def test_ext_marking_equation_sync_net(self):
import pm4py
log = pm4py.read_xes(os.path.join("input_data", "running-example.xes"))
net, im, fm = pm4py.discover_petri_net_inductive(log)
sync_net, sync_im, sync_fm = pm4py.construct_synchronous_product_net(log[0], net, im, fm)
res = pm4py.solve_extended_marking_equation(log[0], sync_net, sync_im, sync_fm)
self.assertIsNotNone(res)
def execute_script():
log = pm4py.read_xes(
os.path.join("..", "tests", "input_data", "receipt.xes"))
net, im, fm = inductive_miner.apply(
log, variant=inductive_miner.Variants.IM_CLEAN)
idx = 0
# try to resolve the marking equation to find an heuristics and possible a vector of transitions
# leading from im to fm
sync_net, sync_im, sync_fm = pm4py.construct_synchronous_product_net(
log[idx], net, im, fm)
me_solver = marking_equation.build(sync_net, sync_im, sync_fm)
h, x = me_solver.solve()
firing_sequence, reach_fm1, explained_events = me_solver.get_firing_sequence(
x)
print("for trace at index " + str(idx) + ": marking equation h = ", h)
print("x vector reaches fm = ", reach_fm1)
print("firing sequence = ", firing_sequence)
# it fails and the value of heuristics is low
#
# now let's try with extended marking equation to find the heuristics and the vector!
eme_solver = extended_marking_equation.build(log[idx], sync_net, sync_im,
sync_fm)
h, x = eme_solver.solve()
# the heuristics is much better
firing_sequence, reach_fm2, explained_events = eme_solver.get_firing_sequence(
x)
print(
"for trace at index " + str(idx) + ": extended marking equation h = ",
h)
print("x vector reaches fm = ", reach_fm2)
print("firing sequence = ", firing_sequence)
def test_mark_em_equation(self):
log = pm4py.read_xes("input_data/running-example.xes")
net, im, fm = pm4py.read_pnml("input_data/running-example.pnml")
sync_net, sync_im, sync_fm = pm4py.construct_synchronous_product_net(
log[0], net, im, fm)
m_h = pm4py.solve_marking_equation(sync_net, sync_im, sync_fm)
em_h = pm4py.solve_extended_marking_equation(log[0], sync_net, sync_im,
sync_fm)