


import math
import random
from typing import Any

from .hill_climbing import SearchProblem







def 						lowerCamelCase(   a__	,a__ = True	,a__ = math.inf	,a__ = -math.inf	,a__ = math.inf	,a__ = -math.inf	,a__ = False	,a__ = 100	,a__ = 0.01	,a__ = 1	,):
    _SCREAMING_SNAKE_CASE			  =False
    _SCREAMING_SNAKE_CASE			  =search_prob
    _SCREAMING_SNAKE_CASE			  =start_temperate
    _SCREAMING_SNAKE_CASE			  =[]
    _SCREAMING_SNAKE_CASE			  =0
    _SCREAMING_SNAKE_CASE			  =None

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

       # starting the problem with initial coordinates (12, 47)
       snake_case_						:			str													=							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
       snake_case_						:			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)
       snake_case_						:			str													=							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
       snake_case_						:			List[str]													=							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 						lowerCamelCase(   a__	,a__):
           return (3 * x**2) - (6 * y)

       snake_case_						:			Tuple													=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
       snake_case_						:			Dict													=							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()}"""
       )

       snake_case_						:			List[str]													=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
       snake_case_						:			Tuple													=							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()}"""
       )



from collections.abc import Generator







def 						lowerCamelCase(   ):
				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =0, 1
				while True:
								_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =b, a + b
								yield b







def 						lowerCamelCase(   a__ = 1000):
				_SCREAMING_SNAKE_CASE			  =1
				_SCREAMING_SNAKE_CASE			  =fibonacci_generator()
				while len(str(next(a__))) < n:
								answer += 1
				return answer + 1


if __name__ == "__main__":
							print(solution(int(str(input()).strip())))