code: def __init__(self):
      # to have a tight packing on the chart wether only the x axis or also
      # the y axis have (see matplotlib)
      self.ytight = False
  
      # y-margin (top/bottom) for the subcharts. This will not overrule the
      # option plotinfo.plotymargin
      self.yadjust = 0.0
      # Each new line is in z-order below the previous one. change it False
      # to have lines paint above the previous line
      self.zdown = True
      # Rotation of the date labes on the x axis
      self.tickrotation = 15
  
      # How many "subparts" takes a major chart (datas) in the overall chart
      # This is proportional to the total number of subcharts
      self.rowsmajor = 5
  
      # How many "subparts" takes a minor chart (indicators/observers) in the
      # overall chart. This is proportional to the total number of subcharts
      # Together with rowsmajor, this defines a proportion ratio betwen data
      # charts and indicators/observers charts
      self.rowsminor = 1
  
      # Distance in between subcharts
      self.plotdist = 0.0
  
      # Have a grid in the background of all charts
      self.grid = True
  
      # Default plotstyle for the OHLC bars which (line -> line on close)
      # Other options: 'bar' and 'candle'
      self.style = "line"
  
      # Default color for the 'line on close' plot
      self.loc = "black"
      # Default color for a bullish bar/candle (0.75 -> intensity of gray)
      self.barup = "0.75"
      # Default color for a bearish bar/candle
      self.bardown = "red"
      # Level of transparency to apply to bars/cancles (NOT USED)
      self.bartrans = 1.0
  
      # Wether the candlesticks have to be filled or be transparent
      self.barupfill = True
      self.bardownfill = True
  
      # Opacity for the filled candlesticks (1.0 opaque - 0.0 transparent)
      self.baralpha = 1.0
  
      # Alpha blending for fill areas between lines (_fill_gt and _fill_lt)
      self.fillalpha = 0.20
  
      # Wether to plot volume or not. Note: if the data in question has no
      # volume values, volume plotting will be skipped even if this is True
      self.volume = True
  
      # Wether to overlay the volume on the data or use a separate subchart
      self.voloverlay = True
      # Scaling of the volume to the data when plotting as overlay
      self.volscaling = 0.33
      # Pushing overlay volume up for better visibiliy. Experimentation
      # needed if the volume and data overlap too much
      self.volpushup = 0.00
  
      # Default colour for the volume of a bullish day
      self.volup = "#aaaaaa"  # 0.66 of gray
      # Default colour for the volume of a bearish day
      self.voldown = "#cc6073"  # (204, 96, 115)
      # Transparency to apply to the volume when overlaying
      self.voltrans = 0.50
  
      # Transparency for text labels (NOT USED CURRENTLY)
      self.subtxttrans = 0.66
      # Default font text size for labels on the chart
      self.subtxtsize = 9
  
      # Transparency for the legend (NOT USED CURRENTLY)
      self.legendtrans = 0.25
      # Wether indicators have a leged displaey in their charts
      self.legendind = True
      # Location of the legend for indicators (see matplotlib)
      self.legendindloc = "upper left"
  
      # Location of the legend for datafeeds (see matplotlib)
      self.legenddataloc = "upper left"
  
      # Plot the last value of a line after the Object name
      self.linevalues = True
  
      # Plot a tag at the end of each line with the last value
      self.valuetags = True
  
      # Default color for horizontal lines (see plotinfo.plothlines)
      self.hlinescolor = "0.66"  # shade of gray
      # Default style for horizontal lines
      self.hlinesstyle = "--"
      # Default width for horizontal lines
      self.hlineswidth = 1.0
  
      # Default color scheme: Tableau 10
      self.lcolors = tableau10
  
      # strftime Format string for the display of ticks on the x axis
      self.fmt_x_ticks = "%Y-%m-%d %H:%M"
  
      # strftime Format string for the display of data points values
      self.fmt_x_data = None
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
label_desc: Use image node_id 1 to create a new PlotScheme object from inherited base classes: object with example: obj = PlotScheme()