How to use the chaco.api.OverlayPlotContainer function in chaco

def _create_plot_component():

    container = OverlayPlotContainer(padding = 50, fill_padding = True,
                                     bgcolor = "lightgray", use_backbuffer=True)

    # Create the initial X-series of data
    numpoints = 30
    low = -5
    high = 15.0
    x = linspace(low, high, numpoints)
    y = jn(0, x)

    lineplot = create_line_plot((x,y), color=tuple(COLOR_PALETTE[0]), width=2.0)
    lineplot.selected_color = "none"
    scatter = ScatterPlot(index = lineplot.index,
                       value = lineplot.value,
                       index_mapper = lineplot.index_mapper,
                       value_mapper = lineplot.value_mapper,
                       color = tuple(COLOR_PALETTE[0]),

rect1.overlays.append(Overlay("One", component=rect1))
        rect2.overlays.append(Overlay("Two", component=rect2))
        container1 = OverlayPlotContainer(bounds=[400, 400], resizable="")
        container1.add(rect1, rect2)
        container1.bgcolor = (0.60, 0.98, 0.60, 0.5) #"palegreen"

        rect3 = Region("purple", position=[50, 50])
        rect4 = Region("teal", position=[200, 50])
        rect3.overlays.append(Overlay("Three", component=rect3))
        rect4.overlays.append(Overlay("Four", component=rect4))
        container2 = OverlayPlotContainer(bounds=[400, 400], resizable="")
        container2.add(rect3, rect4)
        container2.bgcolor = "navajowhite"
        container2.position = [200, 200]

        top_container = OverlayPlotContainer()
        top_container.add(container1, container2)

        return Window(self, -1, component=top_container)

OverlayPlotContainer.draw(self, gc, *args, **kw)

class GraphicGeneratorController(Controller):

    def traits_view(self):
        v = View(
                 UItem('container', editor=ComponentEditor(),
                       style='custom'),
                 width=500,
                 height=500,
                 resizable=True,
                 )
        return v

class GraphicModel(HasTraits):
    container = Instance(OverlayPlotContainer)
    def load(self):
        data = ArrayPlotData()
        p = Plot(data=data, padding=100)
        X = linspace(0, 2 * pi)
        data.set_data('x0', X)
        data.set_data('y0', cos(X))

        p.plot(('x0', 'y0'))
        self.container.add(p)

    def _container_default(self):
        c = RotatingContainer(bgcolor='white')
        return c


if __name__ == '__main__':

def __init__(self, *args, **kws):
        super(OverlayPlotContainer, self).__init__(*args, **kws)
        self._setup_plots()

def main():
    plot = create_plot()
    plot.bounds = [400,300]
    plot.outer_position = [30,30]
    plot.resizable = ""
    cmap_renderer = plot.plots["my_plot"][0]

    # Create the colorbar, handing in the appropriate range and colormap
    colorbar = create_colorbar(plot.color_mapper)
    colorbar.outer_position = [450,30]
    colorbar.plot = cmap_renderer
    colorbar.padding_top = plot.padding_top
    colorbar.padding_bottom = plot.padding_bottom

    container = OverlayPlotContainer(bgcolor = "transparent",
                    fit_window = True)
    container.add(plot)
    container.add(colorbar)

    start_vtk(container)

def _plot_default(self):
        container = OverlayPlotContainer(bgcolor = "white")
        plots = self._make_curves()
        for plot in plots:
            plot.padding = 60
            container.add(plot)

        bottom_axis = PlotAxis(plot, orientation='bottom')

        label_list=['var a', 'var b', 'var c', 'var d', 'var e', 'var f',
                    'var g', 'var h', 'var i']
        vertical_axis = LabelAxis(plot, orientation='left',
                                title='Categories',
                                positions = list(range(1, 10)),
                                labels=label_list)
        vertical2_axis = LabelAxis(plot, orientation='right',
                                   positions = list(range(1, 10)),
                                   labels=label_list)

selection_color = "lawngreen")
            )
        scatter.index.on_trait_change(self._metadata_handler,
                                     "metadata_changed")
        
        scatter.tools.append(PanTool(scatter, drag_button='right'))
        scatter.tools.append(ZoomTool(scatter))

        plot.index_axis.title = "Longitude"
        plot.index_axis.tick_label_formatter = self._convert_lon
        plot.value_axis.title = "Latitude"
        plot.value_axis.tick_label_formatter = self._convert_lat

        plot.padding_right = plot.padding_top = 2

        container = OverlayPlotContainer(
            use_backbuffer=True,
            bgcolor = "sys_window"
            )
        container.add(plot)
        container.bgcolor = "sys_window"

        return container

quiverplot = QuiverPlot(index = xs, value = ys,
                        vectors = vector_ds,
                        index_mapper = LinearMapper(range=xrange),
                        value_mapper = LinearMapper(range=yrange),
                        bgcolor = "white")

        add_default_axes(quiverplot)
        add_default_grids(quiverplot)

        # Attach some tools to the plot
        quiverplot.tools.append(PanTool(quiverplot, constrain_key="shift"))
        zoom = ZoomTool(quiverplot)
        quiverplot.overlays.append(zoom)

        container = OverlayPlotContainer(quiverplot, padding=50)

        return container