Filters cases based on the presence (or absence) of activities.
filter_activity_presence(
log,
activities = NULL,
method = c("all", "none", "one_of", "exact", "only"),
reverse = FALSE,
eventlog = deprecated()
)# S3 method for log
filter_activity_presence(
log,
activities = NULL,
method = c("all", "none", "one_of", "exact", "only"),
reverse = FALSE,
eventlog = deprecated()
)
# S3 method for grouped_log
filter_activity_presence(
log,
activities = NULL,
method = c("all", "none", "one_of", "exact", "only"),
reverse = FALSE,
eventlog = deprecated()
)
When given an object of type log
, it will return a filtered log
.
When given an object of type grouped_log
, the filter will be applied in a stratified way (i.e. each separately for each group).
The returned log will be grouped on the same variables as the original log.
log
: Object of class log
or derivatives (grouped_log
, eventlog
, activitylog
, etc.).
character
vector: Containing one or more activity identifiers.
character
(default "all"
): Filter method: "all"
(default), "none"
, "one_of"
, "exact"
,
or "only"
. For more information, see Details below.
logical
(default FALSE
): Indicating whether the selection should be reversed.
filter_activity_presence(log)
: Filters activities for a log
.
filter_activity_presence(grouped_log)
: Filters activities for a grouped_log
.
This functions allows to filter cases that contain certain activities. It requires as input a vector containing one or more activity labels
and it has a method
argument with following options:
"all"
means that all the specified activity labels must be present for a case to be selected.
"none"
means that they are not allowed to be present.
"one_of"
means that at least one of them must be present.
"exact"
means that only exactly these activities can be present (although multiple times and in random orderings).
"only"
means that only (a set of) these activities are allowed to be present.
When only one activity label is supplied, note that method
s "all"
and "one_of"
will be identical.
Swennen, M. (2018). Using Event Log Knowledge to Support Operational Exellence Techniques (Doctoral dissertation). Hasselt University.
Other filters:
filter_activity_frequency()
,
filter_activity_instance()
,
filter_activity()
,
filter_case_condition()
,
filter_case()
,
filter_endpoints_condition()
,
filter_endpoints()
,
filter_flow_time()
,
filter_idle_time()
,
filter_infrequent_flows()
,
filter_lifecycle_presence()
,
filter_lifecycle()
,
filter_precedence_condition()
,
filter_precedence_resource()
,
filter_precedence()
,
filter_processing_time()
,
filter_resource_frequency()
,
filter_resource()
,
filter_throughput_time()
,
filter_time_period()
,
filter_trace_frequency()
,
filter_trace_length()
,
filter_trace()
,
filter_trim_lifecycle()
,
filter_trim()