How to use the mayavi.mlab.close function in mayavi

def tearDown(self):
        mlab.close(all=True)

def plot_one_scene(lyftdata, scene_token):
    scene = lyftdata.get('scene', scene_token)
    token = scene['first_sample_token']
    while token != '':
        sample = lyftdata.get('sample', token)
        plot_lidar_with_depth(lyftdata, sample)
        token = sample['next']
        input_str=input('Press any key to continue to next sample, enter "kill" to terminate \n')
        mlab.close()
        for proc in psutil.process_iter():
            if proc.name() == "display":
                proc.kill()

        if input_str == "kill":
            break

figure_list.append(current_fig)

    if gallery_conf.get('find_mayavi_figures', False):
        from mayavi import mlab
        e = mlab.get_engine()
        last_matplotlib_fig_num = fig_count + len(figure_list)
        total_fig_num = last_matplotlib_fig_num + len(e.scenes)
        mayavi_fig_nums = range(last_matplotlib_fig_num + 1, total_fig_num + 1)

        for scene, mayavi_fig_num in zip(e.scenes, mayavi_fig_nums):
            current_fig = image_path.format(mayavi_fig_num)
            mlab.savefig(current_fig, figure=scene)
            # make sure the image is not too large
            scale_image(current_fig, current_fig, 850, 999)
            figure_list.append(current_fig)
        mlab.close(all=True)

    # Depending on whether we have one or more figures, we're using a
    # horizontal list or a single rst call to 'image'.
    images_rst = ""
    if len(figure_list) == 1:
        figure_name = figure_list[0]
        images_rst = SINGLE_IMAGE % figure_name.lstrip('/')
    elif len(figure_list) > 1:
        images_rst = HLIST_HEADER
        for figure_name in figure_list:
            images_rst += HLIST_IMAGE_TEMPLATE % figure_name.lstrip('/')

    return figure_list, images_rst

figure_list.append(current_fig)

    if gallery_conf.get('find_mayavi_figures', False):
        from mayavi import mlab
        e = mlab.get_engine()
        last_matplotlib_fig_num = fig_count + len(figure_list)
        total_fig_num = last_matplotlib_fig_num + len(e.scenes)
        mayavi_fig_nums = range(last_matplotlib_fig_num + 1, total_fig_num + 1)

        for scene, mayavi_fig_num in zip(e.scenes, mayavi_fig_nums):
            current_fig = image_path.format(mayavi_fig_num)
            mlab.savefig(current_fig, figure=scene)
            # make sure the image is not too large
            scale_image(current_fig, current_fig, 850, 999)
            figure_list.append(current_fig)
        mlab.close(all=True)

    # Depending on whether we have one or more figures, we're using a
    # horizontal list or a single rst call to 'image'.
    images_rst = ""
    if len(figure_list) == 1:
        figure_name = figure_list[0]
        images_rst = SINGLE_IMAGE % figure_name.lstrip('/')
    elif len(figure_list) > 1:
        images_rst = HLIST_HEADER
        for figure_name in figure_list:
            images_rst += HLIST_IMAGE_TEMPLATE % figure_name.lstrip('/')

    return figure_list, images_rst

figure_list.append(current_fig)

    if gallery_conf.get('find_mayavi_figures', False):
        from mayavi import mlab
        e = mlab.get_engine()
        last_matplotlib_fig_num = fig_count + len(figure_list)
        total_fig_num = last_matplotlib_fig_num + len(e.scenes)
        mayavi_fig_nums = range(last_matplotlib_fig_num + 1, total_fig_num + 1)

        for scene, mayavi_fig_num in zip(e.scenes, mayavi_fig_nums):
            current_fig = image_path.format(mayavi_fig_num)
            mlab.savefig(current_fig, figure=scene)
            # make sure the image is not too large
            scale_image(current_fig, current_fig, 850, 999)
            figure_list.append(current_fig)
        mlab.close(all=True)

    return figure_rst(figure_list, gallery_conf['src_dir'])

figure_list.append(current_fig)

    if gallery_conf.get('find_mayavi_figures', False):
        from mayavi import mlab
        e = mlab.get_engine()
        last_matplotlib_fig_num = fig_count + len(figure_list)
        total_fig_num = last_matplotlib_fig_num + len(e.scenes)
        mayavi_fig_nums = range(last_matplotlib_fig_num + 1, total_fig_num + 1)

        for scene, mayavi_fig_num in zip(e.scenes, mayavi_fig_nums):
            current_fig = image_path.format(mayavi_fig_num)
            mlab.savefig(current_fig, figure=scene)
            # make sure the image is not too large
            scale_image(current_fig, current_fig, 850, 999)
            figure_list.append(current_fig)
        mlab.close(all=True)

    return figure_rst(figure_list, gallery_conf['src_dir'])

time_elapsed = float(open(time_path).read())

        if (not os.path.exists(first_image_file) or
                os.stat(first_image_file).st_mtime
                <= os.stat(src_file).st_mtime):
            # We need to execute the code
            print 'plotting %s' % fname
            t0 = time()
            import matplotlib.pyplot as plt
            plt.close('all')

            try:
                from mayavi import mlab
            except Exception, e:
                from enthought.mayavi import mlab
            mlab.close(all=True)

            cwd = os.getcwd()
            try:
                # First CD in the original example dir, so that any file
                # created by the example get created in this directory
                orig_stdout = sys.stdout
                os.chdir(os.path.dirname(src_file))
                my_buffer = StringIO()
                my_stdout = Tee(sys.stdout, my_buffer)
                sys.stdout = my_stdout
                my_globals = {'pl': plt}
                execfile(os.path.basename(src_file), my_globals)
                time_elapsed = time() - t0
                sys.stdout = orig_stdout
                my_stdout = my_buffer.getvalue()

def close(self):
        """Close all figures and cleanup data structure."""
        for ri, ff in enumerate(self._figures):
            for ci, f in enumerate(ff):
                if f is not None:
                    mlab.close(f)
                    self._figures[ri][ci] = None

        # should we tear down other variables?
        if self._v is not None:
            self._v.dispose()
            self._v = None