Source code for pm4py.algo.transformation.ocel.features.events.event_num_rel_objs_type

'''
    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/>.
'''
from pm4py.objects.ocel.obj import OCEL
from typing import Optional, Dict, Any


[docs]def apply(ocel: OCEL, parameters: Optional[Dict[Any, Any]] = None): """ Feature: assigns to each event the number of related objects per object type. If N different object types are present in the log, then N different columns are created. Parameters ---------------- ocel OCEL parameters Parameters of the algorithm Returns ---------------- data Extracted feature values feature_names Feature names """ if parameters is None: parameters = {} ordered_events = list(ocel.events[ocel.event_id_column]) rel_objs = ocel.relations.groupby(ocel.event_id_column)[ocel.object_id_column].agg(list).to_dict() object_types = list(ocel.objects[ocel.object_type_column].unique()) object_type_association = ocel.objects[[ocel.object_id_column, ocel.object_type_column]].to_dict("records") object_type_association = {x[ocel.object_id_column]: x[ocel.object_type_column] for x in object_type_association} data = [] feature_names = ["@@event_num_rel_objs_type_"+ot for ot in object_types] for ev in ordered_events: data.append([]) for ot in object_types: rel_objs_ot = {x for x in rel_objs[ev] if object_type_association[x] == ot} data[-1].append(len(rel_objs_ot)) return data, feature_names