






"""simple docstring"""




import numpy as np
import skfuzzy as fuzz

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

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

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


_snake_case          =   logging.get_logger(__name__)






class        UpperCamelCase			(	snake_case_      ):


 def __init__(     self		:						Any							,						*UpperCAmelCase__		:						Optional[Any]							,						**UpperCAmelCase__		:						Tuple							)					->       None:
   warnings.warn(
       """The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
       """ use CLIPImageProcessor instead."""							,						UpperCAmelCase__							,						)
   super().__init__(*UpperCAmelCase__							,						**UpperCAmelCase__							)

