Merge remote-tracking branch 'upstream/hotfixes' into release

process-intelligence-solutions · Nov 15, 2023 · 0aaa4bc · 0aaa4bc
2 parents 55c2912 + cc1db31
commit 0aaa4bc
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diff --git a/pm4py/analysis.py b/pm4py/analysis.py
@@ -207,8 +207,6 @@ def cluster_log(log: Union[EventLog, EventStream, pd.DataFrame], sklearn_cluster
         for clust_log in pm4py.cluster_log(df):
             print(clust_log)
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception(
-        "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     properties = get_properties(log, activity_key=activity_key, case_id_key=case_id_key, timestamp_key=timestamp_key)
@@ -237,8 +235,6 @@ def insert_artificial_start_end(log: Union[EventLog, pd.DataFrame], activity_key
 
         dataframe = pm4py.insert_artificial_start_end(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception(
-        "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     properties = get_properties(log, activity_key=activity_key, case_id_key=case_id_key, timestamp_key=timestamp_key)
@@ -278,8 +274,6 @@ def insert_case_service_waiting_time(log: Union[EventLog, pd.DataFrame], service
 
         dataframe = pm4py.insert_case_service_waiting_time(dataframe, activity_key='concept:name', timestamp_key='time:timestamp', case_id_key='case:concept:name', start_timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception(
-        "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     properties = get_properties(log, activity_key=activity_key, case_id_key=case_id_key, timestamp_key=timestamp_key)
@@ -313,8 +307,6 @@ def insert_case_arrival_finish_rate(log: Union[EventLog, pd.DataFrame], arrival_
 
         dataframe = pm4py.insert_case_arrival_finish_rate(dataframe, activity_key='concept:name', timestamp_key='time:timestamp', case_id_key='case:concept:name', start_timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception(
-        "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     properties = get_properties(log, activity_key=activity_key, case_id_key=case_id_key, timestamp_key=timestamp_key)

diff --git a/pm4py/conformance.py b/pm4py/conformance.py
@@ -80,7 +80,6 @@ def conformance_diagnostics_token_based_replay(log: Union[EventLog, pd.DataFrame
         net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         tbr_diagnostics = pm4py.conformance_diagnostics_token_based_replay(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -143,7 +142,6 @@ def conformance_diagnostics_alignments(log: Union[EventLog, pd.DataFrame], *args
         net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         alignments_diagnostics = pm4py.conformance_diagnostics_alignments(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -241,7 +239,6 @@ def fitness_token_based_replay(log: Union[EventLog, pd.DataFrame], petri_net: Pe
         net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         fitness_tbr = pm4py.fitness_token_based_replay(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -291,7 +288,6 @@ def fitness_alignments(log: Union[EventLog, pd.DataFrame], petri_net: PetriNet,
         net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         fitness_alignments = pm4py.fitness_alignments(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -338,7 +334,6 @@ def precision_token_based_replay(log: Union[EventLog, pd.DataFrame], petri_net:
         net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         precision_tbr = pm4py.precision_token_based_replay(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -388,7 +383,6 @@ def precision_alignments(log: Union[EventLog, pd.DataFrame], petri_net: PetriNet
         net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         precision_alignments = pm4py.precision_alignments(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -666,7 +660,6 @@ def conformance_temporal_profile(log: Union[EventLog, pd.DataFrame], temporal_pr
         temporal_profile = pm4py.discover_temporal_profile(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         conformance_temporal_profile = pm4py.conformance_temporal_profile(dataframe, temporal_profile, zeta=1, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -707,8 +700,6 @@ def conformance_declare(log: Union[EventLog, pd.DataFrame], declare_model: Dict[
         declare_model = pm4py.discover_declare(log)
         conf_result = pm4py.conformance_declare(log, declare_model)
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception(
-        "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):
@@ -769,7 +760,6 @@ def conformance_log_skeleton(log: Union[EventLog, pd.DataFrame], log_skeleton: D
         log_skeleton = pm4py.discover_log_skeleton(dataframe, noise_threshold=0.1, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
         conformance_lsk = pm4py.conformance_log_skeleton(dataframe, log_skeleton, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if check_is_pandas_dataframe(log):

diff --git a/pm4py/convert.py b/pm4py/convert.py
@@ -55,7 +55,6 @@ def convert_to_event_log(obj: Union[pd.DataFrame, EventStream], case_id_key: str
        dataframe = pm4py.format_dataframe(dataframe, case_id_column='case:concept:name', activity_column='concept:name', timestamp_column='time:timestamp')
        log = pm4py.convert_to_event_log(dataframe)
     """
-    if type(obj) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
 
     if check_is_pandas_dataframe(obj):
         check_pandas_dataframe_columns(obj, case_id_key=case_id_key)
@@ -88,8 +87,6 @@ def convert_to_event_stream(obj: Union[EventLog, pd.DataFrame], case_id_key: str
        event_stream = pm4py.convert_to_event_stream(log)
 
     """
-    if type(obj) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
-
     if check_is_pandas_dataframe(obj):
         check_pandas_dataframe_columns(obj, case_id_key=case_id_key)
 
@@ -119,8 +116,6 @@ def convert_to_dataframe(obj: Union[EventStream, EventLog], **kwargs) -> pd.Data
        log = pm4py.read_xes("tests/input_data/running-example.xes")
        dataframe = pm4py.convert_to_dataframe(log)
     """
-    if type(obj) not in [pd.DataFrame, EventLog, EventStream]: raise Exception("the method can be applied only to a traditional event log!")
-
     if check_is_pandas_dataframe(obj):
         check_pandas_dataframe_columns(obj)
 
@@ -299,9 +294,6 @@ def convert_log_to_ocel(log: Union[EventLog, EventStream, pd.DataFrame], activit
         ocel = pm4py.convert_log_to_ocel(log, activity_column='concept:name', timestamp_column='time:timestamp',
                         object_types=['case:concept:name'])
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]:
-        raise Exception(
-            "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     if isinstance(log, EventStream):
@@ -392,8 +384,6 @@ def convert_log_to_time_intervals(log: Union[EventLog, pd.DataFrame], filter_act
         time_intervals = pm4py.convert_log_to_time_intervals(log, ('Confirmation of receipt', 'T02 Check confirmation of receipt'))
         print(len(time_intervals))
     """
-    if type(log) not in [pd.DataFrame, EventLog, EventStream]: raise Exception(
-        "the method can be applied only to a traditional event log!")
     __event_log_deprecation_warning(log)
 
     properties = get_properties(log, activity_key=activity_key, case_id_key=case_id_key, timestamp_key=timestamp_key)