pm4py.convert.convert_log_to_networkx#

pm4py.convert.convert_log_to_networkx(log: EventLog | EventStream | DataFrame, include_df: bool = True, case_id_key: str = 'concept:name', other_case_attributes_as_nodes: Collection[str] | None = None, event_attributes_as_nodes: Collection[str] | None = None) → DiGraph[source]#

Converts an event log object to a NetworkX DiGraph object. The nodes of the graph are the events, the cases (and possibly the attributes of the log). The edges are: - Connecting each event to the corresponding case (BELONGS_TO type) - Connecting every event to the directly-following one (DF type, if enabled) - Connecting every case/event to the given attribute values (ATTRIBUTE_EDGE type)

Parameters:

  • log – log object (EventLog, EventStream, Pandas dataframe)

  • include_df (bool) – include the directly-follows graph relation in the graph (bool)

  • case_id_attribute – specify which attribute at the case level should be considered the case ID (str)

  • other_case_attributes_as_nodes – specify which attributes at the case level should be inserted in the graph as nodes (other than the caseID) (list, default empty)

  • event_attributes_as_nodes – specify which attributes at the event level should be inserted in the graph as nodes (list, default empty)

Return type:

nx.DiGraph

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