





from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__lowerCamelCase :  List[Any]										=  1.0_5_4_5_7_1_8_1_7E-3_4  # unit of ℏ : J * s

__lowerCamelCase :  Optional[Any]										=  3E8  # unit of c : m * s^-1



def 	A_       (  _lowerCAmelCase							,     _lowerCAmelCase							,     _lowerCAmelCase  )		->				Dict:

 if (force, area, distance).count(0  ) != 1:
  raise ValueError("One and only one argument must be 0"  )
 if force < 0:
  raise ValueError("Magnitude of force can not be negative"  )
 if distance < 0:
  raise ValueError("Distance can not be negative"  )
 if area < 0:
  raise ValueError("Area can not be negative"  )
 if force == 0:
  UpperCamelCase			:      int			=     (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
      240 * (distance) ** 4
  )
  return {"force": force}
 elif area == 0:
  UpperCamelCase			:      Tuple			=     (240 * force * (distance) ** 4) / (
      REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
  )
  return {"area": area}
 elif distance == 0:
  UpperCamelCase			:      Dict			=     (
      (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (240 * force)
  ) ** (1 / 4)
  return {"distance": distance}
 raise ValueError("One and only one argument must be 0"  )


# Run doctest
if __name__ == "__main__":
    import doctest

    doctest.testmod()







from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream



class       A__     ( __snake_case    ):





      def __init__(				self ,							A_ ,							A_ = None ,							A_ = None ,							A_ = False ,							A_ = False ,							A_ = None ,							A_ = None ,							**A_ ,							):
       '''simple docstring'''




       super().__init__(
           features=A_ ,							cache_dir=A_ ,							keep_in_memory=A_ ,							streaming=A_ ,							num_proc=A_ ,							**A_ ,							)
       UpperCamelCase			:      Optional[int] 			=     Generator(
           cache_dir=A_ ,							features=A_ ,							generator=A_ ,							gen_kwargs=A_ ,							**A_ ,							)





      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       if self.streaming:
        UpperCamelCase			:      Optional[Any] 			=     self.builder.as_streaming_dataset(split="train"     )
       # Build regular (map-style) dataset
       else:
        UpperCamelCase			:      Union[str, Any] 			=     None
        UpperCamelCase			:      Union[str, Any] 			=     None
        UpperCamelCase			:      List[Any] 			=     None
        UpperCamelCase			:      List[str] 			=     None

        self.builder.download_and_prepare(
            download_config=A_ ,							download_mode=A_ ,							verification_mode=A_ ,							base_path=A_ ,							num_proc=self.num_proc ,							)
        UpperCamelCase			:      int 			=     self.builder.as_dataset(
            split="train" ,							verification_mode=A_ ,							in_memory=self.keep_in_memory     )
       return dataset
