docs: def make_param_dict_from_file(self,path_to_params):
          """
          make param dict from a file on disk
          """
          # then we were given a path to a parameter file
          param_list = list(csv.reader(open(path_to_params,"rb")))
          # delete empty elements (if any)
          param_file = [x for x in param_list if x != []]
          # make dict of [wavenames] = raw_params
          name_list = []
          param_list = []
          # get header names for each param (names of param_list columns)
          param_colnames = param_file[0][1:] # 0th element is "Name" or "Wavename"
          # start from 1.  (row 0 is the header)
          for i in np.arange(1, len(param_file)):
              name_list.append(param_file[i][0])
              param_list.append(param_file[i][1:])
          # remove ' ' blank spaces from param_list
          param_list = [[x.strip() for x in y] for y in param_list]
          param_dict = {}
          # i loops through param_colnames, j loops thru param values per wave
          for i in np.arange(0, len(param_colnames)):
              param_dict[param_colnames[i]] = []
              for j in np.arange(0,len(name_list)):
                  param_dict[param_colnames[i]].append(param_list[j][i])
          # now we have param_dict, and name_list
          self._param_dict = param_dict
          self._row_names = name_list