'''
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 typing import List, Dict, Collection, Set, Tuple
import pandas as pd
from pm4py.objects.ocel.obj import OCEL
[docs]def ocel_get_object_types(ocel: OCEL) -> List[str]:
"""
Gets the list of object types contained in the object-centric event log
(e.g., ["order", "item", "delivery"]).
Parameters
-----------------
ocel
Object-centric event log
Returns
----------------
object_types_list
List of object types contained in the event log (e.g., ["order", "item", "delivery"])
"""
return list(ocel.objects[ocel.object_type_column].unique())
[docs]def ocel_get_attribute_names(ocel: OCEL) -> List[str]:
"""
Gets the list of attributes at the event and the object level of an object-centric event log
(e.g. ["cost", "amount", "name"])
Parameters
-------------------
ocel
Object-centric event log
Returns
-------------------
attributes_list
List of attributes at the event and object level (e.g. ["cost", "amount", "name"])
"""
from pm4py.objects.ocel.util import attributes_names
return attributes_names.get_attribute_names(ocel)
[docs]def ocel_flattening(ocel: OCEL, object_type: str) -> pd.DataFrame:
"""
Flattens the object-centric event log to a traditional event log with the choice of an object type.
In the flattened log, the objects of a given object type are the cases, and each case
contains the set of events related to the object.
Parameters
-------------------
ocel
Object-centric event log
object_type
Object type
Returns
------------------
dataframe
Flattened log in the form of a Pandas dataframe
"""
from pm4py.objects.ocel.util import flattening
return flattening.flatten(ocel, object_type)
[docs]def ocel_object_type_activities(ocel: OCEL) -> Dict[str, Collection[str]]:
"""
Gets the set of activities performed for each object type
Parameters
----------------
ocel
Object-centric event log
Returns
----------------
dict
A dictionary having as key the object types and as values the activities performed for that object type
"""
from pm4py.statistics.ocel import ot_activities
return ot_activities.get_object_type_activities(ocel)
[docs]def ocel_objects_ot_count(ocel: OCEL) -> Dict[str, Dict[str, int]]:
"""
Counts for each event the number of related objects per type
Parameters
-------------------
ocel
Object-centric Event log
parameters
Parameters of the algorithm, including:
- Parameters.EVENT_ID => the event identifier to be used
- Parameters.OBJECT_ID => the object identifier to be used
- Parameters.OBJECT_TYPE => the object type to be used
Returns
-------------------
dict_ot
Dictionary associating to each event identifier a dictionary with the number of related objects
"""
from pm4py.statistics.ocel import objects_ot_count
return objects_ot_count.get_objects_ot_count(ocel)
[docs]def ocel_temporal_summary(ocel: OCEL) -> pd.DataFrame:
"""
Returns the ``temporal summary'' from an object-centric event log.
The temporal summary aggregates all the events performed in the same timestamp,
and reports the set of activities and the involved objects.
:param ocel: object-centric event log
:rtype: ``pd.DataFrame``
.. code-block:: python3
import pm4py
temporal_summary = pm4py.ocel_temporal_summary(ocel)
"""
gdf = ocel.relations.groupby(ocel.event_timestamp)
act_comb = gdf[ocel.event_activity].agg(set).to_frame()
obj_comb = gdf[ocel.object_id_column].agg(set).to_frame()
temporal_summary = act_comb.join(obj_comb).reset_index()
return temporal_summary
[docs]def ocel_objects_summary(ocel: OCEL) -> pd.DataFrame:
"""
Gets the objects summary of an object-centric event log
:param ocel: object-centric event log
:rtype: ``pd.DataFrame``
.. code-block:: python3
import pm4py
objects_summary = pm4py.ocel_objects_summary(ocel)
"""
gdf = ocel.relations.groupby(ocel.object_id_column)
act_comb = gdf[ocel.event_activity].agg(list).to_frame().rename(columns={ocel.event_activity: "activities_lifecycle"})
lif_start_tim = gdf[ocel.event_timestamp].min().to_frame().rename(columns={ocel.event_timestamp: "lifecycle_start"})
lif_end_tim = gdf[ocel.event_timestamp].max().to_frame().rename(columns={ocel.event_timestamp: "lifecycle_end"})
objects_summary = act_comb.join(lif_start_tim)
objects_summary = objects_summary.join(lif_end_tim)
objects_summary = objects_summary.reset_index()
objects_summary["lifecycle_duration"] = (objects_summary["lifecycle_end"] - objects_summary["lifecycle_start"]).astype('timedelta64[s]')
ev_rel_obj = ocel.relations.groupby(ocel.event_id_column)[ocel.object_id_column].apply(list).to_dict()
objects_ids = set(ocel.objects[ocel.object_id_column].unique())
graph = {o: set() for o in objects_ids}
for ev in ev_rel_obj:
rel_obj = ev_rel_obj[ev]
for o1 in rel_obj:
for o2 in rel_obj:
if o1 != o2:
graph[o1].add(o2)
objects_summary["interacting_objects"] = objects_summary[ocel.object_id_column].map(graph)
return objects_summary
[docs]def discover_objects_graph(ocel: OCEL, graph_type: str = "object_interaction") -> Set[Tuple[str, str]]:
"""
Discovers an object graph from the provided object-centric event log
:param ocel: object-centric event log
:param graph_type: type of graph to consider (object_interaction, object_descendants, object_inheritance, object_cobirth, object_codeath)
:rtype: ``Dict[str, Any]``
.. code-block:: python3
import pm4py
ocel = pm4py.read_ocel('trial.ocel')
obj_graph = pm4py.ocel_discover_objects_graph(ocel, graph_type='object_interaction')
"""
if graph_type == "object_interaction":
from pm4py.algo.transformation.ocel.graphs import object_interaction_graph
return object_interaction_graph.apply(ocel)
elif graph_type == "object_descendants":
from pm4py.algo.transformation.ocel.graphs import object_descendants_graph
return object_descendants_graph.apply(ocel)
elif graph_type == "object_inheritance":
from pm4py.algo.transformation.ocel.graphs import object_inheritance_graph
return object_inheritance_graph.apply(ocel)
elif graph_type == "object_cobirth":
from pm4py.algo.transformation.ocel.graphs import object_cobirth_graph
return object_cobirth_graph.apply(ocel)
elif graph_type == "object_codeath":
from pm4py.algo.transformation.ocel.graphs import object_codeath_graph
return object_codeath_graph.apply(ocel)