pm4py.algo.discovery.powl.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

Subpackages#

Submodules#

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

Bases: IMBasePOWL

instance() → POWLDiscoveryVariant[source]#

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

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

Bases: IMBasePOWL

instance() → POWLDiscoveryVariant[source]#

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

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

Bases: IMBasePOWL

instance() → POWLDiscoveryVariant[source]#

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

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

Bases: IMBasePOWL

instance() → POWLDiscoveryVariant[source]#

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

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

Bases: Generic[T], InductiveMinerFramework[T]

instance() → POWLDiscoveryVariant[source]#

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

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

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

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

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

Bases: Enum

TREE = 1#

BRUTE_FORCE = 2#

MAXIMAL = 3#

DYNAMIC_CLUSTERING = 4#