
import math
import random
from typing import Any

from .hill_climbing import SearchProblem




def        __UpperCamelCase					(    lowerCAmelCase__							:    Union[str, Any]  ,       lowerCAmelCase__							:    bool = True  ,       lowerCAmelCase__							:    float = math.inf  ,       lowerCAmelCase__							:    float = -math.inf  ,       lowerCAmelCase__							:    float = math.inf  ,       lowerCAmelCase__							:    float = -math.inf  ,       lowerCAmelCase__							:    bool = False  ,       lowerCAmelCase__							:    float = 1_0_0  ,       lowerCAmelCase__							:    float = 0.01  ,       lowerCAmelCase__							:    float = 1  ,       ):
 __a			:  int		    =  False
 __a			:  Any		    =  search_prob
 __a			:  Tuple		    =  start_temperate
 __a			:  Any		    =  []
 __a			:  Dict		    =  0
 __a			:  Optional[Any]		    =  None

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

 if visualization:
  from matplotlib import pyplot as plt

  plt.plot(range(lowerCAmelCase__  )  ,       lowerCAmelCase__  )
  plt.xlabel('''Iterations'''  )
  plt.ylabel('''Function values'''  )
  plt.show()
 return best_state


if __name__ == "__main__":




      def        __UpperCamelCase					(    lowerCAmelCase__							:    Optional[int]  ,       lowerCAmelCase__							:    Dict  ):
       return (x**2) + (y**2)

      # starting the problem with initial coordinates (12, 47)
      lowercase__          =SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
      lowercase__          =simulated_annealing(
          prob, find_max=False, max_x=100, 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)
      lowercase__          =SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
      lowercase__          =simulated_annealing(
          prob, find_max=True, max_x=100, 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        __UpperCamelCase					(    lowerCAmelCase__							:    Optional[Any]  ,       lowerCAmelCase__							:    Dict  ):
       return (3 * x**2) - (6 * y)

      lowercase__          =SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
      lowercase__          =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()}"""
      )

      lowercase__          =SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
      lowercase__          =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()}"""
      )


from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowercase__          =10




def        __UpperCamelCase					(    lowerCAmelCase__							:    int  ,       lowerCAmelCase__							:    int  ,       lowerCAmelCase__							:    list[int]  ,       lowerCAmelCase__							:    int  ):
 for i in range(lowerCAmelCase__  ,       lowerCAmelCase__  ):
  if array[i] == target:
   return i
 return -1




def        __UpperCamelCase					(    lowerCAmelCase__							:    list[int]  ,       lowerCAmelCase__							:    int  ):
 __a			:  List[Any]		    =  0
 __a			:  Union[str, Any]		    =  len(lowerCAmelCase__  )
 while left <= right:
  if right - left < precision:
   return lin_search(lowerCAmelCase__  ,       lowerCAmelCase__  ,       lowerCAmelCase__  ,       lowerCAmelCase__  )

  __a			:  str		    =  (left + right) // 3 + 1
  __a			:  List[Any]		    =  2 * (left + right) // 3 + 1

  if array[one_third] == target:
   return one_third
  elif array[two_third] == target:
   return two_third

  elif target < array[one_third]:
   __a			:  List[str]		    =  one_third - 1
  elif array[two_third] < target:
   __a			:  List[str]		    =  two_third + 1

  else:
   __a			:  Dict		    =  one_third + 1
   __a			:  Any		    =  two_third - 1
 else:
  return -1




def        __UpperCamelCase					(    lowerCAmelCase__							:    int  ,       lowerCAmelCase__							:    int  ,       lowerCAmelCase__							:    list[int]  ,       lowerCAmelCase__							:    int  ):
 if left < right:
  if right - left < precision:
   return lin_search(lowerCAmelCase__  ,       lowerCAmelCase__  ,       lowerCAmelCase__  ,       lowerCAmelCase__  )
  __a			:  Union[str, Any]		    =  (left + right) // 3 + 1
  __a			:  Optional[Any]		    =  2 * (left + right) // 3 + 1

  if array[one_third] == target:
   return one_third
  elif array[two_third] == target:
   return two_third

  elif target < array[one_third]:
   return rec_ternary_search(lowerCAmelCase__  ,       one_third - 1  ,       lowerCAmelCase__  ,       lowerCAmelCase__  )
  elif array[two_third] < target:
   return rec_ternary_search(two_third + 1  ,       lowerCAmelCase__  ,       lowerCAmelCase__  ,       lowerCAmelCase__  )
  else:
   return rec_ternary_search(one_third + 1  ,       two_third - 1  ,       lowerCAmelCase__  ,       lowerCAmelCase__  )
 else:
  return -1


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      lowercase__          =input('Enter numbers separated by comma:\n').strip()
      lowercase__          =[int(item.strip()) for item in user_input.split(',')]
      assert collection == sorted(collection), F"List must be ordered.\n{collection}."
      lowercase__          =int(input('Enter the number to be found in the list:\n').strip())
      lowercase__          =ite_ternary_search(collection, target)
      lowercase__          =rec_ternary_search(0, len(collection) - 1, collection, target)
      if resulta != -1:
            print(F"""Iterative search: {target} found at positions: {resulta}""")
            print(F"""Recursive search: {target} found at positions: {resulta}""")
      else:
            print('Not found')
