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: Initialize Von Mises mixture
  
  Parameters
  ----------
  k: int,
     number of components
  precision: float,
             the fixed precision parameter
  means: array of shape(self.k, 3), optional
         input component centers
  weights: array of shape(self.k), optional
           input components weights
  null_class: bool, optional
              Inclusion of a null class within the model
              (related to k=0)
  
  fixme
  -----
  consistency checks
docstr_tok: ["Initialize","Von","Mises","mixture","Parameters","--","--","--","--","--","k",":","int",",","number","of","components","precision",":","float",",","the","fixed","precision","parameter","means",":","array","of","shape","(","self.k",",","3",")",",","optional","input","component","centers","weights",":","array","of","shape","(","self.k",")",",","optional","input","components","weights","null_class",":","bool",",","optional","Inclusion","of","a","null","class","within","the","model","(","related","to","k=0",")","fixme","--","--","-","consistency","checks"]
code: def __init__(
      self, k, precision, means=None, weights=None, null_class=False
  ):
      """Initialize Von Mises mixture
  
      Parameters
      ----------
      k: int,
         number of components
      precision: float,
                 the fixed precision parameter
      means: array of shape(self.k, 3), optional
             input component centers
      weights: array of shape(self.k), optional
               input components weights
      null_class: bool, optional
                  Inclusion of a null class within the model
                  (related to k=0)
  
      fixme
      -----
      consistency checks
      """
      self.k = k
      self.dim = 2
      self.em_dim = 3
      self.means = means
      self.precision = precision
      self.weights = weights
      self.null_class = null_class
  
imports: from warnings import warn
  import numpy
label_desc: Use image node_id 1 to create a new VonMisesMixture object  with example: obj = VonMisesMixture(k, precision, means, weights, null_class)