def METHOD_NAME():
    # Create some data
    numpts = 1000
    x = sort(random(numpts))
    y = random(numpts)
    color = randint(0, 7, numpts)
    # Create a plot data obect and give it this data
    pd = ArrayPlotData()
    pd.set_data("index", x)
    pd.set_data("value", y)
    pd.set_data("color", color)
    # Create the plot
    plot = Plot(pd)
    plot.plot(
        ("index", "value", "color"),
        type="cmap_scatter",
        name="my_plot",
        color_mapper=accent,
        marker="square",
        fill_alpha=0.5,
        marker_size=6,
        outline_color="black",
        border_visible=True,
        bgcolor="white",
    )
    # Tweak some of the plot properties
    plot.title = "Colormapped Scatter Plot with Range-selectable Data Points"
    plot.padding = 50
    plot.x_grid.visible = False
    plot.y_grid.visible = False
    plot.x_axis.font = "sans-serif 16"
    plot.y_axis.font = "sans-serif 16"
    # Right now, some of the tools are a little invasive, and we need the
    # actual ColomappedScatterPlot object to give to them
    cmap_renderer = plot.plots["my_plot"][0]
    # Attach some tools to the plot
    plot.tools.append(PanTool(plot, constrain_key="shift"))
    zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
    plot.overlays.append(zoom)
    selection = ColormappedSelectionOverlay(
        cmap_renderer, fade_alpha=0.35, selection_type="mask"
    )
    cmap_renderer.overlays.append(selection)
    # Create the colorbar, handing in the appropriate range and colormap
    colorbar = create_colorbar(plot.color_mapper)
    colorbar.plot = cmap_renderer
    colorbar.padding_top = plot.padding_top
    colorbar.padding_bottom = plot.padding_bottom
    # Create a container to position the plot and the colorbar side-by-side
    container = HPlotContainer(use_backbuffer=True)
    container.add(plot)
    container.add(colorbar)
    container.bgcolor = "lightgray"
    return container