'''
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.algo.discovery.causal.variants import alpha, heuristic
from enum import Enum
from pm4py.util import exec_utils
from typing import Optional, Dict, Any, Union, Tuple
[docs]class Variants(Enum):
CAUSAL_ALPHA = alpha
CAUSAL_HEURISTIC = heuristic
CAUSAL_ALPHA = Variants.CAUSAL_ALPHA
CAUSAL_HEURISTIC = Variants.CAUSAL_HEURISTIC
VERSIONS = {CAUSAL_ALPHA, CAUSAL_HEURISTIC}
[docs]def apply(dfg: Dict[Tuple[str, str], int], variant=CAUSAL_ALPHA) -> Dict[Tuple[str, str], int]:
"""
Computes the causal relation on the basis of a given directly follows graph.
Parameters
-----------
dfg
Directly follows graph
variant
Variant of the algorithm to use:
- Variants.CAUSAL_ALPHA
- Variants.CAUSAL_HEURISTIC
Returns
-----------
causal relations
dict
"""
return exec_utils.get_variant(variant).apply(dfg)