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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 enum import Enum
from pm4py.util import exec_utils
from pm4py.algo.clustering.profiles.variants import sklearn_profiles
from pm4py.objects.log.obj import EventLog, EventStream
import pandas as pd
from typing import Optional, Dict, Any, Generator, Union
class Variants(Enum):
SKLEARN_PROFILES = sklearn_profiles
def apply(log: Union[EventLog, EventStream, pd.DataFrame], variant=Variants.SKLEARN_PROFILES, parameters: Optional[Dict[Any, Any]] = None) -> Generator[EventLog, None, None]:
"""
Apply clustering to the provided event log
(methods based on the extraction of profiles for the traces of the event log)
Implements the approach described in:
Song, Minseok, Christian W. Günther, and Wil MP Van der Aalst. "Trace clustering in process mining." Business Process Management Workshops: BPM 2008 International Workshops, Milano, Italy, September 1-4, 2008. Revised Papers 6. Springer Berlin Heidelberg, 2009.
Parameters
----------------
log
Event log
variant
Variant of the clustering to be used, available values:
- Variants.SKLEARN_PROFILES
parameters
Variant-specific parameters
Returns
----------------
generator
Generator of dataframes (clusters)
"""
return exec_utils.get_variant(variant).apply(log, parameters=parameters)
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