Performance profile


Instead of a frequencies, process maps can also be used to visualize performance of the process, by using performance() to configure the map, instead of frequency().

patients %>%

There are three different parameters specific to the performance() configuration: the aggregation function, the time units, and the flow time type.

Aggregation function

The FUN argument specifies the aggregation function to apply on the processing time (e.g. min, max, mean, median, etc.). By default, the mean durations are shown. We can adjust this to the maximum, for example.

patients %>%
    process_map(performance(FUN = max))

Any function that takes a numerical vector and returns a single value can be used. For example, let’s say we want to show the 0.90 percentile.

p90 <- function(x, ...) {
    quantile(x, probs = 0.9, ...)

patients %>%
    process_map(performance(FUN = p90))

Note that the ... is mandatory as process_map() will automatically add na.rm = T to the aggregation function call.

Time units

The units argument allows to specify the time units to be used.

patients %>%
    process_map(performance(mean, "days"))
patients %>%
    process_map(performance(mean, "hours"))

Flow time type

Finally, you can set the flowt_time argument.

There are two different duration types that can be displayed on the edges:

  • idle_time: the time between the end of the source activity, and the start of the target activity. Can be negative if the source activity overlaps with the target activity.
  • inter_start_time: the time between the start of the source- and target activities, including the duration of the from-activity.

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