





import math
import random
from typing import Any

from .hill_climbing import SearchProblem





def lowerCAmelCase__(__snake_case       ,__snake_case = True       ,__snake_case = math.inf       ,__snake_case = -math.inf       ,__snake_case = math.inf       ,__snake_case = -math.inf       ,__snake_case = False       ,__snake_case = 100       ,__snake_case = 0.0_1       ,__snake_case = 1       ,)				->      Tuple:







	'''simple docstring'''







	lowerCamelCase__								=		False
	lowerCamelCase__								=		search_prob
	lowerCamelCase__								=		start_temperate
	lowerCamelCase__								=		[]
	lowerCamelCase__								=		0
	lowerCamelCase__								=		None

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

	if visualization:
		from matplotlib import pyplot as plt

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


if __name__ == "__main__":





			def lowerCAmelCase__(__snake_case       ,__snake_case							)				->      Tuple:







				'''simple docstring'''







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

			# starting the problem with initial coordinates (12, 47)
			_a 						=      SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
			_a 						=      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)
			_a 						=      SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
			_a 						=      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 lowerCAmelCase__(__snake_case       ,__snake_case							)				->      int:







				'''simple docstring'''







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

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

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







class 			_lowercase :  # Public class to implement a graph


       """simple docstring"""




       def __init__(   self							:			Dict					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			list[list[bool]]       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  row
             lowerCamelCase__		:				Optional[Any]    =  col
             lowerCamelCase__		:				Union[str, Any]    =  graph





       def 						lowerCAmelCase     (   self							:			Optional[int]					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			list[list[bool]]       ):


             '''simple docstring'''



             return (
                 0 <= i < self.ROW
                 and 0 <= j < self.COL
                 and not visited[i][j]
                 and self.graph[i][j]
             )





       def 						lowerCAmelCase     (   self							:			Dict					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			list[list[bool]]       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  [-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
             lowerCamelCase__		:				Tuple    =  [-1, 0, 1, -1, 1, -1, 0, 1]
             lowerCamelCase__		:				List[Any]    =  True  # Make those cells visited
             for k in range(8       ):
                   if self.is_safe(i + row_nbr[k]					,      j + col_nbr[k]					,      __lowerCamelCase       ):
                         self.diffs(i + row_nbr[k]					,      j + col_nbr[k]					,      __lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			List[Any]       ):  # And finally, count all islands.


             '''simple docstring'''



             lowerCamelCase__		:				List[Any]    =  [[False for j in range(self.COL       )] for i in range(self.ROW       )]
             lowerCamelCase__		:				Optional[Any]    =  0
             for i in range(self.ROW       ):
                   for j in range(self.COL       ):
                         if visited[i][j] is False and self.graph[i][j] == 1:
                               self.diffs(__lowerCamelCase					,      __lowerCamelCase					,      __lowerCamelCase       )
                               count += 1
             return count


