class_docstr: Metropolis-Hastings optimized for binary variables
  
  Parameters
  ----------
  scaling : scalar or array
      Initial scale factor for proposal. Defaults to 1.
class_docstr_tok: ["Metropolis-Hastings","optimized","for","binary","variables","Parameters","--","--","--","--","--","scaling",":","scalar","or","array","Initial","scale","factor","for","proposal",".","Defaults","to","1","."]
code: def __init__(self, model, scaling=1.0):
      self.model = model
      self.scaling = scaling
  
      super(BinaryMetropolis, self).__init__()
  
imports: from __future__ import division
  import scipy.linalg
  import numpy
  import numpy.random
label_desc: Use image node_id 1 to create a new BinaryMetropolis object from inherited base classes: object with example: obj = BinaryMetropolis(model, scaling)