human
Solve the following python programming problem given the following code:
def mask_relative_difference(data, target1, target2, days = 5, padding_days = 1, per_zone = False) : 
    '
    Masks everywhere except the ``days`` number of days where the
    resource of the two technologies ``target1`` and ``target2`` is most
    different.

    Parameters
    ----------
    data : Calliope model data
    target1 : str
    target2 : str
    days : int, default 5
    padding_days : int, default 1
    per_zone: bool, default False

    ' 
    data_length = len (data._dt) 
    def _get_most_different(data, target1, target2, days, padding_days, target_zone = None) : 
        day_len = int ((24 / data.time_res_data)) 
        targets = (target1, target2) 
        relative_series = [] 
        for t in targets : 
            if (not target_zone) : 
                t_series = data.r [t].sum (1) 
else : 
                t_series = data.r [t].loc [:, target_zone] 
if (t_series.max () < 0) : 
                relative = (t_series / t_series.min ()) 
else : 
                relative = (t_series / t_series.max ()) 
relative_series.append (relative) 
diff = (relative_series [0] - relative_series [1]).abs () 
        most_different = diff.sort_values (ascending = False, inplace = False) 
        datetimes = data._dt.loc [most_different.index] 
        result = datetimes.dt.date.drop_duplicates ().head (days) 
        periods = [] 
        for (index, r) in result.iteritems () : 
            selected = data._dt [(data._dt.dt.date == r)].index [0] 
            start = (selected - (padding_days * day_len)) 
            end = (selected + ((padding_days + 1) * day_len)) 
            periods.append ((start, end)) 
return periods 
if (not per_zone) : 
        periods = _get_most_different (data, target1, target2, days, padding_days) 
else : 
        periods = [] 
        for zone in data._x : 
            p = _get_most_different (data, target1, target2, p, padding_days, target_zone = zone) 
            periods.extend (p) 
mask = pd.Series (1, index = list (range (data_length))) 
    for p in periods : 
      ...

    
    

    Fix the buggy line: p = _get_most_different (data, target1, target2, p, padding_days, target_zone = zone)
assistant
#Here is Python program to fix the buggy line: p = _get_most_different (data, target1, target2, p, padding_days, target_zone = zone)
.

p = _get_most_different (data, target1, target2, days, padding_days, target_zone = zone)