class_docstr: Sampling distribution for mystic optimizers
      
class_docstr_tok: ["Sampling","distribution","for","mystic","optimizers"]
docstr: generate a sample of given size (tuple) from the distribution
docstr_tok: ["generate","a","sample","of","given","size","(","tuple",")","from","the","distribution"]
code: def __call__(self, size=None):
      """generate a sample of given size (tuple) from the distribution"""
      return self.norm * self.rvs(size)
  
file_path: mystic/mystic/math/__init__.py
imports: from .poly import polyeval, poly1d
  from .grid import gridpts, samplepts, fillpts
  from .approx import almostEqual, tolerance
  from .approx import approx_equal
  from .None import discrete
  from .None import distance
label_desc: Use image node_id 2 for calling the Distribution obj's underlying member method code with example usage: obj.__call__(size) and returns: unknown