pm4py.algo.conformance.declare package#

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/>.

Subpackages#

Submodules#

pm4py.algo.conformance.declare.algorithm module#

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/>.

class pm4py.algo.conformance.declare.algorithm.Variants(value)[source]#

Bases: Enum

An enumeration.

CLASSIC = <module 'pm4py.algo.conformance.declare.variants.classic' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\conformance\\declare\\variants\\classic.py'>#
pm4py.algo.conformance.declare.algorithm.apply(log: Union[EventLog, DataFrame], model: Dict[str, Dict[Any, Dict[str, int]]], variant=Variants.CLASSIC, parameters: Optional[Dict[Any, Any]] = None) List[Dict[str, Any]][source]#

Applies conformance checking against a DECLARE model.

Parameters#

log

Event log / Pandas dataframe

model

DECLARE model

variant

Variant to be used: - Variants.CLASSIC

parameters

Variant-specific parameters

Returns#

lst_conf_res

List containing for every case a dictionary with different keys: - no_constr_total => the total number of constraints of the DECLARE model - deviations => a list of deviations - no_dev_total => the total number of deviations - dev_fitness => the fitness (1 - no_dev_total / no_constr_total) - is_fit => True if the case is perfectly fit

pm4py.algo.conformance.declare.algorithm.get_diagnostics_dataframe(log, conf_result, variant=Variants.CLASSIC, parameters=None) DataFrame[source]#

Gets the diagnostics dataframe from a log and the results of DECLARE-based conformance checking

Parameters#

log

Event log

conf_result

Results of conformance checking

variant

Variant to be used: - Variants.CLASSIC

parameters

Variant-specific parameters

Returns#

diagn_dataframe

Diagnostics dataframe