def test_log_skeleton(self):
log = xes_importer.apply(
os.path.join("input_data", "running-example.xes"))
from pm4py.algo.discovery.log_skeleton import algorithm as lsk_discovery
model = lsk_discovery.apply(log)
from pm4py.algo.conformance.log_skeleton import algorithm as lsk_conformance
conf = lsk_conformance.apply(log, model)
def execute_script():
# loads a XES event log
event_log = pm4py.read_xes("../tests/input_data/receipt.xes")
# gets the dataframe out of the event log (through conversion)
dataframe = pm4py.convert_to_dataframe(event_log)
# discovers the log skeleton model
log_skeleton = log_skeleton_discovery.apply(
event_log,
parameters={
log_skeleton_discovery.Variants.CLASSIC.value.Parameters.NOISE_THRESHOLD:
0.03
})
# apply conformance checking
conf_result = log_skeleton_conformance.apply(event_log, log_skeleton)
# gets the diagnostic result out of the dataframe
diagnostics = log_skeleton_conformance.get_diagnostics_dataframe(
event_log, conf_result)
# merges the dataframe containing the events, and the diagnostics dataframe, using the pd.merge method
merged_df = pd.merge(dataframe,
diagnostics,
how="left",
left_on="case:concept:name",
right_on="case_id",
suffixes=('', '_diagn'))
print(merged_df)
def test_log_skeleton(self):
log = pm4py.read_xes("input_data/running-example.xes")
log_skeleton = log_skeleton_discovery.apply(
log,
parameters={
log_skeleton_discovery.Variants.CLASSIC.value.Parameters.NOISE_THRESHOLD:
0.05
})
conf_result = log_skeleton_conformance.apply(log, log_skeleton)
diagn_df = log_skeleton_conformance.get_diagnostics_dataframe(
log, conf_result)
def execute_script():
log = xes_importer.apply(
os.path.join("..", "tests", "input_data", "receipt.xes"))
# discovers the log skeleton with a minimal noise
log_skeleton = lsk.apply(
log,
parameters={
lsk.Variants.CLASSIC.value.Parameters.NOISE_THRESHOLD: 0.01
})
print(log_skeleton)
# applies conformance checking to it
results = lsk_conf.apply(log, log_skeleton)
for i in range(min(len(results), 5)):
# print the i-the conformance checking
print(results[i])
def test_log_skeleton(self):
log = xes_importer.apply(os.path.join("input_data", "receipt.xes"))
skeleton = lsk_alg.apply(log)
conf_res = lsk_conf_alg.apply(log, skeleton)
for r in self.working_relationships:
r_instance = self.relationships[r](self.log,
self.all_activities,
self.noise_threshold,
include_extenstions=extension)
res[r] = r_instance.apply()
res['activities'] = list(self.all_activities)
return res
if __name__ == "__main__":
importer = XES_Importer()
path = os.path.join(os.path.dirname(__file__),
'../../../res/logs/running-example.xes')
log_and_activset = importer.import_file(path, [], [])
log = log_and_activset[0]
activset = log_and_activset[1]
skeleton = lsk_discovery.apply(
log,
parameters={
lsk_discovery.Variants.CLASSIC.value.Parameters.NOISE_THRESHOLD: 0
})
print(skeleton)
model = Log_Skeleton(log, activset, 0.1)
model.set_working_relationships(['always_before', 'counter'])
print(model.apply())
