import math
class 				a_ :






 '''simple docstring'''






 def __init__(			self					:  Any			,    lowercase__					:  int			,    lowercase__					:  int			,    lowercase__					:  int			,    lowercase__					:  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__     	=					x
        lowerCAmelCase__     	=					y
        lowerCAmelCase__     	=					step_size
        lowerCAmelCase__     	=					function_to_optimize




 def 		__snake_case						(			self					:  Union[str, Any]):







        '''simple docstring'''



        return self.function(self.x			,    self.y)




 def 		__snake_case						(			self					:  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__     	=					self.step_size
        return [
            SearchProblem(lowercase__			,    lowercase__			,    lowercase__			,    self.function)
            for x, y in (
                (self.x - step_size, self.y - step_size),
                (self.x - step_size, self.y),
                (self.x - step_size, self.y + step_size),
                (self.x, self.y - step_size),
                (self.x, self.y + step_size),
                (self.x + step_size, self.y - step_size),
                (self.x + step_size, self.y),
                (self.x + step_size, self.y + step_size),
            )
        ]




 def __hash__(			self					:  Optional[int]):







        '''simple docstring'''



        return hash(str(self))




 def __eq__(			self					:  Dict			,    lowercase__					:  Optional[int]):







        '''simple docstring'''



        if isinstance(lowercase__			,    lowercase__):
               return hash(str(self)) == hash(str(lowercase__))
        return False




 def __str__(			self					:  Dict):







        '''simple docstring'''



        return F"""x: {self.x} y: {self.y}"""






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__ = True	,  lowerCAmelCase__ = math.inf	,  lowerCAmelCase__ = -math.inf	,  lowerCAmelCase__ = math.inf	,  lowerCAmelCase__ = -math.inf	,  lowerCAmelCase__ = False	,  lowerCAmelCase__ = 1_0_0_0_0	,  ):
       lowerCAmelCase__     	=					search_prob
       lowerCAmelCase__     	=					[]  # list to store the current score at each iteration
       lowerCAmelCase__     	=					0
       lowerCAmelCase__     	=					False
       lowerCAmelCase__     	=					set()
       while not solution_found and iterations < max_iter:
              visited.add(lowerCAmelCase__	)
              iterations += 1
              lowerCAmelCase__     	=					current_state.score()
              scores.append(lowerCAmelCase__	)
              lowerCAmelCase__     	=					current_state.get_neighbors()
              lowerCAmelCase__     	=					-math.inf
              lowerCAmelCase__     	=					math.inf
              lowerCAmelCase__     	=					None  # to hold the next best neighbor
              for neighbor in neighbors:
                     if neighbor in visited:
                            continue  # do not want to visit the same state again
                     if (
                         neighbor.x > max_x
                         or neighbor.x < min_x
                         or neighbor.y > max_y
                         or neighbor.y < min_y
                     ):
                            continue  # neighbor outside our bounds
                     lowerCAmelCase__     	=					neighbor.score() - current_score
                     if find_max:  # finding max
                            # going to direction with greatest ascent
                            if change > max_change and change > 0:
                                   lowerCAmelCase__     	=					change
                                   lowerCAmelCase__     	=					neighbor
                     else:  # finding min
                            # to direction with greatest descent
                            if change < min_change and change < 0:
                                   lowerCAmelCase__     	=					change
                                   lowerCAmelCase__     	=					neighbor
              if next_state is not None:
                     # we found at least one neighbor which improved the current state
                     lowerCAmelCase__     	=					next_state
              else:
                     # since we have no neighbor that improves the solution we stop the search
                     lowerCAmelCase__     	=					True

       if visualization:
              from matplotlib import pyplot as plt

              plt.plot(range(lowerCAmelCase__	)	,  lowerCAmelCase__	)
              plt.xlabel('Iterations'	)
              plt.ylabel('Function values'	)
              plt.show()

       return current_state


if __name__ == "__main__":
    import doctest

    doctest.testmod()






    def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	):
           return (x**2) + (y**2)

    # starting the problem with initial coordinates (3, 4)
    lowerCAmelCase__							= SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
    lowerCAmelCase__							= hill_climbing(prob, find_max=False)
    print(
        'The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: '
        F'{local_min.score()}'
    )

    # starting the problem with initial coordinates (12, 47)
    lowerCAmelCase__							= SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
    lowerCAmelCase__							= hill_climbing(
        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()}'
    )






    def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	):
           return (3 * x**2) - (6 * y)

    lowerCAmelCase__							= SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
    lowerCAmelCase__							= hill_climbing(prob, find_max=True)



    print(
        'The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: '
        F'{local_min.score()}'
    )


"""simple docstring"""




import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


snake_case    =		1_0_0_0_0_0_0_0_0_0_0_0
snake_case    =		1_0_0_0_0

snake_case   ,			snake_case    =		os.path.split(__file__)
snake_case    =		os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))

def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE				=	pa.Table.from_pydict({'col': [0] * chunk_size}			)
					SCREAMING_SNAKE_CASE				=	pa.concat_tables([table] * (num_examples // chunk_size)			)
					return datasets.Dataset(SCREAMING_SNAKE_CASE_,     fingerprint='table_100B'			)




@dataclass
class      UpperCamelCase	:

				"""simple docstring"""



				UpperCAmelCase_				:      int
				UpperCAmelCase_				:      int
				UpperCAmelCase_				:      int
				UpperCAmelCase_				:      int


				def 							A					(				self			)    ->    Optional[Any]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	np.random.default_rng(self.seed			)
									SCREAMING_SNAKE_CASE				=	rng.integers(low=self.low		,	high=self.high		,	size=self.size			).tolist()


				def __iter__(				self			)    ->    Union[str, Any]:
									"""simple docstring"""







									return iter(self._sampled_values			)




				def __len__(				self			)    ->    Optional[Any]:
									"""simple docstring"""







									return self.size






@get_duration
def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE				=	dataset[0]

@get_duration
def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE				=	dataset[-1]

@get_duration
def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE				=	dataset[range(len(SCREAMING_SNAKE_CASE_			) // 2,     len(SCREAMING_SNAKE_CASE_			) // 2 + 1_0_2_4			)]

@get_duration
def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE				=	dataset[RandIter(0,     len(SCREAMING_SNAKE_CASE_			),     1_0_2_4,     seed=4_2			)]

def   UpperCamelCase_  (		):
					SCREAMING_SNAKE_CASE				=	{'num examples': SPEED_TEST_N_EXAMPLES}
					SCREAMING_SNAKE_CASE				=	(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
					print('generating dataset'			)
					SCREAMING_SNAKE_CASE				=	generate_100B_dataset(num_examples=SCREAMING_SNAKE_CASE_,     chunk_size=SCREAMING_SNAKE_CASE_			)
					print('Functions'			)
					for func in functions:
										print(func.__name__			)
										SCREAMING_SNAKE_CASE				=	func(SCREAMING_SNAKE_CASE_			)

					with open(SCREAMING_SNAKE_CASE_,     'wb'			) as f:
										f.write(json.dumps(SCREAMING_SNAKE_CASE_			).encode('utf-8'			)			)


if __name__ == "__main__":  # useful to run the profiler
	benchmark_table_100B()
