



import math
import random
from typing import Any

from .hill_climbing import SearchProblem
def 		UpperCamelCase     (       snake_case__	:   str	,					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 = 100	,					snake_case__	:   float = 0.01	,					snake_case__	:   float = 1	,					)     ->					Any:
   UpperCamelCase   :  Dict						     =     False
   UpperCamelCase   :  Union[str, Any]						     =     search_prob
   UpperCamelCase   :  str						     =     start_temperate
   UpperCamelCase   :  Optional[int]						     =     []
   UpperCamelCase   :  Any						     =     0
   UpperCamelCase   :  Optional[int]						     =     None

   while not search_end:
      UpperCamelCase   :  Dict						     =     current_state.score()
      if best_state is None or current_score > best_state.score():
         UpperCamelCase   :  Optional[int]						     =     current_state
      scores.append(snake_case__     )
      iterations += 1
      UpperCamelCase   :  Any						     =     None
      UpperCamelCase   :  Union[str, 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(snake_case__     ) - 1     )  # picking a random neighbor
         UpperCamelCase   :  Optional[Any]						     =     neighbors.pop(snake_case__     )
         UpperCamelCase   :  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:
            UpperCamelCase   :  str						     =     change * -1  # in case we are finding minimum
         if change > 0:  # improves the solution
            UpperCamelCase   :  Optional[Any]						     =     picked_neighbor
         else:
            UpperCamelCase   :  Optional[Any]						     =     (math.e) ** (
                change / current_temp
            )  # probability generation function
            if random.random() < probability:  # random number within probability
               UpperCamelCase   :  Any						     =     picked_neighbor
      UpperCamelCase   :  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
         UpperCamelCase   :  Any						     =     True
      else:
         UpperCamelCase   :  Optional[Any]						     =     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 		UpperCamelCase     (       snake_case__	:   List[str]	,					snake_case__	:   str     )     ->					Dict:
       return (x**2) + (y**2)

    # starting the problem with initial coordinates (12, 47)
    __UpperCAmelCase	       =	SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
    __UpperCAmelCase	       =	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)
    __UpperCAmelCase	       =	SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
    __UpperCAmelCase	       =	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     (       snake_case__	:   Tuple	,					snake_case__	:   Optional[int]     )     ->					Dict:
       return (3 * x**2) - (6 * y)

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

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









import re
def 		UpperCamelCase     (       snake_case__	:   str     )     ->					str:

   if len(re.findall('[ATCG]'	,					snake_case__     )     ) != len(snake_case__     ):
      raise ValueError('Invalid Strand'     )

   return dna.translate(dna.maketrans('ATCG'	,					'TAGC'     )     )


if __name__ == "__main__":
    import doctest

    doctest.testmod()



