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: Calculate and set means from `x` and `z`
  
  Parameters
  ----------
  x: array of shape(n,3)
     should be on the unit sphere
  z: array of shape(self.k)
docstr_tok: ["Calculate","and","set","means","from","`","x","`","and","`","z","`","Parameters","--","--","--","--","--","x",":","array","of","shape","(","n,3",")","should","be","on","the","unit","sphere","z",":","array","of","shape","(","self.k",")"]
code: def estimate_means(self, x, z):
      """Calculate and set means from `x` and `z`
  
      Parameters
      ----------
      x: array of shape(n,3)
         should be on the unit sphere
      z: array of shape(self.k)
      """
      m = np.dot(z.T, x)
      self.means = (m.T / np.sqrt(np.sum(m**2, 1))).T
  
imports: from warnings import warn
  import numpy
label_desc: Use image node_id 9 for calling the VonMisesMixture obj's underlying member method code with example usage: obj.estimate_means(x, z) without return types