code: def define_threshold(dat, s_freq, method, value, nbins=120):
      
      if method == 'mean':
          value = value * mean(dat)
      elif method == 'median':
          value = value * median(dat)
      elif method == 'std':
          value = value * std(dat)
      elif method == 'mean+std':
          value = mean(dat) + value * std(dat)
      elif method == 'median+std':
          value = median(dat) + value * std(dat)
      elif method == 'histmax':
          hist = histogram(dat, bins=nbins)
          idx_maxbin = argmax(hist[0])
          maxamp = mean((hist[1][idx_maxbin], hist[1][idx_maxbin + 1]))
          value = value * maxamp
  
      return value
docs: Return the value of the threshold based on relative values.
  
      Parameters
      ----------
      dat : ndarray (dtype='float')
          vector with the data after selection-transformation
      s_freq : float
          sampling frequency
      method : str
          one of 'mean', 'median', 'std', 'mean+std', 'median+std', 'histmax'
      value : float
          value to multiply the values for
      nbins : int
          for histmax method, number of bins in the histogram
  
      Returns
      -------
      float
          threshold in useful units.