



import warnings
from collections.abc import Callable
from typing import Any

import numpy
from matplotlib import pyplot

__UpperCAmelCase						  =     0.25 + 0.0j
__UpperCAmelCase						  =     -0.4 + 0.6j
__UpperCAmelCase						  =     -0.1 + 0.651j
__UpperCAmelCase						  =     -2.0
__UpperCAmelCase						  =     56
__UpperCAmelCase						  =     2.0
__UpperCAmelCase						  =     6_66





def 						__lowerCamelCase       (      __magic_name__	:  complex     , __magic_name__	:  numpy.ndarray						):
							return numpy.exp(__magic_name__						) + c_parameter





def 						__lowerCamelCase       (      __magic_name__	:  complex     , __magic_name__	:  numpy.ndarray						):
							return z_values * z_values + c_parameter





def 						__lowerCamelCase       (      __magic_name__	:  float     , __magic_name__	:  int						):
							a__:       Dict											=numpy.linspace(-window_size     , __magic_name__     , __magic_name__						)
							a__:       int											=x.reshape((nb_pixels, 1)						)
							a__:       str											=numpy.linspace(-window_size     , __magic_name__     , __magic_name__						)
							a__:       str											=y.reshape((1, nb_pixels)						)
							return x + 1.0j * y





def 						__lowerCamelCase       (      __magic_name__	:  Callable[[Any, numpy.ndarray], numpy.ndarray]     , __magic_name__	:  Any     , __magic_name__	:  int     , __magic_name__	:  numpy.ndarray     , __magic_name__	:  float | None = None     , ):
							a__:       Tuple											=z_a.astype("complex64"						)
							for _ in range(__magic_name__						):
														a__:       List[Any]											=eval_function(__magic_name__     , __magic_name__						)
														if infinity is not None:
																					numpy.nan_to_num(__magic_name__     , copy=__magic_name__     , nan=__magic_name__						)
																					a__:       List[Any]											=infinity
							return z_n





def 						__lowerCamelCase       (      __magic_name__	:  str     , __magic_name__	:  Any     , __magic_name__	:  float     , __magic_name__	:  numpy.ndarray     , ):
							a__:       Any											=(abs(__magic_name__						)).transpose()
							a__:       List[str]											=abs_z_final[::-1, :]
							pyplot.matshow(abs_z_final < escape_radius						)
							pyplot.title(F"Julia set of ${function_label}$, $c={function_params}$"						)
							pyplot.show()





def 						__lowerCamelCase       (      ):
							warnings.filterwarnings(
							    "ignore"     , category=__magic_name__     , message="overflow encountered in multiply"						)
							warnings.filterwarnings(
							    "ignore"     , category=__magic_name__     , message="invalid value encountered in multiply"     , )
							warnings.filterwarnings(
							    "ignore"     , category=__magic_name__     , message="overflow encountered in absolute"						)
							warnings.filterwarnings(
							    "ignore"     , category=__magic_name__     , message="overflow encountered in exp"						)


if __name__ == "__main__":
		__UpperCAmelCase						  =     prepare_grid(window_size, nb_pixels)

		ignore_overflow_warnings()  # See file header for explanations

		__UpperCAmelCase						  =     24
		__UpperCAmelCase						  =     2 * abs(c_cauliflower) + 1
		__UpperCAmelCase						  =     iterate_function(
		    eval_quadratic_polynomial,
		    c_cauliflower,
		    nb_iterations,
		    z_a,
		    infinity=1.1 * escape_radius,
		)
		show_results('''z^2+c''', c_cauliflower, escape_radius, z_final)

		__UpperCAmelCase						  =     64
		__UpperCAmelCase						  =     2 * abs(c_polynomial_a) + 1
		__UpperCAmelCase						  =     iterate_function(
		    eval_quadratic_polynomial,
		    c_polynomial_a,
		    nb_iterations,
		    z_a,
		    infinity=1.1 * escape_radius,
		)
		show_results('''z^2+c''', c_polynomial_a, escape_radius, z_final)

		__UpperCAmelCase						  =     1_61
		__UpperCAmelCase						  =     2 * abs(c_polynomial_a) + 1
		__UpperCAmelCase						  =     iterate_function(
		    eval_quadratic_polynomial,
		    c_polynomial_a,
		    nb_iterations,
		    z_a,
		    infinity=1.1 * escape_radius,
		)
		show_results('''z^2+c''', c_polynomial_a, escape_radius, z_final)

		__UpperCAmelCase						  =     12
		__UpperCAmelCase						  =     1_0000.0
		__UpperCAmelCase						  =     iterate_function(
		    eval_exponential,
		    c_exponential,
		    nb_iterations,
		    z_a + 2,
		    infinity=1.0E10,
		)
		show_results('''e^z+c''', c_exponential, escape_radius, z_final)










import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


__UpperCAmelCase						  =     10_00_00_00_00_00
__UpperCAmelCase						  =     1_00_00

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





def 						__lowerCamelCase       (      __magic_name__	:  int     , __magic_name__	:  int						):
							a__:       Any											=pa.Table.from_pydict({"col": [0] * chunk_size}						)
							a__:       Optional[Any]											=pa.concat_tables([table] * (num_examples // chunk_size)						)
							return datasets.Dataset(__magic_name__     , fingerprint="table_100B"						)


@dataclass
class 	lowerCamelCase__ :
						_lowerCAmelCase								= 42
						_lowerCAmelCase								= 42
						_lowerCAmelCase								= 42
						_lowerCAmelCase								= 42


						def   _lowerCamelCase			( self						:  Union[str, Any]			):
													a__:       Tuple											=np.random.default_rng(self.seed			)
													a__:       Tuple											=rng.integers(low=self.low      ,       high=self.high      ,       size=self.size			).tolist()


						def __iter__( self						:  Any			):
													return iter(self._sampled_values			)







						def __len__( self						:  Any			):
													return self.size





@get_duration
def 						__lowerCamelCase       (      __magic_name__	:  datasets.Dataset						):
							a__:       Union[str, Any]											=dataset[0]





@get_duration
def 						__lowerCamelCase       (      __magic_name__	:  datasets.Dataset						):
							a__:       Optional[Any]											=dataset[-1]





@get_duration
def 						__lowerCamelCase       (      __magic_name__	:  datasets.Dataset						):
							a__:       List[str]											=dataset[range(len(__magic_name__						) // 2     , len(__magic_name__						) // 2 + 1_024						)]





@get_duration
def 						__lowerCamelCase       (      __magic_name__	:  datasets.Dataset						):
							a__:       Optional[int]											=dataset[RandIter(0     , len(__magic_name__						)     , 1_024     , seed=42						)]





def 						__lowerCamelCase       (      ):
							a__:       Dict											={"num examples": SPEED_TEST_N_EXAMPLES}
							a__:       Union[str, Any]											=(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
							print("generating dataset"						)
							a__:       Dict											=generate_100B_dataset(num_examples=__magic_name__     , chunk_size=__magic_name__						)
							print("Functions"						)
							for func in functions:
														print(func.__name__						)
														a__:       Dict											=func(__magic_name__						)

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


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





