Windows

Ver. 1.1.5 (2023-02-02)

This module provides pool of window objects further used in the context of online adaptivity.

class mlpro.bf.streams.tasks.windows.Window(p_buffer_size: int, p_delay: bool = False, p_enable_statistics: bool = False, p_name: str = None, p_range_max=1, p_duplicate_data: bool = False, p_visualize: bool = False, p_logging=True, **p_kwargs)

Bases: StreamTask

This is the base class for window implementations

Parameters:

  • p_buffer_size (int) – the size/length of the buffer/window.

  • p_delay (bool, optional) – Set to true if full buffer is desired before passing the window data to next step. Default is false.

  • p_name (str, optional) – Name of the Window. Default is None.

  • -Optional (p_logging) – Maximum range of task parallelism for window task. Default is set to multithread.

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

  • p_ada (bool, optional) – Adaptivity property of object. Default is True.

  • -Optional – Log level for the object. Default is log everything.

C_NAME = 'Window'
C_PLOT_STANDALONE: bool = False
C_PLOT_IN_WINDOW = 'In Window'
C_PLOT_OUTSIDE_WINDOW = 'Out Window'
C_EVENT_BUFFER_FULL = 'BUFFER_FULL'
C_EVENT_DATA_REMOVED = 'DATA_REMOVED'
_run(p_inst_new: list, p_inst_del: list)

Method to run the window including adding and deleting of elements

Parameters:

  • p_inst_new (list) – Instance/s to be added to the window

  • p_inst_del (list) – Instance/s to be deleted from the window

get_buffered_data()

Method to fetch the date from the window buffer

Returns:

  • buffer (dict) – the buffered data in the form of dictionary

  • buffer_pos (int) – the latest buffer position

get_boundaries()

Method to get the current boundaries of the Window

Returns:

boundaries – Returns the current window boundaries in the form of a Numpy array.

Return type:

np.ndarray

get_mean()

Method to get the mean of the data in the Window.

Returns:

mean – Returns the mean of the current data in the window in the form of a Numpy array.

Return type:

np.ndarray

get_variance()

Method to get the variance of the data in the Window.

Returns:

variance – Returns the variance of the current data in the window as a numpy array.

Return type:

np.ndarray

get_std_deviation()

Method to get the standard deviation of the data in the window.

Returns:

std – Returns the standard deviation of the data in the window as a numpy array.

Return type:

np.ndarray

_init_plot_2d(p_figure: Figure, p_settings: PlotSettings)

Custom method to initialize a 2D plot for the window object

Parameters:

  • p_figure (Figure) – The figure object that hosts the plot

  • p_settings (list of PlotSettings objects.) – Additional settings for the plot

_init_plot_3d(p_figure: Figure, p_settings: PlotSettings)

Custom method to initialize a 3D plot for window object

Parameters:

  • p_figure (matplotlib.figure.Figure) – The figure object to host the plot.

  • p_settings (PlotSettings) – Additional Settings for the plot

_init_plot_nd(p_figure: Figure, p_settings: PlotSettings)

Custom method to initialize plot for Window tasks for N-dimensional plotting.

Parameters:

  • p_figure (Figure) – Figure to host the plot

  • p_settings (PlotSettings) – PlotSettings objects with specific settings for the plot

_update_plot_2d(p_settings: PlotSettings, p_inst_new: list, p_inst_del: list, **p_kwargs)

Default 3-dimensional plotting implementation for window tasks. See class mlpro.bf.plot.Plottable for more details.

Parameters:

  • p_settings (PlotSettings) – Object with further plot settings.

  • p_inst_new (list) – List of new stream instances to be plotted.

  • p_inst_del (list) – List of obsolete stream instances to be removed.

  • p_kwargs (dict) – Further optional plot parameters.

_update_plot_3d(p_settings: PlotSettings, p_inst_new: list, p_inst_del: list, **p_kwargs)

Default 3-dimensional plotting implementation for window tasks. See class mlpro.bf.plot.Plottable for more details.

Parameters:

  • p_settings (PlotSettings) – Object with further plot settings.

  • p_inst_new (list) – List of new stream instances to be plotted.

  • p_inst_del (list) – List of obsolete stream instances to be removed.

  • p_kwargs (dict) – Further optional plot parameters.

_update_plot_nd(p_settings: PlotSettings, p_inst_new: list, p_inst_del: list, **p_kwargs)

Default N-dimensional plotting implementation for window tasks. See class mlpro.bf.plot.Plottable for more details.

Parameters:

  • p_settings (PlotSettings) – Object with further plot settings.

  • p_inst_new (list) – List of new stream instances to be plotted.

  • p_inst_del (list) – List of obsolete stream instances to be removed.

  • p_kwargs (dict) – Further optional plot parameters.