





"""simple docstring"""




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




def _a (  SCREAMING_SNAKE_CASE__      :  int       )	->    Any:

							'''simple docstring'''






							def is_in_circle(SCREAMING_SNAKE_CASE__      :  float			,				SCREAMING_SNAKE_CASE__      :  float       ) -> bool:
														SCREAMING_SNAKE_CASE__       :      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
							SCREAMING_SNAKE_CASE__       :      List[Any]     =						mean(
							    int(is_in_circle(uniform(-1.0			,				1.0       )			,				uniform(-1.0			,				1.0       )       )       )
							    for _ in range(SCREAMING_SNAKE_CASE__       )       )
							# The ratio of the area for circle to square is pi/4.
							SCREAMING_SNAKE_CASE__       :      int     =						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 _a (  SCREAMING_SNAKE_CASE__      :  int			,				SCREAMING_SNAKE_CASE__      :  Callable[[float], float]			,				SCREAMING_SNAKE_CASE__      :  float = 0.0			,				SCREAMING_SNAKE_CASE__      :  float = 1.0			,				)	->    float:

							'''simple docstring'''






							return mean(
							    function_to_integrate(uniform(SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__       )       ) for _ in range(SCREAMING_SNAKE_CASE__       )       ) * (max_value - min_value)




def _a (  SCREAMING_SNAKE_CASE__      :  int			,				SCREAMING_SNAKE_CASE__      :  float = 0.0			,				SCREAMING_SNAKE_CASE__      :  float = 1.0       )	->    None:

							'''simple docstring'''






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

							SCREAMING_SNAKE_CASE__       :      Any     =						area_under_curve_estimator(
							    SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__       )
							SCREAMING_SNAKE_CASE__       :      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 _a (  SCREAMING_SNAKE_CASE__      :  int       )	->    None:

							'''simple docstring'''






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

							SCREAMING_SNAKE_CASE__       :      List[Any]     =						area_under_curve_estimator(
							    SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__			,				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()













from __future__ import annotations




def _a (  SCREAMING_SNAKE_CASE__      :  list[float]			,				SCREAMING_SNAKE_CASE__      :  list[float]       )	->    float:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      List[Any]     =						sorted(numsa + numsa       )
							SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Dict     =						divmod(len(SCREAMING_SNAKE_CASE__       )			,				2       )
							if mod == 1:
														return all_numbers[div]
							else:
														return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		_lowerCamelCase :    List[str]  							= [float(x) for x in input('''Enter the elements of first array: ''').split()]
		_lowerCamelCase :    Any  							= [float(x) for x in input('''Enter the elements of second array: ''').split()]
		print(f"The median of two arrays is: {median_of_two_arrays(array_a, array_a)}")






