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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 pm4py.algo.conformance.log_skeleton.variants import classic | |
| from enum import Enum | |
| from pm4py.util import exec_utils | |
| from typing import Optional, Dict, Any, Union, List, Set | |
| from pm4py.objects.log.obj import EventLog, Trace | |
| import pandas as pd | |
| class Variants(Enum): | |
| CLASSIC = classic | |
| CLASSIC = Variants.CLASSIC | |
| DEFAULT_VARIANT = Variants.CLASSIC | |
| def apply(obj: Union[EventLog, Trace, pd.DataFrame], model: Dict[str, Any], variant=DEFAULT_VARIANT, parameters: Optional[Dict[Any, Any]] = None) -> List[Set[Any]]: | |
| """ | |
| Apply log-skeleton based conformance checking given an event log/trace | |
| and a log-skeleton model | |
| Parameters | |
| -------------- | |
| obj | |
| Object (event log/trace) | |
| model | |
| Log-skeleton model | |
| variant | |
| Variant of the algorithm, possible values: Variants.CLASSIC | |
| parameters | |
| Parameters of the algorithm, including: | |
| - Parameters.ACTIVITY_KEY | |
| - Parameters.CONSIDERED_CONSTRAINTS, among: equivalence, always_after, always_before, never_together, directly_follows, activ_freq | |
| Returns | |
| -------------- | |
| aligned_traces | |
| Conformance checking results for each trace: | |
| - Outputs.IS_FIT => boolean that tells if the trace is perfectly fit according to the model | |
| - Outputs.DEV_FITNESS => deviation based fitness (between 0 and 1; the more the trace is near to 1 the more fit is) | |
| - Outputs.DEVIATIONS => list of deviations in the model | |
| """ | |
| if parameters is None: | |
| parameters = {} | |
| if type(obj) is Trace: | |
| return exec_utils.get_variant(variant).apply_trace(obj, model, parameters=parameters) | |
| else: | |
| return exec_utils.get_variant(variant).apply_log(obj, model, parameters=parameters) | |
| def apply_from_variants_list(var_list: List[List[str]], model: Dict[str, Any], variant=DEFAULT_VARIANT, parameters: Optional[Dict[Any, Any]] = None) -> List[Set[Any]]: | |
| """ | |
| Performs conformance checking using the log skeleton, | |
| applying it from a list of variants | |
| Parameters | |
| -------------- | |
| var_list | |
| List of variants | |
| model | |
| Log skeleton model | |
| variant | |
| Variant of the algorithm, possible values: Variants.CLASSIC | |
| parameters | |
| Parameters | |
| Returns | |
| -------------- | |
| conformance_dictio | |
| Dictionary containing, for each variant, the result | |
| of log skeleton checking | |
| """ | |
| if parameters is None: | |
| parameters = {} | |
| return exec_utils.get_variant(variant).apply_from_variants_list(var_list, model, parameters=parameters) | |
| def get_diagnostics_dataframe(log: EventLog, conf_result: List[Set[Any]], variant=DEFAULT_VARIANT, parameters: Optional[Dict[Any, Any]] = None) -> pd.DataFrame: | |
| """ | |
| Gets the diagnostics dataframe from a log and the results | |
| of log skeleton-based conformance checking | |
| Parameters | |
| -------------- | |
| log | |
| Event log | |
| conf_result | |
| Results of conformance checking | |
| Returns | |
| -------------- | |
| diagn_dataframe | |
| Diagnostics dataframe | |
| """ | |
| if parameters is None: | |
| parameters = {} | |
| return exec_utils.get_variant(variant).get_diagnostics_dataframe(log, conf_result, parameters=parameters) | |