View source: R/filter_precedence.R
filter_precedence | R Documentation |
Filters cases based on the precedence relations between two sets of activities.
filter_precedence(
log,
antecedents,
consequents,
precedence_type = c("directly_follows", "eventually_follows"),
filter_method = c("all", "one_of", "none"),
reverse = FALSE,
eventlog = deprecated()
)
## S3 method for class 'log'
filter_precedence(
log,
antecedents,
consequents,
precedence_type = c("directly_follows", "eventually_follows"),
filter_method = c("all", "one_of", "none"),
reverse = FALSE,
eventlog = deprecated()
)
## S3 method for class 'grouped_log'
filter_precedence(
log,
antecedents,
consequents,
precedence_type = c("directly_follows", "eventually_follows"),
filter_method = c("all", "one_of", "none"),
reverse = FALSE,
eventlog = deprecated()
)
log |
|
antecedents, consequents |
|
precedence_type |
|
filter_method |
|
reverse |
|
eventlog |
In order to extract a subset of an event log which conforms with a set of precedence rules, one can use the filter_precedence
method.
There are two types of precendence relations which can be tested: activities that should directly follow ("directly_follows"
) each other,
or activities that should eventually follow ("eventually_follows"
) each other. The type can be set with the precedence_type
argument.
Further, the filter requires a vector of one or more antecedents
(containing activity labels), and one or more consequents
.
Finally, a filter_method
argument can be set. This argument is relevant when there is more than one antecedent or consequent.
In such a case, you can specify that all possible precedence combinations must be present ("all"
),
at least one of them ("one_of"
), or none ("none"
).
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.
filter_precedence(log)
: Filters cases for a log
.
filter_precedence(grouped_log)
: Filters cases for a grouped_log
.
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_presence()
,
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_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()
eventdataR::patients %>%
filter_precedence(antecedents = "Triage and Assessment",
consequents = "Blood test",
precedence_type = "directly_follows") %>%
bupaR::traces()
eventdataR::patients %>%
filter_precedence(antecedents = "Triage and Assessment",
consequents = c("Blood test", "X-Ray", "MRI SCAN"),
precedence_type = "eventually_follows",
filter_method = "one_of") %>%
bupaR::traces()
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