





def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__							,):
		lowerCamelCase_	:     Optional[Any] 						=      [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:
				lowerCamelCase_	:     Optional[Any] 						=      1 - (matter_density + radiation_density + dark_energy)

				lowerCamelCase_	:     Optional[int] 						=      (
				    radiation_density * (redshift + 1) ** 4
				    + matter_density * (redshift + 1) ** 3
				    + curvature * (redshift + 1) ** 2
				    + dark_energy
				)

				lowerCamelCase_	:     Optional[Any] 						=      hubble_constant * e_a ** (1 / 2)
				return hubble


if __name__ == "__main__":
		import doctest

		# run doctest
		doctest.testmod()

		# demo LCDM approximation
		_lowercase		:  Optional[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,
		    )
		)







_lowercase		:  Optional[Any]			       ="""
# Transformers installation
! pip install transformers datasets
# 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/transformers.git
"""

_lowercase		:  Union[str, Any]			       =[{"""type""": """code""", """content""": INSTALL_CONTENT}]
_lowercase		:  List[Any]			       ={
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}
