How to use the visualqc.utils.get_axis function in VisualQC

def show_image(self, img, annot=None):
        """Display the requested slices of an image on the existing axes."""

        for ax_index, (dim_index, slice_index) in enumerate(self.slices):
            self.h_images[ax_index].set(data=get_axis(img, dim_index, slice_index),
                                        cmap=self.current_cmap)

        if annot is not None:
            self._identify_foreground(annot)
        else:
            self.fg_annot_h.set_visible(False)

ax = ax.flatten()
    # display surfaces
    for sf_counter, ((hemi, view), spath) in enumerate(surf_vis.items()):
        plt.sca(ax[sf_counter])
        img = mpimg.imread(spath)
        # img = crop_image(img)
        plt.imshow(img)
        ax[sf_counter].text(0, 0, '{} {}'.format(hemi, view))
        plt.axis('off')

    # display slices
    for ax_counter, (dim_index, slice_num) in enumerate(slices):
        plt.sca(ax[ax_counter + num_surf_vis])

        slice_mri = get_axis(mri, dim_index, slice_num)
        slice_seg = get_axis(seg, dim_index, slice_num)

        # display MRI
        mri_rgb = mri_mapper.to_rgba(slice_mri)
        h_mri = plt.imshow(mri_rgb, **display_params_mri)

        if 'volumetric' in qcw.vis_type:
            seg_rgb = seg_mapper.to_rgba(slice_seg)
            h_seg = plt.imshow(seg_rgb, **display_params_seg)
        elif 'contour' in qcw.vis_type:
            h_seg = plot_contours_in_slice(slice_seg, unique_labels, color4label)

        plt.axis('off')

        # # encoding the souce of the object (image/line) being displayed
        # handle_seg.set_label('seg {} {}'.format(dim_index, slice_num))

def show_image(self, img, annot=None):
        """Display the requested slices of an image on the existing axes."""

        for ax_index, (dim_index, slice_index) in enumerate(self.slices):
            self.h_images[ax_index].set(data=get_axis(img, dim_index, slice_index),
                                        cmap=self.current_cmap)

        if annot is not None:
            self._identify_foreground(annot)
        else:
            self.fg_annot_h.set_visible(False)

def overlay_dwi_edges(self):

        # not cropping to help checking align in full FOV
        overlaid = scale_0to1(self.b0_volume)
        base_img = scale_0to1(self.dw_volumes[..., self.current_grad_index].squeeze())
        slices = pick_slices(base_img, self.views, self.num_slices_per_view)
        for ax_index, (dim_index, slice_index) in enumerate(slices):
            mixed = dwi_overlay_edges(get_axis(base_img, dim_index, slice_index),
                                      get_axis(overlaid, dim_index, slice_index))
            self.images_fg[ax_index].set(data=mixed)
            self.images_fg_label[ax_index].set_text(str(slice_index))

        # the following needs to be done outside show_image3d, as we need custom mixing
        self._set_backgrounds_visibility(False)
        self._set_foregrounds_visibility(True)
        self._identify_foreground('Alignment check to b=0, '
                                  'grad index {}'.format(self.current_grad_index))

def mix_and_display(self):
        """Static mix and display."""

        # TODO maintain a dict mixed[vis_type] to do computation only once
        for ax_index, (dim_index, slice_index) in enumerate(self.slices):
            slice_one = get_axis(self.image_one, dim_index, slice_index)
            slice_two = get_axis(self.image_two, dim_index, slice_index)
            mixed_slice = self.mixer(slice_one, slice_two)
            # mixed_slice is already in RGB mode m x p x 3, so
            #   prev. cmap (gray) has no effect on color_mixed data
            self.h_images[ax_index].set(data=mixed_slice, cmap=self.current_cmap)

ax = ax.flatten()
    # display surfaces
    for sf_counter, ((hemi, view), spath) in enumerate(surf_vis.items()):
        plt.sca(ax[sf_counter])
        img = mpimg.imread(spath)
        # img = crop_image(img)
        plt.imshow(img)
        ax[sf_counter].text(0, 0, '{} {}'.format(hemi, view))
        plt.axis('off')

    # display slices
    for ax_counter, (dim_index, slice_num) in enumerate(slices):
        plt.sca(ax[ax_counter + num_surf_vis])

        slice_mri = get_axis(mri, dim_index, slice_num)
        slice_seg = get_axis(seg, dim_index, slice_num)

        # display MRI
        mri_rgb = mri_mapper.to_rgba(slice_mri)
        h_mri = plt.imshow(mri_rgb, **display_params_mri)

        if 'volumetric' in qcw.vis_type:
            seg_rgb = seg_mapper.to_rgba(slice_seg)
            h_seg = plt.imshow(seg_rgb, **display_params_seg)
        elif 'contour' in qcw.vis_type:
            h_seg = plot_contours_in_slice(slice_seg, unique_labels, color4label)

        plt.axis('off')

        # # encoding the souce of the object (image/line) being displayed
        # handle_seg.set_label('seg {} {}'.format(dim_index, slice_num))
        # handle_mri.set_label('mri {} {}'.format(dim_index, slice_num))

def attach_image_to_foreground_axes(self, image3d, cmap='gray'):
        """Attaches a given image to the foreground axes and bring it forth"""

        image3d = crop_image(image3d, self.padding)
        image3d = scale_0to1(image3d)
        slices = pick_slices(image3d, self.views, self.num_slices_per_view)
        for ax_index, (dim_index, slice_index) in enumerate(slices):
            slice_data = get_axis(image3d, dim_index, slice_index)
            self.images_fg[ax_index].set(data=slice_data, cmap=cmap)
        for ax in self.fg_axes:
            ax.set(visible=True, zorder=self.layer_order_zoomedin)