How to use the visualqc.config.default_review_figsize function in VisualQC

def open_figure(self):
        """Creates the master figure to show everything in."""

        self.figsize = cfg.default_review_figsize
        plt.style.use('dark_background')
        self.fig, self.axes = plt.subplots(self.num_rows, self.num_cols,
                                           figsize=self.figsize)
        self.axes = self.axes.flatten()

        self.fig.canvas.set_window_title('VisualQC Alignment : {} {} {} '
                                         ''.format(self.in_dir, self.image1_name, self.image2_name))

        # vmin/vmax are controlled, because we rescale all to [0, 1]
        self.display_params = dict(interpolation='none', aspect='equal', origin='lower',
                                   cmap=self.current_cmap, vmin=0.0, vmax=1.0)

        # turning off axes, creating image objects
        self.h_images = [None] * len(self.axes)
        empty_image = np.full((10, 10, 3), 0.0)
        for ix, ax in enumerate(self.axes):

def open_figure(self):
        """Creates the master figure to show everything in."""

        # number of stats to be overlaid on top of carpet plot
        self.num_stats = 3
        self.figsize = cfg.default_review_figsize

        # empty/dummy data for placeholding
        empty_image = np.full((200, 200), 0.0)
        empty_vec = np.full((200, 1), 0.0)
        time_points = list(range(200))

        # overlay order -- larger appears on top of smaller
        self.layer_order_carpet = 1
        self.layer_order_stats = 2
        self.layer_order_zoomedin = 3
        self.layer_order_to_hide = -1
        self.total_num_layers = 3

        plt.style.use('dark_background')

        # 1. main carpet, in the background

def open_figure(self):
        """Creates the master figure to show everything in."""

        # number of stats to be overlaid on top of carpet plot
        self.num_stats = 3
        self.figsize = cfg.default_review_figsize

        # empty/dummy data for placeholding
        empty_image = np.full((200, 200), 0.0)
        label_x, label_y = (5, 5) # x, y in image data space
        empty_vec = np.full((200, 1), 0.0)
        gradients = list(range(200))

        # overlay order -- larger appears on top of smaller
        self.layer_order_carpet = 1
        self.layer_order_stats = 2
        self.layer_order_zoomedin = 3
        self.layer_order_to_hide = -1
        self.total_num_layers = 3

        plt.style.use('dark_background')

def open_figure(self):
        """Creates the master figure to show everything in."""

        self.figsize = cfg.default_review_figsize
        plt.style.use('dark_background')
        self.fig, self.axes = plt.subplots(self.num_rows, self.num_cols,
                                           figsize=self.figsize)
        self.axes = self.axes.flatten()

        self.fig.canvas.set_window_title('VisualQC Quantitative MR : {} '
                                         ''.format(self.in_dir))

        # vmin/vmax are controlled, because we rescale all to [0, 1]
        self.display_params = dict(interpolation='none', aspect='equal',
                                   origin='lower', cmap=self.current_cmap,
                                   vmin=0.0, vmax=1.0)

        # turning off axes, creating image objects
        self.h_images = [None] * len(self.axes)
        self.h_slice_numbers = [None] * len(self.axes)

def init_layout(self, views, num_rows_per_view,
                    num_slices_per_view, padding=cfg.default_padding):

        plt.style.use('dark_background')

        # vmin/vmax are controlled, because we rescale all to [0, 1]
        self.display_params = dict(interpolation='none', aspect='equal',
                                   origin='lower', cmap='gray', vmin=0.0, vmax=1.0)
        self.figsize = cfg.default_review_figsize

        self.collage = Collage(view_set=views,
                               num_slices=num_slices_per_view, num_rows=num_rows_per_view,
                               display_params=self.display_params,
                               bounding_rect=cfg.bounding_box_review,
                               figsize=self.figsize)
        self.fig = self.collage.fig
        self.fig.canvas.set_window_title('VisualQC T1 MRI : {} {} '
                                         ''.format(self.in_dir, self.mri_name))

        self.padding = padding

def init_layout(self,
                    view_set=cfg.defacing_view_set,
                    num_rows_per_view=cfg.defacing_num_rows_per_view,
                    num_slices_per_view=cfg.defacing_num_slices_per_view,
                    padding=cfg.default_padding):
        """initializes the layout"""

        plt.style.use('dark_background')

        # vmin/vmax are controlled, because we rescale all to [0, 1]
        self.display_params = dict(interpolation='none', aspect='equal',
                                   origin='lower', cmap='gray',
                                   vmin=0.0, vmax=1.0)
        self.figsize = cfg.default_review_figsize

        self.collage = Collage(view_set=view_set,
                               num_slices=num_slices_per_view,
                               num_rows=num_rows_per_view,
                               display_params=self.display_params,
                               bounding_rect=cfg.bbox_defacing_MRI_review,
                               figsize=self.figsize)
        self.fig = self.collage.fig
        self.fig.canvas.set_window_title('VisualQC defacing : {} {} '
                                         ''.format(self.in_dir,
                                                   self.defaced_name))

        self.padding = padding

def open_figure(self):
        """Creates the master figure to show everything in."""

        self.figsize = cfg.default_review_figsize
        plt.style.use('dark_background')
        self.fig, self.axes = plt.subplots(self.num_rows_total, self.num_cols_final,
                                           figsize=self.figsize)
        self.axes = self.axes.flatten()
        self.fig.canvas.set_window_title('VisualQC {} {} : {}'
                                         ' '.format(self.vis_type, self.seg_name, self.in_dir))

        self.display_params_mri = dict(interpolation='none', aspect='equal',
                                       origin='lower',
                                       alpha=self.alpha_mri)
        self.display_params_seg = dict(interpolation='none', aspect='equal',
                                       origin='lower',
                                       alpha=self.alpha_seg)

        normalize_mri = colors.Normalize(vmin=cfg.min_cmap_range_t1_mri,
                                         vmax=cfg.max_cmap_range_t1_mri, clip=True)