def METHOD_NAME():
    # Create a scalar field to colormap
    x_extents = (-2 * pi, 2 * pi)
    y_extents = (-1.5 * pi, 1.5 * pi)
    xs = linspace(-2 * pi, 2 * pi, 200)
    ys = linspace(-1.5 * pi, 1.5 * pi, 100)
    x, y = meshgrid(xs, ys)
    zs = sin(log(abs((x + 1) ** 4) + 0.05)) * cos(y) * 1.1 * (-y) + sin(
        ((x + 1) ** 2 + y ** 2) / 4
    )
    # Create a plot data obect and give it this data
    pd = ArrayPlotData()
    pd.set_data("imagedata", zs)
    # Create the left plot, a colormap and simple contours
    lplot = Plot(pd)
    lplot.img_plot(
        "imagedata",
        name="cm_plot",
        xbounds=x_extents,
        ybounds=y_extents,
        colormap=gmt_drywet,
    )
    lplot.contour_plot(
        "imagedata", type="line", xbounds=x_extents, ybounds=y_extents
    )
    # Tweak some of the plot properties
    lplot.title = "Colormap and contours"
    lplot.padding = 20
    lplot.bgcolor = "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",
        levels=15,
        styles="solid",
        widths=list(linspace(4.0, 0.1, 15)),
        colors=gmt_drywet,
    )
    # Add some tools to the plot
    zoom = ZoomTool(rplot, tool_mode="box", always_on=False)
    rplot.overlays.append(zoom)
    rplot.tools.append(PanTool(rplot, constrain_key="shift"))
    # Tweak some of the plot properties
    rplot.title = "Varying contour lines"
    rplot.padding = 20
    rplot.bgcolor = "white"
    rplot.fill_padding = True
    # Create a container and add our plots
    container = HPlotContainer(
        padding=40, fill_padding=True, bgcolor="white", use_backbuffer=True
    )
    container.add(colorbar)
    container.add(lplot)
    container.add(rplot)
    return container