SNN2.src.core.data.flow.MVNO module

class default flow

Use this module to manage a default flow object.

class SNN2.src.core.data.flow.MVNO.MVNOFlow(*args, dataset: str | None = None, columns: List[str] | None = None, gray_post_train_portion: float = 0.7, gray_in_train_portion: float = 0.3, **kwargs)

Bases: augmented_cls

MVNO.

PreProcessing flow for the MVNO dataset

execute(*args, **kwargs) → None

get_triplet(data: ~SNN2.src.decorators.decorators.c_logger.<locals>.augmented_cls, pkl_name: str = 'default_get_triplet_name') → augmented_cls

class SNN2.src.core.data.flow.MVNO.MVNOFlow_getGoodBadDiff(*args, **kwargs)

Bases: augmented_cls

local_load() → None

load.

class SNN2.src.core.data.flow.MVNO.MVNOFlow_load(*args, **kwargs)

Bases: augmented_cls

MVNOFlow_load. Class used to manage and execute a specific sequence of operations for the loading of the dataframe.

This class object receives the action_parm from the caller. The class object also receives the pkl handler. The method __call__ is used to execute the sequence of operations.

It’s possible to request the number of steps that this class object will exeucte through object.steps attribute. It’s also avaialbe the attribue object.pkl_list that contains the list of pkl files that will be used in the sequence of operations.

It available the method object.check_pkl that returns ture if the pkl files are available and internally loads the pkl files.

local_load() → None

load.