pm4py.statistics.passed_time.log 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
Subpackages#
Submodules#
pm4py.statistics.passed_time.log.algorithm 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.statistics.passed_time.log.algorithm.Variants(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- PRE = <module 'pm4py.statistics.passed_time.log.variants.pre' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\statistics\\passed_time\\log\\variants\\pre.py'>#
- POST = <module 'pm4py.statistics.passed_time.log.variants.post' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\statistics\\passed_time\\log\\variants\\post.py'>#
- PREPOST = <module 'pm4py.statistics.passed_time.log.variants.prepost' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\statistics\\passed_time\\log\\variants\\prepost.py'>#
- pm4py.statistics.passed_time.log.algorithm.apply(log: EventLog, activity: str, variant=Variants.PRE, parameters: Dict[Any, Any] | None = None) Dict[str, Any][source]#
Gets statistics on execution times of the paths to/from the activity
Parameters#
- log
Log
- activity
Activity
- variant
- Variant:
Variants.PRE
Variants.POST
Variants.PREPOST
- parameters
Possible parameters of the algorithm
Returns#
- dictio
Dictio containing the times from/to the activity