pm4py.algo.conformance.antialignments.variants package#

PM4Py – A Process Mining Library for Python

Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

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.conformance.antialignments.variants.discounted_a_star module#

PM4Py – A Process Mining Library for Python

Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

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

class pm4py.algo.conformance.antialignments.variants.discounted_a_star.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

MARKING_LIMIT = 'marking_limit'#
EXPONENT = 'exponent'#
EPSILON = 'epsilon'#
pm4py.algo.conformance.antialignments.variants.discounted_a_star.apply(log, petri_net, ini, fin, parameters=None)[source]#

This function is a preliminary function for __search of the discounted algorihtm for AA. The function gets the parameters and launches the algorithm on the variants (all traces aren’t usefull for AA, see paper).

pm4py.algo.conformance.antialignments.variants.discounted_a_star.getPrecision(run, variants, epsilon)[source]#

Once we obtained an AA, we can get the precision of the process model. This is computed with the levenshtein edit distance.