




import math
import random
from typing import Any

from .hill_climbing import SearchProblem







def 		lowercase__   (		__A:	Dict							,__A:	Dict = True							,__A:	Union[str, Any] = math.inf							,__A:	Optional[int] = -math.inf							,__A:	List[str] = math.inf							,__A:	List[str] = -math.inf							,__A:	Dict = False							,__A:	Any = 1_0_0							,__A:	List[str] = 0.01							,__A:	List[Any] = 1							,):





     '''simple docstring'''






     __magic_name__							:	int    							=							False
     __magic_name__							:	Tuple    							=							search_prob
     __magic_name__							:	str    							=							start_temperate
     __magic_name__							:	Any    							=							[]
     __magic_name__							:	str    							=							0
     __magic_name__							:	str    							=							None

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





      '''simple docstring'''






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

 # starting the problem with initial coordinates (12, 47)
 __lowerCamelCase   :						Optional[int]				=			SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
 __lowerCamelCase   :						Union[str, 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   :						List[Any]				=			SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
 __lowerCamelCase   :						List[Any]				=			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 		lowercase__   (		__A:	int							,__A:	Tuple				):





      '''simple docstring'''






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

 __lowerCamelCase   :						int				=			SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
 __lowerCamelCase   :						int				=			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   :						Tuple				=			SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
 __lowerCamelCase   :						int				=			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 sys
import turtle







def 		lowercase__   (		__A:	tuple[float, float]							,__A:	tuple[float, float]				):





					'''simple docstring'''






					return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2







def 		lowercase__   (		__A:	tuple[float, float]							,__A:	tuple[float, float]							,__A:	tuple[float, float]							,__A:	int							,):





					'''simple docstring'''






					my_pen.up()
					my_pen.goto(vertexa[0]							,vertexa[1]				)
					my_pen.down()
					my_pen.goto(vertexa[0]							,vertexa[1]				)
					my_pen.goto(vertexa[0]							,vertexa[1]				)
					my_pen.goto(vertexa[0]							,vertexa[1]				)

					if depth == 0:
										return

					triangle(__A							,get_mid(__A							,__A				)							,get_mid(__A							,__A				)							,depth - 1				)
					triangle(__A							,get_mid(__A							,__A				)							,get_mid(__A							,__A				)							,depth - 1				)
					triangle(__A							,get_mid(__A							,__A				)							,get_mid(__A							,__A				)							,depth - 1				)


if __name__ == "__main__":
	if len(sys.argv) != 2:
		raise ValueError(
		    '''Correct format for using this script: '''
		    '''python fractals.py <int:depth_for_fractal>'''
		)
	__lowerCamelCase   :						Any				=			turtle.Turtle()
	my_pen.ht()
	my_pen.speed(5)
	my_pen.pencolor('''red''')

	__lowerCamelCase   :						Optional[Any]				=			[(-1_75, -1_25), (0, 1_75), (1_75, -1_25)]  # vertices of triangle
	triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))



