




'''simple docstring'''





import random

class      _a       :






					def __init__(				self      ,_SCREAMING_SNAKE_CASE      ,_SCREAMING_SNAKE_CASE					)							->    None:
										_snake_case							=   x
										_snake_case							=   y






					def        _lowercase			(				self					)							->    bool:
										return (self.x**2 + self.y**2) <= 1






					@classmethod
					def        _lowercase			(				cls					)							->    Any:
										return cls(x=random.random()      ,y=random.random()					)







def 			__a			(     _UpperCamelCase:					int					)		->				float:

					"""simple docstring"""




					if number_of_simulations < 1:
										raise ValueError("At least one simulation is necessary to estimate PI."					)

					_snake_case							=   0
					for _ in range(_UpperCamelCase					):
										_snake_case							=   Point.random_unit_square()

										if random_point.is_in_unit_circle():
															number_in_unit_circle += 1

					return 4 * number_in_unit_circle / number_of_simulations


if __name__ == "__main__":
			# import doctest

			# doctest.testmod()
			from math import pi

			UpperCamelCase_		:    List[str]									=		'''Please enter the desired number of Monte Carlo simulations: '''
			UpperCamelCase_		:    List[Any]									=		estimate_pi(int(input(prompt).strip()))
			print(F'An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}')








'''simple docstring'''





UpperCamelCase_		:    Optional[Any]									=		'''
# Diffusers installation
! pip install diffusers transformers datasets accelerate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/diffusers.git
'''

UpperCamelCase_		:    List[Any]									=		[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]


