3.3.1 Top level (sample, files)

The top level has two parameters:

  files: 
    - "/yourhardrive/yourfolder/sample_one_a.binx"
    - "/yourhardrive/yourfolder/sample_one_b.binx"

3.3.2 settings level

The settings level allows you to specify the dose rate of your source used for the irradiation in Gy/s (dose_source) and the environmental dose rate in Gy/ka (dose_env). Each value needs to be provided with its uncertainty, as shown in the example:

  settings:
    dose_points: null
    dose_source: { value: 0.1535, error: 0.00005891 }
    dose_env: { value: 2.512, error: 0.05626 }

Additionally, you can set specify the regeneration dose points (in s). The default is null, because irradiation times are automatically extracted from the data by create_DataFile(). However, this information might be missing or, more likely, wrong and it is very cumbersome to fix those numbers manually in the measurement data. Therefore the dose points can be provided with the config file:

  settings:
    dose_points: [10, 20, 50, 0, 10]
    dose_source: { value: 0.1535, error: 0.00005891 }
    dose_env: { value: 2.512, error: 0.05626 }

The example corresponds to 5 (five) regeneration dose points of 10 s, 20 s, …, 10 s.

Note

• You should add the values as you have specified them in the measurement sequence, except for the natural dose point (0 s) and the test dose points, which must not be added.

• The provided vector will be shortened automatically to fit the actual number of dose points.

• An error will be thrown if you provide not enough dose points

3.3.3 rules level

The rules level enables you to provide a couple of parameters, which are used in Bayesian modelling.

Example:

   rules:
        beginSignal: 6
        endSignal: 8
        beginBackground: 50
        endBackground: 55
        beginTest: 6
        endTest: 8
        beginTestBackground: 50
        endTestBackground: 55
        inflatePercent: 0.027
        nbOfLastCycleToRemove: 1

Please ensure that the set values correspond to your measurement data. For instance, if your OSL curve has only 100 channels (data points), it does not make sense to set larger integral settings (e.g., 1000), and such a setting will lead to an error. Integral values for (\(L_x\)) and (\(T_x\)) are usually set to identical values unless you have good reasons to use different integral settings.

3.5.1 Show available parameters

In this mode, the function displays available parameters in the terminal and returns a list that can be modified in R and then passed to create_DataFile():

l <- write_YAMLConfigFile()

── Allowed function parameters (start) ─────────────────────────────────────────────────────────────────────────────────

sample
files
settings.dose_points
settings.dose_source.value
settings.dose_source.error
settings.dose_env.value
settings.dose_env.error
settings.rules.beginSignal
settings.rules.endSignal
settings.rules.beginBackground
settings.rules.endBackground
settings.rules.beginTest
settings.rules.endTest
settings.rules.beginTestBackground
settings.rules.endTestBackground
settings.rules.inflatePercent
settings.rules.nbOfLastCycleToRemove

── Allowed function parameters (end) ───────────────────────────────────────────────────────────────────────────────────

str(l)

List of 1
 $ :List of 3
  ..$ sample  : chr "reference"
  ..$ files   : NULL
  ..$ settings:List of 4
  .. ..$ dose_points: NULL
  .. ..$ dose_source:List of 2
  .. .. ..$ value: int 0
  .. .. ..$ error: int 0
  .. ..$ dose_env   :List of 2
  .. .. ..$ value: int 0
  .. .. ..$ error: int 0
  .. ..$ rules      :List of 10
  .. .. ..$ beginSignal          : int 0
  .. .. ..$ endSignal            : int 0
  .. .. ..$ beginBackground      : int 0
  .. .. ..$ endBackground        : int 0
  .. .. ..$ beginTest            : int 0
  .. .. ..$ endTest              : int 0
  .. .. ..$ beginTestBackground  : int 0
  .. .. ..$ endTestBackground    : int 0
  .. .. ..$ inflatePercent       : int 0
  .. .. ..$ nbOfLastCycleToRemove: int 0

3.5.2 Write YAML file

Alternatively, the function can be used to generate a config file with preset values. You can then modify the generated YAML file with any text-editor.

l <- write_YAMLConfigFile(output_file = "<your filepath>")