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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) | |