def _check_ch_names(inv, info):
 inv_ch_names = inv['eigen_fields']['col_names']
 if (inv['noise_cov'].ch_names != inv_ch_names):
  raise ValueError('Channels in inverse operator eigen fields do not match noise covariance channels.')
 data_ch_names = info['ch_names']
 missing_ch_names = list()
 for ch_name in inv_ch_names:
  if (ch_name not in data_ch_names):
   missing_ch_names.append(ch_name)
 n_missing = len(missing_ch_names)
 if (n_missing > 0):
  raise ValueError((('%d channels in inverse operator ' % n_missing) + ('are not present in the data (%s)' % missing_ch_names)))

def _check_ch_names ( inv , info ) : inv_ch_names = inv [ 'eigen_fields' ] [ 'col_names' ] if ( inv [ 'noise_cov' ] . ch_names != inv_ch_names ) : raise ValueError ( 'Channels in inverse operator eigen fields do not match noise covariance channels.' ) data_ch_names = info [ 'ch_names' ] missing_ch_names = list ( ) for ch_name in inv_ch_names : if ( ch_name not in data_ch_names ) : missing_ch_names . append ( ch_name ) n_missing = len ( missing_ch_names ) if ( n_missing > 0 ) : raise ValueError ( ( ( '%d channels in inverse operator ' % n_missing ) + ( 'are not present in the data (%s)' % missing_ch_names ) ) )
check that channels in inverse operator are measurements .