Source code for pm4py.algo.discovery.ocel.link_analysis.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
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.
Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
from pm4py.algo.discovery.ocel.link_analysis.variants import classic
from enum import Enum
from pm4py.util import exec_utils
import pandas as pd
from typing import Optional, Dict, Any
from pm4py.objects.log.obj import EventLog, EventStream
from typing import Union
from pm4py.objects.conversion.log import converter
[docs]
class Variants(Enum):
CLASSIC = classic
[docs]
def apply(
log: Union[EventLog, EventStream, pd.DataFrame],
variant=Variants.CLASSIC,
parameters: Optional[Dict[Any, Any]] = None,
) -> pd.DataFrame:
"""
Applies a link analysis algorithm on the provided log object.
Parameters
-----------------
log
Event log
variant
Variant of the algorithm to consider
parameters
Variant-specific parameters
Returns
-----------------
link_analysis_dataframe
Link analysis dataframe
"""
if parameters is None:
parameters = {}
return exec_utils.get_variant(variant).apply(
converter.apply(
log,
variant=converter.Variants.TO_DATA_FRAME,
parameters=parameters,
),
parameters=parameters,
)