



import math
import random
from typing import Any

from .hill_climbing import SearchProblem
def  UpperCamelCase						(       _A			:				str			,							_A			:				bool = True			,							_A			:				float = math.inf			,							_A			:				float = -math.inf			,							_A			:				float = math.inf			,							_A			:				float = -math.inf			,							_A			:				bool = False			,							_A			:				float = 100			,							_A			:				float = 0.01			,							_A			:				float = 1			,							)->       Any:





						"""simple docstring"""





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

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





												"""simple docstring"""





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

						# starting the problem with initial coordinates (12, 47)
						UpperCAmelCase_							:      Optional[int]      =  SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
						UpperCAmelCase_							:      List[str]      =  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_							:      Optional[int]      =  SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
						UpperCAmelCase_							:      Tuple      =  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						(       _A			:				Optional[int]			,							_A			:				int    )->       int:





												"""simple docstring"""





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

						UpperCAmelCase_							:      str      =  SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						UpperCAmelCase_							:      List[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()}'''
						)

						UpperCAmelCase_							:      Optional[int]      =  SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						UpperCAmelCase_							:      str      =  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()}'''
						)










def  UpperCamelCase						(       _A			:				str			,							_A			:				str    )->       str:





						"""simple docstring"""





						A__							=       len(_A    )
						A__							=       len(_A    )
						A__							=       (
						    first_str_length if first_str_length > second_str_length else second_str_length
						)
						A__							=       []
						for char_count in range(_A    ):
												if char_count < first_str_length:
																		output_list.append(first_str[char_count]    )
												if char_count < second_str_length:
																		output_list.append(second_str[char_count]    )
						return "".join(_A    )


if __name__ == "__main__":
						print(alternative_string_arrange("AB", "XYZ"), end=" ")





