


'''simple docstring'''





import numpy as np
import skfuzzy as fuzz

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

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





from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str = "" ):






			"""simple docstring"""




			__A=	url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
			__A=	BeautifulSoup(requests.get(_SCREAMING_SNAKE_CASE ).text,'html.parser' )
			__A=	soup.find_all('td',attrs='titleColumn' )
			__A=	soup.find_all('td',class_='ratingColumn imdbRating' )
			return {
			    title.a.text: float(rating.strong.text )
			    for title, rating in zip(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE )
			}






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str = "IMDb_Top_250_Movies.csv" ):






			"""simple docstring"""




			__A=	get_imdb_top_aaa_movies()
			with open(_SCREAMING_SNAKE_CASE,'w',newline='' ) as out_file:
						__A=	csv.writer(_SCREAMING_SNAKE_CASE )
						writer.writerow(['Movie title', 'IMDb rating'] )
						for title, rating in movies.items():
									writer.writerow([title, rating] )


if __name__ == "__main__":
					write_movies()



