pyplt.gui.experiment.preflearning package¶
Submodules¶
pyplt.gui.experiment.preflearning.pltab module¶
-
class
pyplt.gui.experiment.preflearning.pltab.
PLFrame
(parent, parent_window, files_tab, preproc_tab, fs_tab)¶ Bases:
tkinter.Frame
Frame widget that is visible whenever the Preference Learning tab is in the ‘unlocked’ state.
Extends the class tkinter.Frame.
Initializes the frame widget and its contents.
Parameters: - parent (tkinter widget) – the parent widget of this frame widget.
- parent_window (tkinter.Toplevel) – the window which will contain this frame widget.
- files_tab (
pyplt.gui.experiment.dataset.loading.DataLoadingTab
) – the Load Data tab. - preproc_tab (
pyplt.gui.experiment.preprocessing.preproctab.PreProcessingTab
) – the Preprocessing tab. - fs_tab (
pyplt.gui.experiment.featureselection.featselectiontab.FeatureSelectionTab
) – the Feature Selection tab.
-
get_algorithm
()¶ Get the preference learning algorithm type chosen by the user.
Returns: the preference learning algorithm chosen by the user. Return type: pyplt.util.enums.PLAlgo
-
get_algorithm_params
()¶ Get the parameters of the preference learning algorithm chosen by the user (if applicable).
Returns: the parameters of the preference learning algorithm chosen by the user (if applicable). Return type: list
-
get_evaluator
()¶ Get the evaluation method type chosen by the user.
Returns: the evaluation method type chosen by the user. Return type: pyplt.util.enums.EvaluatorType
-
get_evaluator_params
()¶ Get the parameters of the evaluation method chosen by the user (if applicable).
Returns: the parameters of the evaluation method chosen by the user (if applicable). Return type: list
-
run_exp
()¶ Trigger the execution of the experiment in a separate thread from the main (GUI) thread.
A
pyplt.gui.experiment.progresswindow.ProgressWindow
widget is also initialized to keep a progress log and progress bar of the experiment execution process.Threading is carried out using the threading.Thread class.
-
class
pyplt.gui.experiment.preflearning.pltab.
PLTab
(parent, parent_window, files_tab, preproc_tab, fs_tab)¶ Bases:
pyplt.gui.util.tab_locking.LockableTab
GUI tab for the preference learning and evaluation 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 PLTab object.
Parameters: - parent (tkinter widget) – the parent widget of this tab (frame) widget.
- parent_window (tkinter.Toplevel) – the window which will contain this tab (frame) widget.
- files_tab (
pyplt.gui.experiment.dataset.loading.DataLoadingTab
) – the Load Data tab. - preproc_tab (
pyplt.gui.experiment.preprocessing.preproctab.PreProcessingTab
) – the Preprocessing tab. - fs_tab (
pyplt.gui.experiment.featureselection.featselectiontab.FeatureSelectionTab
) – the Feature Selection tab.
-
get_evaluator
()¶ Get the evaluation method type chosen by the user via the PLFrame.
Returns: the evaluation method type chosen by the user. Return type: pyplt.util.enums.EvaluatorType
-
get_evaluator_params
()¶ Get the parameters of the evaluation method chosen by the user (if applicable).
Returns: the parameters of the evaluation method chosen by the user (if applicable). Return type: list
-
get_normal_frame
()¶ Return a PLFrame widget for when the tab is in the ‘unlocked’ state.
The PLFrame widget is instantiated only once on the first occasion that the tab is ‘unlocked’.
Returns: the PLFrame widget that is visible whenever the tab is in the ‘unlocked’ state. Return type: pyplt.gui.experiment.preflearning.pltab.PLFrame
-
get_pl_algorithm
()¶ Get the preference learning algorithm type chosen by the user via the PLFrame.
Returns: the preference learning algorithm type chosen by the user. Return type: pyplt.util.enums.PLAlgo
-
get_pl_algorithm_params
()¶ Get the parameters of the preference learning algorithm chosen by the user (if applicable).
Returns: the parameters of the preference learning algorithm chosen by the user (if applicable). Return type: list
-
run_experiment
()¶ Call the method which triggers the execution of the experiment.
Module contents¶
This package contains GUI-based modules that manage the preference learning stage of setting up an experiment.