pm4py.algo.discovery.causal package#

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py 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 General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

Subpackages#

Submodules#

pm4py.algo.discovery.causal.algorithm module#

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py 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 General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

class pm4py.algo.discovery.causal.algorithm.Variants(value)[source]#

Bases: Enum

An enumeration.

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