class_docstr: Replays a bar in 2 steps:
  
    - In the 1st step the "Open-High-Low" could be evaluated to decide if to
      act on the close (the close is still there ... should not be evaluated)
  
    - If a "Close" order has been executed
  
      In this 1st fragment the "Close" is replaced through the "open" althoug
      other alternatives would be possible like high - low average, or an
      algorithm based on where the "close" ac
  
    and
  
    - Open-High-Low-Close
code: def __call__(self, data):
      # Make a copy of the new bar and remove it from stream
      closebar = [data.lines[i][0] for i in range(data.size())]
      datadt = data.datetime.date()  # keep the date
  
      ohlbar = closebar[:]  # Make an open-high-low bar
  
      # Adjust volume
      ohlbar[data.Volume] = int(
          closebar[data.Volume] * (1.0 - self.p.cvol)
      )
  
      dt = datetime.datetime.combine(datadt, data.p.sessionstart)
      ohlbar[data.DateTime] = data.date2num(dt)
  
      dt = datetime.datetime.combine(datadt, data.p.sessionend)
      closebar[data.DateTime] = data.date2num(dt)
  
      # Update stream
      data.backwards()  # remove the copied bar from stream
      # Overwrite the new data bar with our pending data - except start point
      if self.pendingbar is not None:
          data._updatebar(self.pendingbar)
  
      self.pendingbar = (
          closebar  # update the pending bar to the new bar
      )
      data._add2stack(
          ohlbar
      )  # Add the openbar to the stack for processing
  
      return False
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import argparse
  import datetime
  import backtrader
  import backtrader.indicators
label_desc: Use image node_id 2 for calling the DayStepsCloseFilter obj's underlying member method code with example usage: obj.__call__(data) and returns: False