97 97 _OSL (NA) measured 149 0.012 74.012 98 98 irradiation (NA) predefined 2 0.000 15.000 99 99 TL (UVVIS) measured 680 0.100 68.000 100 100 _TL (NA) predefined 4 0.000 198.000 101 101 _TL (NA) measured 990 0.000 98.900 102 102 OSL (UVVIS) measured 500 0.100 50.000 103 103 _OSL (NA) predefined 5 0.000 216.000 104 104 _OSL (NA) measured 1150 0.000 114.900 105 105 _OSL (NA) predefined 2 0.000 50.000 106 106 _OSL (NA) measured 151 0.012 75.012 107 107 irradiation (NA) predefined 2 0.000 60.000 108 108 TL (UVVIS) measured 1180 0.100 118.000 109 109 _TL (NA) predefined 5 0.000 268.000 110 110 _TL (NA) measured 1740 0.000 173.900 111 111 OSL (UVVIS) measured 500 0.100 50.000 112 112 _OSL (NA) predefined 5 0.000 216.000 113 113 _OSL (NA) measured 1150 0.000 114.900 114 114 _OSL (NA) predefined 2 0.000 50.000 115 115 _OSL (NA) measured 151 0.020 75.020 116 116 irradiation (NA) predefined 2 0.000 15.000 117 117 TL (UVVIS) measured 680 0.100 68.000 118 118 _TL (NA) predefined 4 0.000 198.000 119 119 _TL (NA) measured 980 0.000 97.900 120 120 OSL (UVVIS) measured 500 0.100 50.000 121 121 _OSL (NA) predefined 5 0.000 216.000 122 122 _OSL (NA) measured 1140 0.000 113.900 123 123 _OSL (NA) predefined 2 0.000 50.000 124 124 _OSL (NA) measured 149 0.012 74.012 y.min y.max originator .uid 1 0 82.0 read_XSYG2R() 2016-01-30-10:54.0.226260372670367 2 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.77414278825745 3 26 262.0 read_XSYG2R() 2016-01-30-10:54.0.429038936737925 4 0 891.0 read_XSYG2R() 2016-01-30-10:54.0.336071660276502 5 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.832267640857026 6 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.339185907738283 7 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.517060354584828 8 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.537775189615786 9 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.20047601335682 10 4 555.0 read_XSYG2R() 2016-01-30-10:54.0.868833578424528 11 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.742296873126179 12 34 160.0 read_XSYG2R() 2016-01-30-10:54.0.589681873098016 13 0 122.0 read_XSYG2R() 2016-01-30-10:54.0.630885894177482 14 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.663541194982827 15 42 127.0 read_XSYG2R() 2016-01-30-10:54.0.905940495431423 16 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.381334827048704 17 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.328897463157773 18 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.870911038015038 19 11 1591.0 read_XSYG2R() 2016-01-30-10:54.0.932349309092388 20 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.297850674483925 21 33 262.0 read_XSYG2R() 2016-01-30-10:54.0.605329250684008 22 0 473.0 read_XSYG2R() 2016-01-30-10:54.0.289562621153891 23 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.925942022586241 24 43 128.0 read_XSYG2R() 2016-01-30-10:54.0.291019570548087 25 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.320679558906704 26 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.968130854191259 27 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.0512687624432147 28 3 736.0 read_XSYG2R() 2016-01-30-10:54.0.42879255511798 29 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.0236395532265306 30 33 160.0 read_XSYG2R() 2016-01-30-10:54.0.585047567961738 31 0 149.0 read_XSYG2R() 2016-01-30-10:54.0.522002540295944 32 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.454029348213226 33 42 127.0 read_XSYG2R() 2016-01-30-10:54.0.710487167816609 34 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.830461921636015 35 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.0631769173778594 36 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.593671935843304 37 13 3495.0 read_XSYG2R() 2016-01-30-10:54.0.229677951894701 38 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.921212903689593 39 27 263.0 read_XSYG2R() 2016-01-30-10:54.0.462135725654662 40 0 1152.0 read_XSYG2R() 2016-01-30-10:54.0.173798899399117 41 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.905658074887469 42 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.341222140239552 43 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.4814964144025 44 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.0450054712127894 45 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.268596603535116 46 9 912.0 read_XSYG2R() 2016-01-30-10:54.0.370865847915411 47 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.512568636797369 48 33 160.0 read_XSYG2R() 2016-01-30-10:54.0.869454299798235 49 0 215.0 read_XSYG2R() 2016-01-30-10:54.0.186754534952343 50 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.931624148506671 51 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.561583923641592 52 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.465734504396096 53 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.929129796102643 54 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.29691950744018 55 25 5564.0 read_XSYG2R() 2016-01-30-10:54.0.534651084803045 56 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.792043952038512 57 27 262.0 read_XSYG2R() 2016-01-30-10:54.0.208661240758374 58 0 2346.0 read_XSYG2R() 2016-01-30-10:54.0.937022477388382 59 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.633003524737433 60 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.744804858230054 61 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.451362358173355 62 0 40.3 read_XSYG2R() 2016-01-30-10:54.0.91636705910787 63 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.0463254018686712 64 12 1146.0 read_XSYG2R() 2016-01-30-10:54.0.528479704400524 65 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.478199049830437 66 34 160.0 read_XSYG2R() 2016-01-30-10:54.0.122971840202808 67 0 292.0 read_XSYG2R() 2016-01-30-10:54.0.879391883034259 68 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.242106179939583 69 42 128.0 read_XSYG2R() 2016-01-30-10:54.0.482210234506056 70 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.936310092685744 71 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.58761327737011 72 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.662958577508107 73 47 7423.0 read_XSYG2R() 2016-01-30-10:54.0.349518121918663 74 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.395675572101027 75 25 261.0 read_XSYG2R() 2016-01-30-10:54.0.832506845006719 76 0 3505.0 read_XSYG2R() 2016-01-30-10:54.0.673705363180488 77 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.836654497077689 78 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.655996734043583 79 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.762605228461325 80 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.723475385224447 81 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.953630778472871 82 15 1414.0 read_XSYG2R() 2016-01-30-10:54.0.372155147604644 83 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.212284204317257 84 34 161.0 read_XSYG2R() 2016-01-30-10:54.0.78430981375277 85 0 388.0 read_XSYG2R() 2016-01-30-10:54.0.858382838079706 86 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.0998988668434322 87 42 128.0 read_XSYG2R() 2016-01-30-10:54.0.619967711856589 88 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.079608827130869 89 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.850248564733192 90 0 40.0 read_XSYG2R() 2016-01-30-10:54.0.123581775929779 91 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.0850816639140248 92 38 261.0 read_XSYG2R() 2016-01-30-10:54.0.185026297112927 93 0 27.0 read_XSYG2R() 2016-01-30-10:54.0.738029998959973 94 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.906962538138032 95 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.196863719262183 96 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.223747788928449 97 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.452920723007992 98 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.588007028913125 99 17 1505.0 read_XSYG2R() 2016-01-30-10:54.0.202315265778452 100 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.568469027988613 101 34 160.0 read_XSYG2R() 2016-01-30-10:54.0.770061913877726 102 2 371.0 read_XSYG2R() 2016-01-30-10:54.0.194079604931176 103 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.159584373235703 104 42 127.0 read_XSYG2R() 2016-01-30-10:54.0.883203205419704 105 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.194686755770817 106 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.57188334944658 107 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.310936602763832 108 12 4354.0 read_XSYG2R() 2016-01-30-10:54.0.00642073270864785 109 25 260.0 read_XSYG2R() 2016-01-30-10:54.0.673262577038258 110 32 262.0 read_XSYG2R() 2016-01-30-10:54.0.945887796580791 111 0 1150.0 read_XSYG2R() 2016-01-30-10:54.0.931073016719893 112 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.524589899694547 113 43 127.0 read_XSYG2R() 2016-01-30-10:54.0.901807451387867 114 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.473460933892056 115 0 40.1 read_XSYG2R() 2016-01-30-10:54.0.0573154254816473 116 1 1.0 read_XSYG2R() 2016-01-30-10:54.0.314163006609306 117 10 1540.0 read_XSYG2R() 2016-01-30-10:54.0.891242811921984 118 25 160.0 read_XSYG2R() 2016-01-30-10:54.0.495065419003367 119 33 160.0 read_XSYG2R() 2016-01-30-10:54.0.0757919212337583 120 0 372.0 read_XSYG2R() 2016-01-30-10:54.0.193264133529738 121 25 125.0 read_XSYG2R() 2016-01-30-10:54.0.787167773349211 122 43 126.0 read_XSYG2R() 2016-01-30-10:54.0.778637015959248 123 40 40.0 read_XSYG2R() 2016-01-30-10:54.0.902725383639336 124 0 40.2 read_XSYG2R() 2016-01-30-10:54.0.911328677553684 .pid info 1 2016-01-.... state, p.... 2 2016-01-.... state, p.... 3 2016-01-.... state, p.... 4 2016-01-.... state, p.... 5 2016-01-.... state, p.... 6 2016-01-.... state, p.... 7 2016-01-.... state, p.... 8 2016-01-.... state, p.... 9 2016-01-.... state, p.... 10 2016-01-.... state, p.... 11 2016-01-.... state, p.... 12 2016-01-.... state, p.... 13 2016-01-.... state, p.... 14 2016-01-.... state, p.... 15 2016-01-.... state, p.... 16 2016-01-.... state, p.... 17 2016-01-.... state, p.... 18 2016-01-.... state, p.... 19 2016-01-.... state, p.... 20 2016-01-.... state, p.... 21 2016-01-.... state, p.... 22 2016-01-.... state, p.... 23 2016-01-.... state, p.... 24 2016-01-.... state, p.... 25 2016-01-.... state, p.... 26 2016-01-.... state, p.... 27 2016-01-.... state, p.... 28 2016-01-.... state, p.... 29 2016-01-.... state, p.... 30 2016-01-.... state, p.... 31 2016-01-.... state, p.... 32 2016-01-.... state, p.... 33 2016-01-.... state, p.... 34 2016-01-.... state, p.... 35 2016-01-.... state, p.... 36 2016-01-.... state, p.... 37 2016-01-.... state, p.... 38 2016-01-.... state, p.... 39 2016-01-.... state, p.... 40 2016-01-.... state, p.... 41 2016-01-.... state, p.... 42 2016-01-.... state, p.... 43 2016-01-.... state, p.... 44 2016-01-.... state, p.... 45 2016-01-.... state, p.... 46 2016-01-.... state, p.... 47 2016-01-.... state, p.... 48 2016-01-.... state, p.... 49 2016-01-.... state, p.... 50 2016-01-.... state, p.... 51 2016-01-.... state, p.... 52 2016-01-.... state, p.... 53 2016-01-.... state, p.... 54 2016-01-.... state, p.... 55 2016-01-.... state, p.... 56 2016-01-.... state, p.... 57 2016-01-.... state, p.... 58 2016-01-.... state, p.... 59 2016-01-.... state, p.... 60 2016-01-.... state, p.... 61 2016-01-.... state, p.... 62 2016-01-.... state, p.... 63 2016-01-.... state, p.... 64 2016-01-.... state, p.... 65 2016-01-.... state, p.... 66 2016-01-.... state, p.... 67 2016-01-.... state, p.... 68 2016-01-.... state, p.... 69 2016-01-.... state, p.... 70 2016-01-.... state, p.... 71 2016-01-.... state, p.... 72 2016-01-.... state, p.... 73 2016-01-.... state, p.... 74 2016-01-.... state, p.... 75 2016-01-.... state, p.... 76 2016-01-.... state, p.... 77 2016-01-.... state, p.... 78 2016-01-.... state, p.... 79 2016-01-.... state, p.... 80 2016-01-.... state, p.... 81 2016-01-.... state, p.... 82 2016-01-.... state, p.... 83 2016-01-.... state, p.... 84 2016-01-.... state, p.... 85 2016-01-.... state, p.... 86 2016-01-.... state, p.... 87 2016-01-.... state, p.... 88 2016-01-.... state, p.... 89 2016-01-.... state, p.... 90 2016-01-.... state, p.... 91 2016-01-.... state, p.... 92 2016-01-.... state, p.... 93 2016-01-.... state, p.... 94 2016-01-.... state, p.... 95 2016-01-.... state, p.... 96 2016-01-.... state, p.... 97 2016-01-.... state, p.... 98 2016-01-.... state, p.... 99 2016-01-.... state, p.... 100 2016-01-.... state, p.... 101 2016-01-.... state, p.... 102 2016-01-.... state, p.... 103 2016-01-.... state, p.... 104 2016-01-.... state, p.... 105 2016-01-.... state, p.... 106 2016-01-.... state, p.... 107 2016-01-.... state, p.... 108 2016-01-.... state, p.... 109 2016-01-.... state, p.... 110 2016-01-.... state, p.... 111 2016-01-.... state, p.... 112 2016-01-.... state, p.... 113 2016-01-.... state, p.... 114 2016-01-.... state, p.... 115 2016-01-.... state, p.... 116 2016-01-.... state, p.... 117 2016-01-.... state, p.... 118 2016-01-.... state, p.... 119 2016-01-.... state, p.... 120 2016-01-.... state, p.... 121 2016-01-.... state, p.... 122 2016-01-.... state, p.... 123 2016-01-.... state, p.... 124 2016-01-.... state, p.... > > > > > cleanEx() > nameEx("subset_SingleGrainData") > ### * subset_SingleGrainData > > flush(stderr()); flush(stdout()) > > ### Name: subset_SingleGrainData > ### Title: Simple Subsetting of Single Grain Data from Risø BIN/BINX files > ### Aliases: subset_SingleGrainData > ### Keywords: datagen manip > > ### ** Examples > > > ## load example data > data(ExampleData.BINfileData, envir = environment()) > > ## set POSITION/GRAIN pair dataset > selection <- data.frame(POSITION = c(1,5,7), GRAIN = c(0,0,0)) > > ##subset > subset_SingleGrainData(object = CWOSL.SAR.Data, selection = selection) [Risoe.BINfileData object] BIN/BINX version: 03 Object date: 060920, 070920, 080920, 090920, 100920 User: Default System ID: 0 (unknown) Overall records: 90 Records type: IRSL (n = 3) OSL (n = 42) TL (n = 45) Position range: 1 : 7 Run range: 1 : 8 Set range: 2 : 6 > > > > > cleanEx() > nameEx("template_DRAC") > ### * template_DRAC > > flush(stderr()); flush(stdout()) > > ### Name: template_DRAC > ### Title: Create a DRAC input data template (v1.2) > ### Aliases: template_DRAC > > ### ** Examples > > > # create a new DRAC input input > input <- template_DRAC(preset = "DRAC-example_quartz") -------------------- IMPORTANT NOTE ------------------------ This function returns a DRAC input template to be used in conjunction with the use_DRAC() function. The template was reproduced with great care, but we do not take any responsibility and we are not liable for any mistakes or unforeseen misbehaviour. Note that this template is only compatible with DRAC version 1.1. Before using this template make sure that this is the correct version, otherwise expect unspecified errors. Please ensure you cite the use of DRAC in your work, published or otherwise. Please cite the website name and version (e.g. DRAC v1.1) and the accompanying journal article: Durcan, J.A., King, G.E., Duller, G.A.T., 2015. DRAC: Dose rate and age calculation for trapped charge dating. Quaternary Geochronology 28, 54-61. Set 'notification = FALSE' to hide this message. -------------------- IMPORTANT NOTE ------------------------ > > # show content of the input > print(input) TI:1 => Project ID VALUES = DRAC-example ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = Inputs can be alphabetic, numeric or selected symbols (/ - () [] _). Spaces are not permitted. TI:2 => Sample ID VALUES = Quartz ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = Inputs can be alphabetic, numeric or selected symbols (/ - () [] _). Spaces are not permitted. TI:3 => Mineral VALUES = Q ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The mineral used for dating: quartz, feldspar or polymineral. Input must be 'Q' , 'F' or 'PM'. OPTIONS = Q, F, PM TI:4 => Conversion factors VALUES = Guerinetal2011 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = The conversion factors required to calculate dose rates from radionuclide conce ntrations. Users have the option of datasets from Adamiec and Aitken (1998), Gue rin et al. (2011), Liritzis et al. (2013) or Cresswell et al. (2018). Input must be 'AdamiecAitken1998', 'Guerinetal2011', 'Liritzisetal2013', 'Cresswelletal201 8', or 'X' if conversion factors are not required. OPTIONS = AdamiecAitken1998, Guerinetal2011, Liritzisetal2013, Cresswelletal2018, X TI:5 => External U (ppm) VALUES = 3.4 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:6 => errExternal U (ppm) VALUES = 0.51 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:7 => External Th (ppm) VALUES = 14.47 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:8 => errExternal Th (ppm) VALUES = 1.69 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:9 => External K (%) VALUES = 1.2 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:10 => errExternal K (%) VALUES = 0.14 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:11 => External Rb (ppm) VALUES = 0 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:12 => errExternal Rb (ppm) VALUES = 0 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Radionuclide concentrations in parts per million for Uranium, Thorium and Rubid ium and % for Potassium. Inputs must be 0 or positive and should not be left bla nk. TI:13 => Calculate external Rb from K conc? VALUES = N ALLOWS 'X' = FALSE REQUIRED = FALSE DESCRIPTION = Option to calculate a Rubidium concentration from Potassium, using the 270:1 ra tio suggested by Mejdahl (1987). Input should be yes 'Y' or no 'N'. OPTIONS = Y, N TI:14 => Internal U (ppm) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:15 => errInternal U (ppm) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:16 => Internal Th (ppm) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:17 => errInternal Th (ppm) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:18 => Internal K (%) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:19 => errInternal K (%) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:20 => Rb (ppm) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:21 => errRb (ppm) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Internal radionuclide concentrations in parts per million for Uranium, Thorium and Rubidium and % for Potassium. Inputs must be 0 or positive and should not be left blank. TI:22 => Calculate internal Rb from K conc? VALUES = N ALLOWS 'X' = FALSE REQUIRED = FALSE DESCRIPTION = Option to calculate an internal Rubidium concentration from Potassium, using th e 270:1 ratio suggested by Mejdahl (1987). Input should be yes 'Y' or no 'N'. OPTIONS = Y, N TI:23 => User external alphadoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input directly measured values for external alpha, beta and gamma dos e rates (in Gy.ka-1). Any positive inputs in these fields will override dose rat es calculated from radionuclide concentrations. Inputs should be 0 or positive a nd should not be left blank TI:24 => errUser external alphadoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input directly measured values for external alpha, beta and gamma dos e rates (in Gy.ka-1). Any positive inputs in these fields will override dose rat es calculated from radionuclide concentrations. Inputs should be 0 or positive a nd should not be left blank TI:25 => User external betadoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input directly measured values for external alpha, beta and gamma dos e rates (in Gy.ka-1). Any positive inputs in these fields will override dose rat es calculated from radionuclide concentrations. Inputs should be 0 or positive a nd should not be left blank TI:26 => errUser external betadoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input directly measured values for external alpha, beta and gamma dos e rates (in Gy.ka-1). Any positive inputs in these fields will override dose rat es calculated from radionuclide concentrations. Inputs should be 0 or positive a nd should not be left blank TI:27 => User external gamma doserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input directly measured values for external alpha, beta and gamma dos e rates (in Gy.ka-1). Any positive inputs in these fields will override dose rat es calculated from radionuclide concentrations. Inputs should be 0 or positive a nd should not be left blank TI:28 => errUser external gammadoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input directly measured values for external alpha, beta and gamma dos e rates (in Gy.ka-1). Any positive inputs in these fields will override dose rat es calculated from radionuclide concentrations. Inputs should be 0 or positive a nd should not be left blank TI:29 => User internal doserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input an internal dose rate (either alpha, beta or the sum of the two ; in Gy.ka-1). DRAC will assume that this value has already been corrected for a ttenuation. Inputs in this field will override dose rates calculated from radion uclide concentrations. Inputs should be 0 or positive and not left blank. TI:30 => errUser internal doserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input an internal dose rate (either alpha, beta or the sum of the two ; in Gy.ka-1). DRAC will assume that this value has already been corrected for a ttenuation. Inputs in this field will override dose rates calculated from radion uclide concentrations. Inputs should be 0 or positive and not left blank. TI:31 => Scale gammadoserate at shallow depths? VALUES = N ALLOWS 'X' = FALSE REQUIRED = FALSE DESCRIPTION = Users may choose to scale gamma dose rates for samples taken within 0.3 m of th e ground surface. The scaling factors of Aitken (1985) are used. Input should be yes 'Y' or no 'N'. OPTIONS = Y, N TI:32 => Grain size min (microns) VALUES = 90 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The grain size range analysed. DRAC can be used for the grain size ranges betwe en 1 and 1000 microns. Inputs should range between 1 and 1000 and not be left bl ank. TI:33 => Grain size max (microns) VALUES = 125 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The grain size range analysed. DRAC can be used for the grain size ranges betwe en 1 and 1000 microns. Inputs should range between 1 and 1000 and not be left bl ank. TI:34 => alpha-Grain size attenuation VALUES = Brennanetal1991 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The grain size attenuation factors for the alpha dose rate. Users have the opti on of datasets from Bell (1980) and Brennan et al. (1991). Input must be 'Bell19 80' or 'Brennanetal1991'. OPTIONS = Bell1980, Brennanetal1991 TI:35 => beta-Grain size attenuation VALUES = Guerinetal2012-Q ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The grain size attenuation factors for the beta dose rate. Users have the optio n of datasets from Mejdahl (1979), Brennan (2003) and Guerin et al. (2012) for q uartz or feldspar. Input must be 'Mejdahl1979', 'Brennan2003', 'Guerinetal2012-Q ' or 'Guerinetal2012-F' . OPTIONS = Mejdahl1979, Brennan2003, Guerinetal2012-Q, Guerinetal2012-F TI:36 => Etch depth min (microns) VALUES = 8 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The user defined etch depth range (microns). Inputs should range between 0 and 30 and not be left blank. TI:37 => Etch depth max (microns) VALUES = 10 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = The user defined etch depth range (microns). Inputs should range between 0 and 30 and not be left blank. TI:38 => beta-Etch depth attenuation factor VALUES = Bell1979 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = The etch depth attenuation factors for the beta dose rate. Users have the optio n of datasets from Bell (1979) and Brennan (2003). Input must be 'Bell1979' or ' Brennan2003'. Note: only the dataset of Bell (1980) is provided for attenuation of the alpha dose rate by etching. OPTIONS = Bell1979, Brennan2003, X TI:39 => a-value VALUES = 0 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Alpha track efficiency value and uncertainty defined by the user. Inputs should be 0 or positive and not left blank. TI:40 => erra-value VALUES = 0 ALLOWS 'X' = TRUE REQUIRED = TRUE DESCRIPTION = Alpha track efficiency value and uncertainty defined by the user. Inputs should be 0 or positive and not left blank. TI:41 => Water content ((wet weight - dry weight)/dry weight) % VALUES = 5 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = Sediment water content (%) over the burial period. Inputs should be 0 or positi ve and not be left blank. TI:42 => errWater content % VALUES = 2 ALLOWS 'X' = FALSE REQUIRED = FALSE DESCRIPTION = Sediment water content (%) over the burial period. Inputs should be 0 or positi ve and not be left blank. TI:43 => Depth (m) VALUES = 2.22 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Depth and uncertainty from which sample was extracted beneath the ground surfac e. Inputs should be 0 or positive and not left blank. TI:44 => errDepth (m) VALUES = 0.05 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Depth and uncertainty from which sample was extracted beneath the ground surfac e. Inputs should be 0 or positive and not left blank. TI:45 => Overburden density (g cm-3) VALUES = 1.8 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = Density of the overlying sediment matrix from which the sample was taken. Input s should be 0 or positive and not be left blank. The scaling calculation will us e the overburden density and uncertainty provided. TI:46 => errOverburden density (g cm-3) VALUES = 0.1 ALLOWS 'X' = FALSE REQUIRED = TRUE DESCRIPTION = Density of the overlying sediment matrix from which the sample was taken. Input s should be 0 or positive and not be left blank. The scaling calculation will us e the overburden density and uncertainty provided. TI:47 => Latitude (decimal degrees) VALUES = 30 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Latitude and longitude of sample location (in degree decimals). Positive values should be used for northern latitudes and eastern longitudes and negative value s for southern latitudes and western longitudes. Inputs should range from -90 to 90 degrees for latitudes and -180 to 180 degrees for longitude. TI:48 => Longitude (decimal degrees) VALUES = 70 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Latitude and longitude of sample location (in degree decimals). Positive values should be used for northern latitudes and eastern longitudes and negative value s for southern latitudes and western longitudes. Inputs should range from -90 to 90 degrees for latitudes and -180 to 180 degrees for longitude. TI:49 => Altitude (m) VALUES = 150 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Altitude of sample location in metres above sea level. Input should be less tha n 5000 and not left blank. TI:50 => User cosmicdoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input a cosmic dose rate (in Gy.ka-1). Inputs in these fields will ov erride the DRAC calculated cosmic dose rate. Inputs should be positive or 'X' if not required, and not left blank. TI:51 => errUser cosmicdoserate (Gy.ka-1) VALUES = X ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Users may input a cosmic dose rate (in Gy.ka-1). Inputs in these fields will ov erride the DRAC calculated cosmic dose rate. Inputs should be positive or 'X' if not required, and not left blank. TI:52 => De (Gy) VALUES = 20 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Sample De and uncertainty (in Gy). Inputs should be positive or 'X' if not requ ired, and not left blank. TI:53 => errDe (Gy) VALUES = 0.2 ALLOWS 'X' = TRUE REQUIRED = FALSE DESCRIPTION = Sample De and uncertainty (in Gy). Inputs should be positive or 'X' if not requ ired, and not left blank. > print(input$`Project ID`) [1] "DRAC-example" attr(,"required") [1] TRUE attr(,"allowsX") [1] FALSE attr(,"default_class") [1] "character" attr(,"key") [1] "TI:1" attr(,"description") [1] "Inputs can be alphabetic, numeric or selected symbols (/ - () [] _). Spaces are not permitted." > print(input[[4]]) [1] Guerinetal2011 attr(,"required") [1] FALSE attr(,"allowsX") [1] TRUE attr(,"default_class") [1] factor attr(,"key") [1] TI:4 attr(,"description") [1] The conversion factors required to calculate dose rates from radionuclide concentrations. Users have the option of datasets from Adamiec and Aitken (1998), Guerin et al. (2011), Liritzis et al. (2013) or Cresswell et al. (2018). Input must be 'AdamiecAitken1998', 'Guerinetal2011', 'Liritzisetal2013', 'Cresswelletal2018', or 'X' if conversion factors are not required. 5 Levels: AdamiecAitken1998 Guerinetal2011 ... X > > > ## Example: DRAC Quartz example > # note that you only have to assign new values where they > # are different to the default values > input$`Project ID` <- "DRAC-Example" > input$`Sample ID` <- "Quartz" > input$`Conversion factors` <- "AdamiecAitken1998" > input$`External U (ppm)` <- 3.4 > input$`errExternal U (ppm)` <- 0.51 > input$`External Th (ppm)` <- 14.47 > input$`errExternal Th (ppm)` <- 1.69 > input$`External K (%)` <- 1.2 > input$`errExternal K (%)` <- 0.14 > input$`Calculate external Rb from K conc?` <- "N" > input$`Calculate internal Rb from K conc?` <- "N" > input$`Scale gammadoserate at shallow depths?` <- "N" > input$`Grain size min (microns)` <- 90 [[[<-.DRAC.list]]()] Error: Grain size min (microns): found numeric, expected integer -> coercing to integer > input$`Grain size max (microns)` <- 125 [[[<-.DRAC.list]]()] Error: Grain size max (microns): found numeric, expected integer -> coercing to integer > input$`Water content ((wet weight - dry weight)/dry weight) %` <- 5 > input$`errWater content %` <- 2 > input$`Depth (m)` <- 2.2 > input$`errDepth (m)` <- 0.22 > input$`Overburden density (g cm-3)` <- 1.8 > input$`errOverburden density (g cm-3)` <- 0.1 > input$`Latitude (decimal degrees)` <- 30.0000 > input$`Longitude (decimal degrees)` <- 70.0000 > input$`Altitude (m)` <- 150 > input$`De (Gy)` <- 20 > input$`errDe (Gy)` <- 0.2 > > # use DRAC > ## Not run: > ##D output <- use_DRAC(input) > ## End(Not run) > > > > > cleanEx() > nameEx("trim_RLum.Data") > ### * trim_RLum.Data > > flush(stderr()); flush(stdout()) > > ### Name: trim_RLum.Data > ### Title: Trim Channels of RLum.Data-class Objects > ### Aliases: trim_RLum.Data > ### Keywords: manip > > ### ** Examples > > ## trim all TL curves in the object to channels 10 to 20 > data(ExampleData.BINfileData, envir = environment()) > temp <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data, pos = 1) > > c <- trim_RLum.Data( + object = temp, + recordType = "TL", + trim_range = c(10,20)) > > plot_RLum.Analysis( + object = c, + combine = TRUE, + subset = list(recordType = "TL")) > > ## simulate a situation where one OSL curve > ## in the dataset has only 999 channels instead of 1000 > ## all curves should be limited to 999 > temp@records[[2]]@data <- temp@records[[2]]@data[-nrow(temp[[2]]@data),] > > c <- trim_RLum.Data(object = temp) > nrow(c@records[[4]]@data) [1] 999 > > > > > > cleanEx() > nameEx("tune_Data") > ### * tune_Data > > flush(stderr()); flush(stdout()) > > ### Name: tune_Data > ### Title: Tune data for experimental purpose > ### Aliases: tune_Data > ### Keywords: manip > > ### ** Examples > > > ## load example data set > data(ExampleData.DeValues, envir = environment()) > x <- ExampleData.DeValues$CA1 > > ## plot original data > plot_AbanicoPlot(data = x, + summary = c("n", "mean")) > > ## decrease error by 10 % > plot_AbanicoPlot(data = tune_Data(x, decrease.error = 0.1), + summary = c("n", "mean")) Warning: [tune_Data()] Dear ripley, these activities on your Linux machine have been tracked and will be submitted to the R.Lum data base. Cheating does not pay off! [2026-03-12 23:59:32.11889] > > ## increase sample size by 200 % > #plot_AbanicoPlot(data = tune_Data(x, increase.data = 2), > # summary = c("n", "mean")) > > > > > cleanEx() > nameEx("use_DRAC") > ### * use_DRAC > > flush(stderr()); flush(stdout()) > > ### Name: use_DRAC > ### Title: Use DRAC to calculate dose rate data > ### Aliases: use_DRAC > > ### ** Examples > > > ## (1) Method using the DRAC spreadsheet > > file <- "/PATH/TO/DRAC_Input_Template.csv" > > # send the actual IO template spreadsheet to DRAC > ## Not run: > ##D use_DRAC(file = file) > ## End(Not run) > > ## (2) Method using an R template object > # Create a template > input <- template_DRAC(preset = "DRAC-example_quartz") -------------------- IMPORTANT NOTE ------------------------ This function returns a DRAC input template to be used in conjunction with the use_DRAC() function. The template was reproduced with great care, but we do not take any responsibility and we are not liable for any mistakes or unforeseen misbehaviour. Note that this template is only compatible with DRAC version 1.1. Before using this template make sure that this is the correct version, otherwise expect unspecified errors. Please ensure you cite the use of DRAC in your work, published or otherwise. Please cite the website name and version (e.g. DRAC v1.1) and the accompanying journal article: Durcan, J.A., King, G.E., Duller, G.A.T., 2015. DRAC: Dose rate and age calculation for trapped charge dating. Quaternary Geochronology 28, 54-61. Set 'notification = FALSE' to hide this message. -------------------- IMPORTANT NOTE ------------------------ > > # Fill the template with values > input$`Project ID` <- "DRAC-Example" > input$`Sample ID` <- "Quartz" > input$`Conversion factors` <- "AdamiecAitken1998" > input$`External U (ppm)` <- 3.4 > input$`errExternal U (ppm)` <- 0.51 > input$`External Th (ppm)` <- 14.47 > input$`errExternal Th (ppm)` <- 1.69 > input$`External K (%)` <- 1.2 > input$`errExternal K (%)` <- 0.14 > input$`Calculate external Rb from K conc?` <- "N" > input$`Calculate internal Rb from K conc?` <- "N" > input$`Scale gammadoserate at shallow depths?` <- "N" > input$`Grain size min (microns)` <- 90 [[[<-.DRAC.list]]()] Error: Grain size min (microns): found numeric, expected integer -> coercing to integer > input$`Grain size max (microns)` <- 125 [[[<-.DRAC.list]]()] Error: Grain size max (microns): found numeric, expected integer -> coercing to integer > input$`Water content ((wet weight - dry weight)/dry weight) %` <- 5 > input$`errWater content %` <- 2 > input$`Depth (m)` <- 2.2 > input$`errDepth (m)` <- 0.22 > input$`Overburden density (g cm-3)` <- 1.8 > input$`errOverburden density (g cm-3)` <- 0.1 > input$`Latitude (decimal degrees)` <- 30.0000 > input$`Longitude (decimal degrees)` <- 70.0000 > input$`Altitude (m)` <- 150 > input$`De (Gy)` <- 20 > input$`errDe (Gy)` <- 0.2 > > # use DRAC > ## Not run: > ##D output <- use_DRAC(input) > ##D > ##D ## export as LaTeX table > ##D .as.latex.table(output) > ## End(Not run) > > > > > cleanEx() > nameEx("verify_SingleGrainData") > ### * verify_SingleGrainData > > flush(stderr()); flush(stdout()) > > ### Name: verify_SingleGrainData > ### Title: Verify single grain data sets and check for invalid grains, i.e. > ### zero-light level grains > ### Aliases: verify_SingleGrainData > ### Keywords: datagen manip > > ### ** Examples > > > ##01 - basic example I > ##just show how to apply the function > data(ExampleData.XSYG, envir = environment()) > > ##verify and get data.frame out of it > verify_SingleGrainData(OSL.SARMeasurement$Sequence.Object)$selection_full Warning: [verify_SingleGrainData()] 'selection_id' is NA, everything tagged for removal POSITION GRAIN MEAN VAR RATIO THRESHOLD VALID 1 NA NA 23.66271 2.572619e+02 10.872037 10 TRUE 2 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 3 NA NA 146.85632 4.982419e+03 33.927165 10 TRUE 4 NA NA 23.20000 4.901230e+03 211.259934 10 TRUE 5 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 6 NA NA 107.87043 7.125950e+02 6.606027 10 FALSE 7 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 8 NA NA 27.06067 3.495743e+02 12.918172 10 TRUE 9 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 10 NA NA 111.65882 2.120132e+04 189.875911 10 TRUE 11 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 12 NA NA 94.00808 1.421120e+03 15.117001 10 TRUE 13 NA NA 14.78800 1.018989e+02 6.890645 10 FALSE 14 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 15 NA NA 107.90087 7.100111e+02 6.580216 10 FALSE 16 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 17 NA NA 26.88278 3.521022e+02 13.097686 10 TRUE 18 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 19 NA NA 203.04576 1.440995e+05 709.689721 10 TRUE 20 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 21 NA NA 147.35434 4.941044e+03 33.531721 10 TRUE 22 NA NA 18.48800 1.309212e+03 70.814165 10 TRUE 23 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 24 NA NA 107.37241 7.180268e+02 6.687256 10 FALSE 25 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 26 NA NA 26.53464 3.569946e+02 13.453909 10 TRUE 27 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 28 NA NA 149.22647 4.077393e+04 273.235223 10 TRUE 29 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 30 NA NA 93.65100 1.425739e+03 15.223959 10 TRUE 31 NA NA 15.43400 1.468754e+02 9.516353 10 FALSE 32 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 33 NA NA 107.74087 7.151408e+02 6.637600 10 FALSE 34 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 35 NA NA 26.88278 3.521553e+02 13.099660 10 TRUE 36 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 37 NA NA 437.18390 7.404312e+05 1693.637907 10 TRUE 38 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 39 NA NA 146.74713 4.976541e+03 33.912357 10 TRUE 40 NA NA 26.99200 8.015916e+03 296.973761 10 TRUE 41 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 42 NA NA 107.87652 7.046340e+02 6.531857 10 FALSE 43 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 44 NA NA 26.88079 3.520762e+02 13.097687 10 TRUE 45 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 46 NA NA 183.18088 6.418055e+04 350.367102 10 TRUE 47 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 48 NA NA 94.05556 1.416457e+03 15.059791 10 TRUE 49 NA NA 16.43000 2.741815e+02 16.687855 10 TRUE 50 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 51 NA NA 108.64071 6.910736e+02 6.361093 10 FALSE 52 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 53 NA NA 27.62109 3.416066e+02 12.367601 10 TRUE 54 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 55 NA NA 693.53644 1.868981e+06 2694.856789 10 TRUE 56 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 57 NA NA 146.77471 4.985033e+03 33.963838 10 TRUE 58 NA NA 41.61400 3.277204e+04 787.524417 10 TRUE 59 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 60 NA NA 107.84087 7.062001e+02 6.548538 10 FALSE 61 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 62 NA NA 26.89205 3.523737e+02 13.103264 10 TRUE 63 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 64 NA NA 229.96912 1.033205e+05 449.279678 10 TRUE 65 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 66 NA NA 94.09293 1.419207e+03 15.083033 10 TRUE 67 NA NA 17.54000 4.446938e+02 25.353124 10 TRUE 68 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 69 NA NA 107.82348 7.152073e+02 6.633131 10 FALSE 70 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 71 NA NA 26.88212 3.521107e+02 13.098323 10 TRUE 72 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 73 NA NA 919.37203 3.298185e+06 3587.432532 10 TRUE 74 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 75 NA NA 146.25829 4.992561e+03 34.135236 10 TRUE 76 NA NA 55.33200 7.126496e+04 1287.951921 10 TRUE 77 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 78 NA NA 107.44397 7.226060e+02 6.725422 10 FALSE 79 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 80 NA NA 26.70197 3.544455e+02 13.274131 10 TRUE 81 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 82 NA NA 278.14412 1.553639e+05 558.573294 10 TRUE 83 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 84 NA NA 94.03131 1.419523e+03 15.096277 10 TRUE 85 NA NA 20.75400 7.620376e+02 36.717624 10 TRUE 86 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 87 NA NA 108.72566 6.921674e+02 6.366182 10 FALSE 88 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 89 NA NA 27.60612 3.412339e+02 12.360804 10 TRUE 90 NA NA 15.83136 4.363311e+01 2.756120 10 FALSE 91 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 92 NA NA 146.50230 4.921485e+03 33.593229 10 TRUE 93 NA NA 13.75400 2.191331e+01 1.593232 10 FALSE 94 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 95 NA NA 108.25351 6.988567e+02 6.455741 10 FALSE 96 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 97 NA NA 27.23758 3.468351e+02 12.733694 10 TRUE 98 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 99 NA NA 296.30735 1.763985e+05 595.322619 10 TRUE 100 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 101 NA NA 93.99192 1.420900e+03 15.117255 10 TRUE 102 NA NA 19.43600 8.624027e+02 44.371409 10 TRUE 103 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 104 NA NA 107.82174 7.110169e+02 6.594375 10 FALSE 105 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 106 NA NA 26.88344 3.521723e+02 13.099971 10 TRUE 107 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 108 NA NA 532.60085 1.130401e+06 2122.416765 10 TRUE 109 NA NA 133.00000 1.364500e+04 102.593985 10 TRUE 110 NA NA 146.72471 4.962003e+03 33.818454 10 TRUE 111 NA NA 27.52000 7.629970e+03 277.251800 10 TRUE 112 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 113 NA NA 107.92696 7.062523e+02 6.543799 10 FALSE 114 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 115 NA NA 26.87815 3.520057e+02 13.096354 10 TRUE 116 NA NA 1.00000 0.000000e+00 0.000000 10 FALSE 117 NA NA 302.94412 1.862969e+05 614.954596 10 TRUE 118 NA NA 76.25000 3.389583e+03 44.453552 10 TRUE 119 NA NA 94.41327 1.419383e+03 15.033721 10 TRUE 120 NA NA 20.19800 8.579387e+02 42.476417 10 TRUE 121 NA NA 79.00000 1.967500e+03 24.905063 10 TRUE 122 NA NA 108.15702 6.957128e+02 6.432433 10 FALSE 123 NA NA 40.00000 0.000000e+00 0.000000 10 FALSE 124 NA NA 27.24765 3.470933e+02 12.738468 10 TRUE > > ##02 - basic example II > data(ExampleData.BINfileData, envir = environment()) > id <- verify_SingleGrainData(object = CWOSL.SAR.Data, + cleanup_level = "aliquot")$selection_id > > ## Not run: > ##D ##03 - advanced example I > ##D ##importing and exporting a BIN-file > ##D > ##D ##select and import file > ##D file <- file.choose() > ##D object <- read_BIN2R(file) > ##D > ##D ##remove invalid aliquots(!) > ##D object <- verify_SingleGrainData(object, cleanup = TRUE) > ##D > ##D ##export to new BIN-file > ##D write_R2BIN(object, paste0(dirname(file),"/", basename(file), "_CLEANED.BIN")) > ## End(Not run) > > > > > cleanEx() > nameEx("write_R2BIN") > ### * write_R2BIN > > flush(stderr()); flush(stdout()) > > ### Name: write_R2BIN > ### Title: Export Risoe.BINfileData into Risø BIN/BINX-file > ### Aliases: write_R2BIN > ### Keywords: IO > > ### ** Examples > > ##load example dataset > file <- system.file("extdata/BINfile_V8.binx", package = "Luminescence") > temp <- read_BIN2R(file) [read_BIN2R()] Importing ... path: /data/blackswan/ripley/R/packages/tests-vg/Luminescence.Rcheck/Luminescence/extdata file: BINfile_V8.binx n_rec: 2 | | | 0% | |=================================== | 50% | |======================================================================| 100% >> 2 records read successfully > > ##create temporary file path > ##(for usage replace by own path) > temp_file <- tempfile(pattern = "output", fileext = ".binx") > > ##export to temporary file path > write_R2BIN(temp, file = temp_file) [write_R2BIN()] Exporting ... path: /tmp/Rtmp66j6gd file: output15384c74373200.binx n_rec: 2 | | | 0% | |======================================================================| 100% >> 2 records written successfully > > > > > cleanEx() > nameEx("write_R2TIFF") > ### * write_R2TIFF > > flush(stderr()); flush(stdout()) > > ### Name: write_R2TIFF > ### Title: Export RLum.Data.Image and RLum.Data.Spectrum objects to TIFF > ### Images > ### Aliases: write_R2TIFF > ### Keywords: IO > > ### ** Examples > > data(ExampleData.RLum.Data.Image, envir = environment()) > write_R2TIFF(ExampleData.RLum.Data.Image, file = tempfile(fileext = ".tiff")) > > > > > cleanEx() > nameEx("write_RLum2CSV") > ### * write_RLum2CSV > > flush(stderr()); flush(stdout()) > > ### Name: write_RLum2CSV > ### Title: Export RLum-objects to CSV > ### Aliases: write_RLum2CSV > ### Keywords: IO > > ### ** Examples > > > ## transform values to a list (and do not write) > data(ExampleData.BINfileData, envir = environment()) > object <- Risoe.BINfileData2RLum.Analysis(CWOSL.SAR.Data)[[1]] > write_RLum2CSV(object, export = FALSE) $`1_TL (PMT)` [,1] [,2] [1,] 0.884 2 [2,] 1.768 0 [3,] 2.652 13 [4,] 3.536 1 [5,] 4.420 1 [6,] 5.304 5 [7,] 6.188 6 [8,] 7.072 12 [9,] 7.956 12 [10,] 8.840 0 [11,] 9.724 2 [12,] 10.608 4 [13,] 11.492 2 [14,] 12.376 4 [15,] 13.260 6 [16,] 14.144 6 [17,] 15.028 4 [18,] 15.912 8 [19,] 16.796 6 [20,] 17.680 8 [21,] 18.564 3 [22,] 19.448 2 [23,] 20.332 8 [24,] 21.216 1 [25,] 22.100 4 [26,] 22.984 3 [27,] 23.868 6 [28,] 24.752 8 [29,] 25.636 3 [30,] 26.520 1 [31,] 27.404 3 [32,] 28.288 1 [33,] 29.172 1 [34,] 30.056 1 [35,] 30.940 12 [36,] 31.824 5 [37,] 32.708 1 [38,] 33.592 10 [39,] 34.476 0 [40,] 35.360 0 [41,] 36.244 2 [42,] 37.128 2 [43,] 38.012 2 [44,] 38.896 1 [45,] 39.780 12 [46,] 40.664 1 [47,] 41.548 3 [48,] 42.432 4 [49,] 43.316 2 [50,] 44.200 6 [51,] 45.084 4 [52,] 45.968 1 [53,] 46.852 3 [54,] 47.736 6 [55,] 48.620 6 [56,] 49.504 5 [57,] 50.388 5 [58,] 51.272 0 [59,] 52.156 0 [60,] 53.040 5 [61,] 53.924 2 [62,] 54.808 2 [63,] 55.692 0 [64,] 56.576 2 [65,] 57.460 2 [66,] 58.344 3 [67,] 59.228 15 [68,] 60.112 4 [69,] 60.996 0 [70,] 61.880 7 [71,] 62.764 4 [72,] 63.648 4 [73,] 64.532 0 [74,] 65.416 3 [75,] 66.300 14 [76,] 67.184 4 [77,] 68.068 7 [78,] 68.952 7 [79,] 69.836 4 [80,] 70.720 4 [81,] 71.604 2 [82,] 72.488 4 [83,] 73.372 1 [84,] 74.256 8 [85,] 75.140 3 [86,] 76.024 1 [87,] 76.908 3 [88,] 77.792 2 [89,] 78.676 5 [90,] 79.560 2 [91,] 80.444 17 [92,] 81.328 12 [93,] 82.212 5 [94,] 83.096 4 [95,] 83.980 3 [96,] 84.864 3 [97,] 85.748 18 [98,] 86.632 3 [99,] 87.516 12 [100,] 88.400 2 [101,] 89.284 4 [102,] 90.168 5 [103,] 91.052 7 [104,] 91.936 4 [105,] 92.820 4 [106,] 93.704 2 [107,] 94.588 8 [108,] 95.472 7 [109,] 96.356 1 [110,] 97.240 9 [111,] 98.124 5 [112,] 99.008 9 [113,] 99.892 5 [114,] 100.776 13 [115,] 101.660 0 [116,] 102.544 10 [117,] 103.428 1 [118,] 104.312 1 [119,] 105.196 1 [120,] 106.080 2 [121,] 106.964 6 [122,] 107.848 6 [123,] 108.732 9 [124,] 109.616 4 [125,] 110.500 12 [126,] 111.384 8 [127,] 112.268 1 [128,] 113.152 8 [129,] 114.036 2 [130,] 114.920 7 [131,] 115.804 6 [132,] 116.688 7 [133,] 117.572 1 [134,] 118.456 2 [135,] 119.340 5 [136,] 120.224 1 [137,] 121.108 6 [138,] 121.992 0 [139,] 122.876 11 [140,] 123.760 5 [141,] 124.644 1 [142,] 125.528 3 [143,] 126.412 13 [144,] 127.296 11 [145,] 128.180 1 [146,] 129.064 3 [147,] 129.948 5 [148,] 130.832 6 [149,] 131.716 5 [150,] 132.600 2 [151,] 133.484 5 [152,] 134.368 0 [153,] 135.252 16 [154,] 136.136 5 [155,] 137.020 10 [156,] 137.904 1 [157,] 138.788 3 [158,] 139.672 17 [159,] 140.556 4 [160,] 141.440 7 [161,] 142.324 10 [162,] 143.208 10 [163,] 144.092 4 [164,] 144.976 6 [165,] 145.860 3 [166,] 146.744 8 [167,] 147.628 4 [168,] 148.512 9 [169,] 149.396 5 [170,] 150.280 7 [171,] 151.164 6 [172,] 152.048 5 [173,] 152.932 8 [174,] 153.816 10 [175,] 154.700 8 [176,] 155.584 3 [177,] 156.468 7 [178,] 157.352 11 [179,] 158.236 4 [180,] 159.120 21 [181,] 160.004 14 [182,] 160.888 3 [183,] 161.772 4 [184,] 162.656 20 [185,] 163.540 9 [186,] 164.424 11 [187,] 165.308 8 [188,] 166.192 11 [189,] 167.076 14 [190,] 167.960 13 [191,] 168.844 12 [192,] 169.728 11 [193,] 170.612 25 [194,] 171.496 7 [195,] 172.380 9 [196,] 173.264 10 [197,] 174.148 18 [198,] 175.032 9 [199,] 175.916 15 [200,] 176.800 11 [201,] 177.684 19 [202,] 178.568 24 [203,] 179.452 29 [204,] 180.336 18 [205,] 181.220 27 [206,] 182.104 26 [207,] 182.988 25 [208,] 183.872 21 [209,] 184.756 17 [210,] 185.640 24 [211,] 186.524 32 [212,] 187.408 22 [213,] 188.292 25 [214,] 189.176 29 [215,] 190.060 35 [216,] 190.944 25 [217,] 191.828 27 [218,] 192.712 45 [219,] 193.596 43 [220,] 194.480 43 [221,] 195.364 44 [222,] 196.248 53 [223,] 197.132 51 [224,] 198.016 42 [225,] 198.900 56 [226,] 199.784 40 [227,] 200.668 49 [228,] 201.552 45 [229,] 202.436 85 [230,] 203.320 66 [231,] 204.204 72 [232,] 205.088 67 [233,] 205.972 83 [234,] 206.856 88 [235,] 207.740 90 [236,] 208.624 78 [237,] 209.508 81 [238,] 210.392 74 [239,] 211.276 108 [240,] 212.160 87 [241,] 213.044 110 [242,] 213.928 99 [243,] 214.812 123 [244,] 215.696 127 [245,] 216.580 144 [246,] 217.464 108 [247,] 218.348 120 [248,] 219.232 129 [249,] 220.116 131 [250,] 221.000 72 $`2_OSL (PMT)` [,1] [,2] [1,] 0.04 11111 [2,] 0.08 9280 [3,] 0.12 8218 [4,] 0.16 6794 [5,] 0.20 5743 [6,] 0.24 5050 [7,] 0.28 4156 [8,] 0.32 3750 [9,] 0.36 3170 [10,] 0.40 2703 [11,] 0.44 2408 [12,] 0.48 2066 [13,] 0.52 1790 [14,] 0.56 1647 [15,] 0.60 1461 [16,] 0.64 1289 [17,] 0.68 1010 [18,] 0.72 971 [19,] 0.76 829 [20,] 0.80 766 [21,] 0.84 713 [22,] 0.88 600 [23,] 0.92 555 [24,] 0.96 475 [25,] 1.00 433 [26,] 1.04 473 [27,] 1.08 362 [28,] 1.12 371 [29,] 1.16 313 [30,] 1.20 281 [31,] 1.24 269 [32,] 1.28 245 [33,] 1.32 247 [34,] 1.36 213 [35,] 1.40 185 [36,] 1.44 179 [37,] 1.48 186 [38,] 1.52 177 [39,] 1.56 113 [40,] 1.60 156 [41,] 1.64 117 [42,] 1.68 167 [43,] 1.72 116 [44,] 1.76 123 [45,] 1.80 120 [46,] 1.84 116 [47,] 1.88 87 [48,] 1.92 93 [49,] 1.96 109 [50,] 2.00 109 [51,] 2.04 80 [52,] 2.08 91 [53,] 2.12 94 [54,] 2.16 90 [55,] 2.20 101 [56,] 2.24 86 [57,] 2.28 107 [58,] 2.32 91 [59,] 2.36 73 [60,] 2.40 89 [61,] 2.44 68 [62,] 2.48 65 [63,] 2.52 72 [64,] 2.56 90 [65,] 2.60 72 [66,] 2.64 92 [67,] 2.68 77 [68,] 2.72 94 [69,] 2.76 86 [70,] 2.80 95 [71,] 2.84 107 [72,] 2.88 91 [73,] 2.92 52 [74,] 2.96 73 [75,] 3.00 74 [76,] 3.04 75 [77,] 3.08 75 [78,] 3.12 72 [79,] 3.16 102 [80,] 3.20 72 [81,] 3.24 65 [82,] 3.28 56 [83,] 3.32 90 [84,] 3.36 68 [85,] 3.40 70 [86,] 3.44 55 [87,] 3.48 51 [88,] 3.52 62 [89,] 3.56 53 [90,] 3.60 73 [91,] 3.64 74 [92,] 3.68 50 [93,] 3.72 66 [94,] 3.76 83 [95,] 3.80 51 [96,] 3.84 64 [97,] 3.88 38 [98,] 3.92 61 [99,] 3.96 50 [100,] 4.00 74 [101,] 4.04 54 [102,] 4.08 72 [103,] 4.12 74 [104,] 4.16 57 [105,] 4.20 64 [106,] 4.24 46 [107,] 4.28 55 [108,] 4.32 65 [109,] 4.36 80 [110,] 4.40 49 [111,] 4.44 31 [112,] 4.48 61 [113,] 4.52 67 [114,] 4.56 60 [115,] 4.60 49 [116,] 4.64 75 [117,] 4.68 58 [118,] 4.72 46 [119,] 4.76 55 [120,] 4.80 56 [121,] 4.84 53 [122,] 4.88 69 [123,] 4.92 55 [124,] 4.96 49 [125,] 5.00 56 [126,] 5.04 63 [127,] 5.08 46 [128,] 5.12 67 [129,] 5.16 69 [130,] 5.20 59 [131,] 5.24 57 [132,] 5.28 68 [133,] 5.32 74 [134,] 5.36 64 [135,] 5.40 45 [136,] 5.44 54 [137,] 5.48 45 [138,] 5.52 44 [139,] 5.56 85 [140,] 5.60 54 [141,] 5.64 46 [142,] 5.68 49 [143,] 5.72 67 [144,] 5.76 56 [145,] 5.80 37 [146,] 5.84 48 [147,] 5.88 56 [148,] 5.92 53 [149,] 5.96 42 [150,] 6.00 67 [151,] 6.04 63 [152,] 6.08 63 [153,] 6.12 57 [154,] 6.16 51 [155,] 6.20 52 [156,] 6.24 51 [157,] 6.28 52 [158,] 6.32 67 [159,] 6.36 39 [160,] 6.40 38 [161,] 6.44 46 [162,] 6.48 45 [163,] 6.52 48 [164,] 6.56 53 [165,] 6.60 45 [166,] 6.64 48 [167,] 6.68 40 [168,] 6.72 40 [169,] 6.76 47 [170,] 6.80 75 [171,] 6.84 37 [172,] 6.88 56 [173,] 6.92 47 [174,] 6.96 33 [175,] 7.00 47 [176,] 7.04 39 [177,] 7.08 50 [178,] 7.12 46 [179,] 7.16 44 [180,] 7.20 44 [181,] 7.24 36 [182,] 7.28 51 [183,] 7.32 44 [184,] 7.36 43 [185,] 7.40 39 [186,] 7.44 58 [187,] 7.48 60 [188,] 7.52 53 [189,] 7.56 61 [190,] 7.60 42 [191,] 7.64 66 [192,] 7.68 42 [193,] 7.72 59 [194,] 7.76 54 [195,] 7.80 66 [196,] 7.84 41 [197,] 7.88 42 [198,] 7.92 51 [199,] 7.96 28 [200,] 8.00 29 [201,] 8.04 52 [202,] 8.08 50 [203,] 8.12 54 [204,] 8.16 53 [205,] 8.20 53 [206,] 8.24 36 [207,] 8.28 35 [208,] 8.32 53 [209,] 8.36 31 [210,] 8.40 45 [211,] 8.44 40 [212,] 8.48 27 [213,] 8.52 52 [214,] 8.56 48 [215,] 8.60 49 [216,] 8.64 51 [217,] 8.68 51 [218,] 8.72 32 [219,] 8.76 44 [220,] 8.80 48 [221,] 8.84 56 [222,] 8.88 44 [223,] 8.92 55 [224,] 8.96 30 [225,] 9.00 35 [226,] 9.04 60 [227,] 9.08 47 [228,] 9.12 43 [229,] 9.16 31 [230,] 9.20 38 [231,] 9.24 34 [232,] 9.28 43 [233,] 9.32 44 [234,] 9.36 41 [235,] 9.40 53 [236,] 9.44 35 [237,] 9.48 82 [238,] 9.52 33 [239,] 9.56 44 [240,] 9.60 43 [241,] 9.64 40 [242,] 9.68 31 [243,] 9.72 46 [244,] 9.76 50 [245,] 9.80 42 [246,] 9.84 64 [247,] 9.88 47 [248,] 9.92 39 [249,] 9.96 48 [250,] 10.00 53 [251,] 10.04 47 [252,] 10.08 49 [253,] 10.12 35 [254,] 10.16 40 [255,] 10.20 35 [256,] 10.24 42 [257,] 10.28 38 [258,] 10.32 35 [259,] 10.36 38 [260,] 10.40 53 [261,] 10.44 48 [262,] 10.48 34 [263,] 10.52 55 [264,] 10.56 36 [265,] 10.60 52 [266,] 10.64 52 [267,] 10.68 41 [268,] 10.72 47 [269,] 10.76 37 [270,] 10.80 43 [271,] 10.84 39 [272,] 10.88 36 [273,] 10.92 36 [274,] 10.96 27 [275,] 11.00 41 [276,] 11.04 47 [277,] 11.08 38 [278,] 11.12 36 [279,] 11.16 39 [280,] 11.20 32 [281,] 11.24 32 [282,] 11.28 37 [283,] 11.32 43 [284,] 11.36 39 [285,] 11.40 48 [286,] 11.44 41 [287,] 11.48 43 [288,] 11.52 42 [289,] 11.56 50 [290,] 11.60 48 [291,] 11.64 48 [292,] 11.68 54 [293,] 11.72 42 [294,] 11.76 44 [295,] 11.80 39 [296,] 11.84 30 [297,] 11.88 32 [298,] 11.92 43 [299,] 11.96 52 [300,] 12.00 36 [301,] 12.04 37 [302,] 12.08 44 [303,] 12.12 39 [304,] 12.16 46 [305,] 12.20 44 [306,] 12.24 31 [307,] 12.28 44 [308,] 12.32 45 [309,] 12.36 33 [310,] 12.40 39 [311,] 12.44 61 [312,] 12.48 35 [313,] 12.52 27 [314,] 12.56 47 [315,] 12.60 50 [316,] 12.64 39 [317,] 12.68 25 [318,] 12.72 31 [319,] 12.76 47 [320,] 12.80 46 [321,] 12.84 40 [322,] 12.88 55 [323,] 12.92 50 [324,] 12.96 51 [325,] 13.00 46 [326,] 13.04 46 [327,] 13.08 50 [328,] 13.12 43 [329,] 13.16 44 [330,] 13.20 37 [331,] 13.24 45 [332,] 13.28 38 [333,] 13.32 40 [334,] 13.36 28 [335,] 13.40 51 [336,] 13.44 31 [337,] 13.48 41 [338,] 13.52 42 [339,] 13.56 39 [340,] 13.60 33 [341,] 13.64 49 [342,] 13.68 46 [343,] 13.72 37 [344,] 13.76 27 [345,] 13.80 40 [346,] 13.84 40 [347,] 13.88 25 [348,] 13.92 30 [349,] 13.96 32 [350,] 14.00 42 [351,] 14.04 30 [352,] 14.08 33 [353,] 14.12 59 [354,] 14.16 36 [355,] 14.20 45 [356,] 14.24 38 [357,] 14.28 40 [358,] 14.32 31 [359,] 14.36 30 [360,] 14.40 53 [361,] 14.44 42 [362,] 14.48 48 [363,] 14.52 37 [364,] 14.56 43 [365,] 14.60 28 [366,] 14.64 33 [367,] 14.68 41 [368,] 14.72 35 [369,] 14.76 28 [370,] 14.80 24 [371,] 14.84 28 [372,] 14.88 36 [373,] 14.92 42 [374,] 14.96 49 [375,] 15.00 55 [376,] 15.04 25 [377,] 15.08 30 [378,] 15.12 38 [379,] 15.16 31 [380,] 15.20 34 [381,] 15.24 43 [382,] 15.28 51 [383,] 15.32 50 [384,] 15.36 45 [385,] 15.40 39 [386,] 15.44 41 [387,] 15.48 42 [388,] 15.52 27 [389,] 15.56 27 [390,] 15.60 62 [391,] 15.64 30 [392,] 15.68 24 [393,] 15.72 44 [394,] 15.76 40 [395,] 15.80 35 [396,] 15.84 51 [397,] 15.88 52 [398,] 15.92 23 [399,] 15.96 42 [400,] 16.00 34 [401,] 16.04 70 [402,] 16.08 41 [403,] 16.12 44 [404,] 16.16 45 [405,] 16.20 37 [406,] 16.24 31 [407,] 16.28 34 [408,] 16.32 32 [409,] 16.36 47 [410,] 16.40 37 [411,] 16.44 37 [412,] 16.48 28 [413,] 16.52 47 [414,] 16.56 39 [415,] 16.60 40 [416,] 16.64 39 [417,] 16.68 48 [418,] 16.72 32 [419,] 16.76 25 [420,] 16.80 37 [421,] 16.84 42 [422,] 16.88 31 [423,] 16.92 43 [424,] 16.96 26 [425,] 17.00 40 [426,] 17.04 43 [427,] 17.08 36 [428,] 17.12 37 [429,] 17.16 32 [430,] 17.20 42 [431,] 17.24 31 [432,] 17.28 35 [433,] 17.32 28 [434,] 17.36 38 [435,] 17.40 34 [436,] 17.44 43 [437,] 17.48 48 [438,] 17.52 46 [439,] 17.56 44 [440,] 17.60 37 [441,] 17.64 37 [442,] 17.68 49 [443,] 17.72 31 [444,] 17.76 41 [445,] 17.80 41 [446,] 17.84 22 [447,] 17.88 37 [448,] 17.92 32 [449,] 17.96 48 [450,] 18.00 36 [451,] 18.04 33 [452,] 18.08 33 [453,] 18.12 43 [454,] 18.16 51 [455,] 18.20 22 [456,] 18.24 39 [457,] 18.28 45 [458,] 18.32 33 [459,] 18.36 36 [460,] 18.40 38 [461,] 18.44 30 [462,] 18.48 35 [463,] 18.52 36 [464,] 18.56 32 [465,] 18.60 39 [466,] 18.64 39 [467,] 18.68 28 [468,] 18.72 41 [469,] 18.76 28 [470,] 18.80 41 [471,] 18.84 32 [472,] 18.88 32 [473,] 18.92 51 [474,] 18.96 29 [475,] 19.00 41 [476,] 19.04 49 [477,] 19.08 30 [478,] 19.12 37 [479,] 19.16 32 [480,] 19.20 37 [481,] 19.24 38 [482,] 19.28 31 [483,] 19.32 40 [484,] 19.36 35 [485,] 19.40 44 [486,] 19.44 36 [487,] 19.48 44 [488,] 19.52 33 [489,] 19.56 35 [490,] 19.60 46 [491,] 19.64 45 [492,] 19.68 25 [493,] 19.72 47 [494,] 19.76 35 [495,] 19.80 25 [496,] 19.84 26 [497,] 19.88 28 [498,] 19.92 36 [499,] 19.96 39 [500,] 20.00 43 [501,] 20.04 46 [502,] 20.08 28 [503,] 20.12 40 [504,] 20.16 50 [505,] 20.20 26 [506,] 20.24 37 [507,] 20.28 43 [508,] 20.32 33 [509,] 20.36 24 [510,] 20.40 42 [511,] 20.44 40 [512,] 20.48 39 [513,] 20.52 41 [514,] 20.56 34 [515,] 20.60 48 [516,] 20.64 46 [517,] 20.68 44 [518,] 20.72 36 [519,] 20.76 40 [520,] 20.80 40 [521,] 20.84 47 [522,] 20.88 38 [523,] 20.92 43 [524,] 20.96 35 [525,] 21.00 56 [526,] 21.04 34 [527,] 21.08 36 [528,] 21.12 26 [529,] 21.16 36 [530,] 21.20 43 [531,] 21.24 43 [532,] 21.28 40 [533,] 21.32 42 [534,] 21.36 30 [535,] 21.40 32 [536,] 21.44 32 [537,] 21.48 29 [538,] 21.52 39 [539,] 21.56 26 [540,] 21.60 40 [541,] 21.64 39 [542,] 21.68 42 [543,] 21.72 28 [544,] 21.76 39 [545,] 21.80 42 [546,] 21.84 33 [547,] 21.88 47 [548,] 21.92 35 [549,] 21.96 28 [550,] 22.00 36 [551,] 22.04 29 [552,] 22.08 22 [553,] 22.12 31 [554,] 22.16 28 [555,] 22.20 30 [556,] 22.24 44 [557,] 22.28 44 [558,] 22.32 36 [559,] 22.36 46 [560,] 22.40 29 [561,] 22.44 30 [562,] 22.48 42 [563,] 22.52 23 [564,] 22.56 28 [565,] 22.60 34 [566,] 22.64 21 [567,] 22.68 51 [568,] 22.72 40 [569,] 22.76 37 [570,] 22.80 24 [571,] 22.84 40 [572,] 22.88 47 [573,] 22.92 45 [574,] 22.96 34 [575,] 23.00 42 [576,] 23.04 36 [577,] 23.08 59 [578,] 23.12 34 [579,] 23.16 31 [580,] 23.20 39 [581,] 23.24 27 [582,] 23.28 31 [583,] 23.32 35 [584,] 23.36 48 [585,] 23.40 30 [586,] 23.44 46 [587,] 23.48 17 [588,] 23.52 47 [589,] 23.56 28 [590,] 23.60 42 [591,] 23.64 38 [592,] 23.68 37 [593,] 23.72 33 [594,] 23.76 42 [595,] 23.80 32 [596,] 23.84 21 [597,] 23.88 20 [598,] 23.92 33 [599,] 23.96 30 [600,] 24.00 32 [601,] 24.04 31 [602,] 24.08 28 [603,] 24.12 23 [604,] 24.16 36 [605,] 24.20 20 [606,] 24.24 34 [607,] 24.28 29 [608,] 24.32 44 [609,] 24.36 43 [610,] 24.40 43 [611,] 24.44 31 [612,] 24.48 39 [613,] 24.52 37 [614,] 24.56 35 [615,] 24.60 37 [616,] 24.64 30 [617,] 24.68 41 [618,] 24.72 37 [619,] 24.76 32 [620,] 24.80 31 [621,] 24.84 37 [622,] 24.88 45 [623,] 24.92 32 [624,] 24.96 29 [625,] 25.00 34 [626,] 25.04 41 [627,] 25.08 22 [628,] 25.12 25 [629,] 25.16 43 [630,] 25.20 15 [631,] 25.24 24 [632,] 25.28 29 [633,] 25.32 30 [634,] 25.36 24 [635,] 25.40 27 [636,] 25.44 29 [637,] 25.48 53 [638,] 25.52 29 [639,] 25.56 32 [640,] 25.60 19 [641,] 25.64 39 [642,] 25.68 37 [643,] 25.72 42 [644,] 25.76 40 [645,] 25.80 35 [646,] 25.84 27 [647,] 25.88 39 [648,] 25.92 23 [649,] 25.96 25 [650,] 26.00 50 [651,] 26.04 25 [652,] 26.08 35 [653,] 26.12 40 [654,] 26.16 39 [655,] 26.20 32 [656,] 26.24 41 [657,] 26.28 28 [658,] 26.32 29 [659,] 26.36 28 [660,] 26.40 41 [661,] 26.44 28 [662,] 26.48 45 [663,] 26.52 23 [664,] 26.56 32 [665,] 26.60 43 [666,] 26.64 34 [667,] 26.68 36 [668,] 26.72 27 [669,] 26.76 22 [670,] 26.80 45 [671,] 26.84 41 [672,] 26.88 42 [673,] 26.92 18 [674,] 26.96 42 [675,] 27.00 31 [676,] 27.04 50 [677,] 27.08 24 [678,] 27.12 49 [679,] 27.16 31 [680,] 27.20 23 [681,] 27.24 43 [682,] 27.28 27 [683,] 27.32 32 [684,] 27.36 19 [685,] 27.40 31 [686,] 27.44 36 [687,] 27.48 29 [688,] 27.52 46 [689,] 27.56 36 [690,] 27.60 28 [691,] 27.64 28 [692,] 27.68 24 [693,] 27.72 36 [694,] 27.76 40 [695,] 27.80 41 [696,] 27.84 44 [697,] 27.88 38 [698,] 27.92 28 [699,] 27.96 30 [700,] 28.00 33 [701,] 28.04 24 [702,] 28.08 21 [703,] 28.12 32 [704,] 28.16 41 [705,] 28.20 31 [706,] 28.24 30 [707,] 28.28 35 [708,] 28.32 44 [709,] 28.36 36 [710,] 28.40 32 [711,] 28.44 40 [712,] 28.48 49 [713,] 28.52 37 [714,] 28.56 26 [715,] 28.60 30 [716,] 28.64 29 [717,] 28.68 28 [718,] 28.72 20 [719,] 28.76 28 [720,] 28.80 26 [721,] 28.84 41 [722,] 28.88 34 [723,] 28.92 26 [724,] 28.96 27 [725,] 29.00 25 [726,] 29.04 41 [727,] 29.08 34 [728,] 29.12 25 [729,] 29.16 35 [730,] 29.20 31 [731,] 29.24 44 [732,] 29.28 25 [733,] 29.32 41 [734,] 29.36 23 [735,] 29.40 52 [736,] 29.44 38 [737,] 29.48 26 [738,] 29.52 31 [739,] 29.56 27 [740,] 29.60 45 [741,] 29.64 33 [742,] 29.68 30 [743,] 29.72 27 [744,] 29.76 26 [745,] 29.80 30 [746,] 29.84 32 [747,] 29.88 28 [748,] 29.92 27 [749,] 29.96 34 [750,] 30.00 30 [751,] 30.04 31 [752,] 30.08 25 [753,] 30.12 23 [754,] 30.16 30 [755,] 30.20 32 [756,] 30.24 30 [757,] 30.28 27 [758,] 30.32 17 [759,] 30.36 33 [760,] 30.40 35 [761,] 30.44 29 [762,] 30.48 35 [763,] 30.52 39 [764,] 30.56 32 [765,] 30.60 41 [766,] 30.64 36 [767,] 30.68 28 [768,] 30.72 32 [769,] 30.76 26 [770,] 30.80 28 [771,] 30.84 24 [772,] 30.88 25 [773,] 30.92 33 [774,] 30.96 25 [775,] 31.00 30 [776,] 31.04 34 [777,] 31.08 31 [778,] 31.12 33 [779,] 31.16 22 [780,] 31.20 27 [781,] 31.24 29 [782,] 31.28 22 [783,] 31.32 29 [784,] 31.36 61 [785,] 31.40 59 [786,] 31.44 40 [787,] 31.48 22 [788,] 31.52 44 [789,] 31.56 28 [790,] 31.60 28 [791,] 31.64 26 [792,] 31.68 27 [793,] 31.72 43 [794,] 31.76 29 [795,] 31.80 21 [796,] 31.84 35 [797,] 31.88 25 [798,] 31.92 36 [799,] 31.96 17 [800,] 32.00 39 [801,] 32.04 37 [802,] 32.08 28 [803,] 32.12 37 [804,] 32.16 33 [805,] 32.20 33 [806,] 32.24 27 [807,] 32.28 24 [808,] 32.32 30 [809,] 32.36 30 [810,] 32.40 42 [811,] 32.44 32 [812,] 32.48 33 [813,] 32.52 43 [814,] 32.56 39 [815,] 32.60 31 [816,] 32.64 34 [817,] 32.68 31 [818,] 32.72 32 [819,] 32.76 34 [820,] 32.80 33 [821,] 32.84 23 [822,] 32.88 17 [823,] 32.92 36 [824,] 32.96 26 [825,] 33.00 31 [826,] 33.04 36 [827,] 33.08 27 [828,] 33.12 49 [829,] 33.16 26 [830,] 33.20 30 [831,] 33.24 32 [832,] 33.28 26 [833,] 33.32 29 [834,] 33.36 27 [835,] 33.40 27 [836,] 33.44 18 [837,] 33.48 32 [838,] 33.52 22 [839,] 33.56 37 [840,] 33.60 29 [841,] 33.64 23 [842,] 33.68 40 [843,] 33.72 48 [844,] 33.76 31 [845,] 33.80 30 [846,] 33.84 29 [847,] 33.88 35 [848,] 33.92 19 [849,] 33.96 25 [850,] 34.00 18 [851,] 34.04 24 [852,] 34.08 32 [853,] 34.12 35 [854,] 34.16 38 [855,] 34.20 17 [856,] 34.24 25 [857,] 34.28 28 [858,] 34.32 18 [859,] 34.36 23 [860,] 34.40 30 [861,] 34.44 21 [862,] 34.48 23 [863,] 34.52 38 [864,] 34.56 24 [865,] 34.60 37 [866,] 34.64 29 [867,] 34.68 32 [868,] 34.72 42 [869,] 34.76 32 [870,] 34.80 31 [871,] 34.84 34 [872,] 34.88 18 [873,] 34.92 37 [874,] 34.96 26 [875,] 35.00 30 [876,] 35.04 24 [877,] 35.08 41 [878,] 35.12 34 [879,] 35.16 30 [880,] 35.20 36 [881,] 35.24 35 [882,] 35.28 29 [883,] 35.32 38 [884,] 35.36 30 [885,] 35.40 26 [886,] 35.44 36 [887,] 35.48 34 [888,] 35.52 35 [889,] 35.56 31 [890,] 35.60 25 [891,] 35.64 18 [892,] 35.68 38 [893,] 35.72 36 [894,] 35.76 30 [895,] 35.80 29 [896,] 35.84 25 [897,] 35.88 21 [898,] 35.92 33 [899,] 35.96 40 [900,] 36.00 24 [901,] 36.04 36 [902,] 36.08 27 [903,] 36.12 27 [904,] 36.16 32 [905,] 36.20 39 [906,] 36.24 14 [907,] 36.28 26 [908,] 36.32 31 [909,] 36.36 23 [910,] 36.40 41 [911,] 36.44 33 [912,] 36.48 22 [913,] 36.52 27 [914,] 36.56 33 [915,] 36.60 25 [916,] 36.64 40 [917,] 36.68 34 [918,] 36.72 35 [919,] 36.76 15 [920,] 36.80 30 [921,] 36.84 24 [922,] 36.88 39 [923,] 36.92 32 [924,] 36.96 29 [925,] 37.00 32 [926,] 37.04 32 [927,] 37.08 36 [928,] 37.12 24 [929,] 37.16 33 [930,] 37.20 32 [931,] 37.24 26 [932,] 37.28 38 [933,] 37.32 19 [934,] 37.36 22 [935,] 37.40 24 [936,] 37.44 23 [937,] 37.48 29 [938,] 37.52 30 [939,] 37.56 32 [940,] 37.60 39 [941,] 37.64 31 [942,] 37.68 42 [943,] 37.72 20 [944,] 37.76 24 [945,] 37.80 22 [946,] 37.84 15 [947,] 37.88 32 [948,] 37.92 26 [949,] 37.96 30 [950,] 38.00 32 [951,] 38.04 41 [952,] 38.08 33 [953,] 38.12 24 [954,] 38.16 40 [955,] 38.20 22 [956,] 38.24 31 [957,] 38.28 25 [958,] 38.32 27 [959,] 38.36 28 [960,] 38.40 26 [961,] 38.44 29 [962,] 38.48 28 [963,] 38.52 33 [964,] 38.56 30 [965,] 38.60 22 [966,] 38.64 30 [967,] 38.68 34 [968,] 38.72 22 [969,] 38.76 37 [970,] 38.80 47 [971,] 38.84 23 [972,] 38.88 22 [973,] 38.92 21 [974,] 38.96 34 [975,] 39.00 30 [976,] 39.04 25 [977,] 39.08 31 [978,] 39.12 33 [979,] 39.16 29 [980,] 39.20 20 [981,] 39.24 27 [982,] 39.28 46 [983,] 39.32 29 [984,] 39.36 28 [985,] 39.40 38 [986,] 39.44 30 [987,] 39.48 36 [988,] 39.52 23 [989,] 39.56 25 [990,] 39.60 25 [991,] 39.64 44 [992,] 39.68 32 [993,] 39.72 37 [994,] 39.76 46 [995,] 39.80 24 [996,] 39.84 34 [997,] 39.88 29 [998,] 39.92 46 [999,] 39.96 44 [1000,] 40.00 35 $`3_TL (PMT)` [,1] [,2] [1,] 0.64 4 [2,] 1.28 8 [3,] 1.92 5 [4,] 2.56 7 [5,] 3.20 2 [6,] 3.84 3 [7,] 4.48 0 [8,] 5.12 4 [9,] 5.76 1 [10,] 6.40 4 [11,] 7.04 8 [12,] 7.68 10 [13,] 8.32 25 [14,] 8.96 6 [15,] 9.60 6 [16,] 10.24 2 [17,] 10.88 1 [18,] 11.52 4 [19,] 12.16 6 [20,] 12.80 0 [21,] 13.44 0 [22,] 14.08 4 [23,] 14.72 1 [24,] 15.36 12 [25,] 16.00 14 [26,] 16.64 3 [27,] 17.28 2 [28,] 17.92 5 [29,] 18.56 4 [30,] 19.20 3 [31,] 19.84 6 [32,] 20.48 5 [33,] 21.12 6 [34,] 21.76 1 [35,] 22.40 4 [36,] 23.04 0 [37,] 23.68 3 [38,] 24.32 2 [39,] 24.96 0 [40,] 25.60 5 [41,] 26.24 2 [42,] 26.88 7 [43,] 27.52 0 [44,] 28.16 4 [45,] 28.80 3 [46,] 29.44 7 [47,] 30.08 6 [48,] 30.72 3 [49,] 31.36 10 [50,] 32.00 2 [51,] 32.64 0 [52,] 33.28 0 [53,] 33.92 0 [54,] 34.56 2 [55,] 35.20 6 [56,] 35.84 2 [57,] 36.48 1 [58,] 37.12 6 [59,] 37.76 2 [60,] 38.40 12 [61,] 39.04 3 [62,] 39.68 10 [63,] 40.32 3 [64,] 40.96 6 [65,] 41.60 2 [66,] 42.24 6 [67,] 42.88 4 [68,] 43.52 6 [69,] 44.16 12 [70,] 44.80 5 [71,] 45.44 5 [72,] 46.08 7 [73,] 46.72 1 [74,] 47.36 3 [75,] 48.00 9 [76,] 48.64 4 [77,] 49.28 2 [78,] 49.92 3 [79,] 50.56 4 [80,] 51.20 5 [81,] 51.84 10 [82,] 52.48 5 [83,] 53.12 15 [84,] 53.76 17 [85,] 54.40 9 [86,] 55.04 8 [87,] 55.68 12 [88,] 56.32 1 [89,] 56.96 8 [90,] 57.60 6 [91,] 58.24 11 [92,] 58.88 10 [93,] 59.52 4 [94,] 60.16 5 [95,] 60.80 6 [96,] 61.44 10 [97,] 62.08 13 [98,] 62.72 23 [99,] 63.36 18 [100,] 64.00 20 [101,] 64.64 20 [102,] 65.28 19 [103,] 65.92 15 [104,] 66.56 21 [105,] 67.20 17 [106,] 67.84 24 [107,] 68.48 28 [108,] 69.12 25 [109,] 69.76 15 [110,] 70.40 34 [111,] 71.04 47 [112,] 71.68 32 [113,] 72.32 33 [114,] 72.96 27 [115,] 73.60 31 [116,] 74.24 32 [117,] 74.88 33 [118,] 75.52 50 [119,] 76.16 38 [120,] 76.80 33 [121,] 77.44 42 [122,] 78.08 53 [123,] 78.72 60 [124,] 79.36 51 [125,] 80.00 62 [126,] 80.64 67 [127,] 81.28 64 [128,] 81.92 68 [129,] 82.56 74 [130,] 83.20 62 [131,] 83.84 66 [132,] 84.48 69 [133,] 85.12 103 [134,] 85.76 94 [135,] 86.40 93 [136,] 87.04 103 [137,] 87.68 108 [138,] 88.32 112 [139,] 88.96 96 [140,] 89.60 119 [141,] 90.24 137 [142,] 90.88 121 [143,] 91.52 132 [144,] 92.16 165 [145,] 92.80 138 [146,] 93.44 141 [147,] 94.08 146 [148,] 94.72 160 [149,] 95.36 134 [150,] 96.00 170 [151,] 96.64 157 [152,] 97.28 195 [153,] 97.92 173 [154,] 98.56 170 [155,] 99.20 207 [156,] 99.84 189 [157,] 100.48 209 [158,] 101.12 210 [159,] 101.76 188 [160,] 102.40 233 [161,] 103.04 216 [162,] 103.68 212 [163,] 104.32 251 [164,] 104.96 256 [165,] 105.60 173 [166,] 106.24 239 [167,] 106.88 204 [168,] 107.52 218 [169,] 108.16 199 [170,] 108.80 249 [171,] 109.44 199 [172,] 110.08 214 [173,] 110.72 204 [174,] 111.36 176 [175,] 112.00 182 [176,] 112.64 220 [177,] 113.28 167 [178,] 113.92 194 [179,] 114.56 174 [180,] 115.20 163 [181,] 115.84 158 [182,] 116.48 174 [183,] 117.12 126 [184,] 117.76 128 [185,] 118.40 135 [186,] 119.04 125 [187,] 119.68 105 [188,] 120.32 93 [189,] 120.96 110 [190,] 121.60 92 [191,] 122.24 85 [192,] 122.88 76 [193,] 123.52 92 [194,] 124.16 56 [195,] 124.80 75 [196,] 125.44 68 [197,] 126.08 52 [198,] 126.72 50 [199,] 127.36 62 [200,] 128.00 81 [201,] 128.64 66 [202,] 129.28 62 [203,] 129.92 53 [204,] 130.56 64 [205,] 131.20 56 [206,] 131.84 79 [207,] 132.48 56 [208,] 133.12 57 [209,] 133.76 62 [210,] 134.40 51 [211,] 135.04 57 [212,] 135.68 54 [213,] 136.32 72 [214,] 136.96 57 [215,] 137.60 74 [216,] 138.24 57 [217,] 138.88 65 [218,] 139.52 76 [219,] 140.16 62 [220,] 140.80 60 [221,] 141.44 63 [222,] 142.08 66 [223,] 142.72 64 [224,] 143.36 61 [225,] 144.00 54 [226,] 144.64 77 [227,] 145.28 75 [228,] 145.92 72 [229,] 146.56 61 [230,] 147.20 75 [231,] 147.84 83 [232,] 148.48 53 [233,] 149.12 64 [234,] 149.76 53 [235,] 150.40 54 [236,] 151.04 59 [237,] 151.68 61 [238,] 152.32 50 [239,] 152.96 67 [240,] 153.60 71 [241,] 154.24 62 [242,] 154.88 59 [243,] 155.52 75 [244,] 156.16 77 [245,] 156.80 68 [246,] 157.44 72 [247,] 158.08 52 [248,] 158.72 71 [249,] 159.36 56 [250,] 160.00 65 $`4_OSL (PMT)` [,1] [,2] [1,] 0.04 2538 [2,] 0.08 2233 [3,] 0.12 1860 [4,] 0.16 1680 [5,] 0.20 1376 [6,] 0.24 1314 [7,] 0.28 1195 [8,] 0.32 979 [9,] 0.36 915 [10,] 0.40 787 [11,] 0.44 582 [12,] 0.48 546 [13,] 0.52 572 [14,] 0.56 555 [15,] 0.60 444 [16,] 0.64 433 [17,] 0.68 373 [18,] 0.72 361 [19,] 0.76 283 [20,] 0.80 301 [21,] 0.84 238 [22,] 0.88 254 [23,] 0.92 241 [24,] 0.96 214 [25,] 1.00 243 [26,] 1.04 209 [27,] 1.08 175 [28,] 1.12 174 [29,] 1.16 168 [30,] 1.20 151 [31,] 1.24 146 [32,] 1.28 172 [33,] 1.32 152 [34,] 1.36 126 [35,] 1.40 113 [36,] 1.44 126 [37,] 1.48 120 [38,] 1.52 127 [39,] 1.56 108 [40,] 1.60 114 [41,] 1.64 131 [42,] 1.68 109 [43,] 1.72 120 [44,] 1.76 100 [45,] 1.80 97 [46,] 1.84 102 [47,] 1.88 106 [48,] 1.92 75 [49,] 1.96 117 [50,] 2.00 106 [51,] 2.04 93 [52,] 2.08 104 [53,] 2.12 91 [54,] 2.16 113 [55,] 2.20 95 [56,] 2.24 90 [57,] 2.28 96 [58,] 2.32 70 [59,] 2.36 127 [60,] 2.40 85 [61,] 2.44 100 [62,] 2.48 72 [63,] 2.52 80 [64,] 2.56 72 [65,] 2.60 83 [66,] 2.64 83 [67,] 2.68 72 [68,] 2.72 69 [69,] 2.76 68 [70,] 2.80 77 [71,] 2.84 79 [72,] 2.88 98 [73,] 2.92 93 [74,] 2.96 87 [75,] 3.00 89 [76,] 3.04 42 [77,] 3.08 51 [78,] 3.12 78 [79,] 3.16 93 [80,] 3.20 78 [81,] 3.24 78 [82,] 3.28 79 [83,] 3.32 60 [84,] 3.36 65 [85,] 3.40 83 [86,] 3.44 78 [87,] 3.48 71 [88,] 3.52 71 [89,] 3.56 74 [90,] 3.60 74 [91,] 3.64 76 [92,] 3.68 72 [93,] 3.72 77 [94,] 3.76 88 [95,] 3.80 80 [96,] 3.84 55 [97,] 3.88 55 [98,] 3.92 60 [99,] 3.96 73 [100,] 4.00 63 [101,] 4.04 70 [102,] 4.08 53 [103,] 4.12 62 [104,] 4.16 57 [105,] 4.20 81 [106,] 4.24 53 [107,] 4.28 40 [108,] 4.32 75 [109,] 4.36 65 [110,] 4.40 64 [111,] 4.44 77 [112,] 4.48 61 [113,] 4.52 69 [114,] 4.56 63 [115,] 4.60 59 [116,] 4.64 56 [117,] 4.68 62 [118,] 4.72 70 [119,] 4.76 79 [120,] 4.80 83 [121,] 4.84 68 [122,] 4.88 71 [123,] 4.92 59 [124,] 4.96 62 [125,] 5.00 71 [126,] 5.04 45 [127,] 5.08 88 [128,] 5.12 70 [129,] 5.16 54 [130,] 5.20 72 [131,] 5.24 57 [132,] 5.28 59 [133,] 5.32 64 [134,] 5.36 62 [135,] 5.40 68 [136,] 5.44 67 [137,] 5.48 60 [138,] 5.52 57 [139,] 5.56 82 [140,] 5.60 60 [141,] 5.64 53 [142,] 5.68 75 [143,] 5.72 53 [144,] 5.76 66 [145,] 5.80 61 [146,] 5.84 65 [147,] 5.88 51 [148,] 5.92 68 [149,] 5.96 54 [150,] 6.00 64 [151,] 6.04 42 [152,] 6.08 54 [153,] 6.12 62 [154,] 6.16 41 [155,] 6.20 41 [156,] 6.24 81 [157,] 6.28 48 [158,] 6.32 67 [159,] 6.36 61 [160,] 6.40 82 [161,] 6.44 58 [162,] 6.48 48 [163,] 6.52 69 [164,] 6.56 51 [165,] 6.60 56 [166,] 6.64 43 [167,] 6.68 55 [168,] 6.72 62 [169,] 6.76 41 [170,] 6.80 61 [171,] 6.84 59 [172,] 6.88 76 [173,] 6.92 65 [174,] 6.96 67 [175,] 7.00 68 [176,] 7.04 36 [177,] 7.08 45 [178,] 7.12 47 [179,] 7.16 52 [180,] 7.20 53 [181,] 7.24 52 [182,] 7.28 70 [183,] 7.32 57 [184,] 7.36 33 [185,] 7.40 38 [186,] 7.44 62 [187,] 7.48 64 [188,] 7.52 56 [189,] 7.56 49 [190,] 7.60 51 [191,] 7.64 49 [192,] 7.68 64 [193,] 7.72 47 [194,] 7.76 61 [195,] 7.80 69 [196,] 7.84 55 [197,] 7.88 63 [198,] 7.92 50 [199,] 7.96 45 [200,] 8.00 46 [201,] 8.04 44 [202,] 8.08 54 [203,] 8.12 54 [204,] 8.16 38 [205,] 8.20 55 [206,] 8.24 64 [207,] 8.28 45 [208,] 8.32 47 [209,] 8.36 45 [210,] 8.40 42 [211,] 8.44 56 [212,] 8.48 64 [213,] 8.52 47 [214,] 8.56 46 [215,] 8.60 73 [216,] 8.64 50 [217,] 8.68 50 [218,] 8.72 58 [219,] 8.76 42 [220,] 8.80 56 [221,] 8.84 37 [222,] 8.88 52 [223,] 8.92 50 [224,] 8.96 52 [225,] 9.00 58 [226,] 9.04 49 [227,] 9.08 58 [228,] 9.12 36 [229,] 9.16 56 [230,] 9.20 44 [231,] 9.24 51 [232,] 9.28 40 [233,] 9.32 59 [234,] 9.36 51 [235,] 9.40 43 [236,] 9.44 49 [237,] 9.48 62 [238,] 9.52 57 [239,] 9.56 53 [240,] 9.60 57 [241,] 9.64 51 [242,] 9.68 48 [243,] 9.72 46 [244,] 9.76 53 [245,] 9.80 56 [246,] 9.84 61 [247,] 9.88 71 [248,] 9.92 39 [249,] 9.96 52 [250,] 10.00 44 [251,] 10.04 45 [252,] 10.08 49 [253,] 10.12 56 [254,] 10.16 49 [255,] 10.20 58 [256,] 10.24 49 [257,] 10.28 58 [258,] 10.32 56 [259,] 10.36 147 [260,] 10.40 64 [261,] 10.44 57 [262,] 10.48 43 [263,] 10.52 51 [264,] 10.56 47 [265,] 10.60 39 [266,] 10.64 47 [267,] 10.68 45 [268,] 10.72 32 [269,] 10.76 54 [270,] 10.80 49 [271,] 10.84 42 [272,] 10.88 53 [273,] 10.92 52 [274,] 10.96 41 [275,] 11.00 54 [276,] 11.04 37 [277,] 11.08 44 [278,] 11.12 50 [279,] 11.16 47 [280,] 11.20 65 [281,] 11.24 51 [282,] 11.28 38 [283,] 11.32 65 [284,] 11.36 60 [285,] 11.40 46 [286,] 11.44 42 [287,] 11.48 51 [288,] 11.52 60 [289,] 11.56 43 [290,] 11.60 45 [291,] 11.64 44 [292,] 11.68 45 [293,] 11.72 48 [294,] 11.76 60 [295,] 11.80 29 [296,] 11.84 53 [297,] 11.88 47 [298,] 11.92 44 [299,] 11.96 27 [300,] 12.00 51 [301,] 12.04 48 [302,] 12.08 33 [303,] 12.12 39 [304,] 12.16 31 [305,] 12.20 35 [306,] 12.24 49 [307,] 12.28 42 [308,] 12.32 64 [309,] 12.36 45 [310,] 12.40 34 [311,] 12.44 41 [312,] 12.48 34 [313,] 12.52 51 [314,] 12.56 54 [315,] 12.60 38 [316,] 12.64 49 [317,] 12.68 61 [318,] 12.72 35 [319,] 12.76 51 [320,] 12.80 36 [321,] 12.84 60 [322,] 12.88 43 [323,] 12.92 60 [324,] 12.96 41 [325,] 13.00 34 [326,] 13.04 47 [327,] 13.08 50 [328,] 13.12 53 [329,] 13.16 44 [330,] 13.20 51 [331,] 13.24 42 [332,] 13.28 40 [333,] 13.32 48 [334,] 13.36 46 [335,] 13.40 31 [336,] 13.44 39 [337,] 13.48 48 [338,] 13.52 50 [339,] 13.56 28 [340,] 13.60 35 [341,] 13.64 46 [342,] 13.68 52 [343,] 13.72 42 [344,] 13.76 51 [345,] 13.80 37 [346,] 13.84 49 [347,] 13.88 42 [348,] 13.92 53 [349,] 13.96 48 [350,] 14.00 50 [351,] 14.04 55 [352,] 14.08 43 [353,] 14.12 57 [354,] 14.16 54 [355,] 14.20 37 [356,] 14.24 47 [357,] 14.28 54 [358,] 14.32 43 [359,] 14.36 51 [360,] 14.40 49 [361,] 14.44 51 [362,] 14.48 48 [363,] 14.52 52 [364,] 14.56 49 [365,] 14.60 34 [366,] 14.64 34 [367,] 14.68 44 [368,] 14.72 36 [369,] 14.76 36 [370,] 14.80 54 [371,] 14.84 39 [372,] 14.88 65 [373,] 14.92 55 [374,] 14.96 47 [375,] 15.00 42 [376,] 15.04 33 [377,] 15.08 59 [378,] 15.12 43 [379,] 15.16 27 [380,] 15.20 40 [381,] 15.24 50 [382,] 15.28 53 [383,] 15.32 43 [384,] 15.36 39 [385,] 15.40 29 [386,] 15.44 46 [387,] 15.48 36 [388,] 15.52 28 [389,] 15.56 43 [390,] 15.60 50 [391,] 15.64 49 [392,] 15.68 46 [393,] 15.72 53 [394,] 15.76 48 [395,] 15.80 40 [396,] 15.84 37 [397,] 15.88 47 [398,] 15.92 39 [399,] 15.96 40 [400,] 16.00 38 [401,] 16.04 49 [402,] 16.08 39 [403,] 16.12 41 [404,] 16.16 44 [405,] 16.20 59 [406,] 16.24 38 [407,] 16.28 48 [408,] 16.32 42 [409,] 16.36 48 [410,] 16.40 35 [411,] 16.44 42 [412,] 16.48 41 [413,] 16.52 60 [414,] 16.56 22 [415,] 16.60 42 [416,] 16.64 55 [417,] 16.68 63 [418,] 16.72 45 [419,] 16.76 53 [420,] 16.80 46 [421,] 16.84 39 [422,] 16.88 36 [423,] 16.92 50 [424,] 16.96 48 [425,] 17.00 38 [426,] 17.04 44 [427,] 17.08 38 [428,] 17.12 35 [429,] 17.16 49 [430,] 17.20 36 [431,] 17.24 45 [432,] 17.28 37 [433,] 17.32 31 [434,] 17.36 48 [435,] 17.40 23 [436,] 17.44 57 [437,] 17.48 51 [438,] 17.52 40 [439,] 17.56 29 [440,] 17.60 41 [441,] 17.64 35 [442,] 17.68 78 [443,] 17.72 47 [444,] 17.76 43 [445,] 17.80 50 [446,] 17.84 52 [447,] 17.88 58 [448,] 17.92 44 [449,] 17.96 31 [450,] 18.00 52 [451,] 18.04 48 [452,] 18.08 46 [453,] 18.12 49 [454,] 18.16 41 [455,] 18.20 41 [456,] 18.24 34 [457,] 18.28 49 [458,] 18.32 31 [459,] 18.36 43 [460,] 18.40 41 [461,] 18.44 37 [462,] 18.48 44 [463,] 18.52 48 [464,] 18.56 47 [465,] 18.60 37 [466,] 18.64 42 [467,] 18.68 38 [468,] 18.72 30 [469,] 18.76 48 [470,] 18.80 43 [471,] 18.84 56 [472,] 18.88 49 [473,] 18.92 51 [474,] 18.96 41 [475,] 19.00 41 [476,] 19.04 40 [477,] 19.08 42 [478,] 19.12 44 [479,] 19.16 55 [480,] 19.20 52 [481,] 19.24 52 [482,] 19.28 38 [483,] 19.32 42 [484,] 19.36 34 [485,] 19.40 45 [486,] 19.44 36 [487,] 19.48 52 [488,] 19.52 37 [489,] 19.56 35 [490,] 19.60 23 [491,] 19.64 51 [492,] 19.68 44 [493,] 19.72 43 [494,] 19.76 33 [495,] 19.80 47 [496,] 19.84 39 [497,] 19.88 43 [498,] 19.92 53 [499,] 19.96 40 [500,] 20.00 55 [501,] 20.04 35 [502,] 20.08 34 [503,] 20.12 31 [504,] 20.16 35 [505,] 20.20 46 [506,] 20.24 37 [507,] 20.28 43 [508,] 20.32 44 [509,] 20.36 32 [510,] 20.40 66 [511,] 20.44 36 [512,] 20.48 39 [513,] 20.52 45 [514,] 20.56 45 [515,] 20.60 34 [516,] 20.64 26 [517,] 20.68 42 [518,] 20.72 24 [519,] 20.76 67 [520,] 20.80 50 [521,] 20.84 59 [522,] 20.88 35 [523,] 20.92 38 [524,] 20.96 45 [525,] 21.00 53 [526,] 21.04 42 [527,] 21.08 54 [528,] 21.12 42 [529,] 21.16 49 [530,] 21.20 39 [531,] 21.24 32 [532,] 21.28 45 [533,] 21.32 41 [534,] 21.36 36 [535,] 21.40 41 [536,] 21.44 34 [537,] 21.48 66 [538,] 21.52 39 [539,] 21.56 24 [540,] 21.60 42 [541,] 21.64 34 [542,] 21.68 22 [543,] 21.72 49 [544,] 21.76 50 [545,] 21.80 42 [546,] 21.84 54 [547,] 21.88 36 [548,] 21.92 31 [549,] 21.96 28 [550,] 22.00 32 [551,] 22.04 44 [552,] 22.08 47 [553,] 22.12 37 [554,] 22.16 46 [555,] 22.20 36 [556,] 22.24 57 [557,] 22.28 50 [558,] 22.32 44 [559,] 22.36 48 [560,] 22.40 37 [561,] 22.44 31 [562,] 22.48 43 [563,] 22.52 39 [564,] 22.56 49 [565,] 22.60 32 [566,] 22.64 34 [567,] 22.68 47 [568,] 22.72 42 [569,] 22.76 37 [570,] 22.80 39 [571,] 22.84 42 [572,] 22.88 36 [573,] 22.92 40 [574,] 22.96 26 [575,] 23.00 51 [576,] 23.04 39 [577,] 23.08 45 [578,] 23.12 53 [579,] 23.16 24 [580,] 23.20 59 [581,] 23.24 43 [582,] 23.28 39 [583,] 23.32 43 [584,] 23.36 30 [585,] 23.40 45 [586,] 23.44 43 [587,] 23.48 38 [588,] 23.52 44 [589,] 23.56 30 [590,] 23.60 41 [591,] 23.64 34 [592,] 23.68 44 [593,] 23.72 46 [594,] 23.76 46 [595,] 23.80 38 [596,] 23.84 39 [597,] 23.88 44 [598,] 23.92 36 [599,] 23.96 38 [600,] 24.00 48 [601,] 24.04 44 [602,] 24.08 51 [603,] 24.12 43 [604,] 24.16 41 [605,] 24.20 55 [606,] 24.24 37 [607,] 24.28 41 [608,] 24.32 37 [609,] 24.36 44 [610,] 24.40 60 [611,] 24.44 46 [612,] 24.48 45 [613,] 24.52 57 [614,] 24.56 35 [615,] 24.60 45 [616,] 24.64 33 [617,] 24.68 34 [618,] 24.72 24 [619,] 24.76 52 [620,] 24.80 40 [621,] 24.84 42 [622,] 24.88 42 [623,] 24.92 57 [624,] 24.96 44 [625,] 25.00 42 [626,] 25.04 36 [627,] 25.08 30 [628,] 25.12 44 [629,] 25.16 38 [630,] 25.20 44 [631,] 25.24 24 [632,] 25.28 42 [633,] 25.32 33 [634,] 25.36 40 [635,] 25.40 33 [636,] 25.44 33 [637,] 25.48 42 [638,] 25.52 36 [639,] 25.56 39 [640,] 25.60 40 [641,] 25.64 28 [642,] 25.68 30 [643,] 25.72 32 [644,] 25.76 46 [645,] 25.80 31 [646,] 25.84 56 [647,] 25.88 49 [648,] 25.92 26 [649,] 25.96 45 [650,] 26.00 39 [651,] 26.04 33 [652,] 26.08 40 [653,] 26.12 44 [654,] 26.16 36 [655,] 26.20 44 [656,] 26.24 43 [657,] 26.28 30 [658,] 26.32 38 [659,] 26.36 43 [660,] 26.40 49 [661,] 26.44 37 [662,] 26.48 49 [663,] 26.52 41 [664,] 26.56 29 [665,] 26.60 50 [666,] 26.64 30 [667,] 26.68 44 [668,] 26.72 60 [669,] 26.76 30 [670,] 26.80 41 [671,] 26.84 52 [672,] 26.88 47 [673,] 26.92 44 [674,] 26.96 41 [675,] 27.00 34 [676,] 27.04 28 [677,] 27.08 39 [678,] 27.12 31 [679,] 27.16 28 [680,] 27.20 38 [681,] 27.24 28 [682,] 27.28 30 [683,] 27.32 38 [684,] 27.36 32 [685,] 27.40 42 [686,] 27.44 38 [687,] 27.48 40 [688,] 27.52 37 [689,] 27.56 34 [690,] 27.60 44 [691,] 27.64 49 [692,] 27.68 31 [693,] 27.72 51 [694,] 27.76 31 [695,] 27.80 44 [696,] 27.84 35 [697,] 27.88 25 [698,] 27.92 36 [699,] 27.96 48 [700,] 28.00 41 [701,] 28.04 40 [702,] 28.08 39 [703,] 28.12 40 [704,] 28.16 33 [705,] 28.20 56 [706,] 28.24 23 [707,] 28.28 37 [708,] 28.32 39 [709,] 28.36 54 [710,] 28.40 38 [711,] 28.44 48 [712,] 28.48 42 [713,] 28.52 43 [714,] 28.56 30 [715,] 28.60 39 [716,] 28.64 41 [717,] 28.68 43 [718,] 28.72 29 [719,] 28.76 38 [720,] 28.80 31 [721,] 28.84 35 [722,] 28.88 33 [723,] 28.92 40 [724,] 28.96 56 [725,] 29.00 39 [726,] 29.04 36 [727,] 29.08 40 [728,] 29.12 47 [729,] 29.16 47 [730,] 29.20 30 [731,] 29.24 55 [732,] 29.28 37 [733,] 29.32 44 [734,] 29.36 41 [735,] 29.40 38 [736,] 29.44 54 [737,] 29.48 34 [738,] 29.52 49 [739,] 29.56 34 [740,] 29.60 44 [741,] 29.64 42 [742,] 29.68 32 [743,] 29.72 35 [744,] 29.76 39 [745,] 29.80 43 [746,] 29.84 43 [747,] 29.88 41 [748,] 29.92 47 [749,] 29.96 35 [750,] 30.00 34 [751,] 30.04 38 [752,] 30.08 32 [753,] 30.12 36 [754,] 30.16 32 [755,] 30.20 45 [756,] 30.24 25 [757,] 30.28 38 [758,] 30.32 23 [759,] 30.36 43 [760,] 30.40 34 [761,] 30.44 32 [762,] 30.48 42 [763,] 30.52 38 [764,] 30.56 31 [765,] 30.60 54 [766,] 30.64 46 [767,] 30.68 53 [768,] 30.72 35 [769,] 30.76 40 [770,] 30.80 36 [771,] 30.84 32 [772,] 30.88 50 [773,] 30.92 48 [774,] 30.96 42 [775,] 31.00 50 [776,] 31.04 26 [777,] 31.08 36 [778,] 31.12 27 [779,] 31.16 39 [780,] 31.20 37 [781,] 31.24 31 [782,] 31.28 37 [783,] 31.32 39 [784,] 31.36 27 [785,] 31.40 46 [786,] 31.44 46 [787,] 31.48 30 [788,] 31.52 39 [789,] 31.56 31 [790,] 31.60 32 [791,] 31.64 38 [792,] 31.68 54 [793,] 31.72 39 [794,] 31.76 51 [795,] 31.80 42 [796,] 31.84 44 [797,] 31.88 38 [798,] 31.92 35 [799,] 31.96 34 [800,] 32.00 48 [801,] 32.04 36 [802,] 32.08 44 [803,] 32.12 35 [804,] 32.16 41 [805,] 32.20 52 [806,] 32.24 35 [807,] 32.28 44 [808,] 32.32 38 [809,] 32.36 31 [810,] 32.40 38 [811,] 32.44 38 [812,] 32.48 39 [813,] 32.52 36 [814,] 32.56 22 [815,] 32.60 30 [816,] 32.64 33 [817,] 32.68 33 [818,] 32.72 24 [819,] 32.76 55 [820,] 32.80 39 [821,] 32.84 33 [822,] 32.88 43 [823,] 32.92 47 [824,] 32.96 53 [825,] 33.00 25 [826,] 33.04 40 [827,] 33.08 57 [828,] 33.12 34 [829,] 33.16 41 [830,] 33.20 34 [831,] 33.24 33 [832,] 33.28 30 [833,] 33.32 36 [834,] 33.36 54 [835,] 33.40 50 [836,] 33.44 57 [837,] 33.48 49 [838,] 33.52 29 [839,] 33.56 33 [840,] 33.60 22 [841,] 33.64 39 [842,] 33.68 38 [843,] 33.72 29 [844,] 33.76 44 [845,] 33.80 39 [846,] 33.84 36 [847,] 33.88 29 [848,] 33.92 43 [849,] 33.96 39 [850,] 34.00 35 [851,] 34.04 45 [852,] 34.08 28 [853,] 34.12 38 [854,] 34.16 50 [855,] 34.20 32 [856,] 34.24 41 [857,] 34.28 37 [858,] 34.32 31 [859,] 34.36 25 [860,] 34.40 50 [861,] 34.44 30 [862,] 34.48 44 [863,] 34.52 36 [864,] 34.56 34 [865,] 34.60 48 [866,] 34.64 41 [867,] 34.68 29 [868,] 34.72 31 [869,] 34.76 43 [870,] 34.80 45 [871,] 34.84 42 [872,] 34.88 35 [873,] 34.92 43 [874,] 34.96 39 [875,] 35.00 48 [876,] 35.04 45 [877,] 35.08 50 [878,] 35.12 37 [879,] 35.16 48 [880,] 35.20 37 [881,] 35.24 38 [882,] 35.28 37 [883,] 35.32 30 [884,] 35.36 22 [885,] 35.40 30 [886,] 35.44 45 [887,] 35.48 38 [888,] 35.52 33 [889,] 35.56 39 [890,] 35.60 38 [891,] 35.64 25 [892,] 35.68 29 [893,] 35.72 37 [894,] 35.76 48 [895,] 35.80 29 [896,] 35.84 37 [897,] 35.88 32 [898,] 35.92 38 [899,] 35.96 53 [900,] 36.00 43 [901,] 36.04 42 [902,] 36.08 33 [903,] 36.12 39 [904,] 36.16 33 [905,] 36.20 40 [906,] 36.24 37 [907,] 36.28 44 [908,] 36.32 21 [909,] 36.36 40 [910,] 36.40 47 [911,] 36.44 34 [912,] 36.48 36 [913,] 36.52 34 [914,] 36.56 38 [915,] 36.60 44 [916,] 36.64 36 [917,] 36.68 38 [918,] 36.72 25 [919,] 36.76 41 [920,] 36.80 36 [921,] 36.84 31 [922,] 36.88 36 [923,] 36.92 37 [924,] 36.96 42 [925,] 37.00 48 [926,] 37.04 43 [927,] 37.08 34 [928,] 37.12 31 [929,] 37.16 30 [930,] 37.20 37 [931,] 37.24 30 [932,] 37.28 27 [933,] 37.32 46 [934,] 37.36 34 [935,] 37.40 27 [936,] 37.44 30 [937,] 37.48 45 [938,] 37.52 29 [939,] 37.56 34 [940,] 37.60 48 [941,] 37.64 43 [942,] 37.68 48 [943,] 37.72 32 [944,] 37.76 49 [945,] 37.80 40 [946,] 37.84 41 [947,] 37.88 39 [948,] 37.92 24 [949,] 37.96 40 [950,] 38.00 51 [951,] 38.04 34 [952,] 38.08 36 [953,] 38.12 32 [954,] 38.16 34 [955,] 38.20 40 [956,] 38.24 42 [957,] 38.28 34 [958,] 38.32 46 [959,] 38.36 30 [960,] 38.40 38 [961,] 38.44 31 [962,] 38.48 29 [963,] 38.52 51 [964,] 38.56 44 [965,] 38.60 26 [966,] 38.64 32 [967,] 38.68 28 [968,] 38.72 35 [969,] 38.76 33 [970,] 38.80 32 [971,] 38.84 35 [972,] 38.88 48 [973,] 38.92 41 [974,] 38.96 34 [975,] 39.00 34 [976,] 39.04 32 [977,] 39.08 41 [978,] 39.12 41 [979,] 39.16 27 [980,] 39.20 38 [981,] 39.24 37 [982,] 39.28 52 [983,] 39.32 26 [984,] 39.36 38 [985,] 39.40 45 [986,] 39.44 44 [987,] 39.48 36 [988,] 39.52 36 [989,] 39.56 35 [990,] 39.60 34 [991,] 39.64 26 [992,] 39.68 28 [993,] 39.72 40 [994,] 39.76 37 [995,] 39.80 37 [996,] 39.84 50 [997,] 39.88 28 [998,] 39.92 41 [999,] 39.96 31 [1000,] 40.00 26 $`5_TL (PMT)` [,1] [,2] [1,] 0.884 2 [2,] 1.768 2 [3,] 2.652 11 [4,] 3.536 13 [5,] 4.420 1 [6,] 5.304 5 [7,] 6.188 5 [8,] 7.072 11 [9,] 7.956 15 [10,] 8.840 4 [11,] 9.724 18 [12,] 10.608 13 [13,] 11.492 5 [14,] 12.376 1 [15,] 13.260 19 [16,] 14.144 4 [17,] 15.028 6 [18,] 15.912 5 [19,] 16.796 3 [20,] 17.680 2 [21,] 18.564 6 [22,] 19.448 16 [23,] 20.332 15 [24,] 21.216 12 [25,] 22.100 3 [26,] 22.984 4 [27,] 23.868 6 [28,] 24.752 2 [29,] 25.636 6 [30,] 26.520 2 [31,] 27.404 2 [32,] 28.288 9 [33,] 29.172 2 [34,] 30.056 1 [35,] 30.940 8 [36,] 31.824 10 [37,] 32.708 8 [38,] 33.592 3 [39,] 34.476 8 [40,] 35.360 5 [41,] 36.244 4 [42,] 37.128 11 [43,] 38.012 3 [44,] 38.896 0 [45,] 39.780 3 [46,] 40.664 0 [47,] 41.548 9 [48,] 42.432 3 [49,] 43.316 2 [50,] 44.200 1 [51,] 45.084 3 [52,] 45.968 5 [53,] 46.852 5 [54,] 47.736 8 [55,] 48.620 9 [56,] 49.504 2 [57,] 50.388 8 [58,] 51.272 4 [59,] 52.156 4 [60,] 53.040 13 [61,] 53.924 12 [62,] 54.808 3 [63,] 55.692 7 [64,] 56.576 10 [65,] 57.460 7 [66,] 58.344 7 [67,] 59.228 6 [68,] 60.112 8 [69,] 60.996 11 [70,] 61.880 17 [71,] 62.764 17 [72,] 63.648 15 [73,] 64.532 11 [74,] 65.416 22 [75,] 66.300 18 [76,] 67.184 26 [77,] 68.068 16 [78,] 68.952 22 [79,] 69.836 37 [80,] 70.720 25 [81,] 71.604 29 [82,] 72.488 27 [83,] 73.372 20 [84,] 74.256 23 [85,] 75.140 58 [86,] 76.024 26 [87,] 76.908 48 [88,] 77.792 41 [89,] 78.676 45 [90,] 79.560 41 [91,] 80.444 47 [92,] 81.328 54 [93,] 82.212 67 [94,] 83.096 78 [95,] 83.980 52 [96,] 84.864 65 [97,] 85.748 72 [98,] 86.632 88 [99,] 87.516 66 [100,] 88.400 68 [101,] 89.284 82 [102,] 90.168 97 [103,] 91.052 109 [104,] 91.936 106 [105,] 92.820 100 [106,] 93.704 136 [107,] 94.588 132 [108,] 95.472 160 [109,] 96.356 127 [110,] 97.240 146 [111,] 98.124 153 [112,] 99.008 158 [113,] 99.892 177 [114,] 100.776 129 [115,] 101.660 202 [116,] 102.544 154 [117,] 103.428 188 [118,] 104.312 233 [119,] 105.196 202 [120,] 106.080 182 [121,] 106.964 217 [122,] 107.848 197 [123,] 108.732 171 [124,] 109.616 215 [125,] 110.500 214 [126,] 111.384 208 [127,] 112.268 176 [128,] 113.152 169 [129,] 114.036 189 [130,] 114.920 182 [131,] 115.804 169 [132,] 116.688 170 [133,] 117.572 180 [134,] 118.456 144 [135,] 119.340 136 [136,] 120.224 127 [137,] 121.108 149 [138,] 121.992 103 [139,] 122.876 112 [140,] 123.760 126 [141,] 124.644 124 [142,] 125.528 112 [143,] 126.412 115 [144,] 127.296 95 [145,] 128.180 104 [146,] 129.064 135 [147,] 129.948 128 [148,] 130.832 114 [149,] 131.716 117 [150,] 132.600 115 [151,] 133.484 121 [152,] 134.368 119 [153,] 135.252 105 [154,] 136.136 104 [155,] 137.020 122 [156,] 137.904 120 [157,] 138.788 138 [158,] 139.672 117 [159,] 140.556 128 [160,] 141.440 109 [161,] 142.324 125 [162,] 143.208 142 [163,] 144.092 125 [164,] 144.976 117 [165,] 145.860 146 [166,] 146.744 107 [167,] 147.628 127 [168,] 148.512 145 [169,] 149.396 110 [170,] 150.280 151 [171,] 151.164 144 [172,] 152.048 127 [173,] 152.932 120 [174,] 153.816 154 [175,] 154.700 144 [176,] 155.584 97 [177,] 156.468 140 [178,] 157.352 110 [179,] 158.236 126 [180,] 159.120 120 [181,] 160.004 151 [182,] 160.888 147 [183,] 161.772 120 [184,] 162.656 104 [185,] 163.540 145 [186,] 164.424 117 [187,] 165.308 111 [188,] 166.192 135 [189,] 167.076 152 [190,] 167.960 148 [191,] 168.844 136 [192,] 169.728 135 [193,] 170.612 88 [194,] 171.496 147 [195,] 172.380 146 [196,] 173.264 145 [197,] 174.148 120 [198,] 175.032 117 [199,] 175.916 135 [200,] 176.800 131 [201,] 177.684 123 [202,] 178.568 115 [203,] 179.452 110 [204,] 180.336 120 [205,] 181.220 112 [206,] 182.104 137 [207,] 182.988 138 [208,] 183.872 123 [209,] 184.756 125 [210,] 185.640 141 [211,] 186.524 130 [212,] 187.408 129 [213,] 188.292 113 [214,] 189.176 131 [215,] 190.060 135 [216,] 190.944 166 [217,] 191.828 137 [218,] 192.712 132 [219,] 193.596 148 [220,] 194.480 171 [221,] 195.364 128 [222,] 196.248 137 [223,] 197.132 180 [224,] 198.016 143 [225,] 198.900 158 [226,] 199.784 194 [227,] 200.668 162 [228,] 201.552 196 [229,] 202.436 161 [230,] 203.320 148 [231,] 204.204 192 [232,] 205.088 183 [233,] 205.972 156 [234,] 206.856 171 [235,] 207.740 190 [236,] 208.624 170 [237,] 209.508 185 [238,] 210.392 212 [239,] 211.276 174 [240,] 212.160 196 [241,] 213.044 183 [242,] 213.928 189 [243,] 214.812 174 [244,] 215.696 179 [245,] 216.580 189 [246,] 217.464 170 [247,] 218.348 174 [248,] 219.232 190 [249,] 220.116 181 [250,] 221.000 87 $`6_OSL (PMT)` [,1] [,2] [1,] 0.04 4129 [2,] 0.08 3462 [3,] 0.12 3093 [4,] 0.16 2619 [5,] 0.20 2237 [6,] 0.24 1971 [7,] 0.28 1670 [8,] 0.32 1528 [9,] 0.36 1319 [10,] 0.40 1155 [11,] 0.44 963 [12,] 0.48 907 [13,] 0.52 841 [14,] 0.56 726 [15,] 0.60 641 [16,] 0.64 544 [17,] 0.68 495 [18,] 0.72 409 [19,] 0.76 410 [20,] 0.80 409 [21,] 0.84 345 [22,] 0.88 284 [23,] 0.92 259 [24,] 0.96 256 [25,] 1.00 232 [26,] 1.04 252 [27,] 1.08 173 [28,] 1.12 170 [29,] 1.16 158 [30,] 1.20 169 [31,] 1.24 137 [32,] 1.28 170 [33,] 1.32 127 [34,] 1.36 142 [35,] 1.40 81 [36,] 1.44 114 [37,] 1.48 117 [38,] 1.52 100 [39,] 1.56 101 [40,] 1.60 109 [41,] 1.64 97 [42,] 1.68 96 [43,] 1.72 110 [44,] 1.76 82 [45,] 1.80 114 [46,] 1.84 84 [47,] 1.88 96 [48,] 1.92 84 [49,] 1.96 93 [50,] 2.00 57 [51,] 2.04 85 [52,] 2.08 93 [53,] 2.12 69 [54,] 2.16 81 [55,] 2.20 74 [56,] 2.24 76 [57,] 2.28 72 [58,] 2.32 94 [59,] 2.36 61 [60,] 2.40 61 [61,] 2.44 55 [62,] 2.48 73 [63,] 2.52 73 [64,] 2.56 73 [65,] 2.60 54 [66,] 2.64 73 [67,] 2.68 48 [68,] 2.72 57 [69,] 2.76 63 [70,] 2.80 68 [71,] 2.84 41 [72,] 2.88 52 [73,] 2.92 55 [74,] 2.96 74 [75,] 3.00 61 [76,] 3.04 61 [77,] 3.08 71 [78,] 3.12 45 [79,] 3.16 57 [80,] 3.20 69 [81,] 3.24 66 [82,] 3.28 58 [83,] 3.32 64 [84,] 3.36 69 [85,] 3.40 40 [86,] 3.44 46 [87,] 3.48 58 [88,] 3.52 62 [89,] 3.56 42 [90,] 3.60 49 [91,] 3.64 60 [92,] 3.68 55 [93,] 3.72 63 [94,] 3.76 58 [95,] 3.80 66 [96,] 3.84 42 [97,] 3.88 64 [98,] 3.92 39 [99,] 3.96 45 [100,] 4.00 58 [101,] 4.04 65 [102,] 4.08 70 [103,] 4.12 47 [104,] 4.16 38 [105,] 4.20 39 [106,] 4.24 47 [107,] 4.28 54 [108,] 4.32 52 [109,] 4.36 51 [110,] 4.40 50 [111,] 4.44 53 [112,] 4.48 54 [113,] 4.52 41 [114,] 4.56 55 [115,] 4.60 58 [116,] 4.64 34 [117,] 4.68 54 [118,] 4.72 48 [119,] 4.76 41 [120,] 4.80 42 [121,] 4.84 57 [122,] 4.88 66 [123,] 4.92 43 [124,] 4.96 43 [125,] 5.00 58 [126,] 5.04 52 [127,] 5.08 48 [128,] 5.12 49 [129,] 5.16 55 [130,] 5.20 53 [131,] 5.24 53 [132,] 5.28 42 [133,] 5.32 49 [134,] 5.36 49 [135,] 5.40 50 [136,] 5.44 46 [137,] 5.48 50 [138,] 5.52 43 [139,] 5.56 59 [140,] 5.60 55 [141,] 5.64 55 [142,] 5.68 64 [143,] 5.72 43 [144,] 5.76 34 [145,] 5.80 56 [146,] 5.84 39 [147,] 5.88 55 [148,] 5.92 53 [149,] 5.96 51 [150,] 6.00 39 [151,] 6.04 52 [152,] 6.08 55 [153,] 6.12 38 [154,] 6.16 41 [155,] 6.20 46 [156,] 6.24 56 [157,] 6.28 58 [158,] 6.32 45 [159,] 6.36 55 [160,] 6.40 38 [161,] 6.44 44 [162,] 6.48 46 [163,] 6.52 51 [164,] 6.56 50 [165,] 6.60 42 [166,] 6.64 45 [167,] 6.68 39 [168,] 6.72 62 [169,] 6.76 37 [170,] 6.80 41 [171,] 6.84 44 [172,] 6.88 47 [173,] 6.92 62 [174,] 6.96 47 [175,] 7.00 42 [176,] 7.04 50 [177,] 7.08 56 [178,] 7.12 49 [179,] 7.16 42 [180,] 7.20 51 [181,] 7.24 51 [182,] 7.28 50 [183,] 7.32 50 [184,] 7.36 45 [185,] 7.40 38 [186,] 7.44 38 [187,] 7.48 26 [188,] 7.52 51 [189,] 7.56 31 [190,] 7.60 42 [191,] 7.64 31 [192,] 7.68 45 [193,] 7.72 68 [194,] 7.76 47 [195,] 7.80 39 [196,] 7.84 36 [197,] 7.88 31 [198,] 7.92 56 [199,] 7.96 53 [200,] 8.00 48 [201,] 8.04 56 [202,] 8.08 42 [203,] 8.12 43 [204,] 8.16 64 [205,] 8.20 41 [206,] 8.24 59 [207,] 8.28 43 [208,] 8.32 38 [209,] 8.36 54 [210,] 8.40 52 [211,] 8.44 52 [212,] 8.48 41 [213,] 8.52 48 [214,] 8.56 37 [215,] 8.60 53 [216,] 8.64 44 [217,] 8.68 54 [218,] 8.72 45 [219,] 8.76 61 [220,] 8.80 43 [221,] 8.84 50 [222,] 8.88 44 [223,] 8.92 35 [224,] 8.96 35 [225,] 9.00 49 [226,] 9.04 40 [227,] 9.08 41 [228,] 9.12 53 [229,] 9.16 34 [230,] 9.20 38 [231,] 9.24 47 [232,] 9.28 48 [233,] 9.32 55 [234,] 9.36 37 [235,] 9.40 37 [236,] 9.44 25 [237,] 9.48 53 [238,] 9.52 31 [239,] 9.56 37 [240,] 9.60 33 [241,] 9.64 45 [242,] 9.68 42 [243,] 9.72 39 [244,] 9.76 44 [245,] 9.80 43 [246,] 9.84 43 [247,] 9.88 41 [248,] 9.92 43 [249,] 9.96 43 [250,] 10.00 42 [251,] 10.04 26 [252,] 10.08 41 [253,] 10.12 52 [254,] 10.16 41 [255,] 10.20 47 [256,] 10.24 43 [257,] 10.28 46 [258,] 10.32 45 [259,] 10.36 51 [260,] 10.40 46 [261,] 10.44 47 [262,] 10.48 34 [263,] 10.52 34 [264,] 10.56 44 [265,] 10.60 50 [266,] 10.64 60 [267,] 10.68 43 [268,] 10.72 39 [269,] 10.76 47 [270,] 10.80 50 [271,] 10.84 36 [272,] 10.88 33 [273,] 10.92 35 [274,] 10.96 42 [275,] 11.00 35 [276,] 11.04 45 [277,] 11.08 32 [278,] 11.12 35 [279,] 11.16 39 [280,] 11.20 38 [281,] 11.24 30 [282,] 11.28 34 [283,] 11.32 45 [284,] 11.36 55 [285,] 11.40 58 [286,] 11.44 29 [287,] 11.48 22 [288,] 11.52 44 [289,] 11.56 36 [290,] 11.60 35 [291,] 11.64 33 [292,] 11.68 50 [293,] 11.72 49 [294,] 11.76 60 [295,] 11.80 38 [296,] 11.84 48 [297,] 11.88 34 [298,] 11.92 39 [299,] 11.96 48 [300,] 12.00 40 [301,] 12.04 31 [302,] 12.08 45 [303,] 12.12 50 [304,] 12.16 51 [305,] 12.20 36 [306,] 12.24 43 [307,] 12.28 54 [308,] 12.32 45 [309,] 12.36 40 [310,] 12.40 37 [311,] 12.44 46 [312,] 12.48 29 [313,] 12.52 42 [314,] 12.56 35 [315,] 12.60 47 [316,] 12.64 42 [317,] 12.68 35 [318,] 12.72 29 [319,] 12.76 39 [320,] 12.80 34 [321,] 12.84 39 [322,] 12.88 31 [323,] 12.92 34 [324,] 12.96 36 [325,] 13.00 43 [326,] 13.04 29 [327,] 13.08 57 [328,] 13.12 33 [329,] 13.16 46 [330,] 13.20 55 [331,] 13.24 57 [332,] 13.28 47 [333,] 13.32 35 [334,] 13.36 34 [335,] 13.40 42 [336,] 13.44 43 [337,] 13.48 35 [338,] 13.52 42 [339,] 13.56 52 [340,] 13.60 34 [341,] 13.64 31 [342,] 13.68 45 [343,] 13.72 29 [344,] 13.76 44 [345,] 13.80 38 [346,] 13.84 34 [347,] 13.88 44 [348,] 13.92 28 [349,] 13.96 37 [350,] 14.00 42 [351,] 14.04 44 [352,] 14.08 43 [353,] 14.12 40 [354,] 14.16 35 [355,] 14.20 48 [356,] 14.24 43 [357,] 14.28 43 [358,] 14.32 36 [359,] 14.36 37 [360,] 14.40 38 [361,] 14.44 42 [362,] 14.48 40 [363,] 14.52 51 [364,] 14.56 45 [365,] 14.60 39 [366,] 14.64 35 [367,] 14.68 36 [368,] 14.72 24 [369,] 14.76 35 [370,] 14.80 34 [371,] 14.84 34 [372,] 14.88 28 [373,] 14.92 42 [374,] 14.96 40 [375,] 15.00 27 [376,] 15.04 35 [377,] 15.08 39 [378,] 15.12 29 [379,] 15.16 50 [380,] 15.20 50 [381,] 15.24 41 [382,] 15.28 30 [383,] 15.32 40 [384,] 15.36 46 [385,] 15.40 42 [386,] 15.44 46 [387,] 15.48 40 [388,] 15.52 46 [389,] 15.56 38 [390,] 15.60 39 [391,] 15.64 33 [392,] 15.68 47 [393,] 15.72 42 [394,] 15.76 30 [395,] 15.80 38 [396,] 15.84 41 [397,] 15.88 35 [398,] 15.92 37 [399,] 15.96 42 [400,] 16.00 29 [401,] 16.04 34 [402,] 16.08 57 [403,] 16.12 32 [404,] 16.16 55 [405,] 16.20 38 [406,] 16.24 29 [407,] 16.28 44 [408,] 16.32 47 [409,] 16.36 31 [410,] 16.40 55 [411,] 16.44 36 [412,] 16.48 33 [413,] 16.52 51 [414,] 16.56 34 [415,] 16.60 28 [416,] 16.64 33 [417,] 16.68 39 [418,] 16.72 46 [419,] 16.76 49 [420,] 16.80 48 [421,] 16.84 34 [422,] 16.88 33 [423,] 16.92 25 [424,] 16.96 48 [425,] 17.00 27 [426,] 17.04 48 [427,] 17.08 36 [428,] 17.12 44 [429,] 17.16 34 [430,] 17.20 46 [431,] 17.24 36 [432,] 17.28 40 [433,] 17.32 37 [434,] 17.36 28 [435,] 17.40 42 [436,] 17.44 26 [437,] 17.48 29 [438,] 17.52 35 [439,] 17.56 54 [440,] 17.60 28 [441,] 17.64 47 [442,] 17.68 43 [443,] 17.72 46 [444,] 17.76 51 [445,] 17.80 56 [446,] 17.84 49 [447,] 17.88 49 [448,] 17.92 45 [449,] 17.96 31 [450,] 18.00 33 [451,] 18.04 27 [452,] 18.08 39 [453,] 18.12 31 [454,] 18.16 23 [455,] 18.20 29 [456,] 18.24 38 [457,] 18.28 38 [458,] 18.32 39 [459,] 18.36 35 [460,] 18.40 40 [461,] 18.44 43 [462,] 18.48 26 [463,] 18.52 42 [464,] 18.56 40 [465,] 18.60 49 [466,] 18.64 42 [467,] 18.68 42 [468,] 18.72 38 [469,] 18.76 34 [470,] 18.80 33 [471,] 18.84 35 [472,] 18.88 44 [473,] 18.92 45 [474,] 18.96 30 [475,] 19.00 45 [476,] 19.04 29 [477,] 19.08 39 [478,] 19.12 54 [479,] 19.16 28 [480,] 19.20 43 [481,] 19.24 52 [482,] 19.28 30 [483,] 19.32 44 [484,] 19.36 43 [485,] 19.40 47 [486,] 19.44 42 [487,] 19.48 41 [488,] 19.52 45 [489,] 19.56 45 [490,] 19.60 41 [491,] 19.64 43 [492,] 19.68 39 [493,] 19.72 23 [494,] 19.76 50 [495,] 19.80 34 [496,] 19.84 34 [497,] 19.88 47 [498,] 19.92 39 [499,] 19.96 26 [500,] 20.00 39 [501,] 20.04 52 [502,] 20.08 34 [503,] 20.12 42 [504,] 20.16 50 [505,] 20.20 38 [506,] 20.24 50 [507,] 20.28 38 [508,] 20.32 33 [509,] 20.36 36 [510,] 20.40 33 [511,] 20.44 20 [512,] 20.48 31 [513,] 20.52 42 [514,] 20.56 42 [515,] 20.60 54 [516,] 20.64 39 [517,] 20.68 35 [518,] 20.72 34 [519,] 20.76 30 [520,] 20.80 36 [521,] 20.84 33 [522,] 20.88 33 [523,] 20.92 46 [524,] 20.96 45 [525,] 21.00 37 [526,] 21.04 39 [527,] 21.08 51 [528,] 21.12 50 [529,] 21.16 36 [530,] 21.20 37 [531,] 21.24 32 [532,] 21.28 40 [533,] 21.32 43 [534,] 21.36 43 [535,] 21.40 27 [536,] 21.44 49 [537,] 21.48 38 [538,] 21.52 29 [539,] 21.56 38 [540,] 21.60 39 [541,] 21.64 30 [542,] 21.68 39 [543,] 21.72 35 [544,] 21.76 27 [545,] 21.80 26 [546,] 21.84 32 [547,] 21.88 37 [548,] 21.92 34 [549,] 21.96 35 [550,] 22.00 33 [551,] 22.04 32 [552,] 22.08 26 [553,] 22.12 30 [554,] 22.16 35 [555,] 22.20 37 [556,] 22.24 36 [557,] 22.28 34 [558,] 22.32 29 [559,] 22.36 46 [560,] 22.40 21 [561,] 22.44 40 [562,] 22.48 44 [563,] 22.52 35 [564,] 22.56 23 [565,] 22.60 34 [566,] 22.64 40 [567,] 22.68 42 [568,] 22.72 39 [569,] 22.76 46 [570,] 22.80 35 [571,] 22.84 19 [572,] 22.88 36 [573,] 22.92 31 [574,] 22.96 38 [575,] 23.00 32 [576,] 23.04 38 [577,] 23.08 37 [578,] 23.12 35 [579,] 23.16 31 [580,] 23.20 32 [581,] 23.24 31 [582,] 23.28 37 [583,] 23.32 40 [584,] 23.36 37 [585,] 23.40 36 [586,] 23.44 49 [587,] 23.48 35 [588,] 23.52 41 [589,] 23.56 26 [590,] 23.60 38 [591,] 23.64 45 [592,] 23.68 35 [593,] 23.72 35 [594,] 23.76 40 [595,] 23.80 38 [596,] 23.84 35 [597,] 23.88 30 [598,] 23.92 36 [599,] 23.96 23 [600,] 24.00 51 [601,] 24.04 39 [602,] 24.08 28 [603,] 24.12 31 [604,] 24.16 38 [605,] 24.20 38 [606,] 24.24 36 [607,] 24.28 47 [608,] 24.32 41 [609,] 24.36 27 [610,] 24.40 25 [611,] 24.44 29 [612,] 24.48 43 [613,] 24.52 45 [614,] 24.56 33 [615,] 24.60 41 [616,] 24.64 28 [617,] 24.68 31 [618,] 24.72 55 [619,] 24.76 31 [620,] 24.80 29 [621,] 24.84 40 [622,] 24.88 29 [623,] 24.92 31 [624,] 24.96 51 [625,] 25.00 35 [626,] 25.04 38 [627,] 25.08 34 [628,] 25.12 42 [629,] 25.16 41 [630,] 25.20 25 [631,] 25.24 30 [632,] 25.28 42 [633,] 25.32 21 [634,] 25.36 46 [635,] 25.40 45 [636,] 25.44 33 [637,] 25.48 38 [638,] 25.52 40 [639,] 25.56 47 [640,] 25.60 30 [641,] 25.64 31 [642,] 25.68 29 [643,] 25.72 29 [644,] 25.76 32 [645,] 25.80 47 [646,] 25.84 36 [647,] 25.88 28 [648,] 25.92 39 [649,] 25.96 47 [650,] 26.00 36 [651,] 26.04 25 [652,] 26.08 50 [653,] 26.12 36 [654,] 26.16 29 [655,] 26.20 45 [656,] 26.24 39 [657,] 26.28 46 [658,] 26.32 39 [659,] 26.36 37 [660,] 26.40 24 [661,] 26.44 35 [662,] 26.48 24 [663,] 26.52 35 [664,] 26.56 37 [665,] 26.60 38 [666,] 26.64 43 [667,] 26.68 38 [668,] 26.72 42 [669,] 26.76 37 [670,] 26.80 31 [671,] 26.84 36 [672,] 26.88 38 [673,] 26.92 42 [674,] 26.96 30 [675,] 27.00 49 [676,] 27.04 37 [677,] 27.08 46 [678,] 27.12 42 [679,] 27.16 32 [680,] 27.20 32 [681,] 27.24 36 [682,] 27.28 22 [683,] 27.32 45 [684,] 27.36 34 [685,] 27.40 42 [686,] 27.44 40 [687,] 27.48 40 [688,] 27.52 42 [689,] 27.56 29 [690,] 27.60 25 [691,] 27.64 47 [692,] 27.68 44 [693,] 27.72 34 [694,] 27.76 32 [695,] 27.80 22 [696,] 27.84 40 [697,] 27.88 32 [698,] 27.92 31 [699,] 27.96 31 [700,] 28.00 35 [701,] 28.04 51 [702,] 28.08 36 [703,] 28.12 46 [704,] 28.16 27 [705,] 28.20 27 [706,] 28.24 26 [707,] 28.28 42 [708,] 28.32 32 [709,] 28.36 40 [710,] 28.40 34 [711,] 28.44 33 [712,] 28.48 41 [713,] 28.52 49 [714,] 28.56 39 [715,] 28.60 38 [716,] 28.64 37 [717,] 28.68 37 [718,] 28.72 44 [719,] 28.76 21 [720,] 28.80 64 [721,] 28.84 37 [722,] 28.88 37 [723,] 28.92 25 [724,] 28.96 21 [725,] 29.00 33 [726,] 29.04 35 [727,] 29.08 26 [728,] 29.12 25 [729,] 29.16 38 [730,] 29.20 39 [731,] 29.24 42 [732,] 29.28 36 [733,] 29.32 26 [734,] 29.36 36 [735,] 29.40 21 [736,] 29.44 30 [737,] 29.48 37 [738,] 29.52 39 [739,] 29.56 49 [740,] 29.60 36 [741,] 29.64 44 [742,] 29.68 32 [743,] 29.72 23 [744,] 29.76 31 [745,] 29.80 28 [746,] 29.84 26 [747,] 29.88 38 [748,] 29.92 27 [749,] 29.96 47 [750,] 30.00 43 [751,] 30.04 39 [752,] 30.08 45 [753,] 30.12 43 [754,] 30.16 43 [755,] 30.20 37 [756,] 30.24 33 [757,] 30.28 23 [758,] 30.32 51 [759,] 30.36 20 [760,] 30.40 52 [761,] 30.44 30 [762,] 30.48 27 [763,] 30.52 32 [764,] 30.56 30 [765,] 30.60 35 [766,] 30.64 40 [767,] 30.68 27 [768,] 30.72 41 [769,] 30.76 29 [770,] 30.80 46 [771,] 30.84 23 [772,] 30.88 32 [773,] 30.92 27 [774,] 30.96 25 [775,] 31.00 29 [776,] 31.04 33 [777,] 31.08 47 [778,] 31.12 34 [779,] 31.16 40 [780,] 31.20 43 [781,] 31.24 33 [782,] 31.28 42 [783,] 31.32 38 [784,] 31.36 35 [785,] 31.40 39 [786,] 31.44 34 [787,] 31.48 47 [788,] 31.52 35 [789,] 31.56 50 [790,] 31.60 27 [791,] 31.64 33 [792,] 31.68 25 [793,] 31.72 34 [794,] 31.76 40 [795,] 31.80 35 [796,] 31.84 49 [797,] 31.88 37 [798,] 31.92 30 [799,] 31.96 21 [800,] 32.00 40 [801,] 32.04 38 [802,] 32.08 39 [803,] 32.12 31 [804,] 32.16 26 [805,] 32.20 33 [806,] 32.24 39 [807,] 32.28 36 [808,] 32.32 31 [809,] 32.36 24 [810,] 32.40 36 [811,] 32.44 39 [812,] 32.48 31 [813,] 32.52 30 [814,] 32.56 32 [815,] 32.60 19 [816,] 32.64 26 [817,] 32.68 38 [818,] 32.72 23 [819,] 32.76 30 [820,] 32.80 16 [821,] 32.84 31 [822,] 32.88 24 [823,] 32.92 39 [824,] 32.96 30 [825,] 33.00 26 [826,] 33.04 35 [827,] 33.08 34 [828,] 33.12 38 [829,] 33.16 49 [830,] 33.20 32 [831,] 33.24 27 [832,] 33.28 33 [833,] 33.32 23 [834,] 33.36 31 [835,] 33.40 37 [836,] 33.44 48 [837,] 33.48 26 [838,] 33.52 28 [839,] 33.56 27 [840,] 33.60 39 [841,] 33.64 28 [842,] 33.68 43 [843,] 33.72 31 [844,] 33.76 46 [845,] 33.80 36 [846,] 33.84 41 [847,] 33.88 38 [848,] 33.92 29 [849,] 33.96 41 [850,] 34.00 33 [851,] 34.04 28 [852,] 34.08 45 [853,] 34.12 41 [854,] 34.16 35 [855,] 34.20 27 [856,] 34.24 41 [857,] 34.28 48 [858,] 34.32 31 [859,] 34.36 28 [860,] 34.40 30 [861,] 34.44 30 [862,] 34.48 32 [863,] 34.52 26 [864,] 34.56 34 [865,] 34.60 39 [866,] 34.64 32 [867,] 34.68 21 [868,] 34.72 29 [869,] 34.76 31 [870,] 34.80 38 [871,] 34.84 35 [872,] 34.88 39 [873,] 34.92 28 [874,] 34.96 46 [875,] 35.00 48 [876,] 35.04 40 [877,] 35.08 30 [878,] 35.12 25 [879,] 35.16 34 [880,] 35.20 35 [881,] 35.24 32 [882,] 35.28 33 [883,] 35.32 43 [884,] 35.36 18 [885,] 35.40 51 [886,] 35.44 26 [887,] 35.48 38 [888,] 35.52 26 [889,] 35.56 32 [890,] 35.60 35 [891,] 35.64 35 [892,] 35.68 27 [893,] 35.72 26 [894,] 35.76 34 [895,] 35.80 34 [896,] 35.84 35 [897,] 35.88 29 [898,] 35.92 41 [899,] 35.96 41 [900,] 36.00 44 [901,] 36.04 28 [902,] 36.08 31 [903,] 36.12 15 [904,] 36.16 37 [905,] 36.20 23 [906,] 36.24 30 [907,] 36.28 32 [908,] 36.32 32 [909,] 36.36 29 [910,] 36.40 38 [911,] 36.44 30 [912,] 36.48 31 [913,] 36.52 38 [914,] 36.56 32 [915,] 36.60 31 [916,] 36.64 27 [917,] 36.68 25 [918,] 36.72 48 [919,] 36.76 42 [920,] 36.80 36 [921,] 36.84 35 [922,] 36.88 44 [923,] 36.92 46 [924,] 36.96 34 [925,] 37.00 18 [926,] 37.04 33 [927,] 37.08 42 [928,] 37.12 39 [929,] 37.16 44 [930,] 37.20 29 [931,] 37.24 29 [932,] 37.28 34 [933,] 37.32 23 [934,] 37.36 20 [935,] 37.40 30 [936,] 37.44 30 [937,] 37.48 32 [938,] 37.52 23 [939,] 37.56 26 [940,] 37.60 32 [941,] 37.64 35 [942,] 37.68 31 [943,] 37.72 27 [944,] 37.76 32 [945,] 37.80 32 [946,] 37.84 32 [947,] 37.88 29 [948,] 37.92 45 [949,] 37.96 30 [950,] 38.00 34 [951,] 38.04 28 [952,] 38.08 32 [953,] 38.12 30 [954,] 38.16 37 [955,] 38.20 36 [956,] 38.24 37 [957,] 38.28 27 [958,] 38.32 29 [959,] 38.36 37 [960,] 38.40 40 [961,] 38.44 45 [962,] 38.48 25 [963,] 38.52 40 [964,] 38.56 39 [965,] 38.60 34 [966,] 38.64 31 [967,] 38.68 33 [968,] 38.72 47 [969,] 38.76 29 [970,] 38.80 38 [971,] 38.84 34 [972,] 38.88 45 [973,] 38.92 28 [974,] 38.96 46 [975,] 39.00 38 [976,] 39.04 37 [977,] 39.08 30 [978,] 39.12 32 [979,] 39.16 31 [980,] 39.20 37 [981,] 39.24 26 [982,] 39.28 29 [983,] 39.32 33 [984,] 39.36 28 [985,] 39.40 35 [986,] 39.44 37 [987,] 39.48 36 [988,] 39.52 24 [989,] 39.56 33 [990,] 39.60 31 [991,] 39.64 30 [992,] 39.68 24 [993,] 39.72 34 [994,] 39.76 38 [995,] 39.80 31 [996,] 39.84 26 [997,] 39.88 39 [998,] 39.92 28 [999,] 39.96 34 [1000,] 40.00 21 $`7_TL (PMT)` [,1] [,2] [1,] 0.64 5 [2,] 1.28 8 [3,] 1.92 0 [4,] 2.56 7 [5,] 3.20 1 [6,] 3.84 1 [7,] 4.48 0 [8,] 5.12 3 [9,] 5.76 8 [10,] 6.40 5 [11,] 7.04 7 [12,] 7.68 3 [13,] 8.32 6 [14,] 8.96 1 [15,] 9.60 18 [16,] 10.24 2 [17,] 10.88 0 [18,] 11.52 3 [19,] 12.16 0 [20,] 12.80 4 [21,] 13.44 8 [22,] 14.08 1 [23,] 14.72 6 [24,] 15.36 4 [25,] 16.00 3 [26,] 16.64 1 [27,] 17.28 2 [28,] 17.92 2 [29,] 18.56 0 [30,] 19.20 2 [31,] 19.84 13 [32,] 20.48 0 [33,] 21.12 1 [34,] 21.76 5 [35,] 22.40 1 [36,] 23.04 0 [37,] 23.68 3 [38,] 24.32 4 [39,] 24.96 1 [40,] 25.60 5 [41,] 26.24 1 [42,] 26.88 3 [43,] 27.52 6 [44,] 28.16 14 [45,] 28.80 7 [46,] 29.44 3 [47,] 30.08 8 [48,] 30.72 2 [49,] 31.36 5 [50,] 32.00 5 [51,] 32.64 3 [52,] 33.28 3 [53,] 33.92 10 [54,] 34.56 2 [55,] 35.20 6 [56,] 35.84 5 [57,] 36.48 6 [58,] 37.12 3 [59,] 37.76 6 [60,] 38.40 6 [61,] 39.04 1 [62,] 39.68 7 [63,] 40.32 4 [64,] 40.96 5 [65,] 41.60 1 [66,] 42.24 3 [67,] 42.88 5 [68,] 43.52 1 [69,] 44.16 6 [70,] 44.80 10 [71,] 45.44 4 [72,] 46.08 16 [73,] 46.72 6 [74,] 47.36 6 [75,] 48.00 10 [76,] 48.64 9 [77,] 49.28 4 [78,] 49.92 6 [79,] 50.56 8 [80,] 51.20 7 [81,] 51.84 3 [82,] 52.48 7 [83,] 53.12 5 [84,] 53.76 8 [85,] 54.40 12 [86,] 55.04 5 [87,] 55.68 13 [88,] 56.32 5 [89,] 56.96 15 [90,] 57.60 5 [91,] 58.24 11 [92,] 58.88 17 [93,] 59.52 21 [94,] 60.16 15 [95,] 60.80 9 [96,] 61.44 17 [97,] 62.08 5 [98,] 62.72 25 [99,] 63.36 6 [100,] 64.00 12 [101,] 64.64 10 [102,] 65.28 28 [103,] 65.92 11 [104,] 66.56 18 [105,] 67.20 31 [106,] 67.84 24 [107,] 68.48 19 [108,] 69.12 20 [109,] 69.76 36 [110,] 70.40 23 [111,] 71.04 32 [112,] 71.68 33 [113,] 72.32 25 [114,] 72.96 33 [115,] 73.60 31 [116,] 74.24 35 [117,] 74.88 48 [118,] 75.52 40 [119,] 76.16 50 [120,] 76.80 44 [121,] 77.44 47 [122,] 78.08 58 [123,] 78.72 63 [124,] 79.36 68 [125,] 80.00 59 [126,] 80.64 56 [127,] 81.28 81 [128,] 81.92 91 [129,] 82.56 81 [130,] 83.20 97 [131,] 83.84 88 [132,] 84.48 103 [133,] 85.12 92 [134,] 85.76 101 [135,] 86.40 117 [136,] 87.04 127 [137,] 87.68 110 [138,] 88.32 134 [139,] 88.96 113 [140,] 89.60 144 [141,] 90.24 156 [142,] 90.88 152 [143,] 91.52 153 [144,] 92.16 159 [145,] 92.80 160 [146,] 93.44 164 [147,] 94.08 187 [148,] 94.72 168 [149,] 95.36 219 [150,] 96.00 207 [151,] 96.64 170 [152,] 97.28 206 [153,] 97.92 217 [154,] 98.56 247 [155,] 99.20 199 [156,] 99.84 234 [157,] 100.48 222 [158,] 101.12 231 [159,] 101.76 244 [160,] 102.40 280 [161,] 103.04 226 [162,] 103.68 247 [163,] 104.32 253 [164,] 104.96 296 [165,] 105.60 239 [166,] 106.24 289 [167,] 106.88 233 [168,] 107.52 274 [169,] 108.16 277 [170,] 108.80 230 [171,] 109.44 230 [172,] 110.08 279 [173,] 110.72 245 [174,] 111.36 231 [175,] 112.00 228 [176,] 112.64 232 [177,] 113.28 194 [178,] 113.92 222 [179,] 114.56 209 [180,] 115.20 178 [181,] 115.84 188 [182,] 116.48 167 [183,] 117.12 163 [184,] 117.76 148 [185,] 118.40 121 [186,] 119.04 126 [187,] 119.68 102 [188,] 120.32 105 [189,] 120.96 112 [190,] 121.60 125 [191,] 122.24 94 [192,] 122.88 115 [193,] 123.52 87 [194,] 124.16 77 [195,] 124.80 75 [196,] 125.44 93 [197,] 126.08 92 [198,] 126.72 73 [199,] 127.36 77 [200,] 128.00 81 [201,] 128.64 84 [202,] 129.28 63 [203,] 129.92 55 [204,] 130.56 67 [205,] 131.20 78 [206,] 131.84 65 [207,] 132.48 60 [208,] 133.12 78 [209,] 133.76 66 [210,] 134.40 62 [211,] 135.04 69 [212,] 135.68 65 [213,] 136.32 75 [214,] 136.96 56 [215,] 137.60 70 [216,] 138.24 65 [217,] 138.88 66 [218,] 139.52 81 [219,] 140.16 78 [220,] 140.80 86 [221,] 141.44 64 [222,] 142.08 49 [223,] 142.72 59 [224,] 143.36 75 [225,] 144.00 79 [226,] 144.64 79 [227,] 145.28 88 [228,] 145.92 73 [229,] 146.56 64 [230,] 147.20 68 [231,] 147.84 58 [232,] 148.48 80 [233,] 149.12 72 [234,] 149.76 59 [235,] 150.40 65 [236,] 151.04 59 [237,] 151.68 56 [238,] 152.32 56 [239,] 152.96 68 [240,] 153.60 48 [241,] 154.24 76 [242,] 154.88 77 [243,] 155.52 94 [244,] 156.16 50 [245,] 156.80 47 [246,] 157.44 70 [247,] 158.08 58 [248,] 158.72 83 [249,] 159.36 41 [250,] 160.00 58 $`8_OSL (PMT)` [,1] [,2] [1,] 0.04 2726 [2,] 0.08 2251 [3,] 0.12 1972 [4,] 0.16 1678 [5,] 0.20 1554 [6,] 0.24 1359 [7,] 0.28 1232 [8,] 0.32 1053 [9,] 0.36 921 [10,] 0.40 778 [11,] 0.44 680 [12,] 0.48 604 [13,] 0.52 505 [14,] 0.56 559 [15,] 0.60 474 [16,] 0.64 420 [17,] 0.68 414 [18,] 0.72 321 [19,] 0.76 329 [20,] 0.80 332 [21,] 0.84 249 [22,] 0.88 254 [23,] 0.92 249 [24,] 0.96 205 [25,] 1.00 214 [26,] 1.04 190 [27,] 1.08 193 [28,] 1.12 175 [29,] 1.16 153 [30,] 1.20 154 [31,] 1.24 166 [32,] 1.28 158 [33,] 1.32 146 [34,] 1.36 129 [35,] 1.40 136 [36,] 1.44 101 [37,] 1.48 122 [38,] 1.52 96 [39,] 1.56 125 [40,] 1.60 117 [41,] 1.64 97 [42,] 1.68 103 [43,] 1.72 130 [44,] 1.76 87 [45,] 1.80 104 [46,] 1.84 116 [47,] 1.88 133 [48,] 1.92 122 [49,] 1.96 92 [50,] 2.00 86 [51,] 2.04 89 [52,] 2.08 89 [53,] 2.12 117 [54,] 2.16 90 [55,] 2.20 96 [56,] 2.24 88 [57,] 2.28 90 [58,] 2.32 78 [59,] 2.36 95 [60,] 2.40 93 [61,] 2.44 76 [62,] 2.48 73 [63,] 2.52 79 [64,] 2.56 86 [65,] 2.60 85 [66,] 2.64 59 [67,] 2.68 91 [68,] 2.72 84 [69,] 2.76 95 [70,] 2.80 83 [71,] 2.84 78 [72,] 2.88 82 [73,] 2.92 87 [74,] 2.96 76 [75,] 3.00 97 [76,] 3.04 83 [77,] 3.08 84 [78,] 3.12 74 [79,] 3.16 91 [80,] 3.20 79 [81,] 3.24 73 [82,] 3.28 76 [83,] 3.32 94 [84,] 3.36 74 [85,] 3.40 78 [86,] 3.44 76 [87,] 3.48 82 [88,] 3.52 75 [89,] 3.56 75 [90,] 3.60 77 [91,] 3.64 84 [92,] 3.68 80 [93,] 3.72 77 [94,] 3.76 67 [95,] 3.80 69 [96,] 3.84 85 [97,] 3.88 66 [98,] 3.92 68 [99,] 3.96 64 [100,] 4.00 73 [101,] 4.04 71 [102,] 4.08 61 [103,] 4.12 61 [104,] 4.16 87 [105,] 4.20 83 [106,] 4.24 94 [107,] 4.28 56 [108,] 4.32 77 [109,] 4.36 69 [110,] 4.40 80 [111,] 4.44 62 [112,] 4.48 79 [113,] 4.52 64 [114,] 4.56 77 [115,] 4.60 61 [116,] 4.64 60 [117,] 4.68 75 [118,] 4.72 71 [119,] 4.76 59 [120,] 4.80 67 [121,] 4.84 61 [122,] 4.88 63 [123,] 4.92 92 [124,] 4.96 61 [125,] 5.00 76 [126,] 5.04 65 [127,] 5.08 91 [128,] 5.12 90 [129,] 5.16 56 [130,] 5.20 59 [131,] 5.24 56 [132,] 5.28 63 [133,] 5.32 45 [134,] 5.36 61 [135,] 5.40 43 [136,] 5.44 67 [137,] 5.48 76 [138,] 5.52 62 [139,] 5.56 60 [140,] 5.60 80 [141,] 5.64 77 [142,] 5.68 78 [143,] 5.72 62 [144,] 5.76 67 [145,] 5.80 50 [146,] 5.84 57 [147,] 5.88 48 [148,] 5.92 54 [149,] 5.96 62 [150,] 6.00 63 [151,] 6.04 54 [152,] 6.08 80 [153,] 6.12 55 [154,] 6.16 68 [155,] 6.20 63 [156,] 6.24 61 [157,] 6.28 60 [158,] 6.32 73 [159,] 6.36 54 [160,] 6.40 72 [161,] 6.44 52 [162,] 6.48 48 [163,] 6.52 66 [164,] 6.56 77 [165,] 6.60 58 [166,] 6.64 52 [167,] 6.68 51 [168,] 6.72 52 [169,] 6.76 53 [170,] 6.80 75 [171,] 6.84 39 [172,] 6.88 54 [173,] 6.92 46 [174,] 6.96 51 [175,] 7.00 50 [176,] 7.04 64 [177,] 7.08 51 [178,] 7.12 61 [179,] 7.16 54 [180,] 7.20 71 [181,] 7.24 55 [182,] 7.28 59 [183,] 7.32 72 [184,] 7.36 84 [185,] 7.40 47 [186,] 7.44 60 [187,] 7.48 47 [188,] 7.52 42 [189,] 7.56 71 [190,] 7.60 51 [191,] 7.64 52 [192,] 7.68 53 [193,] 7.72 65 [194,] 7.76 56 [195,] 7.80 59 [196,] 7.84 52 [197,] 7.88 52 [198,] 7.92 40 [199,] 7.96 55 [200,] 8.00 53 [201,] 8.04 87 [202,] 8.08 55 [203,] 8.12 32 [204,] 8.16 46 [205,] 8.20 53 [206,] 8.24 52 [207,] 8.28 44 [208,] 8.32 54 [209,] 8.36 51 [210,] 8.40 77 [211,] 8.44 44 [212,] 8.48 45 [213,] 8.52 35 [214,] 8.56 58 [215,] 8.60 51 [216,] 8.64 49 [217,] 8.68 45 [218,] 8.72 71 [219,] 8.76 50 [220,] 8.80 62 [221,] 8.84 40 [222,] 8.88 54 [223,] 8.92 70 [224,] 8.96 61 [225,] 9.00 53 [226,] 9.04 52 [227,] 9.08 39 [228,] 9.12 78 [229,] 9.16 47 [230,] 9.20 61 [231,] 9.24 31 [232,] 9.28 50 [233,] 9.32 48 [234,] 9.36 59 [235,] 9.40 53 [236,] 9.44 53 [237,] 9.48 78 [238,] 9.52 57 [239,] 9.56 58 [240,] 9.60 55 [241,] 9.64 63 [242,] 9.68 66 [243,] 9.72 48 [244,] 9.76 38 [245,] 9.80 45 [246,] 9.84 57 [247,] 9.88 58 [248,] 9.92 55 [249,] 9.96 51 [250,] 10.00 73 [251,] 10.04 46 [252,] 10.08 71 [253,] 10.12 56 [254,] 10.16 35 [255,] 10.20 43 [256,] 10.24 71 [257,] 10.28 66 [258,] 10.32 49 [259,] 10.36 45 [260,] 10.40 51 [261,] 10.44 44 [262,] 10.48 54 [263,] 10.52 53 [264,] 10.56 57 [265,] 10.60 61 [266,] 10.64 32 [267,] 10.68 61 [268,] 10.72 58 [269,] 10.76 47 [270,] 10.80 57 [271,] 10.84 50 [272,] 10.88 67 [273,] 10.92 47 [274,] 10.96 43 [275,] 11.00 68 [276,] 11.04 49 [277,] 11.08 61 [278,] 11.12 70 [279,] 11.16 45 [280,] 11.20 49 [281,] 11.24 48 [282,] 11.28 56 [283,] 11.32 45 [284,] 11.36 56 [285,] 11.40 55 [286,] 11.44 37 [287,] 11.48 69 [288,] 11.52 46 [289,] 11.56 51 [290,] 11.60 54 [291,] 11.64 41 [292,] 11.68 55 [293,] 11.72 49 [294,] 11.76 50 [295,] 11.80 52 [296,] 11.84 48 [297,] 11.88 55 [298,] 11.92 63 [299,] 11.96 58 [300,] 12.00 48 [301,] 12.04 52 [302,] 12.08 53 [303,] 12.12 65 [304,] 12.16 54 [305,] 12.20 53 [306,] 12.24 51 [307,] 12.28 59 [308,] 12.32 46 [309,] 12.36 44 [310,] 12.40 83 [311,] 12.44 44 [312,] 12.48 29 [313,] 12.52 56 [314,] 12.56 53 [315,] 12.60 74 [316,] 12.64 67 [317,] 12.68 44 [318,] 12.72 39 [319,] 12.76 48 [320,] 12.80 55 [321,] 12.84 58 [322,] 12.88 42 [323,] 12.92 46 [324,] 12.96 57 [325,] 13.00 59 [326,] 13.04 58 [327,] 13.08 56 [328,] 13.12 53 [329,] 13.16 46 [330,] 13.20 48 [331,] 13.24 54 [332,] 13.28 42 [333,] 13.32 57 [334,] 13.36 55 [335,] 13.40 44 [336,] 13.44 58 [337,] 13.48 53 [338,] 13.52 50 [339,] 13.56 45 [340,] 13.60 35 [341,] 13.64 56 [342,] 13.68 53 [343,] 13.72 52 [344,] 13.76 58 [345,] 13.80 44 [346,] 13.84 48 [347,] 13.88 44 [348,] 13.92 52 [349,] 13.96 32 [350,] 14.00 49 [351,] 14.04 47 [352,] 14.08 31 [353,] 14.12 58 [354,] 14.16 50 [355,] 14.20 57 [356,] 14.24 40 [357,] 14.28 46 [358,] 14.32 54 [359,] 14.36 48 [360,] 14.40 45 [361,] 14.44 43 [362,] 14.48 56 [363,] 14.52 48 [364,] 14.56 50 [365,] 14.60 33 [366,] 14.64 42 [367,] 14.68 54 [368,] 14.72 78 [369,] 14.76 62 [370,] 14.80 44 [371,] 14.84 45 [372,] 14.88 62 [373,] 14.92 50 [374,] 14.96 54 [375,] 15.00 55 [376,] 15.04 49 [377,] 15.08 54 [378,] 15.12 56 [379,] 15.16 42 [380,] 15.20 49 [381,] 15.24 51 [382,] 15.28 61 [383,] 15.32 46 [384,] 15.36 49 [385,] 15.40 41 [386,] 15.44 52 [387,] 15.48 47 [388,] 15.52 43 [389,] 15.56 62 [390,] 15.60 42 [391,] 15.64 42 [392,] 15.68 44 [393,] 15.72 47 [394,] 15.76 49 [395,] 15.80 60 [396,] 15.84 51 [397,] 15.88 62 [398,] 15.92 49 [399,] 15.96 60 [400,] 16.00 32 [401,] 16.04 75 [402,] 16.08 33 [403,] 16.12 59 [404,] 16.16 51 [405,] 16.20 48 [406,] 16.24 40 [407,] 16.28 44 [408,] 16.32 40 [409,] 16.36 41 [410,] 16.40 49 [411,] 16.44 52 [412,] 16.48 49 [413,] 16.52 50 [414,] 16.56 51 [415,] 16.60 48 [416,] 16.64 45 [417,] 16.68 57 [418,] 16.72 36 [419,] 16.76 48 [420,] 16.80 48 [421,] 16.84 47 [422,] 16.88 50 [423,] 16.92 42 [424,] 16.96 46 [425,] 17.00 52 [426,] 17.04 40 [427,] 17.08 46 [428,] 17.12 60 [429,] 17.16 41 [430,] 17.20 42 [431,] 17.24 51 [432,] 17.28 45 [433,] 17.32 29 [434,] 17.36 57 [435,] 17.40 53 [436,] 17.44 37 [437,] 17.48 43 [438,] 17.52 32 [439,] 17.56 50 [440,] 17.60 62 [441,] 17.64 51 [442,] 17.68 59 [443,] 17.72 42 [444,] 17.76 49 [445,] 17.80 39 [446,] 17.84 56 [447,] 17.88 53 [448,] 17.92 46 [449,] 17.96 59 [450,] 18.00 53 [451,] 18.04 64 [452,] 18.08 31 [453,] 18.12 45 [454,] 18.16 44 [455,] 18.20 53 [456,] 18.24 37 [457,] 18.28 36 [458,] 18.32 52 [459,] 18.36 57 [460,] 18.40 44 [461,] 18.44 48 [462,] 18.48 46 [463,] 18.52 31 [464,] 18.56 67 [465,] 18.60 43 [466,] 18.64 58 [467,] 18.68 53 [468,] 18.72 47 [469,] 18.76 59 [470,] 18.80 47 [471,] 18.84 31 [472,] 18.88 51 [473,] 18.92 44 [474,] 18.96 43 [475,] 19.00 49 [476,] 19.04 42 [477,] 19.08 48 [478,] 19.12 42 [479,] 19.16 37 [480,] 19.20 45 [481,] 19.24 54 [482,] 19.28 42 [483,] 19.32 50 [484,] 19.36 42 [485,] 19.40 47 [486,] 19.44 51 [487,] 19.48 54 [488,] 19.52 46 [489,] 19.56 39 [490,] 19.60 42 [491,] 19.64 38 [492,] 19.68 49 [493,] 19.72 63 [494,] 19.76 41 [495,] 19.80 50 [496,] 19.84 44 [497,] 19.88 52 [498,] 19.92 57 [499,] 19.96 43 [500,] 20.00 48 [501,] 20.04 38 [502,] 20.08 38 [503,] 20.12 53 [504,] 20.16 30 [505,] 20.20 47 [506,] 20.24 46 [507,] 20.28 48 [508,] 20.32 56 [509,] 20.36 54 [510,] 20.40 45 [511,] 20.44 48 [512,] 20.48 28 [513,] 20.52 48 [514,] 20.56 42 [515,] 20.60 42 [516,] 20.64 39 [517,] 20.68 46 [518,] 20.72 38 [519,] 20.76 48 [520,] 20.80 44 [521,] 20.84 26 [522,] 20.88 37 [523,] 20.92 41 [524,] 20.96 37 [525,] 21.00 54 [526,] 21.04 52 [527,] 21.08 36 [528,] 21.12 53 [529,] 21.16 43 [530,] 21.20 51 [531,] 21.24 54 [532,] 21.28 51 [533,] 21.32 55 [534,] 21.36 57 [535,] 21.40 61 [536,] 21.44 33 [537,] 21.48 51 [538,] 21.52 37 [539,] 21.56 28 [540,] 21.60 46 [541,] 21.64 46 [542,] 21.68 28 [543,] 21.72 39 [544,] 21.76 60 [545,] 21.80 48 [546,] 21.84 55 [547,] 21.88 35 [548,] 21.92 54 [549,] 21.96 39 [550,] 22.00 48 [551,] 22.04 46 [552,] 22.08 31 [553,] 22.12 51 [554,] 22.16 46 [555,] 22.20 44 [556,] 22.24 62 [557,] 22.28 33 [558,] 22.32 55 [559,] 22.36 44 [560,] 22.40 51 [561,] 22.44 39 [562,] 22.48 49 [563,] 22.52 29 [564,] 22.56 45 [565,] 22.60 59 [566,] 22.64 44 [567,] 22.68 27 [568,] 22.72 65 [569,] 22.76 41 [570,] 22.80 40 [571,] 22.84 43 [572,] 22.88 43 [573,] 22.92 49 [574,] 22.96 31 [575,] 23.00 38 [576,] 23.04 53 [577,] 23.08 34 [578,] 23.12 54 [579,] 23.16 37 [580,] 23.20 34 [581,] 23.24 72 [582,] 23.28 46 [583,] 23.32 45 [584,] 23.36 39 [585,] 23.40 37 [586,] 23.44 58 [587,] 23.48 46 [588,] 23.52 39 [589,] 23.56 58 [590,] 23.60 43 [591,] 23.64 46 [592,] 23.68 57 [593,] 23.72 40 [594,] 23.76 46 [595,] 23.80 56 [596,] 23.84 42 [597,] 23.88 44 [598,] 23.92 54 [599,] 23.96 61 [600,] 24.00 36 [601,] 24.04 38 [602,] 24.08 46 [603,] 24.12 58 [604,] 24.16 50 [605,] 24.20 43 [606,] 24.24 51 [607,] 24.28 40 [608,] 24.32 31 [609,] 24.36 30 [610,] 24.40 50 [611,] 24.44 38 [612,] 24.48 38 [613,] 24.52 47 [614,] 24.56 55 [615,] 24.60 44 [616,] 24.64 27 [617,] 24.68 40 [618,] 24.72 46 [619,] 24.76 49 [620,] 24.80 39 [621,] 24.84 39 [622,] 24.88 25 [623,] 24.92 35 [624,] 24.96 38 [625,] 25.00 43 [626,] 25.04 53 [627,] 25.08 51 [628,] 25.12 67 [629,] 25.16 46 [630,] 25.20 61 [631,] 25.24 41 [632,] 25.28 44 [633,] 25.32 35 [634,] 25.36 46 [635,] 25.40 49 [636,] 25.44 43 [637,] 25.48 47 [638,] 25.52 36 [639,] 25.56 68 [640,] 25.60 52 [641,] 25.64 52 [642,] 25.68 43 [643,] 25.72 33 [644,] 25.76 42 [645,] 25.80 62 [646,] 25.84 40 [647,] 25.88 51 [648,] 25.92 46 [649,] 25.96 45 [650,] 26.00 54 [651,] 26.04 41 [652,] 26.08 41 [653,] 26.12 40 [654,] 26.16 37 [655,] 26.20 44 [656,] 26.24 49 [657,] 26.28 54 [658,] 26.32 49 [659,] 26.36 44 [660,] 26.40 43 [661,] 26.44 49 [662,] 26.48 41 [663,] 26.52 47 [664,] 26.56 44 [665,] 26.60 40 [666,] 26.64 51 [667,] 26.68 44 [668,] 26.72 41 [669,] 26.76 52 [670,] 26.80 47 [671,] 26.84 37 [672,] 26.88 37 [673,] 26.92 42 [674,] 26.96 36 [675,] 27.00 49 [676,] 27.04 29 [677,] 27.08 30 [678,] 27.12 34 [679,] 27.16 52 [680,] 27.20 42 [681,] 27.24 33 [682,] 27.28 44 [683,] 27.32 41 [684,] 27.36 44 [685,] 27.40 46 [686,] 27.44 32 [687,] 27.48 43 [688,] 27.52 62 [689,] 27.56 54 [690,] 27.60 25 [691,] 27.64 41 [692,] 27.68 45 [693,] 27.72 42 [694,] 27.76 54 [695,] 27.80 46 [696,] 27.84 43 [697,] 27.88 45 [698,] 27.92 39 [699,] 27.96 44 [700,] 28.00 56 [701,] 28.04 52 [702,] 28.08 48 [703,] 28.12 55 [704,] 28.16 36 [705,] 28.20 43 [706,] 28.24 36 [707,] 28.28 39 [708,] 28.32 56 [709,] 28.36 37 [710,] 28.40 48 [711,] 28.44 46 [712,] 28.48 56 [713,] 28.52 39 [714,] 28.56 52 [715,] 28.60 37 [716,] 28.64 57 [717,] 28.68 40 [718,] 28.72 41 [719,] 28.76 41 [720,] 28.80 32 [721,] 28.84 52 [722,] 28.88 38 [723,] 28.92 45 [724,] 28.96 49 [725,] 29.00 52 [726,] 29.04 34 [727,] 29.08 34 [728,] 29.12 60 [729,] 29.16 46 [730,] 29.20 37 [731,] 29.24 43 [732,] 29.28 39 [733,] 29.32 56 [734,] 29.36 35 [735,] 29.40 43 [736,] 29.44 38 [737,] 29.48 44 [738,] 29.52 52 [739,] 29.56 63 [740,] 29.60 43 [741,] 29.64 31 [742,] 29.68 41 [743,] 29.72 43 [744,] 29.76 46 [745,] 29.80 51 [746,] 29.84 53 [747,] 29.88 29 [748,] 29.92 46 [749,] 29.96 47 [750,] 30.00 48 [751,] 30.04 50 [752,] 30.08 34 [753,] 30.12 36 [754,] 30.16 50 [755,] 30.20 50 [756,] 30.24 45 [757,] 30.28 40 [758,] 30.32 37 [759,] 30.36 39 [760,] 30.40 54 [761,] 30.44 51 [762,] 30.48 35 [763,] 30.52 45 [764,] 30.56 37 [765,] 30.60 36 [766,] 30.64 39 [767,] 30.68 38 [768,] 30.72 40 [769,] 30.76 31 [770,] 30.80 34 [771,] 30.84 28 [772,] 30.88 53 [773,] 30.92 43 [774,] 30.96 43 [775,] 31.00 38 [776,] 31.04 34 [777,] 31.08 41 [778,] 31.12 39 [779,] 31.16 44 [780,] 31.20 54 [781,] 31.24 57 [782,] 31.28 42 [783,] 31.32 54 [784,] 31.36 25 [785,] 31.40 56 [786,] 31.44 45 [787,] 31.48 43 [788,] 31.52 38 [789,] 31.56 36 [790,] 31.60 42 [791,] 31.64 50 [792,] 31.68 35 [793,] 31.72 48 [794,] 31.76 35 [795,] 31.80 60 [796,] 31.84 43 [797,] 31.88 40 [798,] 31.92 46 [799,] 31.96 44 [800,] 32.00 46 [801,] 32.04 52 [802,] 32.08 34 [803,] 32.12 56 [804,] 32.16 44 [805,] 32.20 47 [806,] 32.24 49 [807,] 32.28 43 [808,] 32.32 43 [809,] 32.36 40 [810,] 32.40 31 [811,] 32.44 46 [812,] 32.48 43 [813,] 32.52 59 [814,] 32.56 46 [815,] 32.60 29 [816,] 32.64 49 [817,] 32.68 29 [818,] 32.72 42 [819,] 32.76 44 [820,] 32.80 44 [821,] 32.84 48 [822,] 32.88 47 [823,] 32.92 48 [824,] 32.96 36 [825,] 33.00 41 [826,] 33.04 46 [827,] 33.08 32 [828,] 33.12 44 [829,] 33.16 51 [830,] 33.20 37 [831,] 33.24 52 [832,] 33.28 32 [833,] 33.32 46 [834,] 33.36 50 [835,] 33.40 33 [836,] 33.44 44 [837,] 33.48 49 [838,] 33.52 48 [839,] 33.56 23 [840,] 33.60 36 [841,] 33.64 46 [842,] 33.68 39 [843,] 33.72 49 [844,] 33.76 40 [845,] 33.80 40 [846,] 33.84 53 [847,] 33.88 43 [848,] 33.92 38 [849,] 33.96 52 [850,] 34.00 30 [851,] 34.04 30 [852,] 34.08 31 [853,] 34.12 49 [854,] 34.16 41 [855,] 34.20 39 [856,] 34.24 42 [857,] 34.28 47 [858,] 34.32 49 [859,] 34.36 42 [860,] 34.40 42 [861,] 34.44 43 [862,] 34.48 47 [863,] 34.52 40 [864,] 34.56 31 [865,] 34.60 47 [866,] 34.64 39 [867,] 34.68 41 [868,] 34.72 26 [869,] 34.76 29 [870,] 34.80 24 [871,] 34.84 41 [872,] 34.88 49 [873,] 34.92 53 [874,] 34.96 43 [875,] 35.00 36 [876,] 35.04 39 [877,] 35.08 38 [878,] 35.12 39 [879,] 35.16 33 [880,] 35.20 51 [881,] 35.24 31 [882,] 35.28 36 [883,] 35.32 34 [884,] 35.36 45 [885,] 35.40 56 [886,] 35.44 26 [887,] 35.48 48 [888,] 35.52 38 [889,] 35.56 38 [890,] 35.60 42 [891,] 35.64 24 [892,] 35.68 31 [893,] 35.72 46 [894,] 35.76 38 [895,] 35.80 35 [896,] 35.84 32 [897,] 35.88 51 [898,] 35.92 44 [899,] 35.96 35 [900,] 36.00 51 [901,] 36.04 45 [902,] 36.08 41 [903,] 36.12 36 [904,] 36.16 36 [905,] 36.20 33 [906,] 36.24 50 [907,] 36.28 47 [908,] 36.32 51 [909,] 36.36 38 [910,] 36.40 34 [911,] 36.44 32 [912,] 36.48 44 [913,] 36.52 43 [914,] 36.56 43 [915,] 36.60 29 [916,] 36.64 33 [917,] 36.68 54 [918,] 36.72 47 [919,] 36.76 36 [920,] 36.80 47 [921,] 36.84 56 [922,] 36.88 47 [923,] 36.92 43 [924,] 36.96 56 [925,] 37.00 28 [926,] 37.04 39 [927,] 37.08 44 [928,] 37.12 37 [929,] 37.16 43 [930,] 37.20 44 [931,] 37.24 38 [932,] 37.28 46 [933,] 37.32 42 [934,] 37.36 34 [935,] 37.40 44 [936,] 37.44 36 [937,] 37.48 39 [938,] 37.52 48 [939,] 37.56 46 [940,] 37.60 34 [941,] 37.64 43 [942,] 37.68 30 [943,] 37.72 44 [944,] 37.76 29 [945,] 37.80 44 [946,] 37.84 49 [947,] 37.88 42 [948,] 37.92 30 [949,] 37.96 40 [950,] 38.00 36 [951,] 38.04 43 [952,] 38.08 28 [953,] 38.12 34 [954,] 38.16 46 [955,] 38.20 39 [956,] 38.24 34 [957,] 38.28 43 [958,] 38.32 32 [959,] 38.36 39 [960,] 38.40 38 [961,] 38.44 33 [962,] 38.48 26 [963,] 38.52 38 [964,] 38.56 40 [965,] 38.60 31 [966,] 38.64 35 [967,] 38.68 52 [968,] 38.72 35 [969,] 38.76 58 [970,] 38.80 44 [971,] 38.84 34 [972,] 38.88 39 [973,] 38.92 45 [974,] 38.96 50 [975,] 39.00 43 [976,] 39.04 43 [977,] 39.08 53 [978,] 39.12 55 [979,] 39.16 39 [980,] 39.20 38 [981,] 39.24 41 [982,] 39.28 36 [983,] 39.32 36 [984,] 39.36 43 [985,] 39.40 34 [986,] 39.44 29 [987,] 39.48 36 [988,] 39.52 37 [989,] 39.56 40 [990,] 39.60 50 [991,] 39.64 48 [992,] 39.68 46 [993,] 39.72 51 [994,] 39.76 50 [995,] 39.80 32 [996,] 39.84 41 [997,] 39.88 41 [998,] 39.92 41 [999,] 39.96 31 [1000,] 40.00 48 $`9_TL (PMT)` [,1] [,2] [1,] 0.884 13 [2,] 1.768 98 [3,] 2.652 6 [4,] 3.536 6 [5,] 4.420 9 [6,] 5.304 8 [7,] 6.188 9 [8,] 7.072 9 [9,] 7.956 4 [10,] 8.840 13 [11,] 9.724 10 [12,] 10.608 5 [13,] 11.492 5 [14,] 12.376 19 [15,] 13.260 11 [16,] 14.144 4 [17,] 15.028 6 [18,] 15.912 10 [19,] 16.796 9 [20,] 17.680 4 [21,] 18.564 8 [22,] 19.448 10 [23,] 20.332 7 [24,] 21.216 3 [25,] 22.100 6 [26,] 22.984 5 [27,] 23.868 5 [28,] 24.752 4 [29,] 25.636 6 [30,] 26.520 11 [31,] 27.404 3 [32,] 28.288 0 [33,] 29.172 8 [34,] 30.056 2 [35,] 30.940 2 [36,] 31.824 4 [37,] 32.708 10 [38,] 33.592 6 [39,] 34.476 11 [40,] 35.360 25 [41,] 36.244 4 [42,] 37.128 4 [43,] 38.012 4 [44,] 38.896 10 [45,] 39.780 5 [46,] 40.664 17 [47,] 41.548 5 [48,] 42.432 11 [49,] 43.316 13 [50,] 44.200 6 [51,] 45.084 2 [52,] 45.968 3 [53,] 46.852 11 [54,] 47.736 10 [55,] 48.620 6 [56,] 49.504 5 [57,] 50.388 10 [58,] 51.272 4 [59,] 52.156 1 [60,] 53.040 11 [61,] 53.924 12 [62,] 54.808 10 [63,] 55.692 3 [64,] 56.576 5 [65,] 57.460 7 [66,] 58.344 5 [67,] 59.228 5 [68,] 60.112 7 [69,] 60.996 3 [70,] 61.880 6 [71,] 62.764 3 [72,] 63.648 10 [73,] 64.532 4 [74,] 65.416 5 [75,] 66.300 13 [76,] 67.184 2 [77,] 68.068 5 [78,] 68.952 4 [79,] 69.836 4 [80,] 70.720 3 [81,] 71.604 13 [82,] 72.488 12 [83,] 73.372 4 [84,] 74.256 9 [85,] 75.140 24 [86,] 76.024 7 [87,] 76.908 8 [88,] 77.792 21 [89,] 78.676 11 [90,] 79.560 19 [91,] 80.444 7 [92,] 81.328 7 [93,] 82.212 15 [94,] 83.096 27 [95,] 83.980 15 [96,] 84.864 27 [97,] 85.748 21 [98,] 86.632 33 [99,] 87.516 30 [100,] 88.400 26 [101,] 89.284 31 [102,] 90.168 26 [103,] 91.052 52 [104,] 91.936 22 [105,] 92.820 33 [106,] 93.704 31 [107,] 94.588 35 [108,] 95.472 43 [109,] 96.356 47 [110,] 97.240 35 [111,] 98.124 60 [112,] 99.008 66 [113,] 99.892 59 [114,] 100.776 51 [115,] 101.660 63 [116,] 102.544 59 [117,] 103.428 60 [118,] 104.312 76 [119,] 105.196 80 [120,] 106.080 77 [121,] 106.964 91 [122,] 107.848 111 [123,] 108.732 73 [124,] 109.616 91 [125,] 110.500 106 [126,] 111.384 96 [127,] 112.268 101 [128,] 113.152 102 [129,] 114.036 127 [130,] 114.920 136 [131,] 115.804 134 [132,] 116.688 147 [133,] 117.572 129 [134,] 118.456 144 [135,] 119.340 129 [136,] 120.224 150 [137,] 121.108 155 [138,] 121.992 166 [139,] 122.876 152 [140,] 123.760 222 [141,] 124.644 181 [142,] 125.528 175 [143,] 126.412 211 [144,] 127.296 202 [145,] 128.180 192 [146,] 129.064 217 [147,] 129.948 215 [148,] 130.832 223 [149,] 131.716 213 [150,] 132.600 234 [151,] 133.484 271 [152,] 134.368 221 [153,] 135.252 295 [154,] 136.136 285 [155,] 137.020 246 [156,] 137.904 245 [157,] 138.788 295 [158,] 139.672 272 [159,] 140.556 260 [160,] 141.440 273 [161,] 142.324 238 [162,] 143.208 277 [163,] 144.092 303 [164,] 144.976 281 [165,] 145.860 290 [166,] 146.744 288 [167,] 147.628 245 [168,] 148.512 260 [169,] 149.396 289 [170,] 150.280 292 [171,] 151.164 238 [172,] 152.048 283 [173,] 152.932 290 [174,] 153.816 287 [175,] 154.700 303 [176,] 155.584 308 [177,] 156.468 270 [178,] 157.352 282 [179,] 158.236 272 [180,] 159.120 299 [181,] 160.004 269 [182,] 160.888 259 [183,] 161.772 257 [184,] 162.656 284 [185,] 163.540 278 [186,] 164.424 278 [187,] 165.308 317 [188,] 166.192 286 [189,] 167.076 291 [190,] 167.960 296 [191,] 168.844 319 [192,] 169.728 270 [193,] 170.612 276 [194,] 171.496 268 [195,] 172.380 232 [196,] 173.264 302 [197,] 174.148 238 [198,] 175.032 261 [199,] 175.916 247 [200,] 176.800 271 [201,] 177.684 267 [202,] 178.568 271 [203,] 179.452 286 [204,] 180.336 259 [205,] 181.220 298 [206,] 182.104 299 [207,] 182.988 276 [208,] 183.872 276 [209,] 184.756 272 [210,] 185.640 266 [211,] 186.524 279 [212,] 187.408 264 [213,] 188.292 291 [214,] 189.176 269 [215,] 190.060 302 [216,] 190.944 296 [217,] 191.828 263 [218,] 192.712 281 [219,] 193.596 352 [220,] 194.480 321 [221,] 195.364 302 [222,] 196.248 262 [223,] 197.132 299 [224,] 198.016 342 [225,] 198.900 319 [226,] 199.784 309 [227,] 200.668 302 [228,] 201.552 366 [229,] 202.436 295 [230,] 203.320 349 [231,] 204.204 348 [232,] 205.088 343 [233,] 205.972 366 [234,] 206.856 315 [235,] 207.740 348 [236,] 208.624 393 [237,] 209.508 366 [238,] 210.392 389 [239,] 211.276 379 [240,] 212.160 411 [241,] 213.044 467 [242,] 213.928 369 [243,] 214.812 358 [244,] 215.696 371 [245,] 216.580 349 [246,] 217.464 360 [247,] 218.348 376 [248,] 219.232 359 [249,] 220.116 364 [250,] 221.000 105 $`10_OSL (PMT)` [,1] [,2] [1,] 0.04 8150 [2,] 0.08 7000 [3,] 0.12 5947 [4,] 0.16 5118 [5,] 0.20 4534 [6,] 0.24 3776 [7,] 0.28 3512 [8,] 0.32 2887 [9,] 0.36 2479 [10,] 0.40 2130 [11,] 0.44 1991 [12,] 0.48 1783 [13,] 0.52 1495 [14,] 0.56 1359 [15,] 0.60 1161 [16,] 0.64 1033 [17,] 0.68 982 [18,] 0.72 846 [19,] 0.76 884 [20,] 0.80 700 [21,] 0.84 612 [22,] 0.88 543 [23,] 0.92 527 [24,] 0.96 471 [25,] 1.00 440 [26,] 1.04 410 [27,] 1.08 372 [28,] 1.12 343 [29,] 1.16 337 [30,] 1.20 282 [31,] 1.24 292 [32,] 1.28 288 [33,] 1.32 274 [34,] 1.36 272 [35,] 1.40 197 [36,] 1.44 203 [37,] 1.48 228 [38,] 1.52 244 [39,] 1.56 214 [40,] 1.60 184 [41,] 1.64 229 [42,] 1.68 187 [43,] 1.72 171 [44,] 1.76 166 [45,] 1.80 130 [46,] 1.84 140 [47,] 1.88 150 [48,] 1.92 161 [49,] 1.96 143 [50,] 2.00 129 [51,] 2.04 137 [52,] 2.08 142 [53,] 2.12 124 [54,] 2.16 140 [55,] 2.20 146 [56,] 2.24 150 [57,] 2.28 108 [58,] 2.32 145 [59,] 2.36 146 [60,] 2.40 125 [61,] 2.44 102 [62,] 2.48 135 [63,] 2.52 119 [64,] 2.56 145 [65,] 2.60 112 [66,] 2.64 105 [67,] 2.68 127 [68,] 2.72 112 [69,] 2.76 107 [70,] 2.80 105 [71,] 2.84 108 [72,] 2.88 117 [73,] 2.92 135 [74,] 2.96 100 [75,] 3.00 108 [76,] 3.04 112 [77,] 3.08 100 [78,] 3.12 112 [79,] 3.16 93 [80,] 3.20 96 [81,] 3.24 99 [82,] 3.28 94 [83,] 3.32 110 [84,] 3.36 96 [85,] 3.40 76 [86,] 3.44 97 [87,] 3.48 88 [88,] 3.52 85 [89,] 3.56 96 [90,] 3.60 89 [91,] 3.64 99 [92,] 3.68 64 [93,] 3.72 80 [94,] 3.76 86 [95,] 3.80 86 [96,] 3.84 87 [97,] 3.88 111 [98,] 3.92 90 [99,] 3.96 80 [100,] 4.00 109 [101,] 4.04 105 [102,] 4.08 94 [103,] 4.12 75 [104,] 4.16 80 [105,] 4.20 90 [106,] 4.24 88 [107,] 4.28 95 [108,] 4.32 94 [109,] 4.36 90 [110,] 4.40 79 [111,] 4.44 82 [112,] 4.48 74 [113,] 4.52 84 [114,] 4.56 82 [115,] 4.60 75 [116,] 4.64 83 [117,] 4.68 83 [118,] 4.72 79 [119,] 4.76 57 [120,] 4.80 62 [121,] 4.84 65 [122,] 4.88 100 [123,] 4.92 68 [124,] 4.96 94 [125,] 5.00 92 [126,] 5.04 90 [127,] 5.08 70 [128,] 5.12 77 [129,] 5.16 83 [130,] 5.20 75 [131,] 5.24 81 [132,] 5.28 78 [133,] 5.32 84 [134,] 5.36 80 [135,] 5.40 98 [136,] 5.44 79 [137,] 5.48 59 [138,] 5.52 95 [139,] 5.56 85 [140,] 5.60 86 [141,] 5.64 94 [142,] 5.68 89 [143,] 5.72 86 [144,] 5.76 93 [145,] 5.80 83 [146,] 5.84 103 [147,] 5.88 64 [148,] 5.92 60 [149,] 5.96 76 [150,] 6.00 57 [151,] 6.04 68 [152,] 6.08 72 [153,] 6.12 74 [154,] 6.16 65 [155,] 6.20 106 [156,] 6.24 81 [157,] 6.28 61 [158,] 6.32 66 [159,] 6.36 78 [160,] 6.40 62 [161,] 6.44 53 [162,] 6.48 67 [163,] 6.52 70 [164,] 6.56 69 [165,] 6.60 61 [166,] 6.64 84 [167,] 6.68 91 [168,] 6.72 79 [169,] 6.76 84 [170,] 6.80 63 [171,] 6.84 72 [172,] 6.88 60 [173,] 6.92 64 [174,] 6.96 75 [175,] 7.00 72 [176,] 7.04 72 [177,] 7.08 76 [178,] 7.12 64 [179,] 7.16 89 [180,] 7.20 64 [181,] 7.24 79 [182,] 7.28 60 [183,] 7.32 94 [184,] 7.36 75 [185,] 7.40 80 [186,] 7.44 84 [187,] 7.48 66 [188,] 7.52 73 [189,] 7.56 80 [190,] 7.60 66 [191,] 7.64 61 [192,] 7.68 62 [193,] 7.72 78 [194,] 7.76 73 [195,] 7.80 54 [196,] 7.84 63 [197,] 7.88 60 [198,] 7.92 72 [199,] 7.96 61 [200,] 8.00 73 [201,] 8.04 71 [202,] 8.08 49 [203,] 8.12 72 [204,] 8.16 68 [205,] 8.20 66 [206,] 8.24 59 [207,] 8.28 78 [208,] 8.32 60 [209,] 8.36 85 [210,] 8.40 59 [211,] 8.44 72 [212,] 8.48 78 [213,] 8.52 66 [214,] 8.56 60 [215,] 8.60 70 [216,] 8.64 69 [217,] 8.68 58 [218,] 8.72 65 [219,] 8.76 65 [220,] 8.80 50 [221,] 8.84 65 [222,] 8.88 76 [223,] 8.92 68 [224,] 8.96 65 [225,] 9.00 51 [226,] 9.04 70 [227,] 9.08 60 [228,] 9.12 65 [229,] 9.16 77 [230,] 9.20 71 [231,] 9.24 70 [232,] 9.28 95 [233,] 9.32 63 [234,] 9.36 70 [235,] 9.40 61 [236,] 9.44 64 [237,] 9.48 70 [238,] 9.52 69 [239,] 9.56 60 [240,] 9.60 69 [241,] 9.64 66 [242,] 9.68 69 [243,] 9.72 64 [244,] 9.76 81 [245,] 9.80 61 [246,] 9.84 57 [247,] 9.88 63 [248,] 9.92 86 [249,] 9.96 74 [250,] 10.00 51 [251,] 10.04 42 [252,] 10.08 61 [253,] 10.12 73 [254,] 10.16 87 [255,] 10.20 61 [256,] 10.24 62 [257,] 10.28 91 [258,] 10.32 60 [259,] 10.36 78 [260,] 10.40 64 [261,] 10.44 50 [262,] 10.48 58 [263,] 10.52 82 [264,] 10.56 52 [265,] 10.60 63 [266,] 10.64 74 [267,] 10.68 68 [268,] 10.72 71 [269,] 10.76 51 [270,] 10.80 73 [271,] 10.84 71 [272,] 10.88 53 [273,] 10.92 67 [274,] 10.96 56 [275,] 11.00 38 [276,] 11.04 60 [277,] 11.08 77 [278,] 11.12 64 [279,] 11.16 47 [280,] 11.20 69 [281,] 11.24 59 [282,] 11.28 54 [283,] 11.32 41 [284,] 11.36 68 [285,] 11.40 63 [286,] 11.44 43 [287,] 11.48 80 [288,] 11.52 54 [289,] 11.56 76 [290,] 11.60 62 [291,] 11.64 58 [292,] 11.68 52 [293,] 11.72 49 [294,] 11.76 68 [295,] 11.80 43 [296,] 11.84 53 [297,] 11.88 48 [298,] 11.92 63 [299,] 11.96 68 [300,] 12.00 65 [301,] 12.04 79 [302,] 12.08 57 [303,] 12.12 52 [304,] 12.16 61 [305,] 12.20 61 [306,] 12.24 64 [307,] 12.28 71 [308,] 12.32 71 [309,] 12.36 49 [310,] 12.40 58 [311,] 12.44 58 [312,] 12.48 55 [313,] 12.52 57 [314,] 12.56 68 [315,] 12.60 60 [316,] 12.64 75 [317,] 12.68 52 [318,] 12.72 49 [319,] 12.76 60 [320,] 12.80 58 [321,] 12.84 54 [322,] 12.88 51 [323,] 12.92 57 [324,] 12.96 65 [325,] 13.00 45 [326,] 13.04 56 [327,] 13.08 54 [328,] 13.12 67 [329,] 13.16 89 [330,] 13.20 68 [331,] 13.24 65 [332,] 13.28 50 [333,] 13.32 58 [334,] 13.36 62 [335,] 13.40 61 [336,] 13.44 53 [337,] 13.48 59 [338,] 13.52 65 [339,] 13.56 65 [340,] 13.60 51 [341,] 13.64 50 [342,] 13.68 49 [343,] 13.72 47 [344,] 13.76 57 [345,] 13.80 53 [346,] 13.84 66 [347,] 13.88 54 [348,] 13.92 49 [349,] 13.96 75 [350,] 14.00 58 [351,] 14.04 40 [352,] 14.08 65 [353,] 14.12 69 [354,] 14.16 55 [355,] 14.20 51 [356,] 14.24 58 [357,] 14.28 55 [358,] 14.32 54 [359,] 14.36 67 [360,] 14.40 39 [361,] 14.44 48 [362,] 14.48 58 [363,] 14.52 68 [364,] 14.56 62 [365,] 14.60 57 [366,] 14.64 75 [367,] 14.68 47 [368,] 14.72 47 [369,] 14.76 56 [370,] 14.80 47 [371,] 14.84 54 [372,] 14.88 57 [373,] 14.92 76 [374,] 14.96 75 [375,] 15.00 62 [376,] 15.04 60 [377,] 15.08 48 [378,] 15.12 60 [379,] 15.16 66 [380,] 15.20 54 [381,] 15.24 55 [382,] 15.28 71 [383,] 15.32 53 [384,] 15.36 68 [385,] 15.40 42 [386,] 15.44 53 [387,] 15.48 74 [388,] 15.52 54 [389,] 15.56 56 [390,] 15.60 57 [391,] 15.64 55 [392,] 15.68 51 [393,] 15.72 42 [394,] 15.76 49 [395,] 15.80 51 [396,] 15.84 60 [397,] 15.88 62 [398,] 15.92 53 [399,] 15.96 46 [400,] 16.00 62 [401,] 16.04 78 [402,] 16.08 60 [403,] 16.12 63 [404,] 16.16 74 [405,] 16.20 41 [406,] 16.24 57 [407,] 16.28 61 [408,] 16.32 47 [409,] 16.36 62 [410,] 16.40 71 [411,] 16.44 57 [412,] 16.48 55 [413,] 16.52 68 [414,] 16.56 43 [415,] 16.60 57 [416,] 16.64 43 [417,] 16.68 57 [418,] 16.72 59 [419,] 16.76 60 [420,] 16.80 70 [421,] 16.84 81 [422,] 16.88 52 [423,] 16.92 45 [424,] 16.96 65 [425,] 17.00 36 [426,] 17.04 58 [427,] 17.08 65 [428,] 17.12 71 [429,] 17.16 57 [430,] 17.20 51 [431,] 17.24 60 [432,] 17.28 55 [433,] 17.32 43 [434,] 17.36 59 [435,] 17.40 64 [436,] 17.44 52 [437,] 17.48 50 [438,] 17.52 52 [439,] 17.56 61 [440,] 17.60 54 [441,] 17.64 63 [442,] 17.68 65 [443,] 17.72 53 [444,] 17.76 50 [445,] 17.80 43 [446,] 17.84 47 [447,] 17.88 65 [448,] 17.92 61 [449,] 17.96 49 [450,] 18.00 58 [451,] 18.04 64 [452,] 18.08 42 [453,] 18.12 66 [454,] 18.16 64 [455,] 18.20 51 [456,] 18.24 73 [457,] 18.28 59 [458,] 18.32 55 [459,] 18.36 50 [460,] 18.40 54 [461,] 18.44 53 [462,] 18.48 68 [463,] 18.52 49 [464,] 18.56 59 [465,] 18.60 60 [466,] 18.64 41 [467,] 18.68 55 [468,] 18.72 56 [469,] 18.76 46 [470,] 18.80 47 [471,] 18.84 54 [472,] 18.88 57 [473,] 18.92 57 [474,] 18.96 61 [475,] 19.00 62 [476,] 19.04 56 [477,] 19.08 57 [478,] 19.12 55 [479,] 19.16 65 [480,] 19.20 52 [481,] 19.24 69 [482,] 19.28 61 [483,] 19.32 54 [484,] 19.36 56 [485,] 19.40 51 [486,] 19.44 58 [487,] 19.48 65 [488,] 19.52 55 [489,] 19.56 39 [490,] 19.60 69 [491,] 19.64 55 [492,] 19.68 60 [493,] 19.72 52 [494,] 19.76 49 [495,] 19.80 59 [496,] 19.84 57 [497,] 19.88 47 [498,] 19.92 59 [499,] 19.96 48 [500,] 20.00 51 [501,] 20.04 49 [502,] 20.08 48 [503,] 20.12 53 [504,] 20.16 63 [505,] 20.20 68 [506,] 20.24 62 [507,] 20.28 65 [508,] 20.32 60 [509,] 20.36 54 [510,] 20.40 40 [511,] 20.44 40 [512,] 20.48 42 [513,] 20.52 47 [514,] 20.56 55 [515,] 20.60 51 [516,] 20.64 67 [517,] 20.68 42 [518,] 20.72 47 [519,] 20.76 52 [520,] 20.80 55 [521,] 20.84 58 [522,] 20.88 50 [523,] 20.92 50 [524,] 20.96 46 [525,] 21.00 54 [526,] 21.04 64 [527,] 21.08 50 [528,] 21.12 36 [529,] 21.16 62 [530,] 21.20 57 [531,] 21.24 65 [532,] 21.28 43 [533,] 21.32 39 [534,] 21.36 57 [535,] 21.40 40 [536,] 21.44 53 [537,] 21.48 66 [538,] 21.52 46 [539,] 21.56 65 [540,] 21.60 53 [541,] 21.64 46 [542,] 21.68 43 [543,] 21.72 57 [544,] 21.76 54 [545,] 21.80 61 [546,] 21.84 36 [547,] 21.88 67 [548,] 21.92 44 [549,] 21.96 41 [550,] 22.00 68 [551,] 22.04 67 [552,] 22.08 69 [553,] 22.12 60 [554,] 22.16 57 [555,] 22.20 50 [556,] 22.24 55 [557,] 22.28 51 [558,] 22.32 66 [559,] 22.36 33 [560,] 22.40 76 [561,] 22.44 47 [562,] 22.48 42 [563,] 22.52 53 [564,] 22.56 58 [565,] 22.60 44 [566,] 22.64 52 [567,] 22.68 45 [568,] 22.72 58 [569,] 22.76 57 [570,] 22.80 49 [571,] 22.84 42 [572,] 22.88 47 [573,] 22.92 64 [574,] 22.96 35 [575,] 23.00 48 [576,] 23.04 54 [577,] 23.08 35 [578,] 23.12 44 [579,] 23.16 40 [580,] 23.20 42 [581,] 23.24 56 [582,] 23.28 56 [583,] 23.32 73 [584,] 23.36 53 [585,] 23.40 37 [586,] 23.44 49 [587,] 23.48 45 [588,] 23.52 64 [589,] 23.56 56 [590,] 23.60 47 [591,] 23.64 48 [592,] 23.68 47 [593,] 23.72 51 [594,] 23.76 74 [595,] 23.80 43 [596,] 23.84 56 [597,] 23.88 47 [598,] 23.92 58 [599,] 23.96 57 [600,] 24.00 52 [601,] 24.04 34 [602,] 24.08 47 [603,] 24.12 66 [604,] 24.16 40 [605,] 24.20 56 [606,] 24.24 56 [607,] 24.28 44 [608,] 24.32 51 [609,] 24.36 62 [610,] 24.40 45 [611,] 24.44 46 [612,] 24.48 43 [613,] 24.52 57 [614,] 24.56 39 [615,] 24.60 46 [616,] 24.64 58 [617,] 24.68 49 [618,] 24.72 46 [619,] 24.76 52 [620,] 24.80 40 [621,] 24.84 49 [622,] 24.88 57 [623,] 24.92 46 [624,] 24.96 59 [625,] 25.00 60 [626,] 25.04 37 [627,] 25.08 62 [628,] 25.12 54 [629,] 25.16 53 [630,] 25.20 57 [631,] 25.24 41 [632,] 25.28 52 [633,] 25.32 73 [634,] 25.36 52 [635,] 25.40 71 [636,] 25.44 62 [637,] 25.48 55 [638,] 25.52 51 [639,] 25.56 41 [640,] 25.60 62 [641,] 25.64 59 [642,] 25.68 48 [643,] 25.72 64 [644,] 25.76 54 [645,] 25.80 51 [646,] 25.84 50 [647,] 25.88 48 [648,] 25.92 45 [649,] 25.96 53 [650,] 26.00 61 [651,] 26.04 39 [652,] 26.08 49 [653,] 26.12 56 [654,] 26.16 60 [655,] 26.20 51 [656,] 26.24 40 [657,] 26.28 45 [658,] 26.32 60 [659,] 26.36 34 [660,] 26.40 53 [661,] 26.44 39 [662,] 26.48 48 [663,] 26.52 39 [664,] 26.56 57 [665,] 26.60 55 [666,] 26.64 46 [667,] 26.68 50 [668,] 26.72 46 [669,] 26.76 50 [670,] 26.80 59 [671,] 26.84 55 [672,] 26.88 40 [673,] 26.92 55 [674,] 26.96 57 [675,] 27.00 31 [676,] 27.04 38 [677,] 27.08 61 [678,] 27.12 49 [679,] 27.16 50 [680,] 27.20 40 [681,] 27.24 52 [682,] 27.28 51 [683,] 27.32 65 [684,] 27.36 46 [685,] 27.40 57 [686,] 27.44 46 [687,] 27.48 47 [688,] 27.52 58 [689,] 27.56 58 [690,] 27.60 55 [691,] 27.64 43 [692,] 27.68 54 [693,] 27.72 47 [694,] 27.76 50 [695,] 27.80 50 [696,] 27.84 51 [697,] 27.88 42 [698,] 27.92 60 [699,] 27.96 60 [700,] 28.00 68 [701,] 28.04 49 [702,] 28.08 42 [703,] 28.12 58 [704,] 28.16 56 [705,] 28.20 41 [706,] 28.24 43 [707,] 28.28 45 [708,] 28.32 53 [709,] 28.36 61 [710,] 28.40 54 [711,] 28.44 57 [712,] 28.48 47 [713,] 28.52 65 [714,] 28.56 65 [715,] 28.60 60 [716,] 28.64 34 [717,] 28.68 64 [718,] 28.72 54 [719,] 28.76 58 [720,] 28.80 68 [721,] 28.84 43 [722,] 28.88 45 [723,] 28.92 44 [724,] 28.96 57 [725,] 29.00 57 [726,] 29.04 55 [727,] 29.08 44 [728,] 29.12 53 [729,] 29.16 40 [730,] 29.20 54 [731,] 29.24 40 [732,] 29.28 54 [733,] 29.32 47 [734,] 29.36 49 [735,] 29.40 40 [736,] 29.44 60 [737,] 29.48 51 [738,] 29.52 43 [739,] 29.56 60 [740,] 29.60 55 [741,] 29.64 35 [742,] 29.68 38 [743,] 29.72 44 [744,] 29.76 38 [745,] 29.80 47 [746,] 29.84 63 [747,] 29.88 58 [748,] 29.92 49 [749,] 29.96 55 [750,] 30.00 60 [751,] 30.04 58 [752,] 30.08 53 [753,] 30.12 67 [754,] 30.16 55 [755,] 30.20 62 [756,] 30.24 52 [757,] 30.28 56 [758,] 30.32 70 [759,] 30.36 58 [760,] 30.40 44 [761,] 30.44 55 [762,] 30.48 53 [763,] 30.52 55 [764,] 30.56 50 [765,] 30.60 67 [766,] 30.64 40 [767,] 30.68 48 [768,] 30.72 76 [769,] 30.76 55 [770,] 30.80 49 [771,] 30.84 44 [772,] 30.88 55 [773,] 30.92 47 [774,] 30.96 48 [775,] 31.00 49 [776,] 31.04 50 [777,] 31.08 65 [778,] 31.12 67 [779,] 31.16 55 [780,] 31.20 50 [781,] 31.24 42 [782,] 31.28 56 [783,] 31.32 52 [784,] 31.36 36 [785,] 31.40 41 [786,] 31.44 53 [787,] 31.48 58 [788,] 31.52 32 [789,] 31.56 34 [790,] 31.60 46 [791,] 31.64 68 [792,] 31.68 49 [793,] 31.72 48 [794,] 31.76 36 [795,] 31.80 39 [796,] 31.84 60 [797,] 31.88 59 [798,] 31.92 57 [799,] 31.96 42 [800,] 32.00 43 [801,] 32.04 39 [802,] 32.08 52 [803,] 32.12 63 [804,] 32.16 53 [805,] 32.20 47 [806,] 32.24 51 [807,] 32.28 36 [808,] 32.32 33 [809,] 32.36 70 [810,] 32.40 44 [811,] 32.44 59 [812,] 32.48 54 [813,] 32.52 37 [814,] 32.56 48 [815,] 32.60 40 [816,] 32.64 32 [817,] 32.68 35 [818,] 32.72 53 [819,] 32.76 52 [820,] 32.80 44 [821,] 32.84 47 [822,] 32.88 41 [823,] 32.92 49 [824,] 32.96 33 [825,] 33.00 35 [826,] 33.04 44 [827,] 33.08 50 [828,] 33.12 49 [829,] 33.16 45 [830,] 33.20 33 [831,] 33.24 54 [832,] 33.28 60 [833,] 33.32 71 [834,] 33.36 47 [835,] 33.40 46 [836,] 33.44 67 [837,] 33.48 62 [838,] 33.52 46 [839,] 33.56 53 [840,] 33.60 48 [841,] 33.64 64 [842,] 33.68 40 [843,] 33.72 48 [844,] 33.76 55 [845,] 33.80 50 [846,] 33.84 48 [847,] 33.88 52 [848,] 33.92 45 [849,] 33.96 45 [850,] 34.00 51 [851,] 34.04 33 [852,] 34.08 37 [853,] 34.12 45 [854,] 34.16 53 [855,] 34.20 59 [856,] 34.24 49 [857,] 34.28 52 [858,] 34.32 40 [859,] 34.36 43 [860,] 34.40 66 [861,] 34.44 50 [862,] 34.48 42 [863,] 34.52 52 [864,] 34.56 32 [865,] 34.60 34 [866,] 34.64 31 [867,] 34.68 61 [868,] 34.72 51 [869,] 34.76 44 [870,] 34.80 44 [871,] 34.84 56 [872,] 34.88 40 [873,] 34.92 48 [874,] 34.96 52 [875,] 35.00 35 [876,] 35.04 41 [877,] 35.08 31 [878,] 35.12 48 [879,] 35.16 48 [880,] 35.20 46 [881,] 35.24 38 [882,] 35.28 60 [883,] 35.32 50 [884,] 35.36 42 [885,] 35.40 62 [886,] 35.44 42 [887,] 35.48 56 [888,] 35.52 47 [889,] 35.56 44 [890,] 35.60 40 [891,] 35.64 42 [892,] 35.68 53 [893,] 35.72 59 [894,] 35.76 52 [895,] 35.80 71 [896,] 35.84 42 [897,] 35.88 32 [898,] 35.92 46 [899,] 35.96 57 [900,] 36.00 48 [901,] 36.04 60 [902,] 36.08 54 [903,] 36.12 54 [904,] 36.16 40 [905,] 36.20 48 [906,] 36.24 36 [907,] 36.28 69 [908,] 36.32 49 [909,] 36.36 58 [910,] 36.40 57 [911,] 36.44 42 [912,] 36.48 52 [913,] 36.52 56 [914,] 36.56 40 [915,] 36.60 71 [916,] 36.64 47 [917,] 36.68 51 [918,] 36.72 66 [919,] 36.76 48 [920,] 36.80 45 [921,] 36.84 37 [922,] 36.88 65 [923,] 36.92 46 [924,] 36.96 48 [925,] 37.00 37 [926,] 37.04 43 [927,] 37.08 52 [928,] 37.12 40 [929,] 37.16 65 [930,] 37.20 47 [931,] 37.24 50 [932,] 37.28 38 [933,] 37.32 38 [934,] 37.36 44 [935,] 37.40 53 [936,] 37.44 47 [937,] 37.48 44 [938,] 37.52 47 [939,] 37.56 36 [940,] 37.60 51 [941,] 37.64 49 [942,] 37.68 51 [943,] 37.72 34 [944,] 37.76 52 [945,] 37.80 40 [946,] 37.84 46 [947,] 37.88 58 [948,] 37.92 41 [949,] 37.96 52 [950,] 38.00 42 [951,] 38.04 46 [952,] 38.08 49 [953,] 38.12 51 [954,] 38.16 38 [955,] 38.20 40 [956,] 38.24 46 [957,] 38.28 45 [958,] 38.32 61 [959,] 38.36 51 [960,] 38.40 46 [961,] 38.44 49 [962,] 38.48 57 [963,] 38.52 42 [964,] 38.56 57 [965,] 38.60 62 [966,] 38.64 44 [967,] 38.68 42 [968,] 38.72 44 [969,] 38.76 51 [970,] 38.80 38 [971,] 38.84 44 [972,] 38.88 39 [973,] 38.92 41 [974,] 38.96 48 [975,] 39.00 61 [976,] 39.04 47 [977,] 39.08 51 [978,] 39.12 38 [979,] 39.16 65 [980,] 39.20 39 [981,] 39.24 48 [982,] 39.28 45 [983,] 39.32 64 [984,] 39.36 44 [985,] 39.40 33 [986,] 39.44 45 [987,] 39.48 42 [988,] 39.52 36 [989,] 39.56 43 [990,] 39.60 48 [991,] 39.64 44 [992,] 39.68 67 [993,] 39.72 38 [994,] 39.76 47 [995,] 39.80 57 [996,] 39.84 40 [997,] 39.88 55 [998,] 39.92 49 [999,] 39.96 36 [1000,] 40.00 60 $`11_TL (PMT)` [,1] [,2] [1,] 0.64 4 [2,] 1.28 9 [3,] 1.92 0 [4,] 2.56 4 [5,] 3.20 5 [6,] 3.84 7 [7,] 4.48 3 [8,] 5.12 3 [9,] 5.76 4 [10,] 6.40 8 [11,] 7.04 1 [12,] 7.68 3 [13,] 8.32 6 [14,] 8.96 0 [15,] 9.60 7 [16,] 10.24 10 [17,] 10.88 2 [18,] 11.52 3 [19,] 12.16 8 [20,] 12.80 7 [21,] 13.44 2 [22,] 14.08 3 [23,] 14.72 7 [24,] 15.36 3 [25,] 16.00 1 [26,] 16.64 4 [27,] 17.28 5 [28,] 17.92 5 [29,] 18.56 4 [30,] 19.20 10 [31,] 19.84 9 [32,] 20.48 0 [33,] 21.12 2 [34,] 21.76 6 [35,] 22.40 12 [36,] 23.04 6 [37,] 23.68 1 [38,] 24.32 0 [39,] 24.96 0 [40,] 25.60 4 [41,] 26.24 1 [42,] 26.88 4 [43,] 27.52 1 [44,] 28.16 1 [45,] 28.80 3 [46,] 29.44 7 [47,] 30.08 1 [48,] 30.72 21 [49,] 31.36 2 [50,] 32.00 3 [51,] 32.64 4 [52,] 33.28 6 [53,] 33.92 4 [54,] 34.56 6 [55,] 35.20 5 [56,] 35.84 3 [57,] 36.48 12 [58,] 37.12 5 [59,] 37.76 3 [60,] 38.40 9 [61,] 39.04 3 [62,] 39.68 9 [63,] 40.32 11 [64,] 40.96 13 [65,] 41.60 3 [66,] 42.24 4 [67,] 42.88 3 [68,] 43.52 3 [69,] 44.16 4 [70,] 44.80 4 [71,] 45.44 14 [72,] 46.08 5 [73,] 46.72 2 [74,] 47.36 2 [75,] 48.00 2 [76,] 48.64 0 [77,] 49.28 7 [78,] 49.92 9 [79,] 50.56 4 [80,] 51.20 2 [81,] 51.84 9 [82,] 52.48 10 [83,] 53.12 6 [84,] 53.76 5 [85,] 54.40 5 [86,] 55.04 11 [87,] 55.68 13 [88,] 56.32 11 [89,] 56.96 4 [90,] 57.60 13 [91,] 58.24 6 [92,] 58.88 9 [93,] 59.52 10 [94,] 60.16 9 [95,] 60.80 11 [96,] 61.44 16 [97,] 62.08 4 [98,] 62.72 16 [99,] 63.36 18 [100,] 64.00 17 [101,] 64.64 14 [102,] 65.28 18 [103,] 65.92 27 [104,] 66.56 15 [105,] 67.20 22 [106,] 67.84 18 [107,] 68.48 26 [108,] 69.12 22 [109,] 69.76 26 [110,] 70.40 21 [111,] 71.04 29 [112,] 71.68 31 [113,] 72.32 40 [114,] 72.96 19 [115,] 73.60 41 [116,] 74.24 33 [117,] 74.88 43 [118,] 75.52 35 [119,] 76.16 35 [120,] 76.80 45 [121,] 77.44 41 [122,] 78.08 38 [123,] 78.72 59 [124,] 79.36 47 [125,] 80.00 50 [126,] 80.64 70 [127,] 81.28 47 [128,] 81.92 64 [129,] 82.56 62 [130,] 83.20 85 [131,] 83.84 84 [132,] 84.48 98 [133,] 85.12 82 [134,] 85.76 107 [135,] 86.40 86 [136,] 87.04 89 [137,] 87.68 96 [138,] 88.32 105 [139,] 88.96 132 [140,] 89.60 118 [141,] 90.24 145 [142,] 90.88 116 [143,] 91.52 150 [144,] 92.16 142 [145,] 92.80 157 [146,] 93.44 168 [147,] 94.08 151 [148,] 94.72 179 [149,] 95.36 165 [150,] 96.00 169 [151,] 96.64 152 [152,] 97.28 190 [153,] 97.92 236 [154,] 98.56 198 [155,] 99.20 213 [156,] 99.84 233 [157,] 100.48 204 [158,] 101.12 227 [159,] 101.76 228 [160,] 102.40 255 [161,] 103.04 231 [162,] 103.68 232 [163,] 104.32 232 [164,] 104.96 268 [165,] 105.60 255 [166,] 106.24 217 [167,] 106.88 219 [168,] 107.52 242 [169,] 108.16 229 [170,] 108.80 265 [171,] 109.44 210 [172,] 110.08 251 [173,] 110.72 199 [174,] 111.36 208 [175,] 112.00 242 [176,] 112.64 226 [177,] 113.28 217 [178,] 113.92 203 [179,] 114.56 162 [180,] 115.20 207 [181,] 115.84 179 [182,] 116.48 177 [183,] 117.12 147 [184,] 117.76 147 [185,] 118.40 164 [186,] 119.04 120 [187,] 119.68 128 [188,] 120.32 141 [189,] 120.96 117 [190,] 121.60 124 [191,] 122.24 116 [192,] 122.88 93 [193,] 123.52 91 [194,] 124.16 73 [195,] 124.80 61 [196,] 125.44 92 [197,] 126.08 77 [198,] 126.72 68 [199,] 127.36 77 [200,] 128.00 59 [201,] 128.64 74 [202,] 129.28 73 [203,] 129.92 75 [204,] 130.56 103 [205,] 131.20 69 [206,] 131.84 87 [207,] 132.48 66 [208,] 133.12 78 [209,] 133.76 68 [210,] 134.40 76 [211,] 135.04 56 [212,] 135.68 88 [213,] 136.32 77 [214,] 136.96 76 [215,] 137.60 76 [216,] 138.24 99 [217,] 138.88 82 [218,] 139.52 83 [219,] 140.16 69 [220,] 140.80 73 [221,] 141.44 78 [222,] 142.08 58 [223,] 142.72 91 [224,] 143.36 62 [225,] 144.00 110 [226,] 144.64 81 [227,] 145.28 74 [228,] 145.92 62 [229,] 146.56 71 [230,] 147.20 65 [231,] 147.84 79 [232,] 148.48 68 [233,] 149.12 101 [234,] 149.76 73 [235,] 150.40 69 [236,] 151.04 70 [237,] 151.68 85 [238,] 152.32 66 [239,] 152.96 62 [240,] 153.60 78 [241,] 154.24 85 [242,] 154.88 58 [243,] 155.52 70 [244,] 156.16 85 [245,] 156.80 74 [246,] 157.44 60 [247,] 158.08 67 [248,] 158.72 85 [249,] 159.36 60 [250,] 160.00 64 $`12_OSL (PMT)` [,1] [,2] [1,] 0.04 2656 [2,] 0.08 2304 [3,] 0.12 2055 [4,] 0.16 1796 [5,] 0.20 1505 [6,] 0.24 1379 [7,] 0.28 1219 [8,] 0.32 1047 [9,] 0.36 973 [10,] 0.40 869 [11,] 0.44 711 [12,] 0.48 638 [13,] 0.52 630 [14,] 0.56 559 [15,] 0.60 454 [16,] 0.64 491 [17,] 0.68 431 [18,] 0.72 370 [19,] 0.76 351 [20,] 0.80 287 [21,] 0.84 258 [22,] 0.88 301 [23,] 0.92 247 [24,] 0.96 229 [25,] 1.00 236 [26,] 1.04 197 [27,] 1.08 191 [28,] 1.12 202 [29,] 1.16 192 [30,] 1.20 154 [31,] 1.24 172 [32,] 1.28 156 [33,] 1.32 171 [34,] 1.36 142 [35,] 1.40 126 [36,] 1.44 130 [37,] 1.48 128 [38,] 1.52 161 [39,] 1.56 147 [40,] 1.60 137 [41,] 1.64 129 [42,] 1.68 132 [43,] 1.72 133 [44,] 1.76 113 [45,] 1.80 114 [46,] 1.84 126 [47,] 1.88 109 [48,] 1.92 102 [49,] 1.96 127 [50,] 2.00 139 [51,] 2.04 146 [52,] 2.08 99 [53,] 2.12 97 [54,] 2.16 120 [55,] 2.20 111 [56,] 2.24 108 [57,] 2.28 110 [58,] 2.32 96 [59,] 2.36 88 [60,] 2.40 96 [61,] 2.44 88 [62,] 2.48 86 [63,] 2.52 90 [64,] 2.56 101 [65,] 2.60 106 [66,] 2.64 111 [67,] 2.68 96 [68,] 2.72 108 [69,] 2.76 93 [70,] 2.80 97 [71,] 2.84 107 [72,] 2.88 105 [73,] 2.92 110 [74,] 2.96 107 [75,] 3.00 94 [76,] 3.04 105 [77,] 3.08 106 [78,] 3.12 113 [79,] 3.16 102 [80,] 3.20 79 [81,] 3.24 62 [82,] 3.28 86 [83,] 3.32 98 [84,] 3.36 105 [85,] 3.40 85 [86,] 3.44 98 [87,] 3.48 98 [88,] 3.52 81 [89,] 3.56 81 [90,] 3.60 75 [91,] 3.64 98 [92,] 3.68 90 [93,] 3.72 70 [94,] 3.76 69 [95,] 3.80 92 [96,] 3.84 93 [97,] 3.88 107 [98,] 3.92 95 [99,] 3.96 110 [100,] 4.00 95 [101,] 4.04 80 [102,] 4.08 90 [103,] 4.12 77 [104,] 4.16 82 [105,] 4.20 70 [106,] 4.24 79 [107,] 4.28 78 [108,] 4.32 71 [109,] 4.36 91 [110,] 4.40 78 [111,] 4.44 76 [112,] 4.48 64 [113,] 4.52 76 [114,] 4.56 76 [115,] 4.60 86 [116,] 4.64 93 [117,] 4.68 91 [118,] 4.72 84 [119,] 4.76 78 [120,] 4.80 65 [121,] 4.84 86 [122,] 4.88 72 [123,] 4.92 79 [124,] 4.96 94 [125,] 5.00 59 [126,] 5.04 77 [127,] 5.08 70 [128,] 5.12 84 [129,] 5.16 76 [130,] 5.20 86 [131,] 5.24 87 [132,] 5.28 75 [133,] 5.32 81 [134,] 5.36 83 [135,] 5.40 68 [136,] 5.44 82 [137,] 5.48 80 [138,] 5.52 83 [139,] 5.56 43 [140,] 5.60 80 [141,] 5.64 77 [142,] 5.68 69 [143,] 5.72 98 [144,] 5.76 72 [145,] 5.80 82 [146,] 5.84 91 [147,] 5.88 85 [148,] 5.92 66 [149,] 5.96 76 [150,] 6.00 57 [151,] 6.04 80 [152,] 6.08 70 [153,] 6.12 60 [154,] 6.16 67 [155,] 6.20 59 [156,] 6.24 74 [157,] 6.28 68 [158,] 6.32 75 [159,] 6.36 89 [160,] 6.40 82 [161,] 6.44 66 [162,] 6.48 67 [163,] 6.52 84 [164,] 6.56 83 [165,] 6.60 73 [166,] 6.64 99 [167,] 6.68 72 [168,] 6.72 70 [169,] 6.76 78 [170,] 6.80 55 [171,] 6.84 88 [172,] 6.88 48 [173,] 6.92 69 [174,] 6.96 73 [175,] 7.00 66 [176,] 7.04 77 [177,] 7.08 83 [178,] 7.12 78 [179,] 7.16 72 [180,] 7.20 73 [181,] 7.24 72 [182,] 7.28 78 [183,] 7.32 64 [184,] 7.36 72 [185,] 7.40 71 [186,] 7.44 78 [187,] 7.48 66 [188,] 7.52 66 [189,] 7.56 65 [190,] 7.60 67 [191,] 7.64 78 [192,] 7.68 77 [193,] 7.72 67 [194,] 7.76 79 [195,] 7.80 72 [196,] 7.84 73 [197,] 7.88 69 [198,] 7.92 61 [199,] 7.96 58 [200,] 8.00 69 [201,] 8.04 63 [202,] 8.08 69 [203,] 8.12 63 [204,] 8.16 56 [205,] 8.20 76 [206,] 8.24 74 [207,] 8.28 65 [208,] 8.32 70 [209,] 8.36 89 [210,] 8.40 72 [211,] 8.44 81 [212,] 8.48 60 [213,] 8.52 78 [214,] 8.56 61 [215,] 8.60 65 [216,] 8.64 68 [217,] 8.68 86 [218,] 8.72 79 [219,] 8.76 72 [220,] 8.80 63 [221,] 8.84 73 [222,] 8.88 85 [223,] 8.92 60 [224,] 8.96 65 [225,] 9.00 69 [226,] 9.04 76 [227,] 9.08 73 [228,] 9.12 56 [229,] 9.16 87 [230,] 9.20 69 [231,] 9.24 60 [232,] 9.28 72 [233,] 9.32 62 [234,] 9.36 86 [235,] 9.40 58 [236,] 9.44 64 [237,] 9.48 71 [238,] 9.52 53 [239,] 9.56 75 [240,] 9.60 41 [241,] 9.64 58 [242,] 9.68 67 [243,] 9.72 52 [244,] 9.76 53 [245,] 9.80 73 [246,] 9.84 61 [247,] 9.88 71 [248,] 9.92 64 [249,] 9.96 74 [250,] 10.00 64 [251,] 10.04 85 [252,] 10.08 63 [253,] 10.12 66 [254,] 10.16 73 [255,] 10.20 65 [256,] 10.24 67 [257,] 10.28 67 [258,] 10.32 63 [259,] 10.36 75 [260,] 10.40 60 [261,] 10.44 57 [262,] 10.48 83 [263,] 10.52 88 [264,] 10.56 57 [265,] 10.60 49 [266,] 10.64 49 [267,] 10.68 63 [268,] 10.72 55 [269,] 10.76 60 [270,] 10.80 71 [271,] 10.84 61 [272,] 10.88 61 [273,] 10.92 65 [274,] 10.96 45 [275,] 11.00 65 [276,] 11.04 63 [277,] 11.08 64 [278,] 11.12 64 [279,] 11.16 70 [280,] 11.20 51 [281,] 11.24 73 [282,] 11.28 49 [283,] 11.32 64 [284,] 11.36 75 [285,] 11.40 38 [286,] 11.44 58 [287,] 11.48 55 [288,] 11.52 70 [289,] 11.56 46 [290,] 11.60 61 [291,] 11.64 58 [292,] 11.68 54 [293,] 11.72 69 [294,] 11.76 47 [295,] 11.80 57 [296,] 11.84 51 [297,] 11.88 58 [298,] 11.92 53 [299,] 11.96 68 [300,] 12.00 61 [301,] 12.04 61 [302,] 12.08 60 [303,] 12.12 45 [304,] 12.16 72 [305,] 12.20 46 [306,] 12.24 54 [307,] 12.28 65 [308,] 12.32 74 [309,] 12.36 53 [310,] 12.40 57 [311,] 12.44 67 [312,] 12.48 57 [313,] 12.52 88 [314,] 12.56 53 [315,] 12.60 56 [316,] 12.64 70 [317,] 12.68 67 [318,] 12.72 63 [319,] 12.76 60 [320,] 12.80 67 [321,] 12.84 62 [322,] 12.88 55 [323,] 12.92 77 [324,] 12.96 63 [325,] 13.00 50 [326,] 13.04 66 [327,] 13.08 69 [328,] 13.12 70 [329,] 13.16 83 [330,] 13.20 63 [331,] 13.24 67 [332,] 13.28 51 [333,] 13.32 52 [334,] 13.36 78 [335,] 13.40 60 [336,] 13.44 68 [337,] 13.48 49 [338,] 13.52 64 [339,] 13.56 58 [340,] 13.60 68 [341,] 13.64 69 [342,] 13.68 60 [343,] 13.72 52 [344,] 13.76 52 [345,] 13.80 70 [346,] 13.84 57 [347,] 13.88 61 [348,] 13.92 56 [349,] 13.96 54 [350,] 14.00 64 [351,] 14.04 66 [352,] 14.08 55 [353,] 14.12 57 [354,] 14.16 65 [355,] 14.20 83 [356,] 14.24 56 [357,] 14.28 54 [358,] 14.32 58 [359,] 14.36 70 [360,] 14.40 44 [361,] 14.44 67 [362,] 14.48 61 [363,] 14.52 53 [364,] 14.56 76 [365,] 14.60 58 [366,] 14.64 56 [367,] 14.68 60 [368,] 14.72 56 [369,] 14.76 66 [370,] 14.80 67 [371,] 14.84 48 [372,] 14.88 68 [373,] 14.92 53 [374,] 14.96 59 [375,] 15.00 59 [376,] 15.04 66 [377,] 15.08 68 [378,] 15.12 73 [379,] 15.16 63 [380,] 15.20 55 [381,] 15.24 68 [382,] 15.28 59 [383,] 15.32 48 [384,] 15.36 94 [385,] 15.40 57 [386,] 15.44 71 [387,] 15.48 56 [388,] 15.52 56 [389,] 15.56 53 [390,] 15.60 67 [391,] 15.64 58 [392,] 15.68 68 [393,] 15.72 66 [394,] 15.76 53 [395,] 15.80 58 [396,] 15.84 63 [397,] 15.88 76 [398,] 15.92 42 [399,] 15.96 66 [400,] 16.00 76 [401,] 16.04 62 [402,] 16.08 63 [403,] 16.12 38 [404,] 16.16 63 [405,] 16.20 68 [406,] 16.24 60 [407,] 16.28 48 [408,] 16.32 58 [409,] 16.36 60 [410,] 16.40 67 [411,] 16.44 58 [412,] 16.48 72 [413,] 16.52 39 [414,] 16.56 45 [415,] 16.60 38 [416,] 16.64 67 [417,] 16.68 50 [418,] 16.72 73 [419,] 16.76 73 [420,] 16.80 61 [421,] 16.84 70 [422,] 16.88 60 [423,] 16.92 55 [424,] 16.96 66 [425,] 17.00 65 [426,] 17.04 60 [427,] 17.08 54 [428,] 17.12 53 [429,] 17.16 70 [430,] 17.20 39 [431,] 17.24 55 [432,] 17.28 69 [433,] 17.32 54 [434,] 17.36 65 [435,] 17.40 80 [436,] 17.44 39 [437,] 17.48 63 [438,] 17.52 64 [439,] 17.56 66 [440,] 17.60 60 [441,] 17.64 62 [442,] 17.68 50 [443,] 17.72 57 [444,] 17.76 56 [445,] 17.80 54 [446,] 17.84 48 [447,] 17.88 52 [448,] 17.92 42 [449,] 17.96 60 [450,] 18.00 56 [451,] 18.04 47 [452,] 18.08 56 [453,] 18.12 63 [454,] 18.16 66 [455,] 18.20 48 [456,] 18.24 58 [457,] 18.28 62 [458,] 18.32 54 [459,] 18.36 55 [460,] 18.40 64 [461,] 18.44 37 [462,] 18.48 72 [463,] 18.52 49 [464,] 18.56 44 [465,] 18.60 72 [466,] 18.64 44 [467,] 18.68 66 [468,] 18.72 60 [469,] 18.76 69 [470,] 18.80 55 [471,] 18.84 59 [472,] 18.88 52 [473,] 18.92 69 [474,] 18.96 47 [475,] 19.00 36 [476,] 19.04 40 [477,] 19.08 61 [478,] 19.12 52 [479,] 19.16 58 [480,] 19.20 56 [481,] 19.24 54 [482,] 19.28 48 [483,] 19.32 67 [484,] 19.36 68 [485,] 19.40 85 [486,] 19.44 58 [487,] 19.48 55 [488,] 19.52 69 [489,] 19.56 58 [490,] 19.60 50 [491,] 19.64 44 [492,] 19.68 43 [493,] 19.72 56 [494,] 19.76 63 [495,] 19.80 47 [496,] 19.84 65 [497,] 19.88 59 [498,] 19.92 51 [499,] 19.96 29 [500,] 20.00 54 [501,] 20.04 65 [502,] 20.08 74 [503,] 20.12 63 [504,] 20.16 58 [505,] 20.20 34 [506,] 20.24 51 [507,] 20.28 57 [508,] 20.32 44 [509,] 20.36 53 [510,] 20.40 66 [511,] 20.44 46 [512,] 20.48 67 [513,] 20.52 59 [514,] 20.56 51 [515,] 20.60 54 [516,] 20.64 54 [517,] 20.68 60 [518,] 20.72 58 [519,] 20.76 66 [520,] 20.80 64 [521,] 20.84 72 [522,] 20.88 33 [523,] 20.92 53 [524,] 20.96 52 [525,] 21.00 63 [526,] 21.04 58 [527,] 21.08 46 [528,] 21.12 47 [529,] 21.16 65 [530,] 21.20 68 [531,] 21.24 40 [532,] 21.28 51 [533,] 21.32 54 [534,] 21.36 41 [535,] 21.40 55 [536,] 21.44 54 [537,] 21.48 63 [538,] 21.52 81 [539,] 21.56 50 [540,] 21.60 55 [541,] 21.64 83 [542,] 21.68 68 [543,] 21.72 51 [544,] 21.76 52 [545,] 21.80 65 [546,] 21.84 66 [547,] 21.88 45 [548,] 21.92 57 [549,] 21.96 67 [550,] 22.00 58 [551,] 22.04 57 [552,] 22.08 59 [553,] 22.12 56 [554,] 22.16 58 [555,] 22.20 47 [556,] 22.24 56 [557,] 22.28 50 [558,] 22.32 56 [559,] 22.36 45 [560,] 22.40 67 [561,] 22.44 51 [562,] 22.48 57 [563,] 22.52 58 [564,] 22.56 45 [565,] 22.60 37 [566,] 22.64 59 [567,] 22.68 68 [568,] 22.72 54 [569,] 22.76 56 [570,] 22.80 66 [571,] 22.84 49 [572,] 22.88 64 [573,] 22.92 64 [574,] 22.96 45 [575,] 23.00 77 [576,] 23.04 58 [577,] 23.08 37 [578,] 23.12 48 [579,] 23.16 67 [580,] 23.20 69 [581,] 23.24 65 [582,] 23.28 44 [583,] 23.32 43 [584,] 23.36 55 [585,] 23.40 69 [586,] 23.44 54 [587,] 23.48 68 [588,] 23.52 45 [589,] 23.56 64 [590,] 23.60 64 [591,] 23.64 51 [592,] 23.68 70 [593,] 23.72 57 [594,] 23.76 44 [595,] 23.80 67 [596,] 23.84 62 [597,] 23.88 52 [598,] 23.92 51 [599,] 23.96 50 [600,] 24.00 65 [601,] 24.04 40 [602,] 24.08 60 [603,] 24.12 56 [604,] 24.16 50 [605,] 24.20 60 [606,] 24.24 59 [607,] 24.28 57 [608,] 24.32 52 [609,] 24.36 55 [610,] 24.40 56 [611,] 24.44 53 [612,] 24.48 65 [613,] 24.52 77 [614,] 24.56 60 [615,] 24.60 57 [616,] 24.64 61 [617,] 24.68 44 [618,] 24.72 54 [619,] 24.76 42 [620,] 24.80 53 [621,] 24.84 64 [622,] 24.88 35 [623,] 24.92 59 [624,] 24.96 61 [625,] 25.00 46 [626,] 25.04 58 [627,] 25.08 63 [628,] 25.12 55 [629,] 25.16 61 [630,] 25.20 62 [631,] 25.24 31 [632,] 25.28 67 [633,] 25.32 50 [634,] 25.36 40 [635,] 25.40 44 [636,] 25.44 47 [637,] 25.48 54 [638,] 25.52 65 [639,] 25.56 56 [640,] 25.60 63 [641,] 25.64 43 [642,] 25.68 57 [643,] 25.72 50 [644,] 25.76 49 [645,] 25.80 47 [646,] 25.84 41 [647,] 25.88 64 [648,] 25.92 45 [649,] 25.96 44 [650,] 26.00 71 [651,] 26.04 57 [652,] 26.08 76 [653,] 26.12 51 [654,] 26.16 49 [655,] 26.20 57 [656,] 26.24 53 [657,] 26.28 61 [658,] 26.32 47 [659,] 26.36 56 [660,] 26.40 43 [661,] 26.44 53 [662,] 26.48 43 [663,] 26.52 64 [664,] 26.56 63 [665,] 26.60 52 [666,] 26.64 47 [667,] 26.68 45 [668,] 26.72 45 [669,] 26.76 57 [670,] 26.80 58 [671,] 26.84 61 [672,] 26.88 45 [673,] 26.92 50 [674,] 26.96 49 [675,] 27.00 60 [676,] 27.04 55 [677,] 27.08 76 [678,] 27.12 50 [679,] 27.16 61 [680,] 27.20 49 [681,] 27.24 63 [682,] 27.28 50 [683,] 27.32 57 [684,] 27.36 63 [685,] 27.40 63 [686,] 27.44 37 [687,] 27.48 53 [688,] 27.52 49 [689,] 27.56 75 [690,] 27.60 43 [691,] 27.64 67 [692,] 27.68 54 [693,] 27.72 60 [694,] 27.76 43 [695,] 27.80 58 [696,] 27.84 44 [697,] 27.88 59 [698,] 27.92 70 [699,] 27.96 39 [700,] 28.00 55 [701,] 28.04 57 [702,] 28.08 52 [703,] 28.12 86 [704,] 28.16 53 [705,] 28.20 45 [706,] 28.24 56 [707,] 28.28 54 [708,] 28.32 62 [709,] 28.36 52 [710,] 28.40 51 [711,] 28.44 47 [712,] 28.48 50 [713,] 28.52 51 [714,] 28.56 44 [715,] 28.60 60 [716,] 28.64 51 [717,] 28.68 47 [718,] 28.72 46 [719,] 28.76 59 [720,] 28.80 43 [721,] 28.84 41 [722,] 28.88 69 [723,] 28.92 37 [724,] 28.96 55 [725,] 29.00 70 [726,] 29.04 49 [727,] 29.08 70 [728,] 29.12 53 [729,] 29.16 56 [730,] 29.20 55 [731,] 29.24 34 [732,] 29.28 62 [733,] 29.32 66 [734,] 29.36 47 [735,] 29.40 82 [736,] 29.44 37 [737,] 29.48 50 [738,] 29.52 63 [739,] 29.56 53 [740,] 29.60 62 [741,] 29.64 59 [742,] 29.68 41 [743,] 29.72 55 [744,] 29.76 52 [745,] 29.80 52 [746,] 29.84 55 [747,] 29.88 60 [748,] 29.92 49 [749,] 29.96 46 [750,] 30.00 55 [751,] 30.04 50 [752,] 30.08 58 [753,] 30.12 62 [754,] 30.16 51 [755,] 30.20 43 [756,] 30.24 43 [757,] 30.28 63 [758,] 30.32 33 [759,] 30.36 55 [760,] 30.40 57 [761,] 30.44 40 [762,] 30.48 66 [763,] 30.52 52 [764,] 30.56 51 [765,] 30.60 52 [766,] 30.64 54 [767,] 30.68 49 [768,] 30.72 41 [769,] 30.76 48 [770,] 30.80 50 [771,] 30.84 66 [772,] 30.88 48 [773,] 30.92 42 [774,] 30.96 40 [775,] 31.00 69 [776,] 31.04 49 [777,] 31.08 56 [778,] 31.12 45 [779,] 31.16 47 [780,] 31.20 43 [781,] 31.24 61 [782,] 31.28 57 [783,] 31.32 42 [784,] 31.36 74 [785,] 31.40 59 [786,] 31.44 64 [787,] 31.48 64 [788,] 31.52 48 [789,] 31.56 56 [790,] 31.60 67 [791,] 31.64 31 [792,] 31.68 43 [793,] 31.72 43 [794,] 31.76 43 [795,] 31.80 51 [796,] 31.84 44 [797,] 31.88 56 [798,] 31.92 69 [799,] 31.96 49 [800,] 32.00 36 [801,] 32.04 72 [802,] 32.08 46 [803,] 32.12 54 [804,] 32.16 63 [805,] 32.20 55 [806,] 32.24 57 [807,] 32.28 39 [808,] 32.32 71 [809,] 32.36 47 [810,] 32.40 69 [811,] 32.44 48 [812,] 32.48 71 [813,] 32.52 51 [814,] 32.56 60 [815,] 32.60 49 [816,] 32.64 58 [817,] 32.68 47 [818,] 32.72 51 [819,] 32.76 57 [820,] 32.80 41 [821,] 32.84 57 [822,] 32.88 62 [823,] 32.92 49 [824,] 32.96 64 [825,] 33.00 46 [826,] 33.04 54 [827,] 33.08 52 [828,] 33.12 54 [829,] 33.16 46 [830,] 33.20 67 [831,] 33.24 47 [832,] 33.28 50 [833,] 33.32 36 [834,] 33.36 45 [835,] 33.40 56 [836,] 33.44 42 [837,] 33.48 47 [838,] 33.52 51 [839,] 33.56 41 [840,] 33.60 57 [841,] 33.64 32 [842,] 33.68 62 [843,] 33.72 44 [844,] 33.76 46 [845,] 33.80 49 [846,] 33.84 52 [847,] 33.88 41 [848,] 33.92 52 [849,] 33.96 44 [850,] 34.00 60 [851,] 34.04 55 [852,] 34.08 56 [853,] 34.12 47 [854,] 34.16 43 [855,] 34.20 57 [856,] 34.24 62 [857,] 34.28 61 [858,] 34.32 48 [859,] 34.36 51 [860,] 34.40 63 [861,] 34.44 68 [862,] 34.48 49 [863,] 34.52 48 [864,] 34.56 65 [865,] 34.60 57 [866,] 34.64 51 [867,] 34.68 44 [868,] 34.72 49 [869,] 34.76 63 [870,] 34.80 58 [871,] 34.84 56 [872,] 34.88 70 [873,] 34.92 47 [874,] 34.96 42 [875,] 35.00 53 [876,] 35.04 41 [877,] 35.08 59 [878,] 35.12 42 [879,] 35.16 55 [880,] 35.20 53 [881,] 35.24 72 [882,] 35.28 59 [883,] 35.32 59 [884,] 35.36 40 [885,] 35.40 61 [886,] 35.44 38 [887,] 35.48 49 [888,] 35.52 55 [889,] 35.56 58 [890,] 35.60 69 [891,] 35.64 48 [892,] 35.68 44 [893,] 35.72 47 [894,] 35.76 56 [895,] 35.80 40 [896,] 35.84 49 [897,] 35.88 38 [898,] 35.92 57 [899,] 35.96 45 [900,] 36.00 39 [901,] 36.04 54 [902,] 36.08 35 [903,] 36.12 59 [904,] 36.16 34 [905,] 36.20 55 [906,] 36.24 45 [907,] 36.28 40 [908,] 36.32 58 [909,] 36.36 51 [910,] 36.40 57 [911,] 36.44 61 [912,] 36.48 44 [913,] 36.52 49 [914,] 36.56 61 [915,] 36.60 74 [916,] 36.64 61 [917,] 36.68 50 [918,] 36.72 63 [919,] 36.76 53 [920,] 36.80 68 [921,] 36.84 47 [922,] 36.88 62 [923,] 36.92 47 [924,] 36.96 61 [925,] 37.00 64 [926,] 37.04 57 [927,] 37.08 67 [928,] 37.12 49 [929,] 37.16 53 [930,] 37.20 41 [931,] 37.24 49 [932,] 37.28 41 [933,] 37.32 63 [934,] 37.36 55 [935,] 37.40 39 [936,] 37.44 45 [937,] 37.48 45 [938,] 37.52 60 [939,] 37.56 56 [940,] 37.60 43 [941,] 37.64 57 [942,] 37.68 41 [943,] 37.72 44 [944,] 37.76 38 [945,] 37.80 48 [946,] 37.84 74 [947,] 37.88 55 [948,] 37.92 38 [949,] 37.96 56 [950,] 38.00 52 [951,] 38.04 47 [952,] 38.08 58 [953,] 38.12 63 [954,] 38.16 49 [955,] 38.20 47 [956,] 38.24 37 [957,] 38.28 67 [958,] 38.32 51 [959,] 38.36 57 [960,] 38.40 63 [961,] 38.44 47 [962,] 38.48 35 [963,] 38.52 54 [964,] 38.56 53 [965,] 38.60 51 [966,] 38.64 48 [967,] 38.68 54 [968,] 38.72 38 [969,] 38.76 46 [970,] 38.80 62 [971,] 38.84 44 [972,] 38.88 50 [973,] 38.92 43 [974,] 38.96 52 [975,] 39.00 56 [976,] 39.04 41 [977,] 39.08 59 [978,] 39.12 57 [979,] 39.16 51 [980,] 39.20 33 [981,] 39.24 52 [982,] 39.28 63 [983,] 39.32 61 [984,] 39.36 43 [985,] 39.40 37 [986,] 39.44 43 [987,] 39.48 79 [988,] 39.52 54 [989,] 39.56 46 [990,] 39.60 40 [991,] 39.64 44 [992,] 39.68 34 [993,] 39.72 36 [994,] 39.76 49 [995,] 39.80 64 [996,] 39.84 42 [997,] 39.88 41 [998,] 39.92 48 [999,] 39.96 49 [1000,] 40.00 51 $`13_TL (PMT)` [,1] [,2] [1,] 0.884 11 [2,] 1.768 11 [3,] 2.652 2 [4,] 3.536 3 [5,] 4.420 4 [6,] 5.304 2 [7,] 6.188 9 [8,] 7.072 0 [9,] 7.956 12 [10,] 8.840 8 [11,] 9.724 2 [12,] 10.608 0 [13,] 11.492 4 [14,] 12.376 5 [15,] 13.260 0 [16,] 14.144 6 [17,] 15.028 10 [18,] 15.912 3 [19,] 16.796 5 [20,] 17.680 3 [21,] 18.564 6 [22,] 19.448 8 [23,] 20.332 4 [24,] 21.216 4 [25,] 22.100 5 [26,] 22.984 3 [27,] 23.868 0 [28,] 24.752 2 [29,] 25.636 2 [30,] 26.520 1 [31,] 27.404 6 [32,] 28.288 1 [33,] 29.172 2 [34,] 30.056 8 [35,] 30.940 4 [36,] 31.824 2 [37,] 32.708 8 [38,] 33.592 8 [39,] 34.476 8 [40,] 35.360 3 [41,] 36.244 3 [42,] 37.128 3 [43,] 38.012 5 [44,] 38.896 3 [45,] 39.780 6 [46,] 40.664 3 [47,] 41.548 10 [48,] 42.432 8 [49,] 43.316 1 [50,] 44.200 5 [51,] 45.084 8 [52,] 45.968 3 [53,] 46.852 5 [54,] 47.736 1 [55,] 48.620 11 [56,] 49.504 3 [57,] 50.388 2 [58,] 51.272 5 [59,] 52.156 5 [60,] 53.040 4 [61,] 53.924 3 [62,] 54.808 5 [63,] 55.692 2 [64,] 56.576 6 [65,] 57.460 3 [66,] 58.344 3 [67,] 59.228 6 [68,] 60.112 3 [69,] 60.996 8 [70,] 61.880 7 [71,] 62.764 6 [72,] 63.648 7 [73,] 64.532 4 [74,] 65.416 2 [75,] 66.300 8 [76,] 67.184 6 [77,] 68.068 0 [78,] 68.952 4 [79,] 69.836 5 [80,] 70.720 11 [81,] 71.604 7 [82,] 72.488 10 [83,] 73.372 12 [84,] 74.256 3 [85,] 75.140 15 [86,] 76.024 4 [87,] 76.908 10 [88,] 77.792 18 [89,] 78.676 15 [90,] 79.560 12 [91,] 80.444 13 [92,] 81.328 17 [93,] 82.212 7 [94,] 83.096 24 [95,] 83.980 9 [96,] 84.864 31 [97,] 85.748 16 [98,] 86.632 15 [99,] 87.516 27 [100,] 88.400 11 [101,] 89.284 24 [102,] 90.168 25 [103,] 91.052 22 [104,] 91.936 40 [105,] 92.820 27 [106,] 93.704 17 [107,] 94.588 35 [108,] 95.472 25 [109,] 96.356 56 [110,] 97.240 39 [111,] 98.124 50 [112,] 99.008 36 [113,] 99.892 72 [114,] 100.776 56 [115,] 101.660 42 [116,] 102.544 36 [117,] 103.428 65 [118,] 104.312 50 [119,] 105.196 64 [120,] 106.080 74 [121,] 106.964 92 [122,] 107.848 80 [123,] 108.732 81 [124,] 109.616 96 [125,] 110.500 108 [126,] 111.384 109 [127,] 112.268 114 [128,] 113.152 103 [129,] 114.036 134 [130,] 114.920 140 [131,] 115.804 149 [132,] 116.688 151 [133,] 117.572 162 [134,] 118.456 163 [135,] 119.340 201 [136,] 120.224 179 [137,] 121.108 219 [138,] 121.992 248 [139,] 122.876 220 [140,] 123.760 239 [141,] 124.644 257 [142,] 125.528 288 [143,] 126.412 276 [144,] 127.296 263 [145,] 128.180 275 [146,] 129.064 281 [147,] 129.948 332 [148,] 130.832 376 [149,] 131.716 371 [150,] 132.600 358 [151,] 133.484 371 [152,] 134.368 391 [153,] 135.252 403 [154,] 136.136 396 [155,] 137.020 456 [156,] 137.904 419 [157,] 138.788 419 [158,] 139.672 446 [159,] 140.556 418 [160,] 141.440 454 [161,] 142.324 454 [162,] 143.208 465 [163,] 144.092 494 [164,] 144.976 447 [165,] 145.860 475 [166,] 146.744 451 [167,] 147.628 430 [168,] 148.512 482 [169,] 149.396 480 [170,] 150.280 463 [171,] 151.164 473 [172,] 152.048 492 [173,] 152.932 480 [174,] 153.816 450 [175,] 154.700 437 [176,] 155.584 488 [177,] 156.468 457 [178,] 157.352 466 [179,] 158.236 485 [180,] 159.120 414 [181,] 160.004 424 [182,] 160.888 456 [183,] 161.772 428 [184,] 162.656 428 [185,] 163.540 480 [186,] 164.424 442 [187,] 165.308 457 [188,] 166.192 474 [189,] 167.076 449 [190,] 167.960 495 [191,] 168.844 451 [192,] 169.728 521 [193,] 170.612 456 [194,] 171.496 476 [195,] 172.380 472 [196,] 173.264 467 [197,] 174.148 474 [198,] 175.032 450 [199,] 175.916 515 [200,] 176.800 469 [201,] 177.684 483 [202,] 178.568 429 [203,] 179.452 469 [204,] 180.336 458 [205,] 181.220 480 [206,] 182.104 446 [207,] 182.988 491 [208,] 183.872 454 [209,] 184.756 526 [210,] 185.640 441 [211,] 186.524 472 [212,] 187.408 520 [213,] 188.292 491 [214,] 189.176 458 [215,] 190.060 510 [216,] 190.944 540 [217,] 191.828 519 [218,] 192.712 549 [219,] 193.596 507 [220,] 194.480 520 [221,] 195.364 496 [222,] 196.248 524 [223,] 197.132 587 [224,] 198.016 546 [225,] 198.900 554 [226,] 199.784 581 [227,] 200.668 583 [228,] 201.552 582 [229,] 202.436 574 [230,] 203.320 630 [231,] 204.204 592 [232,] 205.088 645 [233,] 205.972 574 [234,] 206.856 560 [235,] 207.740 630 [236,] 208.624 595 [237,] 209.508 612 [238,] 210.392 642 [239,] 211.276 622 [240,] 212.160 589 [241,] 213.044 633 [242,] 213.928 565 [243,] 214.812 613 [244,] 215.696 646 [245,] 216.580 613 [246,] 217.464 556 [247,] 218.348 617 [248,] 219.232 595 [249,] 220.116 628 [250,] 221.000 213 $`14_OSL (PMT)` [,1] [,2] [1,] 0.04 12801 [2,] 0.08 10899 [3,] 0.12 9374 [4,] 0.16 7790 [5,] 0.20 6619 [6,] 0.24 5908 [7,] 0.28 5074 [8,] 0.32 4316 [9,] 0.36 3749 [10,] 0.40 3334 [11,] 0.44 2885 [12,] 0.48 2446 [13,] 0.52 2211 [14,] 0.56 2105 [15,] 0.60 1835 [16,] 0.64 1513 [17,] 0.68 1376 [18,] 0.72 1296 [19,] 0.76 1110 [20,] 0.80 1068 [21,] 0.84 937 [22,] 0.88 840 [23,] 0.92 776 [24,] 0.96 746 [25,] 1.00 658 [26,] 1.04 610 [27,] 1.08 564 [28,] 1.12 533 [29,] 1.16 509 [30,] 1.20 465 [31,] 1.24 434 [32,] 1.28 415 [33,] 1.32 405 [34,] 1.36 352 [35,] 1.40 366 [36,] 1.44 316 [37,] 1.48 305 [38,] 1.52 348 [39,] 1.56 274 [40,] 1.60 301 [41,] 1.64 239 [42,] 1.68 298 [43,] 1.72 313 [44,] 1.76 270 [45,] 1.80 261 [46,] 1.84 236 [47,] 1.88 267 [48,] 1.92 225 [49,] 1.96 223 [50,] 2.00 183 [51,] 2.04 197 [52,] 2.08 208 [53,] 2.12 196 [54,] 2.16 169 [55,] 2.20 197 [56,] 2.24 203 [57,] 2.28 160 [58,] 2.32 195 [59,] 2.36 180 [60,] 2.40 201 [61,] 2.44 159 [62,] 2.48 182 [63,] 2.52 187 [64,] 2.56 151 [65,] 2.60 151 [66,] 2.64 180 [67,] 2.68 174 [68,] 2.72 156 [69,] 2.76 192 [70,] 2.80 142 [71,] 2.84 150 [72,] 2.88 168 [73,] 2.92 159 [74,] 2.96 138 [75,] 3.00 137 [76,] 3.04 129 [77,] 3.08 135 [78,] 3.12 138 [79,] 3.16 150 [80,] 3.20 140 [81,] 3.24 177 [82,] 3.28 128 [83,] 3.32 141 [84,] 3.36 140 [85,] 3.40 173 [86,] 3.44 132 [87,] 3.48 162 [88,] 3.52 115 [89,] 3.56 124 [90,] 3.60 130 [91,] 3.64 151 [92,] 3.68 150 [93,] 3.72 134 [94,] 3.76 140 [95,] 3.80 149 [96,] 3.84 149 [97,] 3.88 118 [98,] 3.92 129 [99,] 3.96 122 [100,] 4.00 115 [101,] 4.04 117 [102,] 4.08 125 [103,] 4.12 148 [104,] 4.16 124 [105,] 4.20 104 [106,] 4.24 137 [107,] 4.28 113 [108,] 4.32 147 [109,] 4.36 125 [110,] 4.40 125 [111,] 4.44 134 [112,] 4.48 113 [113,] 4.52 116 [114,] 4.56 117 [115,] 4.60 129 [116,] 4.64 143 [117,] 4.68 114 [118,] 4.72 105 [119,] 4.76 110 [120,] 4.80 119 [121,] 4.84 104 [122,] 4.88 121 [123,] 4.92 120 [124,] 4.96 114 [125,] 5.00 99 [126,] 5.04 103 [127,] 5.08 127 [128,] 5.12 91 [129,] 5.16 114 [130,] 5.20 116 [131,] 5.24 103 [132,] 5.28 104 [133,] 5.32 112 [134,] 5.36 115 [135,] 5.40 122 [136,] 5.44 110 [137,] 5.48 83 [138,] 5.52 118 [139,] 5.56 132 [140,] 5.60 112 [141,] 5.64 133 [142,] 5.68 107 [143,] 5.72 110 [144,] 5.76 96 [145,] 5.80 122 [146,] 5.84 88 [147,] 5.88 106 [148,] 5.92 104 [149,] 5.96 92 [150,] 6.00 108 [151,] 6.04 100 [152,] 6.08 111 [153,] 6.12 97 [154,] 6.16 106 [155,] 6.20 95 [156,] 6.24 89 [157,] 6.28 96 [158,] 6.32 119 [159,] 6.36 92 [160,] 6.40 99 [161,] 6.44 99 [162,] 6.48 110 [163,] 6.52 126 [164,] 6.56 88 [165,] 6.60 120 [166,] 6.64 92 [167,] 6.68 88 [168,] 6.72 100 [169,] 6.76 119 [170,] 6.80 89 [171,] 6.84 92 [172,] 6.88 96 [173,] 6.92 107 [174,] 6.96 101 [175,] 7.00 116 [176,] 7.04 101 [177,] 7.08 98 [178,] 7.12 110 [179,] 7.16 102 [180,] 7.20 103 [181,] 7.24 101 [182,] 7.28 93 [183,] 7.32 122 [184,] 7.36 78 [185,] 7.40 134 [186,] 7.44 101 [187,] 7.48 91 [188,] 7.52 94 [189,] 7.56 106 [190,] 7.60 98 [191,] 7.64 105 [192,] 7.68 109 [193,] 7.72 102 [194,] 7.76 103 [195,] 7.80 119 [196,] 7.84 85 [197,] 7.88 99 [198,] 7.92 86 [199,] 7.96 85 [200,] 8.00 96 [201,] 8.04 88 [202,] 8.08 92 [203,] 8.12 87 [204,] 8.16 121 [205,] 8.20 103 [206,] 8.24 90 [207,] 8.28 90 [208,] 8.32 107 [209,] 8.36 101 [210,] 8.40 87 [211,] 8.44 93 [212,] 8.48 90 [213,] 8.52 91 [214,] 8.56 78 [215,] 8.60 81 [216,] 8.64 122 [217,] 8.68 100 [218,] 8.72 84 [219,] 8.76 86 [220,] 8.80 96 [221,] 8.84 91 [222,] 8.88 77 [223,] 8.92 94 [224,] 8.96 82 [225,] 9.00 86 [226,] 9.04 85 [227,] 9.08 90 [228,] 9.12 95 [229,] 9.16 78 [230,] 9.20 96 [231,] 9.24 82 [232,] 9.28 70 [233,] 9.32 93 [234,] 9.36 83 [235,] 9.40 91 [236,] 9.44 125 [237,] 9.48 86 [238,] 9.52 105 [239,] 9.56 93 [240,] 9.60 95 [241,] 9.64 98 [242,] 9.68 83 [243,] 9.72 86 [244,] 9.76 88 [245,] 9.80 95 [246,] 9.84 102 [247,] 9.88 108 [248,] 9.92 87 [249,] 9.96 83 [250,] 10.00 97 [251,] 10.04 83 [252,] 10.08 84 [253,] 10.12 75 [254,] 10.16 104 [255,] 10.20 83 [256,] 10.24 95 [257,] 10.28 86 [258,] 10.32 89 [259,] 10.36 92 [260,] 10.40 91 [261,] 10.44 89 [262,] 10.48 84 [263,] 10.52 84 [264,] 10.56 83 [265,] 10.60 83 [266,] 10.64 75 [267,] 10.68 87 [268,] 10.72 104 [269,] 10.76 98 [270,] 10.80 101 [271,] 10.84 78 [272,] 10.88 103 [273,] 10.92 82 [274,] 10.96 107 [275,] 11.00 90 [276,] 11.04 108 [277,] 11.08 74 [278,] 11.12 81 [279,] 11.16 75 [280,] 11.20 81 [281,] 11.24 80 [282,] 11.28 79 [283,] 11.32 87 [284,] 11.36 73 [285,] 11.40 79 [286,] 11.44 69 [287,] 11.48 83 [288,] 11.52 68 [289,] 11.56 85 [290,] 11.60 104 [291,] 11.64 98 [292,] 11.68 78 [293,] 11.72 83 [294,] 11.76 78 [295,] 11.80 81 [296,] 11.84 81 [297,] 11.88 69 [298,] 11.92 72 [299,] 11.96 80 [300,] 12.00 103 [301,] 12.04 81 [302,] 12.08 80 [303,] 12.12 72 [304,] 12.16 69 [305,] 12.20 85 [306,] 12.24 89 [307,] 12.28 101 [308,] 12.32 76 [309,] 12.36 79 [310,] 12.40 93 [311,] 12.44 94 [312,] 12.48 84 [313,] 12.52 69 [314,] 12.56 78 [315,] 12.60 80 [316,] 12.64 101 [317,] 12.68 81 [318,] 12.72 89 [319,] 12.76 71 [320,] 12.80 71 [321,] 12.84 72 [322,] 12.88 90 [323,] 12.92 81 [324,] 12.96 81 [325,] 13.00 75 [326,] 13.04 63 [327,] 13.08 78 [328,] 13.12 74 [329,] 13.16 86 [330,] 13.20 83 [331,] 13.24 84 [332,] 13.28 90 [333,] 13.32 63 [334,] 13.36 80 [335,] 13.40 87 [336,] 13.44 88 [337,] 13.48 65 [338,] 13.52 69 [339,] 13.56 83 [340,] 13.60 82 [341,] 13.64 61 [342,] 13.68 84 [343,] 13.72 77 [344,] 13.76 79 [345,] 13.80 85 [346,] 13.84 70 [347,] 13.88 96 [348,] 13.92 103 [349,] 13.96 59 [350,] 14.00 77 [351,] 14.04 81 [352,] 14.08 61 [353,] 14.12 72 [354,] 14.16 98 [355,] 14.20 89 [356,] 14.24 69 [357,] 14.28 83 [358,] 14.32 71 [359,] 14.36 84 [360,] 14.40 79 [361,] 14.44 92 [362,] 14.48 78 [363,] 14.52 60 [364,] 14.56 63 [365,] 14.60 59 [366,] 14.64 79 [367,] 14.68 83 [368,] 14.72 80 [369,] 14.76 78 [370,] 14.80 74 [371,] 14.84 93 [372,] 14.88 86 [373,] 14.92 72 [374,] 14.96 92 [375,] 15.00 84 [376,] 15.04 103 [377,] 15.08 85 [378,] 15.12 60 [379,] 15.16 91 [380,] 15.20 60 [381,] 15.24 76 [382,] 15.28 94 [383,] 15.32 72 [384,] 15.36 83 [385,] 15.40 77 [386,] 15.44 62 [387,] 15.48 87 [388,] 15.52 87 [389,] 15.56 56 [390,] 15.60 87 [391,] 15.64 68 [392,] 15.68 86 [393,] 15.72 70 [394,] 15.76 80 [395,] 15.80 87 [396,] 15.84 81 [397,] 15.88 78 [398,] 15.92 94 [399,] 15.96 69 [400,] 16.00 72 [401,] 16.04 70 [402,] 16.08 81 [403,] 16.12 78 [404,] 16.16 72 [405,] 16.20 84 [406,] 16.24 83 [407,] 16.28 79 [408,] 16.32 76 [409,] 16.36 89 [410,] 16.40 64 [411,] 16.44 68 [412,] 16.48 92 [413,] 16.52 66 [414,] 16.56 81 [415,] 16.60 72 [416,] 16.64 81 [417,] 16.68 74 [418,] 16.72 64 [419,] 16.76 71 [420,] 16.80 70 [421,] 16.84 90 [422,] 16.88 67 [423,] 16.92 73 [424,] 16.96 80 [425,] 17.00 66 [426,] 17.04 74 [427,] 17.08 75 [428,] 17.12 71 [429,] 17.16 78 [430,] 17.20 83 [431,] 17.24 72 [432,] 17.28 78 [433,] 17.32 74 [434,] 17.36 75 [435,] 17.40 86 [436,] 17.44 66 [437,] 17.48 76 [438,] 17.52 82 [439,] 17.56 81 [440,] 17.60 60 [441,] 17.64 88 [442,] 17.68 82 [443,] 17.72 85 [444,] 17.76 77 [445,] 17.80 70 [446,] 17.84 74 [447,] 17.88 99 [448,] 17.92 88 [449,] 17.96 74 [450,] 18.00 65 [451,] 18.04 80 [452,] 18.08 72 [453,] 18.12 73 [454,] 18.16 59 [455,] 18.20 87 [456,] 18.24 79 [457,] 18.28 92 [458,] 18.32 58 [459,] 18.36 75 [460,] 18.40 66 [461,] 18.44 58 [462,] 18.48 74 [463,] 18.52 75 [464,] 18.56 75 [465,] 18.60 79 [466,] 18.64 60 [467,] 18.68 84 [468,] 18.72 80 [469,] 18.76 68 [470,] 18.80 76 [471,] 18.84 64 [472,] 18.88 70 [473,] 18.92 85 [474,] 18.96 66 [475,] 19.00 69 [476,] 19.04 71 [477,] 19.08 68 [478,] 19.12 61 [479,] 19.16 88 [480,] 19.20 59 [481,] 19.24 83 [482,] 19.28 54 [483,] 19.32 58 [484,] 19.36 69 [485,] 19.40 53 [486,] 19.44 78 [487,] 19.48 79 [488,] 19.52 59 [489,] 19.56 76 [490,] 19.60 75 [491,] 19.64 91 [492,] 19.68 78 [493,] 19.72 65 [494,] 19.76 81 [495,] 19.80 66 [496,] 19.84 68 [497,] 19.88 55 [498,] 19.92 74 [499,] 19.96 77 [500,] 20.00 62 [501,] 20.04 87 [502,] 20.08 66 [503,] 20.12 63 [504,] 20.16 75 [505,] 20.20 91 [506,] 20.24 51 [507,] 20.28 66 [508,] 20.32 82 [509,] 20.36 73 [510,] 20.40 63 [511,] 20.44 68 [512,] 20.48 63 [513,] 20.52 61 [514,] 20.56 92 [515,] 20.60 81 [516,] 20.64 62 [517,] 20.68 70 [518,] 20.72 79 [519,] 20.76 75 [520,] 20.80 95 [521,] 20.84 79 [522,] 20.88 73 [523,] 20.92 54 [524,] 20.96 75 [525,] 21.00 87 [526,] 21.04 64 [527,] 21.08 72 [528,] 21.12 80 [529,] 21.16 57 [530,] 21.20 56 [531,] 21.24 79 [532,] 21.28 78 [533,] 21.32 80 [534,] 21.36 68 [535,] 21.40 79 [536,] 21.44 49 [537,] 21.48 57 [538,] 21.52 79 [539,] 21.56 71 [540,] 21.60 81 [541,] 21.64 77 [542,] 21.68 60 [543,] 21.72 67 [544,] 21.76 61 [545,] 21.80 70 [546,] 21.84 73 [547,] 21.88 63 [548,] 21.92 65 [549,] 21.96 69 [550,] 22.00 62 [551,] 22.04 78 [552,] 22.08 73 [553,] 22.12 80 [554,] 22.16 71 [555,] 22.20 64 [556,] 22.24 71 [557,] 22.28 68 [558,] 22.32 80 [559,] 22.36 61 [560,] 22.40 74 [561,] 22.44 58 [562,] 22.48 68 [563,] 22.52 75 [564,] 22.56 87 [565,] 22.60 64 [566,] 22.64 76 [567,] 22.68 61 [568,] 22.72 66 [569,] 22.76 58 [570,] 22.80 71 [571,] 22.84 59 [572,] 22.88 66 [573,] 22.92 93 [574,] 22.96 63 [575,] 23.00 68 [576,] 23.04 82 [577,] 23.08 89 [578,] 23.12 52 [579,] 23.16 63 [580,] 23.20 51 [581,] 23.24 67 [582,] 23.28 72 [583,] 23.32 76 [584,] 23.36 71 [585,] 23.40 69 [586,] 23.44 59 [587,] 23.48 75 [588,] 23.52 83 [589,] 23.56 67 [590,] 23.60 84 [591,] 23.64 84 [592,] 23.68 75 [593,] 23.72 66 [594,] 23.76 61 [595,] 23.80 60 [596,] 23.84 76 [597,] 23.88 75 [598,] 23.92 72 [599,] 23.96 79 [600,] 24.00 71 [601,] 24.04 75 [602,] 24.08 80 [603,] 24.12 85 [604,] 24.16 66 [605,] 24.20 65 [606,] 24.24 62 [607,] 24.28 76 [608,] 24.32 56 [609,] 24.36 55 [610,] 24.40 68 [611,] 24.44 69 [612,] 24.48 78 [613,] 24.52 81 [614,] 24.56 67 [615,] 24.60 75 [616,] 24.64 58 [617,] 24.68 67 [618,] 24.72 67 [619,] 24.76 57 [620,] 24.80 55 [621,] 24.84 58 [622,] 24.88 63 [623,] 24.92 74 [624,] 24.96 53 [625,] 25.00 67 [626,] 25.04 76 [627,] 25.08 73 [628,] 25.12 62 [629,] 25.16 70 [630,] 25.20 64 [631,] 25.24 87 [632,] 25.28 70 [633,] 25.32 69 [634,] 25.36 73 [635,] 25.40 66 [636,] 25.44 56 [637,] 25.48 71 [638,] 25.52 80 [639,] 25.56 80 [640,] 25.60 58 [641,] 25.64 86 [642,] 25.68 58 [643,] 25.72 64 [644,] 25.76 65 [645,] 25.80 67 [646,] 25.84 83 [647,] 25.88 47 [648,] 25.92 54 [649,] 25.96 59 [650,] 26.00 62 [651,] 26.04 77 [652,] 26.08 70 [653,] 26.12 55 [654,] 26.16 83 [655,] 26.20 71 [656,] 26.24 59 [657,] 26.28 66 [658,] 26.32 66 [659,] 26.36 68 [660,] 26.40 54 [661,] 26.44 68 [662,] 26.48 84 [663,] 26.52 59 [664,] 26.56 49 [665,] 26.60 77 [666,] 26.64 70 [667,] 26.68 58 [668,] 26.72 56 [669,] 26.76 59 [670,] 26.80 78 [671,] 26.84 52 [672,] 26.88 65 [673,] 26.92 82 [674,] 26.96 59 [675,] 27.00 71 [676,] 27.04 68 [677,] 27.08 72 [678,] 27.12 84 [679,] 27.16 71 [680,] 27.20 73 [681,] 27.24 60 [682,] 27.28 73 [683,] 27.32 64 [684,] 27.36 71 [685,] 27.40 75 [686,] 27.44 68 [687,] 27.48 68 [688,] 27.52 84 [689,] 27.56 73 [690,] 27.60 72 [691,] 27.64 67 [692,] 27.68 74 [693,] 27.72 64 [694,] 27.76 63 [695,] 27.80 54 [696,] 27.84 70 [697,] 27.88 60 [698,] 27.92 62 [699,] 27.96 62 [700,] 28.00 50 [701,] 28.04 60 [702,] 28.08 77 [703,] 28.12 68 [704,] 28.16 70 [705,] 28.20 65 [706,] 28.24 58 [707,] 28.28 55 [708,] 28.32 76 [709,] 28.36 60 [710,] 28.40 65 [711,] 28.44 64 [712,] 28.48 63 [713,] 28.52 55 [714,] 28.56 97 [715,] 28.60 49 [716,] 28.64 74 [717,] 28.68 49 [718,] 28.72 66 [719,] 28.76 51 [720,] 28.80 72 [721,] 28.84 67 [722,] 28.88 86 [723,] 28.92 51 [724,] 28.96 71 [725,] 29.00 70 [726,] 29.04 74 [727,] 29.08 76 [728,] 29.12 72 [729,] 29.16 59 [730,] 29.20 52 [731,] 29.24 75 [732,] 29.28 81 [733,] 29.32 65 [734,] 29.36 70 [735,] 29.40 71 [736,] 29.44 64 [737,] 29.48 51 [738,] 29.52 57 [739,] 29.56 61 [740,] 29.60 72 [741,] 29.64 54 [742,] 29.68 61 [743,] 29.72 63 [744,] 29.76 60 [745,] 29.80 69 [746,] 29.84 64 [747,] 29.88 55 [748,] 29.92 64 [749,] 29.96 46 [750,] 30.00 56 [751,] 30.04 64 [752,] 30.08 61 [753,] 30.12 64 [754,] 30.16 80 [755,] 30.20 69 [756,] 30.24 71 [757,] 30.28 66 [758,] 30.32 72 [759,] 30.36 60 [760,] 30.40 80 [761,] 30.44 56 [762,] 30.48 52 [763,] 30.52 75 [764,] 30.56 72 [765,] 30.60 63 [766,] 30.64 63 [767,] 30.68 69 [768,] 30.72 62 [769,] 30.76 74 [770,] 30.80 69 [771,] 30.84 55 [772,] 30.88 73 [773,] 30.92 68 [774,] 30.96 69 [775,] 31.00 61 [776,] 31.04 78 [777,] 31.08 62 [778,] 31.12 51 [779,] 31.16 74 [780,] 31.20 79 [781,] 31.24 67 [782,] 31.28 64 [783,] 31.32 57 [784,] 31.36 76 [785,] 31.40 83 [786,] 31.44 66 [787,] 31.48 59 [788,] 31.52 59 [789,] 31.56 69 [790,] 31.60 45 [791,] 31.64 52 [792,] 31.68 72 [793,] 31.72 69 [794,] 31.76 67 [795,] 31.80 79 [796,] 31.84 52 [797,] 31.88 84 [798,] 31.92 46 [799,] 31.96 56 [800,] 32.00 68 [801,] 32.04 56 [802,] 32.08 69 [803,] 32.12 64 [804,] 32.16 63 [805,] 32.20 69 [806,] 32.24 54 [807,] 32.28 52 [808,] 32.32 57 [809,] 32.36 79 [810,] 32.40 73 [811,] 32.44 72 [812,] 32.48 74 [813,] 32.52 64 [814,] 32.56 67 [815,] 32.60 69 [816,] 32.64 74 [817,] 32.68 80 [818,] 32.72 77 [819,] 32.76 62 [820,] 32.80 63 [821,] 32.84 69 [822,] 32.88 76 [823,] 32.92 65 [824,] 32.96 48 [825,] 33.00 81 [826,] 33.04 62 [827,] 33.08 51 [828,] 33.12 52 [829,] 33.16 62 [830,] 33.20 59 [831,] 33.24 75 [832,] 33.28 51 [833,] 33.32 57 [834,] 33.36 75 [835,] 33.40 67 [836,] 33.44 63 [837,] 33.48 68 [838,] 33.52 57 [839,] 33.56 47 [840,] 33.60 58 [841,] 33.64 66 [842,] 33.68 61 [843,] 33.72 51 [844,] 33.76 56 [845,] 33.80 76 [846,] 33.84 68 [847,] 33.88 44 [848,] 33.92 50 [849,] 33.96 45 [850,] 34.00 46 [851,] 34.04 54 [852,] 34.08 73 [853,] 34.12 67 [854,] 34.16 63 [855,] 34.20 65 [856,] 34.24 60 [857,] 34.28 53 [858,] 34.32 59 [859,] 34.36 67 [860,] 34.40 58 [861,] 34.44 57 [862,] 34.48 51 [863,] 34.52 54 [864,] 34.56 56 [865,] 34.60 71 [866,] 34.64 61 [867,] 34.68 60 [868,] 34.72 63 [869,] 34.76 60 [870,] 34.80 65 [871,] 34.84 56 [872,] 34.88 54 [873,] 34.92 57 [874,] 34.96 70 [875,] 35.00 64 [876,] 35.04 61 [877,] 35.08 60 [878,] 35.12 61 [879,] 35.16 51 [880,] 35.20 60 [881,] 35.24 46 [882,] 35.28 52 [883,] 35.32 51 [884,] 35.36 49 [885,] 35.40 70 [886,] 35.44 55 [887,] 35.48 65 [888,] 35.52 50 [889,] 35.56 53 [890,] 35.60 61 [891,] 35.64 66 [892,] 35.68 53 [893,] 35.72 48 [894,] 35.76 51 [895,] 35.80 48 [896,] 35.84 53 [897,] 35.88 58 [898,] 35.92 52 [899,] 35.96 48 [900,] 36.00 61 [901,] 36.04 57 [902,] 36.08 74 [903,] 36.12 58 [904,] 36.16 53 [905,] 36.20 49 [906,] 36.24 65 [907,] 36.28 81 [908,] 36.32 40 [909,] 36.36 57 [910,] 36.40 60 [911,] 36.44 54 [912,] 36.48 63 [913,] 36.52 68 [914,] 36.56 53 [915,] 36.60 67 [916,] 36.64 67 [917,] 36.68 76 [918,] 36.72 43 [919,] 36.76 60 [920,] 36.80 55 [921,] 36.84 55 [922,] 36.88 65 [923,] 36.92 55 [924,] 36.96 68 [925,] 37.00 62 [926,] 37.04 74 [927,] 37.08 68 [928,] 37.12 68 [929,] 37.16 68 [930,] 37.20 69 [931,] 37.24 81 [932,] 37.28 53 [933,] 37.32 56 [934,] 37.36 62 [935,] 37.40 71 [936,] 37.44 66 [937,] 37.48 59 [938,] 37.52 54 [939,] 37.56 48 [940,] 37.60 79 [941,] 37.64 68 [942,] 37.68 60 [943,] 37.72 81 [944,] 37.76 65 [945,] 37.80 65 [946,] 37.84 52 [947,] 37.88 46 [948,] 37.92 57 [949,] 37.96 74 [950,] 38.00 58 [951,] 38.04 68 [952,] 38.08 74 [953,] 38.12 55 [954,] 38.16 47 [955,] 38.20 53 [956,] 38.24 56 [957,] 38.28 45 [958,] 38.32 47 [959,] 38.36 56 [960,] 38.40 45 [961,] 38.44 57 [962,] 38.48 65 [963,] 38.52 62 [964,] 38.56 60 [965,] 38.60 62 [966,] 38.64 50 [967,] 38.68 49 [968,] 38.72 50 [969,] 38.76 61 [970,] 38.80 53 [971,] 38.84 71 [972,] 38.88 60 [973,] 38.92 60 [974,] 38.96 48 [975,] 39.00 51 [976,] 39.04 48 [977,] 39.08 55 [978,] 39.12 60 [979,] 39.16 66 [980,] 39.20 55 [981,] 39.24 59 [982,] 39.28 45 [983,] 39.32 61 [984,] 39.36 65 [985,] 39.40 51 [986,] 39.44 51 [987,] 39.48 60 [988,] 39.52 50 [989,] 39.56 50 [990,] 39.60 43 [991,] 39.64 52 [992,] 39.68 59 [993,] 39.72 71 [994,] 39.76 74 [995,] 39.80 44 [996,] 39.84 52 [997,] 39.88 71 [998,] 39.92 66 [999,] 39.96 45 [1000,] 40.00 58 $`15_TL (PMT)` [,1] [,2] [1,] 0.64 2 [2,] 1.28 1 [3,] 1.92 5 [4,] 2.56 1 [5,] 3.20 1 [6,] 3.84 3 [7,] 4.48 1 [8,] 5.12 0 [9,] 5.76 1 [10,] 6.40 10 [11,] 7.04 1 [12,] 7.68 2 [13,] 8.32 2 [14,] 8.96 2 [15,] 9.60 6 [16,] 10.24 2 [17,] 10.88 0 [18,] 11.52 0 [19,] 12.16 4 [20,] 12.80 3 [21,] 13.44 2 [22,] 14.08 8 [23,] 14.72 3 [24,] 15.36 5 [25,] 16.00 2 [26,] 16.64 4 [27,] 17.28 3 [28,] 17.92 4 [29,] 18.56 1 [30,] 19.20 5 [31,] 19.84 0 [32,] 20.48 5 [33,] 21.12 3 [34,] 21.76 6 [35,] 22.40 3 [36,] 23.04 10 [37,] 23.68 0 [38,] 24.32 3 [39,] 24.96 3 [40,] 25.60 6 [41,] 26.24 2 [42,] 26.88 1 [43,] 27.52 4 [44,] 28.16 0 [45,] 28.80 4 [46,] 29.44 1 [47,] 30.08 6 [48,] 30.72 6 [49,] 31.36 0 [50,] 32.00 1 [51,] 32.64 7 [52,] 33.28 3 [53,] 33.92 4 [54,] 34.56 8 [55,] 35.20 1 [56,] 35.84 7 [57,] 36.48 4 [58,] 37.12 12 [59,] 37.76 3 [60,] 38.40 3 [61,] 39.04 8 [62,] 39.68 4 [63,] 40.32 3 [64,] 40.96 8 [65,] 41.60 4 [66,] 42.24 5 [67,] 42.88 3 [68,] 43.52 5 [69,] 44.16 6 [70,] 44.80 1 [71,] 45.44 3 [72,] 46.08 2 [73,] 46.72 8 [74,] 47.36 4 [75,] 48.00 10 [76,] 48.64 6 [77,] 49.28 10 [78,] 49.92 3 [79,] 50.56 28 [80,] 51.20 6 [81,] 51.84 10 [82,] 52.48 7 [83,] 53.12 3 [84,] 53.76 12 [85,] 54.40 4 [86,] 55.04 10 [87,] 55.68 14 [88,] 56.32 7 [89,] 56.96 3 [90,] 57.60 11 [91,] 58.24 20 [92,] 58.88 16 [93,] 59.52 16 [94,] 60.16 20 [95,] 60.80 21 [96,] 61.44 13 [97,] 62.08 15 [98,] 62.72 20 [99,] 63.36 20 [100,] 64.00 20 [101,] 64.64 23 [102,] 65.28 17 [103,] 65.92 25 [104,] 66.56 18 [105,] 67.20 25 [106,] 67.84 25 [107,] 68.48 26 [108,] 69.12 32 [109,] 69.76 22 [110,] 70.40 33 [111,] 71.04 26 [112,] 71.68 23 [113,] 72.32 49 [114,] 72.96 39 [115,] 73.60 29 [116,] 74.24 44 [117,] 74.88 44 [118,] 75.52 51 [119,] 76.16 57 [120,] 76.80 66 [121,] 77.44 61 [122,] 78.08 62 [123,] 78.72 75 [124,] 79.36 78 [125,] 80.00 73 [126,] 80.64 84 [127,] 81.28 86 [128,] 81.92 86 [129,] 82.56 99 [130,] 83.20 107 [131,] 83.84 125 [132,] 84.48 112 [133,] 85.12 129 [134,] 85.76 111 [135,] 86.40 127 [136,] 87.04 116 [137,] 87.68 140 [138,] 88.32 146 [139,] 88.96 159 [140,] 89.60 146 [141,] 90.24 150 [142,] 90.88 188 [143,] 91.52 179 [144,] 92.16 176 [145,] 92.80 194 [146,] 93.44 189 [147,] 94.08 199 [148,] 94.72 189 [149,] 95.36 189 [150,] 96.00 195 [151,] 96.64 259 [152,] 97.28 213 [153,] 97.92 239 [154,] 98.56 238 [155,] 99.20 244 [156,] 99.84 236 [157,] 100.48 290 [158,] 101.12 253 [159,] 101.76 282 [160,] 102.40 259 [161,] 103.04 250 [162,] 103.68 282 [163,] 104.32 289 [164,] 104.96 264 [165,] 105.60 263 [166,] 106.24 299 [167,] 106.88 243 [168,] 107.52 282 [169,] 108.16 255 [170,] 108.80 282 [171,] 109.44 284 [172,] 110.08 267 [173,] 110.72 295 [174,] 111.36 265 [175,] 112.00 237 [176,] 112.64 208 [177,] 113.28 183 [178,] 113.92 238 [179,] 114.56 213 [180,] 115.20 198 [181,] 115.84 195 [182,] 116.48 224 [183,] 117.12 210 [184,] 117.76 191 [185,] 118.40 138 [186,] 119.04 152 [187,] 119.68 138 [188,] 120.32 140 [189,] 120.96 129 [190,] 121.60 136 [191,] 122.24 117 [192,] 122.88 116 [193,] 123.52 94 [194,] 124.16 82 [195,] 124.80 89 [196,] 125.44 79 [197,] 126.08 97 [198,] 126.72 85 [199,] 127.36 66 [200,] 128.00 75 [201,] 128.64 91 [202,] 129.28 67 [203,] 129.92 92 [204,] 130.56 76 [205,] 131.20 78 [206,] 131.84 71 [207,] 132.48 86 [208,] 133.12 84 [209,] 133.76 78 [210,] 134.40 74 [211,] 135.04 80 [212,] 135.68 73 [213,] 136.32 75 [214,] 136.96 88 [215,] 137.60 80 [216,] 138.24 85 [217,] 138.88 81 [218,] 139.52 98 [219,] 140.16 82 [220,] 140.80 89 [221,] 141.44 83 [222,] 142.08 97 [223,] 142.72 79 [224,] 143.36 85 [225,] 144.00 82 [226,] 144.64 78 [227,] 145.28 100 [228,] 145.92 90 [229,] 146.56 97 [230,] 147.20 95 [231,] 147.84 72 [232,] 148.48 78 [233,] 149.12 100 [234,] 149.76 61 [235,] 150.40 69 [236,] 151.04 90 [237,] 151.68 74 [238,] 152.32 79 [239,] 152.96 82 [240,] 153.60 76 [241,] 154.24 64 [242,] 154.88 72 [243,] 155.52 76 [244,] 156.16 73 [245,] 156.80 75 [246,] 157.44 75 [247,] 158.08 90 [248,] 158.72 84 [249,] 159.36 82 [250,] 160.00 70 $`16_OSL (PMT)` [,1] [,2] [1,] 0.04 2660 [2,] 0.08 2404 [3,] 0.12 2054 [4,] 0.16 1845 [5,] 0.20 1610 [6,] 0.24 1391 [7,] 0.28 1160 [8,] 0.32 1020 [9,] 0.36 986 [10,] 0.40 878 [11,] 0.44 731 [12,] 0.48 658 [13,] 0.52 600 [14,] 0.56 570 [15,] 0.60 498 [16,] 0.64 465 [17,] 0.68 435 [18,] 0.72 394 [19,] 0.76 305 [20,] 0.80 320 [21,] 0.84 289 [22,] 0.88 266 [23,] 0.92 227 [24,] 0.96 265 [25,] 1.00 236 [26,] 1.04 251 [27,] 1.08 240 [28,] 1.12 188 [29,] 1.16 186 [30,] 1.20 199 [31,] 1.24 200 [32,] 1.28 177 [33,] 1.32 197 [34,] 1.36 183 [35,] 1.40 167 [36,] 1.44 140 [37,] 1.48 174 [38,] 1.52 138 [39,] 1.56 163 [40,] 1.60 164 [41,] 1.64 136 [42,] 1.68 156 [43,] 1.72 163 [44,] 1.76 120 [45,] 1.80 157 [46,] 1.84 132 [47,] 1.88 124 [48,] 1.92 143 [49,] 1.96 127 [50,] 2.00 118 [51,] 2.04 154 [52,] 2.08 130 [53,] 2.12 110 [54,] 2.16 121 [55,] 2.20 118 [56,] 2.24 114 [57,] 2.28 130 [58,] 2.32 111 [59,] 2.36 145 [60,] 2.40 132 [61,] 2.44 114 [62,] 2.48 106 [63,] 2.52 95 [64,] 2.56 130 [65,] 2.60 115 [66,] 2.64 114 [67,] 2.68 125 [68,] 2.72 118 [69,] 2.76 122 [70,] 2.80 108 [71,] 2.84 111 [72,] 2.88 110 [73,] 2.92 109 [74,] 2.96 112 [75,] 3.00 107 [76,] 3.04 119 [77,] 3.08 101 [78,] 3.12 88 [79,] 3.16 107 [80,] 3.20 99 [81,] 3.24 132 [82,] 3.28 107 [83,] 3.32 98 [84,] 3.36 79 [85,] 3.40 88 [86,] 3.44 102 [87,] 3.48 105 [88,] 3.52 94 [89,] 3.56 89 [90,] 3.60 95 [91,] 3.64 96 [92,] 3.68 103 [93,] 3.72 97 [94,] 3.76 100 [95,] 3.80 87 [96,] 3.84 97 [97,] 3.88 107 [98,] 3.92 105 [99,] 3.96 99 [100,] 4.00 110 [101,] 4.04 98 [102,] 4.08 96 [103,] 4.12 88 [104,] 4.16 84 [105,] 4.20 91 [106,] 4.24 64 [107,] 4.28 89 [108,] 4.32 86 [109,] 4.36 94 [110,] 4.40 107 [111,] 4.44 93 [112,] 4.48 82 [113,] 4.52 98 [114,] 4.56 84 [115,] 4.60 97 [116,] 4.64 89 [117,] 4.68 84 [118,] 4.72 94 [119,] 4.76 85 [120,] 4.80 87 [121,] 4.84 74 [122,] 4.88 100 [123,] 4.92 101 [124,] 4.96 96 [125,] 5.00 111 [126,] 5.04 95 [127,] 5.08 87 [128,] 5.12 93 [129,] 5.16 87 [130,] 5.20 127 [131,] 5.24 91 [132,] 5.28 93 [133,] 5.32 82 [134,] 5.36 104 [135,] 5.40 112 [136,] 5.44 88 [137,] 5.48 103 [138,] 5.52 95 [139,] 5.56 91 [140,] 5.60 95 [141,] 5.64 111 [142,] 5.68 86 [143,] 5.72 73 [144,] 5.76 77 [145,] 5.80 88 [146,] 5.84 65 [147,] 5.88 79 [148,] 5.92 110 [149,] 5.96 89 [150,] 6.00 80 [151,] 6.04 84 [152,] 6.08 77 [153,] 6.12 87 [154,] 6.16 101 [155,] 6.20 84 [156,] 6.24 83 [157,] 6.28 84 [158,] 6.32 89 [159,] 6.36 68 [160,] 6.40 86 [161,] 6.44 87 [162,] 6.48 80 [163,] 6.52 68 [164,] 6.56 70 [165,] 6.60 77 [166,] 6.64 82 [167,] 6.68 83 [168,] 6.72 94 [169,] 6.76 93 [170,] 6.80 86 [171,] 6.84 95 [172,] 6.88 100 [173,] 6.92 90 [174,] 6.96 95 [175,] 7.00 76 [176,] 7.04 80 [177,] 7.08 89 [178,] 7.12 95 [179,] 7.16 57 [180,] 7.20 82 [181,] 7.24 90 [182,] 7.28 95 [183,] 7.32 86 [184,] 7.36 84 [185,] 7.40 84 [186,] 7.44 69 [187,] 7.48 74 [188,] 7.52 68 [189,] 7.56 90 [190,] 7.60 77 [191,] 7.64 73 [192,] 7.68 75 [193,] 7.72 77 [194,] 7.76 73 [195,] 7.80 75 [196,] 7.84 93 [197,] 7.88 96 [198,] 7.92 82 [199,] 7.96 92 [200,] 8.00 98 [201,] 8.04 82 [202,] 8.08 83 [203,] 8.12 92 [204,] 8.16 85 [205,] 8.20 83 [206,] 8.24 81 [207,] 8.28 67 [208,] 8.32 75 [209,] 8.36 82 [210,] 8.40 65 [211,] 8.44 82 [212,] 8.48 85 [213,] 8.52 68 [214,] 8.56 72 [215,] 8.60 90 [216,] 8.64 71 [217,] 8.68 89 [218,] 8.72 70 [219,] 8.76 80 [220,] 8.80 85 [221,] 8.84 61 [222,] 8.88 89 [223,] 8.92 79 [224,] 8.96 64 [225,] 9.00 81 [226,] 9.04 81 [227,] 9.08 64 [228,] 9.12 79 [229,] 9.16 91 [230,] 9.20 87 [231,] 9.24 95 [232,] 9.28 78 [233,] 9.32 72 [234,] 9.36 70 [235,] 9.40 56 [236,] 9.44 91 [237,] 9.48 80 [238,] 9.52 62 [239,] 9.56 86 [240,] 9.60 56 [241,] 9.64 70 [242,] 9.68 67 [243,] 9.72 87 [244,] 9.76 90 [245,] 9.80 74 [246,] 9.84 77 [247,] 9.88 65 [248,] 9.92 55 [249,] 9.96 70 [250,] 10.00 63 [251,] 10.04 70 [252,] 10.08 80 [253,] 10.12 77 [254,] 10.16 84 [255,] 10.20 89 [256,] 10.24 85 [257,] 10.28 85 [258,] 10.32 67 [259,] 10.36 70 [260,] 10.40 80 [261,] 10.44 70 [262,] 10.48 71 [263,] 10.52 79 [264,] 10.56 80 [265,] 10.60 74 [266,] 10.64 77 [267,] 10.68 78 [268,] 10.72 77 [269,] 10.76 62 [270,] 10.80 68 [271,] 10.84 73 [272,] 10.88 86 [273,] 10.92 85 [274,] 10.96 66 [275,] 11.00 50 [276,] 11.04 66 [277,] 11.08 70 [278,] 11.12 82 [279,] 11.16 73 [280,] 11.20 68 [281,] 11.24 76 [282,] 11.28 77 [283,] 11.32 80 [284,] 11.36 68 [285,] 11.40 83 [286,] 11.44 82 [287,] 11.48 72 [288,] 11.52 69 [289,] 11.56 84 [290,] 11.60 57 [291,] 11.64 87 [292,] 11.68 72 [293,] 11.72 75 [294,] 11.76 62 [295,] 11.80 69 [296,] 11.84 68 [297,] 11.88 67 [298,] 11.92 65 [299,] 11.96 68 [300,] 12.00 84 [301,] 12.04 77 [302,] 12.08 66 [303,] 12.12 72 [304,] 12.16 70 [305,] 12.20 106 [306,] 12.24 77 [307,] 12.28 59 [308,] 12.32 66 [309,] 12.36 67 [310,] 12.40 66 [311,] 12.44 51 [312,] 12.48 72 [313,] 12.52 89 [314,] 12.56 76 [315,] 12.60 83 [316,] 12.64 83 [317,] 12.68 62 [318,] 12.72 74 [319,] 12.76 65 [320,] 12.80 72 [321,] 12.84 64 [322,] 12.88 69 [323,] 12.92 75 [324,] 12.96 80 [325,] 13.00 106 [326,] 13.04 88 [327,] 13.08 62 [328,] 13.12 70 [329,] 13.16 71 [330,] 13.20 77 [331,] 13.24 71 [332,] 13.28 107 [333,] 13.32 68 [334,] 13.36 78 [335,] 13.40 77 [336,] 13.44 75 [337,] 13.48 73 [338,] 13.52 49 [339,] 13.56 66 [340,] 13.60 82 [341,] 13.64 82 [342,] 13.68 85 [343,] 13.72 87 [344,] 13.76 73 [345,] 13.80 72 [346,] 13.84 67 [347,] 13.88 77 [348,] 13.92 72 [349,] 13.96 76 [350,] 14.00 89 [351,] 14.04 59 [352,] 14.08 75 [353,] 14.12 70 [354,] 14.16 77 [355,] 14.20 72 [356,] 14.24 77 [357,] 14.28 66 [358,] 14.32 78 [359,] 14.36 58 [360,] 14.40 83 [361,] 14.44 77 [362,] 14.48 63 [363,] 14.52 71 [364,] 14.56 75 [365,] 14.60 65 [366,] 14.64 64 [367,] 14.68 46 [368,] 14.72 54 [369,] 14.76 66 [370,] 14.80 86 [371,] 14.84 70 [372,] 14.88 52 [373,] 14.92 63 [374,] 14.96 76 [375,] 15.00 58 [376,] 15.04 68 [377,] 15.08 78 [378,] 15.12 68 [379,] 15.16 78 [380,] 15.20 59 [381,] 15.24 78 [382,] 15.28 72 [383,] 15.32 75 [384,] 15.36 68 [385,] 15.40 71 [386,] 15.44 74 [387,] 15.48 70 [388,] 15.52 72 [389,] 15.56 66 [390,] 15.60 70 [391,] 15.64 69 [392,] 15.68 58 [393,] 15.72 71 [394,] 15.76 75 [395,] 15.80 77 [396,] 15.84 58 [397,] 15.88 92 [398,] 15.92 94 [399,] 15.96 65 [400,] 16.00 65 [401,] 16.04 71 [402,] 16.08 78 [403,] 16.12 76 [404,] 16.16 83 [405,] 16.20 73 [406,] 16.24 76 [407,] 16.28 86 [408,] 16.32 76 [409,] 16.36 71 [410,] 16.40 56 [411,] 16.44 68 [412,] 16.48 61 [413,] 16.52 68 [414,] 16.56 57 [415,] 16.60 85 [416,] 16.64 71 [417,] 16.68 81 [418,] 16.72 76 [419,] 16.76 66 [420,] 16.80 76 [421,] 16.84 73 [422,] 16.88 55 [423,] 16.92 63 [424,] 16.96 68 [425,] 17.00 63 [426,] 17.04 66 [427,] 17.08 67 [428,] 17.12 81 [429,] 17.16 34 [430,] 17.20 78 [431,] 17.24 71 [432,] 17.28 59 [433,] 17.32 64 [434,] 17.36 66 [435,] 17.40 76 [436,] 17.44 52 [437,] 17.48 70 [438,] 17.52 59 [439,] 17.56 55 [440,] 17.60 66 [441,] 17.64 71 [442,] 17.68 60 [443,] 17.72 83 [444,] 17.76 70 [445,] 17.80 64 [446,] 17.84 102 [447,] 17.88 46 [448,] 17.92 68 [449,] 17.96 64 [450,] 18.00 92 [451,] 18.04 79 [452,] 18.08 74 [453,] 18.12 67 [454,] 18.16 57 [455,] 18.20 65 [456,] 18.24 76 [457,] 18.28 67 [458,] 18.32 75 [459,] 18.36 59 [460,] 18.40 65 [461,] 18.44 74 [462,] 18.48 54 [463,] 18.52 79 [464,] 18.56 55 [465,] 18.60 91 [466,] 18.64 65 [467,] 18.68 69 [468,] 18.72 82 [469,] 18.76 70 [470,] 18.80 64 [471,] 18.84 71 [472,] 18.88 71 [473,] 18.92 87 [474,] 18.96 68 [475,] 19.00 68 [476,] 19.04 64 [477,] 19.08 73 [478,] 19.12 60 [479,] 19.16 75 [480,] 19.20 52 [481,] 19.24 74 [482,] 19.28 47 [483,] 19.32 63 [484,] 19.36 70 [485,] 19.40 53 [486,] 19.44 95 [487,] 19.48 66 [488,] 19.52 71 [489,] 19.56 69 [490,] 19.60 56 [491,] 19.64 70 [492,] 19.68 70 [493,] 19.72 76 [494,] 19.76 82 [495,] 19.80 85 [496,] 19.84 71 [497,] 19.88 61 [498,] 19.92 69 [499,] 19.96 54 [500,] 20.00 58 [501,] 20.04 43 [502,] 20.08 80 [503,] 20.12 54 [504,] 20.16 84 [505,] 20.20 89 [506,] 20.24 77 [507,] 20.28 64 [508,] 20.32 71 [509,] 20.36 69 [510,] 20.40 63 [511,] 20.44 60 [512,] 20.48 68 [513,] 20.52 75 [514,] 20.56 64 [515,] 20.60 66 [516,] 20.64 73 [517,] 20.68 59 [518,] 20.72 58 [519,] 20.76 63 [520,] 20.80 78 [521,] 20.84 49 [522,] 20.88 51 [523,] 20.92 68 [524,] 20.96 59 [525,] 21.00 77 [526,] 21.04 73 [527,] 21.08 56 [528,] 21.12 73 [529,] 21.16 68 [530,] 21.20 68 [531,] 21.24 73 [532,] 21.28 70 [533,] 21.32 65 [534,] 21.36 68 [535,] 21.40 65 [536,] 21.44 72 [537,] 21.48 65 [538,] 21.52 69 [539,] 21.56 71 [540,] 21.60 65 [541,] 21.64 74 [542,] 21.68 65 [543,] 21.72 70 [544,] 21.76 72 [545,] 21.80 54 [546,] 21.84 71 [547,] 21.88 53 [548,] 21.92 88 [549,] 21.96 69 [550,] 22.00 80 [551,] 22.04 80 [552,] 22.08 75 [553,] 22.12 70 [554,] 22.16 69 [555,] 22.20 59 [556,] 22.24 70 [557,] 22.28 62 [558,] 22.32 69 [559,] 22.36 71 [560,] 22.40 50 [561,] 22.44 69 [562,] 22.48 62 [563,] 22.52 88 [564,] 22.56 77 [565,] 22.60 53 [566,] 22.64 59 [567,] 22.68 68 [568,] 22.72 61 [569,] 22.76 64 [570,] 22.80 66 [571,] 22.84 58 [572,] 22.88 77 [573,] 22.92 78 [574,] 22.96 45 [575,] 23.00 64 [576,] 23.04 58 [577,] 23.08 70 [578,] 23.12 66 [579,] 23.16 55 [580,] 23.20 61 [581,] 23.24 68 [582,] 23.28 70 [583,] 23.32 77 [584,] 23.36 66 [585,] 23.40 62 [586,] 23.44 67 [587,] 23.48 67 [588,] 23.52 78 [589,] 23.56 66 [590,] 23.60 66 [591,] 23.64 57 [592,] 23.68 58 [593,] 23.72 42 [594,] 23.76 89 [595,] 23.80 64 [596,] 23.84 58 [597,] 23.88 68 [598,] 23.92 65 [599,] 23.96 57 [600,] 24.00 64 [601,] 24.04 75 [602,] 24.08 65 [603,] 24.12 58 [604,] 24.16 72 [605,] 24.20 63 [606,] 24.24 66 [607,] 24.28 70 [608,] 24.32 66 [609,] 24.36 70 [610,] 24.40 71 [611,] 24.44 71 [612,] 24.48 58 [613,] 24.52 77 [614,] 24.56 66 [615,] 24.60 61 [616,] 24.64 65 [617,] 24.68 66 [618,] 24.72 76 [619,] 24.76 64 [620,] 24.80 69 [621,] 24.84 73 [622,] 24.88 63 [623,] 24.92 51 [624,] 24.96 80 [625,] 25.00 61 [626,] 25.04 62 [627,] 25.08 71 [628,] 25.12 55 [629,] 25.16 98 [630,] 25.20 59 [631,] 25.24 60 [632,] 25.28 54 [633,] 25.32 74 [634,] 25.36 70 [635,] 25.40 56 [636,] 25.44 61 [637,] 25.48 76 [638,] 25.52 65 [639,] 25.56 43 [640,] 25.60 57 [641,] 25.64 67 [642,] 25.68 70 [643,] 25.72 61 [644,] 25.76 60 [645,] 25.80 70 [646,] 25.84 60 [647,] 25.88 48 [648,] 25.92 64 [649,] 25.96 51 [650,] 26.00 73 [651,] 26.04 60 [652,] 26.08 70 [653,] 26.12 54 [654,] 26.16 59 [655,] 26.20 60 [656,] 26.24 53 [657,] 26.28 56 [658,] 26.32 54 [659,] 26.36 68 [660,] 26.40 86 [661,] 26.44 73 [662,] 26.48 49 [663,] 26.52 58 [664,] 26.56 63 [665,] 26.60 48 [666,] 26.64 68 [667,] 26.68 68 [668,] 26.72 59 [669,] 26.76 48 [670,] 26.80 62 [671,] 26.84 73 [672,] 26.88 58 [673,] 26.92 58 [674,] 26.96 59 [675,] 27.00 52 [676,] 27.04 58 [677,] 27.08 72 [678,] 27.12 93 [679,] 27.16 62 [680,] 27.20 79 [681,] 27.24 49 [682,] 27.28 61 [683,] 27.32 56 [684,] 27.36 86 [685,] 27.40 58 [686,] 27.44 56 [687,] 27.48 70 [688,] 27.52 50 [689,] 27.56 66 [690,] 27.60 62 [691,] 27.64 61 [692,] 27.68 68 [693,] 27.72 65 [694,] 27.76 64 [695,] 27.80 85 [696,] 27.84 55 [697,] 27.88 56 [698,] 27.92 59 [699,] 27.96 55 [700,] 28.00 63 [701,] 28.04 73 [702,] 28.08 70 [703,] 28.12 59 [704,] 28.16 59 [705,] 28.20 51 [706,] 28.24 66 [707,] 28.28 51 [708,] 28.32 66 [709,] 28.36 50 [710,] 28.40 85 [711,] 28.44 77 [712,] 28.48 80 [713,] 28.52 75 [714,] 28.56 66 [715,] 28.60 50 [716,] 28.64 66 [717,] 28.68 59 [718,] 28.72 56 [719,] 28.76 63 [720,] 28.80 59 [721,] 28.84 49 [722,] 28.88 56 [723,] 28.92 67 [724,] 28.96 66 [725,] 29.00 52 [726,] 29.04 41 [727,] 29.08 74 [728,] 29.12 54 [729,] 29.16 62 [730,] 29.20 64 [731,] 29.24 50 [732,] 29.28 58 [733,] 29.32 67 [734,] 29.36 43 [735,] 29.40 58 [736,] 29.44 61 [737,] 29.48 59 [738,] 29.52 54 [739,] 29.56 54 [740,] 29.60 67 [741,] 29.64 65 [742,] 29.68 61 [743,] 29.72 52 [744,] 29.76 46 [745,] 29.80 57 [746,] 29.84 67 [747,] 29.88 67 [748,] 29.92 53 [749,] 29.96 54 [750,] 30.00 66 [751,] 30.04 52 [752,] 30.08 45 [753,] 30.12 59 [754,] 30.16 48 [755,] 30.20 68 [756,] 30.24 67 [757,] 30.28 72 [758,] 30.32 51 [759,] 30.36 53 [760,] 30.40 55 [761,] 30.44 58 [762,] 30.48 62 [763,] 30.52 60 [764,] 30.56 52 [765,] 30.60 58 [766,] 30.64 52 [767,] 30.68 50 [768,] 30.72 56 [769,] 30.76 69 [770,] 30.80 79 [771,] 30.84 47 [772,] 30.88 54 [773,] 30.92 62 [774,] 30.96 76 [775,] 31.00 54 [776,] 31.04 54 [777,] 31.08 60 [778,] 31.12 61 [779,] 31.16 66 [780,] 31.20 56 [781,] 31.24 59 [782,] 31.28 57 [783,] 31.32 51 [784,] 31.36 65 [785,] 31.40 55 [786,] 31.44 83 [787,] 31.48 78 [788,] 31.52 67 [789,] 31.56 74 [790,] 31.60 80 [791,] 31.64 58 [792,] 31.68 65 [793,] 31.72 59 [794,] 31.76 65 [795,] 31.80 52 [796,] 31.84 68 [797,] 31.88 48 [798,] 31.92 83 [799,] 31.96 41 [800,] 32.00 55 [801,] 32.04 54 [802,] 32.08 65 [803,] 32.12 52 [804,] 32.16 60 [805,] 32.20 47 [806,] 32.24 57 [807,] 32.28 52 [808,] 32.32 70 [809,] 32.36 93 [810,] 32.40 63 [811,] 32.44 64 [812,] 32.48 54 [813,] 32.52 64 [814,] 32.56 74 [815,] 32.60 54 [816,] 32.64 69 [817,] 32.68 60 [818,] 32.72 52 [819,] 32.76 56 [820,] 32.80 62 [821,] 32.84 53 [822,] 32.88 63 [823,] 32.92 50 [824,] 32.96 54 [825,] 33.00 59 [826,] 33.04 59 [827,] 33.08 53 [828,] 33.12 60 [829,] 33.16 66 [830,] 33.20 52 [831,] 33.24 68 [832,] 33.28 63 [833,] 33.32 46 [834,] 33.36 53 [835,] 33.40 62 [836,] 33.44 61 [837,] 33.48 64 [838,] 33.52 64 [839,] 33.56 50 [840,] 33.60 56 [841,] 33.64 66 [842,] 33.68 65 [843,] 33.72 58 [844,] 33.76 63 [845,] 33.80 81 [846,] 33.84 46 [847,] 33.88 60 [848,] 33.92 69 [849,] 33.96 50 [850,] 34.00 64 [851,] 34.04 46 [852,] 34.08 72 [853,] 34.12 72 [854,] 34.16 46 [855,] 34.20 64 [856,] 34.24 56 [857,] 34.28 70 [858,] 34.32 76 [859,] 34.36 51 [860,] 34.40 65 [861,] 34.44 62 [862,] 34.48 66 [863,] 34.52 64 [864,] 34.56 78 [865,] 34.60 51 [866,] 34.64 58 [867,] 34.68 42 [868,] 34.72 59 [869,] 34.76 64 [870,] 34.80 59 [871,] 34.84 75 [872,] 34.88 58 [873,] 34.92 65 [874,] 34.96 48 [875,] 35.00 64 [876,] 35.04 44 [877,] 35.08 64 [878,] 35.12 62 [879,] 35.16 54 [880,] 35.20 58 [881,] 35.24 40 [882,] 35.28 63 [883,] 35.32 54 [884,] 35.36 68 [885,] 35.40 74 [886,] 35.44 62 [887,] 35.48 48 [888,] 35.52 49 [889,] 35.56 63 [890,] 35.60 56 [891,] 35.64 63 [892,] 35.68 57 [893,] 35.72 41 [894,] 35.76 59 [895,] 35.80 47 [896,] 35.84 61 [897,] 35.88 61 [898,] 35.92 64 [899,] 35.96 57 [900,] 36.00 69 [901,] 36.04 74 [902,] 36.08 59 [903,] 36.12 47 [904,] 36.16 56 [905,] 36.20 64 [906,] 36.24 60 [907,] 36.28 52 [908,] 36.32 42 [909,] 36.36 60 [910,] 36.40 67 [911,] 36.44 66 [912,] 36.48 47 [913,] 36.52 65 [914,] 36.56 80 [915,] 36.60 50 [916,] 36.64 61 [917,] 36.68 66 [918,] 36.72 50 [919,] 36.76 73 [920,] 36.80 62 [921,] 36.84 66 [922,] 36.88 69 [923,] 36.92 75 [924,] 36.96 69 [925,] 37.00 67 [926,] 37.04 74 [927,] 37.08 71 [928,] 37.12 64 [929,] 37.16 58 [930,] 37.20 57 [931,] 37.24 57 [932,] 37.28 50 [933,] 37.32 51 [934,] 37.36 63 [935,] 37.40 83 [936,] 37.44 60 [937,] 37.48 66 [938,] 37.52 42 [939,] 37.56 47 [940,] 37.60 48 [941,] 37.64 67 [942,] 37.68 56 [943,] 37.72 64 [944,] 37.76 50 [945,] 37.80 62 [946,] 37.84 58 [947,] 37.88 53 [948,] 37.92 53 [949,] 37.96 69 [950,] 38.00 58 [951,] 38.04 77 [952,] 38.08 78 [953,] 38.12 46 [954,] 38.16 45 [955,] 38.20 41 [956,] 38.24 57 [957,] 38.28 65 [958,] 38.32 67 [959,] 38.36 50 [960,] 38.40 70 [961,] 38.44 57 [962,] 38.48 77 [963,] 38.52 52 [964,] 38.56 65 [965,] 38.60 43 [966,] 38.64 64 [967,] 38.68 62 [968,] 38.72 47 [969,] 38.76 64 [970,] 38.80 61 [971,] 38.84 74 [972,] 38.88 61 [973,] 38.92 65 [974,] 38.96 56 [975,] 39.00 63 [976,] 39.04 56 [977,] 39.08 58 [978,] 39.12 60 [979,] 39.16 62 [980,] 39.20 74 [981,] 39.24 71 [982,] 39.28 72 [983,] 39.32 59 [984,] 39.36 55 [985,] 39.40 55 [986,] 39.44 50 [987,] 39.48 53 [988,] 39.52 68 [989,] 39.56 52 [990,] 39.60 57 [991,] 39.64 64 [992,] 39.68 63 [993,] 39.72 73 [994,] 39.76 51 [995,] 39.80 60 [996,] 39.84 68 [997,] 39.88 55 [998,] 39.92 49 [999,] 39.96 66 [1000,] 40.00 59 $`17_TL (PMT)` [,1] [,2] [1,] 0.884 20 [2,] 1.768 3 [3,] 2.652 4 [4,] 3.536 1 [5,] 4.420 6 [6,] 5.304 22 [7,] 6.188 1 [8,] 7.072 10 [9,] 7.956 5 [10,] 8.840 10 [11,] 9.724 2 [12,] 10.608 13 [13,] 11.492 8 [14,] 12.376 2 [15,] 13.260 4 [16,] 14.144 8 [17,] 15.028 3 [18,] 15.912 4 [19,] 16.796 7 [20,] 17.680 3 [21,] 18.564 9 [22,] 19.448 1 [23,] 20.332 1 [24,] 21.216 5 [25,] 22.100 8 [26,] 22.984 6 [27,] 23.868 4 [28,] 24.752 7 [29,] 25.636 6 [30,] 26.520 2 [31,] 27.404 14 [32,] 28.288 4 [33,] 29.172 17 [34,] 30.056 3 [35,] 30.940 4 [36,] 31.824 2 [37,] 32.708 3 [38,] 33.592 5 [39,] 34.476 2 [40,] 35.360 1 [41,] 36.244 4 [42,] 37.128 4 [43,] 38.012 4 [44,] 38.896 6 [45,] 39.780 7 [46,] 40.664 4 [47,] 41.548 4 [48,] 42.432 3 [49,] 43.316 4 [50,] 44.200 3 [51,] 45.084 8 [52,] 45.968 1 [53,] 46.852 6 [54,] 47.736 0 [55,] 48.620 1 [56,] 49.504 1 [57,] 50.388 6 [58,] 51.272 3 [59,] 52.156 1 [60,] 53.040 3 [61,] 53.924 9 [62,] 54.808 3 [63,] 55.692 0 [64,] 56.576 8 [65,] 57.460 6 [66,] 58.344 8 [67,] 59.228 7 [68,] 60.112 1 [69,] 60.996 15 [70,] 61.880 3 [71,] 62.764 18 [72,] 63.648 2 [73,] 64.532 8 [74,] 65.416 6 [75,] 66.300 5 [76,] 67.184 6 [77,] 68.068 5 [78,] 68.952 6 [79,] 69.836 7 [80,] 70.720 7 [81,] 71.604 10 [82,] 72.488 18 [83,] 73.372 25 [84,] 74.256 9 [85,] 75.140 13 [86,] 76.024 9 [87,] 76.908 15 [88,] 77.792 14 [89,] 78.676 21 [90,] 79.560 9 [91,] 80.444 24 [92,] 81.328 9 [93,] 82.212 10 [94,] 83.096 7 [95,] 83.980 16 [96,] 84.864 16 [97,] 85.748 18 [98,] 86.632 23 [99,] 87.516 18 [100,] 88.400 39 [101,] 89.284 26 [102,] 90.168 16 [103,] 91.052 35 [104,] 91.936 31 [105,] 92.820 27 [106,] 93.704 26 [107,] 94.588 34 [108,] 95.472 38 [109,] 96.356 56 [110,] 97.240 44 [111,] 98.124 36 [112,] 99.008 59 [113,] 99.892 67 [114,] 100.776 58 [115,] 101.660 75 [116,] 102.544 55 [117,] 103.428 92 [118,] 104.312 55 [119,] 105.196 63 [120,] 106.080 88 [121,] 106.964 117 [122,] 107.848 95 [123,] 108.732 105 [124,] 109.616 140 [125,] 110.500 154 [126,] 111.384 115 [127,] 112.268 147 [128,] 113.152 182 [129,] 114.036 149 [130,] 114.920 157 [131,] 115.804 180 [132,] 116.688 206 [133,] 117.572 195 [134,] 118.456 213 [135,] 119.340 219 [136,] 120.224 230 [137,] 121.108 259 [138,] 121.992 267 [139,] 122.876 283 [140,] 123.760 308 [141,] 124.644 356 [142,] 125.528 346 [143,] 126.412 317 [144,] 127.296 363 [145,] 128.180 420 [146,] 129.064 394 [147,] 129.948 447 [148,] 130.832 478 [149,] 131.716 440 [150,] 132.600 460 [151,] 133.484 541 [152,] 134.368 518 [153,] 135.252 530 [154,] 136.136 567 [155,] 137.020 555 [156,] 137.904 574 [157,] 138.788 577 [158,] 139.672 584 [159,] 140.556 626 [160,] 141.440 673 [161,] 142.324 618 [162,] 143.208 617 [163,] 144.092 631 [164,] 144.976 699 [165,] 145.860 667 [166,] 146.744 673 [167,] 147.628 620 [168,] 148.512 653 [169,] 149.396 583 [170,] 150.280 672 [171,] 151.164 606 [172,] 152.048 661 [173,] 152.932 605 [174,] 153.816 608 [175,] 154.700 638 [176,] 155.584 616 [177,] 156.468 559 [178,] 157.352 573 [179,] 158.236 596 [180,] 159.120 635 [181,] 160.004 646 [182,] 160.888 634 [183,] 161.772 650 [184,] 162.656 593 [185,] 163.540 584 [186,] 164.424 658 [187,] 165.308 570 [188,] 166.192 620 [189,] 167.076 648 [190,] 167.960 670 [191,] 168.844 638 [192,] 169.728 668 [193,] 170.612 661 [194,] 171.496 646 [195,] 172.380 644 [196,] 173.264 655 [197,] 174.148 671 [198,] 175.032 671 [199,] 175.916 691 [200,] 176.800 640 [201,] 177.684 715 [202,] 178.568 653 [203,] 179.452 649 [204,] 180.336 715 [205,] 181.220 686 [206,] 182.104 625 [207,] 182.988 708 [208,] 183.872 644 [209,] 184.756 735 [210,] 185.640 725 [211,] 186.524 730 [212,] 187.408 668 [213,] 188.292 709 [214,] 189.176 699 [215,] 190.060 728 [216,] 190.944 701 [217,] 191.828 752 [218,] 192.712 775 [219,] 193.596 772 [220,] 194.480 748 [221,] 195.364 783 [222,] 196.248 752 [223,] 197.132 788 [224,] 198.016 822 [225,] 198.900 825 [226,] 199.784 784 [227,] 200.668 854 [228,] 201.552 733 [229,] 202.436 879 [230,] 203.320 848 [231,] 204.204 853 [232,] 205.088 808 [233,] 205.972 855 [234,] 206.856 919 [235,] 207.740 913 [236,] 208.624 770 [237,] 209.508 839 [238,] 210.392 817 [239,] 211.276 960 [240,] 212.160 897 [241,] 213.044 879 [242,] 213.928 859 [243,] 214.812 849 [244,] 215.696 837 [245,] 216.580 907 [246,] 217.464 854 [247,] 218.348 895 [248,] 219.232 873 [249,] 220.116 832 [250,] 221.000 266 $`18_OSL (PMT)` [,1] [,2] [1,] 0.04 16684 [2,] 0.08 14410 [3,] 0.12 11961 [4,] 0.16 10396 [5,] 0.20 8549 [6,] 0.24 7578 [7,] 0.28 6513 [8,] 0.32 5633 [9,] 0.36 5106 [10,] 0.40 4259 [11,] 0.44 3758 [12,] 0.48 3379 [13,] 0.52 2941 [14,] 0.56 2653 [15,] 0.60 2286 [16,] 0.64 2111 [17,] 0.68 1816 [18,] 0.72 1628 [19,] 0.76 1605 [20,] 0.80 1337 [21,] 0.84 1310 [22,] 0.88 1090 [23,] 0.92 1044 [24,] 0.96 922 [25,] 1.00 897 [26,] 1.04 864 [27,] 1.08 756 [28,] 1.12 672 [29,] 1.16 688 [30,] 1.20 580 [31,] 1.24 573 [32,] 1.28 603 [33,] 1.32 517 [34,] 1.36 501 [35,] 1.40 517 [36,] 1.44 404 [37,] 1.48 446 [38,] 1.52 404 [39,] 1.56 418 [40,] 1.60 362 [41,] 1.64 378 [42,] 1.68 372 [43,] 1.72 353 [44,] 1.76 290 [45,] 1.80 291 [46,] 1.84 307 [47,] 1.88 280 [48,] 1.92 319 [49,] 1.96 291 [50,] 2.00 299 [51,] 2.04 301 [52,] 2.08 276 [53,] 2.12 301 [54,] 2.16 267 [55,] 2.20 285 [56,] 2.24 245 [57,] 2.28 233 [58,] 2.32 257 [59,] 2.36 227 [60,] 2.40 231 [61,] 2.44 248 [62,] 2.48 253 [63,] 2.52 242 [64,] 2.56 238 [65,] 2.60 270 [66,] 2.64 209 [67,] 2.68 215 [68,] 2.72 223 [69,] 2.76 251 [70,] 2.80 198 [71,] 2.84 214 [72,] 2.88 233 [73,] 2.92 229 [74,] 2.96 239 [75,] 3.00 210 [76,] 3.04 196 [77,] 3.08 208 [78,] 3.12 216 [79,] 3.16 180 [80,] 3.20 206 [81,] 3.24 180 [82,] 3.28 231 [83,] 3.32 229 [84,] 3.36 200 [85,] 3.40 166 [86,] 3.44 212 [87,] 3.48 221 [88,] 3.52 193 [89,] 3.56 178 [90,] 3.60 177 [91,] 3.64 194 [92,] 3.68 198 [93,] 3.72 169 [94,] 3.76 179 [95,] 3.80 193 [96,] 3.84 169 [97,] 3.88 153 [98,] 3.92 183 [99,] 3.96 161 [100,] 4.00 185 [101,] 4.04 151 [102,] 4.08 161 [103,] 4.12 185 [104,] 4.16 183 [105,] 4.20 175 [106,] 4.24 163 [107,] 4.28 171 [108,] 4.32 157 [109,] 4.36 193 [110,] 4.40 164 [111,] 4.44 179 [112,] 4.48 167 [113,] 4.52 219 [114,] 4.56 176 [115,] 4.60 155 [116,] 4.64 176 [117,] 4.68 151 [118,] 4.72 175 [119,] 4.76 151 [120,] 4.80 173 [121,] 4.84 142 [122,] 4.88 145 [123,] 4.92 146 [124,] 4.96 172 [125,] 5.00 142 [126,] 5.04 136 [127,] 5.08 141 [128,] 5.12 183 [129,] 5.16 164 [130,] 5.20 147 [131,] 5.24 161 [132,] 5.28 171 [133,] 5.32 135 [134,] 5.36 137 [135,] 5.40 164 [136,] 5.44 179 [137,] 5.48 154 [138,] 5.52 168 [139,] 5.56 159 [140,] 5.60 161 [141,] 5.64 167 [142,] 5.68 145 [143,] 5.72 151 [144,] 5.76 139 [145,] 5.80 169 [146,] 5.84 176 [147,] 5.88 136 [148,] 5.92 167 [149,] 5.96 143 [150,] 6.00 150 [151,] 6.04 149 [152,] 6.08 149 [153,] 6.12 149 [154,] 6.16 135 [155,] 6.20 132 [156,] 6.24 151 [157,] 6.28 152 [158,] 6.32 142 [159,] 6.36 142 [160,] 6.40 134 [161,] 6.44 134 [162,] 6.48 132 [163,] 6.52 142 [164,] 6.56 133 [165,] 6.60 114 [166,] 6.64 154 [167,] 6.68 119 [168,] 6.72 117 [169,] 6.76 132 [170,] 6.80 133 [171,] 6.84 122 [172,] 6.88 119 [173,] 6.92 135 [174,] 6.96 144 [175,] 7.00 130 [176,] 7.04 145 [177,] 7.08 121 [178,] 7.12 109 [179,] 7.16 135 [180,] 7.20 124 [181,] 7.24 142 [182,] 7.28 121 [183,] 7.32 123 [184,] 7.36 150 [185,] 7.40 134 [186,] 7.44 129 [187,] 7.48 144 [188,] 7.52 131 [189,] 7.56 143 [190,] 7.60 132 [191,] 7.64 142 [192,] 7.68 136 [193,] 7.72 119 [194,] 7.76 115 [195,] 7.80 107 [196,] 7.84 115 [197,] 7.88 145 [198,] 7.92 146 [199,] 7.96 113 [200,] 8.00 146 [201,] 8.04 127 [202,] 8.08 123 [203,] 8.12 147 [204,] 8.16 131 [205,] 8.20 136 [206,] 8.24 166 [207,] 8.28 139 [208,] 8.32 133 [209,] 8.36 133 [210,] 8.40 140 [211,] 8.44 113 [212,] 8.48 107 [213,] 8.52 135 [214,] 8.56 128 [215,] 8.60 123 [216,] 8.64 113 [217,] 8.68 116 [218,] 8.72 109 [219,] 8.76 125 [220,] 8.80 123 [221,] 8.84 128 [222,] 8.88 128 [223,] 8.92 123 [224,] 8.96 91 [225,] 9.00 123 [226,] 9.04 114 [227,] 9.08 124 [228,] 9.12 127 [229,] 9.16 122 [230,] 9.20 105 [231,] 9.24 112 [232,] 9.28 101 [233,] 9.32 132 [234,] 9.36 122 [235,] 9.40 120 [236,] 9.44 113 [237,] 9.48 118 [238,] 9.52 104 [239,] 9.56 139 [240,] 9.60 122 [241,] 9.64 110 [242,] 9.68 91 [243,] 9.72 122 [244,] 9.76 124 [245,] 9.80 125 [246,] 9.84 98 [247,] 9.88 130 [248,] 9.92 106 [249,] 9.96 118 [250,] 10.00 122 [251,] 10.04 117 [252,] 10.08 119 [253,] 10.12 111 [254,] 10.16 96 [255,] 10.20 112 [256,] 10.24 112 [257,] 10.28 136 [258,] 10.32 99 [259,] 10.36 133 [260,] 10.40 115 [261,] 10.44 118 [262,] 10.48 115 [263,] 10.52 112 [264,] 10.56 121 [265,] 10.60 110 [266,] 10.64 128 [267,] 10.68 120 [268,] 10.72 110 [269,] 10.76 88 [270,] 10.80 112 [271,] 10.84 112 [272,] 10.88 115 [273,] 10.92 141 [274,] 10.96 97 [275,] 11.00 110 [276,] 11.04 117 [277,] 11.08 109 [278,] 11.12 111 [279,] 11.16 116 [280,] 11.20 124 [281,] 11.24 123 [282,] 11.28 118 [283,] 11.32 119 [284,] 11.36 99 [285,] 11.40 124 [286,] 11.44 101 [287,] 11.48 111 [288,] 11.52 103 [289,] 11.56 92 [290,] 11.60 103 [291,] 11.64 91 [292,] 11.68 103 [293,] 11.72 123 [294,] 11.76 123 [295,] 11.80 80 [296,] 11.84 125 [297,] 11.88 101 [298,] 11.92 100 [299,] 11.96 99 [300,] 12.00 117 [301,] 12.04 107 [302,] 12.08 98 [303,] 12.12 122 [304,] 12.16 105 [305,] 12.20 115 [306,] 12.24 106 [307,] 12.28 97 [308,] 12.32 99 [309,] 12.36 107 [310,] 12.40 108 [311,] 12.44 93 [312,] 12.48 89 [313,] 12.52 109 [314,] 12.56 113 [315,] 12.60 124 [316,] 12.64 103 [317,] 12.68 111 [318,] 12.72 138 [319,] 12.76 113 [320,] 12.80 81 [321,] 12.84 105 [322,] 12.88 125 [323,] 12.92 116 [324,] 12.96 132 [325,] 13.00 118 [326,] 13.04 111 [327,] 13.08 102 [328,] 13.12 102 [329,] 13.16 90 [330,] 13.20 99 [331,] 13.24 110 [332,] 13.28 106 [333,] 13.32 95 [334,] 13.36 126 [335,] 13.40 84 [336,] 13.44 101 [337,] 13.48 117 [338,] 13.52 119 [339,] 13.56 131 [340,] 13.60 107 [341,] 13.64 110 [342,] 13.68 83 [343,] 13.72 101 [344,] 13.76 102 [345,] 13.80 102 [346,] 13.84 112 [347,] 13.88 115 [348,] 13.92 88 [349,] 13.96 127 [350,] 14.00 105 [351,] 14.04 110 [352,] 14.08 108 [353,] 14.12 105 [354,] 14.16 96 [355,] 14.20 94 [356,] 14.24 103 [357,] 14.28 111 [358,] 14.32 98 [359,] 14.36 102 [360,] 14.40 106 [361,] 14.44 105 [362,] 14.48 101 [363,] 14.52 114 [364,] 14.56 103 [365,] 14.60 89 [366,] 14.64 97 [367,] 14.68 110 [368,] 14.72 102 [369,] 14.76 86 [370,] 14.80 122 [371,] 14.84 110 [372,] 14.88 99 [373,] 14.92 133 [374,] 14.96 102 [375,] 15.00 101 [376,] 15.04 129 [377,] 15.08 96 [378,] 15.12 89 [379,] 15.16 108 [380,] 15.20 105 [381,] 15.24 104 [382,] 15.28 96 [383,] 15.32 95 [384,] 15.36 120 [385,] 15.40 101 [386,] 15.44 99 [387,] 15.48 106 [388,] 15.52 90 [389,] 15.56 80 [390,] 15.60 90 [391,] 15.64 98 [392,] 15.68 91 [393,] 15.72 103 [394,] 15.76 101 [395,] 15.80 85 [396,] 15.84 87 [397,] 15.88 95 [398,] 15.92 105 [399,] 15.96 113 [400,] 16.00 103 [401,] 16.04 83 [402,] 16.08 101 [403,] 16.12 111 [404,] 16.16 110 [405,] 16.20 110 [406,] 16.24 89 [407,] 16.28 89 [408,] 16.32 95 [409,] 16.36 120 [410,] 16.40 94 [411,] 16.44 99 [412,] 16.48 117 [413,] 16.52 83 [414,] 16.56 98 [415,] 16.60 99 [416,] 16.64 84 [417,] 16.68 92 [418,] 16.72 76 [419,] 16.76 92 [420,] 16.80 119 [421,] 16.84 100 [422,] 16.88 87 [423,] 16.92 109 [424,] 16.96 99 [425,] 17.00 118 [426,] 17.04 114 [427,] 17.08 104 [428,] 17.12 83 [429,] 17.16 96 [430,] 17.20 102 [431,] 17.24 113 [432,] 17.28 98 [433,] 17.32 91 [434,] 17.36 97 [435,] 17.40 126 [436,] 17.44 104 [437,] 17.48 90 [438,] 17.52 91 [439,] 17.56 98 [440,] 17.60 88 [441,] 17.64 86 [442,] 17.68 105 [443,] 17.72 99 [444,] 17.76 89 [445,] 17.80 100 [446,] 17.84 104 [447,] 17.88 97 [448,] 17.92 106 [449,] 17.96 96 [450,] 18.00 91 [451,] 18.04 111 [452,] 18.08 88 [453,] 18.12 92 [454,] 18.16 113 [455,] 18.20 102 [456,] 18.24 101 [457,] 18.28 92 [458,] 18.32 84 [459,] 18.36 99 [460,] 18.40 102 [461,] 18.44 121 [462,] 18.48 111 [463,] 18.52 98 [464,] 18.56 98 [465,] 18.60 106 [466,] 18.64 100 [467,] 18.68 115 [468,] 18.72 122 [469,] 18.76 84 [470,] 18.80 86 [471,] 18.84 97 [472,] 18.88 90 [473,] 18.92 100 [474,] 18.96 91 [475,] 19.00 90 [476,] 19.04 114 [477,] 19.08 115 [478,] 19.12 71 [479,] 19.16 105 [480,] 19.20 104 [481,] 19.24 88 [482,] 19.28 92 [483,] 19.32 91 [484,] 19.36 85 [485,] 19.40 102 [486,] 19.44 94 [487,] 19.48 79 [488,] 19.52 112 [489,] 19.56 93 [490,] 19.60 82 [491,] 19.64 111 [492,] 19.68 119 [493,] 19.72 117 [494,] 19.76 114 [495,] 19.80 116 [496,] 19.84 80 [497,] 19.88 90 [498,] 19.92 91 [499,] 19.96 79 [500,] 20.00 110 [501,] 20.04 85 [502,] 20.08 105 [503,] 20.12 92 [504,] 20.16 97 [505,] 20.20 100 [506,] 20.24 88 [507,] 20.28 110 [508,] 20.32 94 [509,] 20.36 86 [510,] 20.40 81 [511,] 20.44 89 [512,] 20.48 76 [513,] 20.52 87 [514,] 20.56 90 [515,] 20.60 123 [516,] 20.64 66 [517,] 20.68 79 [518,] 20.72 94 [519,] 20.76 90 [520,] 20.80 95 [521,] 20.84 109 [522,] 20.88 111 [523,] 20.92 76 [524,] 20.96 85 [525,] 21.00 96 [526,] 21.04 86 [527,] 21.08 89 [528,] 21.12 97 [529,] 21.16 102 [530,] 21.20 93 [531,] 21.24 92 [532,] 21.28 84 [533,] 21.32 91 [534,] 21.36 86 [535,] 21.40 83 [536,] 21.44 82 [537,] 21.48 73 [538,] 21.52 110 [539,] 21.56 84 [540,] 21.60 90 [541,] 21.64 91 [542,] 21.68 89 [543,] 21.72 108 [544,] 21.76 91 [545,] 21.80 123 [546,] 21.84 93 [547,] 21.88 68 [548,] 21.92 99 [549,] 21.96 77 [550,] 22.00 80 [551,] 22.04 90 [552,] 22.08 70 [553,] 22.12 98 [554,] 22.16 111 [555,] 22.20 83 [556,] 22.24 83 [557,] 22.28 122 [558,] 22.32 85 [559,] 22.36 98 [560,] 22.40 82 [561,] 22.44 86 [562,] 22.48 95 [563,] 22.52 77 [564,] 22.56 93 [565,] 22.60 69 [566,] 22.64 97 [567,] 22.68 97 [568,] 22.72 95 [569,] 22.76 67 [570,] 22.80 87 [571,] 22.84 91 [572,] 22.88 89 [573,] 22.92 103 [574,] 22.96 91 [575,] 23.00 95 [576,] 23.04 92 [577,] 23.08 68 [578,] 23.12 59 [579,] 23.16 90 [580,] 23.20 86 [581,] 23.24 98 [582,] 23.28 72 [583,] 23.32 85 [584,] 23.36 105 [585,] 23.40 94 [586,] 23.44 91 [587,] 23.48 91 [588,] 23.52 71 [589,] 23.56 89 [590,] 23.60 90 [591,] 23.64 102 [592,] 23.68 82 [593,] 23.72 91 [594,] 23.76 85 [595,] 23.80 92 [596,] 23.84 92 [597,] 23.88 82 [598,] 23.92 91 [599,] 23.96 114 [600,] 24.00 91 [601,] 24.04 70 [602,] 24.08 79 [603,] 24.12 91 [604,] 24.16 98 [605,] 24.20 120 [606,] 24.24 92 [607,] 24.28 101 [608,] 24.32 84 [609,] 24.36 104 [610,] 24.40 84 [611,] 24.44 100 [612,] 24.48 89 [613,] 24.52 86 [614,] 24.56 79 [615,] 24.60 109 [616,] 24.64 97 [617,] 24.68 80 [618,] 24.72 85 [619,] 24.76 87 [620,] 24.80 119 [621,] 24.84 96 [622,] 24.88 86 [623,] 24.92 91 [624,] 24.96 93 [625,] 25.00 75 [626,] 25.04 73 [627,] 25.08 89 [628,] 25.12 90 [629,] 25.16 107 [630,] 25.20 98 [631,] 25.24 74 [632,] 25.28 81 [633,] 25.32 68 [634,] 25.36 91 [635,] 25.40 98 [636,] 25.44 82 [637,] 25.48 90 [638,] 25.52 82 [639,] 25.56 93 [640,] 25.60 94 [641,] 25.64 113 [642,] 25.68 82 [643,] 25.72 109 [644,] 25.76 89 [645,] 25.80 84 [646,] 25.84 91 [647,] 25.88 92 [648,] 25.92 93 [649,] 25.96 71 [650,] 26.00 75 [651,] 26.04 89 [652,] 26.08 78 [653,] 26.12 79 [654,] 26.16 97 [655,] 26.20 76 [656,] 26.24 89 [657,] 26.28 83 [658,] 26.32 101 [659,] 26.36 85 [660,] 26.40 94 [661,] 26.44 97 [662,] 26.48 90 [663,] 26.52 90 [664,] 26.56 77 [665,] 26.60 83 [666,] 26.64 96 [667,] 26.68 89 [668,] 26.72 101 [669,] 26.76 66 [670,] 26.80 80 [671,] 26.84 93 [672,] 26.88 101 [673,] 26.92 51 [674,] 26.96 91 [675,] 27.00 111 [676,] 27.04 71 [677,] 27.08 81 [678,] 27.12 98 [679,] 27.16 79 [680,] 27.20 88 [681,] 27.24 90 [682,] 27.28 88 [683,] 27.32 102 [684,] 27.36 81 [685,] 27.40 110 [686,] 27.44 92 [687,] 27.48 74 [688,] 27.52 84 [689,] 27.56 98 [690,] 27.60 73 [691,] 27.64 79 [692,] 27.68 81 [693,] 27.72 87 [694,] 27.76 82 [695,] 27.80 112 [696,] 27.84 96 [697,] 27.88 99 [698,] 27.92 98 [699,] 27.96 100 [700,] 28.00 59 [701,] 28.04 94 [702,] 28.08 86 [703,] 28.12 92 [704,] 28.16 72 [705,] 28.20 72 [706,] 28.24 90 [707,] 28.28 89 [708,] 28.32 74 [709,] 28.36 89 [710,] 28.40 82 [711,] 28.44 74 [712,] 28.48 113 [713,] 28.52 81 [714,] 28.56 91 [715,] 28.60 84 [716,] 28.64 81 [717,] 28.68 71 [718,] 28.72 96 [719,] 28.76 72 [720,] 28.80 103 [721,] 28.84 80 [722,] 28.88 82 [723,] 28.92 92 [724,] 28.96 80 [725,] 29.00 85 [726,] 29.04 85 [727,] 29.08 88 [728,] 29.12 87 [729,] 29.16 94 [730,] 29.20 85 [731,] 29.24 73 [732,] 29.28 88 [733,] 29.32 69 [734,] 29.36 81 [735,] 29.40 92 [736,] 29.44 78 [737,] 29.48 100 [738,] 29.52 87 [739,] 29.56 114 [740,] 29.60 66 [741,] 29.64 103 [742,] 29.68 82 [743,] 29.72 83 [744,] 29.76 71 [745,] 29.80 87 [746,] 29.84 77 [747,] 29.88 97 [748,] 29.92 73 [749,] 29.96 84 [750,] 30.00 91 [751,] 30.04 84 [752,] 30.08 74 [753,] 30.12 81 [754,] 30.16 74 [755,] 30.20 77 [756,] 30.24 91 [757,] 30.28 78 [758,] 30.32 85 [759,] 30.36 84 [760,] 30.40 77 [761,] 30.44 53 [762,] 30.48 77 [763,] 30.52 64 [764,] 30.56 80 [765,] 30.60 75 [766,] 30.64 87 [767,] 30.68 97 [768,] 30.72 72 [769,] 30.76 90 [770,] 30.80 85 [771,] 30.84 83 [772,] 30.88 79 [773,] 30.92 81 [774,] 30.96 68 [775,] 31.00 73 [776,] 31.04 73 [777,] 31.08 106 [778,] 31.12 88 [779,] 31.16 65 [780,] 31.20 85 [781,] 31.24 89 [782,] 31.28 81 [783,] 31.32 92 [784,] 31.36 85 [785,] 31.40 90 [786,] 31.44 90 [787,] 31.48 85 [788,] 31.52 91 [789,] 31.56 81 [790,] 31.60 87 [791,] 31.64 69 [792,] 31.68 78 [793,] 31.72 87 [794,] 31.76 106 [795,] 31.80 68 [796,] 31.84 68 [797,] 31.88 71 [798,] 31.92 70 [799,] 31.96 87 [800,] 32.00 81 [801,] 32.04 92 [802,] 32.08 64 [803,] 32.12 94 [804,] 32.16 80 [805,] 32.20 83 [806,] 32.24 73 [807,] 32.28 104 [808,] 32.32 64 [809,] 32.36 69 [810,] 32.40 82 [811,] 32.44 73 [812,] 32.48 79 [813,] 32.52 76 [814,] 32.56 77 [815,] 32.60 77 [816,] 32.64 99 [817,] 32.68 90 [818,] 32.72 78 [819,] 32.76 79 [820,] 32.80 79 [821,] 32.84 93 [822,] 32.88 83 [823,] 32.92 76 [824,] 32.96 70 [825,] 33.00 67 [826,] 33.04 83 [827,] 33.08 88 [828,] 33.12 85 [829,] 33.16 85 [830,] 33.20 80 [831,] 33.24 86 [832,] 33.28 97 [833,] 33.32 71 [834,] 33.36 106 [835,] 33.40 75 [836,] 33.44 86 [837,] 33.48 101 [838,] 33.52 80 [839,] 33.56 77 [840,] 33.60 80 [841,] 33.64 72 [842,] 33.68 113 [843,] 33.72 85 [844,] 33.76 92 [845,] 33.80 87 [846,] 33.84 61 [847,] 33.88 76 [848,] 33.92 76 [849,] 33.96 103 [850,] 34.00 83 [851,] 34.04 66 [852,] 34.08 78 [853,] 34.12 77 [854,] 34.16 94 [855,] 34.20 81 [856,] 34.24 89 [857,] 34.28 89 [858,] 34.32 58 [859,] 34.36 97 [860,] 34.40 70 [861,] 34.44 101 [862,] 34.48 92 [863,] 34.52 81 [864,] 34.56 82 [865,] 34.60 92 [866,] 34.64 77 [867,] 34.68 93 [868,] 34.72 84 [869,] 34.76 78 [870,] 34.80 81 [871,] 34.84 77 [872,] 34.88 111 [873,] 34.92 79 [874,] 34.96 89 [875,] 35.00 85 [876,] 35.04 88 [877,] 35.08 81 [878,] 35.12 76 [879,] 35.16 102 [880,] 35.20 65 [881,] 35.24 65 [882,] 35.28 79 [883,] 35.32 82 [884,] 35.36 82 [885,] 35.40 82 [886,] 35.44 66 [887,] 35.48 74 [888,] 35.52 79 [889,] 35.56 81 [890,] 35.60 60 [891,] 35.64 79 [892,] 35.68 94 [893,] 35.72 82 [894,] 35.76 104 [895,] 35.80 75 [896,] 35.84 86 [897,] 35.88 87 [898,] 35.92 90 [899,] 35.96 67 [900,] 36.00 94 [901,] 36.04 87 [902,] 36.08 95 [903,] 36.12 73 [904,] 36.16 81 [905,] 36.20 81 [906,] 36.24 74 [907,] 36.28 66 [908,] 36.32 89 [909,] 36.36 68 [910,] 36.40 59 [911,] 36.44 81 [912,] 36.48 73 [913,] 36.52 58 [914,] 36.56 77 [915,] 36.60 82 [916,] 36.64 87 [917,] 36.68 86 [918,] 36.72 85 [919,] 36.76 79 [920,] 36.80 91 [921,] 36.84 66 [922,] 36.88 83 [923,] 36.92 81 [924,] 36.96 87 [925,] 37.00 68 [926,] 37.04 71 [927,] 37.08 89 [928,] 37.12 77 [929,] 37.16 75 [930,] 37.20 79 [931,] 37.24 75 [932,] 37.28 89 [933,] 37.32 83 [934,] 37.36 67 [935,] 37.40 80 [936,] 37.44 79 [937,] 37.48 79 [938,] 37.52 69 [939,] 37.56 82 [940,] 37.60 70 [941,] 37.64 76 [942,] 37.68 65 [943,] 37.72 90 [944,] 37.76 93 [945,] 37.80 61 [946,] 37.84 81 [947,] 37.88 87 [948,] 37.92 75 [949,] 37.96 86 [950,] 38.00 76 [951,] 38.04 79 [952,] 38.08 59 [953,] 38.12 61 [954,] 38.16 88 [955,] 38.20 91 [956,] 38.24 69 [957,] 38.28 80 [958,] 38.32 73 [959,] 38.36 66 [960,] 38.40 81 [961,] 38.44 74 [962,] 38.48 62 [963,] 38.52 88 [964,] 38.56 74 [965,] 38.60 76 [966,] 38.64 82 [967,] 38.68 77 [968,] 38.72 59 [969,] 38.76 69 [970,] 38.80 79 [971,] 38.84 87 [972,] 38.88 69 [973,] 38.92 85 [974,] 38.96 86 [975,] 39.00 82 [976,] 39.04 70 [977,] 39.08 79 [978,] 39.12 92 [979,] 39.16 84 [980,] 39.20 83 [981,] 39.24 69 [982,] 39.28 87 [983,] 39.32 78 [984,] 39.36 84 [985,] 39.40 71 [986,] 39.44 83 [987,] 39.48 79 [988,] 39.52 99 [989,] 39.56 82 [990,] 39.60 74 [991,] 39.64 74 [992,] 39.68 64 [993,] 39.72 75 [994,] 39.76 103 [995,] 39.80 75 [996,] 39.84 75 [997,] 39.88 68 [998,] 39.92 87 [999,] 39.96 75 [1000,] 40.00 63 $`19_TL (PMT)` [,1] [,2] [1,] 0.64 2 [2,] 1.28 8 [3,] 1.92 0 [4,] 2.56 1 [5,] 3.20 10 [6,] 3.84 5 [7,] 4.48 2 [8,] 5.12 11 [9,] 5.76 4 [10,] 6.40 19 [11,] 7.04 5 [12,] 7.68 9 [13,] 8.32 7 [14,] 8.96 5 [15,] 9.60 9 [16,] 10.24 3 [17,] 10.88 7 [18,] 11.52 5 [19,] 12.16 6 [20,] 12.80 7 [21,] 13.44 1 [22,] 14.08 3 [23,] 14.72 7 [24,] 15.36 2 [25,] 16.00 5 [26,] 16.64 2 [27,] 17.28 2 [28,] 17.92 1 [29,] 18.56 0 [30,] 19.20 3 [31,] 19.84 3 [32,] 20.48 1 [33,] 21.12 1 [34,] 21.76 6 [35,] 22.40 9 [36,] 23.04 3 [37,] 23.68 7 [38,] 24.32 4 [39,] 24.96 5 [40,] 25.60 3 [41,] 26.24 10 [42,] 26.88 1 [43,] 27.52 3 [44,] 28.16 0 [45,] 28.80 1 [46,] 29.44 1 [47,] 30.08 2 [48,] 30.72 2 [49,] 31.36 5 [50,] 32.00 0 [51,] 32.64 3 [52,] 33.28 3 [53,] 33.92 4 [54,] 34.56 1 [55,] 35.20 12 [56,] 35.84 4 [57,] 36.48 1 [58,] 37.12 5 [59,] 37.76 4 [60,] 38.40 2 [61,] 39.04 2 [62,] 39.68 8 [63,] 40.32 4 [64,] 40.96 7 [65,] 41.60 10 [66,] 42.24 3 [67,] 42.88 13 [68,] 43.52 13 [69,] 44.16 5 [70,] 44.80 6 [71,] 45.44 4 [72,] 46.08 6 [73,] 46.72 11 [74,] 47.36 0 [75,] 48.00 9 [76,] 48.64 1 [77,] 49.28 5 [78,] 49.92 5 [79,] 50.56 7 [80,] 51.20 5 [81,] 51.84 11 [82,] 52.48 4 [83,] 53.12 4 [84,] 53.76 12 [85,] 54.40 6 [86,] 55.04 5 [87,] 55.68 6 [88,] 56.32 11 [89,] 56.96 12 [90,] 57.60 13 [91,] 58.24 16 [92,] 58.88 19 [93,] 59.52 6 [94,] 60.16 16 [95,] 60.80 12 [96,] 61.44 15 [97,] 62.08 16 [98,] 62.72 16 [99,] 63.36 19 [100,] 64.00 18 [101,] 64.64 16 [102,] 65.28 26 [103,] 65.92 19 [104,] 66.56 18 [105,] 67.20 20 [106,] 67.84 22 [107,] 68.48 23 [108,] 69.12 28 [109,] 69.76 33 [110,] 70.40 43 [111,] 71.04 34 [112,] 71.68 30 [113,] 72.32 25 [114,] 72.96 61 [115,] 73.60 40 [116,] 74.24 41 [117,] 74.88 62 [118,] 75.52 72 [119,] 76.16 48 [120,] 76.80 47 [121,] 77.44 54 [122,] 78.08 60 [123,] 78.72 60 [124,] 79.36 74 [125,] 80.00 68 [126,] 80.64 74 [127,] 81.28 88 [128,] 81.92 85 [129,] 82.56 88 [130,] 83.20 106 [131,] 83.84 103 [132,] 84.48 120 [133,] 85.12 132 [134,] 85.76 107 [135,] 86.40 146 [136,] 87.04 157 [137,] 87.68 131 [138,] 88.32 145 [139,] 88.96 150 [140,] 89.60 121 [141,] 90.24 157 [142,] 90.88 165 [143,] 91.52 160 [144,] 92.16 189 [145,] 92.80 216 [146,] 93.44 222 [147,] 94.08 234 [148,] 94.72 202 [149,] 95.36 174 [150,] 96.00 187 [151,] 96.64 214 [152,] 97.28 220 [153,] 97.92 277 [154,] 98.56 251 [155,] 99.20 265 [156,] 99.84 254 [157,] 100.48 262 [158,] 101.12 245 [159,] 101.76 302 [160,] 102.40 296 [161,] 103.04 287 [162,] 103.68 310 [163,] 104.32 299 [164,] 104.96 312 [165,] 105.60 292 [166,] 106.24 291 [167,] 106.88 330 [168,] 107.52 301 [169,] 108.16 295 [170,] 108.80 285 [171,] 109.44 284 [172,] 110.08 272 [173,] 110.72 282 [174,] 111.36 270 [175,] 112.00 279 [176,] 112.64 255 [177,] 113.28 199 [178,] 113.92 245 [179,] 114.56 195 [180,] 115.20 214 [181,] 115.84 172 [182,] 116.48 210 [183,] 117.12 208 [184,] 117.76 181 [185,] 118.40 178 [186,] 119.04 155 [187,] 119.68 159 [188,] 120.32 136 [189,] 120.96 145 [190,] 121.60 121 [191,] 122.24 141 [192,] 122.88 132 [193,] 123.52 97 [194,] 124.16 105 [195,] 124.80 94 [196,] 125.44 106 [197,] 126.08 75 [198,] 126.72 71 [199,] 127.36 96 [200,] 128.00 75 [201,] 128.64 105 [202,] 129.28 111 [203,] 129.92 76 [204,] 130.56 91 [205,] 131.20 74 [206,] 131.84 75 [207,] 132.48 87 [208,] 133.12 66 [209,] 133.76 75 [210,] 134.40 88 [211,] 135.04 84 [212,] 135.68 86 [213,] 136.32 98 [214,] 136.96 82 [215,] 137.60 111 [216,] 138.24 101 [217,] 138.88 97 [218,] 139.52 104 [219,] 140.16 93 [220,] 140.80 91 [221,] 141.44 89 [222,] 142.08 98 [223,] 142.72 87 [224,] 143.36 99 [225,] 144.00 134 [226,] 144.64 85 [227,] 145.28 95 [228,] 145.92 68 [229,] 146.56 105 [230,] 147.20 83 [231,] 147.84 104 [232,] 148.48 110 [233,] 149.12 70 [234,] 149.76 94 [235,] 150.40 91 [236,] 151.04 97 [237,] 151.68 113 [238,] 152.32 83 [239,] 152.96 95 [240,] 153.60 90 [241,] 154.24 100 [242,] 154.88 76 [243,] 155.52 97 [244,] 156.16 92 [245,] 156.80 107 [246,] 157.44 82 [247,] 158.08 101 [248,] 158.72 91 [249,] 159.36 75 [250,] 160.00 74 $`20_OSL (PMT)` [,1] [,2] [1,] 0.04 3102 [2,] 0.08 2613 [3,] 0.12 2358 [4,] 0.16 2071 [5,] 0.20 1823 [6,] 0.24 1609 [7,] 0.28 1341 [8,] 0.32 1236 [9,] 0.36 1049 [10,] 0.40 921 [11,] 0.44 851 [12,] 0.48 725 [13,] 0.52 744 [14,] 0.56 581 [15,] 0.60 541 [16,] 0.64 590 [17,] 0.68 474 [18,] 0.72 475 [19,] 0.76 377 [20,] 0.80 368 [21,] 0.84 361 [22,] 0.88 325 [23,] 0.92 338 [24,] 0.96 308 [25,] 1.00 301 [26,] 1.04 283 [27,] 1.08 280 [28,] 1.12 240 [29,] 1.16 254 [30,] 1.20 246 [31,] 1.24 222 [32,] 1.28 220 [33,] 1.32 184 [34,] 1.36 185 [35,] 1.40 160 [36,] 1.44 204 [37,] 1.48 160 [38,] 1.52 230 [39,] 1.56 183 [40,] 1.60 162 [41,] 1.64 147 [42,] 1.68 180 [43,] 1.72 172 [44,] 1.76 176 [45,] 1.80 163 [46,] 1.84 157 [47,] 1.88 166 [48,] 1.92 173 [49,] 1.96 148 [50,] 2.00 145 [51,] 2.04 140 [52,] 2.08 140 [53,] 2.12 132 [54,] 2.16 124 [55,] 2.20 137 [56,] 2.24 139 [57,] 2.28 144 [58,] 2.32 134 [59,] 2.36 131 [60,] 2.40 145 [61,] 2.44 144 [62,] 2.48 127 [63,] 2.52 136 [64,] 2.56 107 [65,] 2.60 136 [66,] 2.64 123 [67,] 2.68 116 [68,] 2.72 145 [69,] 2.76 117 [70,] 2.80 129 [71,] 2.84 131 [72,] 2.88 137 [73,] 2.92 115 [74,] 2.96 124 [75,] 3.00 135 [76,] 3.04 144 [77,] 3.08 128 [78,] 3.12 119 [79,] 3.16 137 [80,] 3.20 120 [81,] 3.24 124 [82,] 3.28 120 [83,] 3.32 133 [84,] 3.36 107 [85,] 3.40 143 [86,] 3.44 122 [87,] 3.48 132 [88,] 3.52 146 [89,] 3.56 125 [90,] 3.60 130 [91,] 3.64 130 [92,] 3.68 109 [93,] 3.72 109 [94,] 3.76 125 [95,] 3.80 124 [96,] 3.84 115 [97,] 3.88 118 [98,] 3.92 109 [99,] 3.96 115 [100,] 4.00 104 [101,] 4.04 115 [102,] 4.08 148 [103,] 4.12 97 [104,] 4.16 111 [105,] 4.20 111 [106,] 4.24 124 [107,] 4.28 105 [108,] 4.32 114 [109,] 4.36 99 [110,] 4.40 111 [111,] 4.44 110 [112,] 4.48 94 [113,] 4.52 131 [114,] 4.56 82 [115,] 4.60 92 [116,] 4.64 109 [117,] 4.68 133 [118,] 4.72 134 [119,] 4.76 128 [120,] 4.80 113 [121,] 4.84 128 [122,] 4.88 96 [123,] 4.92 117 [124,] 4.96 141 [125,] 5.00 128 [126,] 5.04 115 [127,] 5.08 117 [128,] 5.12 138 [129,] 5.16 116 [130,] 5.20 121 [131,] 5.24 104 [132,] 5.28 120 [133,] 5.32 98 [134,] 5.36 102 [135,] 5.40 127 [136,] 5.44 108 [137,] 5.48 125 [138,] 5.52 92 [139,] 5.56 106 [140,] 5.60 119 [141,] 5.64 100 [142,] 5.68 124 [143,] 5.72 112 [144,] 5.76 80 [145,] 5.80 114 [146,] 5.84 78 [147,] 5.88 123 [148,] 5.92 105 [149,] 5.96 88 [150,] 6.00 94 [151,] 6.04 120 [152,] 6.08 84 [153,] 6.12 96 [154,] 6.16 85 [155,] 6.20 95 [156,] 6.24 102 [157,] 6.28 109 [158,] 6.32 102 [159,] 6.36 101 [160,] 6.40 114 [161,] 6.44 130 [162,] 6.48 99 [163,] 6.52 105 [164,] 6.56 86 [165,] 6.60 105 [166,] 6.64 97 [167,] 6.68 95 [168,] 6.72 109 [169,] 6.76 99 [170,] 6.80 132 [171,] 6.84 106 [172,] 6.88 132 [173,] 6.92 97 [174,] 6.96 96 [175,] 7.00 89 [176,] 7.04 83 [177,] 7.08 132 [178,] 7.12 113 [179,] 7.16 119 [180,] 7.20 78 [181,] 7.24 112 [182,] 7.28 92 [183,] 7.32 98 [184,] 7.36 89 [185,] 7.40 97 [186,] 7.44 116 [187,] 7.48 81 [188,] 7.52 86 [189,] 7.56 99 [190,] 7.60 88 [191,] 7.64 94 [192,] 7.68 104 [193,] 7.72 105 [194,] 7.76 90 [195,] 7.80 102 [196,] 7.84 97 [197,] 7.88 102 [198,] 7.92 88 [199,] 7.96 94 [200,] 8.00 127 [201,] 8.04 107 [202,] 8.08 79 [203,] 8.12 80 [204,] 8.16 136 [205,] 8.20 90 [206,] 8.24 83 [207,] 8.28 97 [208,] 8.32 113 [209,] 8.36 84 [210,] 8.40 106 [211,] 8.44 101 [212,] 8.48 110 [213,] 8.52 96 [214,] 8.56 83 [215,] 8.60 101 [216,] 8.64 91 [217,] 8.68 108 [218,] 8.72 89 [219,] 8.76 125 [220,] 8.80 85 [221,] 8.84 102 [222,] 8.88 88 [223,] 8.92 108 [224,] 8.96 100 [225,] 9.00 98 [226,] 9.04 99 [227,] 9.08 104 [228,] 9.12 96 [229,] 9.16 99 [230,] 9.20 63 [231,] 9.24 96 [232,] 9.28 102 [233,] 9.32 92 [234,] 9.36 82 [235,] 9.40 114 [236,] 9.44 100 [237,] 9.48 108 [238,] 9.52 91 [239,] 9.56 88 [240,] 9.60 85 [241,] 9.64 67 [242,] 9.68 92 [243,] 9.72 81 [244,] 9.76 88 [245,] 9.80 88 [246,] 9.84 124 [247,] 9.88 81 [248,] 9.92 90 [249,] 9.96 101 [250,] 10.00 81 [251,] 10.04 88 [252,] 10.08 76 [253,] 10.12 93 [254,] 10.16 100 [255,] 10.20 67 [256,] 10.24 117 [257,] 10.28 93 [258,] 10.32 78 [259,] 10.36 81 [260,] 10.40 96 [261,] 10.44 85 [262,] 10.48 120 [263,] 10.52 117 [264,] 10.56 89 [265,] 10.60 111 [266,] 10.64 91 [267,] 10.68 95 [268,] 10.72 108 [269,] 10.76 103 [270,] 10.80 122 [271,] 10.84 81 [272,] 10.88 94 [273,] 10.92 73 [274,] 10.96 92 [275,] 11.00 90 [276,] 11.04 98 [277,] 11.08 89 [278,] 11.12 105 [279,] 11.16 104 [280,] 11.20 105 [281,] 11.24 84 [282,] 11.28 100 [283,] 11.32 64 [284,] 11.36 97 [285,] 11.40 95 [286,] 11.44 85 [287,] 11.48 79 [288,] 11.52 98 [289,] 11.56 83 [290,] 11.60 104 [291,] 11.64 80 [292,] 11.68 92 [293,] 11.72 93 [294,] 11.76 91 [295,] 11.80 76 [296,] 11.84 80 [297,] 11.88 82 [298,] 11.92 87 [299,] 11.96 94 [300,] 12.00 92 [301,] 12.04 88 [302,] 12.08 87 [303,] 12.12 84 [304,] 12.16 88 [305,] 12.20 88 [306,] 12.24 98 [307,] 12.28 82 [308,] 12.32 107 [309,] 12.36 91 [310,] 12.40 84 [311,] 12.44 69 [312,] 12.48 79 [313,] 12.52 80 [314,] 12.56 103 [315,] 12.60 81 [316,] 12.64 94 [317,] 12.68 91 [318,] 12.72 97 [319,] 12.76 91 [320,] 12.80 108 [321,] 12.84 97 [322,] 12.88 85 [323,] 12.92 78 [324,] 12.96 75 [325,] 13.00 64 [326,] 13.04 106 [327,] 13.08 84 [328,] 13.12 88 [329,] 13.16 75 [330,] 13.20 83 [331,] 13.24 88 [332,] 13.28 83 [333,] 13.32 105 [334,] 13.36 83 [335,] 13.40 84 [336,] 13.44 84 [337,] 13.48 82 [338,] 13.52 82 [339,] 13.56 99 [340,] 13.60 91 [341,] 13.64 85 [342,] 13.68 106 [343,] 13.72 89 [344,] 13.76 91 [345,] 13.80 79 [346,] 13.84 86 [347,] 13.88 79 [348,] 13.92 81 [349,] 13.96 90 [350,] 14.00 109 [351,] 14.04 87 [352,] 14.08 92 [353,] 14.12 87 [354,] 14.16 94 [355,] 14.20 77 [356,] 14.24 83 [357,] 14.28 98 [358,] 14.32 91 [359,] 14.36 79 [360,] 14.40 82 [361,] 14.44 72 [362,] 14.48 86 [363,] 14.52 88 [364,] 14.56 75 [365,] 14.60 72 [366,] 14.64 97 [367,] 14.68 105 [368,] 14.72 96 [369,] 14.76 91 [370,] 14.80 101 [371,] 14.84 75 [372,] 14.88 86 [373,] 14.92 88 [374,] 14.96 81 [375,] 15.00 92 [376,] 15.04 92 [377,] 15.08 68 [378,] 15.12 79 [379,] 15.16 92 [380,] 15.20 85 [381,] 15.24 76 [382,] 15.28 93 [383,] 15.32 79 [384,] 15.36 65 [385,] 15.40 84 [386,] 15.44 86 [387,] 15.48 91 [388,] 15.52 76 [389,] 15.56 98 [390,] 15.60 84 [391,] 15.64 90 [392,] 15.68 112 [393,] 15.72 89 [394,] 15.76 95 [395,] 15.80 96 [396,] 15.84 64 [397,] 15.88 80 [398,] 15.92 66 [399,] 15.96 80 [400,] 16.00 88 [401,] 16.04 95 [402,] 16.08 90 [403,] 16.12 69 [404,] 16.16 82 [405,] 16.20 89 [406,] 16.24 102 [407,] 16.28 83 [408,] 16.32 82 [409,] 16.36 82 [410,] 16.40 82 [411,] 16.44 88 [412,] 16.48 71 [413,] 16.52 109 [414,] 16.56 76 [415,] 16.60 69 [416,] 16.64 93 [417,] 16.68 85 [418,] 16.72 89 [419,] 16.76 67 [420,] 16.80 72 [421,] 16.84 75 [422,] 16.88 66 [423,] 16.92 73 [424,] 16.96 85 [425,] 17.00 86 [426,] 17.04 64 [427,] 17.08 82 [428,] 17.12 85 [429,] 17.16 101 [430,] 17.20 82 [431,] 17.24 69 [432,] 17.28 88 [433,] 17.32 90 [434,] 17.36 86 [435,] 17.40 78 [436,] 17.44 80 [437,] 17.48 85 [438,] 17.52 87 [439,] 17.56 98 [440,] 17.60 93 [441,] 17.64 73 [442,] 17.68 113 [443,] 17.72 83 [444,] 17.76 94 [445,] 17.80 80 [446,] 17.84 76 [447,] 17.88 82 [448,] 17.92 100 [449,] 17.96 71 [450,] 18.00 89 [451,] 18.04 82 [452,] 18.08 88 [453,] 18.12 69 [454,] 18.16 95 [455,] 18.20 79 [456,] 18.24 90 [457,] 18.28 92 [458,] 18.32 79 [459,] 18.36 77 [460,] 18.40 87 [461,] 18.44 75 [462,] 18.48 97 [463,] 18.52 71 [464,] 18.56 92 [465,] 18.60 92 [466,] 18.64 68 [467,] 18.68 71 [468,] 18.72 92 [469,] 18.76 96 [470,] 18.80 71 [471,] 18.84 78 [472,] 18.88 79 [473,] 18.92 72 [474,] 18.96 76 [475,] 19.00 93 [476,] 19.04 65 [477,] 19.08 63 [478,] 19.12 79 [479,] 19.16 97 [480,] 19.20 73 [481,] 19.24 77 [482,] 19.28 83 [483,] 19.32 72 [484,] 19.36 76 [485,] 19.40 81 [486,] 19.44 111 [487,] 19.48 85 [488,] 19.52 71 [489,] 19.56 80 [490,] 19.60 85 [491,] 19.64 89 [492,] 19.68 93 [493,] 19.72 98 [494,] 19.76 90 [495,] 19.80 109 [496,] 19.84 66 [497,] 19.88 76 [498,] 19.92 72 [499,] 19.96 77 [500,] 20.00 83 [501,] 20.04 73 [502,] 20.08 95 [503,] 20.12 74 [504,] 20.16 80 [505,] 20.20 94 [506,] 20.24 80 [507,] 20.28 86 [508,] 20.32 79 [509,] 20.36 93 [510,] 20.40 75 [511,] 20.44 78 [512,] 20.48 66 [513,] 20.52 73 [514,] 20.56 83 [515,] 20.60 88 [516,] 20.64 70 [517,] 20.68 73 [518,] 20.72 107 [519,] 20.76 85 [520,] 20.80 71 [521,] 20.84 81 [522,] 20.88 86 [523,] 20.92 95 [524,] 20.96 87 [525,] 21.00 88 [526,] 21.04 79 [527,] 21.08 76 [528,] 21.12 69 [529,] 21.16 82 [530,] 21.20 86 [531,] 21.24 68 [532,] 21.28 81 [533,] 21.32 83 [534,] 21.36 79 [535,] 21.40 89 [536,] 21.44 89 [537,] 21.48 93 [538,] 21.52 73 [539,] 21.56 77 [540,] 21.60 83 [541,] 21.64 78 [542,] 21.68 78 [543,] 21.72 81 [544,] 21.76 62 [545,] 21.80 82 [546,] 21.84 80 [547,] 21.88 75 [548,] 21.92 84 [549,] 21.96 75 [550,] 22.00 74 [551,] 22.04 91 [552,] 22.08 80 [553,] 22.12 82 [554,] 22.16 88 [555,] 22.20 79 [556,] 22.24 104 [557,] 22.28 96 [558,] 22.32 57 [559,] 22.36 76 [560,] 22.40 83 [561,] 22.44 73 [562,] 22.48 82 [563,] 22.52 87 [564,] 22.56 87 [565,] 22.60 74 [566,] 22.64 73 [567,] 22.68 69 [568,] 22.72 108 [569,] 22.76 88 [570,] 22.80 103 [571,] 22.84 90 [572,] 22.88 85 [573,] 22.92 83 [574,] 22.96 91 [575,] 23.00 85 [576,] 23.04 75 [577,] 23.08 83 [578,] 23.12 76 [579,] 23.16 86 [580,] 23.20 71 [581,] 23.24 70 [582,] 23.28 72 [583,] 23.32 54 [584,] 23.36 68 [585,] 23.40 77 [586,] 23.44 70 [587,] 23.48 69 [588,] 23.52 68 [589,] 23.56 73 [590,] 23.60 100 [591,] 23.64 89 [592,] 23.68 84 [593,] 23.72 85 [594,] 23.76 69 [595,] 23.80 93 [596,] 23.84 70 [597,] 23.88 94 [598,] 23.92 67 [599,] 23.96 93 [600,] 24.00 79 [601,] 24.04 81 [602,] 24.08 64 [603,] 24.12 81 [604,] 24.16 72 [605,] 24.20 69 [606,] 24.24 73 [607,] 24.28 80 [608,] 24.32 75 [609,] 24.36 63 [610,] 24.40 74 [611,] 24.44 58 [612,] 24.48 97 [613,] 24.52 69 [614,] 24.56 72 [615,] 24.60 95 [616,] 24.64 68 [617,] 24.68 75 [618,] 24.72 80 [619,] 24.76 69 [620,] 24.80 98 [621,] 24.84 64 [622,] 24.88 77 [623,] 24.92 74 [624,] 24.96 80 [625,] 25.00 53 [626,] 25.04 73 [627,] 25.08 82 [628,] 25.12 78 [629,] 25.16 80 [630,] 25.20 96 [631,] 25.24 67 [632,] 25.28 73 [633,] 25.32 89 [634,] 25.36 79 [635,] 25.40 92 [636,] 25.44 69 [637,] 25.48 69 [638,] 25.52 66 [639,] 25.56 69 [640,] 25.60 83 [641,] 25.64 92 [642,] 25.68 94 [643,] 25.72 84 [644,] 25.76 78 [645,] 25.80 90 [646,] 25.84 84 [647,] 25.88 74 [648,] 25.92 84 [649,] 25.96 74 [650,] 26.00 81 [651,] 26.04 63 [652,] 26.08 66 [653,] 26.12 69 [654,] 26.16 81 [655,] 26.20 91 [656,] 26.24 59 [657,] 26.28 88 [658,] 26.32 83 [659,] 26.36 67 [660,] 26.40 66 [661,] 26.44 68 [662,] 26.48 74 [663,] 26.52 72 [664,] 26.56 54 [665,] 26.60 80 [666,] 26.64 64 [667,] 26.68 77 [668,] 26.72 81 [669,] 26.76 94 [670,] 26.80 94 [671,] 26.84 57 [672,] 26.88 61 [673,] 26.92 88 [674,] 26.96 75 [675,] 27.00 80 [676,] 27.04 86 [677,] 27.08 62 [678,] 27.12 74 [679,] 27.16 74 [680,] 27.20 80 [681,] 27.24 57 [682,] 27.28 62 [683,] 27.32 75 [684,] 27.36 79 [685,] 27.40 90 [686,] 27.44 98 [687,] 27.48 75 [688,] 27.52 74 [689,] 27.56 90 [690,] 27.60 70 [691,] 27.64 92 [692,] 27.68 80 [693,] 27.72 64 [694,] 27.76 46 [695,] 27.80 84 [696,] 27.84 83 [697,] 27.88 59 [698,] 27.92 82 [699,] 27.96 85 [700,] 28.00 97 [701,] 28.04 83 [702,] 28.08 80 [703,] 28.12 54 [704,] 28.16 85 [705,] 28.20 92 [706,] 28.24 82 [707,] 28.28 71 [708,] 28.32 72 [709,] 28.36 85 [710,] 28.40 74 [711,] 28.44 85 [712,] 28.48 82 [713,] 28.52 65 [714,] 28.56 69 [715,] 28.60 80 [716,] 28.64 65 [717,] 28.68 45 [718,] 28.72 80 [719,] 28.76 86 [720,] 28.80 57 [721,] 28.84 60 [722,] 28.88 73 [723,] 28.92 71 [724,] 28.96 87 [725,] 29.00 95 [726,] 29.04 88 [727,] 29.08 92 [728,] 29.12 72 [729,] 29.16 66 [730,] 29.20 98 [731,] 29.24 91 [732,] 29.28 61 [733,] 29.32 72 [734,] 29.36 95 [735,] 29.40 87 [736,] 29.44 77 [737,] 29.48 86 [738,] 29.52 91 [739,] 29.56 65 [740,] 29.60 77 [741,] 29.64 77 [742,] 29.68 82 [743,] 29.72 69 [744,] 29.76 77 [745,] 29.80 62 [746,] 29.84 68 [747,] 29.88 74 [748,] 29.92 93 [749,] 29.96 75 [750,] 30.00 81 [751,] 30.04 58 [752,] 30.08 80 [753,] 30.12 96 [754,] 30.16 74 [755,] 30.20 57 [756,] 30.24 67 [757,] 30.28 78 [758,] 30.32 65 [759,] 30.36 64 [760,] 30.40 57 [761,] 30.44 73 [762,] 30.48 90 [763,] 30.52 85 [764,] 30.56 61 [765,] 30.60 82 [766,] 30.64 82 [767,] 30.68 77 [768,] 30.72 68 [769,] 30.76 69 [770,] 30.80 74 [771,] 30.84 58 [772,] 30.88 65 [773,] 30.92 93 [774,] 30.96 87 [775,] 31.00 79 [776,] 31.04 81 [777,] 31.08 96 [778,] 31.12 73 [779,] 31.16 64 [780,] 31.20 74 [781,] 31.24 79 [782,] 31.28 66 [783,] 31.32 81 [784,] 31.36 85 [785,] 31.40 65 [786,] 31.44 66 [787,] 31.48 63 [788,] 31.52 97 [789,] 31.56 75 [790,] 31.60 70 [791,] 31.64 71 [792,] 31.68 91 [793,] 31.72 81 [794,] 31.76 70 [795,] 31.80 67 [796,] 31.84 88 [797,] 31.88 96 [798,] 31.92 92 [799,] 31.96 91 [800,] 32.00 81 [801,] 32.04 69 [802,] 32.08 72 [803,] 32.12 83 [804,] 32.16 91 [805,] 32.20 62 [806,] 32.24 77 [807,] 32.28 78 [808,] 32.32 65 [809,] 32.36 81 [810,] 32.40 65 [811,] 32.44 85 [812,] 32.48 79 [813,] 32.52 61 [814,] 32.56 55 [815,] 32.60 75 [816,] 32.64 63 [817,] 32.68 79 [818,] 32.72 83 [819,] 32.76 86 [820,] 32.80 66 [821,] 32.84 78 [822,] 32.88 62 [823,] 32.92 64 [824,] 32.96 78 [825,] 33.00 68 [826,] 33.04 91 [827,] 33.08 83 [828,] 33.12 89 [829,] 33.16 82 [830,] 33.20 61 [831,] 33.24 64 [832,] 33.28 68 [833,] 33.32 60 [834,] 33.36 94 [835,] 33.40 76 [836,] 33.44 74 [837,] 33.48 75 [838,] 33.52 69 [839,] 33.56 70 [840,] 33.60 63 [841,] 33.64 61 [842,] 33.68 72 [843,] 33.72 68 [844,] 33.76 78 [845,] 33.80 72 [846,] 33.84 76 [847,] 33.88 77 [848,] 33.92 81 [849,] 33.96 79 [850,] 34.00 77 [851,] 34.04 72 [852,] 34.08 59 [853,] 34.12 75 [854,] 34.16 80 [855,] 34.20 59 [856,] 34.24 71 [857,] 34.28 71 [858,] 34.32 78 [859,] 34.36 82 [860,] 34.40 73 [861,] 34.44 69 [862,] 34.48 73 [863,] 34.52 59 [864,] 34.56 82 [865,] 34.60 79 [866,] 34.64 79 [867,] 34.68 70 [868,] 34.72 80 [869,] 34.76 73 [870,] 34.80 64 [871,] 34.84 70 [872,] 34.88 84 [873,] 34.92 85 [874,] 34.96 55 [875,] 35.00 73 [876,] 35.04 71 [877,] 35.08 67 [878,] 35.12 81 [879,] 35.16 67 [880,] 35.20 66 [881,] 35.24 75 [882,] 35.28 72 [883,] 35.32 56 [884,] 35.36 68 [885,] 35.40 101 [886,] 35.44 80 [887,] 35.48 77 [888,] 35.52 62 [889,] 35.56 71 [890,] 35.60 76 [891,] 35.64 65 [892,] 35.68 71 [893,] 35.72 75 [894,] 35.76 64 [895,] 35.80 72 [896,] 35.84 59 [897,] 35.88 64 [898,] 35.92 64 [899,] 35.96 78 [900,] 36.00 75 [901,] 36.04 65 [902,] 36.08 74 [903,] 36.12 62 [904,] 36.16 54 [905,] 36.20 71 [906,] 36.24 72 [907,] 36.28 83 [908,] 36.32 85 [909,] 36.36 72 [910,] 36.40 82 [911,] 36.44 78 [912,] 36.48 79 [913,] 36.52 77 [914,] 36.56 56 [915,] 36.60 76 [916,] 36.64 74 [917,] 36.68 57 [918,] 36.72 84 [919,] 36.76 66 [920,] 36.80 80 [921,] 36.84 61 [922,] 36.88 60 [923,] 36.92 63 [924,] 36.96 84 [925,] 37.00 62 [926,] 37.04 89 [927,] 37.08 69 [928,] 37.12 70 [929,] 37.16 59 [930,] 37.20 76 [931,] 37.24 79 [932,] 37.28 59 [933,] 37.32 91 [934,] 37.36 81 [935,] 37.40 77 [936,] 37.44 69 [937,] 37.48 73 [938,] 37.52 59 [939,] 37.56 89 [940,] 37.60 82 [941,] 37.64 86 [942,] 37.68 85 [943,] 37.72 80 [944,] 37.76 63 [945,] 37.80 89 [946,] 37.84 58 [947,] 37.88 69 [948,] 37.92 67 [949,] 37.96 77 [950,] 38.00 65 [951,] 38.04 73 [952,] 38.08 67 [953,] 38.12 50 [954,] 38.16 88 [955,] 38.20 84 [956,] 38.24 72 [957,] 38.28 67 [958,] 38.32 59 [959,] 38.36 90 [960,] 38.40 83 [961,] 38.44 58 [962,] 38.48 58 [963,] 38.52 85 [964,] 38.56 60 [965,] 38.60 72 [966,] 38.64 69 [967,] 38.68 90 [968,] 38.72 72 [969,] 38.76 76 [970,] 38.80 75 [971,] 38.84 77 [972,] 38.88 72 [973,] 38.92 77 [974,] 38.96 81 [975,] 39.00 81 [976,] 39.04 67 [977,] 39.08 71 [978,] 39.12 62 [979,] 39.16 83 [980,] 39.20 71 [981,] 39.24 61 [982,] 39.28 70 [983,] 39.32 74 [984,] 39.36 75 [985,] 39.40 63 [986,] 39.44 60 [987,] 39.48 73 [988,] 39.52 77 [989,] 39.56 78 [990,] 39.60 69 [991,] 39.64 73 [992,] 39.68 78 [993,] 39.72 86 [994,] 39.76 88 [995,] 39.80 68 [996,] 39.84 63 [997,] 39.88 68 [998,] 39.92 69 [999,] 39.96 67 [1000,] 40.00 102 $`21_TL (PMT)` [,1] [,2] [1,] 0.884 7 [2,] 1.768 4 [3,] 2.652 1 [4,] 3.536 5 [5,] 4.420 2 [6,] 5.304 9 [7,] 6.188 2 [8,] 7.072 7 [9,] 7.956 4 [10,] 8.840 5 [11,] 9.724 5 [12,] 10.608 4 [13,] 11.492 1 [14,] 12.376 0 [15,] 13.260 4 [16,] 14.144 9 [17,] 15.028 8 [18,] 15.912 3 [19,] 16.796 2 [20,] 17.680 1 [21,] 18.564 2 [22,] 19.448 4 [23,] 20.332 5 [24,] 21.216 7 [25,] 22.100 3 [26,] 22.984 2 [27,] 23.868 13 [28,] 24.752 9 [29,] 25.636 6 [30,] 26.520 8 [31,] 27.404 3 [32,] 28.288 2 [33,] 29.172 6 [34,] 30.056 2 [35,] 30.940 7 [36,] 31.824 2 [37,] 32.708 4 [38,] 33.592 6 [39,] 34.476 3 [40,] 35.360 5 [41,] 36.244 4 [42,] 37.128 10 [43,] 38.012 2 [44,] 38.896 9 [45,] 39.780 19 [46,] 40.664 9 [47,] 41.548 10 [48,] 42.432 6 [49,] 43.316 2 [50,] 44.200 1 [51,] 45.084 5 [52,] 45.968 7 [53,] 46.852 7 [54,] 47.736 7 [55,] 48.620 10 [56,] 49.504 9 [57,] 50.388 5 [58,] 51.272 22 [59,] 52.156 7 [60,] 53.040 7 [61,] 53.924 8 [62,] 54.808 11 [63,] 55.692 10 [64,] 56.576 12 [65,] 57.460 13 [66,] 58.344 15 [67,] 59.228 19 [68,] 60.112 12 [69,] 60.996 19 [70,] 61.880 12 [71,] 62.764 15 [72,] 63.648 14 [73,] 64.532 11 [74,] 65.416 17 [75,] 66.300 14 [76,] 67.184 12 [77,] 68.068 20 [78,] 68.952 21 [79,] 69.836 30 [80,] 70.720 27 [81,] 71.604 36 [82,] 72.488 21 [83,] 73.372 23 [84,] 74.256 38 [85,] 75.140 41 [86,] 76.024 45 [87,] 76.908 37 [88,] 77.792 41 [89,] 78.676 65 [90,] 79.560 49 [91,] 80.444 46 [92,] 81.328 58 [93,] 82.212 55 [94,] 83.096 72 [95,] 83.980 65 [96,] 84.864 88 [97,] 85.748 78 [98,] 86.632 102 [99,] 87.516 82 [100,] 88.400 114 [101,] 89.284 102 [102,] 90.168 122 [103,] 91.052 124 [104,] 91.936 133 [105,] 92.820 161 [106,] 93.704 147 [107,] 94.588 175 [108,] 95.472 183 [109,] 96.356 181 [110,] 97.240 164 [111,] 98.124 145 [112,] 99.008 220 [113,] 99.892 220 [114,] 100.776 194 [115,] 101.660 215 [116,] 102.544 232 [117,] 103.428 228 [118,] 104.312 248 [119,] 105.196 266 [120,] 106.080 238 [121,] 106.964 245 [122,] 107.848 236 [123,] 108.732 241 [124,] 109.616 241 [125,] 110.500 231 [126,] 111.384 217 [127,] 112.268 245 [128,] 113.152 247 [129,] 114.036 238 [130,] 114.920 210 [131,] 115.804 226 [132,] 116.688 210 [133,] 117.572 169 [134,] 118.456 207 [135,] 119.340 186 [136,] 120.224 193 [137,] 121.108 224 [138,] 121.992 154 [139,] 122.876 174 [140,] 123.760 188 [141,] 124.644 174 [142,] 125.528 177 [143,] 126.412 134 [144,] 127.296 176 [145,] 128.180 149 [146,] 129.064 156 [147,] 129.948 171 [148,] 130.832 187 [149,] 131.716 144 [150,] 132.600 177 [151,] 133.484 183 [152,] 134.368 167 [153,] 135.252 175 [154,] 136.136 167 [155,] 137.020 198 [156,] 137.904 193 [157,] 138.788 198 [158,] 139.672 186 [159,] 140.556 191 [160,] 141.440 181 [161,] 142.324 195 [162,] 143.208 162 [163,] 144.092 192 [164,] 144.976 187 [165,] 145.860 176 [166,] 146.744 184 [167,] 147.628 202 [168,] 148.512 167 [169,] 149.396 153 [170,] 150.280 189 [171,] 151.164 189 [172,] 152.048 196 [173,] 152.932 192 [174,] 153.816 171 [175,] 154.700 184 [176,] 155.584 187 [177,] 156.468 176 [178,] 157.352 179 [179,] 158.236 201 [180,] 159.120 186 [181,] 160.004 230 [182,] 160.888 191 [183,] 161.772 162 [184,] 162.656 180 [185,] 163.540 160 [186,] 164.424 170 [187,] 165.308 140 [188,] 166.192 172 [189,] 167.076 182 [190,] 167.960 192 [191,] 168.844 183 [192,] 169.728 143 [193,] 170.612 155 [194,] 171.496 170 [195,] 172.380 190 [196,] 173.264 160 [197,] 174.148 175 [198,] 175.032 166 [199,] 175.916 175 [200,] 176.800 159 [201,] 177.684 184 [202,] 178.568 163 [203,] 179.452 174 [204,] 180.336 166 [205,] 181.220 181 [206,] 182.104 165 [207,] 182.988 170 [208,] 183.872 170 [209,] 184.756 164 [210,] 185.640 192 [211,] 186.524 170 [212,] 187.408 204 [213,] 188.292 181 [214,] 189.176 158 [215,] 190.060 180 [216,] 190.944 191 [217,] 191.828 198 [218,] 192.712 178 [219,] 193.596 196 [220,] 194.480 189 [221,] 195.364 198 [222,] 196.248 228 [223,] 197.132 236 [224,] 198.016 219 [225,] 198.900 228 [226,] 199.784 196 [227,] 200.668 206 [228,] 201.552 208 [229,] 202.436 255 [230,] 203.320 257 [231,] 204.204 249 [232,] 205.088 243 [233,] 205.972 225 [234,] 206.856 242 [235,] 207.740 228 [236,] 208.624 260 [237,] 209.508 256 [238,] 210.392 261 [239,] 211.276 269 [240,] 212.160 243 [241,] 213.044 304 [242,] 213.928 241 [243,] 214.812 279 [244,] 215.696 285 [245,] 216.580 263 [246,] 217.464 305 [247,] 218.348 316 [248,] 219.232 244 [249,] 220.116 310 [250,] 221.000 148 $`22_OSL (PMT)` [,1] [,2] [1,] 0.04 4993 [2,] 0.08 4383 [3,] 0.12 3681 [4,] 0.16 3106 [5,] 0.20 2877 [6,] 0.24 2452 [7,] 0.28 2173 [8,] 0.32 1856 [9,] 0.36 1620 [10,] 0.40 1479 [11,] 0.44 1351 [12,] 0.48 1123 [13,] 0.52 1021 [14,] 0.56 838 [15,] 0.60 776 [16,] 0.64 726 [17,] 0.68 663 [18,] 0.72 590 [19,] 0.76 526 [20,] 0.80 499 [21,] 0.84 468 [22,] 0.88 402 [23,] 0.92 448 [24,] 0.96 340 [25,] 1.00 325 [26,] 1.04 269 [27,] 1.08 288 [28,] 1.12 273 [29,] 1.16 265 [30,] 1.20 245 [31,] 1.24 250 [32,] 1.28 210 [33,] 1.32 199 [34,] 1.36 206 [35,] 1.40 183 [36,] 1.44 163 [37,] 1.48 215 [38,] 1.52 178 [39,] 1.56 159 [40,] 1.60 164 [41,] 1.64 128 [42,] 1.68 165 [43,] 1.72 146 [44,] 1.76 169 [45,] 1.80 155 [46,] 1.84 118 [47,] 1.88 143 [48,] 1.92 164 [49,] 1.96 115 [50,] 2.00 120 [51,] 2.04 161 [52,] 2.08 122 [53,] 2.12 137 [54,] 2.16 119 [55,] 2.20 119 [56,] 2.24 133 [57,] 2.28 130 [58,] 2.32 137 [59,] 2.36 113 [60,] 2.40 125 [61,] 2.44 134 [62,] 2.48 95 [63,] 2.52 124 [64,] 2.56 117 [65,] 2.60 136 [66,] 2.64 111 [67,] 2.68 104 [68,] 2.72 121 [69,] 2.76 132 [70,] 2.80 112 [71,] 2.84 117 [72,] 2.88 91 [73,] 2.92 113 [74,] 2.96 109 [75,] 3.00 86 [76,] 3.04 98 [77,] 3.08 99 [78,] 3.12 111 [79,] 3.16 90 [80,] 3.20 84 [81,] 3.24 107 [82,] 3.28 112 [83,] 3.32 110 [84,] 3.36 96 [85,] 3.40 83 [86,] 3.44 92 [87,] 3.48 79 [88,] 3.52 98 [89,] 3.56 97 [90,] 3.60 105 [91,] 3.64 108 [92,] 3.68 104 [93,] 3.72 108 [94,] 3.76 69 [95,] 3.80 99 [96,] 3.84 105 [97,] 3.88 98 [98,] 3.92 98 [99,] 3.96 84 [100,] 4.00 130 [101,] 4.04 88 [102,] 4.08 110 [103,] 4.12 82 [104,] 4.16 91 [105,] 4.20 97 [106,] 4.24 99 [107,] 4.28 80 [108,] 4.32 90 [109,] 4.36 93 [110,] 4.40 80 [111,] 4.44 83 [112,] 4.48 83 [113,] 4.52 96 [114,] 4.56 96 [115,] 4.60 100 [116,] 4.64 86 [117,] 4.68 82 [118,] 4.72 86 [119,] 4.76 86 [120,] 4.80 109 [121,] 4.84 77 [122,] 4.88 114 [123,] 4.92 97 [124,] 4.96 92 [125,] 5.00 62 [126,] 5.04 83 [127,] 5.08 93 [128,] 5.12 116 [129,] 5.16 91 [130,] 5.20 91 [131,] 5.24 83 [132,] 5.28 85 [133,] 5.32 85 [134,] 5.36 97 [135,] 5.40 89 [136,] 5.44 81 [137,] 5.48 78 [138,] 5.52 69 [139,] 5.56 84 [140,] 5.60 86 [141,] 5.64 69 [142,] 5.68 95 [143,] 5.72 89 [144,] 5.76 87 [145,] 5.80 71 [146,] 5.84 64 [147,] 5.88 78 [148,] 5.92 94 [149,] 5.96 63 [150,] 6.00 79 [151,] 6.04 74 [152,] 6.08 82 [153,] 6.12 82 [154,] 6.16 71 [155,] 6.20 72 [156,] 6.24 97 [157,] 6.28 91 [158,] 6.32 76 [159,] 6.36 85 [160,] 6.40 81 [161,] 6.44 88 [162,] 6.48 86 [163,] 6.52 67 [164,] 6.56 94 [165,] 6.60 95 [166,] 6.64 81 [167,] 6.68 76 [168,] 6.72 70 [169,] 6.76 81 [170,] 6.80 76 [171,] 6.84 76 [172,] 6.88 77 [173,] 6.92 69 [174,] 6.96 85 [175,] 7.00 98 [176,] 7.04 73 [177,] 7.08 93 [178,] 7.12 78 [179,] 7.16 95 [180,] 7.20 62 [181,] 7.24 81 [182,] 7.28 78 [183,] 7.32 84 [184,] 7.36 73 [185,] 7.40 84 [186,] 7.44 84 [187,] 7.48 66 [188,] 7.52 77 [189,] 7.56 76 [190,] 7.60 75 [191,] 7.64 88 [192,] 7.68 76 [193,] 7.72 95 [194,] 7.76 74 [195,] 7.80 85 [196,] 7.84 67 [197,] 7.88 78 [198,] 7.92 82 [199,] 7.96 108 [200,] 8.00 78 [201,] 8.04 56 [202,] 8.08 97 [203,] 8.12 93 [204,] 8.16 79 [205,] 8.20 88 [206,] 8.24 92 [207,] 8.28 60 [208,] 8.32 79 [209,] 8.36 76 [210,] 8.40 70 [211,] 8.44 73 [212,] 8.48 56 [213,] 8.52 65 [214,] 8.56 76 [215,] 8.60 86 [216,] 8.64 82 [217,] 8.68 75 [218,] 8.72 73 [219,] 8.76 79 [220,] 8.80 63 [221,] 8.84 86 [222,] 8.88 79 [223,] 8.92 89 [224,] 8.96 69 [225,] 9.00 74 [226,] 9.04 71 [227,] 9.08 56 [228,] 9.12 83 [229,] 9.16 83 [230,] 9.20 64 [231,] 9.24 83 [232,] 9.28 91 [233,] 9.32 97 [234,] 9.36 73 [235,] 9.40 87 [236,] 9.44 63 [237,] 9.48 56 [238,] 9.52 68 [239,] 9.56 69 [240,] 9.60 70 [241,] 9.64 66 [242,] 9.68 84 [243,] 9.72 98 [244,] 9.76 73 [245,] 9.80 68 [246,] 9.84 107 [247,] 9.88 68 [248,] 9.92 70 [249,] 9.96 78 [250,] 10.00 60 [251,] 10.04 92 [252,] 10.08 59 [253,] 10.12 77 [254,] 10.16 66 [255,] 10.20 61 [256,] 10.24 56 [257,] 10.28 89 [258,] 10.32 87 [259,] 10.36 90 [260,] 10.40 83 [261,] 10.44 97 [262,] 10.48 71 [263,] 10.52 49 [264,] 10.56 88 [265,] 10.60 92 [266,] 10.64 76 [267,] 10.68 97 [268,] 10.72 81 [269,] 10.76 78 [270,] 10.80 76 [271,] 10.84 73 [272,] 10.88 67 [273,] 10.92 90 [274,] 10.96 83 [275,] 11.00 68 [276,] 11.04 70 [277,] 11.08 69 [278,] 11.12 78 [279,] 11.16 83 [280,] 11.20 65 [281,] 11.24 96 [282,] 11.28 100 [283,] 11.32 74 [284,] 11.36 68 [285,] 11.40 86 [286,] 11.44 70 [287,] 11.48 66 [288,] 11.52 77 [289,] 11.56 63 [290,] 11.60 84 [291,] 11.64 72 [292,] 11.68 96 [293,] 11.72 58 [294,] 11.76 66 [295,] 11.80 69 [296,] 11.84 72 [297,] 11.88 70 [298,] 11.92 69 [299,] 11.96 66 [300,] 12.00 74 [301,] 12.04 76 [302,] 12.08 55 [303,] 12.12 68 [304,] 12.16 73 [305,] 12.20 116 [306,] 12.24 65 [307,] 12.28 80 [308,] 12.32 76 [309,] 12.36 88 [310,] 12.40 75 [311,] 12.44 60 [312,] 12.48 95 [313,] 12.52 82 [314,] 12.56 71 [315,] 12.60 79 [316,] 12.64 73 [317,] 12.68 90 [318,] 12.72 62 [319,] 12.76 78 [320,] 12.80 72 [321,] 12.84 63 [322,] 12.88 74 [323,] 12.92 72 [324,] 12.96 89 [325,] 13.00 83 [326,] 13.04 73 [327,] 13.08 62 [328,] 13.12 72 [329,] 13.16 57 [330,] 13.20 59 [331,] 13.24 93 [332,] 13.28 77 [333,] 13.32 76 [334,] 13.36 70 [335,] 13.40 66 [336,] 13.44 80 [337,] 13.48 89 [338,] 13.52 64 [339,] 13.56 86 [340,] 13.60 63 [341,] 13.64 65 [342,] 13.68 78 [343,] 13.72 70 [344,] 13.76 65 [345,] 13.80 74 [346,] 13.84 72 [347,] 13.88 65 [348,] 13.92 83 [349,] 13.96 70 [350,] 14.00 83 [351,] 14.04 80 [352,] 14.08 93 [353,] 14.12 89 [354,] 14.16 76 [355,] 14.20 83 [356,] 14.24 93 [357,] 14.28 82 [358,] 14.32 74 [359,] 14.36 79 [360,] 14.40 64 [361,] 14.44 71 [362,] 14.48 105 [363,] 14.52 75 [364,] 14.56 79 [365,] 14.60 63 [366,] 14.64 72 [367,] 14.68 83 [368,] 14.72 61 [369,] 14.76 64 [370,] 14.80 74 [371,] 14.84 65 [372,] 14.88 73 [373,] 14.92 58 [374,] 14.96 89 [375,] 15.00 64 [376,] 15.04 74 [377,] 15.08 73 [378,] 15.12 86 [379,] 15.16 67 [380,] 15.20 74 [381,] 15.24 82 [382,] 15.28 67 [383,] 15.32 69 [384,] 15.36 91 [385,] 15.40 58 [386,] 15.44 68 [387,] 15.48 81 [388,] 15.52 86 [389,] 15.56 47 [390,] 15.60 70 [391,] 15.64 68 [392,] 15.68 75 [393,] 15.72 55 [394,] 15.76 65 [395,] 15.80 77 [396,] 15.84 78 [397,] 15.88 72 [398,] 15.92 59 [399,] 15.96 60 [400,] 16.00 64 [401,] 16.04 47 [402,] 16.08 60 [403,] 16.12 71 [404,] 16.16 67 [405,] 16.20 61 [406,] 16.24 69 [407,] 16.28 61 [408,] 16.32 65 [409,] 16.36 66 [410,] 16.40 80 [411,] 16.44 77 [412,] 16.48 66 [413,] 16.52 63 [414,] 16.56 76 [415,] 16.60 80 [416,] 16.64 90 [417,] 16.68 81 [418,] 16.72 66 [419,] 16.76 71 [420,] 16.80 75 [421,] 16.84 73 [422,] 16.88 75 [423,] 16.92 61 [424,] 16.96 68 [425,] 17.00 50 [426,] 17.04 62 [427,] 17.08 68 [428,] 17.12 89 [429,] 17.16 77 [430,] 17.20 72 [431,] 17.24 75 [432,] 17.28 58 [433,] 17.32 65 [434,] 17.36 69 [435,] 17.40 60 [436,] 17.44 72 [437,] 17.48 56 [438,] 17.52 63 [439,] 17.56 79 [440,] 17.60 66 [441,] 17.64 73 [442,] 17.68 90 [443,] 17.72 64 [444,] 17.76 73 [445,] 17.80 68 [446,] 17.84 71 [447,] 17.88 61 [448,] 17.92 50 [449,] 17.96 75 [450,] 18.00 76 [451,] 18.04 66 [452,] 18.08 73 [453,] 18.12 64 [454,] 18.16 52 [455,] 18.20 80 [456,] 18.24 65 [457,] 18.28 84 [458,] 18.32 90 [459,] 18.36 75 [460,] 18.40 77 [461,] 18.44 46 [462,] 18.48 77 [463,] 18.52 70 [464,] 18.56 78 [465,] 18.60 52 [466,] 18.64 56 [467,] 18.68 51 [468,] 18.72 72 [469,] 18.76 64 [470,] 18.80 65 [471,] 18.84 59 [472,] 18.88 73 [473,] 18.92 54 [474,] 18.96 70 [475,] 19.00 81 [476,] 19.04 61 [477,] 19.08 69 [478,] 19.12 75 [479,] 19.16 71 [480,] 19.20 68 [481,] 19.24 85 [482,] 19.28 71 [483,] 19.32 57 [484,] 19.36 74 [485,] 19.40 67 [486,] 19.44 76 [487,] 19.48 83 [488,] 19.52 76 [489,] 19.56 99 [490,] 19.60 80 [491,] 19.64 66 [492,] 19.68 54 [493,] 19.72 76 [494,] 19.76 75 [495,] 19.80 76 [496,] 19.84 81 [497,] 19.88 71 [498,] 19.92 53 [499,] 19.96 65 [500,] 20.00 60 [501,] 20.04 65 [502,] 20.08 68 [503,] 20.12 66 [504,] 20.16 65 [505,] 20.20 91 [506,] 20.24 65 [507,] 20.28 72 [508,] 20.32 73 [509,] 20.36 78 [510,] 20.40 70 [511,] 20.44 70 [512,] 20.48 71 [513,] 20.52 66 [514,] 20.56 52 [515,] 20.60 68 [516,] 20.64 58 [517,] 20.68 85 [518,] 20.72 56 [519,] 20.76 68 [520,] 20.80 71 [521,] 20.84 80 [522,] 20.88 59 [523,] 20.92 63 [524,] 20.96 59 [525,] 21.00 70 [526,] 21.04 60 [527,] 21.08 64 [528,] 21.12 64 [529,] 21.16 72 [530,] 21.20 83 [531,] 21.24 69 [532,] 21.28 66 [533,] 21.32 67 [534,] 21.36 75 [535,] 21.40 63 [536,] 21.44 79 [537,] 21.48 64 [538,] 21.52 73 [539,] 21.56 60 [540,] 21.60 65 [541,] 21.64 71 [542,] 21.68 57 [543,] 21.72 58 [544,] 21.76 70 [545,] 21.80 78 [546,] 21.84 70 [547,] 21.88 75 [548,] 21.92 62 [549,] 21.96 62 [550,] 22.00 68 [551,] 22.04 79 [552,] 22.08 51 [553,] 22.12 76 [554,] 22.16 71 [555,] 22.20 55 [556,] 22.24 73 [557,] 22.28 90 [558,] 22.32 92 [559,] 22.36 76 [560,] 22.40 54 [561,] 22.44 68 [562,] 22.48 64 [563,] 22.52 69 [564,] 22.56 41 [565,] 22.60 52 [566,] 22.64 70 [567,] 22.68 70 [568,] 22.72 75 [569,] 22.76 63 [570,] 22.80 74 [571,] 22.84 64 [572,] 22.88 74 [573,] 22.92 73 [574,] 22.96 69 [575,] 23.00 60 [576,] 23.04 73 [577,] 23.08 83 [578,] 23.12 59 [579,] 23.16 66 [580,] 23.20 63 [581,] 23.24 61 [582,] 23.28 68 [583,] 23.32 90 [584,] 23.36 64 [585,] 23.40 70 [586,] 23.44 55 [587,] 23.48 62 [588,] 23.52 67 [589,] 23.56 60 [590,] 23.60 68 [591,] 23.64 73 [592,] 23.68 73 [593,] 23.72 71 [594,] 23.76 69 [595,] 23.80 73 [596,] 23.84 63 [597,] 23.88 63 [598,] 23.92 71 [599,] 23.96 58 [600,] 24.00 49 [601,] 24.04 62 [602,] 24.08 70 [603,] 24.12 56 [604,] 24.16 78 [605,] 24.20 74 [606,] 24.24 63 [607,] 24.28 68 [608,] 24.32 57 [609,] 24.36 51 [610,] 24.40 61 [611,] 24.44 77 [612,] 24.48 62 [613,] 24.52 62 [614,] 24.56 61 [615,] 24.60 66 [616,] 24.64 71 [617,] 24.68 73 [618,] 24.72 63 [619,] 24.76 48 [620,] 24.80 80 [621,] 24.84 52 [622,] 24.88 69 [623,] 24.92 71 [624,] 24.96 54 [625,] 25.00 63 [626,] 25.04 68 [627,] 25.08 62 [628,] 25.12 63 [629,] 25.16 55 [630,] 25.20 59 [631,] 25.24 84 [632,] 25.28 64 [633,] 25.32 56 [634,] 25.36 64 [635,] 25.40 64 [636,] 25.44 61 [637,] 25.48 63 [638,] 25.52 72 [639,] 25.56 55 [640,] 25.60 58 [641,] 25.64 66 [642,] 25.68 75 [643,] 25.72 72 [644,] 25.76 44 [645,] 25.80 58 [646,] 25.84 68 [647,] 25.88 67 [648,] 25.92 64 [649,] 25.96 69 [650,] 26.00 60 [651,] 26.04 65 [652,] 26.08 65 [653,] 26.12 69 [654,] 26.16 60 [655,] 26.20 62 [656,] 26.24 64 [657,] 26.28 72 [658,] 26.32 76 [659,] 26.36 60 [660,] 26.40 74 [661,] 26.44 86 [662,] 26.48 50 [663,] 26.52 65 [664,] 26.56 61 [665,] 26.60 76 [666,] 26.64 74 [667,] 26.68 72 [668,] 26.72 70 [669,] 26.76 65 [670,] 26.80 56 [671,] 26.84 62 [672,] 26.88 55 [673,] 26.92 39 [674,] 26.96 74 [675,] 27.00 59 [676,] 27.04 82 [677,] 27.08 61 [678,] 27.12 63 [679,] 27.16 68 [680,] 27.20 51 [681,] 27.24 80 [682,] 27.28 50 [683,] 27.32 69 [684,] 27.36 69 [685,] 27.40 51 [686,] 27.44 65 [687,] 27.48 89 [688,] 27.52 70 [689,] 27.56 54 [690,] 27.60 66 [691,] 27.64 66 [692,] 27.68 74 [693,] 27.72 73 [694,] 27.76 59 [695,] 27.80 64 [696,] 27.84 89 [697,] 27.88 65 [698,] 27.92 79 [699,] 27.96 63 [700,] 28.00 60 [701,] 28.04 63 [702,] 28.08 66 [703,] 28.12 60 [704,] 28.16 58 [705,] 28.20 91 [706,] 28.24 60 [707,] 28.28 64 [708,] 28.32 79 [709,] 28.36 43 [710,] 28.40 50 [711,] 28.44 63 [712,] 28.48 66 [713,] 28.52 53 [714,] 28.56 68 [715,] 28.60 69 [716,] 28.64 69 [717,] 28.68 62 [718,] 28.72 89 [719,] 28.76 63 [720,] 28.80 77 [721,] 28.84 77 [722,] 28.88 68 [723,] 28.92 66 [724,] 28.96 45 [725,] 29.00 49 [726,] 29.04 60 [727,] 29.08 71 [728,] 29.12 77 [729,] 29.16 57 [730,] 29.20 66 [731,] 29.24 67 [732,] 29.28 53 [733,] 29.32 63 [734,] 29.36 57 [735,] 29.40 81 [736,] 29.44 69 [737,] 29.48 65 [738,] 29.52 62 [739,] 29.56 73 [740,] 29.60 61 [741,] 29.64 61 [742,] 29.68 77 [743,] 29.72 78 [744,] 29.76 60 [745,] 29.80 78 [746,] 29.84 63 [747,] 29.88 68 [748,] 29.92 56 [749,] 29.96 61 [750,] 30.00 59 [751,] 30.04 84 [752,] 30.08 65 [753,] 30.12 61 [754,] 30.16 58 [755,] 30.20 57 [756,] 30.24 73 [757,] 30.28 65 [758,] 30.32 65 [759,] 30.36 65 [760,] 30.40 64 [761,] 30.44 90 [762,] 30.48 77 [763,] 30.52 58 [764,] 30.56 60 [765,] 30.60 78 [766,] 30.64 73 [767,] 30.68 78 [768,] 30.72 57 [769,] 30.76 53 [770,] 30.80 52 [771,] 30.84 70 [772,] 30.88 63 [773,] 30.92 55 [774,] 30.96 65 [775,] 31.00 80 [776,] 31.04 64 [777,] 31.08 48 [778,] 31.12 77 [779,] 31.16 67 [780,] 31.20 65 [781,] 31.24 67 [782,] 31.28 46 [783,] 31.32 67 [784,] 31.36 73 [785,] 31.40 64 [786,] 31.44 69 [787,] 31.48 60 [788,] 31.52 59 [789,] 31.56 56 [790,] 31.60 43 [791,] 31.64 79 [792,] 31.68 55 [793,] 31.72 83 [794,] 31.76 73 [795,] 31.80 74 [796,] 31.84 59 [797,] 31.88 75 [798,] 31.92 88 [799,] 31.96 63 [800,] 32.00 58 [801,] 32.04 56 [802,] 32.08 53 [803,] 32.12 76 [804,] 32.16 86 [805,] 32.20 58 [806,] 32.24 55 [807,] 32.28 64 [808,] 32.32 59 [809,] 32.36 68 [810,] 32.40 65 [811,] 32.44 61 [812,] 32.48 58 [813,] 32.52 53 [814,] 32.56 61 [815,] 32.60 65 [816,] 32.64 54 [817,] 32.68 67 [818,] 32.72 71 [819,] 32.76 77 [820,] 32.80 77 [821,] 32.84 58 [822,] 32.88 67 [823,] 32.92 61 [824,] 32.96 85 [825,] 33.00 49 [826,] 33.04 75 [827,] 33.08 66 [828,] 33.12 72 [829,] 33.16 64 [830,] 33.20 53 [831,] 33.24 59 [832,] 33.28 73 [833,] 33.32 62 [834,] 33.36 63 [835,] 33.40 63 [836,] 33.44 64 [837,] 33.48 54 [838,] 33.52 53 [839,] 33.56 52 [840,] 33.60 51 [841,] 33.64 64 [842,] 33.68 74 [843,] 33.72 54 [844,] 33.76 53 [845,] 33.80 59 [846,] 33.84 63 [847,] 33.88 63 [848,] 33.92 57 [849,] 33.96 57 [850,] 34.00 77 [851,] 34.04 66 [852,] 34.08 53 [853,] 34.12 72 [854,] 34.16 63 [855,] 34.20 66 [856,] 34.24 88 [857,] 34.28 54 [858,] 34.32 57 [859,] 34.36 71 [860,] 34.40 58 [861,] 34.44 71 [862,] 34.48 60 [863,] 34.52 68 [864,] 34.56 65 [865,] 34.60 58 [866,] 34.64 57 [867,] 34.68 58 [868,] 34.72 67 [869,] 34.76 66 [870,] 34.80 53 [871,] 34.84 75 [872,] 34.88 77 [873,] 34.92 51 [874,] 34.96 63 [875,] 35.00 53 [876,] 35.04 59 [877,] 35.08 63 [878,] 35.12 63 [879,] 35.16 63 [880,] 35.20 65 [881,] 35.24 72 [882,] 35.28 75 [883,] 35.32 60 [884,] 35.36 62 [885,] 35.40 63 [886,] 35.44 61 [887,] 35.48 58 [888,] 35.52 70 [889,] 35.56 49 [890,] 35.60 58 [891,] 35.64 50 [892,] 35.68 50 [893,] 35.72 53 [894,] 35.76 62 [895,] 35.80 61 [896,] 35.84 78 [897,] 35.88 61 [898,] 35.92 67 [899,] 35.96 54 [900,] 36.00 55 [901,] 36.04 56 [902,] 36.08 49 [903,] 36.12 52 [904,] 36.16 60 [905,] 36.20 50 [906,] 36.24 72 [907,] 36.28 60 [908,] 36.32 63 [909,] 36.36 56 [910,] 36.40 56 [911,] 36.44 50 [912,] 36.48 65 [913,] 36.52 59 [914,] 36.56 70 [915,] 36.60 68 [916,] 36.64 72 [917,] 36.68 81 [918,] 36.72 65 [919,] 36.76 65 [920,] 36.80 60 [921,] 36.84 69 [922,] 36.88 54 [923,] 36.92 75 [924,] 36.96 49 [925,] 37.00 64 [926,] 37.04 54 [927,] 37.08 39 [928,] 37.12 58 [929,] 37.16 58 [930,] 37.20 59 [931,] 37.24 52 [932,] 37.28 56 [933,] 37.32 62 [934,] 37.36 76 [935,] 37.40 56 [936,] 37.44 58 [937,] 37.48 52 [938,] 37.52 57 [939,] 37.56 69 [940,] 37.60 48 [941,] 37.64 60 [942,] 37.68 61 [943,] 37.72 54 [944,] 37.76 73 [945,] 37.80 64 [946,] 37.84 53 [947,] 37.88 57 [948,] 37.92 67 [949,] 37.96 57 [950,] 38.00 67 [951,] 38.04 60 [952,] 38.08 44 [953,] 38.12 53 [954,] 38.16 70 [955,] 38.20 61 [956,] 38.24 69 [957,] 38.28 63 [958,] 38.32 73 [959,] 38.36 78 [960,] 38.40 74 [961,] 38.44 78 [962,] 38.48 56 [963,] 38.52 77 [964,] 38.56 59 [965,] 38.60 75 [966,] 38.64 52 [967,] 38.68 46 [968,] 38.72 62 [969,] 38.76 78 [970,] 38.80 66 [971,] 38.84 71 [972,] 38.88 40 [973,] 38.92 64 [974,] 38.96 49 [975,] 39.00 72 [976,] 39.04 55 [977,] 39.08 62 [978,] 39.12 60 [979,] 39.16 68 [980,] 39.20 63 [981,] 39.24 66 [982,] 39.28 63 [983,] 39.32 53 [984,] 39.36 65 [985,] 39.40 48 [986,] 39.44 60 [987,] 39.48 58 [988,] 39.52 52 [989,] 39.56 71 [990,] 39.60 60 [991,] 39.64 56 [992,] 39.68 57 [993,] 39.72 71 [994,] 39.76 80 [995,] 39.80 60 [996,] 39.84 75 [997,] 39.88 74 [998,] 39.92 60 [999,] 39.96 46 [1000,] 40.00 45 $`23_TL (PMT)` [,1] [,2] [1,] 0.64 22 [2,] 1.28 2 [3,] 1.92 2 [4,] 2.56 5 [5,] 3.20 6 [6,] 3.84 5 [7,] 4.48 2 [8,] 5.12 6 [9,] 5.76 5 [10,] 6.40 4 [11,] 7.04 2 [12,] 7.68 15 [13,] 8.32 5 [14,] 8.96 10 [15,] 9.60 7 [16,] 10.24 4 [17,] 10.88 1 [18,] 11.52 9 [19,] 12.16 4 [20,] 12.80 3 [21,] 13.44 3 [22,] 14.08 2 [23,] 14.72 10 [24,] 15.36 4 [25,] 16.00 3 [26,] 16.64 2 [27,] 17.28 5 [28,] 17.92 6 [29,] 18.56 6 [30,] 19.20 10 [31,] 19.84 6 [32,] 20.48 3 [33,] 21.12 10 [34,] 21.76 8 [35,] 22.40 1 [36,] 23.04 9 [37,] 23.68 0 [38,] 24.32 10 [39,] 24.96 4 [40,] 25.60 4 [41,] 26.24 8 [42,] 26.88 2 [43,] 27.52 6 [44,] 28.16 0 [45,] 28.80 4 [46,] 29.44 10 [47,] 30.08 9 [48,] 30.72 0 [49,] 31.36 5 [50,] 32.00 7 [51,] 32.64 7 [52,] 33.28 4 [53,] 33.92 6 [54,] 34.56 5 [55,] 35.20 2 [56,] 35.84 10 [57,] 36.48 5 [58,] 37.12 5 [59,] 37.76 9 [60,] 38.40 5 [61,] 39.04 3 [62,] 39.68 1 [63,] 40.32 0 [64,] 40.96 4 [65,] 41.60 1 [66,] 42.24 5 [67,] 42.88 5 [68,] 43.52 34 [69,] 44.16 3 [70,] 44.80 11 [71,] 45.44 6 [72,] 46.08 6 [73,] 46.72 6 [74,] 47.36 5 [75,] 48.00 3 [76,] 48.64 14 [77,] 49.28 2 [78,] 49.92 7 [79,] 50.56 11 [80,] 51.20 1 [81,] 51.84 7 [82,] 52.48 3 [83,] 53.12 3 [84,] 53.76 8 [85,] 54.40 4 [86,] 55.04 9 [87,] 55.68 19 [88,] 56.32 8 [89,] 56.96 9 [90,] 57.60 12 [91,] 58.24 12 [92,] 58.88 14 [93,] 59.52 12 [94,] 60.16 7 [95,] 60.80 14 [96,] 61.44 21 [97,] 62.08 14 [98,] 62.72 30 [99,] 63.36 16 [100,] 64.00 17 [101,] 64.64 8 [102,] 65.28 33 [103,] 65.92 20 [104,] 66.56 35 [105,] 67.20 35 [106,] 67.84 22 [107,] 68.48 25 [108,] 69.12 21 [109,] 69.76 42 [110,] 70.40 22 [111,] 71.04 31 [112,] 71.68 31 [113,] 72.32 29 [114,] 72.96 29 [115,] 73.60 44 [116,] 74.24 42 [117,] 74.88 47 [118,] 75.52 58 [119,] 76.16 40 [120,] 76.80 51 [121,] 77.44 58 [122,] 78.08 74 [123,] 78.72 55 [124,] 79.36 68 [125,] 80.00 55 [126,] 80.64 76 [127,] 81.28 74 [128,] 81.92 88 [129,] 82.56 80 [130,] 83.20 98 [131,] 83.84 95 [132,] 84.48 99 [133,] 85.12 109 [134,] 85.76 104 [135,] 86.40 136 [136,] 87.04 114 [137,] 87.68 132 [138,] 88.32 159 [139,] 88.96 119 [140,] 89.60 165 [141,] 90.24 160 [142,] 90.88 162 [143,] 91.52 168 [144,] 92.16 123 [145,] 92.80 170 [146,] 93.44 165 [147,] 94.08 193 [148,] 94.72 159 [149,] 95.36 191 [150,] 96.00 206 [151,] 96.64 231 [152,] 97.28 229 [153,] 97.92 225 [154,] 98.56 239 [155,] 99.20 248 [156,] 99.84 240 [157,] 100.48 267 [158,] 101.12 238 [159,] 101.76 270 [160,] 102.40 270 [161,] 103.04 256 [162,] 103.68 272 [163,] 104.32 237 [164,] 104.96 273 [165,] 105.60 238 [166,] 106.24 251 [167,] 106.88 270 [168,] 107.52 258 [169,] 108.16 252 [170,] 108.80 239 [171,] 109.44 244 [172,] 110.08 245 [173,] 110.72 233 [174,] 111.36 235 [175,] 112.00 238 [176,] 112.64 222 [177,] 113.28 208 [178,] 113.92 219 [179,] 114.56 227 [180,] 115.20 185 [181,] 115.84 196 [182,] 116.48 162 [183,] 117.12 155 [184,] 117.76 155 [185,] 118.40 136 [186,] 119.04 133 [187,] 119.68 120 [188,] 120.32 150 [189,] 120.96 126 [190,] 121.60 115 [191,] 122.24 126 [192,] 122.88 108 [193,] 123.52 102 [194,] 124.16 107 [195,] 124.80 106 [196,] 125.44 113 [197,] 126.08 97 [198,] 126.72 94 [199,] 127.36 92 [200,] 128.00 78 [201,] 128.64 92 [202,] 129.28 76 [203,] 129.92 80 [204,] 130.56 81 [205,] 131.20 90 [206,] 131.84 90 [207,] 132.48 98 [208,] 133.12 65 [209,] 133.76 95 [210,] 134.40 108 [211,] 135.04 100 [212,] 135.68 77 [213,] 136.32 87 [214,] 136.96 89 [215,] 137.60 110 [216,] 138.24 68 [217,] 138.88 75 [218,] 139.52 89 [219,] 140.16 90 [220,] 140.80 91 [221,] 141.44 88 [222,] 142.08 100 [223,] 142.72 84 [224,] 143.36 100 [225,] 144.00 114 [226,] 144.64 97 [227,] 145.28 94 [228,] 145.92 95 [229,] 146.56 87 [230,] 147.20 95 [231,] 147.84 93 [232,] 148.48 84 [233,] 149.12 91 [234,] 149.76 88 [235,] 150.40 83 [236,] 151.04 102 [237,] 151.68 91 [238,] 152.32 89 [239,] 152.96 89 [240,] 153.60 109 [241,] 154.24 99 [242,] 154.88 103 [243,] 155.52 76 [244,] 156.16 84 [245,] 156.80 85 [246,] 157.44 79 [247,] 158.08 88 [248,] 158.72 80 [249,] 159.36 80 [250,] 160.00 87 $`24_OSL (PMT)` [,1] [,2] [1,] 0.04 3179 [2,] 0.08 2681 [3,] 0.12 2278 [4,] 0.16 2056 [5,] 0.20 1749 [6,] 0.24 1564 [7,] 0.28 1299 [8,] 0.32 1280 [9,] 0.36 1088 [10,] 0.40 1041 [11,] 0.44 824 [12,] 0.48 745 [13,] 0.52 677 [14,] 0.56 653 [15,] 0.60 536 [16,] 0.64 483 [17,] 0.68 446 [18,] 0.72 404 [19,] 0.76 398 [20,] 0.80 360 [21,] 0.84 338 [22,] 0.88 322 [23,] 0.92 296 [24,] 0.96 270 [25,] 1.00 271 [26,] 1.04 223 [27,] 1.08 256 [28,] 1.12 236 [29,] 1.16 272 [30,] 1.20 236 [31,] 1.24 222 [32,] 1.28 205 [33,] 1.32 204 [34,] 1.36 202 [35,] 1.40 171 [36,] 1.44 170 [37,] 1.48 164 [38,] 1.52 163 [39,] 1.56 188 [40,] 1.60 165 [41,] 1.64 134 [42,] 1.68 130 [43,] 1.72 146 [44,] 1.76 130 [45,] 1.80 144 [46,] 1.84 144 [47,] 1.88 122 [48,] 1.92 155 [49,] 1.96 142 [50,] 2.00 143 [51,] 2.04 116 [52,] 2.08 121 [53,] 2.12 134 [54,] 2.16 102 [55,] 2.20 136 [56,] 2.24 128 [57,] 2.28 111 [58,] 2.32 108 [59,] 2.36 113 [60,] 2.40 115 [61,] 2.44 134 [62,] 2.48 135 [63,] 2.52 109 [64,] 2.56 113 [65,] 2.60 113 [66,] 2.64 120 [67,] 2.68 102 [68,] 2.72 116 [69,] 2.76 116 [70,] 2.80 126 [71,] 2.84 114 [72,] 2.88 106 [73,] 2.92 114 [74,] 2.96 95 [75,] 3.00 127 [76,] 3.04 103 [77,] 3.08 87 [78,] 3.12 127 [79,] 3.16 93 [80,] 3.20 98 [81,] 3.24 123 [82,] 3.28 130 [83,] 3.32 104 [84,] 3.36 106 [85,] 3.40 103 [86,] 3.44 93 [87,] 3.48 107 [88,] 3.52 89 [89,] 3.56 114 [90,] 3.60 125 [91,] 3.64 103 [92,] 3.68 95 [93,] 3.72 88 [94,] 3.76 122 [95,] 3.80 97 [96,] 3.84 108 [97,] 3.88 123 [98,] 3.92 118 [99,] 3.96 97 [100,] 4.00 120 [101,] 4.04 102 [102,] 4.08 117 [103,] 4.12 107 [104,] 4.16 98 [105,] 4.20 134 [106,] 4.24 122 [107,] 4.28 97 [108,] 4.32 118 [109,] 4.36 79 [110,] 4.40 100 [111,] 4.44 106 [112,] 4.48 93 [113,] 4.52 97 [114,] 4.56 90 [115,] 4.60 109 [116,] 4.64 85 [117,] 4.68 97 [118,] 4.72 94 [119,] 4.76 100 [120,] 4.80 104 [121,] 4.84 112 [122,] 4.88 95 [123,] 4.92 86 [124,] 4.96 98 [125,] 5.00 85 [126,] 5.04 108 [127,] 5.08 87 [128,] 5.12 75 [129,] 5.16 85 [130,] 5.20 75 [131,] 5.24 84 [132,] 5.28 92 [133,] 5.32 101 [134,] 5.36 105 [135,] 5.40 84 [136,] 5.44 94 [137,] 5.48 95 [138,] 5.52 84 [139,] 5.56 101 [140,] 5.60 90 [141,] 5.64 75 [142,] 5.68 91 [143,] 5.72 92 [144,] 5.76 97 [145,] 5.80 94 [146,] 5.84 91 [147,] 5.88 86 [148,] 5.92 91 [149,] 5.96 113 [150,] 6.00 70 [151,] 6.04 85 [152,] 6.08 81 [153,] 6.12 97 [154,] 6.16 74 [155,] 6.20 93 [156,] 6.24 72 [157,] 6.28 86 [158,] 6.32 105 [159,] 6.36 107 [160,] 6.40 105 [161,] 6.44 92 [162,] 6.48 104 [163,] 6.52 92 [164,] 6.56 91 [165,] 6.60 78 [166,] 6.64 83 [167,] 6.68 103 [168,] 6.72 70 [169,] 6.76 82 [170,] 6.80 86 [171,] 6.84 108 [172,] 6.88 88 [173,] 6.92 97 [174,] 6.96 90 [175,] 7.00 76 [176,] 7.04 94 [177,] 7.08 92 [178,] 7.12 88 [179,] 7.16 93 [180,] 7.20 81 [181,] 7.24 88 [182,] 7.28 86 [183,] 7.32 88 [184,] 7.36 75 [185,] 7.40 88 [186,] 7.44 89 [187,] 7.48 75 [188,] 7.52 82 [189,] 7.56 70 [190,] 7.60 91 [191,] 7.64 62 [192,] 7.68 75 [193,] 7.72 96 [194,] 7.76 67 [195,] 7.80 82 [196,] 7.84 87 [197,] 7.88 88 [198,] 7.92 102 [199,] 7.96 80 [200,] 8.00 73 [201,] 8.04 77 [202,] 8.08 82 [203,] 8.12 88 [204,] 8.16 61 [205,] 8.20 76 [206,] 8.24 90 [207,] 8.28 86 [208,] 8.32 81 [209,] 8.36 79 [210,] 8.40 106 [211,] 8.44 81 [212,] 8.48 107 [213,] 8.52 84 [214,] 8.56 83 [215,] 8.60 75 [216,] 8.64 79 [217,] 8.68 72 [218,] 8.72 71 [219,] 8.76 82 [220,] 8.80 72 [221,] 8.84 93 [222,] 8.88 90 [223,] 8.92 78 [224,] 8.96 88 [225,] 9.00 108 [226,] 9.04 79 [227,] 9.08 68 [228,] 9.12 96 [229,] 9.16 113 [230,] 9.20 87 [231,] 9.24 84 [232,] 9.28 83 [233,] 9.32 90 [234,] 9.36 85 [235,] 9.40 80 [236,] 9.44 109 [237,] 9.48 86 [238,] 9.52 88 [239,] 9.56 77 [240,] 9.60 84 [241,] 9.64 83 [242,] 9.68 94 [243,] 9.72 85 [244,] 9.76 93 [245,] 9.80 93 [246,] 9.84 71 [247,] 9.88 80 [248,] 9.92 90 [249,] 9.96 78 [250,] 10.00 78 [251,] 10.04 83 [252,] 10.08 81 [253,] 10.12 89 [254,] 10.16 89 [255,] 10.20 77 [256,] 10.24 92 [257,] 10.28 76 [258,] 10.32 68 [259,] 10.36 77 [260,] 10.40 100 [261,] 10.44 57 [262,] 10.48 90 [263,] 10.52 82 [264,] 10.56 77 [265,] 10.60 85 [266,] 10.64 90 [267,] 10.68 81 [268,] 10.72 86 [269,] 10.76 82 [270,] 10.80 74 [271,] 10.84 72 [272,] 10.88 71 [273,] 10.92 81 [274,] 10.96 90 [275,] 11.00 78 [276,] 11.04 74 [277,] 11.08 67 [278,] 11.12 73 [279,] 11.16 83 [280,] 11.20 78 [281,] 11.24 92 [282,] 11.28 66 [283,] 11.32 80 [284,] 11.36 74 [285,] 11.40 70 [286,] 11.44 73 [287,] 11.48 81 [288,] 11.52 82 [289,] 11.56 77 [290,] 11.60 64 [291,] 11.64 66 [292,] 11.68 56 [293,] 11.72 68 [294,] 11.76 79 [295,] 11.80 84 [296,] 11.84 89 [297,] 11.88 73 [298,] 11.92 83 [299,] 11.96 85 [300,] 12.00 77 [301,] 12.04 81 [302,] 12.08 92 [303,] 12.12 75 [304,] 12.16 77 [305,] 12.20 83 [306,] 12.24 73 [307,] 12.28 108 [308,] 12.32 86 [309,] 12.36 74 [310,] 12.40 99 [311,] 12.44 73 [312,] 12.48 59 [313,] 12.52 77 [314,] 12.56 94 [315,] 12.60 79 [316,] 12.64 80 [317,] 12.68 77 [318,] 12.72 66 [319,] 12.76 81 [320,] 12.80 87 [321,] 12.84 69 [322,] 12.88 89 [323,] 12.92 96 [324,] 12.96 89 [325,] 13.00 81 [326,] 13.04 83 [327,] 13.08 84 [328,] 13.12 70 [329,] 13.16 68 [330,] 13.20 81 [331,] 13.24 82 [332,] 13.28 85 [333,] 13.32 96 [334,] 13.36 80 [335,] 13.40 64 [336,] 13.44 71 [337,] 13.48 83 [338,] 13.52 80 [339,] 13.56 74 [340,] 13.60 88 [341,] 13.64 70 [342,] 13.68 69 [343,] 13.72 85 [344,] 13.76 79 [345,] 13.80 65 [346,] 13.84 72 [347,] 13.88 61 [348,] 13.92 102 [349,] 13.96 87 [350,] 14.00 70 [351,] 14.04 71 [352,] 14.08 71 [353,] 14.12 75 [354,] 14.16 82 [355,] 14.20 79 [356,] 14.24 80 [357,] 14.28 79 [358,] 14.32 96 [359,] 14.36 70 [360,] 14.40 97 [361,] 14.44 74 [362,] 14.48 58 [363,] 14.52 93 [364,] 14.56 83 [365,] 14.60 72 [366,] 14.64 90 [367,] 14.68 77 [368,] 14.72 73 [369,] 14.76 81 [370,] 14.80 78 [371,] 14.84 90 [372,] 14.88 65 [373,] 14.92 86 [374,] 14.96 78 [375,] 15.00 69 [376,] 15.04 79 [377,] 15.08 59 [378,] 15.12 65 [379,] 15.16 61 [380,] 15.20 66 [381,] 15.24 81 [382,] 15.28 77 [383,] 15.32 93 [384,] 15.36 67 [385,] 15.40 68 [386,] 15.44 86 [387,] 15.48 78 [388,] 15.52 62 [389,] 15.56 64 [390,] 15.60 64 [391,] 15.64 73 [392,] 15.68 70 [393,] 15.72 65 [394,] 15.76 101 [395,] 15.80 79 [396,] 15.84 63 [397,] 15.88 70 [398,] 15.92 94 [399,] 15.96 74 [400,] 16.00 67 [401,] 16.04 71 [402,] 16.08 68 [403,] 16.12 86 [404,] 16.16 59 [405,] 16.20 62 [406,] 16.24 107 [407,] 16.28 84 [408,] 16.32 74 [409,] 16.36 76 [410,] 16.40 83 [411,] 16.44 59 [412,] 16.48 81 [413,] 16.52 83 [414,] 16.56 56 [415,] 16.60 81 [416,] 16.64 81 [417,] 16.68 62 [418,] 16.72 69 [419,] 16.76 72 [420,] 16.80 72 [421,] 16.84 68 [422,] 16.88 85 [423,] 16.92 71 [424,] 16.96 84 [425,] 17.00 77 [426,] 17.04 57 [427,] 17.08 82 [428,] 17.12 81 [429,] 17.16 74 [430,] 17.20 68 [431,] 17.24 70 [432,] 17.28 67 [433,] 17.32 68 [434,] 17.36 79 [435,] 17.40 61 [436,] 17.44 66 [437,] 17.48 63 [438,] 17.52 76 [439,] 17.56 68 [440,] 17.60 58 [441,] 17.64 73 [442,] 17.68 94 [443,] 17.72 65 [444,] 17.76 63 [445,] 17.80 69 [446,] 17.84 70 [447,] 17.88 71 [448,] 17.92 54 [449,] 17.96 58 [450,] 18.00 71 [451,] 18.04 78 [452,] 18.08 70 [453,] 18.12 68 [454,] 18.16 72 [455,] 18.20 92 [456,] 18.24 68 [457,] 18.28 64 [458,] 18.32 69 [459,] 18.36 74 [460,] 18.40 71 [461,] 18.44 89 [462,] 18.48 62 [463,] 18.52 61 [464,] 18.56 63 [465,] 18.60 63 [466,] 18.64 93 [467,] 18.68 68 [468,] 18.72 73 [469,] 18.76 82 [470,] 18.80 70 [471,] 18.84 72 [472,] 18.88 92 [473,] 18.92 62 [474,] 18.96 70 [475,] 19.00 66 [476,] 19.04 84 [477,] 19.08 77 [478,] 19.12 71 [479,] 19.16 86 [480,] 19.20 80 [481,] 19.24 78 [482,] 19.28 83 [483,] 19.32 67 [484,] 19.36 72 [485,] 19.40 65 [486,] 19.44 68 [487,] 19.48 66 [488,] 19.52 57 [489,] 19.56 70 [490,] 19.60 83 [491,] 19.64 62 [492,] 19.68 90 [493,] 19.72 70 [494,] 19.76 95 [495,] 19.80 56 [496,] 19.84 71 [497,] 19.88 60 [498,] 19.92 71 [499,] 19.96 70 [500,] 20.00 65 [501,] 20.04 78 [502,] 20.08 85 [503,] 20.12 60 [504,] 20.16 69 [505,] 20.20 58 [506,] 20.24 73 [507,] 20.28 74 [508,] 20.32 70 [509,] 20.36 70 [510,] 20.40 65 [511,] 20.44 62 [512,] 20.48 68 [513,] 20.52 72 [514,] 20.56 73 [515,] 20.60 64 [516,] 20.64 72 [517,] 20.68 82 [518,] 20.72 68 [519,] 20.76 60 [520,] 20.80 67 [521,] 20.84 55 [522,] 20.88 75 [523,] 20.92 75 [524,] 20.96 81 [525,] 21.00 68 [526,] 21.04 62 [527,] 21.08 60 [528,] 21.12 72 [529,] 21.16 66 [530,] 21.20 67 [531,] 21.24 72 [532,] 21.28 66 [533,] 21.32 68 [534,] 21.36 82 [535,] 21.40 64 [536,] 21.44 75 [537,] 21.48 80 [538,] 21.52 83 [539,] 21.56 77 [540,] 21.60 59 [541,] 21.64 66 [542,] 21.68 86 [543,] 21.72 75 [544,] 21.76 61 [545,] 21.80 74 [546,] 21.84 62 [547,] 21.88 69 [548,] 21.92 61 [549,] 21.96 82 [550,] 22.00 79 [551,] 22.04 73 [552,] 22.08 58 [553,] 22.12 63 [554,] 22.16 75 [555,] 22.20 69 [556,] 22.24 67 [557,] 22.28 53 [558,] 22.32 94 [559,] 22.36 85 [560,] 22.40 59 [561,] 22.44 76 [562,] 22.48 73 [563,] 22.52 48 [564,] 22.56 56 [565,] 22.60 79 [566,] 22.64 90 [567,] 22.68 63 [568,] 22.72 70 [569,] 22.76 73 [570,] 22.80 57 [571,] 22.84 57 [572,] 22.88 66 [573,] 22.92 70 [574,] 22.96 88 [575,] 23.00 60 [576,] 23.04 64 [577,] 23.08 74 [578,] 23.12 93 [579,] 23.16 74 [580,] 23.20 77 [581,] 23.24 79 [582,] 23.28 82 [583,] 23.32 75 [584,] 23.36 80 [585,] 23.40 77 [586,] 23.44 97 [587,] 23.48 64 [588,] 23.52 88 [589,] 23.56 78 [590,] 23.60 74 [591,] 23.64 95 [592,] 23.68 61 [593,] 23.72 71 [594,] 23.76 59 [595,] 23.80 78 [596,] 23.84 79 [597,] 23.88 89 [598,] 23.92 59 [599,] 23.96 69 [600,] 24.00 76 [601,] 24.04 52 [602,] 24.08 76 [603,] 24.12 69 [604,] 24.16 76 [605,] 24.20 80 [606,] 24.24 86 [607,] 24.28 76 [608,] 24.32 51 [609,] 24.36 63 [610,] 24.40 63 [611,] 24.44 74 [612,] 24.48 64 [613,] 24.52 59 [614,] 24.56 63 [615,] 24.60 49 [616,] 24.64 55 [617,] 24.68 69 [618,] 24.72 55 [619,] 24.76 72 [620,] 24.80 77 [621,] 24.84 77 [622,] 24.88 57 [623,] 24.92 49 [624,] 24.96 62 [625,] 25.00 65 [626,] 25.04 60 [627,] 25.08 51 [628,] 25.12 59 [629,] 25.16 70 [630,] 25.20 50 [631,] 25.24 76 [632,] 25.28 77 [633,] 25.32 67 [634,] 25.36 69 [635,] 25.40 64 [636,] 25.44 61 [637,] 25.48 73 [638,] 25.52 50 [639,] 25.56 64 [640,] 25.60 75 [641,] 25.64 60 [642,] 25.68 66 [643,] 25.72 61 [644,] 25.76 68 [645,] 25.80 61 [646,] 25.84 55 [647,] 25.88 61 [648,] 25.92 66 [649,] 25.96 50 [650,] 26.00 73 [651,] 26.04 62 [652,] 26.08 61 [653,] 26.12 63 [654,] 26.16 53 [655,] 26.20 80 [656,] 26.24 75 [657,] 26.28 78 [658,] 26.32 65 [659,] 26.36 65 [660,] 26.40 66 [661,] 26.44 58 [662,] 26.48 62 [663,] 26.52 78 [664,] 26.56 54 [665,] 26.60 58 [666,] 26.64 68 [667,] 26.68 84 [668,] 26.72 67 [669,] 26.76 80 [670,] 26.80 69 [671,] 26.84 73 [672,] 26.88 64 [673,] 26.92 72 [674,] 26.96 77 [675,] 27.00 56 [676,] 27.04 76 [677,] 27.08 71 [678,] 27.12 70 [679,] 27.16 56 [680,] 27.20 72 [681,] 27.24 67 [682,] 27.28 74 [683,] 27.32 68 [684,] 27.36 77 [685,] 27.40 53 [686,] 27.44 70 [687,] 27.48 67 [688,] 27.52 49 [689,] 27.56 91 [690,] 27.60 74 [691,] 27.64 81 [692,] 27.68 70 [693,] 27.72 53 [694,] 27.76 63 [695,] 27.80 59 [696,] 27.84 61 [697,] 27.88 82 [698,] 27.92 72 [699,] 27.96 66 [700,] 28.00 67 [701,] 28.04 80 [702,] 28.08 55 [703,] 28.12 73 [704,] 28.16 73 [705,] 28.20 64 [706,] 28.24 65 [707,] 28.28 61 [708,] 28.32 71 [709,] 28.36 52 [710,] 28.40 74 [711,] 28.44 70 [712,] 28.48 63 [713,] 28.52 73 [714,] 28.56 72 [715,] 28.60 47 [716,] 28.64 73 [717,] 28.68 65 [718,] 28.72 83 [719,] 28.76 74 [720,] 28.80 72 [721,] 28.84 63 [722,] 28.88 65 [723,] 28.92 69 [724,] 28.96 70 [725,] 29.00 83 [726,] 29.04 67 [727,] 29.08 52 [728,] 29.12 67 [729,] 29.16 79 [730,] 29.20 56 [731,] 29.24 72 [732,] 29.28 75 [733,] 29.32 46 [734,] 29.36 57 [735,] 29.40 57 [736,] 29.44 70 [737,] 29.48 89 [738,] 29.52 82 [739,] 29.56 64 [740,] 29.60 59 [741,] 29.64 65 [742,] 29.68 62 [743,] 29.72 61 [744,] 29.76 69 [745,] 29.80 58 [746,] 29.84 70 [747,] 29.88 61 [748,] 29.92 70 [749,] 29.96 63 [750,] 30.00 60 [751,] 30.04 47 [752,] 30.08 67 [753,] 30.12 75 [754,] 30.16 73 [755,] 30.20 58 [756,] 30.24 65 [757,] 30.28 58 [758,] 30.32 51 [759,] 30.36 56 [760,] 30.40 64 [761,] 30.44 72 [762,] 30.48 77 [763,] 30.52 71 [764,] 30.56 76 [765,] 30.60 46 [766,] 30.64 87 [767,] 30.68 68 [768,] 30.72 69 [769,] 30.76 69 [770,] 30.80 78 [771,] 30.84 71 [772,] 30.88 83 [773,] 30.92 63 [774,] 30.96 70 [775,] 31.00 65 [776,] 31.04 66 [777,] 31.08 56 [778,] 31.12 74 [779,] 31.16 54 [780,] 31.20 71 [781,] 31.24 103 [782,] 31.28 69 [783,] 31.32 56 [784,] 31.36 62 [785,] 31.40 59 [786,] 31.44 73 [787,] 31.48 45 [788,] 31.52 96 [789,] 31.56 74 [790,] 31.60 77 [791,] 31.64 46 [792,] 31.68 49 [793,] 31.72 72 [794,] 31.76 86 [795,] 31.80 58 [796,] 31.84 70 [797,] 31.88 46 [798,] 31.92 63 [799,] 31.96 74 [800,] 32.00 71 [801,] 32.04 56 [802,] 32.08 64 [803,] 32.12 51 [804,] 32.16 76 [805,] 32.20 73 [806,] 32.24 66 [807,] 32.28 71 [808,] 32.32 69 [809,] 32.36 57 [810,] 32.40 52 [811,] 32.44 55 [812,] 32.48 56 [813,] 32.52 71 [814,] 32.56 81 [815,] 32.60 58 [816,] 32.64 76 [817,] 32.68 56 [818,] 32.72 61 [819,] 32.76 61 [820,] 32.80 50 [821,] 32.84 51 [822,] 32.88 47 [823,] 32.92 66 [824,] 32.96 71 [825,] 33.00 57 [826,] 33.04 62 [827,] 33.08 71 [828,] 33.12 61 [829,] 33.16 58 [830,] 33.20 45 [831,] 33.24 80 [832,] 33.28 64 [833,] 33.32 65 [834,] 33.36 76 [835,] 33.40 62 [836,] 33.44 53 [837,] 33.48 64 [838,] 33.52 72 [839,] 33.56 65 [840,] 33.60 73 [841,] 33.64 49 [842,] 33.68 79 [843,] 33.72 79 [844,] 33.76 94 [845,] 33.80 49 [846,] 33.84 70 [847,] 33.88 55 [848,] 33.92 58 [849,] 33.96 88 [850,] 34.00 74 [851,] 34.04 63 [852,] 34.08 64 [853,] 34.12 50 [854,] 34.16 62 [855,] 34.20 67 [856,] 34.24 87 [857,] 34.28 56 [858,] 34.32 63 [859,] 34.36 56 [860,] 34.40 55 [861,] 34.44 57 [862,] 34.48 69 [863,] 34.52 82 [864,] 34.56 46 [865,] 34.60 85 [866,] 34.64 54 [867,] 34.68 61 [868,] 34.72 55 [869,] 34.76 71 [870,] 34.80 62 [871,] 34.84 64 [872,] 34.88 68 [873,] 34.92 61 [874,] 34.96 50 [875,] 35.00 68 [876,] 35.04 62 [877,] 35.08 64 [878,] 35.12 53 [879,] 35.16 47 [880,] 35.20 61 [881,] 35.24 73 [882,] 35.28 60 [883,] 35.32 62 [884,] 35.36 65 [885,] 35.40 66 [886,] 35.44 58 [887,] 35.48 85 [888,] 35.52 75 [889,] 35.56 52 [890,] 35.60 70 [891,] 35.64 62 [892,] 35.68 64 [893,] 35.72 57 [894,] 35.76 56 [895,] 35.80 49 [896,] 35.84 71 [897,] 35.88 75 [898,] 35.92 63 [899,] 35.96 53 [900,] 36.00 57 [901,] 36.04 67 [902,] 36.08 73 [903,] 36.12 87 [904,] 36.16 65 [905,] 36.20 58 [906,] 36.24 49 [907,] 36.28 78 [908,] 36.32 60 [909,] 36.36 65 [910,] 36.40 70 [911,] 36.44 54 [912,] 36.48 47 [913,] 36.52 71 [914,] 36.56 51 [915,] 36.60 65 [916,] 36.64 58 [917,] 36.68 51 [918,] 36.72 81 [919,] 36.76 56 [920,] 36.80 68 [921,] 36.84 70 [922,] 36.88 58 [923,] 36.92 53 [924,] 36.96 88 [925,] 37.00 68 [926,] 37.04 61 [927,] 37.08 59 [928,] 37.12 58 [929,] 37.16 62 [930,] 37.20 66 [931,] 37.24 61 [932,] 37.28 69 [933,] 37.32 57 [934,] 37.36 62 [935,] 37.40 57 [936,] 37.44 45 [937,] 37.48 68 [938,] 37.52 80 [939,] 37.56 52 [940,] 37.60 49 [941,] 37.64 58 [942,] 37.68 51 [943,] 37.72 89 [944,] 37.76 67 [945,] 37.80 54 [946,] 37.84 58 [947,] 37.88 57 [948,] 37.92 72 [949,] 37.96 72 [950,] 38.00 64 [951,] 38.04 53 [952,] 38.08 61 [953,] 38.12 62 [954,] 38.16 56 [955,] 38.20 58 [956,] 38.24 82 [957,] 38.28 70 [958,] 38.32 68 [959,] 38.36 80 [960,] 38.40 72 [961,] 38.44 58 [962,] 38.48 95 [963,] 38.52 62 [964,] 38.56 59 [965,] 38.60 66 [966,] 38.64 64 [967,] 38.68 63 [968,] 38.72 63 [969,] 38.76 59 [970,] 38.80 78 [971,] 38.84 75 [972,] 38.88 52 [973,] 38.92 57 [974,] 38.96 72 [975,] 39.00 69 [976,] 39.04 62 [977,] 39.08 54 [978,] 39.12 62 [979,] 39.16 62 [980,] 39.20 53 [981,] 39.24 54 [982,] 39.28 68 [983,] 39.32 50 [984,] 39.36 45 [985,] 39.40 73 [986,] 39.44 65 [987,] 39.48 82 [988,] 39.52 72 [989,] 39.56 61 [990,] 39.60 55 [991,] 39.64 74 [992,] 39.68 72 [993,] 39.72 76 [994,] 39.76 74 [995,] 39.80 56 [996,] 39.84 49 [997,] 39.88 56 [998,] 39.92 55 [999,] 39.96 69 [1000,] 40.00 75 $`25_TL (PMT)` [,1] [,2] [1,] 0.884 1 [2,] 1.768 3 [3,] 2.652 3 [4,] 3.536 3 [5,] 4.420 1 [6,] 5.304 8 [7,] 6.188 11 [8,] 7.072 5 [9,] 7.956 9 [10,] 8.840 5 [11,] 9.724 6 [12,] 10.608 1 [13,] 11.492 3 [14,] 12.376 4 [15,] 13.260 4 [16,] 14.144 10 [17,] 15.028 8 [18,] 15.912 7 [19,] 16.796 3 [20,] 17.680 2 [21,] 18.564 3 [22,] 19.448 2 [23,] 20.332 12 [24,] 21.216 4 [25,] 22.100 2 [26,] 22.984 7 [27,] 23.868 1 [28,] 24.752 4 [29,] 25.636 11 [30,] 26.520 2 [31,] 27.404 1 [32,] 28.288 3 [33,] 29.172 4 [34,] 30.056 4 [35,] 30.940 3 [36,] 31.824 11 [37,] 32.708 9 [38,] 33.592 9 [39,] 34.476 15 [40,] 35.360 3 [41,] 36.244 1 [42,] 37.128 3 [43,] 38.012 6 [44,] 38.896 2 [45,] 39.780 4 [46,] 40.664 8 [47,] 41.548 1 [48,] 42.432 9 [49,] 43.316 3 [50,] 44.200 4 [51,] 45.084 6 [52,] 45.968 5 [53,] 46.852 2 [54,] 47.736 9 [55,] 48.620 9 [56,] 49.504 7 [57,] 50.388 3 [58,] 51.272 6 [59,] 52.156 2 [60,] 53.040 6 [61,] 53.924 2 [62,] 54.808 18 [63,] 55.692 10 [64,] 56.576 7 [65,] 57.460 3 [66,] 58.344 5 [67,] 59.228 9 [68,] 60.112 2 [69,] 60.996 1 [70,] 61.880 11 [71,] 62.764 2 [72,] 63.648 4 [73,] 64.532 7 [74,] 65.416 4 [75,] 66.300 7 [76,] 67.184 2 [77,] 68.068 1 [78,] 68.952 5 [79,] 69.836 3 [80,] 70.720 4 [81,] 71.604 8 [82,] 72.488 11 [83,] 73.372 7 [84,] 74.256 3 [85,] 75.140 0 [86,] 76.024 11 [87,] 76.908 5 [88,] 77.792 8 [89,] 78.676 4 [90,] 79.560 2 [91,] 80.444 13 [92,] 81.328 0 [93,] 82.212 2 [94,] 83.096 4 [95,] 83.980 6 [96,] 84.864 6 [97,] 85.748 16 [98,] 86.632 2 [99,] 87.516 2 [100,] 88.400 3 [101,] 89.284 9 [102,] 90.168 5 [103,] 91.052 2 [104,] 91.936 2 [105,] 92.820 5 [106,] 93.704 13 [107,] 94.588 9 [108,] 95.472 4 [109,] 96.356 9 [110,] 97.240 11 [111,] 98.124 1 [112,] 99.008 7 [113,] 99.892 14 [114,] 100.776 5 [115,] 101.660 5 [116,] 102.544 4 [117,] 103.428 4 [118,] 104.312 2 [119,] 105.196 3 [120,] 106.080 4 [121,] 106.964 6 [122,] 107.848 0 [123,] 108.732 3 [124,] 109.616 2 [125,] 110.500 2 [126,] 111.384 13 [127,] 112.268 4 [128,] 113.152 1 [129,] 114.036 9 [130,] 114.920 3 [131,] 115.804 11 [132,] 116.688 7 [133,] 117.572 5 [134,] 118.456 9 [135,] 119.340 6 [136,] 120.224 11 [137,] 121.108 5 [138,] 121.992 2 [139,] 122.876 12 [140,] 123.760 5 [141,] 124.644 6 [142,] 125.528 8 [143,] 126.412 4 [144,] 127.296 9 [145,] 128.180 13 [146,] 129.064 2 [147,] 129.948 6 [148,] 130.832 5 [149,] 131.716 3 [150,] 132.600 8 [151,] 133.484 6 [152,] 134.368 8 [153,] 135.252 6 [154,] 136.136 8 [155,] 137.020 12 [156,] 137.904 7 [157,] 138.788 7 [158,] 139.672 10 [159,] 140.556 11 [160,] 141.440 22 [161,] 142.324 6 [162,] 143.208 4 [163,] 144.092 19 [164,] 144.976 10 [165,] 145.860 8 [166,] 146.744 7 [167,] 147.628 13 [168,] 148.512 8 [169,] 149.396 8 [170,] 150.280 21 [171,] 151.164 20 [172,] 152.048 3 [173,] 152.932 11 [174,] 153.816 14 [175,] 154.700 16 [176,] 155.584 7 [177,] 156.468 24 [178,] 157.352 24 [179,] 158.236 24 [180,] 159.120 30 [181,] 160.004 20 [182,] 160.888 19 [183,] 161.772 25 [184,] 162.656 16 [185,] 163.540 16 [186,] 164.424 28 [187,] 165.308 35 [188,] 166.192 21 [189,] 167.076 19 [190,] 167.960 27 [191,] 168.844 19 [192,] 169.728 27 [193,] 170.612 27 [194,] 171.496 23 [195,] 172.380 33 [196,] 173.264 27 [197,] 174.148 38 [198,] 175.032 30 [199,] 175.916 34 [200,] 176.800 35 [201,] 177.684 24 [202,] 178.568 29 [203,] 179.452 55 [204,] 180.336 27 [205,] 181.220 30 [206,] 182.104 27 [207,] 182.988 31 [208,] 183.872 38 [209,] 184.756 29 [210,] 185.640 47 [211,] 186.524 53 [212,] 187.408 58 [213,] 188.292 43 [214,] 189.176 55 [215,] 190.060 41 [216,] 190.944 38 [217,] 191.828 73 [218,] 192.712 55 [219,] 193.596 52 [220,] 194.480 46 [221,] 195.364 47 [222,] 196.248 55 [223,] 197.132 54 [224,] 198.016 59 [225,] 198.900 57 [226,] 199.784 82 [227,] 200.668 79 [228,] 201.552 73 [229,] 202.436 72 [230,] 203.320 69 [231,] 204.204 86 [232,] 205.088 87 [233,] 205.972 78 [234,] 206.856 75 [235,] 207.740 108 [236,] 208.624 86 [237,] 209.508 91 [238,] 210.392 78 [239,] 211.276 127 [240,] 212.160 97 [241,] 213.044 124 [242,] 213.928 108 [243,] 214.812 98 [244,] 215.696 119 [245,] 216.580 103 [246,] 217.464 119 [247,] 218.348 125 [248,] 219.232 131 [249,] 220.116 108 [250,] 221.000 135 $`26_OSL (PMT)` [,1] [,2] [1,] 0.04 85 [2,] 0.08 107 [3,] 0.12 79 [4,] 0.16 74 [5,] 0.20 98 [6,] 0.24 90 [7,] 0.28 68 [8,] 0.32 93 [9,] 0.36 77 [10,] 0.40 69 [11,] 0.44 72 [12,] 0.48 60 [13,] 0.52 55 [14,] 0.56 64 [15,] 0.60 78 [16,] 0.64 71 [17,] 0.68 69 [18,] 0.72 70 [19,] 0.76 70 [20,] 0.80 54 [21,] 0.84 59 [22,] 0.88 60 [23,] 0.92 71 [24,] 0.96 58 [25,] 1.00 83 [26,] 1.04 72 [27,] 1.08 59 [28,] 1.12 53 [29,] 1.16 59 [30,] 1.20 61 [31,] 1.24 74 [32,] 1.28 57 [33,] 1.32 53 [34,] 1.36 66 [35,] 1.40 78 [36,] 1.44 65 [37,] 1.48 64 [38,] 1.52 65 [39,] 1.56 70 [40,] 1.60 51 [41,] 1.64 65 [42,] 1.68 59 [43,] 1.72 76 [44,] 1.76 52 [45,] 1.80 78 [46,] 1.84 50 [47,] 1.88 68 [48,] 1.92 59 [49,] 1.96 68 [50,] 2.00 83 [51,] 2.04 64 [52,] 2.08 44 [53,] 2.12 82 [54,] 2.16 57 [55,] 2.20 60 [56,] 2.24 65 [57,] 2.28 56 [58,] 2.32 69 [59,] 2.36 60 [60,] 2.40 78 [61,] 2.44 81 [62,] 2.48 71 [63,] 2.52 68 [64,] 2.56 50 [65,] 2.60 59 [66,] 2.64 59 [67,] 2.68 52 [68,] 2.72 53 [69,] 2.76 61 [70,] 2.80 63 [71,] 2.84 79 [72,] 2.88 58 [73,] 2.92 58 [74,] 2.96 70 [75,] 3.00 69 [76,] 3.04 77 [77,] 3.08 53 [78,] 3.12 63 [79,] 3.16 53 [80,] 3.20 72 [81,] 3.24 69 [82,] 3.28 42 [83,] 3.32 60 [84,] 3.36 62 [85,] 3.40 41 [86,] 3.44 58 [87,] 3.48 47 [88,] 3.52 61 [89,] 3.56 59 [90,] 3.60 71 [91,] 3.64 63 [92,] 3.68 65 [93,] 3.72 60 [94,] 3.76 73 [95,] 3.80 84 [96,] 3.84 49 [97,] 3.88 52 [98,] 3.92 56 [99,] 3.96 50 [100,] 4.00 46 [101,] 4.04 45 [102,] 4.08 69 [103,] 4.12 66 [104,] 4.16 73 [105,] 4.20 70 [106,] 4.24 55 [107,] 4.28 73 [108,] 4.32 60 [109,] 4.36 61 [110,] 4.40 60 [111,] 4.44 74 [112,] 4.48 63 [113,] 4.52 49 [114,] 4.56 47 [115,] 4.60 63 [116,] 4.64 50 [117,] 4.68 62 [118,] 4.72 48 [119,] 4.76 70 [120,] 4.80 49 [121,] 4.84 61 [122,] 4.88 64 [123,] 4.92 60 [124,] 4.96 52 [125,] 5.00 51 [126,] 5.04 59 [127,] 5.08 60 [128,] 5.12 69 [129,] 5.16 71 [130,] 5.20 67 [131,] 5.24 63 [132,] 5.28 59 [133,] 5.32 44 [134,] 5.36 48 [135,] 5.40 47 [136,] 5.44 71 [137,] 5.48 50 [138,] 5.52 75 [139,] 5.56 63 [140,] 5.60 51 [141,] 5.64 57 [142,] 5.68 48 [143,] 5.72 63 [144,] 5.76 60 [145,] 5.80 50 [146,] 5.84 74 [147,] 5.88 64 [148,] 5.92 47 [149,] 5.96 54 [150,] 6.00 57 [151,] 6.04 69 [152,] 6.08 48 [153,] 6.12 66 [154,] 6.16 77 [155,] 6.20 41 [156,] 6.24 47 [157,] 6.28 47 [158,] 6.32 51 [159,] 6.36 73 [160,] 6.40 71 [161,] 6.44 61 [162,] 6.48 64 [163,] 6.52 45 [164,] 6.56 44 [165,] 6.60 62 [166,] 6.64 51 [167,] 6.68 52 [168,] 6.72 66 [169,] 6.76 62 [170,] 6.80 43 [171,] 6.84 59 [172,] 6.88 57 [173,] 6.92 48 [174,] 6.96 50 [175,] 7.00 55 [176,] 7.04 52 [177,] 7.08 55 [178,] 7.12 61 [179,] 7.16 54 [180,] 7.20 70 [181,] 7.24 41 [182,] 7.28 54 [183,] 7.32 75 [184,] 7.36 65 [185,] 7.40 61 [186,] 7.44 49 [187,] 7.48 51 [188,] 7.52 59 [189,] 7.56 64 [190,] 7.60 71 [191,] 7.64 55 [192,] 7.68 46 [193,] 7.72 47 [194,] 7.76 54 [195,] 7.80 72 [196,] 7.84 36 [197,] 7.88 36 [198,] 7.92 48 [199,] 7.96 58 [200,] 8.00 51 [201,] 8.04 61 [202,] 8.08 43 [203,] 8.12 54 [204,] 8.16 53 [205,] 8.20 36 [206,] 8.24 57 [207,] 8.28 71 [208,] 8.32 57 [209,] 8.36 54 [210,] 8.40 42 [211,] 8.44 39 [212,] 8.48 50 [213,] 8.52 58 [214,] 8.56 46 [215,] 8.60 43 [216,] 8.64 70 [217,] 8.68 37 [218,] 8.72 63 [219,] 8.76 59 [220,] 8.80 59 [221,] 8.84 58 [222,] 8.88 62 [223,] 8.92 62 [224,] 8.96 63 [225,] 9.00 52 [226,] 9.04 65 [227,] 9.08 66 [228,] 9.12 62 [229,] 9.16 55 [230,] 9.20 48 [231,] 9.24 42 [232,] 9.28 55 [233,] 9.32 66 [234,] 9.36 64 [235,] 9.40 43 [236,] 9.44 50 [237,] 9.48 57 [238,] 9.52 63 [239,] 9.56 62 [240,] 9.60 44 [241,] 9.64 50 [242,] 9.68 61 [243,] 9.72 47 [244,] 9.76 52 [245,] 9.80 46 [246,] 9.84 49 [247,] 9.88 50 [248,] 9.92 66 [249,] 9.96 57 [250,] 10.00 50 [251,] 10.04 42 [252,] 10.08 67 [253,] 10.12 51 [254,] 10.16 46 [255,] 10.20 47 [256,] 10.24 48 [257,] 10.28 34 [258,] 10.32 45 [259,] 10.36 44 [260,] 10.40 60 [261,] 10.44 54 [262,] 10.48 53 [263,] 10.52 48 [264,] 10.56 47 [265,] 10.60 54 [266,] 10.64 56 [267,] 10.68 60 [268,] 10.72 56 [269,] 10.76 58 [270,] 10.80 71 [271,] 10.84 49 [272,] 10.88 52 [273,] 10.92 59 [274,] 10.96 48 [275,] 11.00 41 [276,] 11.04 43 [277,] 11.08 44 [278,] 11.12 54 [279,] 11.16 49 [280,] 11.20 51 [281,] 11.24 65 [282,] 11.28 62 [283,] 11.32 57 [284,] 11.36 53 [285,] 11.40 43 [286,] 11.44 69 [287,] 11.48 47 [288,] 11.52 53 [289,] 11.56 47 [290,] 11.60 59 [291,] 11.64 58 [292,] 11.68 37 [293,] 11.72 57 [294,] 11.76 57 [295,] 11.80 60 [296,] 11.84 56 [297,] 11.88 57 [298,] 11.92 58 [299,] 11.96 53 [300,] 12.00 68 [301,] 12.04 38 [302,] 12.08 44 [303,] 12.12 48 [304,] 12.16 53 [305,] 12.20 60 [306,] 12.24 64 [307,] 12.28 45 [308,] 12.32 54 [309,] 12.36 58 [310,] 12.40 48 [311,] 12.44 49 [312,] 12.48 61 [313,] 12.52 54 [314,] 12.56 54 [315,] 12.60 55 [316,] 12.64 57 [317,] 12.68 55 [318,] 12.72 69 [319,] 12.76 45 [320,] 12.80 56 [321,] 12.84 48 [322,] 12.88 61 [323,] 12.92 55 [324,] 12.96 58 [325,] 13.00 55 [326,] 13.04 56 [327,] 13.08 64 [328,] 13.12 47 [329,] 13.16 56 [330,] 13.20 57 [331,] 13.24 41 [332,] 13.28 57 [333,] 13.32 28 [334,] 13.36 47 [335,] 13.40 44 [336,] 13.44 55 [337,] 13.48 63 [338,] 13.52 54 [339,] 13.56 65 [340,] 13.60 57 [341,] 13.64 66 [342,] 13.68 57 [343,] 13.72 56 [344,] 13.76 51 [345,] 13.80 40 [346,] 13.84 71 [347,] 13.88 48 [348,] 13.92 53 [349,] 13.96 50 [350,] 14.00 56 [351,] 14.04 53 [352,] 14.08 44 [353,] 14.12 44 [354,] 14.16 59 [355,] 14.20 70 [356,] 14.24 46 [357,] 14.28 41 [358,] 14.32 46 [359,] 14.36 60 [360,] 14.40 57 [361,] 14.44 49 [362,] 14.48 55 [363,] 14.52 61 [364,] 14.56 58 [365,] 14.60 59 [366,] 14.64 43 [367,] 14.68 43 [368,] 14.72 42 [369,] 14.76 68 [370,] 14.80 48 [371,] 14.84 54 [372,] 14.88 62 [373,] 14.92 57 [374,] 14.96 41 [375,] 15.00 44 [376,] 15.04 55 [377,] 15.08 62 [378,] 15.12 57 [379,] 15.16 64 [380,] 15.20 39 [381,] 15.24 44 [382,] 15.28 53 [383,] 15.32 44 [384,] 15.36 55 [385,] 15.40 54 [386,] 15.44 51 [387,] 15.48 57 [388,] 15.52 56 [389,] 15.56 62 [390,] 15.60 50 [391,] 15.64 52 [392,] 15.68 57 [393,] 15.72 65 [394,] 15.76 54 [395,] 15.80 57 [396,] 15.84 49 [397,] 15.88 48 [398,] 15.92 55 [399,] 15.96 50 [400,] 16.00 49 [401,] 16.04 60 [402,] 16.08 51 [403,] 16.12 45 [404,] 16.16 63 [405,] 16.20 64 [406,] 16.24 51 [407,] 16.28 53 [408,] 16.32 41 [409,] 16.36 49 [410,] 16.40 42 [411,] 16.44 58 [412,] 16.48 48 [413,] 16.52 43 [414,] 16.56 51 [415,] 16.60 50 [416,] 16.64 50 [417,] 16.68 63 [418,] 16.72 50 [419,] 16.76 49 [420,] 16.80 39 [421,] 16.84 46 [422,] 16.88 59 [423,] 16.92 39 [424,] 16.96 42 [425,] 17.00 50 [426,] 17.04 50 [427,] 17.08 55 [428,] 17.12 49 [429,] 17.16 48 [430,] 17.20 45 [431,] 17.24 67 [432,] 17.28 62 [433,] 17.32 39 [434,] 17.36 36 [435,] 17.40 53 [436,] 17.44 37 [437,] 17.48 28 [438,] 17.52 46 [439,] 17.56 53 [440,] 17.60 48 [441,] 17.64 58 [442,] 17.68 57 [443,] 17.72 38 [444,] 17.76 44 [445,] 17.80 50 [446,] 17.84 46 [447,] 17.88 46 [448,] 17.92 48 [449,] 17.96 47 [450,] 18.00 50 [451,] 18.04 56 [452,] 18.08 46 [453,] 18.12 47 [454,] 18.16 42 [455,] 18.20 53 [456,] 18.24 55 [457,] 18.28 61 [458,] 18.32 48 [459,] 18.36 47 [460,] 18.40 40 [461,] 18.44 49 [462,] 18.48 68 [463,] 18.52 52 [464,] 18.56 57 [465,] 18.60 57 [466,] 18.64 63 [467,] 18.68 42 [468,] 18.72 58 [469,] 18.76 60 [470,] 18.80 58 [471,] 18.84 52 [472,] 18.88 52 [473,] 18.92 48 [474,] 18.96 46 [475,] 19.00 52 [476,] 19.04 48 [477,] 19.08 50 [478,] 19.12 45 [479,] 19.16 49 [480,] 19.20 61 [481,] 19.24 56 [482,] 19.28 58 [483,] 19.32 51 [484,] 19.36 59 [485,] 19.40 60 [486,] 19.44 49 [487,] 19.48 50 [488,] 19.52 56 [489,] 19.56 58 [490,] 19.60 73 [491,] 19.64 42 [492,] 19.68 52 [493,] 19.72 49 [494,] 19.76 45 [495,] 19.80 55 [496,] 19.84 52 [497,] 19.88 60 [498,] 19.92 55 [499,] 19.96 45 [500,] 20.00 47 [501,] 20.04 49 [502,] 20.08 53 [503,] 20.12 53 [504,] 20.16 52 [505,] 20.20 60 [506,] 20.24 51 [507,] 20.28 69 [508,] 20.32 45 [509,] 20.36 42 [510,] 20.40 61 [511,] 20.44 65 [512,] 20.48 51 [513,] 20.52 58 [514,] 20.56 55 [515,] 20.60 43 [516,] 20.64 55 [517,] 20.68 46 [518,] 20.72 46 [519,] 20.76 54 [520,] 20.80 46 [521,] 20.84 43 [522,] 20.88 44 [523,] 20.92 46 [524,] 20.96 56 [525,] 21.00 34 [526,] 21.04 48 [527,] 21.08 55 [528,] 21.12 42 [529,] 21.16 40 [530,] 21.20 56 [531,] 21.24 49 [532,] 21.28 40 [533,] 21.32 59 [534,] 21.36 49 [535,] 21.40 42 [536,] 21.44 44 [537,] 21.48 29 [538,] 21.52 42 [539,] 21.56 57 [540,] 21.60 50 [541,] 21.64 57 [542,] 21.68 49 [543,] 21.72 48 [544,] 21.76 48 [545,] 21.80 39 [546,] 21.84 59 [547,] 21.88 57 [548,] 21.92 57 [549,] 21.96 55 [550,] 22.00 57 [551,] 22.04 46 [552,] 22.08 48 [553,] 22.12 61 [554,] 22.16 59 [555,] 22.20 42 [556,] 22.24 60 [557,] 22.28 44 [558,] 22.32 59 [559,] 22.36 57 [560,] 22.40 40 [561,] 22.44 50 [562,] 22.48 39 [563,] 22.52 64 [564,] 22.56 49 [565,] 22.60 65 [566,] 22.64 55 [567,] 22.68 50 [568,] 22.72 43 [569,] 22.76 54 [570,] 22.80 71 [571,] 22.84 51 [572,] 22.88 56 [573,] 22.92 32 [574,] 22.96 35 [575,] 23.00 52 [576,] 23.04 56 [577,] 23.08 61 [578,] 23.12 35 [579,] 23.16 60 [580,] 23.20 45 [581,] 23.24 35 [582,] 23.28 52 [583,] 23.32 48 [584,] 23.36 46 [585,] 23.40 52 [586,] 23.44 70 [587,] 23.48 47 [588,] 23.52 69 [589,] 23.56 46 [590,] 23.60 61 [591,] 23.64 52 [592,] 23.68 46 [593,] 23.72 35 [594,] 23.76 47 [595,] 23.80 41 [596,] 23.84 63 [597,] 23.88 58 [598,] 23.92 46 [599,] 23.96 42 [600,] 24.00 44 [601,] 24.04 59 [602,] 24.08 56 [603,] 24.12 45 [604,] 24.16 41 [605,] 24.20 46 [606,] 24.24 49 [607,] 24.28 55 [608,] 24.32 53 [609,] 24.36 45 [610,] 24.40 55 [611,] 24.44 51 [612,] 24.48 57 [613,] 24.52 52 [614,] 24.56 56 [615,] 24.60 55 [616,] 24.64 56 [617,] 24.68 51 [618,] 24.72 65 [619,] 24.76 58 [620,] 24.80 58 [621,] 24.84 45 [622,] 24.88 51 [623,] 24.92 42 [624,] 24.96 56 [625,] 25.00 62 [626,] 25.04 69 [627,] 25.08 49 [628,] 25.12 65 [629,] 25.16 36 [630,] 25.20 59 [631,] 25.24 56 [632,] 25.28 45 [633,] 25.32 54 [634,] 25.36 49 [635,] 25.40 62 [636,] 25.44 52 [637,] 25.48 52 [638,] 25.52 48 [639,] 25.56 43 [640,] 25.60 47 [641,] 25.64 64 [642,] 25.68 43 [643,] 25.72 47 [644,] 25.76 62 [645,] 25.80 51 [646,] 25.84 54 [647,] 25.88 51 [648,] 25.92 48 [649,] 25.96 63 [650,] 26.00 49 [651,] 26.04 41 [652,] 26.08 51 [653,] 26.12 53 [654,] 26.16 47 [655,] 26.20 64 [656,] 26.24 51 [657,] 26.28 27 [658,] 26.32 35 [659,] 26.36 48 [660,] 26.40 59 [661,] 26.44 44 [662,] 26.48 65 [663,] 26.52 51 [664,] 26.56 41 [665,] 26.60 55 [666,] 26.64 46 [667,] 26.68 53 [668,] 26.72 49 [669,] 26.76 60 [670,] 26.80 52 [671,] 26.84 57 [672,] 26.88 32 [673,] 26.92 39 [674,] 26.96 44 [675,] 27.00 57 [676,] 27.04 44 [677,] 27.08 62 [678,] 27.12 42 [679,] 27.16 43 [680,] 27.20 43 [681,] 27.24 41 [682,] 27.28 54 [683,] 27.32 35 [684,] 27.36 65 [685,] 27.40 44 [686,] 27.44 41 [687,] 27.48 47 [688,] 27.52 48 [689,] 27.56 47 [690,] 27.60 48 [691,] 27.64 57 [692,] 27.68 57 [693,] 27.72 59 [694,] 27.76 63 [695,] 27.80 47 [696,] 27.84 55 [697,] 27.88 51 [698,] 27.92 45 [699,] 27.96 63 [700,] 28.00 46 [701,] 28.04 50 [702,] 28.08 45 [703,] 28.12 37 [704,] 28.16 55 [705,] 28.20 59 [706,] 28.24 46 [707,] 28.28 53 [708,] 28.32 43 [709,] 28.36 29 [710,] 28.40 49 [711,] 28.44 55 [712,] 28.48 46 [713,] 28.52 51 [714,] 28.56 49 [715,] 28.60 49 [716,] 28.64 40 [717,] 28.68 47 [718,] 28.72 36 [719,] 28.76 46 [720,] 28.80 54 [721,] 28.84 46 [722,] 28.88 70 [723,] 28.92 47 [724,] 28.96 49 [725,] 29.00 44 [726,] 29.04 36 [727,] 29.08 41 [728,] 29.12 52 [729,] 29.16 52 [730,] 29.20 51 [731,] 29.24 44 [732,] 29.28 45 [733,] 29.32 46 [734,] 29.36 45 [735,] 29.40 56 [736,] 29.44 46 [737,] 29.48 41 [738,] 29.52 50 [739,] 29.56 53 [740,] 29.60 48 [741,] 29.64 46 [742,] 29.68 52 [743,] 29.72 51 [744,] 29.76 50 [745,] 29.80 50 [746,] 29.84 45 [747,] 29.88 44 [748,] 29.92 56 [749,] 29.96 55 [750,] 30.00 36 [751,] 30.04 51 [752,] 30.08 41 [753,] 30.12 53 [754,] 30.16 56 [755,] 30.20 45 [756,] 30.24 64 [757,] 30.28 40 [758,] 30.32 46 [759,] 30.36 52 [760,] 30.40 55 [761,] 30.44 52 [762,] 30.48 34 [763,] 30.52 42 [764,] 30.56 57 [765,] 30.60 51 [766,] 30.64 49 [767,] 30.68 43 [768,] 30.72 57 [769,] 30.76 47 [770,] 30.80 54 [771,] 30.84 67 [772,] 30.88 48 [773,] 30.92 32 [774,] 30.96 61 [775,] 31.00 49 [776,] 31.04 43 [777,] 31.08 55 [778,] 31.12 38 [779,] 31.16 47 [780,] 31.20 42 [781,] 31.24 52 [782,] 31.28 69 [783,] 31.32 57 [784,] 31.36 48 [785,] 31.40 44 [786,] 31.44 60 [787,] 31.48 45 [788,] 31.52 48 [789,] 31.56 58 [790,] 31.60 45 [791,] 31.64 60 [792,] 31.68 43 [793,] 31.72 38 [794,] 31.76 61 [795,] 31.80 35 [796,] 31.84 67 [797,] 31.88 67 [798,] 31.92 51 [799,] 31.96 55 [800,] 32.00 45 [801,] 32.04 44 [802,] 32.08 43 [803,] 32.12 49 [804,] 32.16 55 [805,] 32.20 43 [806,] 32.24 49 [807,] 32.28 48 [808,] 32.32 42 [809,] 32.36 47 [810,] 32.40 42 [811,] 32.44 47 [812,] 32.48 48 [813,] 32.52 44 [814,] 32.56 42 [815,] 32.60 40 [816,] 32.64 55 [817,] 32.68 69 [818,] 32.72 40 [819,] 32.76 45 [820,] 32.80 38 [821,] 32.84 31 [822,] 32.88 48 [823,] 32.92 53 [824,] 32.96 44 [825,] 33.00 56 [826,] 33.04 44 [827,] 33.08 46 [828,] 33.12 48 [829,] 33.16 43 [830,] 33.20 43 [831,] 33.24 67 [832,] 33.28 44 [833,] 33.32 61 [834,] 33.36 39 [835,] 33.40 59 [836,] 33.44 27 [837,] 33.48 49 [838,] 33.52 51 [839,] 33.56 42 [840,] 33.60 48 [841,] 33.64 36 [842,] 33.68 44 [843,] 33.72 38 [844,] 33.76 39 [845,] 33.80 52 [846,] 33.84 48 [847,] 33.88 53 [848,] 33.92 53 [849,] 33.96 40 [850,] 34.00 41 [851,] 34.04 51 [852,] 34.08 46 [853,] 34.12 45 [854,] 34.16 59 [855,] 34.20 36 [856,] 34.24 49 [857,] 34.28 48 [858,] 34.32 42 [859,] 34.36 45 [860,] 34.40 52 [861,] 34.44 41 [862,] 34.48 36 [863,] 34.52 39 [864,] 34.56 34 [865,] 34.60 49 [866,] 34.64 57 [867,] 34.68 50 [868,] 34.72 51 [869,] 34.76 36 [870,] 34.80 43 [871,] 34.84 31 [872,] 34.88 34 [873,] 34.92 51 [874,] 34.96 47 [875,] 35.00 69 [876,] 35.04 48 [877,] 35.08 41 [878,] 35.12 59 [879,] 35.16 55 [880,] 35.20 39 [881,] 35.24 54 [882,] 35.28 38 [883,] 35.32 58 [884,] 35.36 44 [885,] 35.40 52 [886,] 35.44 47 [887,] 35.48 47 [888,] 35.52 54 [889,] 35.56 40 [890,] 35.60 42 [891,] 35.64 40 [892,] 35.68 47 [893,] 35.72 55 [894,] 35.76 63 [895,] 35.80 30 [896,] 35.84 44 [897,] 35.88 42 [898,] 35.92 45 [899,] 35.96 54 [900,] 36.00 39 [901,] 36.04 47 [902,] 36.08 41 [903,] 36.12 58 [904,] 36.16 53 [905,] 36.20 56 [906,] 36.24 62 [907,] 36.28 37 [908,] 36.32 53 [909,] 36.36 52 [910,] 36.40 57 [911,] 36.44 49 [912,] 36.48 40 [913,] 36.52 45 [914,] 36.56 43 [915,] 36.60 57 [916,] 36.64 44 [917,] 36.68 46 [918,] 36.72 43 [919,] 36.76 59 [920,] 36.80 45 [921,] 36.84 52 [922,] 36.88 55 [923,] 36.92 44 [924,] 36.96 46 [925,] 37.00 47 [926,] 37.04 50 [927,] 37.08 55 [928,] 37.12 41 [929,] 37.16 32 [930,] 37.20 43 [931,] 37.24 42 [932,] 37.28 41 [933,] 37.32 54 [934,] 37.36 54 [935,] 37.40 51 [936,] 37.44 58 [937,] 37.48 48 [938,] 37.52 48 [939,] 37.56 37 [940,] 37.60 47 [941,] 37.64 55 [942,] 37.68 39 [943,] 37.72 57 [944,] 37.76 48 [945,] 37.80 42 [946,] 37.84 51 [947,] 37.88 35 [948,] 37.92 42 [949,] 37.96 37 [950,] 38.00 45 [951,] 38.04 41 [952,] 38.08 39 [953,] 38.12 44 [954,] 38.16 37 [955,] 38.20 47 [956,] 38.24 50 [957,] 38.28 54 [958,] 38.32 47 [959,] 38.36 35 [960,] 38.40 43 [961,] 38.44 60 [962,] 38.48 43 [963,] 38.52 35 [964,] 38.56 47 [965,] 38.60 59 [966,] 38.64 43 [967,] 38.68 54 [968,] 38.72 45 [969,] 38.76 62 [970,] 38.80 38 [971,] 38.84 54 [972,] 38.88 61 [973,] 38.92 49 [974,] 38.96 50 [975,] 39.00 50 [976,] 39.04 41 [977,] 39.08 41 [978,] 39.12 36 [979,] 39.16 42 [980,] 39.20 59 [981,] 39.24 51 [982,] 39.28 49 [983,] 39.32 48 [984,] 39.36 39 [985,] 39.40 47 [986,] 39.44 54 [987,] 39.48 42 [988,] 39.52 40 [989,] 39.56 43 [990,] 39.60 47 [991,] 39.64 52 [992,] 39.68 33 [993,] 39.72 54 [994,] 39.76 34 [995,] 39.80 54 [996,] 39.84 50 [997,] 39.88 54 [998,] 39.92 54 [999,] 39.96 46 [1000,] 40.00 48 $`27_TL (PMT)` [,1] [,2] [1,] 0.64 0 [2,] 1.28 5 [3,] 1.92 1 [4,] 2.56 2 [5,] 3.20 4 [6,] 3.84 2 [7,] 4.48 4 [8,] 5.12 3 [9,] 5.76 3 [10,] 6.40 4 [11,] 7.04 14 [12,] 7.68 5 [13,] 8.32 7 [14,] 8.96 10 [15,] 9.60 5 [16,] 10.24 5 [17,] 10.88 11 [18,] 11.52 1 [19,] 12.16 0 [20,] 12.80 6 [21,] 13.44 6 [22,] 14.08 7 [23,] 14.72 3 [24,] 15.36 4 [25,] 16.00 2 [26,] 16.64 2 [27,] 17.28 9 [28,] 17.92 5 [29,] 18.56 3 [30,] 19.20 0 [31,] 19.84 7 [32,] 20.48 5 [33,] 21.12 5 [34,] 21.76 0 [35,] 22.40 4 [36,] 23.04 7 [37,] 23.68 3 [38,] 24.32 6 [39,] 24.96 3 [40,] 25.60 9 [41,] 26.24 3 [42,] 26.88 2 [43,] 27.52 4 [44,] 28.16 4 [45,] 28.80 1 [46,] 29.44 2 [47,] 30.08 29 [48,] 30.72 5 [49,] 31.36 5 [50,] 32.00 1 [51,] 32.64 5 [52,] 33.28 5 [53,] 33.92 3 [54,] 34.56 3 [55,] 35.20 3 [56,] 35.84 0 [57,] 36.48 3 [58,] 37.12 2 [59,] 37.76 2 [60,] 38.40 3 [61,] 39.04 6 [62,] 39.68 0 [63,] 40.32 11 [64,] 40.96 8 [65,] 41.60 9 [66,] 42.24 1 [67,] 42.88 1 [68,] 43.52 7 [69,] 44.16 14 [70,] 44.80 9 [71,] 45.44 3 [72,] 46.08 0 [73,] 46.72 3 [74,] 47.36 2 [75,] 48.00 1 [76,] 48.64 4 [77,] 49.28 8 [78,] 49.92 3 [79,] 50.56 12 [80,] 51.20 9 [81,] 51.84 5 [82,] 52.48 4 [83,] 53.12 9 [84,] 53.76 4 [85,] 54.40 6 [86,] 55.04 8 [87,] 55.68 8 [88,] 56.32 14 [89,] 56.96 8 [90,] 57.60 6 [91,] 58.24 3 [92,] 58.88 11 [93,] 59.52 12 [94,] 60.16 9 [95,] 60.80 9 [96,] 61.44 16 [97,] 62.08 23 [98,] 62.72 13 [99,] 63.36 16 [100,] 64.00 19 [101,] 64.64 22 [102,] 65.28 20 [103,] 65.92 17 [104,] 66.56 19 [105,] 67.20 32 [106,] 67.84 25 [107,] 68.48 23 [108,] 69.12 23 [109,] 69.76 21 [110,] 70.40 29 [111,] 71.04 31 [112,] 71.68 46 [113,] 72.32 50 [114,] 72.96 23 [115,] 73.60 35 [116,] 74.24 31 [117,] 74.88 52 [118,] 75.52 37 [119,] 76.16 38 [120,] 76.80 54 [121,] 77.44 41 [122,] 78.08 57 [123,] 78.72 56 [124,] 79.36 67 [125,] 80.00 75 [126,] 80.64 57 [127,] 81.28 80 [128,] 81.92 94 [129,] 82.56 76 [130,] 83.20 68 [131,] 83.84 110 [132,] 84.48 86 [133,] 85.12 95 [134,] 85.76 105 [135,] 86.40 121 [136,] 87.04 114 [137,] 87.68 130 [138,] 88.32 129 [139,] 88.96 141 [140,] 89.60 136 [141,] 90.24 148 [142,] 90.88 141 [143,] 91.52 155 [144,] 92.16 153 [145,] 92.80 154 [146,] 93.44 145 [147,] 94.08 176 [148,] 94.72 181 [149,] 95.36 198 [150,] 96.00 199 [151,] 96.64 204 [152,] 97.28 217 [153,] 97.92 203 [154,] 98.56 245 [155,] 99.20 190 [156,] 99.84 240 [157,] 100.48 215 [158,] 101.12 251 [159,] 101.76 233 [160,] 102.40 246 [161,] 103.04 263 [162,] 103.68 257 [163,] 104.32 266 [164,] 104.96 300 [165,] 105.60 268 [166,] 106.24 245 [167,] 106.88 264 [168,] 107.52 242 [169,] 108.16 264 [170,] 108.80 238 [171,] 109.44 269 [172,] 110.08 256 [173,] 110.72 232 [174,] 111.36 219 [175,] 112.00 235 [176,] 112.64 218 [177,] 113.28 201 [178,] 113.92 205 [179,] 114.56 178 [180,] 115.20 185 [181,] 115.84 172 [182,] 116.48 201 [183,] 117.12 147 [184,] 117.76 173 [185,] 118.40 158 [186,] 119.04 172 [187,] 119.68 155 [188,] 120.32 117 [189,] 120.96 141 [190,] 121.60 79 [191,] 122.24 111 [192,] 122.88 104 [193,] 123.52 94 [194,] 124.16 105 [195,] 124.80 89 [196,] 125.44 76 [197,] 126.08 87 [198,] 126.72 86 [199,] 127.36 87 [200,] 128.00 82 [201,] 128.64 92 [202,] 129.28 74 [203,] 129.92 88 [204,] 130.56 111 [205,] 131.20 71 [206,] 131.84 98 [207,] 132.48 71 [208,] 133.12 80 [209,] 133.76 80 [210,] 134.40 92 [211,] 135.04 78 [212,] 135.68 101 [213,] 136.32 93 [214,] 136.96 93 [215,] 137.60 76 [216,] 138.24 75 [217,] 138.88 84 [218,] 139.52 82 [219,] 140.16 94 [220,] 140.80 92 [221,] 141.44 93 [222,] 142.08 89 [223,] 142.72 95 [224,] 143.36 101 [225,] 144.00 87 [226,] 144.64 80 [227,] 145.28 114 [228,] 145.92 96 [229,] 146.56 78 [230,] 147.20 91 [231,] 147.84 120 [232,] 148.48 95 [233,] 149.12 81 [234,] 149.76 82 [235,] 150.40 75 [236,] 151.04 69 [237,] 151.68 82 [238,] 152.32 92 [239,] 152.96 89 [240,] 153.60 102 [241,] 154.24 75 [242,] 154.88 90 [243,] 155.52 64 [244,] 156.16 80 [245,] 156.80 74 [246,] 157.44 70 [247,] 158.08 84 [248,] 158.72 96 [249,] 159.36 91 [250,] 160.00 68 $`28_OSL (PMT)` [,1] [,2] [1,] 0.04 3334 [2,] 0.08 2773 [3,] 0.12 2460 [4,] 0.16 2209 [5,] 0.20 1924 [6,] 0.24 1594 [7,] 0.28 1450 [8,] 0.32 1260 [9,] 0.36 1116 [10,] 0.40 1029 [11,] 0.44 962 [12,] 0.48 759 [13,] 0.52 717 [14,] 0.56 666 [15,] 0.60 592 [16,] 0.64 488 [17,] 0.68 485 [18,] 0.72 431 [19,] 0.76 423 [20,] 0.80 384 [21,] 0.84 380 [22,] 0.88 345 [23,] 0.92 300 [24,] 0.96 282 [25,] 1.00 236 [26,] 1.04 229 [27,] 1.08 248 [28,] 1.12 211 [29,] 1.16 203 [30,] 1.20 215 [31,] 1.24 212 [32,] 1.28 189 [33,] 1.32 185 [34,] 1.36 199 [35,] 1.40 170 [36,] 1.44 171 [37,] 1.48 137 [38,] 1.52 154 [39,] 1.56 189 [40,] 1.60 150 [41,] 1.64 150 [42,] 1.68 166 [43,] 1.72 145 [44,] 1.76 129 [45,] 1.80 153 [46,] 1.84 116 [47,] 1.88 134 [48,] 1.92 151 [49,] 1.96 149 [50,] 2.00 121 [51,] 2.04 136 [52,] 2.08 119 [53,] 2.12 128 [54,] 2.16 139 [55,] 2.20 112 [56,] 2.24 125 [57,] 2.28 125 [58,] 2.32 140 [59,] 2.36 112 [60,] 2.40 107 [61,] 2.44 120 [62,] 2.48 96 [63,] 2.52 112 [64,] 2.56 104 [65,] 2.60 137 [66,] 2.64 98 [67,] 2.68 107 [68,] 2.72 109 [69,] 2.76 101 [70,] 2.80 99 [71,] 2.84 101 [72,] 2.88 108 [73,] 2.92 111 [74,] 2.96 117 [75,] 3.00 117 [76,] 3.04 98 [77,] 3.08 107 [78,] 3.12 98 [79,] 3.16 105 [80,] 3.20 108 [81,] 3.24 90 [82,] 3.28 111 [83,] 3.32 94 [84,] 3.36 105 [85,] 3.40 103 [86,] 3.44 118 [87,] 3.48 83 [88,] 3.52 96 [89,] 3.56 128 [90,] 3.60 104 [91,] 3.64 97 [92,] 3.68 91 [93,] 3.72 84 [94,] 3.76 103 [95,] 3.80 81 [96,] 3.84 93 [97,] 3.88 88 [98,] 3.92 105 [99,] 3.96 71 [100,] 4.00 98 [101,] 4.04 109 [102,] 4.08 74 [103,] 4.12 119 [104,] 4.16 106 [105,] 4.20 117 [106,] 4.24 101 [107,] 4.28 87 [108,] 4.32 90 [109,] 4.36 84 [110,] 4.40 83 [111,] 4.44 86 [112,] 4.48 98 [113,] 4.52 99 [114,] 4.56 90 [115,] 4.60 81 [116,] 4.64 92 [117,] 4.68 91 [118,] 4.72 81 [119,] 4.76 77 [120,] 4.80 108 [121,] 4.84 86 [122,] 4.88 93 [123,] 4.92 96 [124,] 4.96 99 [125,] 5.00 106 [126,] 5.04 83 [127,] 5.08 91 [128,] 5.12 81 [129,] 5.16 95 [130,] 5.20 98 [131,] 5.24 70 [132,] 5.28 104 [133,] 5.32 78 [134,] 5.36 85 [135,] 5.40 83 [136,] 5.44 75 [137,] 5.48 82 [138,] 5.52 57 [139,] 5.56 83 [140,] 5.60 82 [141,] 5.64 82 [142,] 5.68 70 [143,] 5.72 81 [144,] 5.76 88 [145,] 5.80 90 [146,] 5.84 98 [147,] 5.88 85 [148,] 5.92 80 [149,] 5.96 94 [150,] 6.00 94 [151,] 6.04 86 [152,] 6.08 72 [153,] 6.12 90 [154,] 6.16 87 [155,] 6.20 81 [156,] 6.24 85 [157,] 6.28 76 [158,] 6.32 66 [159,] 6.36 80 [160,] 6.40 77 [161,] 6.44 84 [162,] 6.48 100 [163,] 6.52 85 [164,] 6.56 81 [165,] 6.60 79 [166,] 6.64 81 [167,] 6.68 79 [168,] 6.72 85 [169,] 6.76 72 [170,] 6.80 82 [171,] 6.84 78 [172,] 6.88 69 [173,] 6.92 73 [174,] 6.96 62 [175,] 7.00 79 [176,] 7.04 62 [177,] 7.08 97 [178,] 7.12 89 [179,] 7.16 97 [180,] 7.20 71 [181,] 7.24 73 [182,] 7.28 92 [183,] 7.32 89 [184,] 7.36 78 [185,] 7.40 65 [186,] 7.44 93 [187,] 7.48 96 [188,] 7.52 75 [189,] 7.56 83 [190,] 7.60 83 [191,] 7.64 107 [192,] 7.68 98 [193,] 7.72 67 [194,] 7.76 63 [195,] 7.80 84 [196,] 7.84 78 [197,] 7.88 93 [198,] 7.92 70 [199,] 7.96 84 [200,] 8.00 64 [201,] 8.04 80 [202,] 8.08 97 [203,] 8.12 92 [204,] 8.16 84 [205,] 8.20 72 [206,] 8.24 82 [207,] 8.28 63 [208,] 8.32 76 [209,] 8.36 99 [210,] 8.40 74 [211,] 8.44 107 [212,] 8.48 75 [213,] 8.52 90 [214,] 8.56 70 [215,] 8.60 71 [216,] 8.64 71 [217,] 8.68 75 [218,] 8.72 76 [219,] 8.76 87 [220,] 8.80 71 [221,] 8.84 76 [222,] 8.88 68 [223,] 8.92 90 [224,] 8.96 85 [225,] 9.00 88 [226,] 9.04 83 [227,] 9.08 78 [228,] 9.12 76 [229,] 9.16 80 [230,] 9.20 60 [231,] 9.24 85 [232,] 9.28 65 [233,] 9.32 76 [234,] 9.36 56 [235,] 9.40 68 [236,] 9.44 92 [237,] 9.48 80 [238,] 9.52 77 [239,] 9.56 81 [240,] 9.60 62 [241,] 9.64 68 [242,] 9.68 57 [243,] 9.72 77 [244,] 9.76 86 [245,] 9.80 77 [246,] 9.84 61 [247,] 9.88 68 [248,] 9.92 88 [249,] 9.96 62 [250,] 10.00 73 [251,] 10.04 78 [252,] 10.08 71 [253,] 10.12 89 [254,] 10.16 81 [255,] 10.20 68 [256,] 10.24 68 [257,] 10.28 71 [258,] 10.32 61 [259,] 10.36 66 [260,] 10.40 77 [261,] 10.44 65 [262,] 10.48 75 [263,] 10.52 80 [264,] 10.56 67 [265,] 10.60 68 [266,] 10.64 61 [267,] 10.68 66 [268,] 10.72 77 [269,] 10.76 66 [270,] 10.80 69 [271,] 10.84 86 [272,] 10.88 78 [273,] 10.92 62 [274,] 10.96 52 [275,] 11.00 60 [276,] 11.04 63 [277,] 11.08 76 [278,] 11.12 67 [279,] 11.16 85 [280,] 11.20 64 [281,] 11.24 69 [282,] 11.28 67 [283,] 11.32 71 [284,] 11.36 61 [285,] 11.40 60 [286,] 11.44 78 [287,] 11.48 59 [288,] 11.52 72 [289,] 11.56 72 [290,] 11.60 82 [291,] 11.64 78 [292,] 11.68 78 [293,] 11.72 84 [294,] 11.76 78 [295,] 11.80 61 [296,] 11.84 59 [297,] 11.88 53 [298,] 11.92 71 [299,] 11.96 64 [300,] 12.00 69 [301,] 12.04 65 [302,] 12.08 72 [303,] 12.12 81 [304,] 12.16 64 [305,] 12.20 67 [306,] 12.24 77 [307,] 12.28 71 [308,] 12.32 61 [309,] 12.36 53 [310,] 12.40 85 [311,] 12.44 78 [312,] 12.48 66 [313,] 12.52 60 [314,] 12.56 56 [315,] 12.60 59 [316,] 12.64 74 [317,] 12.68 75 [318,] 12.72 82 [319,] 12.76 79 [320,] 12.80 76 [321,] 12.84 82 [322,] 12.88 53 [323,] 12.92 71 [324,] 12.96 68 [325,] 13.00 74 [326,] 13.04 56 [327,] 13.08 74 [328,] 13.12 77 [329,] 13.16 66 [330,] 13.20 51 [331,] 13.24 61 [332,] 13.28 83 [333,] 13.32 79 [334,] 13.36 72 [335,] 13.40 57 [336,] 13.44 58 [337,] 13.48 60 [338,] 13.52 74 [339,] 13.56 89 [340,] 13.60 57 [341,] 13.64 99 [342,] 13.68 76 [343,] 13.72 64 [344,] 13.76 63 [345,] 13.80 67 [346,] 13.84 64 [347,] 13.88 60 [348,] 13.92 68 [349,] 13.96 81 [350,] 14.00 75 [351,] 14.04 74 [352,] 14.08 53 [353,] 14.12 63 [354,] 14.16 70 [355,] 14.20 71 [356,] 14.24 72 [357,] 14.28 73 [358,] 14.32 63 [359,] 14.36 70 [360,] 14.40 72 [361,] 14.44 78 [362,] 14.48 65 [363,] 14.52 72 [364,] 14.56 74 [365,] 14.60 83 [366,] 14.64 65 [367,] 14.68 66 [368,] 14.72 59 [369,] 14.76 77 [370,] 14.80 50 [371,] 14.84 57 [372,] 14.88 81 [373,] 14.92 61 [374,] 14.96 63 [375,] 15.00 75 [376,] 15.04 76 [377,] 15.08 57 [378,] 15.12 73 [379,] 15.16 70 [380,] 15.20 54 [381,] 15.24 85 [382,] 15.28 74 [383,] 15.32 63 [384,] 15.36 74 [385,] 15.40 85 [386,] 15.44 93 [387,] 15.48 60 [388,] 15.52 62 [389,] 15.56 61 [390,] 15.60 74 [391,] 15.64 64 [392,] 15.68 72 [393,] 15.72 62 [394,] 15.76 53 [395,] 15.80 74 [396,] 15.84 84 [397,] 15.88 58 [398,] 15.92 58 [399,] 15.96 75 [400,] 16.00 66 [401,] 16.04 70 [402,] 16.08 60 [403,] 16.12 68 [404,] 16.16 69 [405,] 16.20 80 [406,] 16.24 56 [407,] 16.28 72 [408,] 16.32 52 [409,] 16.36 65 [410,] 16.40 63 [411,] 16.44 56 [412,] 16.48 65 [413,] 16.52 88 [414,] 16.56 73 [415,] 16.60 83 [416,] 16.64 79 [417,] 16.68 77 [418,] 16.72 76 [419,] 16.76 69 [420,] 16.80 62 [421,] 16.84 62 [422,] 16.88 78 [423,] 16.92 56 [424,] 16.96 58 [425,] 17.00 74 [426,] 17.04 77 [427,] 17.08 73 [428,] 17.12 60 [429,] 17.16 68 [430,] 17.20 63 [431,] 17.24 77 [432,] 17.28 68 [433,] 17.32 86 [434,] 17.36 55 [435,] 17.40 69 [436,] 17.44 70 [437,] 17.48 55 [438,] 17.52 58 [439,] 17.56 55 [440,] 17.60 58 [441,] 17.64 80 [442,] 17.68 82 [443,] 17.72 59 [444,] 17.76 53 [445,] 17.80 56 [446,] 17.84 74 [447,] 17.88 48 [448,] 17.92 52 [449,] 17.96 85 [450,] 18.00 51 [451,] 18.04 76 [452,] 18.08 66 [453,] 18.12 63 [454,] 18.16 63 [455,] 18.20 64 [456,] 18.24 73 [457,] 18.28 66 [458,] 18.32 59 [459,] 18.36 51 [460,] 18.40 60 [461,] 18.44 55 [462,] 18.48 62 [463,] 18.52 53 [464,] 18.56 62 [465,] 18.60 51 [466,] 18.64 69 [467,] 18.68 72 [468,] 18.72 47 [469,] 18.76 62 [470,] 18.80 51 [471,] 18.84 54 [472,] 18.88 86 [473,] 18.92 59 [474,] 18.96 64 [475,] 19.00 70 [476,] 19.04 75 [477,] 19.08 69 [478,] 19.12 81 [479,] 19.16 62 [480,] 19.20 70 [481,] 19.24 69 [482,] 19.28 52 [483,] 19.32 87 [484,] 19.36 52 [485,] 19.40 74 [486,] 19.44 74 [487,] 19.48 54 [488,] 19.52 53 [489,] 19.56 72 [490,] 19.60 48 [491,] 19.64 60 [492,] 19.68 62 [493,] 19.72 76 [494,] 19.76 67 [495,] 19.80 43 [496,] 19.84 66 [497,] 19.88 61 [498,] 19.92 62 [499,] 19.96 45 [500,] 20.00 58 [501,] 20.04 66 [502,] 20.08 55 [503,] 20.12 56 [504,] 20.16 75 [505,] 20.20 59 [506,] 20.24 59 [507,] 20.28 62 [508,] 20.32 49 [509,] 20.36 57 [510,] 20.40 63 [511,] 20.44 85 [512,] 20.48 51 [513,] 20.52 45 [514,] 20.56 57 [515,] 20.60 55 [516,] 20.64 59 [517,] 20.68 64 [518,] 20.72 58 [519,] 20.76 68 [520,] 20.80 66 [521,] 20.84 62 [522,] 20.88 62 [523,] 20.92 71 [524,] 20.96 54 [525,] 21.00 71 [526,] 21.04 56 [527,] 21.08 70 [528,] 21.12 53 [529,] 21.16 67 [530,] 21.20 65 [531,] 21.24 66 [532,] 21.28 49 [533,] 21.32 63 [534,] 21.36 57 [535,] 21.40 44 [536,] 21.44 71 [537,] 21.48 60 [538,] 21.52 87 [539,] 21.56 65 [540,] 21.60 57 [541,] 21.64 53 [542,] 21.68 64 [543,] 21.72 57 [544,] 21.76 72 [545,] 21.80 48 [546,] 21.84 55 [547,] 21.88 70 [548,] 21.92 59 [549,] 21.96 51 [550,] 22.00 75 [551,] 22.04 68 [552,] 22.08 59 [553,] 22.12 52 [554,] 22.16 82 [555,] 22.20 57 [556,] 22.24 77 [557,] 22.28 62 [558,] 22.32 70 [559,] 22.36 56 [560,] 22.40 106 [561,] 22.44 65 [562,] 22.48 42 [563,] 22.52 59 [564,] 22.56 64 [565,] 22.60 46 [566,] 22.64 58 [567,] 22.68 84 [568,] 22.72 57 [569,] 22.76 72 [570,] 22.80 62 [571,] 22.84 69 [572,] 22.88 67 [573,] 22.92 58 [574,] 22.96 67 [575,] 23.00 48 [576,] 23.04 64 [577,] 23.08 50 [578,] 23.12 63 [579,] 23.16 66 [580,] 23.20 55 [581,] 23.24 66 [582,] 23.28 64 [583,] 23.32 69 [584,] 23.36 52 [585,] 23.40 90 [586,] 23.44 52 [587,] 23.48 65 [588,] 23.52 62 [589,] 23.56 56 [590,] 23.60 60 [591,] 23.64 51 [592,] 23.68 61 [593,] 23.72 63 [594,] 23.76 52 [595,] 23.80 59 [596,] 23.84 59 [597,] 23.88 70 [598,] 23.92 68 [599,] 23.96 64 [600,] 24.00 60 [601,] 24.04 60 [602,] 24.08 66 [603,] 24.12 65 [604,] 24.16 53 [605,] 24.20 67 [606,] 24.24 48 [607,] 24.28 49 [608,] 24.32 51 [609,] 24.36 60 [610,] 24.40 46 [611,] 24.44 56 [612,] 24.48 63 [613,] 24.52 59 [614,] 24.56 57 [615,] 24.60 47 [616,] 24.64 49 [617,] 24.68 46 [618,] 24.72 58 [619,] 24.76 66 [620,] 24.80 80 [621,] 24.84 52 [622,] 24.88 60 [623,] 24.92 66 [624,] 24.96 62 [625,] 25.00 51 [626,] 25.04 81 [627,] 25.08 58 [628,] 25.12 64 [629,] 25.16 70 [630,] 25.20 67 [631,] 25.24 74 [632,] 25.28 53 [633,] 25.32 58 [634,] 25.36 70 [635,] 25.40 48 [636,] 25.44 64 [637,] 25.48 55 [638,] 25.52 66 [639,] 25.56 63 [640,] 25.60 47 [641,] 25.64 52 [642,] 25.68 78 [643,] 25.72 67 [644,] 25.76 68 [645,] 25.80 61 [646,] 25.84 70 [647,] 25.88 62 [648,] 25.92 53 [649,] 25.96 60 [650,] 26.00 46 [651,] 26.04 71 [652,] 26.08 49 [653,] 26.12 79 [654,] 26.16 66 [655,] 26.20 56 [656,] 26.24 76 [657,] 26.28 56 [658,] 26.32 60 [659,] 26.36 53 [660,] 26.40 70 [661,] 26.44 53 [662,] 26.48 62 [663,] 26.52 48 [664,] 26.56 46 [665,] 26.60 61 [666,] 26.64 57 [667,] 26.68 53 [668,] 26.72 59 [669,] 26.76 58 [670,] 26.80 66 [671,] 26.84 48 [672,] 26.88 69 [673,] 26.92 59 [674,] 26.96 58 [675,] 27.00 73 [676,] 27.04 64 [677,] 27.08 56 [678,] 27.12 43 [679,] 27.16 51 [680,] 27.20 58 [681,] 27.24 43 [682,] 27.28 70 [683,] 27.32 56 [684,] 27.36 66 [685,] 27.40 63 [686,] 27.44 59 [687,] 27.48 62 [688,] 27.52 76 [689,] 27.56 70 [690,] 27.60 62 [691,] 27.64 59 [692,] 27.68 61 [693,] 27.72 58 [694,] 27.76 46 [695,] 27.80 51 [696,] 27.84 59 [697,] 27.88 57 [698,] 27.92 47 [699,] 27.96 61 [700,] 28.00 54 [701,] 28.04 66 [702,] 28.08 56 [703,] 28.12 56 [704,] 28.16 68 [705,] 28.20 57 [706,] 28.24 52 [707,] 28.28 69 [708,] 28.32 37 [709,] 28.36 73 [710,] 28.40 77 [711,] 28.44 68 [712,] 28.48 64 [713,] 28.52 59 [714,] 28.56 58 [715,] 28.60 43 [716,] 28.64 58 [717,] 28.68 55 [718,] 28.72 50 [719,] 28.76 56 [720,] 28.80 55 [721,] 28.84 53 [722,] 28.88 69 [723,] 28.92 83 [724,] 28.96 55 [725,] 29.00 72 [726,] 29.04 59 [727,] 29.08 62 [728,] 29.12 54 [729,] 29.16 77 [730,] 29.20 43 [731,] 29.24 54 [732,] 29.28 65 [733,] 29.32 61 [734,] 29.36 45 [735,] 29.40 37 [736,] 29.44 73 [737,] 29.48 44 [738,] 29.52 52 [739,] 29.56 46 [740,] 29.60 60 [741,] 29.64 66 [742,] 29.68 65 [743,] 29.72 47 [744,] 29.76 64 [745,] 29.80 48 [746,] 29.84 57 [747,] 29.88 47 [748,] 29.92 44 [749,] 29.96 57 [750,] 30.00 55 [751,] 30.04 68 [752,] 30.08 44 [753,] 30.12 54 [754,] 30.16 54 [755,] 30.20 64 [756,] 30.24 71 [757,] 30.28 64 [758,] 30.32 59 [759,] 30.36 62 [760,] 30.40 56 [761,] 30.44 65 [762,] 30.48 70 [763,] 30.52 36 [764,] 30.56 73 [765,] 30.60 71 [766,] 30.64 50 [767,] 30.68 67 [768,] 30.72 73 [769,] 30.76 56 [770,] 30.80 65 [771,] 30.84 45 [772,] 30.88 57 [773,] 30.92 70 [774,] 30.96 56 [775,] 31.00 74 [776,] 31.04 51 [777,] 31.08 60 [778,] 31.12 59 [779,] 31.16 48 [780,] 31.20 52 [781,] 31.24 58 [782,] 31.28 63 [783,] 31.32 51 [784,] 31.36 55 [785,] 31.40 51 [786,] 31.44 51 [787,] 31.48 54 [788,] 31.52 54 [789,] 31.56 50 [790,] 31.60 52 [791,] 31.64 57 [792,] 31.68 55 [793,] 31.72 63 [794,] 31.76 64 [795,] 31.80 63 [796,] 31.84 61 [797,] 31.88 48 [798,] 31.92 79 [799,] 31.96 50 [800,] 32.00 56 [801,] 32.04 49 [802,] 32.08 60 [803,] 32.12 65 [804,] 32.16 49 [805,] 32.20 51 [806,] 32.24 60 [807,] 32.28 49 [808,] 32.32 55 [809,] 32.36 45 [810,] 32.40 63 [811,] 32.44 57 [812,] 32.48 81 [813,] 32.52 47 [814,] 32.56 56 [815,] 32.60 51 [816,] 32.64 49 [817,] 32.68 66 [818,] 32.72 69 [819,] 32.76 46 [820,] 32.80 63 [821,] 32.84 59 [822,] 32.88 65 [823,] 32.92 61 [824,] 32.96 62 [825,] 33.00 53 [826,] 33.04 63 [827,] 33.08 57 [828,] 33.12 76 [829,] 33.16 73 [830,] 33.20 61 [831,] 33.24 48 [832,] 33.28 71 [833,] 33.32 59 [834,] 33.36 41 [835,] 33.40 44 [836,] 33.44 52 [837,] 33.48 57 [838,] 33.52 76 [839,] 33.56 56 [840,] 33.60 65 [841,] 33.64 71 [842,] 33.68 56 [843,] 33.72 47 [844,] 33.76 70 [845,] 33.80 56 [846,] 33.84 59 [847,] 33.88 68 [848,] 33.92 70 [849,] 33.96 58 [850,] 34.00 33 [851,] 34.04 59 [852,] 34.08 56 [853,] 34.12 52 [854,] 34.16 63 [855,] 34.20 57 [856,] 34.24 62 [857,] 34.28 60 [858,] 34.32 64 [859,] 34.36 58 [860,] 34.40 42 [861,] 34.44 66 [862,] 34.48 78 [863,] 34.52 56 [864,] 34.56 61 [865,] 34.60 74 [866,] 34.64 62 [867,] 34.68 47 [868,] 34.72 78 [869,] 34.76 61 [870,] 34.80 60 [871,] 34.84 77 [872,] 34.88 52 [873,] 34.92 56 [874,] 34.96 67 [875,] 35.00 92 [876,] 35.04 52 [877,] 35.08 63 [878,] 35.12 50 [879,] 35.16 46 [880,] 35.20 62 [881,] 35.24 65 [882,] 35.28 58 [883,] 35.32 66 [884,] 35.36 59 [885,] 35.40 50 [886,] 35.44 51 [887,] 35.48 37 [888,] 35.52 68 [889,] 35.56 42 [890,] 35.60 70 [891,] 35.64 64 [892,] 35.68 52 [893,] 35.72 57 [894,] 35.76 77 [895,] 35.80 49 [896,] 35.84 57 [897,] 35.88 75 [898,] 35.92 51 [899,] 35.96 63 [900,] 36.00 51 [901,] 36.04 58 [902,] 36.08 55 [903,] 36.12 57 [904,] 36.16 46 [905,] 36.20 56 [906,] 36.24 57 [907,] 36.28 66 [908,] 36.32 57 [909,] 36.36 58 [910,] 36.40 50 [911,] 36.44 48 [912,] 36.48 52 [913,] 36.52 56 [914,] 36.56 59 [915,] 36.60 49 [916,] 36.64 55 [917,] 36.68 61 [918,] 36.72 66 [919,] 36.76 51 [920,] 36.80 66 [921,] 36.84 61 [922,] 36.88 52 [923,] 36.92 55 [924,] 36.96 54 [925,] 37.00 62 [926,] 37.04 53 [927,] 37.08 57 [928,] 37.12 57 [929,] 37.16 40 [930,] 37.20 58 [931,] 37.24 52 [932,] 37.28 66 [933,] 37.32 63 [934,] 37.36 66 [935,] 37.40 61 [936,] 37.44 49 [937,] 37.48 70 [938,] 37.52 63 [939,] 37.56 60 [940,] 37.60 52 [941,] 37.64 61 [942,] 37.68 72 [943,] 37.72 60 [944,] 37.76 50 [945,] 37.80 58 [946,] 37.84 64 [947,] 37.88 63 [948,] 37.92 70 [949,] 37.96 41 [950,] 38.00 74 [951,] 38.04 54 [952,] 38.08 54 [953,] 38.12 51 [954,] 38.16 68 [955,] 38.20 63 [956,] 38.24 50 [957,] 38.28 52 [958,] 38.32 82 [959,] 38.36 53 [960,] 38.40 59 [961,] 38.44 56 [962,] 38.48 45 [963,] 38.52 47 [964,] 38.56 52 [965,] 38.60 62 [966,] 38.64 62 [967,] 38.68 65 [968,] 38.72 78 [969,] 38.76 64 [970,] 38.80 64 [971,] 38.84 49 [972,] 38.88 54 [973,] 38.92 40 [974,] 38.96 74 [975,] 39.00 71 [976,] 39.04 62 [977,] 39.08 64 [978,] 39.12 72 [979,] 39.16 69 [980,] 39.20 78 [981,] 39.24 64 [982,] 39.28 83 [983,] 39.32 57 [984,] 39.36 54 [985,] 39.40 53 [986,] 39.44 69 [987,] 39.48 68 [988,] 39.52 40 [989,] 39.56 59 [990,] 39.60 56 [991,] 39.64 54 [992,] 39.68 50 [993,] 39.72 64 [994,] 39.76 63 [995,] 39.80 53 [996,] 39.84 55 [997,] 39.88 63 [998,] 39.92 65 [999,] 39.96 60 [1000,] 40.00 59 $`29_TL (PMT)` [,1] [,2] [1,] 0.884 4 [2,] 1.768 4 [3,] 2.652 7 [4,] 3.536 1 [5,] 4.420 10 [6,] 5.304 8 [7,] 6.188 3 [8,] 7.072 6 [9,] 7.956 5 [10,] 8.840 4 [11,] 9.724 5 [12,] 10.608 0 [13,] 11.492 5 [14,] 12.376 4 [15,] 13.260 6 [16,] 14.144 4 [17,] 15.028 3 [18,] 15.912 7 [19,] 16.796 1 [20,] 17.680 3 [21,] 18.564 0 [22,] 19.448 7 [23,] 20.332 6 [24,] 21.216 5 [25,] 22.100 6 [26,] 22.984 1 [27,] 23.868 14 [28,] 24.752 4 [29,] 25.636 1 [30,] 26.520 3 [31,] 27.404 1 [32,] 28.288 4 [33,] 29.172 4 [34,] 30.056 2 [35,] 30.940 7 [36,] 31.824 8 [37,] 32.708 4 [38,] 33.592 22 [39,] 34.476 4 [40,] 35.360 2 [41,] 36.244 9 [42,] 37.128 5 [43,] 38.012 10 [44,] 38.896 6 [45,] 39.780 7 [46,] 40.664 3 [47,] 41.548 1 [48,] 42.432 4 [49,] 43.316 11 [50,] 44.200 11 [51,] 45.084 19 [52,] 45.968 0 [53,] 46.852 12 [54,] 47.736 16 [55,] 48.620 6 [56,] 49.504 8 [57,] 50.388 2 [58,] 51.272 3 [59,] 52.156 5 [60,] 53.040 10 [61,] 53.924 5 [62,] 54.808 20 [63,] 55.692 6 [64,] 56.576 13 [65,] 57.460 7 [66,] 58.344 14 [67,] 59.228 7 [68,] 60.112 8 [69,] 60.996 18 [70,] 61.880 9 [71,] 62.764 13 [72,] 63.648 13 [73,] 64.532 7 [74,] 65.416 15 [75,] 66.300 17 [76,] 67.184 19 [77,] 68.068 26 [78,] 68.952 17 [79,] 69.836 18 [80,] 70.720 37 [81,] 71.604 47 [82,] 72.488 34 [83,] 73.372 26 [84,] 74.256 34 [85,] 75.140 42 [86,] 76.024 36 [87,] 76.908 39 [88,] 77.792 40 [89,] 78.676 46 [90,] 79.560 56 [91,] 80.444 49 [92,] 81.328 61 [93,] 82.212 61 [94,] 83.096 81 [95,] 83.980 70 [96,] 84.864 74 [97,] 85.748 88 [98,] 86.632 65 [99,] 87.516 103 [100,] 88.400 94 [101,] 89.284 120 [102,] 90.168 122 [103,] 91.052 110 [104,] 91.936 138 [105,] 92.820 146 [106,] 93.704 143 [107,] 94.588 118 [108,] 95.472 178 [109,] 96.356 168 [110,] 97.240 199 [111,] 98.124 209 [112,] 99.008 182 [113,] 99.892 160 [114,] 100.776 195 [115,] 101.660 174 [116,] 102.544 199 [117,] 103.428 222 [118,] 104.312 172 [119,] 105.196 245 [120,] 106.080 220 [121,] 106.964 256 [122,] 107.848 229 [123,] 108.732 217 [124,] 109.616 217 [125,] 110.500 263 [126,] 111.384 226 [127,] 112.268 188 [128,] 113.152 233 [129,] 114.036 258 [130,] 114.920 180 [131,] 115.804 168 [132,] 116.688 227 [133,] 117.572 177 [134,] 118.456 177 [135,] 119.340 157 [136,] 120.224 144 [137,] 121.108 165 [138,] 121.992 162 [139,] 122.876 116 [140,] 123.760 142 [141,] 124.644 151 [142,] 125.528 149 [143,] 126.412 139 [144,] 127.296 149 [145,] 128.180 121 [146,] 129.064 145 [147,] 129.948 175 [148,] 130.832 163 [149,] 131.716 144 [150,] 132.600 139 [151,] 133.484 189 [152,] 134.368 176 [153,] 135.252 175 [154,] 136.136 169 [155,] 137.020 178 [156,] 137.904 187 [157,] 138.788 149 [158,] 139.672 154 [159,] 140.556 157 [160,] 141.440 201 [161,] 142.324 205 [162,] 143.208 158 [163,] 144.092 184 [164,] 144.976 176 [165,] 145.860 183 [166,] 146.744 189 [167,] 147.628 185 [168,] 148.512 175 [169,] 149.396 170 [170,] 150.280 197 [171,] 151.164 163 [172,] 152.048 163 [173,] 152.932 158 [174,] 153.816 149 [175,] 154.700 167 [176,] 155.584 184 [177,] 156.468 157 [178,] 157.352 158 [179,] 158.236 201 [180,] 159.120 155 [181,] 160.004 143 [182,] 160.888 179 [183,] 161.772 132 [184,] 162.656 165 [185,] 163.540 162 [186,] 164.424 164 [187,] 165.308 183 [188,] 166.192 177 [189,] 167.076 180 [190,] 167.960 178 [191,] 168.844 155 [192,] 169.728 171 [193,] 170.612 165 [194,] 171.496 168 [195,] 172.380 155 [196,] 173.264 175 [197,] 174.148 152 [198,] 175.032 199 [199,] 175.916 162 [200,] 176.800 147 [201,] 177.684 194 [202,] 178.568 166 [203,] 179.452 152 [204,] 180.336 149 [205,] 181.220 153 [206,] 182.104 159 [207,] 182.988 163 [208,] 183.872 154 [209,] 184.756 183 [210,] 185.640 167 [211,] 186.524 154 [212,] 187.408 167 [213,] 188.292 148 [214,] 189.176 146 [215,] 190.060 154 [216,] 190.944 171 [217,] 191.828 164 [218,] 192.712 155 [219,] 193.596 162 [220,] 194.480 195 [221,] 195.364 210 [222,] 196.248 192 [223,] 197.132 212 [224,] 198.016 174 [225,] 198.900 185 [226,] 199.784 198 [227,] 200.668 192 [228,] 201.552 189 [229,] 202.436 197 [230,] 203.320 249 [231,] 204.204 192 [232,] 205.088 206 [233,] 205.972 219 [234,] 206.856 223 [235,] 207.740 268 [236,] 208.624 225 [237,] 209.508 244 [238,] 210.392 240 [239,] 211.276 187 [240,] 212.160 211 [241,] 213.044 214 [242,] 213.928 223 [243,] 214.812 245 [244,] 215.696 222 [245,] 216.580 242 [246,] 217.464 277 [247,] 218.348 236 [248,] 219.232 233 [249,] 220.116 246 [250,] 221.000 121 $`30_IRSL (PMT)` [,1] [,2] [1,] 0.04 34 [2,] 0.08 42 [3,] 0.12 28 [4,] 0.16 29 [5,] 0.20 35 [6,] 0.24 41 [7,] 0.28 30 [8,] 0.32 31 [9,] 0.36 36 [10,] 0.40 41 [11,] 0.44 30 [12,] 0.48 28 [13,] 0.52 34 [14,] 0.56 31 [15,] 0.60 46 [16,] 0.64 25 [17,] 0.68 20 [18,] 0.72 20 [19,] 0.76 25 [20,] 0.80 21 [21,] 0.84 28 [22,] 0.88 14 [23,] 0.92 19 [24,] 0.96 21 [25,] 1.00 22 [26,] 1.04 32 [27,] 1.08 27 [28,] 1.12 23 [29,] 1.16 21 [30,] 1.20 23 [31,] 1.24 30 [32,] 1.28 21 [33,] 1.32 18 [34,] 1.36 27 [35,] 1.40 29 [36,] 1.44 17 [37,] 1.48 21 [38,] 1.52 28 [39,] 1.56 19 [40,] 1.60 17 [41,] 1.64 24 [42,] 1.68 21 [43,] 1.72 11 [44,] 1.76 27 [45,] 1.80 14 [46,] 1.84 11 [47,] 1.88 24 [48,] 1.92 17 [49,] 1.96 17 [50,] 2.00 14 [51,] 2.04 12 [52,] 2.08 18 [53,] 2.12 18 [54,] 2.16 23 [55,] 2.20 19 [56,] 2.24 14 [57,] 2.28 15 [58,] 2.32 17 [59,] 2.36 16 [60,] 2.40 14 [61,] 2.44 19 [62,] 2.48 7 [63,] 2.52 13 [64,] 2.56 11 [65,] 2.60 13 [66,] 2.64 11 [67,] 2.68 15 [68,] 2.72 15 [69,] 2.76 15 [70,] 2.80 17 [71,] 2.84 12 [72,] 2.88 11 [73,] 2.92 10 [74,] 2.96 14 [75,] 3.00 9 [76,] 3.04 13 [77,] 3.08 13 [78,] 3.12 14 [79,] 3.16 10 [80,] 3.20 7 [81,] 3.24 5 [82,] 3.28 13 [83,] 3.32 9 [84,] 3.36 22 [85,] 3.40 11 [86,] 3.44 10 [87,] 3.48 14 [88,] 3.52 16 [89,] 3.56 7 [90,] 3.60 16 [91,] 3.64 16 [92,] 3.68 15 [93,] 3.72 12 [94,] 3.76 6 [95,] 3.80 13 [96,] 3.84 12 [97,] 3.88 7 [98,] 3.92 9 [99,] 3.96 11 [100,] 4.00 8 [101,] 4.04 12 [102,] 4.08 11 [103,] 4.12 7 [104,] 4.16 13 [105,] 4.20 5 [106,] 4.24 12 [107,] 4.28 6 [108,] 4.32 9 [109,] 4.36 12 [110,] 4.40 12 [111,] 4.44 9 [112,] 4.48 10 [113,] 4.52 14 [114,] 4.56 7 [115,] 4.60 6 [116,] 4.64 9 [117,] 4.68 7 [118,] 4.72 9 [119,] 4.76 4 [120,] 4.80 11 [121,] 4.84 7 [122,] 4.88 15 [123,] 4.92 11 [124,] 4.96 9 [125,] 5.00 13 [126,] 5.04 13 [127,] 5.08 8 [128,] 5.12 11 [129,] 5.16 7 [130,] 5.20 13 [131,] 5.24 10 [132,] 5.28 6 [133,] 5.32 11 [134,] 5.36 6 [135,] 5.40 2 [136,] 5.44 8 [137,] 5.48 7 [138,] 5.52 8 [139,] 5.56 9 [140,] 5.60 4 [141,] 5.64 6 [142,] 5.68 4 [143,] 5.72 8 [144,] 5.76 15 [145,] 5.80 11 [146,] 5.84 8 [147,] 5.88 5 [148,] 5.92 4 [149,] 5.96 13 [150,] 6.00 3 [151,] 6.04 8 [152,] 6.08 7 [153,] 6.12 15 [154,] 6.16 4 [155,] 6.20 11 [156,] 6.24 3 [157,] 6.28 1 [158,] 6.32 3 [159,] 6.36 7 [160,] 6.40 15 [161,] 6.44 6 [162,] 6.48 2 [163,] 6.52 7 [164,] 6.56 7 [165,] 6.60 2 [166,] 6.64 5 [167,] 6.68 2 [168,] 6.72 4 [169,] 6.76 10 [170,] 6.80 7 [171,] 6.84 10 [172,] 6.88 3 [173,] 6.92 9 [174,] 6.96 5 [175,] 7.00 5 [176,] 7.04 1 [177,] 7.08 5 [178,] 7.12 2 [179,] 7.16 4 [180,] 7.20 9 [181,] 7.24 3 [182,] 7.28 5 [183,] 7.32 4 [184,] 7.36 6 [185,] 7.40 8 [186,] 7.44 8 [187,] 7.48 8 [188,] 7.52 5 [189,] 7.56 9 [190,] 7.60 13 [191,] 7.64 1 [192,] 7.68 16 [193,] 7.72 6 [194,] 7.76 4 [195,] 7.80 7 [196,] 7.84 3 [197,] 7.88 9 [198,] 7.92 5 [199,] 7.96 6 [200,] 8.00 12 [201,] 8.04 10 [202,] 8.08 4 [203,] 8.12 9 [204,] 8.16 7 [205,] 8.20 7 [206,] 8.24 0 [207,] 8.28 3 [208,] 8.32 5 [209,] 8.36 8 [210,] 8.40 8 [211,] 8.44 6 [212,] 8.48 7 [213,] 8.52 4 [214,] 8.56 2 [215,] 8.60 10 [216,] 8.64 5 [217,] 8.68 5 [218,] 8.72 6 [219,] 8.76 5 [220,] 8.80 6 [221,] 8.84 9 [222,] 8.88 6 [223,] 8.92 9 [224,] 8.96 1 [225,] 9.00 7 [226,] 9.04 4 [227,] 9.08 4 [228,] 9.12 4 [229,] 9.16 2 [230,] 9.20 10 [231,] 9.24 4 [232,] 9.28 5 [233,] 9.32 5 [234,] 9.36 7 [235,] 9.40 8 [236,] 9.44 2 [237,] 9.48 5 [238,] 9.52 2 [239,] 9.56 4 [240,] 9.60 4 [241,] 9.64 10 [242,] 9.68 8 [243,] 9.72 5 [244,] 9.76 4 [245,] 9.80 5 [246,] 9.84 10 [247,] 9.88 5 [248,] 9.92 3 [249,] 9.96 4 [250,] 10.00 6 [251,] 10.04 3 [252,] 10.08 1 [253,] 10.12 4 [254,] 10.16 6 [255,] 10.20 5 [256,] 10.24 4 [257,] 10.28 4 [258,] 10.32 8 [259,] 10.36 3 [260,] 10.40 6 [261,] 10.44 3 [262,] 10.48 9 [263,] 10.52 8 [264,] 10.56 3 [265,] 10.60 10 [266,] 10.64 11 [267,] 10.68 3 [268,] 10.72 7 [269,] 10.76 4 [270,] 10.80 3 [271,] 10.84 6 [272,] 10.88 3 [273,] 10.92 7 [274,] 10.96 4 [275,] 11.00 3 [276,] 11.04 2 [277,] 11.08 0 [278,] 11.12 8 [279,] 11.16 0 [280,] 11.20 3 [281,] 11.24 7 [282,] 11.28 4 [283,] 11.32 8 [284,] 11.36 3 [285,] 11.40 7 [286,] 11.44 1 [287,] 11.48 7 [288,] 11.52 2 [289,] 11.56 4 [290,] 11.60 5 [291,] 11.64 1 [292,] 11.68 5 [293,] 11.72 4 [294,] 11.76 4 [295,] 11.80 9 [296,] 11.84 2 [297,] 11.88 12 [298,] 11.92 5 [299,] 11.96 2 [300,] 12.00 3 [301,] 12.04 6 [302,] 12.08 13 [303,] 12.12 12 [304,] 12.16 3 [305,] 12.20 2 [306,] 12.24 3 [307,] 12.28 4 [308,] 12.32 4 [309,] 12.36 3 [310,] 12.40 5 [311,] 12.44 3 [312,] 12.48 5 [313,] 12.52 1 [314,] 12.56 2 [315,] 12.60 4 [316,] 12.64 6 [317,] 12.68 8 [318,] 12.72 5 [319,] 12.76 1 [320,] 12.80 9 [321,] 12.84 2 [322,] 12.88 9 [323,] 12.92 7 [324,] 12.96 17 [325,] 13.00 3 [326,] 13.04 5 [327,] 13.08 1 [328,] 13.12 5 [329,] 13.16 8 [330,] 13.20 3 [331,] 13.24 2 [332,] 13.28 2 [333,] 13.32 4 [334,] 13.36 5 [335,] 13.40 6 [336,] 13.44 5 [337,] 13.48 5 [338,] 13.52 8 [339,] 13.56 5 [340,] 13.60 5 [341,] 13.64 3 [342,] 13.68 3 [343,] 13.72 6 [344,] 13.76 3 [345,] 13.80 1 [346,] 13.84 1 [347,] 13.88 1 [348,] 13.92 3 [349,] 13.96 1 [350,] 14.00 7 [351,] 14.04 20 [352,] 14.08 1 [353,] 14.12 1 [354,] 14.16 3 [355,] 14.20 6 [356,] 14.24 5 [357,] 14.28 5 [358,] 14.32 2 [359,] 14.36 3 [360,] 14.40 0 [361,] 14.44 0 [362,] 14.48 2 [363,] 14.52 0 [364,] 14.56 9 [365,] 14.60 5 [366,] 14.64 2 [367,] 14.68 2 [368,] 14.72 2 [369,] 14.76 1 [370,] 14.80 9 [371,] 14.84 7 [372,] 14.88 4 [373,] 14.92 7 [374,] 14.96 8 [375,] 15.00 7 [376,] 15.04 7 [377,] 15.08 7 [378,] 15.12 3 [379,] 15.16 2 [380,] 15.20 8 [381,] 15.24 6 [382,] 15.28 6 [383,] 15.32 2 [384,] 15.36 2 [385,] 15.40 2 [386,] 15.44 6 [387,] 15.48 3 [388,] 15.52 6 [389,] 15.56 2 [390,] 15.60 2 [391,] 15.64 1 [392,] 15.68 9 [393,] 15.72 5 [394,] 15.76 7 [395,] 15.80 1 [396,] 15.84 7 [397,] 15.88 2 [398,] 15.92 4 [399,] 15.96 7 [400,] 16.00 1 [401,] 16.04 6 [402,] 16.08 2 [403,] 16.12 0 [404,] 16.16 2 [405,] 16.20 3 [406,] 16.24 7 [407,] 16.28 6 [408,] 16.32 5 [409,] 16.36 2 [410,] 16.40 8 [411,] 16.44 9 [412,] 16.48 4 [413,] 16.52 2 [414,] 16.56 5 [415,] 16.60 1 [416,] 16.64 5 [417,] 16.68 2 [418,] 16.72 6 [419,] 16.76 1 [420,] 16.80 3 [421,] 16.84 0 [422,] 16.88 4 [423,] 16.92 2 [424,] 16.96 6 [425,] 17.00 4 [426,] 17.04 4 [427,] 17.08 3 [428,] 17.12 1 [429,] 17.16 9 [430,] 17.20 4 [431,] 17.24 5 [432,] 17.28 2 [433,] 17.32 3 [434,] 17.36 3 [435,] 17.40 2 [436,] 17.44 0 [437,] 17.48 1 [438,] 17.52 3 [439,] 17.56 1 [440,] 17.60 1 [441,] 17.64 8 [442,] 17.68 2 [443,] 17.72 3 [444,] 17.76 6 [445,] 17.80 1 [446,] 17.84 1 [447,] 17.88 3 [448,] 17.92 14 [449,] 17.96 7 [450,] 18.00 3 [451,] 18.04 5 [452,] 18.08 3 [453,] 18.12 2 [454,] 18.16 4 [455,] 18.20 4 [456,] 18.24 2 [457,] 18.28 2 [458,] 18.32 4 [459,] 18.36 4 [460,] 18.40 3 [461,] 18.44 5 [462,] 18.48 4 [463,] 18.52 7 [464,] 18.56 3 [465,] 18.60 2 [466,] 18.64 3 [467,] 18.68 1 [468,] 18.72 3 [469,] 18.76 6 [470,] 18.80 2 [471,] 18.84 0 [472,] 18.88 2 [473,] 18.92 6 [474,] 18.96 2 [475,] 19.00 4 [476,] 19.04 0 [477,] 19.08 2 [478,] 19.12 8 [479,] 19.16 0 [480,] 19.20 9 [481,] 19.24 3 [482,] 19.28 2 [483,] 19.32 6 [484,] 19.36 5 [485,] 19.40 4 [486,] 19.44 3 [487,] 19.48 5 [488,] 19.52 0 [489,] 19.56 3 [490,] 19.60 5 [491,] 19.64 2 [492,] 19.68 3 [493,] 19.72 7 [494,] 19.76 1 [495,] 19.80 4 [496,] 19.84 3 [497,] 19.88 7 [498,] 19.92 3 [499,] 19.96 2 [500,] 20.00 2 [501,] 20.04 5 [502,] 20.08 3 [503,] 20.12 1 [504,] 20.16 4 [505,] 20.20 1 [506,] 20.24 4 [507,] 20.28 0 [508,] 20.32 1 [509,] 20.36 1 [510,] 20.40 6 [511,] 20.44 3 [512,] 20.48 0 [513,] 20.52 4 [514,] 20.56 5 [515,] 20.60 6 [516,] 20.64 2 [517,] 20.68 6 [518,] 20.72 2 [519,] 20.76 2 [520,] 20.80 2 [521,] 20.84 0 [522,] 20.88 4 [523,] 20.92 8 [524,] 20.96 8 [525,] 21.00 7 [526,] 21.04 2 [527,] 21.08 0 [528,] 21.12 2 [529,] 21.16 3 [530,] 21.20 1 [531,] 21.24 3 [532,] 21.28 3 [533,] 21.32 5 [534,] 21.36 4 [535,] 21.40 4 [536,] 21.44 6 [537,] 21.48 4 [538,] 21.52 4 [539,] 21.56 7 [540,] 21.60 5 [541,] 21.64 4 [542,] 21.68 5 [543,] 21.72 3 [544,] 21.76 0 [545,] 21.80 5 [546,] 21.84 6 [547,] 21.88 3 [548,] 21.92 3 [549,] 21.96 3 [550,] 22.00 3 [551,] 22.04 3 [552,] 22.08 2 [553,] 22.12 6 [554,] 22.16 2 [555,] 22.20 1 [556,] 22.24 3 [557,] 22.28 2 [558,] 22.32 1 [559,] 22.36 6 [560,] 22.40 2 [561,] 22.44 0 [562,] 22.48 5 [563,] 22.52 4 [564,] 22.56 4 [565,] 22.60 2 [566,] 22.64 3 [567,] 22.68 3 [568,] 22.72 3 [569,] 22.76 3 [570,] 22.80 4 [571,] 22.84 3 [572,] 22.88 1 [573,] 22.92 5 [574,] 22.96 1 [575,] 23.00 7 [576,] 23.04 4 [577,] 23.08 1 [578,] 23.12 0 [579,] 23.16 3 [580,] 23.20 7 [581,] 23.24 4 [582,] 23.28 3 [583,] 23.32 5 [584,] 23.36 0 [585,] 23.40 7 [586,] 23.44 4 [587,] 23.48 1 [588,] 23.52 3 [589,] 23.56 3 [590,] 23.60 7 [591,] 23.64 4 [592,] 23.68 0 [593,] 23.72 1 [594,] 23.76 6 [595,] 23.80 4 [596,] 23.84 4 [597,] 23.88 0 [598,] 23.92 4 [599,] 23.96 3 [600,] 24.00 3 [601,] 24.04 7 [602,] 24.08 1 [603,] 24.12 0 [604,] 24.16 3 [605,] 24.20 3 [606,] 24.24 4 [607,] 24.28 3 [608,] 24.32 3 [609,] 24.36 5 [610,] 24.40 9 [611,] 24.44 6 [612,] 24.48 5 [613,] 24.52 4 [614,] 24.56 3 [615,] 24.60 1 [616,] 24.64 1 [617,] 24.68 9 [618,] 24.72 0 [619,] 24.76 0 [620,] 24.80 4 [621,] 24.84 3 [622,] 24.88 4 [623,] 24.92 2 [624,] 24.96 2 [625,] 25.00 1 [626,] 25.04 0 [627,] 25.08 2 [628,] 25.12 4 [629,] 25.16 6 [630,] 25.20 3 [631,] 25.24 5 [632,] 25.28 3 [633,] 25.32 2 [634,] 25.36 3 [635,] 25.40 2 [636,] 25.44 0 [637,] 25.48 4 [638,] 25.52 2 [639,] 25.56 2 [640,] 25.60 4 [641,] 25.64 1 [642,] 25.68 2 [643,] 25.72 2 [644,] 25.76 3 [645,] 25.80 2 [646,] 25.84 2 [647,] 25.88 3 [648,] 25.92 3 [649,] 25.96 1 [650,] 26.00 1 [651,] 26.04 4 [652,] 26.08 5 [653,] 26.12 3 [654,] 26.16 3 [655,] 26.20 9 [656,] 26.24 5 [657,] 26.28 6 [658,] 26.32 2 [659,] 26.36 11 [660,] 26.40 2 [661,] 26.44 2 [662,] 26.48 3 [663,] 26.52 1 [664,] 26.56 0 [665,] 26.60 1 [666,] 26.64 5 [667,] 26.68 3 [668,] 26.72 1 [669,] 26.76 2 [670,] 26.80 1 [671,] 26.84 0 [672,] 26.88 0 [673,] 26.92 0 [674,] 26.96 2 [675,] 27.00 0 [676,] 27.04 4 [677,] 27.08 7 [678,] 27.12 3 [679,] 27.16 1 [680,] 27.20 5 [681,] 27.24 0 [682,] 27.28 2 [683,] 27.32 9 [684,] 27.36 4 [685,] 27.40 0 [686,] 27.44 3 [687,] 27.48 10 [688,] 27.52 9 [689,] 27.56 2 [690,] 27.60 6 [691,] 27.64 0 [692,] 27.68 3 [693,] 27.72 5 [694,] 27.76 1 [695,] 27.80 9 [696,] 27.84 1 [697,] 27.88 0 [698,] 27.92 2 [699,] 27.96 5 [700,] 28.00 2 [701,] 28.04 6 [702,] 28.08 2 [703,] 28.12 2 [704,] 28.16 3 [705,] 28.20 1 [706,] 28.24 1 [707,] 28.28 2 [708,] 28.32 0 [709,] 28.36 3 [710,] 28.40 4 [711,] 28.44 5 [712,] 28.48 3 [713,] 28.52 2 [714,] 28.56 6 [715,] 28.60 1 [716,] 28.64 2 [717,] 28.68 6 [718,] 28.72 1 [719,] 28.76 3 [720,] 28.80 2 [721,] 28.84 2 [722,] 28.88 3 [723,] 28.92 7 [724,] 28.96 7 [725,] 29.00 2 [726,] 29.04 6 [727,] 29.08 6 [728,] 29.12 4 [729,] 29.16 0 [730,] 29.20 2 [731,] 29.24 2 [732,] 29.28 5 [733,] 29.32 1 [734,] 29.36 0 [735,] 29.40 2 [736,] 29.44 3 [737,] 29.48 3 [738,] 29.52 5 [739,] 29.56 5 [740,] 29.60 3 [741,] 29.64 0 [742,] 29.68 0 [743,] 29.72 2 [744,] 29.76 0 [745,] 29.80 2 [746,] 29.84 5 [747,] 29.88 6 [748,] 29.92 4 [749,] 29.96 2 [750,] 30.00 1 [751,] 30.04 1 [752,] 30.08 3 [753,] 30.12 3 [754,] 30.16 2 [755,] 30.20 3 [756,] 30.24 6 [757,] 30.28 5 [758,] 30.32 5 [759,] 30.36 2 [760,] 30.40 2 [761,] 30.44 3 [762,] 30.48 1 [763,] 30.52 4 [764,] 30.56 0 [765,] 30.60 1 [766,] 30.64 3 [767,] 30.68 3 [768,] 30.72 6 [769,] 30.76 8 [770,] 30.80 1 [771,] 30.84 9 [772,] 30.88 0 [773,] 30.92 4 [774,] 30.96 7 [775,] 31.00 1 [776,] 31.04 15 [777,] 31.08 4 [778,] 31.12 2 [779,] 31.16 1 [780,] 31.20 2 [781,] 31.24 2 [782,] 31.28 6 [783,] 31.32 0 [784,] 31.36 1 [785,] 31.40 3 [786,] 31.44 0 [787,] 31.48 7 [788,] 31.52 5 [789,] 31.56 3 [790,] 31.60 2 [791,] 31.64 3 [792,] 31.68 2 [793,] 31.72 3 [794,] 31.76 2 [795,] 31.80 1 [796,] 31.84 2 [797,] 31.88 5 [798,] 31.92 5 [799,] 31.96 2 [800,] 32.00 1 [801,] 32.04 0 [802,] 32.08 3 [803,] 32.12 0 [804,] 32.16 5 [805,] 32.20 10 [806,] 32.24 1 [807,] 32.28 1 [808,] 32.32 2 [809,] 32.36 1 [810,] 32.40 7 [811,] 32.44 4 [812,] 32.48 1 [813,] 32.52 5 [814,] 32.56 3 [815,] 32.60 0 [816,] 32.64 1 [817,] 32.68 0 [818,] 32.72 1 [819,] 32.76 2 [820,] 32.80 3 [821,] 32.84 1 [822,] 32.88 5 [823,] 32.92 3 [824,] 32.96 4 [825,] 33.00 3 [826,] 33.04 3 [827,] 33.08 5 [828,] 33.12 2 [829,] 33.16 2 [830,] 33.20 2 [831,] 33.24 0 [832,] 33.28 2 [833,] 33.32 3 [834,] 33.36 0 [835,] 33.40 4 [836,] 33.44 2 [837,] 33.48 1 [838,] 33.52 4 [839,] 33.56 5 [840,] 33.60 4 [841,] 33.64 1 [842,] 33.68 6 [843,] 33.72 0 [844,] 33.76 1 [845,] 33.80 9 [846,] 33.84 5 [847,] 33.88 10 [848,] 33.92 2 [849,] 33.96 4 [850,] 34.00 1 [851,] 34.04 1 [852,] 34.08 2 [853,] 34.12 2 [854,] 34.16 3 [855,] 34.20 8 [856,] 34.24 4 [857,] 34.28 4 [858,] 34.32 2 [859,] 34.36 2 [860,] 34.40 0 [861,] 34.44 1 [862,] 34.48 3 [863,] 34.52 1 [864,] 34.56 1 [865,] 34.60 3 [866,] 34.64 7 [867,] 34.68 1 [868,] 34.72 1 [869,] 34.76 6 [870,] 34.80 7 [871,] 34.84 4 [872,] 34.88 7 [873,] 34.92 0 [874,] 34.96 5 [875,] 35.00 1 [876,] 35.04 6 [877,] 35.08 5 [878,] 35.12 2 [879,] 35.16 0 [880,] 35.20 4 [881,] 35.24 4 [882,] 35.28 1 [883,] 35.32 1 [884,] 35.36 4 [885,] 35.40 5 [886,] 35.44 2 [887,] 35.48 3 [888,] 35.52 5 [889,] 35.56 4 [890,] 35.60 4 [891,] 35.64 5 [892,] 35.68 2 [893,] 35.72 5 [894,] 35.76 4 [895,] 35.80 1 [896,] 35.84 3 [897,] 35.88 2 [898,] 35.92 0 [899,] 35.96 0 [900,] 36.00 2 [901,] 36.04 6 [902,] 36.08 3 [903,] 36.12 5 [904,] 36.16 0 [905,] 36.20 4 [906,] 36.24 0 [907,] 36.28 1 [908,] 36.32 1 [909,] 36.36 3 [910,] 36.40 1 [911,] 36.44 3 [912,] 36.48 3 [913,] 36.52 3 [914,] 36.56 1 [915,] 36.60 4 [916,] 36.64 2 [917,] 36.68 4 [918,] 36.72 0 [919,] 36.76 3 [920,] 36.80 3 [921,] 36.84 1 [922,] 36.88 5 [923,] 36.92 2 [924,] 36.96 3 [925,] 37.00 3 [926,] 37.04 1 [927,] 37.08 1 [928,] 37.12 4 [929,] 37.16 1 [930,] 37.20 4 [931,] 37.24 4 [932,] 37.28 3 [933,] 37.32 3 [934,] 37.36 2 [935,] 37.40 7 [936,] 37.44 2 [937,] 37.48 1 [938,] 37.52 1 [939,] 37.56 6 [940,] 37.60 1 [941,] 37.64 0 [942,] 37.68 6 [943,] 37.72 3 [944,] 37.76 7 [945,] 37.80 2 [946,] 37.84 4 [947,] 37.88 1 [948,] 37.92 7 [949,] 37.96 8 [950,] 38.00 3 [951,] 38.04 3 [952,] 38.08 1 [953,] 38.12 3 [954,] 38.16 3 [955,] 38.20 0 [956,] 38.24 4 [957,] 38.28 6 [958,] 38.32 0 [959,] 38.36 2 [960,] 38.40 1 [961,] 38.44 2 [962,] 38.48 2 [963,] 38.52 1 [964,] 38.56 0 [965,] 38.60 1 [966,] 38.64 1 [967,] 38.68 2 [968,] 38.72 3 [969,] 38.76 0 [970,] 38.80 2 [971,] 38.84 14 [972,] 38.88 3 [973,] 38.92 0 [974,] 38.96 4 [975,] 39.00 0 [976,] 39.04 6 [977,] 39.08 3 [978,] 39.12 5 [979,] 39.16 5 [980,] 39.20 2 [981,] 39.24 8 [982,] 39.28 5 [983,] 39.32 1 [984,] 39.36 3 [985,] 39.40 1 [986,] 39.44 2 [987,] 39.48 2 [988,] 39.52 2 [989,] 39.56 1 [990,] 39.60 0 [991,] 39.64 3 [992,] 39.68 4 [993,] 39.72 1 [994,] 39.76 6 [995,] 39.80 2 [996,] 39.84 1 [997,] 39.88 0 [998,] 39.92 6 [999,] 39.96 2 [1000,] 40.00 2 > > ## Not run: > ##D ## write to a temporary file > ##D temp_file <- tempfile(pattern = "output", fileext = ".csv") > ##D write_RLum2CSV(object, temp_file) > ##D > ##D ## write to the working directory > ##D write_RLum2CSV(object) > ## End(Not run) > > > > > ### *