old_contents: """
  ===================================================================
  Plot time-frequency representations on topographies for MEG sensors
  ===================================================================
  
  Both induced power and phase locking values are displayed.
  """
  print __doc__
  
  # Authors: Alexandre Gramfort <gramfort@nmr.mgh.harvard.edu>
  #          Denis Engemann <d.engemann@fz-juelich.de>
  #
  # License: BSD (3-clause)
  
  import numpy as np
  import pylab as pl
  import mne
  from mne import fiff
  from mne.time_frequency import induced_power
  from mne.viz import plot_topo_power, plot_topo_phase_lock
  from mne.datasets import sample
  
  data_path = sample.data_path()
  
  raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif'
  event_fname = data_path + '/MEG/sample/sample_audvis_raw-eve.fif'
  event_id, tmin, tmax = 1, -0.2, 0.5
  
  # Setup for reading the raw data
  raw = fiff.Raw(raw_fname)
  events = mne.read_events(event_fname)
  
  include = []
  raw.info['bads'] += ['MEG 2443', 'EEG 053']  # bads + 2 more
  
  # picks MEG gradiometers
  picks = fiff.pick_types(raw.info, meg='grad', eeg=False, eog=True,
                          stim=False, include=include, exclude='bads')
  
  epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                      baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6))
  data = epochs.get_data()  # as 3D matrix
  
  ###############################################################################
  # Calculate power and phase locking value
  
  frequencies = np.arange(7, 30, 3)  # define frequencies of interest
  n_cycles = frequencies / float(7)  # different number of cycle per frequency
  Fs = raw.info['sfreq']  # sampling in Hz
  decim = 3
  power, phase_lock = induced_power(data, Fs=Fs, frequencies=frequencies,
                                    n_cycles=n_cycles, n_jobs=1, use_fft=False,
                                    decim=decim, zero_mean=True)
  
  ###############################################################################
  # Prepare topography plots, set baseline correction parameters
  
  baseline = (None, 0)  # set the baseline for induced power
  mode = 'ratio'  # set mode for baseline rescaling
  
  ###############################################################################
  # Show topography of power.
  
  title = 'Induced power - MNE sample data'
  plot_topo_power(epochs, power, frequencies, baseline=baseline,
                  mode=mode, decim=decim, vmin=0., vmax=14, title=title)
  pl.show()
  
  ###############################################################################
  # Show topography of phase locking value (PLV)
  
  mode = None  # no baseline rescaling for PLV
  
  title = 'Phase locking value - MNE sample data'
  plot_topo_phase_lock(epochs, phase_lock, frequencies, baseline=baseline,
                      mode=mode, decim=decim, title=title)
  
  pl.show()
  
new_contents: """
  ===================================================================
  Plot time-frequency representations on topographies for MEG sensors
  ===================================================================
  
  Both induced power and phase locking values are displayed.
  """
  print __doc__
  
  # Authors: Alexandre Gramfort <gramfort@nmr.mgh.harvard.edu>
  #          Denis Engemann <d.engemann@fz-juelich.de>
  #
  # License: BSD (3-clause)
  
  import numpy as np
  import pylab as pl
  import mne
  from mne import fiff
  from mne.time_frequency import induced_power
  from mne.viz import plot_topo_power, plot_topo_phase_lock
  from mne.datasets import sample
  
  data_path = sample.data_path()
  
  raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif'
  event_fname = data_path + '/MEG/sample/sample_audvis_raw-eve.fif'
  event_id, tmin, tmax = 1, -0.2, 0.5
  
  # Setup for reading the raw data
  raw = fiff.Raw(raw_fname)
  events = mne.read_events(event_fname)
  
  include = []
  raw.info['bads'] += ['MEG 2443', 'EEG 053']  # bads + 2 more
  
  # picks MEG gradiometers
  picks = fiff.pick_types(raw.info, meg='grad', eeg=False, eog=True,
                          stim=False, include=include, exclude='bads')
  
  epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                      baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6))
  data = epochs.get_data()  # as 3D matrix
  
  layout = mne.layouts.read_layout('Vectorview-all')
  
  ###############################################################################
  # Calculate power and phase locking value
  
  frequencies = np.arange(7, 30, 3)  # define frequencies of interest
  n_cycles = frequencies / float(7)  # different number of cycle per frequency
  Fs = raw.info['sfreq']  # sampling in Hz
  decim = 3
  power, phase_lock = induced_power(data, Fs=Fs, frequencies=frequencies,
                                    n_cycles=n_cycles, n_jobs=1, use_fft=False,
                                    decim=decim, zero_mean=True)
  
  ###############################################################################
  # Prepare topography plots, set baseline correction parameters
  
  baseline = (None, 0)  # set the baseline for induced power
  mode = 'ratio'  # set mode for baseline rescaling
  
  ###############################################################################
  # Show topography of power.
  
  title = 'Induced power - MNE sample data'
  plot_topo_power(epochs, power, frequencies, layout, baseline=baseline,
                  mode=mode, decim=decim, vmin=0., vmax=14, title=title)
  pl.show()
  
  ###############################################################################
  # Show topography of phase locking value (PLV)
  
  mode = None  # no baseline rescaling for PLV
  
  title = 'Phase locking value - MNE sample data'
  plot_topo_phase_lock(epochs, phase_lock, frequencies, layout,
                       baseline=baseline, mode=mode, decim=decim, title=title)
  
  pl.show()
  
subject: revert layout TFR