'''simple docstring'''





import math
import random
from typing import Any

from .hill_climbing import SearchProblem





def 	lowerCAmelCase_				(					snake_case_       : Any					,    snake_case_       : bool = True					,    snake_case_       : float = math.inf					,    snake_case_       : float = -math.inf					,    snake_case_       : float = math.inf					,    snake_case_       : float = -math.inf					,    snake_case_       : bool = False					,    snake_case_       : float = 1_00					,    snake_case_       : float = 0.01					,    snake_case_       : float = 1					,    )    ->      Any:


     '''simple docstring'''




     UpperCAmelCase_           =   False
     UpperCAmelCase_           =   search_prob
     UpperCAmelCase_           =   start_temperate
     UpperCAmelCase_           =   []
     UpperCAmelCase_           =   0
     UpperCAmelCase_           =   None

     while not search_end:
          UpperCAmelCase_           =   current_state.score()
          if best_state is None or current_score > best_state.score():
               UpperCAmelCase_           =   current_state
          scores.append(snake_case_			)
          iterations += 1
          UpperCAmelCase_           =   None
          UpperCAmelCase_           =   current_state.get_neighbors()
          while (
              next_state is None and neighbors
          ):  # till we do not find a neighbor that we can move to
               UpperCAmelCase_           =   random.randint(0					,    len(snake_case_			) - 1			)  # picking a random neighbor
               UpperCAmelCase_           =   neighbors.pop(snake_case_			)
               UpperCAmelCase_           =   picked_neighbor.score() - current_score

               if (
                   picked_neighbor.x > max_x
                   or picked_neighbor.x < min_x
                   or picked_neighbor.y > max_y
                   or picked_neighbor.y < min_y
               ):
                    continue  # neighbor outside our bounds

               if not find_max:
                    UpperCAmelCase_           =   change * -1  # in case we are finding minimum
               if change > 0:  # improves the solution
                    UpperCAmelCase_           =   picked_neighbor
               else:
                    UpperCAmelCase_           =   (math.e) ** (
                        change / current_temp
                    )  # probability generation function
                    if random.random() < probability:  # random number within probability
                         UpperCAmelCase_           =   picked_neighbor
          UpperCAmelCase_           =   current_temp - (current_temp * rate_of_decrease)

          if current_temp < threshold_temp or next_state is None:
               # temperature below threshold, or could not find a suitable neighbor
               UpperCAmelCase_           =   True
          else:
               UpperCAmelCase_           =   next_state

     if visualization:
          from matplotlib import pyplot as plt

          plt.plot(range(snake_case_			)					,    snake_case_			)
          plt.xlabel("Iterations"			)
          plt.ylabel("Function values"			)
          plt.show()
     return best_state


if __name__ == "__main__":





    def 	lowerCAmelCase_				(					snake_case_       : Optional[Any]					,    snake_case_       : int			)    ->      int:


         '''simple docstring'''




         return (x**2) + (y**2)

    # starting the problem with initial coordinates (12, 47)
    SCREAMING_SNAKE_CASE_:     List[Any]  =SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
    SCREAMING_SNAKE_CASE_:     Optional[Any]  =simulated_annealing(
        prob, find_max=False, max_x=1_00, min_x=5, max_y=50, min_y=-5, visualization=True
    )
    print(
        'The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 '
        f"and 50 > y > - 5 found via hill climbing: {local_min.score()}"
    )

    # starting the problem with initial coordinates (12, 47)
    SCREAMING_SNAKE_CASE_:     Tuple  =SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
    SCREAMING_SNAKE_CASE_:     List[str]  =simulated_annealing(
        prob, find_max=True, max_x=1_00, min_x=5, max_y=50, min_y=-5, visualization=True
    )
    print(
        'The maximum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 '
        f"and 50 > y > - 5 found via hill climbing: {local_min.score()}"
    )





    def 	lowerCAmelCase_				(					snake_case_       : int					,    snake_case_       : Union[str, Any]			)    ->      Optional[Any]:


         '''simple docstring'''




         return (3 * x**2) - (6 * y)

    SCREAMING_SNAKE_CASE_:     str  =SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
    SCREAMING_SNAKE_CASE_:     Tuple  =simulated_annealing(prob, find_max=False, visualization=True)
    print(
        'The minimum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: '
        f"{local_min.score()}"
    )

    SCREAMING_SNAKE_CASE_:     List[str]  =SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
    SCREAMING_SNAKE_CASE_:     Tuple  =simulated_annealing(prob, find_max=True, visualization=True)






    print(
        'The maximum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: '
        f"{local_min.score()}"
    )





'''simple docstring'''





from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
SCREAMING_SNAKE_CASE_:     Optional[int]  =Lock()





def 	lowerCAmelCase_				(					snake_case_       : Dict					,    snake_case_       : Dict					,    snake_case_       : Optional[int]					,    snake_case_       : Tuple					,    snake_case_       : Any					,    snake_case_       : Optional[Any]					,    snake_case_       : Union[str, Any]			)    ->      Optional[Any]:


     '''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(snake_case_			)
               process_lock.release()

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

               # take the lower value since you are on the left
               UpperCAmelCase_           =   min(snake_case_					,    snake_case_			)
          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(snake_case_			)
               process_lock.release()

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

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





def 	lowerCAmelCase_				(					snake_case_       : Optional[Any]			)    ->      Dict:


     '''simple docstring'''




     UpperCAmelCase_           =   []
     UpperCAmelCase_           =   []
     # 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
     UpperCAmelCase_           =   Pipe()
     UpperCAmelCase_           =   Pipe()
     process_array_.append(
         Process(
             target=snake_case_					,    args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])					,    )			)
     UpperCAmelCase_           =   temp_rs
     UpperCAmelCase_           =   temp_rr

     for i in range(1					,    len(snake_case_			) - 1			):
          UpperCAmelCase_           =   Pipe()
          UpperCAmelCase_           =   Pipe()
          process_array_.append(
              Process(
                  target=snake_case_					,    args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])					,    )			)
          UpperCAmelCase_           =   temp_rs
          UpperCAmelCase_           =   temp_rr

     process_array_.append(
         Process(
             target=snake_case_					,    args=(
                 len(snake_case_			) - 1,
                 arr[len(snake_case_			) - 1],
                 temp_ls,
                 None,
                 temp_lr,
                 None,
                 result_pipe[len(snake_case_			) - 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(snake_case_			)			):
          UpperCAmelCase_           =   result_pipe[p][0].recv()
          process_array_[p].join()
     return arr





def 	lowerCAmelCase_				(					)    ->      str:


     '''simple docstring'''




     UpperCAmelCase_           =   list(range(10					,    0					,    -1			)			)
     print("Initial List"			)
     print(*snake_case_			)
     UpperCAmelCase_           =   odd_even_transposition(snake_case_			)
     print("Sorted List\n"			)
     print(*snake_case_			)


if __name__ == "__main__":
    main()




