def detect_loop_cut(self):
"""
Detect loop cut
"""
start_activities = self.start_activities
if len(start_activities) == 0:
start_activities = infer_start_activities_from_prev_connections_and_current_dfg(self.initial_dfg, self.dfg,
self.activities)
end_activities = self.end_activities
end_activities = list(set(end_activities) - set(start_activities))
if len(end_activities) == 0:
end_activities = infer_end_activities_from_succ_connections_and_current_dfg(self.initial_dfg, self.dfg,
self.activities)
end_activities = list(set(end_activities) - set(start_activities))
if len(end_activities) == 0:
end_activities = infer_end_activities_from_succ_connections_and_current_dfg(self.initial_dfg, self.dfg,
self.activities,
include_self=False)
all_end_activities = copy(end_activities)
end_activities = list(set(end_activities) - set(start_activities))
end_activities_that_are_also_start = list(set(all_end_activities) - set(end_activities))
do_part = []
redo_part = []
dangerous_redo_part = []
exit_part = []
for sa in start_activities:
do_part.append(sa)
for ea in end_activities:
exit_part.append(ea)
for act in self.activities:
if act not in start_activities and act not in end_activities:
input_connected_activities = get_all_activities_connected_as_input_to_activity(self.dfg, act)
output_connected_activities = get_all_activities_connected_as_output_to_activity(self.dfg, act)
if set(output_connected_activities).issubset(start_activities) and set(start_activities).issubset(
output_connected_activities):
if len(input_connected_activities.intersection(exit_part)) > 0:
dangerous_redo_part.append(act)
redo_part.append(act)
else:
do_part.append(act)
if len(do_part) > 0 and (len(redo_part) > 0 or len(exit_part)) > 0:
if len(redo_part) > 0:
return [True, [do_part + exit_part, redo_part], len(end_activities_that_are_also_start) > 0]
else:
return [True, [do_part, redo_part + exit_part], len(end_activities_that_are_also_start) > 0]
return [False, [], []]
def detect_loop_cut(self, conn_components, this_nx_graph, strongly_connected_components):
"""
Detect loop cut
Parameters
--------------
conn_components
Connected components of the graph
this_nx_graph
NX graph calculated on the DFG
strongly_connected_components
Strongly connected components
"""
all_start_activities = self.start_activities
all_end_activities = self.end_activities
start_activities = all_start_activities
end_activities = list(set(all_end_activities) - set(all_start_activities))
start_act_that_are_also_end = list(set(all_end_activities) - set(end_activities))
do_part = []
redo_part = []
dangerous_redo_part = []
exit_part = []
for sa in start_activities:
do_part.append(sa)
for ea in end_activities:
exit_part.append(ea)
for act in self.activities:
if act not in start_activities and act not in end_activities:
input_connected_activities = get_all_activities_connected_as_input_to_activity(self.dfg, act)
output_connected_activities = get_all_activities_connected_as_output_to_activity(self.dfg, act)
if set(output_connected_activities).issubset(start_activities) and set(start_activities).issubset(
output_connected_activities):
if len(input_connected_activities.intersection(exit_part)) > 0:
dangerous_redo_part.append(act)
redo_part.append(act)
else:
do_part.append(act)
if len(do_part) > 0 and (len(redo_part) > 0 or len(exit_part)) > 0:
if len(redo_part) > 0:
return [True, [do_part + exit_part, redo_part], True, len(start_act_that_are_also_end) > 0]
else:
return [True, [do_part, redo_part + exit_part], False, len(start_act_that_are_also_end) > 0]
return [False, [], False]
def detect_loop_cut(dfg, activities, start_activities, end_activities):
"""
Detect loop cut
"""
all_start_activities = start_activities
all_end_activities = list(
set(end_activities).intersection(set(infer_end_activities(dfg))))
start_activities = all_start_activities
end_activities = list(set(all_end_activities) - set(all_start_activities))
start_act_that_are_also_end = list(
set(all_end_activities) - set(end_activities))
do_part = []
redo_part = []
dangerous_redo_part = []
exit_part = []
for sa in start_activities:
do_part.append(sa)
for ea in end_activities:
exit_part.append(ea)
for act in activities:
if act not in start_activities and act not in end_activities:
input_connected_activities = get_all_activities_connected_as_input_to_activity(
dfg, act)
output_connected_activities = get_all_activities_connected_as_output_to_activity(
dfg, act)
if set(output_connected_activities).issubset(
start_activities) and set(start_activities).issubset(
output_connected_activities):
if len(input_connected_activities.intersection(exit_part)) > 0:
dangerous_redo_part.append(act)
redo_part.append(act)
else:
do_part.append(act)
if (len(do_part) + len(exit_part)) > 0 and len(redo_part) > 0:
return [
True, [do_part + exit_part, redo_part], True,
len(start_act_that_are_also_end) > 0
]
return [False, [], False]
