


import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
   # Create universe of discourse in Python using linspace ()
   lowerCamelCase__							:						List[str]							     =   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).
   lowerCamelCase__							:						List[str]							     =   [0, 2_5, 5_0]
   lowerCamelCase__							:						Any							     =   [2_5, 5_0, 7_5]
   lowerCamelCase__							:						Optional[int]							     =   fuzz.membership.trimf(X, abca)
   lowerCamelCase__							:						Optional[Any]							     =   fuzz.membership.trimf(X, abca)

   # Compute the different operations using inbuilt functions.
   lowerCamelCase__							:						List[Any]							     =   np.ones(7_5)
   lowerCamelCase__							:						Dict							     =   np.zeros((7_5,))
   # 1. Union = max(µA(x), µB(x))
   lowerCamelCase__							:						List[Any]							     =   fuzz.fuzzy_or(X, young, X, middle_aged)[1]
   # 2. Intersection = min(µA(x), µB(x))
   lowerCamelCase__							:						int							     =   fuzz.fuzzy_and(X, young, X, middle_aged)[1]
   # 3. Complement (A) = (1- min(µA(x))
   lowerCamelCase__							:						Dict							     =   fuzz.fuzzy_not(young)
   # 4. Difference (A/B) = min(µA(x),(1- µB(x)))
   lowerCamelCase__							:						str							     =   fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
   # 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
   lowerCamelCase__							:						str							     =   young + middle_aged - (young * middle_aged)
   # 6. Algebraic Product = (µA(x) * µB(x))
   lowerCamelCase__							:						Union[str, Any]							     =   young * middle_aged
   # 7. Bounded Sum = min[1,(µA(x), µB(x))]
   lowerCamelCase__							:						List[Any]							     =   fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
   # 8. Bounded difference = min[0,(µA(x), µB(x))]
   lowerCamelCase__							:						Any							     =   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()









'''simple docstring'''



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
SCREAMING_SNAKE_CASE							=						{
    'E': 12.70,
    'T': 9.06,
    'A': 8.17,
    'O': 7.51,
    'I': 6.97,
    'N': 6.75,
    'S': 6.33,
    'H': 6.09,
    'R': 5.99,
    'D': 4.25,
    'L': 4.03,
    'C': 2.78,
    'U': 2.76,
    'M': 2.41,
    'W': 2.36,
    'F': 2.23,
    'G': 2.02,
    'Y': 1.97,
    'P': 1.93,
    'B': 1.29,
    'V': 0.98,
    'K': 0.77,
    'J': 0.15,
    'X': 0.15,
    'Q': 0.10,
    'Z': 0.07,
}
SCREAMING_SNAKE_CASE							=						'ETAOINSHRDLCUMWFGYPBVKJXQZ'
SCREAMING_SNAKE_CASE							=						'ABCDEFGHIJKLMNOPQRSTUVWXYZ'


def 				lowercase_					(     __A			:							str      )							->   dict[str, int]:



 """simple docstring"""




 lowercase       : List[str]						={letter: 0 for letter in string.ascii_uppercase}
 for letter in message.upper():
  if letter in LETTERS:
   letter_count[letter] += 1

 return letter_count


def 				lowercase_					(     __A			:							tuple      )							->   str:



 """simple docstring"""




 return x[0]


def 				lowercase_					(     __A			:							str      )							->   str:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_letter_count(__A      )
 lowercase       : dict[int, list[str]]						={
     freq: [] for letter, freq in letter_to_freq.items()
 }
 for letter in LETTERS:
  freq_to_letter[letter_to_freq[letter]].append(__A      )

 lowercase       : dict[int, str]						={}

 for freq in freq_to_letter:
  freq_to_letter[freq].sort(key=ETAOIN.find       ,   reverse=__A      )
  lowercase       : Optional[int]						=''''''.join(freq_to_letter[freq]      )

 lowercase       : str						=list(freq_to_letter_str.items()      )
 freq_pairs.sort(key=__A       ,   reverse=__A      )

 lowercase       : list[str]						=[freq_pair[1] for freq_pair in freq_pairs]

 return "".join(__A      )


def 				lowercase_					(     __A			:							str      )							->   int:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_frequency_order(__A      )
 lowercase       : Union[str, Any]						=0
 for common_letter in ETAOIN[:6]:
  if common_letter in freq_order[:6]:
   match_score += 1

 for uncommon_letter in ETAOIN[-6:]:
  if uncommon_letter in freq_order[-6:]:
   match_score += 1

 return match_score


if __name__ == "__main__":
      import doctest

      doctest.testmod()



