code: 
  
  
  
  
  
  
  from __future__ import annotations
  
  SCREAMING_SNAKE_CASE__		:       List[str]   							=							"""Alexander Joslin"""
  
  
  
  
  
  def    _lowerCamelCase	(	__lowerCamelCase					)   -> int:
  
       '''simple docstring'''
  
       if number <= 0:
            UpperCAmelCase__			:     Tuple										= F"n must be greater than 0. Got n = {number}"
            raise ValueError(__lowerCamelCase					)
  
       UpperCAmelCase__			:     List[Any]										= [number + 1] * (number + 1)
  
       # starting position
       UpperCAmelCase__			:     Optional[Any]										= 0
       for i in range(1   ,       __lowerCamelCase					):
            UpperCAmelCase__			:     str										= min(table[i + 1]   ,       table[i] + 1					)
            # check if out of bounds
            if i * 2 <= number:
                 UpperCAmelCase__			:     int										= min(table[i * 2]   ,       table[i] + 1					)
            # check if out of bounds
            if i * 3 <= number:
                 UpperCAmelCase__			:     Dict										= min(table[i * 3]   ,       table[i] + 1					)
       return table[number]
  
  
  if __name__ == "__main__":
        import doctest
  
        doctest.testmod()
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  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()
  
  
  
  
  
  
  