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| ''' | |
| 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 statistics import mean | |
| from enum import Enum | |
| from pm4py.util import exec_utils | |
| from typing import Optional, Dict, Any, Union | |
| from pm4py.objects.petri_net.obj import PetriNet | |
| class Parameters(Enum): | |
| K = "k" | |
| def apply(petri_net: PetriNet, parameters: Optional[Dict[Union[str, Parameters], Any]] = None) -> float: | |
| """ | |
| Gets simplicity from a Petri net | |
| Vázquez-Barreiros, Borja, Manuel Mucientes, and Manuel Lama. "ProDiGen: Mining complete, precise and minimal | |
| structure process models with a genetic algorithm." Information Sciences 294 (2015): 315-333. | |
| Parameters | |
| ----------- | |
| petri_net | |
| Petri net | |
| parameters | |
| Possible parameters of the algorithm: | |
| - K: defines the value to be substracted in the formula: the lower is the value, | |
| the lower is the simplicity value. k is the baseline arc degree (that is subtracted from the others) | |
| Returns | |
| ----------- | |
| simplicity | |
| Simplicity measure associated to the Petri net | |
| """ | |
| if parameters is None: | |
| parameters = {} | |
| # original model: we have plenty of choices there. | |
| # one choice is about taking a model containing the most frequent variant, | |
| # along with a short circuit between the final and the initial marking. | |
| # in that case, the average arc degree of the "original model" is 2 | |
| # keep the default to 2 | |
| k = exec_utils.get_param_value(Parameters.K, parameters, 2) | |
| # TODO: verify the real provenence of the approach before! | |
| all_arc_degrees = [] | |
| for place in petri_net.places: | |
| all_arc_degrees.append(len(place.in_arcs) + len(place.out_arcs)) | |
| for trans in petri_net.transitions: | |
| all_arc_degrees.append(len(trans.in_arcs) + len(trans.out_arcs)) | |
| mean_degree = mean(all_arc_degrees) if all_arc_degrees else 0.0 | |
| simplicity = 1.0 / (1.0 + max(mean_degree - k, 0)) | |
| return simplicity | |