pm4py.algo.conformance.tokenreplay.diagnostics package#

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/>.

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(value)[source]#

Bases: Enum

An enumeration.

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#

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(value)[source]#

Bases: Enum

An enumeration.

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