pm4py.algo.discovery.footprints.log.variants 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.discovery.footprints.log.variants.entire_dataframe 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.footprints.log.variants.entire_dataframe.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

DFG = 'dfg'#
SEQUENCE = 'sequence'#
PARALLEL = 'parallel'#
START_ACTIVITIES = 'start_activities'#
END_ACTIVITIES = 'end_activities'#
ACTIVITIES = 'activities'#
SKIPPABLE = 'skippable'#
ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
MIN_TRACE_LENGTH = 'min_trace_length'#
TRACE = 'trace'#
class pm4py.algo.discovery.footprints.log.variants.entire_dataframe.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

SORT_REQUIRED = 'sort_required'#
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'#
INDEX_KEY = 'index_key'#
pm4py.algo.discovery.footprints.log.variants.entire_dataframe.apply(df: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) Dict[str, Any][source]#

Discovers a footprint object from a dataframe (the footprints of the dataframe are returned)

Parameters#

df

Dataframe

parameters

Parameters of the algorithm

Returns#

footprints_obj

Footprints object

pm4py.algo.discovery.footprints.log.variants.entire_event_log 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.footprints.log.variants.entire_event_log.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

DFG = 'dfg'#
SEQUENCE = 'sequence'#
PARALLEL = 'parallel'#
START_ACTIVITIES = 'start_activities'#
END_ACTIVITIES = 'end_activities'#
ACTIVITIES = 'activities'#
SKIPPABLE = 'skippable'#
ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
MIN_TRACE_LENGTH = 'min_trace_length'#
TRACE = 'trace'#
class pm4py.algo.discovery.footprints.log.variants.entire_event_log.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'#
pm4py.algo.discovery.footprints.log.variants.entire_event_log.apply(log: EventLog, parameters: Dict[str | Parameters, Any] | None = None) Dict[str, Any][source]#

Discovers a footprint object from an event log (the footprints of the event log are returned)

Parameters#

log

Log

parameters
Parameters of the algorithm:
  • Parameters.ACTIVITY_KEY

Returns#

footprints_obj

Footprints object

pm4py.algo.discovery.footprints.log.variants.trace_by_trace 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.footprints.log.variants.trace_by_trace.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

DFG = 'dfg'#
SEQUENCE = 'sequence'#
PARALLEL = 'parallel'#
START_ACTIVITIES = 'start_activities'#
END_ACTIVITIES = 'end_activities'#
ACTIVITIES = 'activities'#
SKIPPABLE = 'skippable'#
ACTIVITIES_ALWAYS_HAPPENING = 'activities_always_happening'#
MIN_TRACE_LENGTH = 'min_trace_length'#
TRACE = 'trace'#
class pm4py.algo.discovery.footprints.log.variants.trace_by_trace.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'#
pm4py.algo.discovery.footprints.log.variants.trace_by_trace.apply(log, parameters: Dict[str | Parameters, Any] | None = None) Dict[str, Any][source]#

Discovers a footprint object from an event log (the footprints are returned case-by-case)

Parameters#

log

Log

parameters
Parameters of the algorithm:
  • Parameters.ACTIVITY_KEY

Returns#

footprints_obj

List of footprints for the cases of the log