class_docstr: Defines a level of significance by taking into account the average of price
  bar components of the past period of a larger timeframe. For example when
  operating with days, the values are taking from the already "past" month
  fixed prices.
  
  Fibonacci levels (configurable) are used to define the support/resistance levels
  
  Example of using this indicator:
  
    data = btfeeds.ADataFeed(dataname=x, timeframe=bt.TimeFrame.Days)
    cerebro.adddata(data)
    cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)
  
  In the ``__init__`` method of the strategy:
  
    pivotindicator = btind.FibonacciPivotPoiont(self.data1)  # the resampled data
  
  The indicator will try to automatically plo to the non-resampled data. To
  disable this behavior use the following during construction:
  
    - _autoplot=False
  
  Note:
  
    The example shows *days* and *months*, but any combination of timeframes
    can be used. See the literature for recommended combinations
  
  Formula:
    - pivot = (h + l + c) / 3  # variants duplicate close or add open
    - support1 = p - level1 * (high - low)  # level1 0.382
    - support2 = p - level2 * (high - low)  # level2 0.618
    - support3 = p - level3 * (high - low)  # level3 1.000
    - resistance1 = p + level1 * (high - low)  # level1 0.382
    - resistance2 = p + level2 * (high - low)  # level2 0.618
    - resistance3 = p + level3 * (high - low)  # level3 1.000
  
  See:
    - http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:pivot_points
code: def __init__(self):
      o = self.data.open
      h = self.data.high  # current high
      l = self.data.low  # current high
      c = self.data.close  # current high
  
      if self.p.close:
          self.lines.p = p = (h + l + 2.0 * c) / 4.0
      elif self.p.open:
          self.lines.p = p = (h + l + c + o) / 4.0
      else:
          self.lines.p = p = (h + l + c) / 3.0
  
      self.lines.s1 = p - self.p.level1 * (h - l)
      self.lines.s2 = p - self.p.level2 * (h - l)
      self.lines.s3 = p - self.p.level3 * (h - l)
  
      self.lines.r1 = p + self.p.level1 * (h - l)
      self.lines.r2 = p + self.p.level2 * (h - l)
      self.lines.r3 = p + self.p.level3 * (h - l)
  
      super(FibonacciPivotPoint, self).__init__()
  
      if self.p._autoplot:
          self.plotinfo.plot = False  # disable own plotting
          self()
  
file_path: backtrader/backtrader/indicators/pivotpoint.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from .None import Indicator, CmpEx
label_desc: Use image node_id 2 to create a new FibonacciPivotPoint object from inherited base classes: Indicator with example: obj = FibonacciPivotPoint()