class_docstr: !
  @brief Common cluster visualizer for 1-, 2- and 3-dimensional data.
  @details `cluster_visualizer_multidim` visualizer can be used to display clusters in N-dimensional data.
  
  The general difference between `cluster_visualizer` and `cluster_visualizer_multidim` is a way of representation
  of 3-dimensional data. In case of `cluster_visualizer` 3-dimensional data is displayed in 3-dimensional plot with
  `x0`, `x1` and `x2` axis. In case of `cluster_visualizer_multidim` it displayed on three 2-dimensional plots:
  `(x0, x1)`, `(x0, x2)` and `(x1, x2)`.
  
  There is an example where sample `Atom` is used for clustering and displayed by `cluster_visualizer`:
  @code
      from pyclustering.utils import read_sample
      from pyclustering.samples.definitions import FCPS_SAMPLES
      from pyclustering.cluster import cluster_visualizer
      from pyclustering.cluster.dbscan import dbscan
  
      sample = read_sample(FCPS_SAMPLES.SAMPLE_ATOM)
      clusters = dbscan(sample, 15, 3).process().get_clusters()
  
      visualizer = cluster_visualizer()
      visualizer.append_clusters(clusters, sample)
      visualizer.show()
  @endcode
  
  Visualized clustering results of `Atom` data:
  @image html dbscan_atom_visualizer.png "Fig. 1. DBSCAN clustering results (3-dimensional data 'Atom')."
  
  @see cluster_visualizer_multidim
docstr: !
  @brief Set title for specified canvas.
  
  @param[in] text (string): Title for the canvas.
  @param[in] canvas (uint): Index of the canvas where title should be displayed.
docstr_tok: ["!","@","brief","Set","title","for","specified","canvas",".","@","param","[","in","]","text","(","string",")",":","Title","for","the","canvas",".","@","param","[","in","]","canvas","(","uint",")",":","Index","of","the","canvas","where","title","should","be","displayed","."]
code: def set_canvas_title(self, text, canvas=0):
      """!
      @brief Set title for specified canvas.
  
      @param[in] text (string): Title for the canvas.
      @param[in] canvas (uint): Index of the canvas where title should be displayed.
  
      """
  
      if canvas > self.__number_canvases:
          raise ValueError(
              "Canvas with index '%d' does not exists (total amount of canvases: '%d')."
              % canvas,
              self.__number_canvases,
          )
  
      self.__canvas_titles[canvas] = text
  
imports: import itertools
  import math
  import matplotlib.pyplot
  import matplotlib.gridspec
  from mpl_toolkits.mplot3d import Axes3D
  from pyclustering.utils.color import color
label_desc: Use image node_id 5 for calling the cluster_visualizer obj's underlying member method code with example usage: obj.set_canvas_title(text, canvas) without return types