def check_source_and_sink_reachability(net, unique_source, unique_sink):
"""
Checks reachability of the source and the sink place from all simulation nodes (places/transitions)
of the Petri net
Parameters
-------------
net
Petri net
unique_source
Unique source place of the Petri net
unique_sink
Unique sink place of the Petri net
Returns
-------------
boolean
Boolean value that is true if each node is in a path from the source place to the sink place
"""
import networkx as nx
graph, unique_source_corr, unique_sink_corr, inv_dictionary = create_networkx_undirected_graph(
net, unique_source, unique_sink)
if unique_source_corr is not None and unique_sink_corr is not None:
nodes_list = list(graph.nodes())
finish_to_sink = list(nx.ancestors(graph, unique_sink_corr))
connected_to_source = list(nx.descendants(graph, unique_source_corr))
if len(finish_to_sink) == len(nodes_list) - 1 and len(
connected_to_source) == len(nodes_list) - 1:
return True
return False
def connected(student_answer):
"""
Checks if the student_answer petri net is a (weakly) connected graph.
"""
# Turn PetriNet object into NetworkX directed graph
normal_graph, _, _, table = create_networkx_undirected_graph(
student_answer, None, None)
if nx.is_connected(normal_graph):
return {'correct': True}
else:
return {'correct': False, 'feedback': 'Graph is not connected.'}
def create_networkx_graph(net, initial_marking, final_marking):
nx_graph, unique_source_corr, unique_sink_corr, inv_dict = \
networkx_graph.create_networkx_undirected_graph(net, initial_marking, final_marking)
inv_inv_dict = {y: x for x, y in inv_dict.items()}
return nx_graph, inv_inv_dict
