content: """
  ========================================
  Plotting topographic maps of evoked data
  ========================================
  
  Load evoked data and plot topomaps for selected time points.
  
  """
  # Authors: Christian Brodbeck <christianbrodbeck@nyu.edu>
  #          Tal Linzen <linzen@nyu.edu>
  #          Denis A. Engeman <denis.engemann@gmail.com>
  #
  # License: BSD (3-clause)
  
  import numpy as np
  import matplotlib.pyplot as plt
  from mne.datasets import sample
  from mne import read_evokeds
  
  print(__doc__)
  
  path = sample.data_path()
  fname = path + '/MEG/sample/sample_audvis-ave.fif'
  
  # load evoked and subtract baseline
  condition = 'Left Auditory'
  evoked = read_evokeds(fname, condition=condition, baseline=(None, 0))
  
  # set time instants in seconds (from 50 to 150ms in a step of 10ms)
  times = np.arange(0.05, 0.15, 0.01)
  # If times is set to None only 10 regularly spaced topographies will be shown
  
  # plot magnetometer data as topomaps
  evoked.plot_topomap(times, ch_type='mag')
  
  # compute a 50 ms bin to stabilize topographies
  evoked.plot_topomap(times, ch_type='mag', average=0.05)
  
  # plot gradiometer data (plots the RMS for each pair of gradiometers)
  evoked.plot_topomap(times, ch_type='grad')
  
  # plot magnetometer data as topomap at 1 time point : 100 ms
  # and add channel labels and title
  evoked.plot_topomap(0.1, ch_type='mag', show_names=True, colorbar=False,
                      size=6, res=128, title='Auditory response')
  plt.subplots_adjust(left=0.01, right=0.99, bottom=0.01, top=0.88)
  