## Introduction

The function process_map can be used very easily to create a process map of an event log. Below, an example of a process map for the patients event log can be found.

library(bupaR)
patients %>%
process_map()

## Map profiles

### Frequency profile

By default, the process map is annotated with frequencies of activities and flows. The is what is called the frequency profile, and can be created explicitly using the frequency function. This function has a value argument, which can be used to adjust the frequencies shown, for instance using relative frequencies instead of the default absolute ones.

patients %>%
process_map(type = frequency("relative"))

### Performance profile

Instead of a frequency profile, one can also use a performance profile, focussing on processing time of activities. The performance profile has two arguments: the FUN argument to specific the function to apply on the processing time (e.g. min, max, mean, median, etc.), and the units argument to specificy the time unit to be used.

patients %>%
process_map(performance(median, "days"))

## Simplifying process maps

When event logs get larger, they will also become more unstructured, making the process maps illegible and expensive to computate. In such cases, it is useful to apply them on a simplified version of the event log, using one or more of the subsetting method provided by edeaR.

## Customizing Process Maps

The process_map function has a render argument, which, if set to FALSE, returns a raw dgr_graph from the DiagrammeR package, which can if needed be further customized, and subsequently rendered. For more information about DiagrammeR, please check their website

patients %>%
process_map(render = F)