Source code for pm4py.algo.transformation.log_to_interval_tree.algorithm

'''
PM4Py – A Process Mining Library for Python
Copyright (C) 2026 Process Intelligence Solutions GmbH

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
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visit <https://www.gnu.org/licenses/>.

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Contact: info@processintelligence.solutions
'''
from enum import Enum
from typing import Optional, Dict, Any

from pm4py.util.intervaltree import IntervalTree

from pm4py.algo.transformation.log_to_interval_tree.variants import open_paths
from pm4py.objects.log.obj import EventLog
from pm4py.util import exec_utils
from pm4py.objects.conversion.log import converter as log_converter


[docs] class Variants(Enum): OPEN_PATHS = open_paths
[docs] def apply( log: EventLog, variant=Variants.OPEN_PATHS, parameters: Optional[Dict[Any, Any]] = None, ) -> IntervalTree: """ Transforms the event log to an interval tree using one of the available variants Parameters ----------------- log Event log variant Variant of the algorithm to be used: - Variants.OPEN_PATHS: transforms the event log to an interval tree in which the intervals are the directly-follows paths in the log (open at the complete timestamp of the source event, and closed at the start timestamp of the target event), and having as associated data the source and the target event. Returns ----------------- tree Interval tree object (which can be queried at a given timestamp, or range of timestamps) """ log = log_converter.apply( log, variant=log_converter.Variants.TO_EVENT_LOG, parameters=parameters ) return exec_utils.get_variant(variant).apply(log, parameters=parameters)