



"""simple docstring"""




import math
import random
from typing import Any

from .hill_climbing import SearchProblem

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Dict						,  SCREAMING_SNAKE_CASE__     :						bool = True						,  SCREAMING_SNAKE_CASE__     :						float = math.inf						,  SCREAMING_SNAKE_CASE__     :						float = -math.inf						,  SCREAMING_SNAKE_CASE__     :						float = math.inf						,  SCREAMING_SNAKE_CASE__     :						float = -math.inf						,  SCREAMING_SNAKE_CASE__     :						bool = False						,  SCREAMING_SNAKE_CASE__     :						float = 100						,  SCREAMING_SNAKE_CASE__     :						float = 0.01						,  SCREAMING_SNAKE_CASE__     :						float = 1						,  )  ->       Any:





     '''simple docstring'''

     _UpperCAmelCase      :     str        =   False
     _UpperCAmelCase      :     Dict        =   search_prob
     _UpperCAmelCase      :     int        =   start_temperate
     _UpperCAmelCase      :     Any        =   []
     _UpperCAmelCase      :     Dict        =   0
     _UpperCAmelCase      :     Optional[int]        =   None

     while not search_end:
          _UpperCAmelCase      :     Union[str, Any]        =   current_state.score()
          if best_state is None or current_score > best_state.score():
               _UpperCAmelCase      :     int        =   current_state
          scores.append(SCREAMING_SNAKE_CASE__    )
          iterations += 1
          _UpperCAmelCase      :     str        =   None
          _UpperCAmelCase      :     Any        =   current_state.get_neighbors()
          while (
              next_state is None and neighbors
          ):  # till we do not find a neighbor that we can move to
               _UpperCAmelCase      :     str        =   random.randint(0						,  len(SCREAMING_SNAKE_CASE__    ) - 1    )  # picking a random neighbor
               _UpperCAmelCase      :     Tuple        =   neighbors.pop(SCREAMING_SNAKE_CASE__    )
               _UpperCAmelCase      :     str        =   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      :     Tuple        =   change * -1  # in case we are finding minimum
               if change > 0:  # improves the solution
                    _UpperCAmelCase      :     Optional[int]        =   picked_neighbor
               else:
                    _UpperCAmelCase      :     str        =   (math.e) ** (
                        change / current_temp
                    )  # probability generation function
                    if random.random() < probability:  # random number within probability
                         _UpperCAmelCase      :     str        =   picked_neighbor
          _UpperCAmelCase      :     Any        =   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      :     List[Any]        =   True
          else:
               _UpperCAmelCase      :     int        =   next_state

     if visualization:
          from matplotlib import pyplot as plt

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


if __name__ == "__main__":

 def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Any						,  SCREAMING_SNAKE_CASE__     :						Union[str, Any]    )  ->       Dict:





      '''simple docstring'''

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

 # starting the problem with initial coordinates (12, 47)
 _lowerCAmelCase    : Union[str, Any]							=							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
 _lowerCAmelCase    : List[str]							=							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)
 _lowerCAmelCase    : Any							=							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
 _lowerCAmelCase    : 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 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						str						,  SCREAMING_SNAKE_CASE__     :						List[Any]    )  ->       str:





      '''simple docstring'''

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

 _lowerCAmelCase    : Optional[Any]							=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
 _lowerCAmelCase    : List[str]							=							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()}"
 )

 _lowerCAmelCase    : Union[str, Any]							=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
 _lowerCAmelCase    : Optional[int]							=							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"""




def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						list    )  ->       list:





     '''simple docstring'''

     if len(SCREAMING_SNAKE_CASE__    ) < 2:
          return collection

     def circle_sort_util(SCREAMING_SNAKE_CASE__     :						list						,  SCREAMING_SNAKE_CASE__     :						int						,  SCREAMING_SNAKE_CASE__     :						int    ) -> bool:
          _UpperCAmelCase      :     Dict        =   False

          if low == high:
               return swapped

          _UpperCAmelCase      :     str        =   low
          _UpperCAmelCase      :     Dict        =   high

          while left < right:
               if collection[left] > collection[right]:
                    _UpperCAmelCase    ,	_UpperCAmelCase      :     List[str]        =   (
                        collection[right],
                        collection[left],
                    )
                    _UpperCAmelCase      :     Optional[int]        =   True

               left += 1
               right -= 1

          if left == right and collection[left] > collection[right + 1]:
               _UpperCAmelCase    ,	_UpperCAmelCase      :     int        =   (
                   collection[right + 1],
                   collection[left],
               )

               _UpperCAmelCase      :     Union[str, Any]        =   True

          _UpperCAmelCase      :     Dict        =   low + int((high - low) / 2    )
          _UpperCAmelCase      :     Any        =   circle_sort_util(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    )
          _UpperCAmelCase      :     Optional[Any]        =   circle_sort_util(SCREAMING_SNAKE_CASE__						,  mid + 1						,  SCREAMING_SNAKE_CASE__    )

          return swapped or left_swap or right_swap

     _UpperCAmelCase      :     Tuple        =   True

     while is_not_sorted is True:
          _UpperCAmelCase      :     Dict        =   circle_sort_util(SCREAMING_SNAKE_CASE__						,  0						,  len(SCREAMING_SNAKE_CASE__    ) - 1    )

     return collection


if __name__ == "__main__":
 _lowerCAmelCase    : Dict							=							input("Enter numbers separated by a comma:\n").strip()
 _lowerCAmelCase    : Optional[Any]							=							[int(item) for item in user_input.split(",")]
 print(circle_sort(unsorted))
