'''
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 typing import Any, Optional, Dict, Union, List, Tuple
import pandas as pd
from pm4py.objects.log.obj import EventLog, EventStream
from pm4py.util import exec_utils
from pm4py.algo.transformation.log_to_features.variants import event_based, trace_based
[docs]class Variants(Enum):
EVENT_BASED = event_based
TRACE_BASED = trace_based
[docs]def apply(log: Union[EventLog, pd.DataFrame, EventStream], variant: Any = Variants.TRACE_BASED,
parameters: Optional[Dict[Any, Any]] = None) -> Tuple[Any, List[str]]:
"""
Extracts the features from a log object
Parameters
---------------
log
Event log
variant
Variant of the feature extraction to use:
- Variants.EVENT_BASED => (default) extracts, for each trace, a list of numerical vectors containing for each
event the corresponding features
- Variants.TRACE_BASED => extracts for each trace a single numerical vector containing the features
of the trace
Returns
---------------
data
Data to provide for decision tree learning
feature_names
Names of the features, in order
"""
if parameters is None:
parameters = {}
return exec_utils.get_variant(variant).apply(log, parameters=parameters)