pm4py.algo.conformance.tokenreplay.diagnostics package¶

Submodules¶

pm4py.algo.conformance.tokenreplay.diagnostics.duration_diagnostics 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/>.

class pm4py.algo.conformance.tokenreplay.diagnostics.duration_diagnostics.Parameters[source]¶

Bases: enum.Enum

An enumeration.

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'¶

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:	For each problematic activity, diagnostics about case duration
Return type:	diagnostics

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:	For each problematic transition, diagnostics about case duration
Return type:	diagnostics

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
Return type:	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
Return type:	median_case_duration

pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis 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/>.

class pm4py.algo.conformance.tokenreplay.diagnostics.root_cause_analysis.Parameters[source]¶

Bases: enum.Enum

An enumeration.

ENABLE_MULTIPLIER = 'enable_multiplier'¶

NUMERIC_ATTRIBUTES = 'numeric_attributes'¶

STRING_ATTRIBUTES = 'string_attributes'¶

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:

For each problematic transition:

a decision tree comparing fit and unfit executions
feature names
classes

Return type:

diagnostics

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:

For each problematic transition:

a decision tree comparing fit and unfit executions
feature names
classes

Return type:

diagnostics

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:	Trace log object
Return type:	log

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

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/>.