"    Input:  {
              (dict)                        - pre-loaded dict with characteristics that will be flattened
                  or
              (flat_dict)                   - pre-loaded flat dict with characteristics

                                                  USE 'characteristic_list' in dict!

              dict_to_add                   - data to analyze and add to dict

              (dict_to_compare)             - flat dict to calculate improvements

              (process_multi_keys)          - list of keys (starts with) to perform stat analysis on flat array,
                                              by default ['##characteristics#*', '##features#*' '##choices#*'],
                                              if empty, no stat analysis

              (skip_stat_analysis)          - if 'yes', just flatten array and add #min
            }

    Output: {
              return       - return code =  0, if successful
                                         >  0, if error
              (error)      - error text if return > 0

              dict_flat         - updated and flattened original dictionary
              max_range_percent - max % range in float/int data (useful to record points with unusual behavior)
              min               - 'yes', if one of monitored values reached min
              max               - 'yes', if one of monitored values reached max
            }

"