pm4py.algo.conformance.log_skeleton 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

Subpackages

• pm4py.algo.conformance.log_skeleton.variants package
  • Submodules
  • pm4py.algo.conformance.log_skeleton.variants.classic module
    • Parameters
      • Parameters.NOISE_THRESHOLD
      • Parameters.CONSIDERED_CONSTRAINTS
      • Parameters.DEFAULT_CONSIDERED_CONSTRAINTS
      • Parameters.CASE_ID_KEY
      • Parameters.ACTIVITY_KEY
      • Parameters.PARAMETER_VARIANT_DELIMITER
    • DiscoveryOutputs
      • DiscoveryOutputs.EQUIVALENCE
      • DiscoveryOutputs.ALWAYS_AFTER
      • DiscoveryOutputs.ALWAYS_BEFORE
      • DiscoveryOutputs.NEVER_TOGETHER
      • DiscoveryOutputs.DIRECTLY_FOLLOWS
      • DiscoveryOutputs.ACTIV_FREQ
    • Outputs
      • Outputs.DEVIATIONS
      • Outputs.NO_DEV_TOTAL
      • Outputs.NO_CONSTR_TOTAL
      • Outputs.DEV_FITNESS
      • Outputs.IS_FIT
    • apply_log()
    • apply_trace()
    • apply_actlist()
    • apply_from_variants_list()
    • after_decode()
    • get_diagnostics_dataframe()

Submodules

pm4py.algo.conformance.log_skeleton.algorithm 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.log_skeleton.algorithm.Variants(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

CLASSIC = <module 'pm4py.algo.conformance.log_skeleton.variants.classic' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\conformance\\log_skeleton\\variants\\classic.py'>

pm4py.algo.conformance.log_skeleton.algorithm.apply(obj: EventLog | Trace | DataFrame, model: Dict[str, Any], variant=Variants.CLASSIC, parameters: Dict[Any, Any] | None = None) → List[Set[Any]]

Apply log-skeleton based conformance checking given an event log/trace and a log-skeleton model

Parameters

obj

Object (event log/trace)

model

Log-skeleton model

variant

Variant of the algorithm, possible values: Variants.CLASSIC

parameters

Parameters of the algorithm, including: - Parameters.ACTIVITY_KEY - Parameters.CONSIDERED_CONSTRAINTS, among: equivalence, always_after, always_before, never_together, directly_follows, activ_freq

Returns

aligned_traces

Conformance checking results for each trace: - Outputs.IS_FIT => boolean that tells if the trace is perfectly fit according to the model - Outputs.DEV_FITNESS => deviation based fitness (between 0 and 1; the more the trace is near to 1 the more fit is) - Outputs.DEVIATIONS => list of deviations in the model

pm4py.algo.conformance.log_skeleton.algorithm.apply_from_variants_list(var_list: List[List[str]], model: Dict[str, Any], variant=Variants.CLASSIC, parameters: Dict[Any, Any] | None = None) → List[Set[Any]]

Performs conformance checking using the log skeleton, applying it from a list of variants

Parameters

var_list

List of variants

model

Log skeleton model

variant

Variant of the algorithm, possible values: Variants.CLASSIC

parameters

Parameters

Returns

conformance_dictio

Dictionary containing, for each variant, the result of log skeleton checking

pm4py.algo.conformance.log_skeleton.algorithm.get_diagnostics_dataframe(log: EventLog, conf_result: List[Set[Any]], variant=Variants.CLASSIC, parameters: Dict[Any, Any] | None = None) → DataFrame

Gets the diagnostics dataframe from a log and the results of log skeleton-based conformance checking

Parameters

log

Event log

conf_result

Results of conformance checking

Returns

diagn_dataframe

Diagnostics dataframe