import math
import random
from typing import Any

from .hill_climbing import SearchProblem




def       _snake_case	(   lowerCAmelCase							:   Tuple   , 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   , ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		List[str]				      =    False
		SCREAMING_SNAKE_CASE_  :		List[Any]				      =    search_prob
		SCREAMING_SNAKE_CASE_  :		Dict				      =    start_temperate
		SCREAMING_SNAKE_CASE_  :		int				      =    []
		SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    0
		SCREAMING_SNAKE_CASE_  :		Any				      =    None

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







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

		# starting the problem with initial coordinates (12, 47)
		__lowerCamelCase					:	List[str]       =  SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
		__lowerCamelCase					:	List[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)
		__lowerCamelCase					:	Any       =  SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
		__lowerCamelCase					:	int       =  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	(   lowerCAmelCase							:   str   , lowerCAmelCase							:   Union[str, Any]	):
				"""simple docstring"""







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

		__lowerCamelCase					:	Any       =  SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
		__lowerCamelCase					:	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					:	List[str]       =  SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
		__lowerCamelCase					:	List[Any]       =  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  lowerCamelCase_						(UpperCamelCase__		:		int							):
    if not isinstance(UpperCamelCase__     ,       UpperCamelCase__							) or number < 0:
        raise ValueError('''Input must be a non-negative integer'''							)

    _UpperCAmelCase							:  str											=    0
    while number:
        # This way we arrive at next set bit (next 1) instead of looping
        # through each bit and checking for 1s hence the
        # loop won't run 32 times it will only run the number of `1` times
        number &= number - 1
        count += 1
    return count


if __name__ == "__main__":
  import doctest

  doctest.testmod()


