parameters: (self, codes)
return_statement: return np.bitwise_or.reduce(codes, axis=1)
docstring: Transform combination(s) of uint64 in one Python integer (each), in a
          strictly monotonic way (i.e. respecting the lexicographic order of
          integer combinations): see BaseMultiIndexCodesEngine documentation.
  
          Parameters
          ----------
          codes : 1- or 2-dimensional array of dtype uint64
              Combinations of integers (one per row)
  
          Returns
          -------
          int, or 1-dimensional array of dtype object
              Integer(s) representing one combination (each).
docstring_summary: Transform combination(s) of uint64 in one Python integer (each), in a
          strictly monotonic way (i.e. respecting the lexicographic order of
          integer combinations): see BaseMultiIndexCodesEngine documentation.
docstring_tokens: Transform combination ( s ) of uint64 in one Python integer ( each ) in a strictly monotonic way ( i . e . respecting the lexicographic order of integer combinations ) : see BaseMultiIndexCodesEngine documentation .
function: def _codes_to_ints(self, codes):
          """
          Transform combination(s) of uint64 in one Python integer (each), in a
          strictly monotonic way (i.e. respecting the lexicographic order of
          integer combinations): see BaseMultiIndexCodesEngine documentation.
  
          Parameters
          ----------
          codes : 1- or 2-dimensional array of dtype uint64
              Combinations of integers (one per row)
  
          Returns
          -------
          int, or 1-dimensional array of dtype object
              Integer(s) representing one combination (each).
          """
  
          # Shift the representation of each level by the pre-calculated number
          # of bits. Since this can overflow uint64, first make sure we are
          # working with Python integers:
          codes = codes.astype("object") << self.offsets
  
          # Now sum and OR are in fact interchangeable. This is a simple
          # composition of the (disjunct) significant bits of each level (i.e.
          # each column in "codes") in a single positive integer (per row):
          if codes.ndim == 1:
              # Single key
              return np.bitwise_or.reduce(codes)
  
          # Multiple keys
          return np.bitwise_or.reduce(codes, axis=1)
function_tokens: def _codes_to_ints ( self , codes ) : # Shift the representation of each level by the pre-calculated number # of bits. Since this can overflow uint64, first make sure we are # working with Python integers: codes = codes . astype ( "object" ) << self . offsets # Now sum and OR are in fact interchangeable. This is a simple # composition of the (disjunct) significant bits of each level (i.e. # each column in "codes") in a single positive integer (per row): if codes . ndim == 1 : # Single key return np . bitwise_or . reduce ( codes ) # Multiple keys return np . bitwise_or . reduce ( codes , axis = 1 )