'''
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.
This program 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 Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.
Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
import datetime
from copy import copy
from enum import Enum
from typing import Optional, Dict, Any, Union
from pm4py.objects import petri_net
from pm4py.objects.log import obj as log_instance
from pm4py.objects.log.obj import EventLog
from pm4py.objects.petri_net.obj import PetriNet, Marking
from pm4py.objects.petri_net.utils import (
final_marking as final_marking_discovery,
)
from pm4py.util import constants
from pm4py.util import exec_utils
from pm4py.util import xes_constants
from pm4py.util.dt_parsing.variants import strpfromiso
[docs]
class Parameters(Enum):
ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY
CASE_ID_KEY = constants.PARAMETER_CONSTANT_CASEID_KEY
RETURN_VISITED_ELEMENTS = "return_visited_elements"
NO_TRACES = "noTraces"
MAX_TRACE_LENGTH = "maxTraceLength"
LOG = "log"
STOCHASTIC_MAP = "smap"
PETRI_SEMANTICS = "petri_semantics"
[docs]
def apply_playout(
net,
initial_marking,
no_traces=100,
max_trace_length=100,
case_id_key=xes_constants.DEFAULT_TRACEID_KEY,
activity_key=xes_constants.DEFAULT_NAME_KEY,
timestamp_key=xes_constants.DEFAULT_TIMESTAMP_KEY,
final_marking=None,
smap=None,
log=None,
return_visited_elements=False,
semantics=petri_net.semantics.ClassicSemantics(),
parameters=None,
):
"""
Do the playout of a Petrinet generating a log
Parameters
----------
net
Petri net to play-out
initial_marking
Initial marking of the Petri net
no_traces
Number of traces to generate
max_trace_length
Maximum number of events per trace (do break)
case_id_key
Trace attribute that is the case ID
activity_key
Event attribute that corresponds to the activity
timestamp_key
Event attribute that corresponds to the timestamp
final_marking
If provided, the final marking of the Petri net
smap
Stochastic map
log
Log
semantics
Semantics of the Petri net to be used (default: petri_net.semantics.ClassicSemantics())
"""
from pm4py.algo.simulation.montecarlo.utils import replay
from pm4py.objects.stochastic_petri import utils as stochastic_utils
if final_marking is None:
# infer the final marking from the net
final_marking = final_marking_discovery.discover_final_marking(net)
if smap is None:
if log is None:
raise Exception(
"please provide at least one between stochastic map and log"
)
if parameters is None:
parameters = {}
parameters_rep = copy(parameters)
parameters_rep[Parameters.ACTIVITY_KEY] = activity_key
parameters_rep[Parameters.TIMESTAMP_KEY] = timestamp_key
smap = replay.get_map_from_log_and_net(
log, net, initial_marking, final_marking, parameters=parameters_rep
)
# assigns to each event an increased timestamp from 1970
curr_timestamp = 10000000
all_visited_elements = []
for i in range(no_traces):
visited_elements = []
visible_transitions_visited = []
marking = copy(initial_marking)
while len(visible_transitions_visited) < max_trace_length:
visited_elements.append(marking)
if not semantics.enabled_transitions(
net, marking
): # supports nets with possible deadlocks
break
all_enabled_trans = semantics.enabled_transitions(net, marking)
if final_marking is not None and marking == final_marking:
en_t_list = list(all_enabled_trans.union({None}))
else:
en_t_list = list(all_enabled_trans)
trans = stochastic_utils.pick_transition(en_t_list, smap)
if trans is None:
break
visited_elements.append(trans)
if trans.label is not None:
visible_transitions_visited.append(trans)
marking = semantics.execute(trans, net, marking)
all_visited_elements.append(tuple(visited_elements))
if return_visited_elements:
return all_visited_elements
log = log_instance.EventLog()
for index, visited_elements in enumerate(all_visited_elements):
trace = log_instance.Trace()
trace.attributes[case_id_key] = str(index)
for element in visited_elements:
if (
type(element) is PetriNet.Transition
and element.label is not None
):
event = log_instance.Event()
event[activity_key] = element.label
event[timestamp_key] = strpfromiso.fix_naivety(
datetime.datetime.fromtimestamp(curr_timestamp)
)
trace.append(event)
# increases by 1 second
curr_timestamp += 1
log.append(trace)
return log
[docs]
def apply(
net: PetriNet,
initial_marking: Marking,
final_marking: Marking = None,
parameters: Optional[Dict[Union[str, Parameters], Any]] = None,
) -> EventLog:
"""
Do the playout of a Petrinet generating a log
Parameters
-----------
net
Petri net to play-out
initial_marking
Initial marking of the Petri net
final_marking
If provided, the final marking of the Petri net
parameters
Parameters of the algorithm:
Parameters.NO_TRACES -> Number of traces of the log to generate
Parameters.MAX_TRACE_LENGTH -> Maximum trace length
Parameters.PETRI_SEMANTICS -> Petri net semantics to be used (default: petri_nets.semantics.ClassicSemantics())
"""
if parameters is None:
parameters = {}
case_id_key = exec_utils.get_param_value(
Parameters.CASE_ID_KEY, parameters, xes_constants.DEFAULT_TRACEID_KEY
)
activity_key = exec_utils.get_param_value(
Parameters.ACTIVITY_KEY, parameters, xes_constants.DEFAULT_NAME_KEY
)
timestamp_key = exec_utils.get_param_value(
Parameters.TIMESTAMP_KEY,
parameters,
xes_constants.DEFAULT_TIMESTAMP_KEY,
)
no_traces = exec_utils.get_param_value(
Parameters.NO_TRACES, parameters, 1000
)
max_trace_length = exec_utils.get_param_value(
Parameters.MAX_TRACE_LENGTH, parameters, 1000
)
smap = exec_utils.get_param_value(
Parameters.STOCHASTIC_MAP, parameters, None
)
log = exec_utils.get_param_value(Parameters.LOG, parameters, None)
return_visited_elements = exec_utils.get_param_value(
Parameters.RETURN_VISITED_ELEMENTS, parameters, False
)
semantics = exec_utils.get_param_value(
Parameters.PETRI_SEMANTICS,
parameters,
petri_net.semantics.ClassicSemantics(),
)
return apply_playout(
net,
initial_marking,
max_trace_length=max_trace_length,
no_traces=no_traces,
case_id_key=case_id_key,
activity_key=activity_key,
timestamp_key=timestamp_key,
final_marking=final_marking,
smap=smap,
log=log,
return_visited_elements=return_visited_elements,
semantics=semantics,
parameters=None,
)
