metsim.py 文件源码

def _aggregate_state(self):
        """Aggregate data out of the state file and load it into `met_data`"""
        # Precipitation record
        begin_record = self.params['start'] - pd.Timedelta("90 days")
        end_record = self.params['start'] - pd.Timedelta("1 days")
        record_dates = date_range(begin_record, end_record,
                                  calendar=self.params['calendar'])
        trailing = self.state['prec'].sel(time=record_dates)
        total_precip = xr.concat([trailing, self.met_data['prec']], dim='time')
        total_precip = (cnst.DAYS_PER_YEAR * total_precip.rolling(
            time=90).mean().drop(record_dates, dim='time'))
        self.met_data['seasonal_prec'] = total_precip

        # Smoothed daily temperature range
        trailing = self.state['t_max'] - self.state['t_min']
        begin_record = self.params['start'] - pd.Timedelta("90 days")
        end_record = self.params['start'] - pd.Timedelta("1 days")
        record_dates = date_range(begin_record, end_record,
                                  calendar=self.params['calendar'])
        trailing['time'] = record_dates
        dtr = self.met_data['t_max'] - self.met_data['t_min']
        sm_dtr = xr.concat([trailing, dtr], dim='time')
        sm_dtr = sm_dtr.rolling(time=30).mean().drop(record_dates, dim='time')
        self.met_data['smoothed_dtr'] = sm_dtr

        # Put in SWE data
        self.state['swe'] = self.state.sel(time=end_record).swe.drop('time')
        self.met_data['swe'] = self.state.swe.copy()