pm4py.algo.conformance.tokenreplay.diagnostics 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.conformance.tokenreplay.diagnostics.duration_diagnostics 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.conformance.tokenreplay.diagnostics.duration_diagnostics.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.conformance.tokenreplay.diagnostics.duration_diagnostics.get_case_duration(case, timestamp_key='time:timestamp')[source]#
Gets the duration of a case
Parameters#
- case
Case
- timestamp_key
Attribute of the event to use as timestamp
Returns#
- case_duration
Case duration
- pm4py.algo.conformance.tokenreplay.diagnostics.duration_diagnostics.get_median_case_duration(list_cases, timestamp_key='time:timestamp')[source]#
Gets the median case duration of a list of cases
Parameters#
- list_cases
List of cases
- timestamp_key
Attribute of the event to use as timestamp
Returns#
- median_case_duration
Median case duration
- pm4py.algo.conformance.tokenreplay.diagnostics.duration_diagnostics.diagnose_from_notexisting_activities(log, notexisting_activities_in_model, parameters=None)[source]#
Provide some conformance diagnostics related to activities that are not present in the model
Parameters#
- log
Trace log
- notexisting_activities_in_model
Not existing activities in the model
- parameters
- Possible parameters of the algorithm, including:
Parameters.TIMESTAMP_KEY -> attribute of the event containing the timestamp
Returns#
- diagnostics
For each problematic activity, diagnostics about case duration
- pm4py.algo.conformance.tokenreplay.diagnostics.duration_diagnostics.diagnose_from_trans_fitness(log, trans_fitness, parameters=None)[source]#
Provide some conformance diagnostics related to transitions that are executed in a unfit manner
Parameters#
- log
Trace log
- trans_fitness
For each transition, keeps track of unfit executions
- parameters
- Possible parameters of the algorithm, including:
Parameters.TIMESTAMP_KEY -> attribute of the event containing the timestamp
Returns#
- diagnostics
For each problematic transition, diagnostics about case duration
pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis 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.conformance.tokenreplay.diagnostics.root_cause_analysis.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- STRING_ATTRIBUTES = 'string_attributes'#
- NUMERIC_ATTRIBUTES = 'numeric_attributes'#
- ENABLE_MULTIPLIER = 'enable_multiplier'#
- pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis.form_log_from_dictio_couple(first_cases_repr, second_cases_repr, enable_multiplier=False)[source]#
Form a log from a couple of dictionary, to use for root cause analysis
Parameters#
- first_cases_repr
First cases representation
- second_cases_repr
Second cases representation
- enable_multiplier
Enable balancing of classes
Returns#
- log
Trace log object
- pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis.form_representation_from_dictio_couple(first_cases_repr, second_cases_repr, string_attributes, numeric_attributes, enable_multiplier=False)[source]#
Gets a log representation, useful for training the decision tree, from a couple of dictionaries along with the list of string attributes and numeric attributes to consider, to use for root cause analysis
Parameters#
- first_cases_repr
First cases representation
- second_cases_repr
Second cases representation
- string_attributes
String attributes contained in the log
- numeric_attributes
Numeric attributes contained in the log
- enable_multiplier
Enable balancing of classes
Returns#
- data
Matrix representation of the event log
- feature_names
Array of feature names
- pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis.diagnose_from_trans_fitness(log, trans_fitness, parameters=None)[source]#
Perform root cause analysis starting from transition fitness knowledge
Parameters#
- log
Trace log object
- trans_fitness
Transition fitness object
- parameters
- Possible parameters of the algorithm, including:
- string_attributes -> List of string event attributes to consider
in building the decision tree
- numeric_attributes -> List of numeric event attributes to consider
in building the decision tree
Returns#
- diagnostics
- For each problematic transition:
a decision tree comparing fit and unfit executions
feature names
classes
- pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis.diagnose_from_notexisting_activities(log, notexisting_activities_in_model, parameters=None)[source]#
Perform root cause analysis related to activities that are not present in the model
Parameters#
- log
Trace log object
- notexisting_activities_in_model
Not existing activities in the model
- parameters
- Possible parameters of the algorithm, including:
- string_attributes -> List of string event attributes to consider
in building the decision tree
- numeric_attributes -> List of numeric event attributes to consider
in building the decision tree
Returns#
- diagnostics
- For each problematic transition:
a decision tree comparing fit and unfit executions
feature names
classes