This document collects scripts for developing, bug-fixing and pre-release validating a specific function.
Found issues as for 2025-08-31:
If show.intervals = TRUE there is an unimportant “scale is overwritten” warning
There are too many warnings when values are omitted due to log scaling. One warning would be enough
If a simulated curve is used as input but no component given, the warnings are not helpful
ToDo:
Test if function works with background component
More tests for RLum input objects
Is the function successfully sourced?
library(OSLdecomposition)
library(ggplot2)
library(Luminescence)Welcome to the R package Luminescence version 1.1.0.9000-12 [Built: 2025-08-18 15:28:02 UTC]
A PhD supervisor: 'You are not depressive, you simply have a crappy life.'source("../R/plot_OSLcurve.R")
source("../R/plot_MultiExponential.R") # core functioncases <- list()
add_component_case <-
function(cases, lambda, n,
channel_width = 0.1,
channel_number = 400,
noise = 0,
background = 0,
reiterate = FALSE,
title = "Unspecified test case"){
components <- data.frame(name = paste("Component", 1:length(n)),
lambda = lambda,
n = n)
curve <- simulate_OSLcomponents(components,
channel.width = channel_width,
channel.number = channel_number,
simulate.curve = TRUE,
add.poisson.noise = TRUE,
add.gaussian.noise = noise,
add.background = background)
# Re-iterate components to add some uncertainty
if (reiterate) {
components <- decompose_OSLcurve(curve,
components,
verbose = FALSE)
}
case <- list(components = components,
curve = curve,
title = title)
cases <- c(cases, list(case))
return(cases)
}
cases <- add_component_case(cases,
lambda = c(1, 0.2, 0.02),
n = c(1000, 1000, 10000),
reiterate = TRUE,
title = "Typical quartz OSL curve")
cases <- add_component_case(cases,
lambda = c(2, 0.5, 0.2, 0.001),
n = c(200, -500, 2000, 100000),
channel_width = 0.875,
channel_number = 42,
title = "Atypical low-res measurement with stretched medium component")
cases <- add_component_case(cases,
lambda = c(0.1, 0.02),
n = c(-10e4, 10e5),
channel_width = 0.2,
channel_number = 200,
title = "Increasing signal")
cases <- add_component_case(cases,
lambda = c(1, 0.01),
n = c(10, 100),
noise = 10,
reiterate = TRUE,
title = "Background-corrected noise")
cases <- add_component_case(cases,
lambda = c(2, 0.5, 0.03, 0.001),
n = c(30e5, 2e6, -5e6, 5e8),
channel_width = 0.01,
channel_number = 5000,
title = "Sharp drop then complex, with many channels")for (case in cases) {
plot_OSLcurve(case$curve, case$components,
title = case$title)
cat("\n")
}
for (case in cases) {
plot_OSLcurve(case$curve, case$components,
show.legend = FALSE,
show.intervals = TRUE,
show.crosssec = TRUE,
show.initial = TRUE)
cat("\n")
}Scale for x is already present.
Adding another scale for x, which will replace the existing scale.
Scale for x is already present.
Adding another scale for x, which will replace the existing scale.
Vary the argument “display”. Vary also the ggplot2 themes
modes <- c("lin","compare_lin","log","compare_log","loglog","LM","res","tab","raw")
themes <- list(ggplot2::theme_minimal(),
ggplot2::theme_dark(),
ggplot2::theme_classic(),
ggplot2::theme_void(),
ggplot2::theme_gray(),
ggplot2::theme_linedraw(),
ggplot2::theme_bw())
for (display_mode in modes) {
case <- sample(cases, size = 1)[[1]] # Random case
cat("Display mode:", display_mode, "with case", case$title, "\n")
tryCatch({
plot_OSLcurve(case$curve, case$components,
display = display_mode,
show.legend = TRUE,
theme.set = sample(themes, size = 1)[[1]],
title = case$title)
},error = function(e) {message("FOUND ERROR", conditionMessage(e))})
cat("\n")
}Display mode: lin with case Increasing signal 
Display mode: compare_lin with case Atypical low-res measurement with stretched medium component 
Display mode: log with case Atypical low-res measurement with stretched medium component Input data contains signal components with negative intensity (increasing signals). These can not be displayed with logarithmic y-axis and are therefore omitted.Warning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.
Display mode: compare_log with case Atypical low-res measurement with stretched medium component Input data contains signal components with negative intensity (increasing signals). These can not be displayed with logarithmic y-axis and are therefore omitted.Warning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.
Display mode: loglog with case Background-corrected noise Input data contains signal components with negative intensity (increasing signals). These can not be displayed with logarithmic y-axis and are therefore omitted.Signal curve contains value equal/lower zero. Values below 0.1 will not be displayed.Warning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.Warning in transformation$transform(x): NaNs wurden erzeugtWarning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation introduced infinite values.
log-10 transformation introduced infinite values.Warning in transformation$transform(x): NaNs wurden erzeugtWarning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.Warning: Removed 24 rows containing missing values or values outside the scale range
(`geom_line()`).
Display mode: LM with case Background-corrected noise 
Display mode: res with case Increasing signal 
Display mode: tab with case Increasing signal 
Display mode: raw with case Increasing signal Input object 'curve' has more than two columns. Just the first two are used to define time and signal
# Repeat test but with
for (display_mode in modes) {
case <- sample(cases, size = 1)[[1]] # Random case
cat("Display mode:", display_mode, "with case", case$title, "\n")
tryCatch({
plot_OSLcurve(case$curve, case$components,
display = display_mode,
show.legend = FALSE,
show.intervals = TRUE,
theme.set = sample(themes, size = 1)[[1]])
},error = function(e) {message("FOUND ERROR", conditionMessage(e))})
cat("\n")
}Display mode: lin with case Increasing signal 
Display mode: compare_lin with case Increasing signal 
Display mode: log with case Atypical low-res measurement with stretched medium component Input data contains signal components with negative intensity (increasing signals). These can not be displayed with logarithmic y-axis and are therefore omitted.Warning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.
Display mode: compare_log with case Sharp drop then complex, with many channels Input data contains signal components with negative intensity (increasing signals). These can not be displayed with logarithmic y-axis and are therefore omitted.Warning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.
Display mode: loglog with case Increasing signal Input data contains signal components with negative intensity (increasing signals). These can not be displayed with logarithmic y-axis and are therefore omitted.Warning in ggplot2::scale_y_log10(limits = ylim): log-10 transformation
introduced infinite values.
Display mode: LM with case Typical quartz OSL curve 
Display mode: res with case Background-corrected noise Scale for x is already present.
Adding another scale for x, which will replace the existing scale.
Display mode: tab with case Typical quartz OSL curve 
Display mode: raw with case Increasing signal Input object 'curve' has more than two columns. Just the first two are used to define time and signal
# Create a simple curve with just one component
curve <- data.frame(
X = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12),
Y = c(377, 244, 163, 93, 59, 28, 17, 13, 10, 8, 9, 5))
# Perform fitting
components <- fit_OSLcurve(curve, F.threshold = 3, K.max = 2)
Decay rates (s^-1):
Cycle Comp. 1 Comp. 2 RSS F-value
K = 1 0.4594 359.9 Inf
K = 2 0.4594 0.4594 359.9 -4.76e-09
Left loop because F-test value (F = -4.76e-09) fell below threshold value (F = 3)
-> The F-test suggests the K = 1 model
Photoionisation cross sections (cm^2):
Cycle Comp. 1 Comp. 2
K = 1 6.47e-18 (Medium)
K = 2 6.47e-18 (Medium) 6.47e-18 (Medium.a)
-> Most known quartz OSL components found in the K = 2 model # Display results
plot_OSLcurve(curve, components)
# Load example data set
data_path <- system.file("examples",
"FB_10Gy_SAR.bin",
package = "OSLdecomposition")
data_set <- Luminescence::read_BIN2R(data_path,
fastForward = TRUE,
verbose = FALSE)
# Separate components
data_set_decomposed <- RLum.OSL_decomposition(data_set,
decay_rates = c(0.8, 0.05))STEP 2.1 ----- Define signal bin intervals -----
OSL curve template necessary but not given. Obtain and use global average curve:
[sum_OSLcurves()]: Built global average curve from arithmetic means from first 999 data points of all 154 OSL records
(time needed: 2.37 s)
Find intervals with lowest component cross correlation by maximising the denominator determinant in Cramers rule:
Maximum determinant = 0.7728 with interval dividing channels at i = 37
(time needed: 0.12 s)
STEP 2.2 ----- Decompose each OSL curve -----
Calculate signal intensity n in each OSL by ' det+nls ' algorithm with empiric error estimation
Table of input decay constants and signal bin intervals for [decompose_OSLcurve()]:
name lambda t.start t.end ch.start ch.end
1 Component 1 0.80 0.000000 3.696296 1 37
2 Component 2 0.05 3.696296 99.800003 38 999
...........
Successfully decomposed 154 records
(time needed: 0.95 s)cat("\nCase 1: Use raw RLum.Data.Curve as input\n")
Case 1: Use raw RLum.Data.Curve as inputplot_OSLcurve(data_set[[4]]@records[[1]])Warning in plot_OSLcurve(data_set[[4]]@records[[1]]): No component curve given
neither in 'components' nor in 'curve'. Set 'display' = 'raw'
cat("\nCase 2: Use decomposed RLum.Data.Curve as input\n")
Case 2: Use decomposed RLum.Data.Curve as inputplot_OSLcurve(data_set_decomposed[[4]]@records[[1]])
cat("\nCase 3: Use data matrix as input\n")
Case 3: Use data matrix as inputplot_OSLcurve(data_set_decomposed[[4]]@records[[1]]@data)Warning in plot_OSLcurve(data_set_decomposed[[4]]@records[[1]]@data): No
component curve given neither in 'components' nor in 'curve'. Set 'display' =
'raw'
cat("\nCase 4: Use invalid RLum object as input\n")
Case 4: Use invalid RLum object as inputtryCatch({plot_OSLcurve(data_set[[4]])},
error = function(e) {
message("TEST ERROR ", conditionMessage(e))
})TEST ERROR [plot_OSLcurve()] Error: Input object 'curve' is not of type 'RLum.Data.Curve' or 'data.frame' or 'matrix'!case <- sample(cases, size = 1)[[1]] # Random case
cat("\nCase 1: No component argument\n")
Case 1: No component argumenttryCatch({plot_OSLcurve(case$curve)},
error = function(e) {
message("TEST ERROR ", conditionMessage(e))
})Input object 'curve' has more than two columns. Just the first two are used to define time and signal
Input object 'curve' has more than two columns. Just the first two are used to define time and signal
cat("\nCase 2: No curve argument\n")
Case 2: No curve argumenttryCatch({plot_OSLcurve(component = case$component)},
error = function(e) {
message("TEST ERROR ", conditionMessage(e))
})
cat("\nCase 3: No arguments at all\n")
Case 3: No arguments at alltryCatch({plot_OSLcurve()},
error = function(e) {
message("TEST ERROR ", conditionMessage(e))
})TEST ERROR [plot_OSLcurve()]: Either 'curve' or 'components' must be definedcat("\nCase 4: Wrong argument\n")
Case 4: Wrong argumenttryCatch({plot_OSLcurve(case$component, case$curve)},
error = function(e) {
message("TEST ERROR ", conditionMessage(e))
})TEST ERROR nicht-numerisches Argument für binären Operatorcase <- sample(cases, size = 1)[[1]] # Random case
plot_obj <- plot_OSLcurve(case$curve, case$components, hide.plot = TRUE)
# Try to display by itself
plot_objTableGrob (15 x 2) "arrange": 4 grobs
z cells name grob
1 1 ( 1-10, 1- 1) arrange gtable[layout]
2 2 (11-15, 1- 1) arrange gtable[layout]
3 3 ( 1-10, 2- 2) arrange gtable[layout]
4 4 (11-15, 2- 2) arrange gtable[layout]# Try to display with print()
print(plot_obj)TableGrob (15 x 2) "arrange": 4 grobs
z cells name grob
1 1 ( 1-10, 1- 1) arrange gtable[layout]
2 2 (11-15, 1- 1) arrange gtable[layout]
3 3 ( 1-10, 2- 2) arrange gtable[layout]
4 4 (11-15, 2- 2) arrange gtable[layout]# Try to display with gridExtra function
gridExtra::grid.arrange(plot_obj)
The first plot is saved as PNG file and shown, the second plot is saved as PDF file and not shown. Both are saved in the working directory (D:/01_OSLdecomp/OSLdecomposition/module_tests). Please check and delete both files after executing this test.
file_name = paste0(getwd(), "/plot_OSLcurve_test.png")
cat("\nSave file:", file_name, "\n")
Save file: D:/01_OSLdecomp/OSLdecomposition/module_tests/plot_OSLcurve_test.png case <- sample(cases, size = 1)[[1]] # Random case
plot_OSLcurve(case$curve, case$components,
hide.plot = FALSE,
filename = file_name)
cat("\n")file_name = "plot_OSLcurve_test.pdf"
cat("\nSave file:", file_name, "\n")
Save file: plot_OSLcurve_test.pdf case <- sample(cases, size = 1)[[1]] # Random case
plot_OSLcurve(case$curve, case$components,
hide.plot = TRUE,
filename = file_name)
cat("\n")