def METHOD_NAME(input_path, store, tz, sort_index=True):
    """
    Parameters
    ----------
    input_path : str
        The root path of the REFIT dataset.
    store : DataStore
        The NILMTK DataStore object.
    measurement_mapping_func : function
        Must take these parameters:
            - house_id
            - chan_id
        Function should return a list of tuples e.g. [('power', 'active')]
    tz : str 
        Timezone e.g. 'US/Eastern'
    sort_index : bool
    """
    check_directory_exists(input_path)
    # Iterate though all houses and channels
    # house 14 is missing!
    houses = [1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,17,18,19,20,21]
    nilmtk_house_id = 0
    prefix = ''
    suffix = '_'
    version_checked = False
    for house_id in houses:
        nilmtk_house_id += 1
        print("Loading house", house_id, end="... ")
        stdout.flush()
        csv_filename = join(input_path, prefix + 'House' + suffix + str(house_id) + '.csv')
        if not version_checked:
            version_checked = True
            if exists(csv_filename):
                print('Using original filenames (House_XX.csv)')
            else:
                prefix = 'CLEAN_'
                suffix = ''
                csv_filename = join(input_path, prefix + 'House' + suffix + str(house_id) + '.csv')
                print('Using CLEAN filenames (CLEAN_HouseXX.csv)')
        if not exists(csv_filename):
            raise RuntimeError('Could not find REFIT files. Please check the provided folder.')
        # The clean version already includes header, so we
        # just skip the text version of the timestamp
        usecols = ['Unix','Aggregate','Appliance1','Appliance2','Appliance3','Appliance4','Appliance5','Appliance6','Appliance7','Appliance8','Appliance9']
        df = _load_csv(csv_filename, usecols, tz)
        if sort_index:
            df = df.sort_index() # might not be sorted...
        chan_id = 0
        for col in df.columns:
            chan_id += 1
            print(chan_id, end=" ")
            stdout.flush()
            key = Key(building=nilmtk_house_id, meter=chan_id)
            chan_df = pd.DataFrame(df[col])
            chan_df.columns = pd.MultiIndex.from_tuples([('power', 'active')])
            # Modify the column labels to reflect the power measurements recorded.
            chan_df.columns.set_names(LEVEL_NAMES, inplace=True)
            store.put(str(key), chan_df)
        print('')