old_contents: import mne
  import sys
  
  from mne import compute_covariance
  
  import matplotlib
  matplotlib.use('Agg')
  import matplotlib.pyplot as plt
  
  from my_settings import *
  
  reject = dict(grad=4000e-13,  # T / m (gradiometers)
                mag=4e-12,  # T (magnetometers)
                eeg=180e-6  #
                )
  
  
  subject = sys.argv[1]
  
  epochs = mne.read_epochs(epochs_folder + "%s_trial_start-epo.fif" % subject)
  epochs.drop_bad_epochs(reject)
  
  fig = epochs.plot_drop_log(subject=subject, show=False)
  fig.savefig(epochs_folder + "pics/%s_drop_log.png" % subject)
  
  # Make noise cov
  cov = compute_covariance(epochs, tmin=None, tmax=-0.2,
                           method="factor_analysis")
  mne.write_cov(mne_folder + "%s-cov.fif" % subject, cov)
  
  
new_contents: import mne
  import sys
  
  from mne import compute_covariance
  
  import matplotlib
  matplotlib.use('Agg')
  import matplotlib.pyplot as plt
  
  from my_settings import *
  
  reject = dict(grad=4000e-13,  # T / m (gradiometers)
                mag=4e-12,  # T (magnetometers)
                eeg=180e-6  #
                )
  
  
  subject = sys.argv[1]
  
  epochs = mne.read_epochs(epochs_folder + "%s_trial_start-epo.fif" % subject)
  epochs.drop_bad_epochs(reject)
  
  fig = epochs.plot_drop_log(subject=subject, show=False)
  fig.savefig(epochs_folder + "pics/%s_drop_log.png" % subject)
  
  # Make noise cov
  cov = compute_covariance(epochs, tmin=None, tmax=0,
                           method="shrunk")
  mne.write_cov(mne_folder + "%s-cov.fif" % subject, cov)
  
  
subject: change method