#NEWLINE# def plot_diagonal( self , title = None , xmin = None , xmax = None , ymin = None , ymax = None , ax = None , show = True , color = None , xlabel = True , ylabel = True , legend = True , chance = True , label = 'Classif. score' ) : #NEWLINE# #INDENT# "Plotting function of GeneralizationAcrossTime object\n\n        Plot each classifier score trained and tested at identical time\n        windows.\n\n        Parameters\n        ----------\n        title : str | None\n            Figure title.\n        xmin : float | None, optional\n            Min time value.\n        xmax : float | None, optional\n            Max time value.\n        ymin : float | None, optional\n            Min score value. If None, sets to min(scores).\n        ymax : float | None, optional\n            Max score value. If None, sets to max(scores).\n        ax : object | None\n            Instance of mataplotlib.axes.Axis. If None, generate new figure.\n        show : bool\n            If True, the figure will be shown. Defaults to True.\n        color : str\n            Score line color.\n        xlabel : bool\n            If True, the xlabel is displayed. Defaults to True.\n        ylabel : bool\n            If True, the ylabel is displayed. Defaults to True.\n        legend : bool\n            If True, a legend is displayed. Defaults to True.\n        chance : bool | float. Defaults to None\n            Plot chance level. If True, chance level is estimated from the type\n            of scorer.\n        label : str\n            Score label used in the legend. Defaults to 'Classif. score'.\n\n        Returns\n        -------\n        fig : instance of matplotlib.figure.Figure\n            The figure.\n        " #NEWLINE# return plot_gat_times ( self , train_time = 'diagonal' , title = title , xmin = xmin , xmax = xmax , ymin = ymin , ymax = ymax , ax = ax , show = show , color = color , xlabel = xlabel , ylabel = ylabel , legend = legend , chance = chance , label = label )