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: Return log weighted density
  
  Parameters
  ----------
  x: array of shape(n,3)
     should be on the unit sphere
  
  Returns
  -------
  log_like: array of shape(n, self.k)
docstr_tok: ["Return","log","weighted","density","Parameters","--","--","--","--","--","x",":","array","of","shape","(","n,3",")","should","be","on","the","unit","sphere","Returns","--","--","--","-","log_like",":","array","of","shape","(","n",",","self.k",")"]
code: def log_weighted_density(self, x):
      """Return log weighted density
  
      Parameters
      ----------
      x: array of shape(n,3)
         should be on the unit sphere
  
      Returns
      -------
      log_like: array of shape(n, self.k)
      """
      return self.log_density_per_component(x) + np.log(self.weights)
  
imports: from warnings import warn
  import numpy
label_desc: Use image node_id 5 for calling the VonMisesMixture obj's underlying member method code with example usage: obj.log_weighted_density(x) and returns: unknown