class_docstr: Model for Von Mises mixture distribution with fixed variance
  on a two-dimensional sphere
class_docstr_tok: ["Model","for","Von","Mises","mixture","distribution","with","fixed","variance","on","a","two-dimensional","sphere"]
docstr: Visualization utility
  
  Parameters
  ----------
  x: array of shape (n, 3)
     should be on the unit sphere
  
  Notes
  -----
  
  Uses ``matplotlib``.
docstr_tok: ["Visualization","utility","Parameters","--","--","--","--","--","x",":","array","of","shape","(","n",",","3",")","should","be","on","the","unit","sphere","Notes","--","--","-","Uses","``","matplotlib","``","."]
code: def show(self, x):
      """Visualization utility
  
      Parameters
      ----------
      x: array of shape (n, 3)
         should be on the unit sphere
  
      Notes
      -----
  
      Uses ``matplotlib``.
      """
      # label the data
      z = np.argmax(self.responsibilities(x), 1)
      import matplotlib.pyplot as plt
      import mpl_toolkits.mplot3d.axes3d as p3
  
      fig = plt.figure()
      ax = p3.Axes3D(fig)
      colors = (
          ["b", "g", "r", "c", "m", "y", "k", "w"]
          * (1 + (1 + self.k) // 8)
      )[: self.k + 1]
      if (self.null_class) and (z == 0).any():
          ax.plot3D(
              x[z == 0, 0],
              x[z == 0, 1],
              x[z == 0, 2],
              ".",
              color=colors[0],
          )
      for k in range(self.k):
          if self.null_class:
              if np.sum(z == (k + 1)) == 0:
                  continue
              uk = z == (k + 1)
              ax.plot3D(
                  x[uk, 0], x[uk, 1], x[uk, 2], ".", color=colors[k + 1]
              )
              ax.plot3D(
                  [self.means[k, 0]],
                  [self.means[k, 1]],
                  [self.means[k, 2]],
                  "o",
                  color=colors[k + 1],
              )
          else:
              if np.sum(z == k) == 0:
                  continue
              ax.plot3D(
                  x[z == k, 0],
                  x[z == k, 1],
                  x[z == k, 2],
                  ".",
                  color=colors[k],
              )
              ax.plot3D(
                  [self.means[k, 0]],
                  [self.means[k, 1]],
                  [self.means[k, 2]],
                  "o",
                  color=colors[k],
              )
      plt.show()
  
imports: from warnings import warn
  import numpy
label_desc: Use image node_id 11 for calling the VonMisesMixture obj's underlying member method code with example usage: obj.show(x) without return types