'''
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
'''
from collections import Counter
from typing import Tuple, List, Optional, Dict, Any
from pm4py.algo.discovery.inductive.dtypes.im_ds import (
IMDataStructureUVCL,
IMDataStructureDFG,
)
from pm4py.algo.discovery.inductive.fall_through.abc import FallThrough
from pm4py.objects.process_tree.obj import ProcessTree, Operator
from pm4py.objects.dfg.obj import DFG
from pm4py.algo.discovery.inductive.dtypes.im_dfg import InductiveDFG
from copy import copy
[docs]
class EmptyTracesUVCL(FallThrough[IMDataStructureUVCL]):
[docs]
@classmethod
def apply(
cls,
obj: IMDataStructureUVCL,
pool=None,
manager=None,
parameters: Optional[Dict[str, Any]] = None,
) -> Optional[Tuple[ProcessTree, List[IMDataStructureUVCL]]]:
if cls.holds(obj, parameters):
data_structure = copy(obj.data_structure)
del data_structure[()]
if data_structure:
return ProcessTree(operator=Operator.XOR), [
IMDataStructureUVCL(Counter()),
IMDataStructureUVCL(data_structure),
]
else:
return ProcessTree(), []
else:
return None
[docs]
@classmethod
def holds(
cls,
obj: IMDataStructureUVCL,
parameters: Optional[Dict[str, Any]] = None,
) -> bool:
return len(list(filter(lambda t: len(t) == 0, obj.data_structure))) > 0
[docs]
class EmptyTracesDFG(FallThrough[IMDataStructureDFG]):
[docs]
@classmethod
def apply(
cls,
obj: IMDataStructureDFG,
pool=None,
manager=None,
parameters: Optional[Dict[str, Any]] = None,
) -> Optional[Tuple[ProcessTree, List[IMDataStructureDFG]]]:
if cls.holds(obj, parameters):
# If the DFG itself is empty, the log contains only empty traces -> just τ
dfg = obj.data_structure.dfg
is_empty = (
len(dfg.graph) == 0
and len(dfg.start_activities) == 0
and len(dfg.end_activities) == 0
)
if is_empty:
return ProcessTree(), []
# Otherwise, split: XOR(τ, non-empty part)
return ProcessTree(operator=Operator.XOR), [
IMDataStructureDFG(InductiveDFG(DFG())),
# note: skip intentionally False here; τ is already handled on the XOR
IMDataStructureDFG(InductiveDFG(obj.data_structure.dfg)),
]
return None
[docs]
@classmethod
def holds(
cls,
obj: IMDataStructureDFG,
parameters: Optional[Dict[str, Any]] = None,
) -> bool:
return obj.data_structure.skip
