# Source code for pm4py.objects.stochastic_petri.tangible_reachability

```
'''
This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
PM4Py is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
PM4Py is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with PM4Py. If not, see <https://www.gnu.org/licenses/>.
'''
from pm4py.objects.petri_net.utils.reachability_graph import construct_reachability_graph
from pm4py.objects.conversion.log import converter as log_converter
[docs]def get_tangible_reachability_from_log_net_im_fm(log, net, im, fm, parameters=None):
"""
Gets the tangible reachability graph from a log and an accepting Petri net
Parameters
---------------
log
Event log
net
Petri net
im
Initial marking
fm
Final marking
Returns
------------
reachab_graph
Reachability graph
tangible_reach_graph
Tangible reachability graph
stochastic_info
Stochastic information
"""
if parameters is None:
parameters = {}
from pm4py.algo.simulation.montecarlo.utils import replay
stochastic_info = replay.get_map_from_log_and_net(log_converter.apply(log, variant=log_converter.Variants.TO_EVENT_LOG, parameters=parameters), net, im, fm,
parameters=parameters)
reachability_graph, tangible_reachability_graph = get_tangible_reachability_from_net_im_sinfo(net, im,
stochastic_info,
parameters=parameters)
return reachability_graph, tangible_reachability_graph, stochastic_info
[docs]def get_tangible_reachability_from_net_im_sinfo(net, im, stochastic_info, parameters=None):
"""
Gets the tangible reacahbility graph from a Petri net, an initial marking and a stochastic map
Parameters
-------------
net
Petri net
im
Initial marking
fm
Final marking
stochastic_info
Stochastic information
Returns
------------
reachab_graph
Reachability graph
tangible_reach_graph
Tangible reachability graph
"""
if parameters is None:
parameters = {}
reachab_graph = construct_reachability_graph(net, im)
tang_reach_graph = get_tangible_reachability_from_reachability(reachab_graph, stochastic_info)
return reachab_graph, tang_reach_graph
[docs]def get_tangible_reachability_from_reachability(reach_graph, stochastic_info):
"""
Gets the tangible reachability graph from the reachability graph and the stochastic transition map
Parameters
------------
reach_graph
Reachability graph
stochastic_info
Stochastic information
Returns
------------
tangible_reach_graph
Tangible reachability graph
"""
timed_transitions = []
for trans in stochastic_info.keys():
random_variable = stochastic_info[trans]
transition_type = random_variable.get_transition_type()
if transition_type == "TIMED":
timed_transitions.append(trans.name)
states_reach = list(reach_graph.states)
for s in states_reach:
state_outgoing_trans = list(s.outgoing)
state_ingoing_trans = list(s.incoming)
timed_trans_outgoing = [x for x in state_outgoing_trans if x.name in timed_transitions]
if not len(state_outgoing_trans) == len(timed_trans_outgoing):
for t in state_outgoing_trans:
reach_graph.transitions.remove(t)
t.from_state.outgoing.remove(t)
t.to_state.incoming.remove(t)
for t in state_ingoing_trans:
reach_graph.transitions.remove(t)
t.from_state.outgoing.remove(t)
t.to_state.incoming.remove(t)
reach_graph.states.remove(s)
states_reach = list(reach_graph.states)
for s in states_reach:
if len(s.incoming) == 0 and len(s.outgoing) == 0:
reach_graph.states.remove(s)
return reach_graph
```