class_docstr: !
  @brief Visualizer of CLIQUE algorithm's results.
  @details CLIQUE visualizer provides visualization services that are specific for CLIQUE algorithm, for example,
            to display grid and its density.
class_docstr_tok: ["!","@","brief","Visualizer","of","CLIQUE","algorithm","'s","results",".","@","details","CLIQUE","visualizer","provides","visualization","services","that","are","specific","for","CLIQUE","algorithm",",","for","example",",","to","display","grid","and","its","density","."]
code: def __draw_cell(ax, pair, cell, density_scale):
      (
          max_corner,
          min_corner,
      ) = clique_visualizer.__get_rectangle_description(cell, pair)
  
      belong_cluster = len(cell.points) > 0
  
      if density_scale != 0.0:
          density_scale = (
              clique_visualizer.__maximum_density_alpha
              * len(cell.points)
              / density_scale
          )
  
      face_color = matplotlib.colors.to_rgba(
          "blue", alpha=density_scale
      )
      edge_color = matplotlib.colors.to_rgba("black", alpha=1.0)
  
      rect = patches.Rectangle(
          min_corner,
          max_corner[0] - min_corner[0],
          max_corner[1] - min_corner[1],
          fill=belong_cluster,
          facecolor=face_color,
          edgecolor=edge_color,
          linewidth=0.5,
      )
      ax.add_patch(rect)
  
imports: import itertools
  from pyclustering.cluster import cluster_visualizer
  from pyclustering.cluster.encoder import type_encoding
  from pyclustering.core.wrapper import ccore_library
  import pyclustering.core.clique_wrapper
  import matplotlib
  import matplotlib.gridspec
  import matplotlib.pyplot
  import matplotlib.patches
label_desc: Use image node_id 5 for calling the clique_visualizer obj's underlying member method code with example usage: obj.__draw_cell(ax, pair, cell, density_scale) without return types