
from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream







class        lowerCAmelCase__      (   __lowercase	):

						def __init__(			self       ,							a       ,							a = None       ,							a = None       ,							a = False       ,							a = False       ,							a = None       ,							a = None       ,							**a       ,							)					->      str:


								'''simple docstring'''

								super().__init__(
								    features=a       ,							cache_dir=a       ,							keep_in_memory=a       ,							streaming=a       ,							num_proc=a       ,							**a       ,							)
								_UpperCamelCase						    =	Generator(
								    cache_dir=a       ,							features=a       ,							generator=a       ,							gen_kwargs=a       ,							**a       ,							)







						def  A_				(			self				)					->      Optional[Any]:


								'''simple docstring'''

								if self.streaming:
										_UpperCamelCase						    =	self.builder.as_streaming_dataset(split="""train"""				)
								# Build regular (map-style) dataset
								else:
										_UpperCamelCase						    =	None
										_UpperCamelCase						    =	None
										_UpperCamelCase						    =	None
										_UpperCamelCase						    =	None

										self.builder.download_and_prepare(
										    download_config=a       ,							download_mode=a       ,							verification_mode=a       ,							base_path=a       ,							num_proc=self.num_proc       ,							)
										_UpperCamelCase						    =	self.builder.as_dataset(
										    split="""train"""       ,							verification_mode=a       ,							in_memory=self.keep_in_memory				)
								return dataset





from math import isclose, sqrt


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				tuple[float, float, float]:

		"""simple docstring"""






		_UpperCamelCase						    =	point_y / 4 / point_x
		_UpperCamelCase						    =	2 * normal_gradient / (1 + normal_gradient * normal_gradient)
		_UpperCamelCase						    =	(1 - normal_gradient * normal_gradient) / (
		    1 + normal_gradient * normal_gradient
		)
		_UpperCamelCase						    =	(sa - ca * incoming_gradient) / (ca + sa * incoming_gradient)

		# to find the next point, solve the simultaeneous equations:
		# y^2 + 4x^2 = 100
		# y - b = m * (x - a)
		# ==> A x^2 + B x + C = 0
		_UpperCamelCase						    =	outgoing_gradient**2 + 4
		_UpperCamelCase						    =	2 * outgoing_gradient * (point_y - outgoing_gradient * point_x)
		_UpperCamelCase						    =	(point_y - outgoing_gradient * point_x) ** 2 - 1_0_0

		_UpperCamelCase						    =	(
		    -linear_term - sqrt(linear_term**2 - 4 * quadratic_term * constant_term )
		) / (2 * quadratic_term)
		_UpperCamelCase						    =	(
		    -linear_term + sqrt(linear_term**2 - 4 * quadratic_term * constant_term )
		) / (2 * quadratic_term)

		# two solutions, one of which is our input point
		_UpperCamelCase						    =	x_minus if isclose(lowerCAmelCase						,  lowerCAmelCase ) else x_plus
		_UpperCamelCase						    =	point_y + outgoing_gradient * (next_x - point_x)

		return next_x, next_y, outgoing_gradient


def 							__A(lowerCAmelCase = 1.4						,  lowerCAmelCase = -9.6 )		->				int:

		"""simple docstring"""






		_UpperCamelCase						    =	0
		_UpperCamelCase						    =	first_x_coord
		_UpperCamelCase						    =	first_y_coord
		_UpperCamelCase						    =	(10.1 - point_y) / (0.0 - point_x)

		while not (-0.01 <= point_x <= 0.01 and point_y > 0):
				_UpperCamelCase    ,	_UpperCamelCase    ,	_UpperCamelCase						    =	next_point(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )
				num_reflections += 1

		return num_reflections


if __name__ == "__main__":
		print(F"""{solution() = }""")



