'''
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.ocel.obj import OCEL
from typing import Optional, Dict, Any
from pm4py.algo.discovery.ocel.ocdfg.variants import classic
from enum import Enum
from pm4py.util import exec_utils
[docs]class Variants(Enum):
CLASSIC = classic
[docs]def apply(ocel: OCEL, variant=Variants.CLASSIC, parameters: Optional[Dict[Any, Any]] = None) -> Dict[str, Any]:
"""
Discovers an OC-DFG model from an object-centric event log
Reference paper:
Berti, Alessandro, and Wil van der Aalst. "Extracting multiple viewpoint models from relational databases." Data-Driven Process Discovery and Analysis. Springer, Cham, 2018. 24-51.
Parameters
----------------
ocel
Object-centric event log
variant
Variant of the algorithm to use:
- Variants.CLASSIC
parameters
Variant-specific parameters
Returns
----------------
ocdfg
Object-centric directly-follows graph
"""
return exec_utils.get_variant(variant).apply(ocel, parameters)