class_docstr: Compute the Hamming distance between the two or more sequences.
  The Hamming distance is the number of differing items in ordered sequences.
  
  http://www.sial.iias.spb.su/files/386-386-1-PB.pdf
  https://github.com/Yomguithereal/talisman/blob/master/src/metrics/mlipns.js
class_docstr_tok: ["Compute","the","Hamming","distance","between","the","two","or","more","sequences",".","The","Hamming","distance","is","the","number","of","differing","items","in","ordered","sequences",".","http",":","\/\/www.sial.iias.spb.su\/files\/386-386-1-PB.pdf","https",":","\/\/github.com\/Yomguithereal\/talisman\/blob\/master\/src\/metrics\/mlipns.js"]
code: def __call__(self, *sequences: Sequence[object]) -> float:
      sequences = self._get_sequences(*sequences)
  
      result = self.quick_answer(*sequences)
      if result is not None:
          return result
  
      mismatches = 0
      ham = Hamming()(*sequences)
      maxlen = max(map(len, sequences))
      while all(sequences) and mismatches <= self.maxmismatches:
          if not maxlen:
              return 1
          if 1 - (maxlen - ham) / maxlen <= self.threshold:
              return 1
          mismatches += 1
          ham -= 1
          maxlen -= 1
  
      if not maxlen:
          return 1
      return 0
  
imports: from __future__ import annotations
  from collections import defaultdict
  from itertools import zip_longest
  from typing import Any, Sequence, TypeVar
  from .base import Base, BaseSimilarity
  from .types import SimFunc, TestFunc
label_desc: Use image node_id 3 for calling the MLIPNS obj's underlying member method code with example usage: obj.__call__() and returns: int, result, int, int, int