OA-STREAMS - Online-adaptive Stream Processing

Ver. 0.6.1 (2023-03-27)

Core classes for online machine learning.

class mlpro.oa.streams.basics.OAShared(p_range: int = 2)

Bases: StreamShared

Template class for shared objects in the context of online adaptive stream processing.

class mlpro.oa.streams.basics.OATask(p_name: str | None = None, p_range_max=1, p_ada: bool = True, p_duplicate_data: bool = False, p_visualize: bool = False, p_logging=True, **p_kwargs)

Bases: StreamTask, Model

Template class for online adaptive ML tasks.

Parameters:

• p_name (str) – Optional name of the task. Default is None.

• p_range_max (int) – Maximum range of asynchonicity. See class Range. Default is Range.C_RANGE_PROCESS.

• p_ada (bool) – Boolean switch for adaptivitiy. Default = True.

• p_duplicate_data (bool) – If True, instances will be duplicated before processing. Default = False.

• p_visualize (bool) – Boolean switch for visualisation. Default = False.

• p_logging – Log level (see constants of class Log). Default: Log.C_LOG_ALL

• p_kwargs (dict) – Further optional named parameters.

C_TYPE = 'OA-Task'

C_PLOT_ACTIVE: bool = True

C_PLOT_STANDALONE: bool = True

C_PLOT_VALID_VIEWS: list = ['2D', '3D', 'ND']

C_PLOT_DEFAULT_VIEW: str = 'ND'

class mlpro.oa.streams.basics.OAWorkflow(p_name: str | None = None, p_range_max=1, p_class_shared=<class 'mlpro.oa.streams.basics.OAShared'>, p_ada: bool = True, p_visualize: bool = False, p_logging=True, **p_kwargs)

Bases: StreamWorkflow, AWorkflow

Online adaptive workflow based on a stream-workflow and an adaptive workflow.

Parameters:

• p_name (str) – Optional name of the workflow. Default is None.

• p_range_max (int) – Maximum range of asynchonicity. See class Range. Default is Range.C_RANGE_PROCESS.

• p_class_shared – Optional class for a shared object (class OAShared or a child class of OAShared)

• p_ada (bool) – Boolean switch for adaptivitiy. Default = True.

• p_visualize (bool) – Boolean switch for visualisation. Default = False.

• p_logging – Log level (see constants of class Log). Default: Log.C_LOG_ALL

• p_kwargs (dict) – Further optional named parameters.

C_TYPE = 'OA-Workflow'

add_task(p_task: StreamTask, p_pred_tasks: list | None = None)

Adds a task to the workflow.

Parameters:

• p_task (Task) – Task object to be added.

• p_pred_tasks (list) – Optional list of predecessor task objects

class mlpro.oa.streams.basics.OAFunction(p_input_space: ~mlpro.bf.math.basics.MSpace, p_output_space: ~mlpro.bf.math.basics.MSpace, p_output_elem_cls=<class 'mlpro.bf.math.basics.Element'>, p_ada: bool = True, p_buffer_size: int = 0, p_name: str | None = None, p_range_max: int = 2, p_autorun=0, p_class_shared=None, p_visualize: bool = False, p_logging=True, **p_par)

Bases: AdaptiveFunction

…

C_TYPE = 'OA-Function'

class mlpro.oa.streams.basics.OAScenario(p_mode, p_cycle_limit=0, p_visualize: bool = False, p_logging=True)

Bases: StreamScenario

…

C_TYPE = 'OA-Scenario'

class mlpro.oa.streams.basics.OATrainingResults(p_scenario: Scenario, p_run, p_cycle_id, p_logging='W')

Bases: TrainingResults

…

class mlpro.oa.streams.basics.OATraining(**p_kwargs)

Bases: Training

…

C_NAME = 'OA'