class_docstr: Gotoh score
  Gotoh's algorithm is essentially Needleman-Wunsch with affine gap
  penalties:
  https://www.cs.umd.edu/class/spring2003/cmsc838t/papers/gotoh1982.pdf
class_docstr_tok: ["Gotoh","score","Gotoh","'s","algorithm","is","essentially","Needleman-Wunsch","with","affine","gap","penalties",":","https",":","\/\/www.cs.umd.edu\/class\/spring2003\/cmsc838t\/papers\/gotoh1982.pdf"]
code: def maximum(self, *sequences: Sequence[object]) -> int:
      return min(map(len, sequences))
  
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 Gotoh obj's underlying member method code with example usage: obj.maximum() and returns: min