def _check_n_samples(n_samples, n_chan):
 n_samples_min = ((10 * (n_chan + 1)) // 2)
 if (n_samples <= 0):
  raise ValueError('No samples found to compute the covariance matrix')
 if (n_samples < n_samples_min):
  warn(('Too few samples (required : %d got : %d), covariance estimate may be unreliable' % (n_samples_min, n_samples)))

def _check_n_samples ( n_samples , n_chan ) : n_samples_min = ( ( 10 * ( n_chan + 1 ) ) // 2 ) if ( n_samples <= 0 ) : raise ValueError ( 'No samples found to compute the covariance matrix' ) if ( n_samples < n_samples_min ) : warn ( ( 'Too few samples (required : %d got : %d), covariance estimate may be unreliable' % ( n_samples_min , n_samples ) ) )
check to see if there are enough samples for reliable cov calc .