


'''simple docstring'''



def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       float						,				_SCREAMING_SNAKE_CASE				:       float						,				_SCREAMING_SNAKE_CASE				:       float						,				_SCREAMING_SNAKE_CASE				:       float						,				_SCREAMING_SNAKE_CASE				:       float						,				):
					__a      :	Dict    =  [redshift, radiation_density, matter_density, dark_energy]
					if any(p < 0 for p in parameters       ):
										raise ValueError('All input parameters must be positive'       )

					if any(p > 1 for p in parameters[1:4]       ):
										raise ValueError('Relative densities cannot be greater than one'       )
					else:
										__a      :	Optional[int]    =  1 - (matter_density + radiation_density + dark_energy)

										__a      :	str    =  (
										    radiation_density * (redshift + 1) ** 4
										    + matter_density * (redshift + 1) ** 3
										    + curvature * (redshift + 1) ** 2
										    + dark_energy
										)

										__a      :	Union[str, Any]    =  hubble_constant * e_a ** (1 / 2)
										return hubble


if __name__ == "__main__":
	import doctest

	# run doctest
	doctest.testmod()

	# demo LCDM approximation
	__lowercase     :						Any	=     0.3

	print(
	    hubble_parameter(
	        hubble_constant=68.3,
	        radiation_density=1E-4,
	        matter_density=matter_density,
	        dark_energy=1 - matter_density,
	        redshift=0,
	    )
	)







'''simple docstring'''



import re

from filelock import FileLock


try:
	import nltk

	__lowercase     :						Optional[Any]	=     True
except (ImportError, ModuleNotFoundError):
	__lowercase     :						Dict	=     False

if NLTK_AVAILABLE:
	with FileLock('.lock') as lock:
		nltk.download('punkt', quiet=True)






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       str       ):
					re.sub('<n>'						,				''						,				_SCREAMING_SNAKE_CASE       )  # remove pegasus newline char
					assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
					return "\n".join(nltk.sent_tokenize(_SCREAMING_SNAKE_CASE       )       )



