pm4py.algo.discovery.inductive 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
Subpackages#
- pm4py.algo.discovery.inductive.base_case package
- pm4py.algo.discovery.inductive.cuts package
- Submodules
- pm4py.algo.discovery.inductive.cuts.abc module
- pm4py.algo.discovery.inductive.cuts.concurrency module
- pm4py.algo.discovery.inductive.cuts.factory module
- pm4py.algo.discovery.inductive.cuts.loop module
- pm4py.algo.discovery.inductive.cuts.sequence module
- pm4py.algo.discovery.inductive.cuts.utils module
- pm4py.algo.discovery.inductive.cuts.xor module
- pm4py.algo.discovery.inductive.dtypes package
- pm4py.algo.discovery.inductive.fall_through package
- Submodules
- pm4py.algo.discovery.inductive.fall_through.abc module
- pm4py.algo.discovery.inductive.fall_through.activity_concurrent module
- pm4py.algo.discovery.inductive.fall_through.activity_once_per_trace module
- pm4py.algo.discovery.inductive.fall_through.empty_traces module
- pm4py.algo.discovery.inductive.fall_through.factory module
- pm4py.algo.discovery.inductive.fall_through.flower module
- pm4py.algo.discovery.inductive.fall_through.strict_tau_loop module
- pm4py.algo.discovery.inductive.fall_through.tau_loop module
- pm4py.algo.discovery.inductive.variants package
Submodules#
pm4py.algo.discovery.inductive.algorithm 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.discovery.inductive.algorithm.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum
- ACTIVITY_KEY = 'pm4py:param:activity_key'#
- TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- class pm4py.algo.discovery.inductive.algorithm.Variants(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum
- IM = IMInstance.IM#
- IMf = IMInstance.IMf#
- IMd = IMInstance.IMd#
- pm4py.algo.discovery.inductive.algorithm.apply(obj: EventLog | DataFrame | DirectlyFollowsGraph | Counter[Tuple[Any]], parameters: Dict[Any, Any] | None = None, variant=Variants.IM) ProcessTree [source]#