
import numpy as np
import skfuzzy as fuzz

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

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




def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			List[Any]:







 """simple docstring"""


 if b == 0:
  return 1
 if (b % 2) == 0:
  return actual_power(__snake_case     ,						int(b / 2						)						) * actual_power(__snake_case     ,						int(b / 2						)						)
 else:
  return a * actual_power(__snake_case     ,						int(b / 2						)						) * actual_power(__snake_case     ,						int(b / 2						)						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			float:







 """simple docstring"""


 if b < 0:
  return 1 / actual_power(__snake_case     ,						__snake_case						)
 return actual_power(__snake_case     ,						__snake_case						)


if __name__ == "__main__":
  print(power(-2, -3))

