def execute_script():
log_path = os.path.join("..", "tests", "input_data", "interval_event_log.xes")
#log_path = os.path.join("..", "tests", "input_data", "reviewing.xes")
log = xes_importer.apply(log_path)
parameters = {}
parameters[constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY] = "start_timestamp"
parameters[constants.PARAMETER_CONSTANT_TIMESTAMP_KEY] = "time:timestamp"
parameters[constants.PARAMETER_CONSTANT_ACTIVITY_KEY] = "concept:name"
parameters["strict"] = False
parameters["format"] = "svg"
start_activities = sa_get.get_start_activities(log, parameters=parameters)
end_activities = ea_get.get_end_activities(log, parameters=parameters)
parameters["start_activities"] = start_activities
parameters["end_activities"] = end_activities
soj_time = soj_time_get.apply(log, parameters=parameters)
print("soj_time")
print(soj_time)
conc_act = conc_act_get.apply(log, parameters=parameters)
print("conc_act")
print(conc_act)
efg = efg_get.apply(log, parameters=parameters)
print("efg")
print(efg)
dfg_freq = dfg_algorithm.apply(log, parameters=parameters, variant=dfg_algorithm.Variants.FREQUENCY)
dfg_perf = dfg_algorithm.apply(log, parameters=parameters, variant=dfg_algorithm.Variants.PERFORMANCE)
dfg_gv_freq = dfg_vis_fact.apply(dfg_freq, log=log, variant=dfg_vis_fact.Variants.FREQUENCY,
parameters=parameters)
dfg_vis_fact.view(dfg_gv_freq)
dfg_gv_perf = dfg_vis_fact.apply(dfg_perf, log=log, variant=dfg_vis_fact.Variants.PERFORMANCE,
parameters=parameters)
dfg_vis_fact.view(dfg_gv_perf)
net, im, fm = dfg_conv.apply(dfg_freq)
gviz = pn_vis.apply(net, im, fm, parameters=parameters)
pn_vis.view(gviz)
def discover_abstraction_log(
log: EventLog,
parameters: Optional[Dict[Any, Any]] = None
) -> Tuple[Any, Any, Any, Any, Any, Any, Any]:
"""
Discovers an abstraction from a log that is useful for the Heuristics Miner ++ algorithm
Parameters
--------------
log
Event log
parameters
Parameters of the algorithm, including:
- Parameters.ACTIVITY_KEY
- Parameters.START_TIMESTAMP_KEY
- Parameters.TIMESTAMP_KEY
- Parameters.CASE_ID_KEY
Returns
--------------
start_activities
Start activities
end_activities
End activities
activities_occurrences
Activities along with their number of occurrences
dfg
Directly-follows graph
performance_dfg
(Performance) Directly-follows graph
sojourn_time
Sojourn time for each activity
concurrent_activities
Concurrent activities
"""
if parameters is None:
parameters = {}
activity_key = exec_utils.get_param_value(Parameters.ACTIVITY_KEY,
parameters, xes.DEFAULT_NAME_KEY)
start_activities = log_sa.get_start_activities(log, parameters=parameters)
end_activities = log_ea.get_end_activities(log, parameters=parameters)
activities_occurrences = log_attributes.get_attribute_values(
log, activity_key, parameters=parameters)
efg_parameters = copy(parameters)
efg_parameters[efg_get.Parameters.KEEP_FIRST_FOLLOWING] = True
dfg = efg_get.apply(log, parameters=efg_parameters)
performance_dfg = dfg_alg.apply(log,
variant=dfg_alg.Variants.PERFORMANCE,
parameters=parameters)
sojourn_time = soj_get.apply(log, parameters=parameters)
concurrent_activities = conc_act_get.apply(log, parameters=parameters)
return (start_activities, end_activities, activities_occurrences, dfg,
performance_dfg, sojourn_time, concurrent_activities)