# Source code for pm4py.sim

```
'''
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/>.
'''
__doc__ = """
The ``pm4py.sim`` module contains the simulation algorithms offered in ``pm4py``
"""
from collections import Counter
from typing import Union, Tuple
from pm4py.objects.log.obj import EventLog
from pm4py.objects.petri_net.obj import PetriNet, Marking
from pm4py.objects.process_tree.obj import ProcessTree
[docs]def play_out(*args: Union[Tuple[PetriNet, Marking, Marking], dict, Counter, ProcessTree], **kwargs) -> EventLog:
"""
Performs the playout of the provided model,
i.e., gets a set of traces from the model.
The function either takes a petri net, initial and final marking, or, a process tree as an input.
:param args: model (Petri net with initial and final marking, or process tree)
:param kwargs: optional parameters of the method, including:
- parameters: dictionary containing the parameters of the playout, including:
- smap: (if provided) stochastic map to be used to stochastically choose the transition
- log: (if provided) EventLog to be used to compute the stochastic map, if smap not provided
:rtype: ``EventLog``
.. code-block:: python3
import pm4py
net, im, fm = pm4py.read_pnml('model.pnml')
log = pm4py.play_out(net, im, fm)
"""
if len(args) == 3:
from pm4py.objects.petri_net.obj import PetriNet
if isinstance(args[0], PetriNet):
from pm4py.objects.petri_net.obj import ResetNet, InhibitorNet
from pm4py.algo.simulation.playout.petri_net import algorithm
from pm4py.objects.petri_net.semantics import ClassicSemantics
from pm4py.objects.petri_net.inhibitor_reset.semantics import InhibitorResetSemantics
net = args[0]
im = args[1]
fm = args[2]
parameters = kwargs["parameters"] if "parameters" in kwargs else None
if parameters is None:
parameters = {}
variant = algorithm.Variants.BASIC_PLAYOUT
# if the log, or the stochastic map of the transitions, is provided
# use the stochastic playout in place of the basic playout
# (that means, the relative weight of the transitions in a marking
# will be considered during transition's picking)
if "log" in parameters or "smap" in parameters:
variant = algorithm.Variants.STOCHASTIC_PLAYOUT
semantics = ClassicSemantics()
if isinstance(net, ResetNet) or isinstance(net, InhibitorNet):
semantics = InhibitorResetSemantics()
parameters["petri_semantics"] = semantics
return algorithm.apply(net, im, final_marking=fm, variant=variant, parameters=parameters)
elif isinstance(args[0], dict):
from pm4py.algo.simulation.playout.dfg import algorithm as dfg_playout
return dfg_playout.apply(args[0], args[1], args[2], **kwargs)
elif len(args) == 1:
from pm4py.objects.process_tree.obj import ProcessTree
if type(args[0]) is ProcessTree:
from pm4py.algo.simulation.playout.process_tree import algorithm
return algorithm.apply(args[0], **kwargs)
raise Exception("unsupported model for playout")
[docs]def generate_process_tree(**kwargs) -> ProcessTree:
"""
Generates a process tree
Reference paper:
PTandLogGenerator: A Generator for Artificial Event Data
:param kwargs: dictionary containing the parameters of the process tree generator algorithm
:rtype: ``ProcessTree``
.. code-block:: python3
import pm4py
process_tree = pm4py.generate_process_tree()
"""
from pm4py.algo.simulation.tree_generator import algorithm
return algorithm.apply(**kwargs)
```