Traces the evolution of the concentrations in the different levels over different simulation steps. For instance, a sequence consisting of one TL and one OSL step has two iterations. For each step the end concentration is extracted. This way, the evolution of the system can be traced throughout a sequence.

trace_ParameterStateEvolution(object, step = NULL, plot = TRUE, ...)

Arguments

object

Luminescence::RLum.Analysis (required): input object created by the function model_LuminescenceSignals. The input can be a list of such objects

step

character (optional): filter the input object to pick particular steps, the input is passed to Luminescence::get_RLum

plot

logical (with default): enables/disables plot output

...

optional arguments to be passed to control the plot output. Supported are xlim, xlab, ylab, log, col, type, bg, main, norm (TRUE/FALSE), grid (TRUE/FALSE), step_names (TRUE/FALSE) Where meaningful, parameters can be provided as vectors. Vectors short than the number of plots are recycled.

Value

Returns a plot and list with matrix objects of the parameter evolution. If object is a list the output is a nested list

Function version

0.1.0

Author

Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom)

How to cite

Kreutzer, S., 2022. trace_ParameterStateEvolution(): Trace parameter state evolution. Function version 0.1.0. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2022. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.10. https://CRAN.R-project.org/package=RLumModel

Examples


sequence <-
list(
IRR = c(20, 10, 1),
TL = c(20, 400, 5),
IRR = c(20, 10, 1),
TL = c(20, 400, 5))

##model sequence
model.output <- model_LuminescenceSignals(
 sequence = sequence,
 verbose = FALSE,
 plot = FALSE,
 model = "Bailey2001")

## trace
trace_ParameterStateEvolution(model.output)