def AccOrLossPlot(self, fig_num: int, title: str, metric: str, axis_labels: list=['train', 'validation'], history_labels: list=['Metric', 'Epoch'], extender: str='_epoch_plot', train_val_lists: list=None):
    '\n        This method wrapp the plot creation for a single metric of the keras train history.\n            :param fig_num:int: figure number\n            :param title:str: figure title\n            :param metric:str: desired metric\n            :param axis_labels:list: axis labels \n            :param history_labels:list: history labels\n            :param extender:str: plot file name extender\n            :param train_val_lists:list: a list containing the train and validation list of a defined metric\n        '
    try:
        figure = plt.figure(fig_num)
        plt.suptitle(title, fontsize=14, fontweight='bold')
        if (metric == 'loss'):
            plt.title(self.CalcResultLoss(history=self._history))
        else:
            plt.title(self.CalcResultAccuracy(history=self._history, metric=metric))
        if (not self._new_style):
            plt.plot(self._history.history[metric], color='blue', label=axis_labels[0])
            plt.plot(self._history.history[('val_' + metric)], color='orange', label=axis_labels[1])
        elif ((train_val_lists != None) and (len(train_val_lists) == 2)):
            for l in train_val_lists[0]:
                plt.plot(self._epochs, self._history.history[l], color='b', label=(((('Training ' + metric) + ' (') + str(format(self._history.history[l][(- 1)], '.5f'))) + ')'))
            for l in train_val_lists[1]:
                plt.plot(self._epochs, self._history.history[l], color='g', label=(((('Validation ' + metric) + ' (') + str(format(self._history.history[l][(- 1)], '.5f'))) + ')'))
        plt.ylabel(history_labels[0])
        plt.xlabel(history_labels[1])
        plt.legend(axis_labels, loc='lower right')
        if self._save_it:
            PlotSaver(self._model_description, figure).SavePyPlotToFile(extender=extender)
        else:
            plt.show()
        figure.clf()
    except Exception as ex:
        template = 'An exception of type {0} occurred in [HistoryPlotter.AccOrLossPlot]. Arguments:\n{1!r}'
        message = template.format(type(ex).__name__, ex.args)
        print(message)
This method wrapp the plot creation for a single metric of the keras train history.
    :param fig_num:int: figure number
    :param title:str: figure title
    :param metric:str: desired metric
    :param axis_labels:list: axis labels 
    :param history_labels:list: history labels
    :param extender:str: plot file name extender
    :param train_val_lists:list: a list containing the train and validation list of a defined metric
def AccOrLossPlot(self, fig_num: int, title: str, metric: str, axis_labels: list=['train', 'validation'], history_labels: list=['Metric', 'Epoch'], extender: str='_epoch_plot', train_val_lists: list=None):
    '\n        This method wrapp the plot creation for a single metric of the keras train history.\n            :param fig_num:int: figure number\n            :param title:str: figure title\n            :param metric:str: desired metric\n            :param axis_labels:list: axis labels \n            :param history_labels:list: history labels\n            :param extender:str: plot file name extender\n            :param train_val_lists:list: a list containing the train and validation list of a defined metric\n        '
    try:
        figure = plt.figure(fig_num)
        plt.suptitle(title, fontsize=14, fontweight='bold')
        if (metric == 'loss'):
            plt.title(self.CalcResultLoss(history=self._history))
        else:
            plt.title(self.CalcResultAccuracy(history=self._history, metric=metric))
        if (not self._new_style):
            plt.plot(self._history.history[metric], color='blue', label=axis_labels[0])
            plt.plot(self._history.history[('val_' + metric)], color='orange', label=axis_labels[1])
        elif ((train_val_lists != None) and (len(train_val_lists) == 2)):
            for l in train_val_lists[0]:
                plt.plot(self._epochs, self._history.history[l], color='b', label=(((('Training ' + metric) + ' (') + str(format(self._history.history[l][(- 1)], '.5f'))) + ')'))
            for l in train_val_lists[1]:
                plt.plot(self._epochs, self._history.history[l], color='g', label=(((('Validation ' + metric) + ' (') + str(format(self._history.history[l][(- 1)], '.5f'))) + ')'))
        plt.ylabel(history_labels[0])
        plt.xlabel(history_labels[1])
        plt.legend(axis_labels, loc='lower right')
        if self._save_it:
            PlotSaver(self._model_description, figure).SavePyPlotToFile(extender=extender)
        else:
            plt.show()
        figure.clf()
    except Exception as ex:
        template = 'An exception of type {0} occurred in [HistoryPlotter.AccOrLossPlot]. Arguments:\n{1!r}'
        message = template.format(type(ex).__name__, ex.args)
        print(message)