pm4py.algo.evaluation.simplicity.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.evaluation.simplicity.variants.arc_degree module#

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

Bases: Enum

K = 'k'#

pm4py.algo.evaluation.simplicity.variants.arc_degree.apply(petri_net: PetriNet, parameters: Dict[str | Parameters, Any] | None = None) → float[source]#

Gets simplicity from a Petri net

Vázquez-Barreiros, Borja, Manuel Mucientes, and Manuel Lama. “ProDiGen: Mining complete, precise and minimal structure process models with a genetic algorithm.” Information Sciences 294 (2015): 315-333.

Parameters#

petri_net

Petri net

parameters

Possible parameters of the algorithm:

K: defines the value to be substracted in the formula: the lower is the value,

the lower is the simplicity value. k is the baseline arc degree (that is subtracted from the others)

Returns#

simplicity: Simplicity measure associated to the Petri net

pm4py.algo.evaluation.simplicity.variants.extended_cardoso 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

pm4py.algo.evaluation.simplicity.variants.extended_cardoso.apply(petri_net: PetriNet, parameters: Dict[Any, Any] | None = None) → float[source]#

Computes the extended Cardoso metric as described in the paper:

“Complexity Metrics for Workflow Nets” Lassen, Kristian Bisgaard, and Wil MP van der Aalst

Parameters#

petri_net: Petri net

Returns#

ext_cardoso_metric: Extended Cardoso metric

pm4py.algo.evaluation.simplicity.variants.extended_cyclomatic 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

pm4py.algo.evaluation.simplicity.variants.extended_cyclomatic.apply(petri_net: PetriNet, im: Marking | None = None, parameters: Dict[Any, Any] | None = None) → float[source]#

Computes the extended cyclomatic metric as described in the paper:

“Complexity Metrics for Workflow Nets” Lassen, Kristian Bisgaard, and Wil MP van der Aalst

Parameters#

petri_net: Petri net

Returns#

ext_cyclomatic_metric: Extended Cyclomatic metric