def step_12(woflan_object, return_asap_when_unsound=False):
woflan_object.set_r_g_s_c(
reachability_graph(woflan_object.get_s_c_net(),
woflan_object.get_initial_marking(),
woflan_object.get_net()))
if woflan_object.print_diagnostics:
print('There are non-live tasks.')
if return_asap_when_unsound:
return False
return step_13(woflan_object,
return_asap_when_unsound=return_asap_when_unsound)
def compute_non_live_sequences(woflan_object):
"""
We want to compute the sequences of transitions which lead to deadlocks.
To do this, we first compute a reachbility graph (possible, since we know that the Petri Net is bounded) and then we
convert it to a spanning tree. Afterwards, we compute the paths which lead to nodes from which the final marking cannot
be reached. Note: We are searching for the shortest sequence. After the first red node, all successors are also red.
Therefore, we do not have to consider them.
:param woflan_object: Object that contains the necessary information
:return: List of sequence of transitions, each sequence is a list
"""
woflan_object.set_r_g(
reachability_graph(woflan_object.get_net(),
woflan_object.get_initial_marking()))
f_m = convert_marking(woflan_object.get_net(),
woflan_object.get_final_marking())
sucessfull_terminate_state = None
for node in woflan_object.get_r_g().nodes:
if all(np.equal(woflan_object.get_r_g().nodes[node]['marking'], f_m)):
sucessfull_terminate_state = node
break
# red nodes are those from which the final marking is not reachable
red_nodes = []
for node in woflan_object.get_r_g().nodes:
if not nx.has_path(woflan_object.get_r_g(), node,
sucessfull_terminate_state):
red_nodes.append(node)
# Compute directed spanning tree
spanning_tree = nx.algorithms.tree.Edmonds(
woflan_object.get_r_g()).find_optimum()
queue = set()
paths = {}
# root node
queue.add(0)
paths[0] = []
processed_nodes = set()
red_paths = []
while len(queue) > 0:
v = queue.pop()
for node in spanning_tree.neighbors(v):
if node not in paths and node not in processed_nodes:
paths[node] = paths[v].copy()
# we can use directly 0 here, since we are working on a spanning tree and there should be no more edges to a node
paths[node].append(woflan_object.get_r_g().get_edge_data(
v, node)[0]['transition'])
if node not in red_nodes:
queue.add(node)
else:
red_paths.append(paths[node])
processed_nodes.add(v)
return red_paths
def step_11(woflan_object, return_asap_when_unsound=False):
woflan_object.set_r_g_s_c(
reachability_graph(woflan_object.get_s_c_net(),
woflan_object.get_initial_marking(),
woflan_object.get_net()))
if nx.is_strongly_connected(woflan_object.get_r_g_s_c()):
if woflan_object.print_diagnostics:
print('All tasks are live.')
return True
else:
if return_asap_when_unsound:
return False
return step_13(woflan_object,
return_asap_when_unsound=return_asap_when_unsound)