


from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean



def 			lowerCAmelCase (		lowerCAmelCase_ )-> Optional[int]:

				# A local function to see if a dot lands in the circle.
				def is_in_circle(lowerCAmelCase_ ,   lowerCAmelCase_ ) -> bool:
								lowerCAmelCase_ :      Tuple    				=				sqrt((x**2) + (y**2) )
								# Our circle has a radius of 1, so a distance
								# greater than 1 would land outside the circle.
								return distance_from_centre <= 1

				# The proportion of guesses that landed in the circle
				lowerCAmelCase_ :      Any    				=				mean(
				    int(is_in_circle(uniform(-1.0 ,   1.0 ) ,   uniform(-1.0 ,   1.0 ) ) )
				    for _ in range(lowerCAmelCase_ ) )
				# The ratio of the area for circle to square is pi/4.
				lowerCAmelCase_ :      Dict    				=				proportion * 4
				print(f"""The estimated value of pi is {pi_estimate}""" )
				print(f"""The numpy value of pi is {pi}""" )
				print(f"""The total error is {abs(pi - pi_estimate )}""" )



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ = 0.0 ,   lowerCAmelCase_ = 1.0 ,   )-> float:
				return mean(
				    function_to_integrate(uniform(lowerCAmelCase_ ,   lowerCAmelCase_ ) ) for _ in range(lowerCAmelCase_ ) ) * (max_value - min_value)



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ = 0.0 ,   lowerCAmelCase_ = 1.0 )-> None:

				def identity_function(lowerCAmelCase_ ) -> float:
								return x

				lowerCAmelCase_ :      Optional[Any]    				=				area_under_curve_estimator(
				    lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
				lowerCAmelCase_ :      str    				=				(max_value * max_value - min_value * min_value) / 2

				print('''******************''' )
				print(f"""Estimating area under y=x where x varies from {min_value} to {max_value}""" )
				print(f"""Estimated value is {estimated_value}""" )
				print(f"""Expected value is {expected_value}""" )
				print(f"""Total error is {abs(estimated_value - expected_value )}""" )
				print('''******************''' )



def 			lowerCAmelCase (		lowerCAmelCase_ )-> None:

				def function_to_integrate(lowerCAmelCase_ ) -> float:
								return sqrt(4.0 - x * x )

				lowerCAmelCase_ :      List[Any]    				=				area_under_curve_estimator(
				    lowerCAmelCase_ ,   lowerCAmelCase_ ,   0.0 ,   2.0 )

				print('''******************''' )
				print('''Estimating pi using area_under_curve_estimator''' )
				print(f"""Estimated value is {estimated_value}""" )
				print(f"""Expected value is {pi}""" )
				print(f"""Total error is {abs(estimated_value - pi )}""" )
				print('''******************''' )


if __name__ == "__main__":
						import doctest

						doctest.testmod()










import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, Features, Value
from .base import TaskTemplate







@dataclass(frozen=UpperCAmelCase__							)
class 				snake_case__(							UpperCAmelCase__							):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__      :  str					=							field(default="""automatic-speech-recognition""",						metadata={"""include_in_asdict_even_if_is_default""": True}							)
						SCREAMING_SNAKE_CASE__      :  ClassVar[Features]					=							Features({"""audio""": Audio()}							)
						SCREAMING_SNAKE_CASE__      :  ClassVar[Features]					=							Features({"""transcription""": Value("""string"""							)}							)
						SCREAMING_SNAKE_CASE__      :  str					=							"audio"
						SCREAMING_SNAKE_CASE__      :  str					=							"transcription"




						def 						lowercase_ (				self   ,						__lowercase							)					->    int:
										if self.audio_column not in features:
														raise ValueError(f"""Column {self.audio_column} is not present in features."""							)
										if not isinstance(features[self.audio_column]   ,						__lowercase							):
														raise ValueError(f"""Column {self.audio_column} is not an Audio type."""							)
										lowerCAmelCase_ :      List[str]    				=				copy.deepcopy(self							)
										lowerCAmelCase_ :      Optional[Any]    				=				self.input_schema.copy()
										lowerCAmelCase_ :      Optional[Any]    				=				features[self.audio_column]
										lowerCAmelCase_ :      List[str]    				=				input_schema
										return task_template




						@property
						def 						lowercase_ (				self							)					->    Dict[str, str]:
										return {self.audio_column: "audio", self.transcription_column: "transcription"}