Genetic Miner: Fixes and Improvements

pm4py/algo/discovery/genetic/__init__.py

@@ -1,24 +1,3 @@
-'''
-    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
-'''
 '''
     PM4Py – A Process Mining Library for Python
 Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)

pm4py/algo/discovery/genetic/algorithm.py

@@ -1,24 +1,3 @@
-'''
-    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
-'''
 '''
     PM4Py – A Process Mining Library for Python
 Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)
@@ -42,11 +21,12 @@
 '''
 from enum import Enum
 from pm4py.util import exec_utils
-from typing import Union, Optional, Dict, Any, Tuple
+from pm4py.algo.discovery.genetic.variants import classic
 from pm4py.objects.petri_net.obj import PetriNet, Marking
 from pm4py.objects.log.obj import EventLog, EventStream
 import pandas as pd
 from pm4py.util import constants
+from typing import Union, Optional, Dict, Any, Tuple
 
 
 class Parameters(Enum):
@@ -59,13 +39,8 @@ class Parameters(Enum):
     MUTATION_RATE = "mutation_rate"
     GENERATIONS = "generations"
     ELITISM_MIN_SAMPLE = "elitism_min_sample"
-    TOURNAMENT_TIMEOUT = "tournament_timeout"
     LOG_CSV = "log_csv"
 
-
-from pm4py.algo.discovery.genetic.variants import classic
-
-
 class Variants(Enum):
     CLASSIC = classic
 

pm4py/algo/discovery/genetic/util.py

@@ -1,6 +1,6 @@
 '''
-    PM4Py – A Process Mining Library for Python
-Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
+    PM4Py – A Process Mining Library for Python
+Copyright (C) 2026 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
@@ -25,22 +25,22 @@
 import itertools
 
 # typing
+from typing import Self, Union
 from collections.abc import Iterable
-from typing import Dict, FrozenSet, List, Tuple
-InputMap = Dict[str, List[FrozenSet]]
-OutputMap = Dict[str, List[FrozenSet]]
-Individual = Tuple[InputMap, OutputMap]
+TransitionMap = dict[str,list[frozenset]]
+InputMap = OutputMap = TransitionMap
+Individual = tuple[InputMap,OutputMap]
 
 class iset(frozenset):
     "Indexable frozenset printing as set, i.e. without `frozenset(…)`"
     def __repr__(self):
         return "{" + repr(sorted(self))[1:-1] + "}"
 
     @staticmethod
-    def flat(item: Iterable) -> "iset":
+    def flat(item: Iterable) -> Self:
         return iset(itertools.chain(*item))
 
-def rand_partition(pool: Iterable) -> List[iset]:
+def rand_partition(pool: Iterable) -> list[Union[set,frozenset]]:
     pool = set(pool)
     #     also ensures no activity in two partitions
     #     s. 4. Causal Matrix, Def. 4; https://doi.org/10.1007/11494744_5
@@ -54,7 +54,23 @@ def rand_partition(pool: Iterable) -> List[iset]:
         pool -= draw
     return partition
 
-def get_src_sink_sets_for_wfnet(I: InputMap, O: OutputMap, T: List[str]) -> Tuple[List[str], List[str]]:
+def add_singleton_partition(tmap: TransitionMap, key: str, t: str):
+    partitions = tmap.setdefault(key, []) # tmap[key] or []
+    if not any(t in partition for partition in partitions):
+        partitions.append(iset({t}))
+
+def remove_transition_from_partitions(tmap: TransitionMap, key: str, t: str):
+    partitions = tmap.setdefault(key, []) # tmap[key] or []
+    for i,partition in enumerate(partitions):
+        if t in partition:
+            updated = iset(partition - {t})
+            if updated:
+                partitions[i] = updated
+            else:
+                del partitions[i]
+            return
+
+def get_src_sink_sets_for_wfnet(I: InputMap, O: OutputMap, T: list[str]) -> tuple[list[str],list[str]]:
     """Determines input set and output set, which need to be connected by a place to create a WF-net"""
     def add2graphs(graphs, t, nextT):
         # find graph
@@ -70,8 +86,8 @@ def add2graphs(graphs, t, nextT):
             else:
                 successors.extend(S)
         graph += successors
-        # merge if end = start
-        for tn in successors:
+        # merge if path end = start
+        for tn in successors: # tn = end
             for g2 in graphs[:]: # [:] = copy
                 if g2[0] == tn and g2 != graph:
                     graph += g2
@@ -82,6 +98,6 @@ def add2graphs(graphs, t, nextT):
     for t in T:
         graphsI = add2graphs(graphsI, t, I)
         graphsO = add2graphs(graphsO, t, O)
-    first = [g[0] for g in graphsO] # ⋃first = reachable via O[∀t]
-    last = [g[0] for g in graphsI] # ⋃first = reachable via I[∀t]
-    return first, last
+    sources = [g[0] for g in graphsO] # ⋃sources = ∀t reachable from O[∀sources]
+    sinks = [g[0] for g in graphsI] # ⋃sinks = ∀t reachable from I[∀sinks]
+    return sources, sinks

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

@@ -1,24 +1,3 @@
-'''
-    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
-'''
 '''
     PM4Py – A Process Mining Library for Python
 Copyright (C) 2026 Process Intelligence Solutions UG (haftungsbeschränkt)