





"""simple docstring"""




import numpy as np
import skfuzzy as fuzz

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

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













from __future__ import annotations




def _a (  SCREAMING_SNAKE_CASE__      :  list[float]			,				SCREAMING_SNAKE_CASE__      :  list[float]       )	->    float:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      List[Any]     =						sorted(numsa + numsa       )
							SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Dict     =						divmod(len(SCREAMING_SNAKE_CASE__       )			,				2       )
							if mod == 1:
														return all_numbers[div]
							else:
														return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		_lowerCamelCase :    List[str]  							= [float(x) for x in input('''Enter the elements of first array: ''').split()]
		_lowerCamelCase :    Any  							= [float(x) for x in input('''Enter the elements of second array: ''').split()]
		print(f"The median of two arrays is: {median_of_two_arrays(array_a, array_a)}")






