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: Compute the per-component density of the data
  
  Parameters
  ----------
  x: array of shape(n,3)
     should be on the unit sphere
  
  Returns
  -------
  like: array of shape(n, self.k), with non-neagtive values
        the density
docstr_tok: ["Compute","the","per-component","density","of","the","data","Parameters","--","--","--","--","--","x",":","array","of","shape","(","n,3",")","should","be","on","the","unit","sphere","Returns","--","--","--","-","like",":","array","of","shape","(","n",",","self.k",")",",","with","non-neagtive","values","the","density"]
code: def density_per_component(self, x):
      """
      Compute the per-component density of the data
  
      Parameters
      ----------
      x: array of shape(n,3)
         should be on the unit sphere
  
      Returns
      -------
      like: array of shape(n, self.k), with non-neagtive values
            the density
      """
      return np.exp(self.log_density_per_component(x))
  
imports: from warnings import warn
  import numpy
label_desc: Use image node_id 3 for calling the VonMisesMixture obj's underlying member method code with example usage: obj.density_per_component(x) and returns: np