pm4py.algo.conformance.footprints.variants package#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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.footprints.variants.log_extensive module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.conformance.footprints.variants.log_extensive.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- DFG = 'dfg'#
- SEQUENCE = 'sequence'#
- PARALLEL = 'parallel'#
- START_ACTIVITIES = 'start_activities'#
- END_ACTIVITIES = 'end_activities'#
- ACTIVITIES = 'activities'#
- SKIPPABLE = 'skippable'#
- ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
- MIN_TRACE_LENGTH = 'min_trace_length'#
- TRACE = 'trace'#
- class pm4py.algo.conformance.footprints.variants.log_extensive.ConfOutputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- FOOTPRINTS = 'footprints'#
- START_ACTIVITIES = 'start_activities'#
- END_ACTIVITIES = 'end_activities'#
- MIN_LENGTH_FIT = 'min_length_fit'#
- IS_FOOTPRINTS_FIT = 'is_footprints_fit'#
- pm4py.algo.conformance.footprints.variants.log_extensive.apply(log_footprints: Dict[str, Any], model_footprints: Dict[str, Any], parameters: Dict[Any, Any] | None = None) Dict[str, Any][source]#
Apply footprints conformance between a log footprints object and a model footprints object
Parameters#
- log_footprints
Footprints of the log (entire log)
- model_footprints
Footprints of the model
- parameters
Parameters of the algorithm
Returns#
- violations
Dictionary containing all the violations
pm4py.algo.conformance.footprints.variants.log_model module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.conformance.footprints.variants.log_model.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- DFG = 'dfg'#
- SEQUENCE = 'sequence'#
- PARALLEL = 'parallel'#
- START_ACTIVITIES = 'start_activities'#
- END_ACTIVITIES = 'end_activities'#
- ACTIVITIES = 'activities'#
- SKIPPABLE = 'skippable'#
- ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
- MIN_TRACE_LENGTH = 'min_trace_length'#
- TRACE = 'trace'#
- class pm4py.algo.conformance.footprints.variants.log_model.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- STRICT = 'strict'#
- pm4py.algo.conformance.footprints.variants.log_model.apply_single(log_footprints: Dict[str, Any], model_footprints: Dict[str, Any], parameters: Dict[str | Parameters, Any] | None = None) Dict[str, Any][source]#
Apply footprints conformance between a log footprints object and a model footprints object
Parameters#
- log_footprints
Footprints of the log (NOT a list, but a single footprints object)
- model_footprints
Footprints of the model
- parameters
- Parameters of the algorithm, including:
Parameters.STRICT => strict check of the footprints
Returns#
- violations
Set of all the violations between the log footprints and the model footprints
- pm4py.algo.conformance.footprints.variants.log_model.apply(log_footprints: Dict[str, Any] | List[Dict[str, Any]], model_footprints: Dict[str, Any], parameters: Dict[str | Parameters, Any] | None = None) List[Dict[str, Any]] | Dict[str, Any][source]#
Apply footprints conformance between a log footprints object and a model footprints object
Parameters#
- log_footprints
Footprints of the log
- model_footprints
Footprints of the model
- parameters
- Parameters of the algorithm, including:
Parameters.STRICT => strict check of the footprints
Returns#
- violations
Set of all the violations between the log footprints and the model footprints, OR list of case-per-case violations
- pm4py.algo.conformance.footprints.variants.log_model.get_diagnostics_dataframe(log: EventLog, conf_result: List[Dict[str, Any]] | Dict[str, Any], parameters: Dict[str | Parameters, Any] | None = None) DataFrame[source]#
Gets the diagnostics dataframe from the log and the results of footprints conformance checking (trace-by-trace)
Parameters#
- log
Event log
- conf_result
Conformance checking results (trace-by-trace)
Returns#
- diagn_dataframe
Diagnostics dataframe
pm4py.algo.conformance.footprints.variants.trace_extensive module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.conformance.footprints.variants.trace_extensive.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- DFG = 'dfg'#
- SEQUENCE = 'sequence'#
- PARALLEL = 'parallel'#
- START_ACTIVITIES = 'start_activities'#
- END_ACTIVITIES = 'end_activities'#
- ACTIVITIES = 'activities'#
- SKIPPABLE = 'skippable'#
- ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
- MIN_TRACE_LENGTH = 'min_trace_length'#
- TRACE = 'trace'#
- class pm4py.algo.conformance.footprints.variants.trace_extensive.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- ENABLE_ACT_ALWAYS_EXECUTED = 'enable_act_always_executed'#
- class pm4py.algo.conformance.footprints.variants.trace_extensive.ConfOutputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- FOOTPRINTS = 'footprints'#
- START_ACTIVITIES = 'start_activities'#
- END_ACTIVITIES = 'end_activities'#
- ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
- MIN_LENGTH_FIT = 'min_length_fit'#
- IS_FOOTPRINTS_FIT = 'is_footprints_fit'#
- pm4py.algo.conformance.footprints.variants.trace_extensive.apply(log_footprints: List[Dict[str, Any]], model_footprints: Dict[str, Any], parameters: Dict[str | Parameters, Any] | None = None) List[Dict[str, Any]][source]#
Apply footprints conformance between a log footprints object and a model footprints object
Parameters#
- log_footprints
Footprints of the log (trace-by-trace)
- model_footprints
Footprints of the model
- parameters
Parameters of the algorithm
Returns#
- violations
List containing, for each trace, a dictionary containing the violations
- pm4py.algo.conformance.footprints.variants.trace_extensive.get_diagnostics_dataframe(log: EventLog, conf_result: List[Dict[str, Any]], parameters: Dict[str | Parameters, Any] | None = None) DataFrame[source]#
Gets the diagnostics dataframe from the log and the results of footprints conformance checking (trace-by-trace)
Parameters#
- log
Event log
- conf_result
Conformance checking results (trace-by-trace)
Returns#
- diagn_dataframe
Diagnostics dataframe