
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz

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

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




'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


lowercase__						       =      logging.get_logger(__name__)






class 	snake_case__       (      __SCREAMING_SNAKE_CASE					):







		"""simple docstring"""

		def __init__(      self				:			Optional[Any]  ,	*UpperCamelCase__				:			Optional[Any]  ,	**UpperCamelCase__				:			str      )						->			None:






				"""simple docstring"""







				warnings.warn(
				    '''The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
				    ''' use GLPNImageProcessor instead.'''  ,	UpperCamelCase__  ,	)
				super().__init__(*UpperCamelCase__  ,	**UpperCamelCase__      )


