pm4py.algo.discovery.causal 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#

pm4py.algo.discovery.causal.variants package

Submodules#

pm4py.algo.discovery.causal.algorithm 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.causal.algorithm.Variants(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

CAUSAL_ALPHA = <module 'pm4py.algo.discovery.causal.variants.alpha' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\causal\\variants\\alpha.py'>#

CAUSAL_HEURISTIC = <module 'pm4py.algo.discovery.causal.variants.heuristic' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\causal\\variants\\heuristic.py'>#

pm4py.algo.discovery.causal.algorithm.apply(dfg: Dict[Tuple[str, str], int], variant=Variants.CAUSAL_ALPHA) → Dict[Tuple[str, str], int][source]#

Computes the causal relation on the basis of a given directly follows graph.

Parameters#

dfg

Directly follows graph

variant

Variant of the algorithm to use:

Variants.CAUSAL_ALPHA
Variants.CAUSAL_HEURISTIC

Returns#

causal relations: dict