pm4py.algo.discovery.inductive.dtypes.im_ds module#

class pm4py.algo.discovery.inductive.dtypes.im_ds.IMDataStructure(obj: T)[source]#

Bases: ABC, Generic[T]

The IMDataStructure is a helper class that unifies all possible data structures (typically logs or dfgs) that can be used for the classical Inductive Miner. The generic TypeVar ‘T’ is supposed to be the underlying data object used, and, should always be able to construct a DFG object. For example, T can be a dataframe, some other object representing an event log or a DFG itself.

property dfg: DirectlyFollowsGraph#
property data_structure: T#
class pm4py.algo.discovery.inductive.dtypes.im_ds.IMDataStructureLog(obj: T)[source]#

Bases: IMDataStructure[T], ABC, Generic[T]

Generic class intended to represent that any subclass carries information that is captured in an event log.

class pm4py.algo.discovery.inductive.dtypes.im_ds.IMDataStructureUVCL(obj: Counter[Tuple[Any]], dfg: DirectlyFollowsGraph | None = None)[source]#

Bases: IMDataStructureLog[Counter[Tuple[Any]]]

Log-Based data structure class that represents the event log as a ‘Univariate Variant Compressed Log (UVCL)’

property dfg: DirectlyFollowsGraph#
class pm4py.algo.discovery.inductive.dtypes.im_ds.IMDataStructureDFG(obj: T)[source]#

Bases: IMDataStructure[InductiveDFG]

DFG-Based data structure class

property dfg: DirectlyFollowsGraph#