class_docstr: Tanimoto distance
  This is identical to the Jaccard similarity coefficient
  and the Tversky index for alpha=1 and beta=1.
class_docstr_tok: ["Tanimoto","distance","This","is","identical","to","the","Jaccard","similarity","coefficient","and","the","Tversky","index","for","alpha=1","and","beta=1","."]
code: def __call__(self, *sequences: Sequence) -> float:
      result = super().__call__(*sequences)
      if result == 0:
          return float("-inf")
      else:
          return log(result, 2)
  
imports: from __future__ import annotations
  from functools import reduce
  from itertools import islice, permutations, repeat
  from math import log
  from typing import Sequence
  from .base import Base, BaseSimilarity
  from .edit_based import DamerauLevenshtein
label_desc: Use image node_id 1 for calling the Tanimoto obj's underlying member method code with example usage: obj.__call__() and returns: float, log