def _plot_update_epochs_proj(params, bools=None):
 if (bools is not None):
  inds = np.where(bools)[0]
  params['info']['projs'] = [copy.deepcopy(params['projs'][ii]) for ii in inds]
  params['proj_bools'] = bools
 (params['projector'], _) = setup_proj(params['info'], add_eeg_ref=False, verbose=False)
 start = int((params['t_start'] / len(params['epochs'].times)))
 n_epochs = params['n_epochs']
 end = (start + n_epochs)
 data = np.concatenate(params['epochs'][start:end].get_data(), axis=1)
 if (params['projector'] is not None):
  data = np.dot(params['projector'], data)
 types = params['types']
 for (pick, ind) in enumerate(params['inds']):
  params['data'][pick] = (data[ind] / params['scalings'][types[pick]])
 params['plot_fun']()

def _plot_update_epochs_proj ( params , bools = None ) : if ( bools is not None ) : inds = np . where ( bools ) [ 0 ] params [ 'info' ] [ 'projs' ] = [ copy . deepcopy ( params [ 'projs' ] [ ii ] ) for ii in inds ] params [ 'proj_bools' ] = bools ( params [ 'projector' ] , _ ) = setup_proj ( params [ 'info' ] , add_eeg_ref = False , verbose = False ) start = int ( ( params [ 't_start' ] / len ( params [ 'epochs' ] . times ) ) ) n_epochs = params [ 'n_epochs' ] end = ( start + n_epochs ) data = np . concatenate ( params [ 'epochs' ] [ start : end ] . get_data ( ) , axis = 1 ) if ( params [ 'projector' ] is not None ) : data = np . dot ( params [ 'projector' ] , data ) types = params [ 'types' ] for ( pick , ind ) in enumerate ( params [ 'inds' ] ) : params [ 'data' ] [ pick ] = ( data [ ind ] / params [ 'scalings' ] [ types [ pick ] ] ) params [ 'plot_fun' ] ( )
deal with proj changed .