






def    _lowerCamelCase	(	)   -> str:

     '''simple docstring'''

     for a in range(300					):
          for b in range(a + 1   ,       400					):
               for c in range(b + 1   ,       500					):
                    if (a + b + c) == 1000 and (a**2) + (b**2) == (c**2):
                         return a * b * c

     return -1





def    _lowerCamelCase	(	)   -> Any:

     '''simple docstring'''

     for a in range(300					):
          for b in range(400					):
               UpperCAmelCase__			:     Optional[int]										= 1000 - a - b
               if a < b < c and (a**2) + (b**2) == (c**2):
                    return a * b * c

     return -1





def    _lowerCamelCase	(	)   -> str:

     '''simple docstring'''
     import timeit

     print(
         timeit.timeit("""solution()"""   ,       setup="""from __main__ import solution"""   ,       number=1000					)					)
     print(
         timeit.timeit(
             """solution_fast()"""   ,       setup="""from __main__ import solution_fast"""   ,       number=1000					)					)


if __name__ == "__main__":
      print(f'''{solution() = }''')














import math
import os

import cva
import numpy as np

SCREAMING_SNAKE_CASE__		:       Optional[Any]   							=							255.0





def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> float:

     '''simple docstring'''
     UpperCAmelCase__			:     List[Any]										= np.mean((original - contrast) ** 2					)
     if mse == 0:
          return 100

     return 20 * math.logaa(PIXEL_MAX / math.sqrt(__lowerCamelCase					)					)





def    _lowerCamelCase	(	)   -> None:

     '''simple docstring'''
     UpperCAmelCase__			:     Union[str, Any]										= os.path.dirname(os.path.realpath(__lowerCamelCase					)					)
     # Loading images (original image and compressed image)
     UpperCAmelCase__			:     List[Any]										= cva.imread(os.path.join(__lowerCamelCase   ,       """image_data/original_image.png"""					)					)
     UpperCAmelCase__			:     Dict										= cva.imread(os.path.join(__lowerCamelCase   ,       """image_data/compressed_image.png"""					)   ,       1					)

     UpperCAmelCase__			:     Tuple										= cva.imread(os.path.join(__lowerCamelCase   ,       """image_data/PSNR-example-base.png"""					)					)
     UpperCAmelCase__			:     int										= cva.imread(
         os.path.join(__lowerCamelCase   ,       """image_data/PSNR-example-comp-10.jpg"""					)   ,       1					)

     # Value expected: 29.73dB
     print("""-- First Test --"""					)
     print(F"PSNR value is {peak_signal_to_noise_ratio(__lowerCamelCase   ,       __lowerCamelCase					)} dB"					)

     # # Value expected: 31.53dB (Wikipedia Example)
     print("""\n-- Second Test --"""					)
     print(F"PSNR value is {peak_signal_to_noise_ratio(__lowerCamelCase   ,       __lowerCamelCase					)} dB"					)


if __name__ == "__main__":
      main()






