pm4py.algo.discovery.alpha 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.discovery.alpha.data_structures package
  • Submodules
  • pm4py.algo.discovery.alpha.data_structures.alpha_classic_abstraction module
    • ClassicAlphaAbstraction
      • ClassicAlphaAbstraction.start_activities
      • ClassicAlphaAbstraction.end_activities
      • ClassicAlphaAbstraction.dfg
      • ClassicAlphaAbstraction.causal_relation
      • ClassicAlphaAbstraction.parallel_relation
      • ClassicAlphaAbstraction.activity_key
• pm4py.algo.discovery.alpha.utils package
  • Submodules
  • pm4py.algo.discovery.alpha.utils.endpoints module
    • derive_end_activities_from_log()
    • derive_start_activities_from_log()
• pm4py.algo.discovery.alpha.variants package
  • Submodules
  • pm4py.algo.discovery.alpha.variants.classic module
    • Parameters
      • Parameters.ACTIVITY_KEY
      • Parameters.START_TIMESTAMP_KEY
      • Parameters.TIMESTAMP_KEY
      • Parameters.CASE_ID_KEY
    • apply()
    • apply_dfg()
    • apply_dfg_sa_ea()
  • pm4py.algo.discovery.alpha.variants.plus module
    • Parameters
      • Parameters.ACTIVITY_KEY
      • Parameters.REMOVE_UNCONNECTED
    • preprocessing()
    • get_relations()
    • processing()
    • get_sharp_relation()
    • get_sharp_relations_for_sets()
    • postprocessing()
    • apply()
    • add_source()
    • add_sink()
    • remove_initial_hidden_if_possible()
    • remove_final_hidden_if_possible()
    • remove_unconnected_transitions()

Submodules

pm4py.algo.discovery.alpha.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.discovery.alpha.algorithm.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'

START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'

CASE_ID_KEY = 'pm4py:param:case_id_key'

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

Bases: Enum

ALPHA_VERSION_CLASSIC = <module 'pm4py.algo.discovery.alpha.variants.classic' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\alpha\\variants\\classic.py'>

ALPHA_VERSION_PLUS = <module 'pm4py.algo.discovery.alpha.variants.plus' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\alpha\\variants\\plus.py'>

pm4py.algo.discovery.alpha.algorithm.apply(log: EventLog | EventStream | DataFrame, parameters: Dict[str | Parameters, Any] | None = None, variant=Variants.ALPHA_VERSION_CLASSIC) → Tuple[PetriNet, Marking, Marking]

Apply the Alpha Miner on top of a log

Parameters

log

Log

variant

Variant of the algorithm to use:

• Variants.ALPHA_VERSION_CLASSIC

• Variants.ALPHA_VERSION_PLUS

parameters

Possible parameters of the algorithm, including:

Parameters.ACTIVITY_KEY -> Name of the attribute that contains the activity

Returns

net

Petri net

marking

Initial marking

final_marking

Final marking

pm4py.algo.discovery.alpha.algorithm.apply_dfg(dfg: Dict[Tuple[str, str], int], parameters: Dict[str | Parameters, Any] | None = None, variant=Variants.ALPHA_VERSION_CLASSIC) → Tuple[PetriNet, Marking, Marking]

Apply Alpha Miner directly on top of a DFG graph

Parameters

dfg

Directly-Follows graph

variant

Variant of the algorithm to use (classic)

parameters

Possible parameters of the algorithm, including:

activity key -> Name of the attribute that contains the activity

Returns

net

Petri net

marking

Initial marking

final_marking

Final marking