





from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
_A :   Union[str, Any]  			=  Lock()



def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase      ,  UpperCAmelCase      ,  UpperCAmelCase      ,  UpperCAmelCase      ,  UpperCAmelCase      ,  UpperCAmelCase					)    ->    Tuple:







   """simple docstring"""
   global process_lock

   # we perform n swaps since after n swaps we know we are sorted
   # we *could* stop early if we are sorted already, but it takes as long to
   # find out we are sorted as it does to sort the list with this algorithm
   for i in range(0      ,  10					):
      if (i + position) % 2 == 0 and r_send is not None:
         # send your value to your right neighbor
         process_lock.acquire()
         r_send[1].send(__lowerCAmelCase					)
         process_lock.release()

         # receive your right neighbor's value
         process_lock.acquire()
         lowerCamelCase__       :						Tuple        =							rr_cv[0].recv()
         process_lock.release()

         # take the lower value since you are on the left
         lowerCamelCase__       :						Optional[Any]        =							min(__lowerCAmelCase      ,  __lowerCAmelCase					)
      elif (i + position) % 2 != 0 and l_send is not None:
         # send your value to your left neighbor
         process_lock.acquire()
         l_send[1].send(__lowerCAmelCase					)
         process_lock.release()

         # receive your left neighbor's value
         process_lock.acquire()
         lowerCamelCase__       :						Optional[int]        =							lr_cv[0].recv()
         process_lock.release()

         # take the higher value since you are on the right
         lowerCamelCase__       :						List[Any]        =							max(__lowerCAmelCase      ,  __lowerCAmelCase					)
    # after all swaps are performed, send the values back to main
   result_pipe[1].send(__lowerCAmelCase					)



def 	_a						(   UpperCAmelCase					)    ->    Dict:







   """simple docstring"""
   lowerCamelCase__       :						Tuple        =							[]
   lowerCamelCase__       :						List[str]        =							[]
   # initialize the list of pipes where the values will be retrieved
   for _ in arr:
      result_pipe.append(Pipe()					)
   # creates the processes
   # the first and last process only have one neighbor so they are made outside
   # of the loop
   lowerCamelCase__       :						List[Any]        =							Pipe()
   lowerCamelCase__       :						Any        =							Pipe()
   process_array_.append(
       Process(
           target=__lowerCAmelCase      ,  args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])      ,  )					)
   lowerCamelCase__       :						List[Any]        =							temp_rs
   lowerCamelCase__       :						Tuple        =							temp_rr

   for i in range(1      ,  len(__lowerCAmelCase					) - 1					):
      lowerCamelCase__       :						Union[str, Any]        =							Pipe()
      lowerCamelCase__       :						int        =							Pipe()
      process_array_.append(
          Process(
              target=__lowerCAmelCase      ,  args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])      ,  )					)
      lowerCamelCase__       :						Optional[Any]        =							temp_rs
      lowerCamelCase__       :						Any        =							temp_rr

   process_array_.append(
       Process(
           target=__lowerCAmelCase      ,  args=(
               len(__lowerCAmelCase					) - 1,
               arr[len(__lowerCAmelCase					) - 1],
               temp_ls,
               None,
               temp_lr,
               None,
               result_pipe[len(__lowerCAmelCase					) - 1],
           )      ,  )					)

   # start the processes
   for p in process_array_:
      p.start()

   # wait for the processes to end and write their values to the list
   for p in range(0      ,  len(__lowerCAmelCase					)					):
      lowerCamelCase__       :						Tuple        =							result_pipe[p][0].recv()
      process_array_[p].join()
   return arr



def 	_a						(   )    ->    Any:







   """simple docstring"""
   lowerCamelCase__       :						Optional[Any]        =							list(range(10      ,  0      ,  -1					)					)
   print('''Initial List'''					)
   print(*__lowerCAmelCase					)
   lowerCamelCase__       :						Any        =							odd_even_transposition(__lowerCAmelCase					)
   print('''Sorted List\n'''					)
   print(*__lowerCAmelCase					)


if __name__ == "__main__":
       main()













import numpy as np
import skfuzzy as fuzz

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

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



