pyplt.gui.experiment.preprocessing package

Submodules

pyplt.gui.experiment.preprocessing.preproctab module

class pyplt.gui.experiment.preprocessing.preproctab.PreProcessingFrame(parent, parent_window, files_tab)

Bases: tkinter.Frame

Frame widget that is visible whenever the Data Pre-Processing tab is in the ‘unlocked’ state.

Extends the class tkinter.Frame.

Initializes the frame widget.

Parameters:
auto_extract_enabled()

Indicate whether or not automatic feature selection (via autoencoder) has been chosen.

Returns:specifies whether or not automatic feature selection (via autoencder) was chosen.
Return type:bool
destroy_tab()

Destroy the contents of the tab.

get_autoencoder_menu()

Get the autoencoder GUI menu widget through which the parameter values selected by the user may be read.

Returns:the autoencoder menu widget.
Return type::class:pyplt.gui.experiment.preprocessing.data_compression.AutoencoderSettings
get_include_settings()

Get the current include/exclude settings for each feature in the original objects data.

Returns:a dict containing the feature indices as the dict’s keys and booleans indicating whether the corresponding feature is to be included in (True) or excluded from (False) the experiment as the dict’s values.
Return type:dict of bool
get_norm_settings()

Get the normalization settings for each feature in the original objects data.

Returns:a dict containing the feature indices as the dict’s keys and enumerated constants of type pyplt.util.enums.NormalizationType indicating how the corresponding feature is to be normalized as the dict’s values.
Return type:dict of pyplt.util.enums.NormalizationType
get_shuffle_settings()

Get the settings chosen by the user with respect to shuffling the dataset.

Returns:
  • shuffle – specifies whether or not to shuffle the dataset at the start of the experiment execution.
  • random_seed – optional seed used to shuffle the dataset.
Return type:
  • shuffle – bool
  • random_seed – int or None
init_tab()

Initialize (or re-initialize) the contents of the tab.

class pyplt.gui.experiment.preprocessing.preproctab.PreProcessingTab(parent, parent_window, files_tab)

Bases: pyplt.gui.util.tab_locking.LockableTab

GUI tab for the data pre-processing stage of setting up an experiment.

Extends the class pyplt.gui.util.tab_locking.LockableTab which, in turn, extends the tkinter.Frame class.

Initializes the PreProcessingTab widget.

Parameters:
auto_extract_enabled()

Indicate whether or not automatic feature selection (via autoencoder) has been chosen.

Returns:specifies whether or not automatic feature selection (via autoencder) was chosen.
Return type:bool
get_autoencoder_menu()

Get the autoencoder GUI menu widget through which the parameter values selected by the user may be read.

Returns:the autoencoder menu widget.
Return type::class:pyplt.gui.experiment.preprocessing.data_compression.AutoencoderSettings
get_include_settings()

Get the user settings for each feature indicating whether or not it is to be included in the experiment.

Returns:a dict containing the feature names as the dict’s keys and booleans indicating whether the corresponding feature is to be included in (True) or excluded from (False) the experiment as the dict’s values.
Return type:dict of bool
get_norm_settings()

Get the user settings for each feature indicating how it is to be normalized.

Returns:a dict containing the feature names as the dict’s keys and enumerated constants of type pyplt.util.enums.NormalizationType indicating how the corresponding feature is to be normalized as the dict’s values.
Return type:dict of pyplt.util.enums.NormalizationType
get_normal_frame()

Return a PreProcessingFrame widget for when the tab is in the ‘unlocked’ state.

The PreProcessingFrame widget is instantiated only once on the first occasion that the tab is ‘unlocked’.

Returns:the PreProcessingFrame widget that is visible whenever the tab is in the ‘unlocked’ state.
Return type:pyplt.gui.experiment.preprocessing.preproctab.PreProcessingFrame
get_shuffle_settings()

Get the settings chosen by the user with respect to shuffling the dataset.

Returns:
  • shuffle – specifies whether or not to shuffle the dataset at the start of the experiment execution.
  • random_seed – optional seed used to shuffle the dataset.
Return type:
  • shuffle – bool
  • random_seed – int or None
lock()

Override method in parent class to destroy the tab contents each time it switches to the ‘locked’ state.

This is carried out by calling the destroy_tab() method of the pyplt.gui.experiment.preprocessing.preproctab.PreProcessingFrame class.

refresh()

Destroy and re-initialize the tab contents.

This is done by subsequent calls to the destroy_tab() and init_tab() methods of the pyplt.gui.experiment.preprocessing.preproctab.PreProcessingFrame class.

unlock()

Override method in parent class to re-initialize the tab contents each time it switches to the ‘unlocked’ state.

This is done to ensure the tab contents reflect the most recently loaded data set and is carried out by calling the init_tab() method of the pyplt.gui.experiment.preprocessing.preproctab.PreProcessingFrame class.

Module contents

This package contains GUI-based modules that manage the data pre-processing stage of setting up an experiment.