



'''simple docstring'''



from __future__ import annotations

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

a__    :      Tuple      				=      (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
a__    :      int      				=      [ord(letter) for letter in string.ascii_lowercase]
a__    :      List[str]      				=      {ord(char) for char in VALID_CHARS}

a__    :      int      				=      ['the', 'be', 'to', 'of', 'and', 'in', 'that', 'have']







def _lowercase (	__A				,__A							):



 '''simple docstring'''



 __UpperCamelCase					   =	""""""
 __UpperCamelCase					   =	42
 __UpperCamelCase					   =	42
 __UpperCamelCase					   =	42

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

 return decoded







def _lowercase (	__A							):



 '''simple docstring'''



 __UpperCamelCase					   =	[]
 for key in product(__UpperCamelCase				,repeat=3							):
  __UpperCamelCase					   =	try_key(__UpperCamelCase				,__UpperCamelCase							)
  if encoded is not None:
   possibles.append(__UpperCamelCase							)
 return possibles







def _lowercase (	__A				,__A							):



 '''simple docstring'''



 return [possible for possible in possibles if common_word in possible.lower()]







def _lowercase (	__A = "p059_cipher.txt"							):



 '''simple docstring'''



 __UpperCamelCase					   =	42
 __UpperCamelCase					   =	42
 __UpperCamelCase					   =	42
 __UpperCamelCase					   =	42
 __UpperCamelCase					   =	Path(__UpperCamelCase							).parent.joinpath(__UpperCamelCase							).read_text(encoding="""utf-8"""							)

 __UpperCamelCase					   =	[int(__UpperCamelCase							) for number in data.strip().split(""","""							)]

 __UpperCamelCase					   =	filter_valid_chars(__UpperCamelCase							)
 for common_word in COMMON_WORDS:
  __UpperCamelCase					   =	filter_common_word(__UpperCamelCase				,__UpperCamelCase							)
  if len(__UpperCamelCase							) == 1:
   break

 __UpperCamelCase					   =	possibles[0]
 return sum(ord(__UpperCamelCase							) 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=7_5, num=7_5, endpoint=True, retstep=False)

							# Create two fuzzy sets by defining any membership function
							# (trapmf(), gbellmf(), gaussmf(), etc).
							SCREAMING_SNAKE_CASE__   			=   [0, 2_5, 5_0]
							SCREAMING_SNAKE_CASE__   			=   [2_5, 5_0, 7_5]
							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(7_5)
							SCREAMING_SNAKE_CASE__   			=   np.zeros((7_5,))
							# 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, 1_0)
							plt.plot(X, bdd_difference)
							plt.title('''bdd_difference''')
							plt.grid(True)

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




