diff --git a/examples/userdemo/colormap_interactive_adjustment.py b/examples/userdemo/colormap_interactive_adjustment.py
index 47563b79328a..bdea2966c431 100644
--- a/examples/userdemo/colormap_interactive_adjustment.py
+++ b/examples/userdemo/colormap_interactive_adjustment.py
@@ -3,88 +3,29 @@
 Interactive Adjustment of Colormap Range
 ========================================
 
-Demonstration of using colorbar, picker, and event functionality to make an
-interactively adjustable colorbar widget.
-
-Left clicks and drags inside the colorbar axes adjust the high range of the
-color scheme. Likewise, right clicks and drags adjust the low range. The
-connected AxesImage immediately updates to reflect the change.
+Demonstration of how a colorbar can be used to interactively adjust the
+range of colormapping on an image. To use the interactive feature, you must
+be in either zoom mode (magnifying glass toolbar button) or
+pan mode (4-way arrow toolbar button) and click inside the colorbar.
+
+When zooming, the bounding box of the zoom region defines the new vmin and
+vmax of the norm. Zooming using the right mouse button will expand the
+vmin and vmax proportionally to the selected region, in the same manner that
+one can zoom out on an axis. When panning, the vmin and vmax of the norm are
+both shifted according to the direction of movement. The
+Home/Back/Forward buttons can also be used to get back to a previous state.
 """
-
-import numpy as np
 import matplotlib.pyplot as plt
-from matplotlib.backend_bases import MouseButton
-
-###############################################################################
-# Callback definitions
-
-
-def on_pick(event):
-    adjust_colorbar(event.mouseevent)
-
-
-def on_move(mouseevent):
-    if mouseevent.inaxes is colorbar.ax:
-        adjust_colorbar(mouseevent)
-
-
-def adjust_colorbar(mouseevent):
-    if mouseevent.button == MouseButton.LEFT:
-        colorbar.norm.vmax = max(mouseevent.ydata, colorbar.norm.vmin)
-    elif mouseevent.button == MouseButton.RIGHT:
-        colorbar.norm.vmin = min(mouseevent.ydata, colorbar.norm.vmax)
-    else:
-        # discard all others
-        return
-
-    canvas.draw_idle()
-
+import numpy as np
 
-###############################################################################
-# Generate figure with Axesimage and Colorbar
+t = np.linspace(0, 2 * np.pi, 1024)
+data2d = np.sin(t)[:, np.newaxis] * np.cos(t)[np.newaxis, :]
 
 fig, ax = plt.subplots()
-canvas = fig.canvas
-
-delta = 0.1
-x = np.arange(-3.0, 4.001, delta)
-y = np.arange(-4.0, 3.001, delta)
-X, Y = np.meshgrid(x, y)
-Z1 = np.exp(-X**2 - Y**2)
-Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
-Z = (0.9*Z1 - 0.5*Z2) * 2
-
-cmap = plt.colormaps['viridis'].with_extremes(
-    over='xkcd:orange', under='xkcd:dark red')
-axesimage = plt.imshow(Z, cmap=cmap)
-colorbar = plt.colorbar(axesimage, ax=ax, use_gridspec=True)
-
-###############################################################################
-# Note that axesimage and colorbar share a Normalize object
-# so they will stay in sync
-
-assert colorbar.norm is axesimage.norm
-colorbar.norm.vmax = 1.5
-axesimage.norm.vmin = -0.75
-
-###############################################################################
-# Hook Colorbar up to canvas events
-
-# `set_navigate` helps you see what value you are about to set the range
-# to, and enables zoom and pan in the colorbar which can be helpful for
-# narrow or wide data ranges
-colorbar.ax.set_navigate(True)
-
-# React to all motion with left or right mouse buttons held
-canvas.mpl_connect("motion_notify_event", on_move)
-
-# React only to left and right clicks
-colorbar.ax.set_picker(True)
-canvas.mpl_connect("pick_event", on_pick)
+im = ax.imshow(data2d)
+ax.set_title('Pan on the colorbar to shift the color mapping\n'
+             'Zoom on the colorbar to scale the color mapping')
 
-###############################################################################
-# Display
-#
-# The colormap will now respond to left and right clicks in the Colorbar axes
+fig.colorbar(im, ax=ax, label='Interactive colorbar')
 
 plt.show()