


'''simple docstring'''



import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
						# Create universe of discourse in Python using linspace ()
						__lowercase     :						int	=     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).
						__lowercase     :						Any	=     [0, 25, 50]
						__lowercase     :						int	=     [25, 50, 75]
						__lowercase     :						List[str]	=     fuzz.membership.trimf(X, abca)
						__lowercase     :						Any	=     fuzz.membership.trimf(X, abca)

						# Compute the different operations using inbuilt functions.
						__lowercase     :						List[Any]	=     np.ones(75)
						__lowercase     :						Any	=     np.zeros((75,))
						# 1. Union = max(µA(x), µB(x))
						__lowercase     :						int	=     fuzz.fuzzy_or(X, young, X, middle_aged)[1]
						# 2. Intersection = min(µA(x), µB(x))
						__lowercase     :						int	=     fuzz.fuzzy_and(X, young, X, middle_aged)[1]
						# 3. Complement (A) = (1- min(µA(x))
						__lowercase     :						str	=     fuzz.fuzzy_not(young)
						# 4. Difference (A/B) = min(µA(x),(1- µB(x)))
						__lowercase     :						List[Any]	=     fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
						# 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
						__lowercase     :						Optional[Any]	=     young + middle_aged - (young * middle_aged)
						# 6. Algebraic Product = (µA(x) * µB(x))
						__lowercase     :						str	=     young * middle_aged
						# 7. Bounded Sum = min[1,(µA(x), µB(x))]
						__lowercase     :						Optional[Any]	=     fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
						# 8. Bounded difference = min[0,(µA(x), µB(x))]
						__lowercase     :						Union[str, 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, 10)
						plt.plot(X, bdd_difference)
						plt.title('bdd_difference')
						plt.grid(True)

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







'''simple docstring'''



import os






def   lowerCamelCase							():
					with open(os.path.dirname(_SCREAMING_SNAKE_CASE       ) + '/p022_names.txt'       ) as file:
										__a      :	List[Any]    =  str(file.readlines()[0]       )
										__a      :	str    =  names.replace('"'						,				''       ).split(','       )

					names.sort()

					__a      :	Union[str, Any]    =  0
					__a      :	Tuple    =  0

					for i, name in enumerate(_SCREAMING_SNAKE_CASE       ):
										for letter in name:
															name_score += ord(_SCREAMING_SNAKE_CASE       ) - 64

										total_score += (i + 1) * name_score
										__a      :	Any    =  0
					return total_score


if __name__ == "__main__":
	print(solution())



