pm4py.algo.conformance.alignments.petri_net.utils package#

PM4Py – A Process Mining Library for Python

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program 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 Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

Submodules#

pm4py.algo.conformance.alignments.petri_net.utils.log_enrichment module#

PM4Py – A Process Mining Library for Python

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.algo.conformance.alignments.petri_net.utils.log_enrichment.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

TARGET_ATTRIBUTE = 'target_attribute'#

ENABLE_DEEPCOPY = 'enable_deepcopy'#

pm4py.algo.conformance.alignments.petri_net.utils.log_enrichment.apply(log: EventLog, aligned_traces: List[Dict[str, Any]], parameters: Dict[str | Parameters, Any] | None = None) → EventLog[source]#

Enriches a log with the results of the alignment against a model, obtained with the parameter ‘ret_tuple_as_trans_desc’ set to True (so the identifiers of the transitions of the model are known). In particular, the events that are not move-on-log are enriched with the identifier of the corresponding element of the model.

Parameters#

log: Event log
aligned_traces: Result of the alignments, done with the parameter ‘ret_tuple_as_trans_Desc_ set to True.
parameters: Parameters of the algorithm: - Parameters.TARGET_ATTRIBUTE: attribute that should be used for the enrichment - Parameters.ENABLE_DEEPCOPY: deepcopy the event log to not enrich the original log.

Returns#

enriched_log: Log enriched with an additional attribute (the identifier of the corresponding element of the model)