code: def tukeyplot(results, dim=None, yticklabels=None):
      npairs = len(results)
  
      fig = plt.figure()
      fsp = fig.add_subplot(111)
      fsp.axis([-50, 50, 0.5, 10.5])
      fsp.set_title("95 % family-wise confidence level")
      fsp.title.set_y(1.025)
      fsp.set_yticks(np.arange(1, 11))
      fsp.set_yticklabels(
          [
              "V-T",
              "V-S",
              "T-S",
              "V-P",
              "T-P",
              "S-P",
              "V-M",
              "T-M",
              "S-M",
              "P-M",
          ]
      )
      # fsp.yaxis.set_major_locator(mticker.MaxNLocator(npairs))
      fsp.yaxis.grid(True, linestyle="-", color="gray")
      fsp.set_xlabel("Differences in mean levels of Var", labelpad=8)
      fsp.xaxis.tick_bottom()
      fsp.yaxis.tick_left()
  
      xticklines = fsp.get_xticklines()
      for xtickline in xticklines:
          xtickline.set_marker(lines.TICKDOWN)
          xtickline.set_markersize(10)
  
      xlabels = fsp.get_xticklabels()
      for xlabel in xlabels:
          xlabel.set_y(-0.04)
  
      yticklines = fsp.get_yticklines()
      for ytickline in yticklines:
          ytickline.set_marker(lines.TICKLEFT)
          ytickline.set_markersize(10)
  
      ylabels = fsp.get_yticklabels()
      for ylabel in ylabels:
          ylabel.set_x(-0.04)
  
      for pair in range(npairs):
          data = 0.5 + results[pair] / 100.0
          # fsp.axhline(y=npairs-pair, xmin=data[0], xmax=data[1], linewidth=1.25,
          fsp.axhline(
              y=npairs - pair,
              xmin=data.mean(),
              xmax=data[1],
              linewidth=1.25,
              color="blue",
              marker="|",
              markevery=1,
          )
  
          fsp.axhline(
              y=npairs - pair,
              xmin=data[0],
              xmax=data.mean(),
              linewidth=1.25,
              color="blue",
              marker="|",
              markevery=1,
          )
  
      # for pair in range(npairs):
      #    data = .5+results[pair]/100.
      #    data = results[pair]
      #    data = np.r_[data[0],data.mean(),data[1]]
      #    l = plt.plot(data, [npairs-pair]*len(data), color='black',
      #                linewidth=.5, marker="|", markevery=1)
  
      fsp.axvline(x=0, linestyle="--", color="black")
  
      fig.subplots_adjust(bottom=0.125)
  
imports: import matplotlib.lines
  import matplotlib.pyplot
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: tukeyplot(results, dim, yticklabels) without return types