old_contents: import matplotlib.pyplot as plt
  
  from bluesky import RunEngine, Mover, SynGauss
  from bluesky.examples import adaptive_scan
  
  
  RE = RunEngine()
  RE.verbose = False
  motor = Mover('motor', ['pos'])
  det = SynGauss('det', motor, 'pos', center=0, Imax=1, sigma=1)
  
  
  def live_scalar_plotter(ax, y, x):
      x_data, y_data = [], []
      line, = ax.plot([], [], 'ro', markersize=10)
  
      def update_plot(doc):
          # Update with the latest data.
          x_data.append(doc['data'][x])
          y_data.append(doc['data'][y])
          line.set_data(x_data, y_data)
          # Rescale and redraw.
          ax.relim(visible_only=True)
          ax.autoscale_view(tight=True)
          ax.figure.canvas.draw()
          ax.figure.canvas.flush_events()
  
      return update_plot
  
  fig, ax = plt.subplots()
  plt.show()
  ax.set_xlim([-15, 5])
  ax.set_ylim([0, 2])
  # Point the function to our axes above, and specify what to plot.
  my_plotter = live_scalar_plotter(ax, 'det', 'pos')
  ad_scan = adaptive_scan(motor, det, 'pos', 'det', -15, 5, .01, 1, .05)
  RE.run(ad_scan, subscriptions={'event': my_plotter})
  
new_contents: import matplotlib.pyplot as plt
  
  from bluesky import RunEngine
  from bluesky.scans import AdaptiveAscan
  from bluesky.examples import Mover, SynGauss
  from bluesky.callbacks import LivePlot, LiveTable
  from bluesky.tests.utils import setup_test_run_engine
  
  
  #plt.ion()
  RE = setup_test_run_engine()
  motor = Mover('motor', ['pos'])
  det = SynGauss('det', motor, 'pos', center=0, Imax=1, sigma=1)
  
  
  #fig, ax = plt.subplots()
  #ax.set_xlim([-15, 5])
  #ax.set_ylim([0, 2])
  # Point the function to our axes above, and specify what to plot.
  #my_plotter = LivePlot('det', 'pos')
  table = LiveTable(['det', 'pos'])
  ad_scan = AdaptiveAscan(motor, [det], 'det', -15, 5, .01, 1, .05, True)
  RE(ad_scan, subscriptions={'all': [table]}) #, my_plotter})
  
subject: Fix adaptive example with LivePlot