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fit_IsothermalHolding(): define the models as functions rather than strings #557

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Feb 3, 2025
Merged

fit_IsothermalHolding(): define the models as functions rather than strings #557

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a6462bd
Define the models as functions rather than strings.
mcol Jan 31, 2025
75282bd
Improve fit of the models by expressing them in terms of log10(s).
mcol Feb 3, 2025
f6b8821
Set rhop in fit_IsothermalHolding() tests to a more plausible value.
mcol Feb 3, 2025
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72 changes: 40 additions & 32 deletions R/fit_IsothermalHolding.R
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Original file line number Diff line number Diff line change
Expand Up @@ -21,8 +21,9 @@
#' @section Function version: 0.1.0
#'
#' @author
#' Svenja Riedesel, DTU Risø (Denmark)
#' Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany)
#' Svenja Riedesel, DTU Risø (Denmark)\cr
#' Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany)\cr
#' Marco Colombo, Institute of Geography, Heidelberg University (Germany)
#'
#' @keywords datagen
#'
Expand Down Expand Up @@ -96,6 +97,7 @@ fit_IsothermalHolding <- function(
###### --- Perform ITL fitting --- #####
# Define variables --------------------------------------------------------
kB <- 8.6173303e-05 # Boltzmann's constant
DeltaE <- 1.5 # upper limit of integration (in eV), see Li&Li (2013), p.6

## get the rhop value from the fading measurement analysis if available,
## otherwise take the input and recycle it for the number of samples
Expand All @@ -104,65 +106,71 @@ fit_IsothermalHolding <- function(
else
rhop <- rep(rhop, length.out = length(sample_id))

# Define formulas to fit --------------------------------------------------
## silence note from R CMD check
A <- Eu <- Et <- s <- NULL

f_GOK <- 'y ~ A * exp(-rhop * log(1.8 * 3e15 * (250 + x))^3) * (1 - (1 - b) * s * exp(-E / (kB * (isoT + 273.15))) * x)^(1 / (1 - b))'
f_BTSPre <- function(Eb) A*exp(-Eb/Eu)*exp(-s*t*exp(-(Et-Eb)/(kB*(isoT+273.15))))
f_BTS <- 'y ~ exp(-rhop * log(1.8 * 3e15 * (250 + x))^3)*integrate(F_BTSPre,0,DeltaE)'
## Define formulas to fit -------------------------------------------------
##
## We define each model as a function that describes the right-hand side
## of the formula. This allows us to use the `$value` term in the BTS model
## to extract the solution of the integral, which would otherwise be
## incorrectly interpreted by nlsLM().

f_GOK <- function(A, b, Et, s10, isoT, x) {
T_K <- isoT[1] + 273.15 # isoT[1] because it comes from data as a vector
A * exp(-rhop * log(1.8 * 3e15 * (250 + x))^3) *
(1 - (1 - b) * 10^s10 * exp(-Et / (kB * T_K)) * x)^(1 / (1 - b))
}
f_BTS <- function(A, Eu, Et, s10, isoT, x) {
T_K <- isoT[1] + 273.15 # isoT[1] because it comes from data as a vector
exp(-rhop * log(1.8 * 3e15 * (250 + x))^3) *
sapply(x, function(t) {
integrate(function(Eb) A * exp(-Eb / Eu) *
exp(-10^s10 * t * exp(-(Et - Eb) / (kB * T_K))),
0, DeltaE)$value
})
}

## switch the models
FUN <- switch(
ITL_model,
'GOK' = f_GOK,
'BTS' = f_BTS)

start <- switch(
ITL_model,
'GOK' = list(A = 1, b = 1, E = 1, s = 1e+5),
'BTS' = list(A = 1, Eb = 1, Eu = 1, s = 1e+5, t = 1))
'GOK' = list(A = 1, b = 1, Et = 1, s10 = 5),
'BTS' = list(A = 1, Eu = 1, Et = 1, s10 = 5))

lower <- switch(
ITL_model,
'GOK' = c(0,0,0,0),
'BTS' = c(0,0,0,0))
'GOK' = c(0, 0, 0, 0),
'BTS' = c(0, 0, 0, 0))

upper <- switch(
ITL_model,
'GOK' = c(Inf,Inf,3,1e+20),
'BTS' = c(Inf,Inf,3,1e+20,Inf))

'GOK' = c(Inf, Inf, 3, 20),
'BTS' = c(Inf, 3, 3, 20))

## Fitting ----------------------------------------------------------------

## add the correct rhop value to the formula
FUN <- gsub(pattern = "rhop", replacement = rhop, x = FUN, fixed = TRUE)

## we have a double loop situation: we have a list with n samples, and
## each sample has n temperature steps
fit_list <- lapply(df_raw_list, function(s){

## extract temperatures
isoT <- unique(s$TEMP)

## run the fitting
tmp <- lapply(isoT, function(isoT){
## add the correct isoT to the formula based on the settings
FUN <- gsub(pattern = "isoT", replacement = isoT, x = FUN, fixed = TRUE)
## run the fitting at each temperature
tmp <- lapply(isoT, function(isoT) {

## extract data to fit
tmp_fitdata <- s[s$TEMP == isoT,]

## run fitting with different start parameters
fit <- try({
minpack.lm::nlsLM(
formula = as.formula(FUN),
data = data.frame(x = tmp_fitdata$TIME, y = tmp_fitdata$LxTx),
formula = if (ITL_model == "GOK") y ~ f_GOK(A, b, Et, s10, isoT, x)
else y ~ f_BTS(A, Eu, Et, s10, isoT, x),
data = data.frame(x = tmp_fitdata$TIME,
y = tmp_fitdata$LxTx,
isoT = isoT), # isoT gets recycled into a vector
start = start,
lower = lower,
upper = upper,
control = list(
maxiter = 500
maxiter = 500
),
trace = trace)
}, silent = TRUE)
Expand Down
4 changes: 2 additions & 2 deletions tests/testthat/test_fit_IsothermalHolding.R
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Original file line number Diff line number Diff line change
Expand Up @@ -22,10 +22,10 @@ test_that("input validation", {
test_that("check functionality", {
testthat::skip_on_cran()

expect_s4_class(fit_IsothermalHolding(input.csv[1], rhop = -7),
expect_s4_class(fit_IsothermalHolding(input.csv[1], rhop = 1e-7),
"RLum.Results")

data <- .import_ThermochronometryData(input.csv[1])
expect_s4_class(fit_IsothermalHolding(data, rhop = -7, mfrow = c(2, 2)),
expect_s4_class(fit_IsothermalHolding(data, rhop = 1e-7, mfrow = c(2, 2)),
"RLum.Results")
})
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