Conformance between an Event Log and a Petri net

Conformance between an Event Log and a Petri net

conformance_alignment(
  eventlog,
  petrinet,
  initial_marking,
  final_marking,
  parameters = default_parameters(eventlog),
  variant = variant_state_equation_a_star(),
  convert = TRUE
)

variant_state_equation_a_star()

variant_dijkstra_no_heuristics()

Arguments

eventlog	A bupaR or PM4PY event log.
petrinet	A bupaR or PM4PY Petri net.
initial_marking	A R vector with the place identifiers of the initial marking or a PM4PY marking. By default the initial marking of the bupaR Petri net will be used if available.
final_marking	A R vector with the place identifiers of the final marking or a PM4PY marking.
parameters	PM4PY conformance parameter. By default the activity_key from the bupaR event log is specified using param_activity_key.
variant	The conformance variant to be used.
convert	TRUE to automatically convert Python objects to their R equivalent. If you pass FALSE you can do manual conversion using the r-py-conversion function.

Value

A data frame describing the conformance result. In case of conformance_alignment a data frame of log and model moves.

Examples

if (pm4py_available()) {
  library(eventdataR)
  data(patients)

  # As Inductive Miner of PM4Py is not life-cycle aware, keep only `complete` events:
  patients_completes <- patients[patients$registration_type == "complete", ]

  # Discover a Petri net
  net <- discovery_inductive(patients_completes)

  # Align event log and Petri net
  a <- conformance_alignment(patients_completes,
                             net$petrinet,
                             net$initial_marking,
                             net$final_marking)

  # Alignment is returned as data frame
  head(a)
}
#>   case_id                    log_id                             model_id
#> 1       1          t_Registration_0 d19b8727-77ea-4a83-8046-6acda08c08b8
#> 2       1 t_Triage and Assessment_1 e44ad74a-e132-4bc5-bbc3-16175413b845
#> 3       1            t_Blood test_2 cd199d8d-f067-4a85-afc1-414b1339b8b0
#> 4       1              t_MRI SCAN_3 28f48800-0941-4a8a-82c4-fbe5953bea8b
#> 5       1                        >>                               skip_3
#> 6       1       t_Discuss Results_4 5e749531-3434-4d69-9ffc-faa2bb012396
#>               log_label           model_label cost visited_states queued_states
#> 1          Registration          Registration    1              7            23
#> 2 Triage and Assessment Triage and Assessment    1              7            23
#> 3            Blood test            Blood test    1              7            23
#> 4              MRI SCAN              MRI SCAN    1              7            23
#> 5                    >>                  <NA>    1              7            23
#> 6       Discuss Results       Discuss Results    1              7            23
#>   traversed_arcs fitness
#> 1             23       1
#> 2             23       1
#> 3             23       1
#> 4             23       1
#> 5             23       1
#> 6             23       1