"""simple docstring"""
import math
import random
from typing import Any

from .hill_climbing import SearchProblem







def 						__a       (     _SCREAMING_SNAKE_CASE		,					_SCREAMING_SNAKE_CASE = True		,					_SCREAMING_SNAKE_CASE = math.inf		,					_SCREAMING_SNAKE_CASE = -math.inf		,					_SCREAMING_SNAKE_CASE = math.inf		,					_SCREAMING_SNAKE_CASE = -math.inf		,					_SCREAMING_SNAKE_CASE = False		,					_SCREAMING_SNAKE_CASE = 100		,					_SCREAMING_SNAKE_CASE = 0.01		,					_SCREAMING_SNAKE_CASE = 1		,					)     ->Any:
  a__:					Tuple      							=     False
  a__:					Tuple      							=     search_prob
  a__:					int      							=     start_temperate
  a__:					Dict      							=     []
  a__:					List[str]      							=     0
  a__:					List[str]      							=     None

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



"""simple docstring"""
import unittest

from knapsack import knapsack as k




class        __snake_case	(					unittest.TestCase    ):



      def   lowerCamelCase_       (						self)     ->      Dict:





        '''simple docstring'''





        a__:					List[Any]      							=     0
        a__:					Dict      							=     [0]
        a__:					int      							=     [0]
        a__:					Optional[Any]      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      0)

        a__:					str      							=     [60]
        a__:					Dict      							=     [10]
        a__:					List[str]      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      0)



      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        a__:					int      							=     3
        a__:					str      							=     [1, 2, 3]
        a__:					Dict      							=     [3, 2, 1]
        a__:					Optional[int]      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      5)



      def   lowerCamelCase_       (						self)     ->      Union[str, Any]:





        '''simple docstring'''





        a__:					Any      							=     50
        a__:					Optional[int]      							=     [60, 1_00, 1_20]
        a__:					str      							=     [10, 20, 30]
        a__:					int      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      2_20)


if __name__ == "__main__":
 unittest.main()


