pm4py.algo.filtering.log.cases 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.filtering.log.cases.case_filter 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.filtering.log.cases.case_filter.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
- pm4py.algo.filtering.log.cases.case_filter.filter_on_case_performance(log: EventLog, inf_perf: float, sup_perf: float, parameters: Dict[str | Parameters, Any] | None = None) EventLog[source]#
Gets a filtered log keeping only traces that satisfy the given performance requirements
Parameters#
- log
Log
- inf_perf
Lower bound on the performance
- sup_perf
Upper bound on the performance
- parameters
Parameters
Returns#
- filtered_log
Filtered log
- pm4py.algo.filtering.log.cases.case_filter.filter_on_ncases(log: EventLog, max_no_cases: int = 1000) EventLog[source]#
Get only a specified number of traces from a log
Parameters#
- log
Log
- max_no_cases
Desidered number of traces from the log
Returns#
- filtered_log
Filtered log
- pm4py.algo.filtering.log.cases.case_filter.filter_on_case_size(log: EventLog, min_case_size: int = 2, max_case_size=None) EventLog[source]#
Get only traces in the log with a given size
Parameters#
- log
Log
- min_case_size
Minimum desidered size of traces
- max_case_size
Maximum desidered size of traces
Returns#
- filtered_log
Filtered log
- pm4py.algo.filtering.log.cases.case_filter.satisfy_perf(trace: Trace, inf_perf: float, sup_perf: float, timestamp_key: str) bool[source]#
Checks if the trace satisfy the performance requirements
Parameters#
- trace
Trace
- inf_perf
Lower bound on the performance
- sup_perf
Upper bound on the performance
- timestamp_key
Timestamp key
Returns#
- boolean
Boolean (is True if the trace satisfy the given performance requirements)