pm4py.algo.discovery.dfg.variants.case_attributes module

class pm4py.algo.discovery.dfg.variants.case_attributes.Parameters(*values)

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'

CASE_ATTRIBUTES = 'case_attributes'

RETURN_NODES_ATTRIBUTES = 'return_nodes_attributes'

pm4py.algo.discovery.dfg.variants.case_attributes.apply(log: EventLog, parameters: Dict[str | Parameters, Any] | None = None) → Tuple[Dict[Tuple[str, str], Dict[str, Dict[str, Any]]], Dict[str, Dict[str, Dict[str, Any]]]] | Dict[Tuple[str, str], Dict[str, Dict[str, Any]]]

Discovers a directly-follows graph from an event log, with the edges that are annotated with the different values for the given case attributes.

Parameters:

• log – Event log

• parameters – Parameters of the variant, including: - Parameters.ACTIVITY_KEY => the attribute to use as activity - Parameters.CASE_ATTRIBUTES => the case attributes that are used to annotate the edges (default: the case ID) - Parameters.RETURN_NODES_ATTRIBUTES => (optional) returns also a dictionary with the values of the attributes for each activity of the graph (default: False)

Returns:

• dfg –

  Directly-follows graph (with the edges annotated with the specified case attributes), e.g.:

  {(‘register request’, ‘examine casually’): {‘creator’: {‘Fluxicon Nitro’: 3}, ‘concept:name’:

  {‘3’: 1, ‘6’: 1, ‘5’: 1}} …

• nodes –

  (Optional) dictionary of activities (annotated with the specified case attributes), e.g.:

  {‘register request’: {‘creator’: {‘Fluxicon Nitro’: 6}, ‘concept:name’:

  {‘3’: 1, ‘2’: 1, ‘1’: 1, ‘6’: 1, ‘5’: 1, ‘4’: 1}} …