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
make param dict from a file on disk