code: def to_timestamp(self, freq=None, how='start'):
          
          from pandas.core.arrays import DatetimeArray
  
          how = libperiod._validate_end_alias(how)
  
          end = how == 'E'
          if end:
              if freq == 'B':
                  # roll forward to ensure we land on B date
                  adjust = Timedelta(1, 'D') - Timedelta(1, 'ns')
                  return self.to_timestamp(how='start') + adjust
              else:
                  adjust = Timedelta(1, 'ns')
                  return (self + self.freq).to_timestamp(how='start') - adjust
  
          if freq is None:
              base, mult = libfrequencies.get_freq_code(self.freq)
              freq = libfrequencies.get_to_timestamp_base(base)
          else:
              freq = Period._maybe_convert_freq(freq)
  
          base, mult = libfrequencies.get_freq_code(freq)
          new_data = self.asfreq(freq, how=how)
  
          new_data = libperiod.periodarr_to_dt64arr(new_data.asi8, base)
          return DatetimeArray._from_sequence(new_data, freq='infer')
docs: Cast to DatetimeArray/Index.
  
          Parameters
          ----------
          freq : string or DateOffset, optional
              Target frequency. The default is 'D' for week or longer,
              'S' otherwise
          how : {'s', 'e', 'start', 'end'}
  
          Returns
          -------
          DatetimeArray/Index