docs: def load(self, path, genes_uuid, regs=['chr', 'left', 'right', 'strand'], meta=[], values=[], full_load=False):
          """
          Loads the multi referenced mapped data from the file system
          
          :param path: The path to the files
          :param genes_uuid: The unique identifier metadata column name to separate the data by the number of references
          :param regs: The region data that are to be analyzed
          :param meta: The metadata that are to be analyzed
          :param values: The values to fill the matrix
          :param full_load: Specifies the method of parsing the data. If False then parser omits the parsing of zero(0) 
          values in order to speed up and save memory. However, while creating the matrix, those zero values are going to be put into the matrix.
          (unless a row contains "all zero columns". This parsing is strongly recommended for sparse datasets.
          If the full_load parameter is True then all the zero(0) data are going to be read.
  
          """
  
          if not full_load:
              warnings.warn("\n\n You are using the optimized loading technique. "
                            "All-zero rows are not going to be loaded into memory. "
                            "To load all the data please set the full_load parameter equal to True.")
          p = Parser(path)
          all_meta_data = p.parse_meta(meta)
          all_data = p.parse_data(regs, values, full_load)
  
          all_data = pd.pivot_table(all_data,
                                     values=values, columns=regs, index=['sample'],
                                     fill_value=0)
  
          group1 = all_meta_data.groupby([genes_uuid]).count()
          for g in group1.index.values:
              series = all_meta_data[genes_uuid] == g
              m = (all_meta_data[series])
              d = (all_data.loc[series]).dropna(axis=1, how='all')  # not to show the NaN data
              self.data_model.append(GenometricSpace.from_memory(d, m))
              self.all_meta_data = all_meta_data