Calculates for each activity type in what percentage of cases it is present.
Usage
activity_presence(
log,
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
# S3 method for class 'eventlog'
activity_presence(
log,
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
# S3 method for class 'grouped_eventlog'
activity_presence(
log,
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
# S3 method for class 'activitylog'
activity_presence(
log,
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
# S3 method for class 'grouped_activitylog'
activity_presence(
log,
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
Arguments
- log
log
: Object of classlog
or derivatives (grouped_log
,eventlog
,activitylog
, etc.).- append
logical
(defaultFALSE
) : The argumentsappend
andappend_column
have been deprecated in favour ofaugment
.
Indicating whether to append results to original log. Ignored when level is"log"
or"trace"
.- append_column
The arguments
append
andappend_column
have been deprecated in favour ofaugment
.
Which of the output columns to append to log, ifappend = TRUE
. Default column depends on chosen level.- sort
logical
(defaultTRUE
): Sort output on count. Only for levels with frequency count output.- eventlog
Details
An indication of variance can be the presence of the activities in the different cases. This metric shows for each activity the absolute number of cases in which each activity occurs together with its relative presence.
Methods (by class)
activity_presence(eventlog)
: Compute activity presence for aneventlog
.activity_presence(grouped_eventlog)
: Compute activity presence for agrouped_eventlog
.activity_presence(activitylog)
: Compute activity presence for anactivitylog
.activity_presence(grouped_activitylog)
: Compute activity presence for agrouped_activitylog
.
References
Swennen, M. (2018). Using Event Log Knowledge to Support Operational Exellence Techniques (Doctoral dissertation). Hasselt University.
See also
Other metrics:
activity_frequency()
,
end_activities()
,
idle_time()
,
number_of_repetitions()
,
number_of_selfloops()
,
number_of_traces()
,
processing_time()
,
resource_frequency()
,
resource_involvement()
,
resource_specialisation()
,
start_activities()
,
throughput_time()
,
trace_coverage()
,
trace_length()
Examples
if (FALSE) { # \dontrun{
data <- data.frame(case = rep("A",5),
activity_id = c("A","B","C","D","E"),
activity_instance_id = 1:5,
lifecycle_id = rep("complete",5),
timestamp = 1:5,
resource = rep("resource 1", 5))
log <- bupaR::eventlog(data,case_id = "case",
activity_id = "activity_id",
activity_instance_id = "activity_instance_id",
lifecycle_id = "lifecycle_id",
timestamp = "timestamp",
resource_id = "resource")
activity_presence(log)
} # }