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Merge branch 'release' of https://github.com/pm4py/pm4py-core into release
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‎pm4py/algo/discovery/genetic/__init__.py‎

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'''
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU Affero General Public License as
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published by the Free Software Foundation, either version 3 of the
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License, or any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU Affero General Public License for more details.
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You should have received a copy of the GNU Affero General Public License
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along with this program. If not, see this software project's root or
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visit <https://www.gnu.org/licenses/>.
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Website: https://processintelligence.solutions
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Contact: info@processintelligence.solutions
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'''
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'''
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)

‎pm4py/algo/discovery/genetic/algorithm.py‎

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'''
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU Affero General Public License as
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published by the Free Software Foundation, either version 3 of the
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License, or any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU Affero General Public License for more details.
14-
15-
You should have received a copy of the GNU Affero General Public License
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along with this program. If not, see this software project's root or
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visit <https://www.gnu.org/licenses/>.
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19-
Website: https://processintelligence.solutions
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Contact: info@processintelligence.solutions
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'''
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'''
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)
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'''
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from enum import Enum
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from pm4py.util import exec_utils
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from typing import Union, Optional, Dict, Any, Tuple
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from pm4py.algo.discovery.genetic.variants import classic
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from pm4py.objects.petri_net.obj import PetriNet, Marking
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from pm4py.objects.log.obj import EventLog, EventStream
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import pandas as pd
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from pm4py.util import constants
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from typing import Union, Optional, Dict, Any, Tuple
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class Parameters(Enum):
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MUTATION_RATE = "mutation_rate"
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GENERATIONS = "generations"
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ELITISM_MIN_SAMPLE = "elitism_min_sample"
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TOURNAMENT_TIMEOUT = "tournament_timeout"
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LOG_CSV = "log_csv"
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from pm4py.algo.discovery.genetic.variants import classic
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class Variants(Enum):
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CLASSIC = classic
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‎pm4py/algo/discovery/genetic/util.py‎

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'''
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU Affero General Public License as
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import itertools
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# typing
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from typing import Self, Union
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from collections.abc import Iterable
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from typing import Dict, FrozenSet, List, Tuple
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InputMap = Dict[str, List[FrozenSet]]
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OutputMap = Dict[str, List[FrozenSet]]
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Individual = Tuple[InputMap, OutputMap]
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TransitionMap = dict[str,list[frozenset]]
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InputMap = OutputMap = TransitionMap
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Individual = tuple[InputMap,OutputMap]
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class iset(frozenset):
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"Indexable frozenset printing as set, i.e. without `frozenset(…)`"
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def __repr__(self):
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return "{" + repr(sorted(self))[1:-1] + "}"
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@staticmethod
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def flat(item: Iterable) -> "iset":
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def flat(item: Iterable) -> Self:
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return iset(itertools.chain(*item))
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def rand_partition(pool: Iterable) -> List[iset]:
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def rand_partition(pool: Iterable) -> list[Union[set,frozenset]]:
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pool = set(pool)
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# also ensures no activity in two partitions
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# s. 4. Causal Matrix, Def. 4; https://doi.org/10.1007/11494744_5
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pool -= draw
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return partition
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def get_src_sink_sets_for_wfnet(I: InputMap, O: OutputMap, T: List[str]) -> Tuple[List[str], List[str]]:
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def add_singleton_partition(tmap: TransitionMap, key: str, t: str):
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partitions = tmap.setdefault(key, []) # tmap[key] or []
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if not any(t in partition for partition in partitions):
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partitions.append(iset({t}))
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def remove_transition_from_partitions(tmap: TransitionMap, key: str, t: str):
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partitions = tmap.setdefault(key, []) # tmap[key] or []
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for i,partition in enumerate(partitions):
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if t in partition:
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updated = iset(partition - {t})
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if updated:
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partitions[i] = updated
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else:
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del partitions[i]
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return
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def get_src_sink_sets_for_wfnet(I: InputMap, O: OutputMap, T: list[str]) -> tuple[list[str],list[str]]:
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"""Determines input set and output set, which need to be connected by a place to create a WF-net"""
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def add2graphs(graphs, t, nextT):
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# find graph
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else:
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successors.extend(S)
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graph += successors
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# merge if end = start
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for tn in successors:
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# merge if path end = start
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for tn in successors: # tn = end
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for g2 in graphs[:]: # [:] = copy
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if g2[0] == tn and g2 != graph:
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graph += g2
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for t in T:
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graphsI = add2graphs(graphsI, t, I)
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graphsO = add2graphs(graphsO, t, O)
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first = [g[0] for g in graphsO] # ⋃first = reachable via O[∀t]
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last = [g[0] for g in graphsI] # ⋃first = reachable via I[∀t]
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return first, last
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sources = [g[0] for g in graphsO] # ⋃sources = ∀t reachable from O[∀sources]
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sinks = [g[0] for g in graphsI] # ⋃sinks = ∀t reachable from I[∀sinks]
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return sources, sinks

‎pm4py/algo/discovery/genetic/variants/__init__.py‎

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'''
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PM4Py – A Process Mining Library for Python
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Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
4-
5-
This program is free software: you can redistribute it and/or modify
6-
it under the terms of the GNU Affero General Public License as
7-
published by the Free Software Foundation, either version 3 of the
8-
License, or any later version.
9-
10-
This program is distributed in the hope that it will be useful,
11-
but WITHOUT ANY WARRANTY; without even the implied warranty of
12-
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13-
GNU Affero General Public License for more details.
14-
15-
You should have received a copy of the GNU Affero General Public License
16-
along with this program. If not, see this software project's root or
17-
visit <https://www.gnu.org/licenses/>.
18-
19-
Website: https://processintelligence.solutions
20-
Contact: info@processintelligence.solutions
21-
'''
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'''
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PM4Py – A Process Mining Library for Python
243
Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)

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