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v0.9.18 (CRAN)
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@RLumSK RLumSK released this 17 Jan 19:25
· 1287 commits to master since this release
v0.9.18
da74d1c

Changes in version 0.9.18 (2022-01-17)

This package version requires R >= 4.0.5

Breaking changes

Changes in RLum.Data.Image and removal of import 'raster'

The S4 class RLum.Data.Image was heavily revised to strip
'Luminescence' of the dependency to the package 'raster' and replace
the functionality with base R functions and objects. The 'raster'
package came in at an early stage of 'Luminescence' to handle image
data. However, most of its massive feature set was never used, but
'raster' caused a lot of trouble to many users and in our automated
tests because of its own dependencies. Soon, 'raster' will be retired
and replaced by an even more powerful package called 'terra'. This was
our cue to make some serious changes instead of carrying forward this
unfortunate implementation in 'Luminescence'.

  • Within the RLum.Data.Image-class image data are now stored in an
    array instead of a RasterBrick object.
  • The function plot_RLum.Data.Image() does not know any more about a
    plot type plotRGB. However, the standard raster plot was even
    improved. Please watch out, however, for changed arguments.
  • The image format import functions read_SPE2R() and read_TIFF2R()
    were modified to support the new class design.
  • The corresponding example dataset was updated.

Removal of app_RLum()

This function was essentially a wrapper around RLumShiny::app_RLum()
written to promote 'RLumShiny'; a package providing a graphical user
interface to 'Luminescence'. 'Luminescence' is essential for
'RLumShiny'. However, this two-way dependency caused unwanted trouble
once the package 'raster' was removed. By removing app_RLum()
'Luminescence' comes lighter because it has fewer dependencies this
unfortunate reverse dependency can be avoided. RLumShiny::app_RLum()
will still work as before, but it cannot be called anymore out of
'Luminescence'. In summary, except for one function less, not much has
changed since both packages need to be installed to run the shiny
applications.

Bugfixes and changes

convert_Activity2Concentration()

  • The function had had-coded conversion factors, now the factors are
    calculated, making it easier to include new data, such as updated
    half-life values.
  • The documentation is extended and should now be read more clear.

use_DRAC()

  • The function now supports up to 5000 datasets, instead of before 33.
    The function template_DRAC() was revised accordingly.
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