Merge branch 'ft-1261-business-hours-simplified-interface' into 'inte…

…gration'

FT 1261 (requires !499 to be merged) updates simplified interface for business hours

See merge request pm4py/pm4py-core!501

pm4py/discovery.py

@@ -64,14 +64,20 @@ def discover_directly_follows_graph(log: Union[EventLog, pd.DataFrame]) -> Tuple
     return discover_dfg(log)
 
 
-def discover_performance_dfg(log: Union[EventLog, pd.DataFrame]) -> Tuple[dict, dict, dict]:
+def discover_performance_dfg(log: Union[EventLog, pd.DataFrame], business_hours: bool = False, worktiming: List[int] = [7, 17], weekends: List[int] = [6, 7]) -> Tuple[dict, dict, dict]:
     """
     Discovers a performance directly-follows graph from an event log
 
     Parameters
     ---------------
     log
         Event log
+    business_hours
+        Enables/disables the computation based on the business hours (default: False)
+    worktiming
+        (If the business hours are enabled) The hour range in which the resources of the log are working (default: 7 to 17)
+    weekends
+        (If the business hours are enabled) The weekends days (default: Saturday (6), Sunday (7))
 
     Returns
     ---------------
@@ -91,7 +97,8 @@ def discover_performance_dfg(log: Union[EventLog, pd.DataFrame]) -> Tuple[dict,
         activity_key = properties[constants.PARAMETER_CONSTANT_ACTIVITY_KEY] if constants.PARAMETER_CONSTANT_ACTIVITY_KEY in properties else xes_constants.DEFAULT_NAME_KEY
         timestamp_key = properties[constants.PARAMETER_CONSTANT_TIMESTAMP_KEY] if constants.PARAMETER_CONSTANT_TIMESTAMP_KEY in properties else xes_constants.DEFAULT_TIMESTAMP_KEY
         case_id_key = properties[constants.PARAMETER_CONSTANT_CASEID_KEY] if constants.PARAMETER_CONSTANT_CASEID_KEY in properties else constants.CASE_CONCEPT_NAME
-        dfg = get_dfg_graph(log, activity_key=activity_key, timestamp_key=timestamp_key, case_id_glue=case_id_key, measure="performance", perf_aggregation_key="all")
+        dfg = get_dfg_graph(log, activity_key=activity_key, timestamp_key=timestamp_key, case_id_glue=case_id_key, measure="performance", perf_aggregation_key="all",
+                            business_hours=business_hours, worktiming=worktiming, weekends=weekends)
         from pm4py.statistics.start_activities.pandas import get as start_activities_module
         from pm4py.statistics.end_activities.pandas import get as end_activities_module
         start_activities = start_activities_module.get_start_activities(log, parameters=properties)
@@ -100,6 +107,9 @@ def discover_performance_dfg(log: Union[EventLog, pd.DataFrame]) -> Tuple[dict,
         from pm4py.algo.discovery.dfg.variants import performance as dfg_discovery
         properties = get_properties(log)
         properties[dfg_discovery.Parameters.AGGREGATION_MEASURE] = "all"
+        properties[dfg_discovery.Parameters.BUSINESS_HOURS] = business_hours
+        properties[dfg_discovery.Parameters.WORKTIMING] = worktiming
+        properties[dfg_discovery.Parameters.WEEKENDS] = weekends
         dfg = dfg_discovery.apply(log, parameters=properties)
         from pm4py.statistics.start_activities.log import get as start_activities_module
         from pm4py.statistics.end_activities.log import get as end_activities_module

pm4py/stats.py

@@ -387,32 +387,42 @@ def get_cycle_time(log: Union[EventLog, pd.DataFrame]) -> float:
         return cycle_time.apply(log, parameters=get_properties(log))
 
 
-def get_all_case_durations(log: Union[EventLog, pd.DataFrame]) -> List[float]:
+def get_all_case_durations(log: Union[EventLog, pd.DataFrame], business_hours: bool = False, worktiming: List[int] = [7, 17], weekends: List[int] = [6, 7]) -> List[float]:
     """
     Gets the durations of the cases in the event log
 
     Parameters
     ---------------
     log
         Event log
+    business_hours
+        Enables/disables the computation based on the business hours (default: False)
+    worktiming
+        (If the business hours are enabled) The hour range in which the resources of the log are working (default: 7 to 17)
+    weekends
+        (If the business hours are enabled) The weekends days (default: Saturday (6), Sunday (7))
 
     Returns
     ---------------
     durations
         Case durations (as list)
     """
     general_checks_classical_event_log(log)
+    properties = copy(get_properties(log))
+    properties["business_hours"] = business_hours
+    properties["worktiming"] = worktiming
+    properties["weekends"] = weekends
     if check_is_pandas_dataframe(log):
         check_pandas_dataframe_columns(log)
         from pm4py.statistics.traces.generic.pandas import case_statistics
-        cd = case_statistics.get_cases_description(log, parameters=get_properties(log))
+        cd = case_statistics.get_cases_description(log, parameters=properties)
         return sorted([x["caseDuration"] for x in cd.values()])
     else:
         from pm4py.statistics.traces.generic.log import case_statistics
-        return case_statistics.get_all_case_durations(log, parameters=get_properties(log))
+        return case_statistics.get_all_case_durations(log, parameters=properties)
 
 
-def get_case_duration(log: Union[EventLog, pd.DataFrame], case_id: str) -> float:
+def get_case_duration(log: Union[EventLog, pd.DataFrame], case_id: str, business_hours: bool = False, worktiming: List[int] = [7, 17], weekends: List[int] = [6, 7]) -> float:
     """
     Gets the duration of a specific case
 
@@ -422,19 +432,29 @@ def get_case_duration(log: Union[EventLog, pd.DataFrame], case_id: str) -> float
         Event log
     case_id
         Case identifier
+    business_hours
+        Enables/disables the computation based on the business hours (default: False)
+    worktiming
+        (If the business hours are enabled) The hour range in which the resources of the log are working (default: 7 to 17)
+    weekends
+        (If the business hours are enabled) The weekends days (default: Saturday (6), Sunday (7))
 
     Returns
     ------------------
     duration
         Duration of the given case
     """
     general_checks_classical_event_log(log)
+    properties = copy(get_properties(log))
+    properties["business_hours"] = business_hours
+    properties["worktiming"] = worktiming
+    properties["weekends"] = weekends
     if check_is_pandas_dataframe(log):
         check_pandas_dataframe_columns(log)
         from pm4py.statistics.traces.generic.pandas import case_statistics
-        cd = case_statistics.get_cases_description(log)
+        cd = case_statistics.get_cases_description(log, parameters=properties)
         return cd[case_id]["caseDuration"]
     else:
         from pm4py.statistics.traces.generic.log import case_statistics
-        cd = case_statistics.get_cases_description(log)
+        cd = case_statistics.get_cases_description(log, parameters=properties)
         return cd[case_id]["caseDuration"]