plot_FilterCombinations {Luminescence}

Plot filter combinations along with the (optional) net transmission window

Description

The function allows to plot transmission windows for different filters. Missing data for specific wavelengths are automatically interpolated for the given filter data using the function approx. With that a standardised output is reached and a net transmission window can be shown.

Usage

plot_FilterCombinations(
  filters,
  wavelength_range = 200:1000,
  show_net_transmission = TRUE,
  interactive = FALSE,
  plot = TRUE,
  ...
)

Arguments

filters

list (required): a named list of filter data for each filter to be shown. The filter data itself should be either provided as data.frame or matrix. (for more options s. Details)

wavelength_range

numeric (with default): wavelength range used for the interpolation

show_net_transmission

logical (with default): show net transmission window as polygon.

interactive

logical (with default): enable/disable interactive plot

plot

logical (with default): enables or disables the plot output

...

further arguments that can be passed to control the plot output. Supported are main, xlab, ylab, xlim, ylim, type, lty, lwd. For non common plotting parameters see the details section.

Details

Calculations

Net transmission window

The net transmission window of two filters is approximated by

T_{final} = T_{1} * T_{2}

Optical density

OD = -log10(T)

Total optical density

OD_{total} = OD_{1} + OD_{2}

Please consider using own calculations for more precise values.

How to provide input data?

CASE 1

The function expects that all filter values are either of type matrix or data.frame with two columns. The first columns contains the wavelength, the second the relative transmission (but not in percentage, i.e. the maximum transmission can be only become 1).

In this case only the transmission window is show as provided. Changes in filter thickness and reflection factor are not considered.

CASE 2

The filter data itself are provided as list element containing a matrix or data.frame and additional information on the thickness of the filter, e.g., list(filter1 = list(filter_matrix, d = 2)). The given filter data are always considered as standard input and the filter thickness value is taken into account by

Transmission = Transmission^(d)

with d given in the same dimension as the original filter data.

CASE 3

Same as CASE 2 but additionally a reflection factor P is provided, e.g., list(filter1 = list(filter_matrix, d = 2, P = 0.9)). The final transmission becomes:

Transmission = Transmission^(d) * P

Advanced plotting parameters

The following further non-common plotting parameters can be passed to the function:

Argument	Datatype	Description
legend	logical	enable/disable legend
legend.pos	character	change legend position (graphics::legend)
legend.text	character	same as the argument legend in (graphics::legend)
net_transmission.col	col	colour of net transmission window polygon
net_transmission.col_lines	col	colour of net transmission window polygon lines
net_transmission.density	numeric	specify line density in the transmission polygon
grid	list	full list of arguments that can be passed to the function graphics::grid

For further modifications standard additional R plot functions are recommend, e.g., the legend can be fully customised by disabling the standard legend and use the function graphics::legend instead.

Value

Returns an S4 object of type RLum.Results.

@data

Object	Type Description
net_transmission_window	matrix	the resulting net transmission window
OD_total	matrix	the total optical density
filter_matrix	matrix	the filter matrix used for plotting

@info

Object	Type Description
call	call	the original function call

Function version

0.3.2

How to cite

Kreutzer, S., 2023. plot_FilterCombinations(): Plot filter combinations along with the (optional) net transmission window. Function version 0.3.2. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Philippe, A., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., Galharret, J., 2023. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.23. https://CRAN.R-project.org/package=Luminescence

Author(s)

Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany) , RLum Developer Team

See Also

RLum.Results, approx

Examples

## (For legal reasons no real filter data are provided)

## Create filter sets
filter1 <- density(rnorm(100, mean = 450, sd = 20))
filter1 <- matrix(c(filter1$x, filter1$y/max(filter1$y)), ncol = 2)
filter2 <- matrix(c(200:799,rep(c(0,0.8,0),each = 200)), ncol = 2)

## Example 1 (standard)
plot_FilterCombinations(filters = list(filter1, filter2))

## Example 2 (with d and P value and name for filter 2)
results <- plot_FilterCombinations(
filters = list(filter_1 = filter1, Rectangle = list(filter2, d = 2, P = 0.6)))
results

## Example 3 show optical density
plot(results$OD_total)

## Not run: 
##Example 4
##show the filters using the interactive mode
plot_FilterCombinations(filters = list(filter1, filter2), interactive = TRUE)


## End(Not run)