code: def create_round_trip_tear_sheet(
      returns,
      positions,
      transactions,
      sector_mappings=None,
      estimate_intraday="infer",
      return_fig=False,
  ):
      """
      Generate a number of figures and plots describing the duration,
      frequency, and profitability of trade "round trips."
      A round trip is started when a new long or short position is
      opened and is only completed when the number of shares in that
      position returns to or crosses zero.
  
      Parameters
      ----------
      returns : pd.Series
          Daily returns of the strategy, noncumulative.
           - See full explanation in create_full_tear_sheet.
      positions : pd.DataFrame
          Daily net position values.
           - See full explanation in create_full_tear_sheet.
      transactions : pd.DataFrame
          Prices and amounts of executed trades. One row per trade.
           - See full explanation in create_full_tear_sheet.
      sector_mappings : dict or pd.Series, optional
          Security identifier to sector mapping.
          Security ids as keys, sectors as values.
      estimate_intraday: boolean or str, optional
          Approximate returns for intraday strategies.
          See description in create_full_tear_sheet.
      return_fig : boolean, optional
          If True, returns the figure that was plotted on.
      """
  
      positions = utils.check_intraday(
          estimate_intraday, returns, positions, transactions
      )
  
      transactions_closed = round_trips.add_closing_transactions(
          positions, transactions
      )
      # extract_round_trips requires BoD portfolio_value
      trades = round_trips.extract_round_trips(
          transactions_closed,
          portfolio_value=positions.sum(axis="columns") / (1 + returns),
      )
  
      if len(trades) < 5:
          warnings.warn(
              """Fewer than 5 round-trip trades made.
                 Skipping round trip tearsheet.""",
              UserWarning,
          )
          return
  
      round_trips.print_round_trip_stats(trades)
  
      plotting.show_profit_attribution(trades)
  
      if sector_mappings is not None:
          sector_trades = (
              round_trips.apply_sector_mappings_to_round_trips(
                  trades, sector_mappings
              )
          )
          plotting.show_profit_attribution(sector_trades)
  
      fig = plt.figure(figsize=(14, 3 * 6))
  
      gs = gridspec.GridSpec(3, 2, wspace=0.5, hspace=0.5)
  
      ax_trade_lifetimes = plt.subplot(gs[0, :])
      ax_prob_profit_trade = plt.subplot(gs[1, 0])
      ax_holding_time = plt.subplot(gs[1, 1])
      ax_pnl_per_round_trip_dollars = plt.subplot(gs[2, 0])
      ax_pnl_per_round_trip_pct = plt.subplot(gs[2, 1])
  
      plotting.plot_round_trip_lifetimes(trades, ax=ax_trade_lifetimes)
  
      plotting.plot_prob_profit_trade(trades, ax=ax_prob_profit_trade)
  
      trade_holding_times = [x.days for x in trades["duration"]]
      sns.distplot(trade_holding_times, kde=False, ax=ax_holding_time)
      ax_holding_time.set(xlabel="Holding time in days")
  
      sns.distplot(
          trades.pnl, kde=False, ax=ax_pnl_per_round_trip_dollars
      )
      ax_pnl_per_round_trip_dollars.set(
          xlabel="PnL per round-trip trade in $"
      )
  
      sns.distplot(
          trades.returns.dropna() * 100,
          kde=False,
          ax=ax_pnl_per_round_trip_pct,
      )
      ax_pnl_per_round_trip_pct.set(xlabel="Round-trip returns in %")
  
      gs.tight_layout(fig)
  
      if return_fig:
          return fig
  
imports: from __future__ import division
  import warnings
  from time import time
  import empyrical
  from IPython.display import display, Markdown
  import matplotlib.gridspec
  import matplotlib.pyplot
  import pandas
  from .None import _seaborn
  from .None import capacity
  from .None import perf_attrib
  from .None import plotting
  from .None import pos
  from .None import round_trips
  from .None import timeseries
  from .None import txn
  from .None import utils
label_desc: Use image node_id 7 for calling a global function with example usage: create_round_trip_tear_sheet(returns, positions, transactions, sector_mappings, estimate_intraday, return_fig) and returns: fig