'''
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 import reachability_graph
import itertools
from enum import Enum
from typing import Optional, Dict, Any, Union, Tuple
from pm4py.objects.petri_net.obj import PetriNet, Marking
[docs]class Outputs(Enum):
DFG = "dfg"
SEQUENCE = "sequence"
PARALLEL = "parallel"
START_ACTIVITIES = "start_activities"
END_ACTIVITIES = "end_activities"
ACTIVITIES = "activities"
SKIPPABLE = "skippable"
ACTIVITIES_ALWAYS_HAPPENING = "activities_always_happening"
MIN_TRACE_LENGTH = "min_trace_length"
TRACE = "trace"
[docs]def findsubsets(s, n):
return list(itertools.combinations(s, n))
[docs]def apply(net: PetriNet, im: Marking, parameters: Optional[Dict[Any, Any]] = None) -> Dict[str, Any]:
"""
Discovers a footprint object from a Petri net
Parameters
--------------
net
Petri net
im
Initial marking
parameters
Parameters of the algorithm
Returns
--------------
footprints_obj
Footprints object
"""
if parameters is None:
parameters = {}
incoming_transitions, outgoing_transitions, eventually_enabled = reachability_graph.marking_flow_petri(net, im,
return_eventually_enabled=True,
parameters=parameters)
sequence = set()
s1 = set()
s2 = set()
for m in outgoing_transitions:
input_trans = set(x for x in incoming_transitions[m] if x.label is not None)
output_trans = set(x for x in outgoing_transitions[m].keys() if x.label is not None)
ev_en = set(x for x in eventually_enabled[m])
two_sets = findsubsets(output_trans, 2)
for (x, y) in two_sets:
s1.add((x, y))
s1.add((y, x))
for t1 in input_trans:
for t2 in ev_en:
sequence.add((t1, t2))
for t2 in output_trans:
s2.add((t1, t2))
parallel = {(x, y) for (x, y) in s2 if (y, x) in s2 and (x, y) in s1}
sequence = {(x, y) for (x, y) in sequence if not (x, y) in parallel}
parallel = {(x.label, y.label) for (x, y) in parallel}
sequence = {(x.label, y.label) for (x, y) in sequence}
par_els = {(x[0], x[1]) for x in sequence if (x[1], x[0]) in sequence}
for el in par_els:
parallel.add(el)
sequence.remove(el)
activities = set(x.label for x in net.transitions if x.label is not None)
start_activities = set(x.label for x in eventually_enabled[im])
return {Outputs.SEQUENCE.value: sequence, Outputs.PARALLEL.value: parallel, Outputs.ACTIVITIES.value: activities, Outputs.START_ACTIVITIES.value: start_activities}