Source code for pm4py.algo.conformance.alignments.edit_distance.algorithm
'''
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
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visit <https://www.gnu.org/licenses/>.
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Contact: info@processintelligence.solutions
'''
from enum import Enum
from typing import Optional, Dict, Any, Union
from pm4py.algo.conformance.alignments.edit_distance.variants import (
edit_distance,
)
from pm4py.objects.log.obj import EventLog
from pm4py.util import exec_utils
from pm4py.util import typing
import pandas as pd
[docs]
class Variants(Enum):
EDIT_DISTANCE = edit_distance
[docs]
def apply(
log1: Union[EventLog, pd.DataFrame],
log2: Union[EventLog, pd.DataFrame],
variant=Variants.EDIT_DISTANCE,
parameters: Optional[Dict[Any, Any]] = None,
) -> typing.ListAlignments:
"""
Aligns each trace of the first log against the second log
Parameters
--------------
log1
First log
log2
Second log
variant
Variant of the algorithm, possible values:
- Variants.EDIT_DISTANCE: minimizes the edit distance
parameters
Parameters of the algorithm
Returns
---------------
aligned_traces
List that contains, for each trace of the first log, the corresponding alignment
"""
return exec_utils.get_variant(variant).apply(
log1, log2, parameters=parameters
)