# pm4py.algo.discovery.alpha package

## pm4py.algo.discovery.alpha.algorithm 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.discovery.alpha.algorithm.Parameters(value)[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
CASE_ID_KEY = 'pm4py:param:case_id_key'
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'
class pm4py.algo.discovery.alpha.algorithm.Variants(value)[source]

Bases: enum.Enum

An enumeration.

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: Union[pm4py.objects.log.obj.EventLog, pm4py.objects.log.obj.EventStream, pandas.core.frame.DataFrame], parameters: Optional[Dict[Union[str, pm4py.algo.discovery.alpha.algorithm.Parameters], Any]] = None, variant=Variants.ALPHA_VERSION_CLASSIC) [source]

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: Optional[Dict[Union[str, pm4py.algo.discovery.alpha.algorithm.Parameters], Any]] = None, variant=Variants.ALPHA_VERSION_CLASSIC) [source]

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

## 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/>.