class_docstr: The algorithm's interface to the registered risk and performance
  metrics.
  
  Parameters
  ----------
  trading_calendar : TrandingCalendar
      The trading calendar used in the simulation.
  first_session : pd.Timestamp
      The label of the first trading session in the simulation.
  last_session : pd.Timestamp
      The label of the last trading session in the simulation.
  capital_base : float
      The starting capital for the simulation.
  emission_rate : {'daily', 'minute'}
      How frequently should a performance packet be generated?
  data_frequency : {'daily', 'minute'}
      The data frequency of the data portal.
  asset_finder : AssetFinder
      The asset finder used in the simulation.
  metrics : list[Metric]
      The metrics to track.
docstr: Handles the close of the given minute in minute emission.
  
  Parameters
  ----------
  dt : Timestamp
      The minute that is ending
  
  Returns
  -------
  A minute perf packet.
docstr_tok: ["Handles","the","close","of","the","given","minute","in","minute","emission",".","Parameters","--","--","--","--","--","dt",":","Timestamp","The","minute","that","is","ending","Returns","--","--","--","-","A","minute","perf","packet","."]
code: def handle_minute_close(self, dt, data_portal):
      """
      Handles the close of the given minute in minute emission.
  
      Parameters
      ----------
      dt : Timestamp
          The minute that is ending
  
      Returns
      -------
      A minute perf packet.
      """
      self.sync_last_sale_prices(dt, data_portal)
  
      packet = {
          "period_start": self._first_session,
          "period_end": self._last_session,
          "capital_base": self._capital_base,
          "minute_perf": {
              "period_open": self._market_open,
              "period_close": dt,
          },
          "cumulative_perf": {
              "period_open": self._first_session,
              "period_close": self._last_session,
          },
          "progress": self._progress(self),
          "cumulative_risk_metrics": {},
      }
      ledger = self._ledger
      ledger.end_of_bar(self._session_count)
      self.end_of_bar(
          packet,
          ledger,
          dt,
          self._session_count,
          data_portal,
      )
      return packet
  
imports: from __future__ import division
  import logbook
  from ..ledger import Ledger
  from zipline.utils.exploding_object import NamedExplodingObject
label_desc: Use image node_id 16 for calling the MetricsTracker obj's underlying member method code with example usage: obj.handle_minute_close(dt, data_portal) and returns: packet