def initialize_tree(self,
dfg,
initial_dfg,
activities,
second_iteration=False):
"""
Initialize the tree
Parameters
-----------
dfg
Directly follows graph of this subtree
initial_dfg
Referral directly follows graph that should be taken in account adding hidden/loop transitions
activities
Activities of this subtree
second_iteration
Boolean that indicates if we are executing this method for the second time
"""
self.second_iteration = second_iteration
if activities is None:
self.activities = get_activities_from_dfg(dfg)
else:
self.activities = copy(activities)
if second_iteration:
self.dfg = clean_dfg_based_on_noise_thresh(self.dfg,
self.activities,
self.noise_threshold)
else:
self.dfg = copy(dfg)
self.initial_dfg = initial_dfg
self.outgoing = get_outgoing_edges(self.dfg)
self.ingoing = get_ingoing_edges(self.dfg)
self.self_loop_activities = get_activities_self_loop(self.dfg)
self.initial_outgoing = get_outgoing_edges(self.initial_dfg)
self.initial_ingoing = get_ingoing_edges(self.initial_dfg)
self.activities_direction = get_activities_direction(
self.dfg, self.activities)
self.activities_dir_list = get_activities_dirlist(
self.activities_direction)
self.negated_dfg = negate(self.dfg)
self.negated_activities = get_activities_from_dfg(self.negated_dfg)
self.negated_outgoing = get_outgoing_edges(self.negated_dfg)
self.negated_ingoing = get_ingoing_edges(self.negated_dfg)
self.detected_cut = None
self.children = []
if second_iteration:
self.detect_cut(second_iteration=second_iteration)
def initialize_tree(self):
"""
Initialize the tree
"""
if self.activities is None:
self.activities = list(set(y for x in self.traces for y in x))
else:
if self.parent is not None and self.parent.detected_cut_add_info == "loop":
self.get_traces_loop()
else:
self.traces = self.get_traces_general()
if self.second_iteration:
self.traces, self.activities = self.clean_traces_noise()
self.start_activities = list(set(x[0] for x in self.traces if x))
self.end_activities = list(set(x[-1] for x in self.traces if x))
self.activities_occurrences = Counter(
[y for x in self.traces for y in x])
self.dfg = Counter(
(x[i - 1], x[i]) for x in self.traces for i in range(1, len(x)))
self.dfg = [(x, y) for x, y in self.dfg.items()]
self.initial_dfg = self.dfg
self.outgoing = get_outgoing_edges(self.dfg)
self.ingoing = get_ingoing_edges(self.dfg)
self.self_loop_activities = get_activities_self_loop(self.dfg)
self.activities_direction = get_activities_direction(
self.dfg, self.activities)
self.activities_dir_list = get_activities_dirlist(
self.activities_direction)
self.negated_dfg = negate(self.dfg)
self.negated_activities = get_activities_from_dfg(self.negated_dfg)
self.negated_outgoing = get_outgoing_edges(self.negated_dfg)
self.negated_ingoing = get_ingoing_edges(self.negated_dfg)
self.contains_empty_traces = min(
len(x)
for x in self.traces) == 0 if len(self.traces) > 0 else False
self.must_insert_skip = self.contains_empty_traces
if self.parent is not None and self.parent.detected_cut == "xor":
self.must_insert_skip = False
self.must_insert_skip = self.rec_must_insert_skip or self.must_insert_skip
if not self.second_iteration:
self.second_tree = self.clone_second_it()
self.detected_cut = None
self.children = []
def detect_cut(initial_dfg, dfg, parent, conf, process, initial_start_activities, initial_end_activities, activities):
"""
Detect generally a cut in the graph (applying all the algorithms)
"""
if dfg:
# print('DFG' + str(dfg) + ' will be cut on ' + str(conf))
# print(dfg)
# Find in order: xor, seq, par, loop, seq, flower
ingoing = get_ingoing_edges(dfg)
outgoing = get_outgoing_edges(dfg)
start_activities = infer_start_activities(dfg)
end_activities = infer_end_activities(dfg)
if parent == "m":
initial_start_activities = start_activities
initial_end_activities = end_activities
activities = get_activities_from_dfg(dfg)
else:
activities = set(activities)
conn_components = detection_utils.get_connected_components(ingoing, outgoing, activities)
# print("Init Start: " + str(initial_start_activities) + ", Init End: " + str(initial_end_activities))
# print(activities)
xor_cut = detect_xor_cut(dfg, conn_components)
if xor_cut[0]:
found_cut = "xor"
print(found_cut)
for index, comp in enumerate(xor_cut[1]):
# print(comp)
filtered_dfg = filter_dfg_on_act(dfg, comp)
save_cut(filtered_dfg, comp, parent, found_cut, index, conf, process, initial_start_activities, initial_end_activities)
else:
this_nx_graph = detection_utils.transform_dfg_to_directed_nx_graph(activities, dfg)
strongly_connected_components = [list(x) for x in nx.strongly_connected_components(this_nx_graph)]
# print(strongly_connected_components)
seq_cut = detect_sequential_cut(dfg, strongly_connected_components)
if seq_cut[0]:
found_cut = "seq"
print("seq")
for index, comp in enumerate(seq_cut[1]):
# print(comp)
filter_dfg = filter_dfg_on_act(dfg, comp)
print(filter_dfg)
save_cut(filter_dfg, comp, parent, found_cut, index, conf, process, initial_start_activities, initial_end_activities)
# self.put_skips_in_seq_cut()?
else:
negated_dfg = detection_utils.negate(dfg)
negated_ingoing = get_ingoing_edges(negated_dfg)
negated_outgoing = get_outgoing_edges(negated_dfg)
par_cut = detect_parallel_cut(this_nx_graph, strongly_connected_components, negated_ingoing, negated_outgoing, activities, dfg, initial_start_activities, initial_end_activities, initial_dfg)
if par_cut[0]:
found_cut = "par"
print("par")
i = 0
for comp in par_cut[1]:
i += 1
# print(comp)
filtter_dfg = filter_dfg_on_act(dfg, comp)
save_cut(filtter_dfg, comp, parent, found_cut, i, conf, process, initial_start_activities, initial_end_activities)
else:
start_activities = infer_start_activities(dfg)
end_activities = infer_end_activities(dfg)
loop_cut = detect_loop_cut(dfg, activities, start_activities, end_activities)
if loop_cut[0]:
if loop_cut[2]:
found_cut = "loop"
print("loop")
for index, comp in enumerate(loop_cut[1]):
# print(comp)
filter_dfg = filter_dfg_on_act(dfg, comp)
save_cut(filter_dfg, comp, parent, found_cut, index, conf, process, initial_start_activities, initial_end_activities)
# if loop_cut[3]:
# insert_skip
else:
found_cut = "seq2"
print('seq 2')
# self.need_loop_on_subtree = True
for index, comp in enumerate(loop_cut[1]):
# print(comp)
filter_dfg = filter_dfg_on_act(dfg, comp)
save_cut(filter_dfg, comp, parent, found_cut, index, conf, process, initial_start_activities, initial_end_activities)
#insert_skip
else:
pass
found_cut = "flower"
print("flower")
#save_cut(dfg, comp, parent, found_cut, 0, conf, process)
return found_cut
else:
print("no DFG or base_xor")
return "base_xor"
