pm4py.algo.discovery.inductive.variants 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/>.

Submodules#

pm4py.algo.discovery.inductive.variants.abc 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.discovery.inductive.variants.abc.Parameters(value)[source]#

Bases: Enum

An enumeration.

MULTIPROCESSING = 'multiprocessing'#
class pm4py.algo.discovery.inductive.variants.abc.InductiveMinerFramework(parameters: Optional[Dict[str, Any]] = None)[source]#

Bases: ABC, Generic[T]

Base Class Implementing the Inductive Miner Framework. How to Extend: 1. Create a dedicated IMDataStructure class (see pm4py.algo.discovery.inductive.dtypes.im_ds.py) 2. Create dedicated Base Cases, Cuts and Fall Throughs for the newly constructed IMDataStructure 3. Extend the BaseCaseFactory, CutFactory and FallThroughFactory with the newly created functions 4. Create a subclass of this class indicating the type on which it is defined and the corresponding IMInstance.

apply_base_cases(obj: T, parameters: Optional[Dict[str, Any]] = None) Optional[ProcessTree][source]#
find_cut(obj: T, parameters: Optional[Dict[str, Any]] = None) Optional[Tuple[ProcessTree, List[T]]][source]#
fall_through(obj: T, parameters: Optional[Dict[str, Any]] = None) Tuple[ProcessTree, List[T]][source]#
apply(obj: T, parameters: Optional[Dict[str, Any]] = None) ProcessTree[source]#
abstract instance() IMInstance[source]#

pm4py.algo.discovery.inductive.variants.im 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.discovery.inductive.variants.im.IM(parameters: Optional[Dict[str, Any]] = None)[source]#

Bases: Generic[T], InductiveMinerFramework[T]

instance() IMInstance[source]#
class pm4py.algo.discovery.inductive.variants.im.IMUVCL(parameters: Optional[Dict[str, Any]] = None)[source]#

Bases: IM[IMDataStructureUVCL]

apply(obj: IMDataStructureUVCL, parameters: Optional[Dict[str, Any]] = None) ProcessTree[source]#

pm4py.algo.discovery.inductive.variants.imd 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.discovery.inductive.variants.imd.IMD(parameters: Optional[Dict[str, Any]] = None)[source]#

Bases: InductiveMinerFramework[IMDataStructureDFG]

instance() IMInstance[source]#

pm4py.algo.discovery.inductive.variants.imf 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.discovery.inductive.variants.imf.IMFParameters(value)[source]#

Bases: Enum

An enumeration.

NOISE_THRESHOLD = 'noise_threshold'#
class pm4py.algo.discovery.inductive.variants.imf.IMF(parameters: Optional[Dict[str, Any]] = None)[source]#

Bases: Generic[T], InductiveMinerFramework[T]

instance() IMInstance[source]#
class pm4py.algo.discovery.inductive.variants.imf.IMFUVCL(parameters: Optional[Dict[str, Any]] = None)[source]#

Bases: IMF[IMDataStructureUVCL]

apply(obj: IMDataStructureUVCL, parameters: Optional[Dict[str, Any]] = None, second_iteration: bool = False) ProcessTree[source]#

pm4py.algo.discovery.inductive.variants.instances 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.discovery.inductive.variants.instances.IMInstance(value)[source]#

Bases: Enum

An enumeration.

IM = 1#
IMd = 2#
IMf = 3#
IMa = 4#
IMi = 5#