pm4py.algo.discovery.dfg.algorithm module#

class pm4py.algo.discovery.dfg.algorithm.Parameters(*values)[source]#

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'#
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
CASE_ID_KEY = 'pm4py:param:case_id_key'#
class pm4py.algo.discovery.dfg.algorithm.Variants(*values)[source]#

Bases: Enum

NATIVE = <module 'pm4py.algo.discovery.dfg.variants.native' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/native.py'>#
FREQUENCY = <module 'pm4py.algo.discovery.dfg.variants.native' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/native.py'>#
PERFORMANCE = <module 'pm4py.algo.discovery.dfg.variants.performance' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/performance.py'>#
FREQUENCY_GREEDY = <module 'pm4py.algo.discovery.dfg.variants.native' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/native.py'>#
PERFORMANCE_GREEDY = <module 'pm4py.algo.discovery.dfg.variants.performance' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/performance.py'>#
FREQ_TRIPLES = <module 'pm4py.algo.discovery.dfg.variants.freq_triples' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/freq_triples.py'>#
CASE_ATTRIBUTES = <module 'pm4py.algo.discovery.dfg.variants.case_attributes' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/case_attributes.py'>#
CLEAN = <module 'pm4py.algo.discovery.dfg.variants.clean' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/discovery/dfg/variants/clean.py'>#
pm4py.algo.discovery.dfg.algorithm.apply(log: EventLog | EventStream | DataFrame, parameters: Dict[Any, Any] | None = None, variant=Variants.NATIVE) → Dict[Tuple[str, str], float][source]#

Calculates DFG graph (frequency or performance) starting from a log

Parameters:

  • log – Log

  • parameters –

    Possible parameters passed to the algorithms:

    Parameters.AGGREGATION_MEASURE -> performance aggregation measure (min, max, mean, median) Parameters.ACTIVITY_KEY -> Attribute to use as activity Parameters.TIMESTAMP_KEY -> Attribute to use as timestamp

  • variant –

    Variant of the algorithm to use, possible values:

    • Variants.NATIVE

    • Variants.FREQUENCY

    • Variants.FREQUENCY_GREEDY

    • Variants.PERFORMANCE

    • Variants.PERFORMANCE_GREEDY

    • Variants.FREQ_TRIPLES

Returns:

DFG graph

Return type:

dfg