Much of the work that took place during the Luminescence 1.1.0 timeframe was devoted to adding new features to RLumShiny, the graphical interface to Luminescence built on the Shiny framework. We see this package as a good entry point to become acquainted with some of the functions provided by Luminescence and their various options.

Our work for the RLumShiny 0.2.5 release concentrated on adding a bunch of new apps:

• aliquotsize to either estimate the number of grains on an aliquot or to compute the packing density (based on calc_AliquotSize());

Only about 3 months from our previous release, we are happy to announce the release of version 1.1.0 of Luminescence R package. This is a major release, which comes with a few new features and many improvements, especially on the graphical side. In total we addressed 99 issues in 530 commits.

Many of the changes came from our work on the RLumShiny package, which made us consider in much greater detail some of the Luminescence functions. We will shortly bring what we think are exciting news on the RLumShiny side, but for the moment, let’s concentrate on what happened during this release cycle.

One of the hard lessons you have to learn as a package developer is that users usually do not care much about what you may have had in mind when writing a function. When we introduced the RLum-class object structure in 'Luminescence' in version 0.4.0 in December 2014 (more than ten years ago!), we had little doubt that it would be highly welcomed by users, as it streamlines their analysis pipelines. As a matter of fact, little is happening today in the package without this object structure, at least from a developer’s perspective.

One of the goals of the REPLAY project is to facilitate interfacing with the Luminescence package. This is a rather ambitious goal, but luckily there is already something available to make the use of Luminescence more direct and approachable.

The RLumShiny package integrates a bunch of Luminescence functions into a web-based app built on top of the shiny framework. This allows the users to work interactively with their data, letting them explore the available options and see how they affect the plots and results. This provides an easy entry point to discover what the package provides while performing an analysis of interest, or perhaps just playing around with sample data.

With the release of version 1.0 still very fresh, we are announcing the release of version 1.0.1, the first maintenance release of the Luminescence R package. This is a minor release meant to address one important regression, but it also brings a few additional robustness and correctness improvements. In total we addressed 13 issues in 53 commits.

We are happy to announce that the Luminescence R package has finally reached version 1.0.0. This is an important milestone, not only in the history of the Luminescence package, but also for the REPLAY project.

This makes it the third release since the start of the REPLAY project:

• Version 0.9.25 was released in September 2024, just over a month into the project, and it already contained a large number of changes (422 commits)

• Version 0.9.26 was a minor release (73 commits) to fix a couple of small regressions that we didn’t want to affect our first REPLAY webinar

• Version 1.0.0 contains most of the work that has occurred between September and February (886 commits) in a number of key areas, which we’ll outline below.

We have finally launched the website for the REPLAY project. We will use it to report on the progress of the project, to inform about webinars and other training opportunities, and to discuss some details concerning the development of the Luminescence package.

At the moment the site is still sparse, but we’ll populate it on a regular basis. In the meantime, you can read our About page, which describes the aims and goals of the REPLAY project.