
import numpy as np
import skfuzzy as fuzz

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

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






def 				a						(							snake_case__:					list						,   snake_case__:					list						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if index == number_of_items:
								return 0
				lowercase_       =					0
				lowercase_       =					0
				lowercase_       =					knapsack(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__						,   index + 1					)
				if weights[index] <= max_weight:
								lowercase_       =					values[index] + knapsack(
								    snake_case__						,   snake_case__						,   snake_case__						,   max_weight - weights[index]						,   index + 1					)
				return max(snake_case__						,   snake_case__					)


if __name__ == "__main__":
						import doctest

						doctest.testmod()




