pm4py.objects.petri_net.importer.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.objects.petri_net.importer.variants.pnml 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.objects.petri_net.importer.variants.pnml.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum
- ENCODING = 'encoding'#
- AUTO_GUESS_FINAL_MARKING = 'auto_guess_final_marking'#
- RETURN_STOCHASTIC_MAP = 'return_stochastic_map'#
- pm4py.objects.petri_net.importer.variants.pnml.import_net(input_file_path, parameters=None)[source]#
Import a Petri net from a PNML file
Parameters#
- input_file_path
Input file path
- parameters
Other parameters of the algorithm
Returns#
- net
Petri net
- im
Initial marking
- fm
Final marking
- pm4py.objects.petri_net.importer.variants.pnml.import_net_from_string(petri_string, parameters=None)[source]#
Imports a Petri net from a string
Parameters#
- petri_string
(Binary) string representing the Petri net
- parameters
Parameters of the algorithm
Returns#
- net
Petri net
- im
Initial marking
- fm
Final marking
- pm4py.objects.petri_net.importer.variants.pnml.import_net_from_xml_object(root, parameters=None)[source]#
Import a Petri net from an etree XML object
Parameters#
- root
Root object of the XML
- parameters
Other parameters of the algorithm: - AUTO_GUESS_FINAL_MARKING: automatic guessing the final marking from the .pnml file