






from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

SCREAMING_SNAKE_CASE 							=						(
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE 							=						[ord(letter) for letter in string.ascii_lowercase]
SCREAMING_SNAKE_CASE 							=						{ord(char) for char in VALID_CHARS}

SCREAMING_SNAKE_CASE 							=						['the', 'be', 'to', 'of', 'and', 'in', 'that', 'have']

def      _lowerCamelCase	(						__A    :							Tuple		,		__A    :							int )      ->					str | None:
    _UpperCAmelCase				:      str			  =				""
    _UpperCAmelCase				:      int
    _UpperCAmelCase				:      int
    _UpperCAmelCase				:      int

    for keychar, cipherchar in zip(cycle(SCREAMING_SNAKE_CASE_ )		,		SCREAMING_SNAKE_CASE_ ):
        _UpperCAmelCase				:      Dict			  =				cipherchar ^ keychar
        if decodedchar not in VALID_INTS:
            return None
        decoded += chr(SCREAMING_SNAKE_CASE_ )

    return decoded

def      _lowerCamelCase	(						__A    :							Tuple )      ->					list[str]:
    _UpperCAmelCase				:      list[str]			  =				[]
    for key in product(SCREAMING_SNAKE_CASE_		,		repeat=3 ):
        _UpperCAmelCase				:      Tuple			  =				try_key(SCREAMING_SNAKE_CASE_		,		SCREAMING_SNAKE_CASE_ )
        if encoded is not None:
            possibles.append(SCREAMING_SNAKE_CASE_ )
    return possibles

def      _lowerCamelCase	(						__A    :							Optional[Any]		,		__A    :							Dict )      ->					list[str]:
    return [possible for possible in possibles if common_word in possible.lower()]

def      _lowerCamelCase	(						__A    :							int = "p059_cipher.txt" )      ->					int:
    _UpperCAmelCase				:      list[int]
    _UpperCAmelCase				:      list[str]
    _UpperCAmelCase				:      str
    _UpperCAmelCase				:      str
    _UpperCAmelCase				:      str			  =				Path(SCREAMING_SNAKE_CASE_ ).parent.joinpath(SCREAMING_SNAKE_CASE_ ).read_text(encoding='''utf-8''' )

    _UpperCAmelCase				:      int			  =				[int(SCREAMING_SNAKE_CASE_ ) for number in data.strip().split(''',''' )]

    _UpperCAmelCase				:      str			  =				filter_valid_chars(SCREAMING_SNAKE_CASE_ )
    for common_word in COMMON_WORDS:
        _UpperCAmelCase				:      Union[str, Any]			  =				filter_common_word(SCREAMING_SNAKE_CASE_		,		SCREAMING_SNAKE_CASE_ )
        if len(SCREAMING_SNAKE_CASE_ ) == 1:
            break

    _UpperCAmelCase				:      List[str]			  =				possibles[0]
    return sum(ord(SCREAMING_SNAKE_CASE_ ) for char in decoded_text )


if __name__ == "__main__":
 print(F'{solution() = }')












import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
  # Create universe of discourse in Python using linspace ()
  SCREAMING_SNAKE_CASE 							=						np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)

  # Create two fuzzy sets by defining any membership function
  # (trapmf(), gbellmf(), gaussmf(), etc).
  SCREAMING_SNAKE_CASE 							=						[0, 25, 50]
  SCREAMING_SNAKE_CASE 							=						[25, 50, 75]
  SCREAMING_SNAKE_CASE 							=						fuzz.membership.trimf(X, abca)
  SCREAMING_SNAKE_CASE 							=						fuzz.membership.trimf(X, abca)

  # Compute the different operations using inbuilt functions.
  SCREAMING_SNAKE_CASE 							=						np.ones(75)
  SCREAMING_SNAKE_CASE 							=						np.zeros((75,))
  # 1. Union = max(µA(x), µB(x))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_or(X, young, X, middle_aged)[1]
  # 2. Intersection = min(µA(x), µB(x))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_and(X, young, X, middle_aged)[1]
  # 3. Complement (A) = (1- min(µA(x))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_not(young)
  # 4. Difference (A/B) = min(µA(x),(1- µB(x)))
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
  # 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
  SCREAMING_SNAKE_CASE 							=						young + middle_aged - (young * middle_aged)
  # 6. Algebraic Product = (µA(x) * µB(x))
  SCREAMING_SNAKE_CASE 							=						young * middle_aged
  # 7. Bounded Sum = min[1,(µA(x), µB(x))]
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
  # 8. Bounded difference = min[0,(µA(x), µB(x))]
  SCREAMING_SNAKE_CASE 							=						fuzz.fuzzy_or(X, zero, X, young - middle_aged)[1]

  # max-min composition
  # max-product composition

  # Plot each set A, set B and each operation result using plot() and subplot().
  from matplotlib import pyplot as plt

  plt.figure()

  plt.subplot(4, 3, 1)
  plt.plot(X, young)
  plt.title('Young')
  plt.grid(True)

  plt.subplot(4, 3, 2)
  plt.plot(X, middle_aged)
  plt.title('Middle aged')
  plt.grid(True)

  plt.subplot(4, 3, 3)
  plt.plot(X, union)
  plt.title('union')
  plt.grid(True)

  plt.subplot(4, 3, 4)
  plt.plot(X, intersection)
  plt.title('intersection')
  plt.grid(True)

  plt.subplot(4, 3, 5)
  plt.plot(X, complement_a)
  plt.title('complement_a')
  plt.grid(True)

  plt.subplot(4, 3, 6)
  plt.plot(X, difference)
  plt.title('difference a/b')
  plt.grid(True)

  plt.subplot(4, 3, 7)
  plt.plot(X, alg_sum)
  plt.title('alg_sum')
  plt.grid(True)

  plt.subplot(4, 3, 8)
  plt.plot(X, alg_product)
  plt.title('alg_product')
  plt.grid(True)

  plt.subplot(4, 3, 9)
  plt.plot(X, bdd_sum)
  plt.title('bdd_sum')
  plt.grid(True)

  plt.subplot(4, 3, 10)
  plt.plot(X, bdd_difference)
  plt.title('bdd_difference')
  plt.grid(True)

  plt.subplots_adjust(hspace=0.5)
  plt.show()




