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 check_loop_need(spec_tree_struct):
"""
Check whether a forced loop transitions shall be added
Parameters
-----------
spec_tree_struct
Internal tree structure (after application of Inductive Miner)
Returns
-----------
need_loop_on_subtree
Checks if the loop on the subtree is needed
"""
self_loop_activities = set(get_activities_self_loop(spec_tree_struct.initial_dfg))
self_loop_activities = self_loop_activities.intersection(set(spec_tree_struct.activities))
need_loop_on_subtree = len(self_loop_activities) > 0
return need_loop_on_subtree
