The goal of ageR is to provide functions that facilitate the creation of age models using different data sources, including databases, comma and tab separated files.
Installation
You can install the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("special-uor/ageR", "dev")Example
⚠️ Users of Windows: ageR::Bacon creates symbolic links (think of them as shortcuts), you should run RStudio in “Administrator mode” to avoid error messages.
Bacon model
Input structure
For an entity X, the input structure should look like
ageR::file_structure(entity = "X", am = "bacon")
#> levelName
#> 1 X
#> 2 ¦--Bacon_runs
#> 3 ¦ °--X
#> 4 ¦ ¦--X_depths.txt
#> 5 ¦ ¦--X_sample_ids.csv
#> 6 ¦ °--X.csv
#> 7 ¦--hiatus.csv
#> 8 °--not_used_dates.csvThe function ageR::create_input can be used to automatically create the appropriate file structure (as shown previously).
Create input structure
-
Start by creating a data frame for the sampling depths, this should have two numeric columns called
idanddepth:sample_depths <- data.frame(id = 1:100, depth = seq(0, 500, length.out = 100)) knitr::kable(head(sample_depths))id depth 1 0.000000 2 5.050505 3 10.101010 4 15.151515 5 20.202020 6 25.252525 -
Create a data frame with the core’s data, this should have at least four columns. The first column can be of character type and the remaining must be numeric. The column names should be
labID,age,error, anddepth. Optionally, a fifth column,cc, can be included to manually select the calibration curve for each observation.core <- data.frame(labID = paste0("X", sprintf("%03d", 1:5)), age = c(50, 200, 1150, 2060, 4050), error = c(10, 15, 5, 1, 70), depth = c(5, 100, 230, 300, 450), cc = 1) knitr::kable(core)labID age error depth cc X001 50 10 5 1 X002 200 15 100 1 X003 1150 5 230 1 X004 2060 1 300 1 X005 4050 70 450 1 -
(Optional) Create a data frame with the hiatuses depths, this should have two numeric columns called
idanddepth:hiatus <- data.frame(id = c(1, 2), depth = c(50, 150)) knitr::kable(hiatus)id depth 1 50 2 150 -
Call the
ageR::create_inputfunction. The first parameter should be a list containing the previous data frames, which must be calledsample_depths,core, andhiatus(if included). Next, a working directory (wdir), the entity’s name, and optionally the age model’s name (by default is Bacon).ageR::create_input(data = list(sample_depths = sample_depths, core = core, # Optional hiatus = hiatus), wdir = "./", entity = "X", am = "bacon")
Run Bacon
ageR::Bacon(wdir = "./",
entity = "X",
# Optional parameters
cpus = 1,
postbomb = 0,
cc = 0,
seed = NA,
alt_depths = NULL,
quiet = FALSE,
acc_step = 5,
acc_lower = NULL,
acc_upper = NULL,
thick_step = 5,
thick_lower = NULL,
thick_upper = NULL,
dry_run = FALSE,
...)Dry-run
Dry-runs are useful to check how many scenarios will be generated with the current configuration:
ageR::Bacon(wdir = "./", entity = "X", dry_run = TRUE, quiet = TRUE)
#> The following scenarios will be executed:
#>
#>
#> | Accumulation rate| Thickness|
#> |-----------------:|---------:|
#> | 5| 10|
#> | 10| 10|
#> | 20| 10|
#> | 5| 15|
#> | 10| 15|
#> | 20| 15|
#> | 5| 20|
#> | 10| 20|
#> | 20| 20|
#> | 5| 30|
#> | 10| 30|
#> | 20| 30|
#> | 5| 40|
#> | 10| 40|
#> | 20| 40|
#> A total of 15 scenarios.Change upper and lower bounds
Based on a dry-run, we might want to constraint our execution to a smaller set of scenarios. This can be done for both accumulation rate and core segment thickness.
ageR::Bacon(wdir = "./", entity = "X", acc_lower = 10, acc_upper = 20, dry_run = TRUE, quiet = TRUE)
#> The following scenarios will be executed:
#>
#>
#> | Accumulation rate| Thickness|
#> |-----------------:|---------:|
#> | 10| 10|
#> | 20| 10|
#> | 10| 15|
#> | 20| 15|
#> | 10| 20|
#> | 20| 20|
#> | 10| 30|
#> | 20| 30|
#> | 10| 40|
#> | 20| 40|
#> A total of 10 scenarios.
ageR::Bacon(wdir = "./", entity = "X", thick_lower = 10, thick_upper = 30, dry_run = TRUE, quiet = TRUE)
#> The following scenarios will be executed:
#>
#>
#> | Accumulation rate| Thickness|
#> |-----------------:|---------:|
#> | 5| 10|
#> | 10| 10|
#> | 20| 10|
#> | 5| 15|
#> | 10| 15|
#> | 20| 15|
#> | 5| 20|
#> | 10| 20|
#> | 20| 20|
#> | 5| 30|
#> | 10| 30|
#> | 20| 30|
#> A total of 12 scenarios.Use mixed calibration curves
This is particular useful for “neo-tropical” sites. It involves three steps:
-
Assign
cc = 4to thecoredata:core <- data.frame(labID = paste0("X", sprintf("%03d", 1:5)), age = c(50, 200, 1150, 2060, 4050), error = c(10, 15, 5, 1, 70), depth = c(5, 100, 230, 300, 450), cc = 4) knitr::kable(core)labID age error depth cc X001 50 10 5 4 X002 200 15 100 4 X003 1150 5 230 4 X004 2060 1 300 4 X005 4050 70 450 4 -
Create a mixed calibration curve with
ageR::mix_curves. The following example uses a 50/50 mix betweenIntCal20(cc1 = 1) andSHCal20(cc2 = 3).ccdir <- "./ccurves" ageR::mix_curves(proportion = 0.5, cc1 = 1, cc = 3, name = "neotropics.14C", dir = ccdir) #> -------------------------------------------------------------------------------- #> | Mixed curved: 50/50 created. | #> -------------------------------------------------------------------------------- -
Add two new parameters to the
ageR::Baconcall:out <- ageR::Bacon(wdir = "./", entity = "X", cc4 = "neotropics.14C", ccdir = ccdir)
Display progress bar
A progress bar can be displayed for long computations. Just “pipe” the function call to ageR::pb().
`%>%` <- magrittr::`%>%`
out <- ageR::Bacon(wdir = "./", entity = "X", cpus = 8, verbose = FALSE) %>%
ageR::pb()Alternatively, if you are not familiar with the “pipe” operator, you can run the following code:
Run example
`%>%` <- magrittr::`%>%`
out <- ageR::Bacon(wdir = "./", entity = "X", cpus = 8, verbose = FALSE) %>%
ageR::pb()
#> --------------------------------------------------------------------------------
#> | Checking input files |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Loading input files |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Setting up environment |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Running Bacon |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S001-AR005-T10 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 10908000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 412 yr, min. 111 yr at 15.1515151515152 cm, max. 907 yr at 500 cm
#> 80% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S002-AR010-T10 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 10908000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 515 yr, min. 130 yr at 0 cm, max. 1065 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S003-AR020-T10 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 10908000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 535 yr, min. 141 yr at 0 cm, max. 1534 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S004-AR005-T15 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 7474000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 578 yr, min. 110 yr at 10.1010101010101 cm, max. 1480 yr at 489.89898989899 cm
#> 80% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S005-AR010-T15 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 7474000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 564 yr, min. 138 yr at 10.1010101010101 cm, max. 1248 yr at 373.737373737374 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S006-AR020-T15 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 7474000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 600 yr, min. 129 yr at 5.05050505050505 cm, max. 1805 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S007-AR005-T20 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 5858000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 763 yr, min. 111 yr between 5.05050505050505 and 10.1010101010101 cm, max. 2049 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S008-AR010-T20 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 5858000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 600 yr, min. 114 yr at 5.05050505050505 cm, max. 1378 yr at 378.787878787879 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S009-AR020-T20 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 5858000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 627 yr, min. 121 yr at 10.1010101010101 cm, max. 1968 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S010-AR005-T30 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 4040000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 761 yr, min. 101 yr at 5.05050505050505 cm, max. 1819 yr at 494.949494949495 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S011-AR010-T30 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 4040000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 641 yr, min. 108 yr at 10.1010101010101 cm, max. 1601 yr at 388.888888888889 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S012-AR020-T30 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 4040000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 696 yr, min. 108 yr at 10.1010101010101 cm, max. 2356 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S013-AR005-T40 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 3232000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 653 yr, min. 105 yr at 5.05050505050505 cm, max. 1626 yr at 358.585858585859 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S014-AR010-T40 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 3232000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 627 yr, min. 107 yr between 5.05050505050505 and 10.1010101010101 cm, max. 1615 yr at 398.989898989899 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | S015-AR020-T40 |
#> --------------------------------------------------------------------------------
#> Boundary set at depth(s) NA
#> Will run 3232000 iterations and store around 2019
#> Calculating age ranges...
#>
#> Preparing ghost graph...
#>
#> Mean 95% confidence ranges 689 yr, min. 105 yr at 5.05050505050505 cm, max. 2357 yr at 500 cm
#> 100% of the dates overlap with the age-depth model (95% ranges)
#>
#> --------------------------------------------------------------------------------
#> | Saving results |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Bacon QC |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Best scenario: Acc. Rate = 10yr/cm - Thickness: 10cm |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Plot Accumulation Rate |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Plot Accumulation Rate: Posterior vs Prior |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Plot Log Posterior (MCMC) |
#> --------------------------------------------------------------------------------
#> --------------------------------------------------------------------------------
#> | Bye! |
#> --------------------------------------------------------------------------------
| Acc. Rate | Thickness | Area Between Curves | Relative Bias | |
|---|---|---|---|---|
| 2 | 10 | 10 | 0.8834312 | 3.89e-17 |
| 5 | 10 | 15 | 1.1360135 | -1.23e-18 |
| 1 | 5 | 10 | 1.2462380 | 2.95e-17 |
| 8 | 10 | 20 | 1.2506841 | -1.72e-17 |
| 11 | 10 | 30 | 1.4717409 | 5.34e-17 |
| 14 | 10 | 40 | 1.6285692 | -4.89e-17 |
| 6 | 20 | 15 | 1.7309200 | -7.50e-17 |
| 12 | 20 | 30 | 1.8129729 | -4.43e-17 |
| 4 | 5 | 15 | 1.8264077 | -4.90e-18 |
| 15 | 20 | 40 | 1.8987923 | -4.71e-17 |
| 3 | 20 | 10 | 1.9251454 | 2.82e-17 |
| 9 | 20 | 20 | 1.9450044 | 9.11e-17 |
| 7 | 5 | 20 | 2.4208650 | -1.28e-17 |
| 10 | 5 | 30 | 4.3136892 | -8.37e-17 |
| 13 | 5 | 40 | 6.0654689 | 2.07e-17 |
