pm4py.streaming.algo.discovery.dfg.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.streaming.algo.discovery.dfg.variants.frequency 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.streaming.algo.discovery.dfg.variants.frequency.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- DICT_VARIANT = 'dict_variant'#
- DICT_ID = 'dict_id'#
- CASE_DICT_ID = 'case_dict_id'#
- DFG_DICT_ID = 'dfg_dict_id'#
- ACT_DICT_ID = 'act_dict_id'#
- START_ACT_DICT_ID = 'start_act_dict_id'#
- ACTIVITY_KEY = 'pm4py:param:activity_key'#
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- class pm4py.streaming.algo.discovery.dfg.variants.frequency.StreamingDfgDiscovery(parameters=None)[source]#
Bases:
StreamingAlgorithm- build_dictionaries(parameters)[source]#
Builds the dictionaries that are needed by the discovery operation
Parameters#
- parameters
- Parameters:
Parameters.DICT_VARIANT: type of dictionary to use
Parameters.CASE_DICT_ID: identifier of the case dictionary (hosting the last activity of a case) (0)
Parameters.DFG_DICT_ID: identifier of the DFG dictionary (1)
Parameters.ACT_ID: identifier of the dictionary hosting the count of the activities (2)
Parameters.START_ACT_DICT_ID: identifier of the dictionary hosting the count of the start activities (3)