class_docstr: Represents a basic subset object.
  
  Explanation
  ===========
  
  We generate subsets using essentially two techniques,
  binary enumeration and lexicographic enumeration.
  The Subset class takes two arguments, the first one
  describes the initial subset to consider and the second
  describes the superset.
  
  Examples
  ========
  
  >>> from sympy.combinatorics import Subset
  >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd'])
  >>> a.next_binary().subset
  ['b']
  >>> a.prev_binary().subset
  ['c']
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docstr: Computes the binary ordered rank.
  
  Examples
  ========
  
  >>> from sympy.combinatorics import Subset
  >>> a = Subset([], ['a','b','c','d'])
  >>> a.rank_binary
  0
  >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd'])
  >>> a.rank_binary
  3
  
  See Also
  ========
  
  iterate_binary, unrank_binary
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code: def rank_binary(self):
      """
      Computes the binary ordered rank.
  
      Examples
      ========
  
      >>> from sympy.combinatorics import Subset
      >>> a = Subset([], ['a','b','c','d'])
      >>> a.rank_binary
      0
      >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd'])
      >>> a.rank_binary
      3
  
      See Also
      ========
  
      iterate_binary, unrank_binary
      """
      if self._rank_binary is None:
          self._rank_binary = int(
              "".join(
                  Subset.bitlist_from_subset(self.subset, self.superset)
              ),
              2,
          )
      return self._rank_binary
  
imports: from itertools import combinations
  from sympy.combinatorics.graycode import GrayCode
label_desc: Use image node_id 11 for calling the Subset obj's underlying member method code with example usage: obj.rank_binary() and returns: self