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

# See the License for the specific language governing permissions and
# limitations under the License.
#===============================================================================

#============= enthought library imports =======================
from traits.api import HasTraits, Instance, Any
from traitsui.api import View, Item, TableEditor
from chaco.api import HPlotContainer, ArrayPlotData, Plot
#============= standard library imports ========================
import os
#============= local library imports  ==========================
from pychron.graph.image_underlay import ImageUnderlay
from pychron.graph.tools.xy_inspector import XYInspector, XYInspectorOverlay

class ImageViewer(HasTraits):
    container = Instance(HPlotContainer, ())
    plot = Any

    def load_image(self, path):
        if os.path.isfile(path):
            with open(path, 'r') as fp:
                self.set_image(fp)

    def set_image(self, buf):
        '''
            buf is a file-like object
        '''
        self.container = HPlotContainer()
        pd = ArrayPlotData(x=[0, 640],
                           y=[0, 480])
        padding = [30, 5, 5, 30]
        plot = Plot(data=pd, padding=padding,

def _container_factory(self):
        pc = HPlotContainer(padding=[5, 5, 5, 20])
        return pc

def _load_image_data(self, data):
        cont = HPlotContainer()
        pd = ArrayPlotData()
        plot = Plot(data=pd, padding=[30, 5, 5, 30], default_origin='top left')

        pd.set_data('img', data)
        img_plot = plot.img_plot('img',
                                 )[0]

        self._add_inspector(img_plot)
        self._add_tools(img_plot)

        cont.add(plot)
        cont.request_redraw()
        self.image_container.container = cont

orientation='v',
                        resizable='v',
                        width=30,
                        padding=20)
    colorbar.plot = plot
    colorbar.padding_top = plot.padding_top
    colorbar.padding_bottom = plot.padding_bottom

    # Add pan and zoom tools to the colorbar
    colorbar.tools.append(PanTool(colorbar, constrain_direction="y", constrain=True))
    zoom_overlay = ZoomTool(colorbar, axis="index", tool_mode="range",
                            always_on=True, drag_button="right")
    colorbar.overlays.append(zoom_overlay)

    # Create a container to position the plot and the colorbar side-by-side
    container = HPlotContainer(plot, colorbar, use_backbuffer=True, bgcolor="lightgray")

    return container

def _container_default(self):
        img_plot = self.img_plot
        zoom_plot = self.zoom_plot
        container = HPlotContainer(img_plot, zoom_plot)
        return container

def set_image(self, buf):
        '''
            buf is a file-like object
        '''
        self.container = HPlotContainer()
        pd = ArrayPlotData(x=[0, 640],
                           y=[0, 480])
        padding = [30, 5, 5, 30]
        plot = Plot(data=pd, padding=padding,
#                    default_origin=''
                    )
        self.plot = plot.plot(('x', 'y'),)[0]
        self.plot.index.sort_order = 'ascending'
        imo = ImageUnderlay(self.plot,
                            padding=padding,
                            path=buf)
        self.plot.overlays.append(imo)

        self._add_tools(self.plot)

        self.container.add(plot)

from chaco.api import ArrayPlotData, HPlotContainer, Plot, jet, ColorBar
from enable.component_editor import ComponentEditor
from traits.api import HasTraits, Instance
from traitsui.api import Item, View

import numpy as np
from chaco.linear_mapper import LinearMapper

N_POINTS = 100

class ColorbarExample(HasTraits):

    plot = Instance(HPlotContainer)

    traits_view = View(Item('plot', editor=ComponentEditor(), show_label=False),
                       width=600, height=600, resizable=True)

    def __init__(self):
        # Create some data
        x = np.random.random(N_POINTS)
        y = np.random.random(N_POINTS)
        color = np.exp(-(x**2 + y**2))

        # Create a plot data object and give it this data
        data = ArrayPlotData(index=x, value=y, color=color)

        # Create the plot
        plot = Plot(data)
        plot.plot(("index", "value", "color"), type="cmap_scatter",

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,
                                                       fill_color="lightgray"))
    
        # we also want to the range selection to inform the cmap plot of
        # the selection, so set that up as well
        self.range_selection.listeners.append(self.my_plot)
    
        # Create a container to position the plot and the colorbar side-by-side
        container = HPlotContainer(use_backbuffer = True)
        container.add(self.tplot)
        container.add(self.colorbar)
        container.bgcolor = "white"
    
        return container

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,
                                                       fill_color="lightgray"))
    
        # we also want to the range selection to inform the cmap plot of
        # the selection, so set that up as well
        self.range_selection.listeners.append(self.my_plot)
    
        # Create a container to position the plot and the colorbar side-by-side
        container = HPlotContainer(use_backbuffer = True)
        container.add(self.tplot)
        container.add(self.colorbar)
        container.bgcolor = "white"
    
        return container

# 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