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

plot.x_grid.visible = False
    plot.y_grid.visible = False
    plot.x_axis.font = "modern 16"
    plot.y_axis.font = "modern 16"

    # Right now, some of the tools are a little invasive, and we need the
    # actual ColomappedSegmentPlot 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)

    # Create the colorbar, handing in the appropriate range and colormap
    colorbar = ColorBar(index_mapper=LinearMapper(range=plot.color_mapper.range),
                        color_mapper=plot.color_mapper,
                        orientation='v',
                        resizable='v',
                        width=30,
                        padding=20)
    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

def draw_colorbar(self):
        scatplot=self.scatplot
        cmap_renderer = scatplot.plots["my_plot"][0]
        selection = ColormappedSelectionOverlay(cmap_renderer, fade_alpha=0.35, 
                                                selection_type="range")
        cmap_renderer.overlays.append(selection)
        if self.thresh is not None:
            cmap_renderer.color_data.metadata['selections']=self.thresh
            cmap_renderer.color_data.metadata_changed={'selections':self.thresh}
        # Create the colorbar, handing in the appropriate range and colormap
        colormap=scatplot.color_mapper
        colorbar = ColorBar(index_mapper=LinearMapper(range=DataRange1D(low = 0.0,
                                       high = 1.0)),
                        orientation='v',
                        resizable='v',
                        width=30,
                        padding=20)
        colorbar_selection=RangeSelection(component=colorbar)
        colorbar.tools.append(colorbar_selection)
        ovr=colorbar.overlays.append(RangeSelectionOverlay(component=colorbar,
                                                   border_color="white",
                                                   alpha=0.8,
                                                   fill_color="lightgray",
                                                   metadata_name='selections'))
        #ipshell('colorbar, colorbar_selection and ovr available:')
        self.cbar_selection=colorbar_selection
        self.cmap_renderer=cmap_renderer
        colorbar.plot = cmap_renderer

# Right now, some of the tools are a little invasive, and we need the 
        # actual CMapImage object to give to them
        self.my_plot = self.tplot.plots["my_plot"][0]
    
        # Attach some tools to the plot
        self.tplot.tools.append(PanTool(self.tplot))
        zoom = ZoomTool(component=self.tplot, tool_mode="box", always_on=False)
        self.tplot.overlays.append(zoom)
        
        # my custom tool to get the connection information
        self.custtool = CustomTool(self.tplot)
        self.tplot.tools.append(self.custtool)
    
        # Create the colorbar, handing in the appropriate range and colormap
        colormap = self.my_plot.color_mapper
        self.colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
                            color_mapper=colormap,
                            plot=self.my_plot,
                            orientation='v',
                            resizable='v',
                            width=30,
                            padding=20)
            
        self.colorbar.padding_top = self.tplot.padding_top
        self.colorbar.padding_bottom = self.tplot.padding_bottom
        
        # TODO: the range selection gives a Segmentation Fault,
        # but why, the matrix_viewer.py example works just fine!
        # create a range selection for the colorbar
        self.range_selection = RangeSelection(component=self.colorbar)
        self.colorbar.tools.append(self.range_selection)
        self.colorbar.overlays.append(RangeSelectionOverlay(component=self.colorbar,

def create_colorbar(colormap):
    colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
                        color_mapper=colormap,
                        orientation='v',
                        resizable='v',
                        width=30,
                        padding=20)
    colorbar.grid_visible = False
    colorbar._axis.tick_visible = False
    colorbar.tools.append(RangeSelection(component=colorbar))
    colorbar.overlays.append(RangeSelectionOverlay(component=colorbar,
                                                   border_color="white",
                                                   alpha=0.8,
                                                   fill_color="lightgray"))
    return colorbar

index_mapper = index_mapper,
            value_mapper = LinearMapper(range=value_range, stretch_data=False),
            fill_color = (0.81960784,  0.89803922,  0.94117647),
            edge_color = 'transparent',
            )
    filled.tools.append(PanTool(filled, constrain=True, constrain_direction="x"))
    axis = PlotAxis(mapper = filled.value_mapper, component=filled, orientation="left",
                   tick_label_position="outside")
    filled.overlays.append(axis)

    grid = PlotGrid(mapper = filled.value_mapper, component=filled, orientation='horizontal',
                    line_color='lightgray', line_style="dot",)
    filled.underlays.append(grid)

    colormap = horizon.color_mapper
    colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
                        color_mapper=colormap,
                        orientation='v',
                        resizable='v',
                        width=20,
                        padding=20)
    
    padding = (40, 20, 0, 0)
    over1 = HPlotContainer(use_backbuffer=True, padding=padding, padding_top=20)
    over1.add(filled)
    over1.add(colorbar)

    over2 = OverlayPlotContainer(padding = padding, padding_bottom=40)
    over2.add(horizon)

    return over1, over2

if name in ['function', 'npts_x', 'npts_y',
                    'min_x', 'max_x', 'min_y', 'max_y']:
            self.compute_model()


class PlotUI(HasTraits):
    
    # container for all plots
    container = Instance(HPlotContainer)
    
    # Plot components within this container:
    polyplot = Instance(ContourPolyPlot)
    lineplot = Instance(ContourLinePlot)
    cross_plot = Instance(Plot)
    cross_plot2 = Instance(Plot)
    colorbar = Instance(ColorBar)
    
    # plot data
    pd = Instance(ArrayPlotData)

    # view options
    num_levels = Int(15)
    colormap = Enum(colormaps)
    
    #Traits view definitions:
    traits_view = View(
        Group(UItem('container', editor=ComponentEditor(size=(800,600)))),
        resizable=True)

    plot_edit_view = View(
        Group(Item('num_levels'),
              Item('colormap')),

# Right now, some of the tools are a little invasive, and we need the 
        # actual CMapImage object to give to them
        self.my_plot = self.tplot.plots["my_plot"][0]
    
        # Attach some tools to the plot
        self.tplot.tools.append(PanTool(self.tplot))
        zoom = ZoomTool(component=self.tplot, tool_mode="box", always_on=False)
        self.tplot.overlays.append(zoom)
        
        # my custom tool to get the connection information
        self.custtool = CustomTool(self.tplot)
        self.tplot.tools.append(self.custtool)
    
        # Create the colorbar, handing in the appropriate range and colormap
        colormap = self.my_plot.color_mapper
        self.colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
                            color_mapper=colormap,
                            plot=self.my_plot,
                            orientation='v',
                            resizable='v',
                            width=30,
                            padding=20)
            
        self.colorbar.padding_top = self.tplot.padding_top
        self.colorbar.padding_bottom = self.tplot.padding_bottom
        
        # create a range selection for the colorbar
        self.range_selection = RangeSelection(component=self.colorbar)
        self.colorbar.tools.append(self.range_selection)
        self.colorbar.overlays.append(RangeSelectionOverlay(component=self.colorbar,
                                                       border_color="white",
                                                       alpha=0.8,

lplot.padding = 20
    lplot.bg_color = "white"
    lplot.fill_padding = True

    # Add some tools to the plot
    zoom = ZoomTool(lplot, tool_mode="box", always_on=False)
    lplot.overlays.append(zoom)
    lplot.tools.append(PanTool(lplot, constrain_key="shift"))

    # Right now, some of the tools are a little invasive, and we need the
    # actual CMapImage object to give to them
    cm_plot = lplot.plots["cm_plot"][0]

    # Create the colorbar, handing in the appropriate range and colormap
    colormap = cm_plot.color_mapper
    colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
                        color_mapper=colormap,
                        plot=cm_plot,
                        orientation='v',
                        resizable='v',
                        width=30,
                        padding=20)
    colorbar.padding_top = lplot.padding_top
    colorbar.padding_bottom = lplot.padding_bottom

    # Create the left plot, contours of varying color and width
    rplot = Plot(pd, range2d=lplot.range2d)
    rplot.contour_plot("imagedata",
                       type="line",
                       xbounds=x_extents,
                       ybounds=y_extents,
                       bgcolor="black",