






from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def       snake_case_		(     lowerCAmelCase_       :						int      ):

							# A local function to see if a dot lands in the circle.
							def is_in_circle(lowerCAmelCase_       :						float       ,       lowerCAmelCase_       :						float      ) -> bool:
														__lowercase      :							Any				=     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
							__lowercase      :							List[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.
							__lowercase      :							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       snake_case_		(     lowerCAmelCase_       :						int       ,       lowerCAmelCase_       :						Callable[[float], float]       ,       lowerCAmelCase_       :						float = 0.0       ,       lowerCAmelCase_       :						float = 1.0       ,       ):
							return mean(
							    function_to_integrate(uniform(lowerCAmelCase_       ,       lowerCAmelCase_      )      ) for _ in range(lowerCAmelCase_      )      ) * (max_value - min_value)
def       snake_case_		(     lowerCAmelCase_       :						int       ,       lowerCAmelCase_       :						float = 0.0       ,       lowerCAmelCase_       :						float = 1.0      ):

							def identity_function(lowerCAmelCase_       :						float      ) -> float:
														return x

							__lowercase      :							Optional[Any]				=     area_under_curve_estimator(
							    lowerCAmelCase_       ,       lowerCAmelCase_       ,       lowerCAmelCase_       ,       lowerCAmelCase_      )
							__lowercase      :							Tuple				=     (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       snake_case_		(     lowerCAmelCase_       :						int      ):

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

							__lowercase      :							Union[str, 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 warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


lowerCamelCase : Union[str, Any]						   =       logging.get_logger(__name__)

class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					def __init__(  self				:	int		,     *__a				:	Dict		,     **__a				:	Optional[Any]							)			->  None:


												"""simple docstring"""

												warnings.warn(
												    """The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
												    """ use BeitImageProcessor instead."""		,     __a		,     )
												super().__init__(*__a		,     **__a							)