feat(pm4py): disable IM fallthroughs in the simplified interface

pm4py/discovery.py

@@ -275,7 +275,7 @@ def discover_petri_net_alpha_plus(log: Union[EventLog, pd.DataFrame], activity_k
     return alpha_miner.apply(log, variant=alpha_miner.Variants.ALPHA_VERSION_PLUS, parameters=get_properties(log, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key))
 
 
-def discover_petri_net_inductive(log: Union[EventLog, pd.DataFrame, DFG], multi_processing: bool = constants.ENABLE_MULTIPROCESSING_DEFAULT, noise_threshold: float = 0.0, activity_key: str = "concept:name", timestamp_key: str = "time:timestamp", case_id_key: str = "case:concept:name") -> Tuple[
+def discover_petri_net_inductive(log: Union[EventLog, pd.DataFrame, DFG], multi_processing: bool = constants.ENABLE_MULTIPROCESSING_DEFAULT, noise_threshold: float = 0.0, activity_key: str = "concept:name", timestamp_key: str = "time:timestamp", case_id_key: str = "case:concept:name", disable_fallthroughs: bool = False) -> Tuple[
         PetriNet, Marking, Marking]:
     """
     Discovers a Petri net using the inductive miner algorithm.
@@ -290,6 +290,7 @@ def discover_petri_net_inductive(log: Union[EventLog, pd.DataFrame, DFG], multi_
     :param activity_key: attribute to be used for the activity
     :param timestamp_key: attribute to be used for the timestamp
     :param case_id_key: attribute to be used as case identifier
+    :param disable_fallthroughs: disable the Inductive Miner fall-throughs
     :rtype: ``Tuple[PetriNet, Marking, Marking]``
 
     .. code-block:: python3
@@ -308,7 +309,7 @@ def discover_petri_net_inductive(log: Union[EventLog, pd.DataFrame, DFG], multi_
             log, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key)
 
     pt = discover_process_tree_inductive(
-        log, noise_threshold, multi_processing=multi_processing, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key)
+        log, noise_threshold, multi_processing=multi_processing, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key, disable_fallthroughs=disable_fallthroughs)
     from pm4py.convert import convert_to_petri_net
     return convert_to_petri_net(pt)
 
@@ -357,7 +358,7 @@ def discover_petri_net_heuristics(log: Union[EventLog, pd.DataFrame], dependency
         return heuristics_miner.apply(log, parameters=parameters)
 
 
-def discover_process_tree_inductive(log: Union[EventLog, pd.DataFrame, DFG], noise_threshold: float = 0.0, multi_processing: bool = constants.ENABLE_MULTIPROCESSING_DEFAULT, activity_key: str = "concept:name", timestamp_key: str = "time:timestamp", case_id_key: str = "case:concept:name") -> ProcessTree:
+def discover_process_tree_inductive(log: Union[EventLog, pd.DataFrame, DFG], noise_threshold: float = 0.0, multi_processing: bool = constants.ENABLE_MULTIPROCESSING_DEFAULT, activity_key: str = "concept:name", timestamp_key: str = "time:timestamp", case_id_key: str = "case:concept:name", disable_fallthroughs: bool = False) -> ProcessTree:
     """
     Discovers a process tree using the inductive miner algorithm
 
@@ -371,6 +372,7 @@ def discover_process_tree_inductive(log: Union[EventLog, pd.DataFrame, DFG], noi
     :param multi_processing: boolean that enables/disables multiprocessing in inductive miner
     :param timestamp_key: attribute to be used for the timestamp
     :param case_id_key: attribute to be used as case identifier
+    :param disable_fallthroughs: disable the Inductive Miner fall-throughs
     :rtype: ``ProcessTree``
 
     .. code-block:: python3
@@ -393,6 +395,7 @@ def discover_process_tree_inductive(log: Union[EventLog, pd.DataFrame, DFG], noi
         log, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key)
     parameters["noise_threshold"] = noise_threshold
     parameters["multiprocessing"] = multi_processing
+    parameters["disable_fallthroughs"] = disable_fallthroughs
 
     variant = inductive_miner.Variants.IMf if noise_threshold > 0 else inductive_miner.Variants.IM
 
@@ -539,7 +542,7 @@ def discover_eventually_follows_graph(log: Union[EventLog, pd.DataFrame], activi
         return get.apply(log, parameters=properties)
 
 
-def discover_bpmn_inductive(log: Union[EventLog, pd.DataFrame, DFG], noise_threshold: float = 0.0, multi_processing: bool = constants.ENABLE_MULTIPROCESSING_DEFAULT, activity_key: str = "concept:name", timestamp_key: str = "time:timestamp", case_id_key: str = "case:concept:name") -> BPMN:
+def discover_bpmn_inductive(log: Union[EventLog, pd.DataFrame, DFG], noise_threshold: float = 0.0, multi_processing: bool = constants.ENABLE_MULTIPROCESSING_DEFAULT, activity_key: str = "concept:name", timestamp_key: str = "time:timestamp", case_id_key: str = "case:concept:name", disable_fallthroughs: bool = False) -> BPMN:
     """
     Discovers a BPMN using the Inductive Miner algorithm
 
@@ -553,6 +556,7 @@ def discover_bpmn_inductive(log: Union[EventLog, pd.DataFrame, DFG], noise_thres
     :param activity_key: attribute to be used for the activity
     :param timestamp_key: attribute to be used for the timestamp
     :param case_id_key: attribute to be used as case identifier
+    :param disable_fallthroughs: disable the Inductive Miner fall-throughs
     :rtype: ``BPMN``
 
     .. code-block:: python3
@@ -571,7 +575,7 @@ def discover_bpmn_inductive(log: Union[EventLog, pd.DataFrame, DFG], noise_thres
             log, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key)
 
     pt = discover_process_tree_inductive(
-        log, noise_threshold, multi_processing=multi_processing, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key)
+        log, noise_threshold, multi_processing=multi_processing, activity_key=activity_key, timestamp_key=timestamp_key, case_id_key=case_id_key, disable_fallthroughs=disable_fallthroughs)
     from pm4py.convert import convert_to_bpmn
     return convert_to_bpmn(pt)