code: def global_message():
      
      # Compute the weight for each item in the tree
      current_thresholds = glances_thresholds.get()
      for i in tree:
          i['weight'] = sum([current_thresholds[t].value() for t in i['thresholds'] if t in current_thresholds])
      themax = max(tree, key=lambda d: d['weight'])
      if themax['weight'] >= themax['thresholds_min']:
          # Check if the weight is > to the minimal threashold value
          return themax['msg']
      else:
          return tree[0]['msg']
docs: Parse the decision tree and return the message.
  
      Note: message corresponding to the current threasholds values