« For users with little or no experience with command-lines (CLI) a graphical user interface (GUI) offers intuitive access that counteracts the perceived steep learning curve of a CLI »

Burow et al. (2016)

  Creating a plot: a common task in R

Hello Shiny!

Input Widgets

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to

« Sharing shiny applications is simple and there are multiple ways to do so! »

An enthuastic sales representative


Motivation

  • Make Luminescence more accessible

  • Streamline common tasks
    (eg. plotting data)

  • Lay the foundation for a common analysis platform
    (see Shiny-Server)

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Current content of RLumShiny (v0.2.1)


« [...] 'shiny' is based on modern programming and markup languages, which allows easy integration of existing JavaScript libraries, thus greatly increasing the capabilities of 'shiny' and R itself. »

Burow et al. (2016)

RLumShiny::jscolorInput()

jscolorInput(inputId, label, value, position = 'bottom', color = 'transparent', mode = 'HSV', slider = TRUE, close = FALSE)

Binding to the JavaScript library jscolor (http://jscolor.com/) to create a JSColor (Javascript/HTML Color Picker) widget.


                        

RLumShiny::popover()

popover(title, content, header = NULL, html = TRUE, class = 'btn btn-default', placement = c('right', 'top', 'left', 'bottom'), trigger = c('click', 'hover', 'focus', 'manual'))

Create a bootstrap button with popover, i.e. a small overlays of content for housing secondary information.

Click me!

RLumShiny::tooltip()

tooltip(refId, text, attr = NULL, animation = TRUE, delay = 100, html = TRUE, placement = 'auto', trigger = 'hover')

Create bootstrap tooltips for any HTML element to be used in shiny applications.

« R allows the creation of complex and transparent data analysis routines for experimental protocols that are not available in existing software. »

Kreutzer et al. (2012)

Why?

For routine luminescence dating applications the commonly used [measurement devices] are bundled with analysis software, such as Viewer or Analyst. These software solutions are appropriate for most of the regular dating and publication jobs, and enable assessment of luminescence characteristics and provide basic statistical data treatment. However, for further statistical analysis and data treatments, this software may reach its limits. In such cases, open programming languages are a more appropriate approach.
modified after Kreutzer et al. (2012)

A potpourri of functions

Since its release in 2012 the functionality of the R package Luminescence drastically increased. What started with a handful of functions to apply a very specific type of signal analysis and to plot the data is now a collection of >100 functions for all sorts of (non-)specialised tasks.

Current content of Luminescence (v0.8.0)

Statistics

It is generally hard to measure and keep track of the distribution and reception of the R package Luminescence (or RLumShiny). The official CRAN download statistics, however, may provide at least some indication on how many and where people are using our package. The data you see on the right-hand side are generated from the raw CRAN logs.

A collection of useful resources

This presentation

The code of this presentation is freely available on GitHub