pm4py.algo.transformation.ocel.split_ocel.variants package#

PM4Py â€“ 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.transformation.ocel.split_ocel.variants.ancestors_descendants 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.transformation.ocel.split_ocel.variants.ancestors_descendants.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

OBJECT_TYPE = 'object_type'#

MAX_OBJS = 'max_objs'#

pm4py.algo.transformation.ocel.split_ocel.variants.ancestors_descendants.apply(ocel: OCEL, parameters: Dict[Any, Any] | None = None) → Collection[OCEL][source]#

Provided an object-centric event log and the specification of an object type, splits the OCEL in one OCEL per object of the given object type, which is the original OCEL filtered on the current object plus its ascendants and descendants

Parameters#

ocel: Object-centric event log
parameters: Parameters of the algorithm, including: - Parameters.OBJECT_TYPE => the object type to consider when applying the algorithm

Returns#

lst_ocels: List of OCELs with the aforementioned possibilities

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

Bases: Enum

CENTRALITY_MEASURE = 'centrality_measure'#

MAX_VALUE_CENTRALITY = 'max_value_centrality'#

ENABLE_PRINTS = 'enable_prints'#

pm4py.algo.transformation.ocel.split_ocel.variants.connected_components.apply(ocel: OCEL, parameters: Dict[Any, Any] | None = None)[source]#

Split the OCEL based on the connected components of the object interaction graph. It is also possible, to remove the nodes with higher centrality providing a centrality measure and a maximum value of this centrality.

Parameters#

ocel: OCEL
parameters: Parameters of the algorithm, including: - Parameters.CENTRALITY_MEASURE => centrality measure - Parameters.MAX_VALUE_CENTRALITY => maximum value of centrality

Returns#

splitted_ocel: List of OCELs found based on the connected components