def get_cycles_petri_net_transitions(net):
"""
Get the cycles of a Petri net (returning only list of transitions belonging to the cycle)
Parameters
-------------
net
Petri net
Returns
-------------
cycles
Cycles (transitions) of the Petri net
"""
import networkx as nx
graph, inv_dictionary = create_networkx_directed_graph(net)
cycles = nx.simple_cycles(graph)
cycles_trans = []
for cycle in cycles:
cycles_trans.append([])
for el in cycle:
if el in inv_dictionary and type(
inv_dictionary[el]) is PetriNet.Transition:
cycles_trans[-1].append(inv_dictionary[el])
return cycles_trans
def get_strongly_connected_subnets(net):
"""
Get the strongly connected components subnets in the Petri net
Parameters
-------------
net
Petri net
Returns
-------------
strongly_connected_transitions
List of strongly connected transitions of the Petri net
"""
import networkx as nx
graph, inv_dictionary = create_networkx_directed_graph(net)
sccg = list(nx.strongly_connected_components(graph))
strongly_connected_subnets = []
for sg in list(sccg):
if len(sg) > 1:
subnet = petri.petrinet.PetriNet()
imarking = petri.petrinet.Marking()
fmarking = petri.petrinet.Marking()
corr = {}
for node in sg:
if node in inv_dictionary:
if type(inv_dictionary[node]
) is petri.petrinet.PetriNet.Transition:
prev_trans = inv_dictionary[node]
new_trans = petri.petrinet.PetriNet.Transition(
prev_trans.name, prev_trans.label)
corr[node] = new_trans
subnet.transitions.add(new_trans)
if type(inv_dictionary[node]
) is petri.petrinet.PetriNet.Place:
prev_place = inv_dictionary[node]
new_place = petri.petrinet.PetriNet.Place(
prev_place.name)
corr[node] = new_place
subnet.places.add(new_place)
for edge in graph.edges:
if edge[0] in sg and edge[1] in sg:
add_arc_from_to(corr[edge[0]], corr[edge[1]], subnet)
strongly_connected_subnets.append([subnet, imarking, fmarking])
return strongly_connected_subnets
def get_cycles_petri_net_places(net):
"""
Get the cycles of a Petri net (returning only list of places belonging to the cycle)
Parameters
-------------
net
Petri net
Returns
-------------
cycles
Cycles (places) of the Petri net
"""
graph, inv_dictionary = create_networkx_directed_graph(net)
cycles = nx.simple_cycles(graph)
cycles_places = []
for cycle in cycles:
cycles_places.append([])
for el in cycle:
if el in inv_dictionary and type(inv_dictionary[el]) is petri.petrinet.PetriNet.Place:
cycles_places[-1].append(inv_dictionary[el])
return cycles_places
