pm4py.algo.filtering.log.ltl package¶
Submodules¶
pm4py.algo.filtering.log.ltl.ltl_checker module¶
This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
PM4Py 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 General Public License for more details.
You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.
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pm4py.algo.filtering.log.ltl.ltl_checker.A_eventually_B(log, A, B, parameters=None)[source]¶ Applies the A eventually B rule
Parameters: - log – Log
- A – A attribute value
- B – B attribute value
- parameters – Parameters of the algorithm, including the attribute key and the positive parameter: - If True, returns all the cases containing A and B and in which A was eventually followed by B - If False, returns all the cases not containing A or B, or in which an instance of A was not eventually followed by an instance of B
Returns: Filtered log
Return type: filtered_log
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pm4py.algo.filtering.log.ltl.ltl_checker.A_eventually_B_eventually_C(log, A, B, C, parameters=None)[source]¶ Applies the A eventually B eventually C rule
Parameters: - log – Log
- A – A attribute value
- B – B attribute value
- C – C attribute value
- parameters – Parameters of the algorithm, including the attribute key and the positive parameter: - If True, returns all the cases containing A, B and C and in which A was eventually followed by B and B was eventually followed by C - If False, returns all the cases not containing A or B or C, or in which an instance of A was not eventually followed by an instance of B or an instance of B was not eventually followed by C
Returns: Filtered log
Return type: filtered_log
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pm4py.algo.filtering.log.ltl.ltl_checker.A_eventually_B_eventually_C_eventually_D(log, A, B, C, D, parameters=None)[source]¶ Applies the A eventually B eventually C rule
Parameters: - log – Log
- A – A attribute value
- B – B attribute value
- C – C attribute value
- D – D attribute value
- parameters – Parameters of the algorithm, including the attribute key and the positive parameter: - If True, returns all the cases containing A, B and C and in which A was eventually followed by B and B was eventually followed by C - If False, returns all the cases not containing A or B or C, or in which an instance of A was not eventually followed by an instance of B or an instance of B was not eventually followed by C
Returns: Filtered log
Return type: filtered_log
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pm4py.algo.filtering.log.ltl.ltl_checker.A_next_B_next_C(log: pm4py.objects.log.obj.EventLog, A: str, B: str, C: str, parameters: Optional[Dict[Union[str, pm4py.algo.filtering.log.ltl.ltl_checker.Parameters], Any]] = None) → pm4py.objects.log.obj.EventLog[source]¶ Applies the A next B next C rule
Parameters: - log – Log
- A – A attribute value
- B – B attribute value
- C – C attribute value
- parameters – Parameters of the algorithm, including the attribute key and the positive parameter: - If True, returns all the cases containing A, B and C and in which A was directly followed by B and B was directly followed by C - If False, returns all the cases not containing A or B or C, or in which none instance of A was directly followed by an instance of B and B was directly followed by C
Returns: Filtered log
Return type: filtered_log
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class
pm4py.algo.filtering.log.ltl.ltl_checker.Parameters[source]¶ Bases:
enum.EnumAn enumeration.
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ATTRIBUTE_KEY= 'pm4py:param:attribute_key'¶
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ENABLE_TIMESTAMP= 'enable_timestamp'¶
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POSITIVE= 'positive'¶
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RESOURCE_KEY= 'pm4py:param:resource_key'¶
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TIMESTAMP_DIFF_BOUNDARIES= 'timestamp_diff_boundaries'¶
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TIMESTAMP_KEY= 'pm4py:param:timestamp_key'¶
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pm4py.algo.filtering.log.ltl.ltl_checker.attr_value_different_persons(log: pm4py.objects.log.obj.EventLog, A: str, parameters: Optional[Dict[Union[str, pm4py.algo.filtering.log.ltl.ltl_checker.Parameters], Any]] = None) → pm4py.objects.log.obj.EventLog[source]¶ Checks whether an attribute value is assumed on events done by different resources
Parameters: log – Log
A – A attribute value
parameters –
- Parameters of the algorithm, including the attribute key and the positive parameter:
- if True, then filters all the cases containing occurrences of A done by different resources
- if False, then filters all the cases not containing occurrences of A done by different resources
Returns: Filtered log
Return type: filtered_log
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pm4py.algo.filtering.log.ltl.ltl_checker.eventually_follows(log: pm4py.objects.log.obj.EventLog, attribute_values: List[str], parameters: Optional[Dict[Union[str, pm4py.algo.filtering.log.ltl.ltl_checker.Parameters], Any]] = None) → pm4py.objects.log.obj.EventLog[source]¶ Applies the eventually follows rule
Parameters: - log – Log
- attribute_values – A list of attribute_values attribute_values[n] follows attribute_values[n-1] follows … follows attribute_values[0]
- parameters – Parameters of the algorithm, including the attribute key and the positive parameter: - If True, returns all the cases containing all attribute_values and in which attribute_values[i] was eventually followed by attribute_values[i + 1] - If False, returns all the cases not containing all attribute_values, or in which an instance of attribute_values[i] was not eventually followed by an instance of attribute_values[i + 1]
Returns: Filtered log
Return type: filtered_log
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pm4py.algo.filtering.log.ltl.ltl_checker.four_eyes_principle(log: pm4py.objects.log.obj.EventLog, A: str, B: str, parameters: Optional[Dict[Union[str, pm4py.algo.filtering.log.ltl.ltl_checker.Parameters], Any]] = None) → pm4py.objects.log.obj.EventLog[source]¶ Verifies the Four Eyes Principle given A and B
Parameters: log – Log
A – A attribute value
B – B attribute value
parameters – Parameters of the algorithm, including the attribute key and the positive parameter: - if True, then filters all the cases containing A and B which have empty intersection between the set
of resources doing A and B
- if False, then filters all the cases containing A and B which have no empty intersection between the set of resources doing A and B
Returns: Filtered log
Return type: filtered_log
Module contents¶
This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
PM4Py 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 General Public License for more details.
You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.