'''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=75, num=75, endpoint=True, retstep=False)

			# Create two fuzzy sets by defining any membership function
			# (trapmf(), gbellmf(), gaussmf(), etc).
			lowerCAmelCase_	:		Dict			=     [0, 25, 50]
			lowerCAmelCase_	:		Optional[Any]			=     [25, 50, 75]
			lowerCAmelCase_	:		Union[str, Any]			=     fuzz.membership.trimf(X, abca)
			lowerCAmelCase_	:		List[str]			=     fuzz.membership.trimf(X, abca)

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



'''simple docstring'''





lowerCAmelCase_	:		Union[str, Any]			=     """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

lowerCAmelCase_	:		List[Any]			=     [{"""type""": """code""", """content""": INSTALL_CONTENT}]
lowerCAmelCase_	:		int			=     {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}


