pm4py.algo.discovery.inductive.variants 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.discovery.inductive.variants.abc 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.discovery.inductive.variants.abc.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

MULTIPROCESSING = 'multiprocessing'#

class pm4py.algo.discovery.inductive.variants.abc.InductiveMinerFramework(parameters: Dict[str, Any] | None = 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: Dict[str, Any] | None = None) → ProcessTree | None[source]#

find_cut(obj: T, parameters: Dict[str, Any] | None = None) → Tuple[ProcessTree, List[T]] | None[source]#

fall_through(obj: T, parameters: Dict[str, Any] | None = None) → Tuple[ProcessTree, List[T]][source]#

apply(obj: T, parameters: Dict[str, Any] | None = None) → ProcessTree[source]#

abstract instance() → IMInstance[source]#

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

Bases: Generic[T], InductiveMinerFramework[T]

instance() → IMInstance[source]#

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

Bases: IM[IMDataStructureUVCL]

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

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

Bases: InductiveMinerFramework[IMDataStructureDFG]

instance() → IMInstance[source]#

pm4py.algo.discovery.inductive.variants.imf 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.discovery.inductive.variants.imf.IMFParameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

NOISE_THRESHOLD = 'noise_threshold'#

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

Bases: Generic[T], InductiveMinerFramework[T]

instance() → IMInstance[source]#

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

Bases: IMF[IMDataStructureUVCL]

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

pm4py.algo.discovery.inductive.variants.instances 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.discovery.inductive.variants.instances.IMInstance(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

IM = 1#

IMd = 2#

IMf = 3#

IMa = 4#

IMi = 5#