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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def disaggregate_humidity(self, method='equal', preserve_daily_mean=False):
 """ Disaggregate relative humidity. Parameters method : str, optional Disaggregation method. ``equal`` Mean daily humidity is duplicated for the 24 hours of the day. (Default) ``minimal``: Calculates humidity from daily dew point temperature by setting the dew point temperature equal to the daily minimum temperature. ``dewpoint_regression``: Calculates humidity from daily dew point temperature by calculating dew point temperature using ``Tdew = a * Tmin + b``, where ``a`` and ``b`` are determined by calibration. ``linear_dewpoint_variation``: Calculates humidity from hourly dew point temperature by assuming a linear dew point temperature variation between consecutive days. ``min_max``: Calculates hourly humidity from observations of daily minimum and maximum humidity. ``month_hour_precip_mean``: Calculates hourly humidity from categorical [month, hour, precip(y/n)] mean values derived from observations. preserve_daily_mean : bool, optional If True, correct the daily mean values of the disaggregated data with the observed daily means. """

        self.data_disagg.hum = melodist.disaggregate_humidity(
            self.data_daily,
            temp=self.data_disagg.temp,
            method=method,
            preserve_daily_mean=preserve_daily_mean,
            **self.statistics.hum
        )