How to use the chaco.tools.api.PanTool function in chaco

def _end_pan(self, event):
        if hasattr(event, "bid"):
            event.window.release_blob(event.bid)
        PanTool._end_pan(self, event)

value_mapper=vol_mapper,
                               line_color="transparent",
                               fill_color="blue",
                               bar_width=0.6,
                               antialias=False,
                               height=100,
                               resizable="h",
                               origin="bottom left",
                               bgcolor="white",
                               border_visible=True
                               )

            vol_plot.padding = 30
            vol_plot.padding_left = 40
            vol_plot.tools.append(
                PanTool(vol_plot, constrain=True, constrain_direction="x"))
            add_default_grids(vol_plot)
            add_default_axes(vol_plot)

            #print vol_plot.index_mapper.range.high
            #print vol_plot.value_mapper.range.low, vol_plot.value_mapper.range.high
            self.vol_plot = vol_plot
            self.container.add(vol_plot)

            ####################################################################
            ## Create price plot

            sorted_vals = np.vstack(
                (self.df.open, self.df.high, self.df.low, self.df.close))
            sorted_vals.sort(0)
            __bool = self.df.close.values - self.df.open.values
            self.up_boolean = __bool >= 0

index_range = DataRange1D(self.index_ds, high='track', tracking_amount=24*3600*365)

        color_mapper = cmap(range=value_range)
    
        # Remove old plots
        container.remove(*container.components)
        for val, row in zip(self.value_ds, self.rows):
            horizon = HorizonPlot(
                index = self.index_ds,
                value = val,
                index_mapper = LinearMapper(range=index_range, stretch_data=False),
                value_mapper = BandedMapper(range=DataRange1D(val)),
                color_mapper = cmap(range=DataRange1D(val)), #color_mapper,
                negative_bands = False,
                )   
            horizon.tools.append(PanTool(horizon, constrain=True, constrain_direction="x"))
            horizon.overlays.append(PlotLabel(component=horizon, hjustify='right', text=row, overlay_position='outside left'))
            container.add(horizon)
        bottom_axis = PlotAxis(horizon, orientation="bottom",
                    tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem()))
        container.overlays = [bottom_axis]

        container.request_redraw()

def main():
    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    pd = ArrayPlotData(index = x)
    for i in range(5):
        pd.set_data("y" + str(i), jn(i,x))

    # Create some line plots of some of the data
    plot = Plot(pd, bgcolor="none", padding=30, border_visible=True,
                 overlay_border=True, use_backbuffer=False)
    plot.legend.visible = True
    plot.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="auto")
    plot.plot(("index", "y3"), name="j_3", color="auto")
    plot.tools.append(PanTool(plot))
    zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
    plot.overlays.append(zoom)

    # Create the mlab test mesh and get references to various parts of the
    # VTK pipeline
    f = mlab.figure(size=(600,500))
    m = mlab.test_mesh()
    scene = mlab.gcf().scene
    render_window = scene.render_window
    renderer = scene.renderer
    rwi = scene.interactor

    plot.resizable = ""
    plot.bounds = [200,200]
    plot.padding = 25
    plot.outer_position = [30,30]

#now make another cursor
        csr2 = CursorTool(cmapImgPlot,
                           drag_button='left',
                           color='white',
                           line_width=2.0
                           )
        self.cursor2 = csr2

        csr2.current_position = 1.0, 1.5

        cmapImgPlot.overlays.append(csr2)

        #add some standard tools. Note, I'm assigning the PanTool to the
        #right mouse-button to avoid conflicting with the cursors
        cmapImgPlot.tools.append(PanTool(cmapImgPlot, drag_button="right"))
        cmapImgPlot.overlays.append(ZoomTool(cmapImgPlot))

def __init__(self, x, y, color="blue", bgcolor="white"):
        self.y_values = y[:]
        if type(x) == ArrayDataSource:
            self.x_values = x.get_data()[:]
            plot = create_line_plot((x, self.y_values), color=color,
                                    bgcolor=bgcolor, add_grid=True, add_axis=True)
        else:
            self.x_values = x[:]
            plot = create_line_plot((self.x_values,self.y_values), color=color,
                                    bgcolor=bgcolor, add_grid=True, add_axis=True)

        plot.resizable = ""
        plot.bounds = [PLOT_SIZE, PLOT_SIZE]
        plot.unified_draw = True

        plot.tools.append(PanTool(plot, drag_button="right"))
        plot.tools.append(MoveTool(plot))
        plot.overlays.append(ZoomTool(plot, tool_mode="box", always_on=False))

        self.plot = plot
        self.numpoints = len(self.x_values)
        self.current_index = self.numpoints/2
        self.increment = 2

# Create the plot
    plot = Plot(pd)
    plot.bgcolor = 'black'

    grid_plot = plot.grid_plot("imagedata",
                       type="grid_vertex",
                       xbounds=xs,
                       ybounds=ys)[0]

    # Tweak some of the plot properties
    plot.title = "My First Grid Vertex Plot"
    plot.padding = 50

    # Attach some tools to the plot
    plot.tools.append(PanTool(plot))
    zoom = ZoomTool(component=grid_plot, tool_mode="box", always_on=False)
    grid_plot.overlays.append(zoom)
    return plot

plot = Plot(pd)
    plot.plot(("index", "value"),
              type="scatter",
              marker="circle",
              index_sort="ascending",
              color="orange",
              marker_size=3,
              bgcolor="white")

    # Tweak some of the plot properties
    plot.title = "Scatter Plot"
    plot.line_width = 0.5
    plot.padding = 50

    # 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)

    return plot

# Check for an active window; if none, open one.
    if len(session.windows) == 0:
        if image:
            win = session.new_window(is_image=True)
            activate(win)
        else:
            figure()

    cont = session.active_window.get_container()

    if not cont:
        cont = Plot(session.data)
        session.active_window.set_container(cont)

    existing_tools = [type(t) for t in (cont.tools + cont.overlays)]
    if not PanTool in existing_tools:
        cont.tools.append(PanTool(cont))
    if not ZoomTool in existing_tools:
        cont.overlays.append(ZoomTool(cont, tool_mode="box", always_on=True, drag_button="right"))

    if not session.hold:
        cont.delplot(*cont.plots.keys())

    return cont

plot.plot(("index", "y1"), line_width=2, name="x", color="blue")
    plot.plot(("index", "y2"), line_width=2, name="x**2", color="green")
    plot.plot(("index", "y3"), line_width=2, name="exp(x)", color="gold")
    plot.plot(("index", "y4"), line_width=2, name="gamma(x)",color="orange")
    plot.plot(("index", "y5"), line_width=2, name="x**x", color="red")

    # Set the value axis to display on a log scale
    plot.value_scale = "log"

    # Tweak some of the plot properties
    plot.title = "Log Plot"
    plot.padding = 50
    plot.legend.visible = True

    # Attach some tools to the plot
    plot.tools.append(PanTool(plot))
    zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
    plot.overlays.append(zoom)

    return plot