Flexible token replay animation for process maps created by bupaR using SVG animations.
Flexible token replay animation for process maps created through the processmapR package from the bupaR suite, which uses DiagrammeR and viz.js library to render process maps using GraphViz. As alternative renderer Leaflet with fixed coordinates for activities is also supported.
ProcessanimateR provides a htmlwidget using SVG animations (SMIL) to create the animation. Sizes, colors, and many more aspects of the token shapes are customizable based on trace, event attributes, or a secondary data frame if an attribute does not change according to the original event log.
WARNING: There are breaking changes in the API of this package between v0.3.0 and v1.0.0
A stable version of ProcessanimateR can be installed from CRAN:
You can also use the development or specific released version by using the remotes package. Note that the current development version may break without warning.
We use the
patients event log provided by the
A basic animation with static color and token size:
Default token color, size, or image can be changed as follows:
animate_process(example_log, mapping = token_aes(size = token_scale(12), shape = "rect")) animate_process(example_log, mapping = token_aes(color = token_scale("red")))
The example animation on the top of this site:
animate_process(patients, mode = "relative", jitter = 10, legend = "color", mapping = token_aes(color = token_scale("employee", scale = "ordinal", range = RColorBrewer::brewer.pal(7, "Paired"))))
Tokens can also be assigned images, for example:
animate_process(example_log, mapping = token_aes(shape = "image", size = token_scale(10), image = token_scale("https://upload.wikimedia.org/wikipedia/en/5/5f/Pacman.gif")))
More advanced usage examples can be found here.
This package makes use of the following libraries:
This software is licensed under the MIT License - see the LICENSE file for details.
This software was partly supported by the HUMAN project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 723737 (HUMAN)