






from __future__ import annotations

from collections import deque
from queue import Queue
from timeit import timeit

SCREAMING_SNAKE_CASE__		:       Optional[int]   							=							{
    """A""": ["""B""", """C"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E"""],
}





def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> list[str]:

     '''simple docstring'''
     UpperCAmelCase__			:     Dict										= {start}
     UpperCAmelCase__			:     Optional[Any]										= [start]
     UpperCAmelCase__			:     Queue										= Queue()
     queue.put(__lowerCamelCase					)
     while not queue.empty():
          UpperCAmelCase__			:     str										= queue.get()
          for w in graph[v]:
               if w not in explored:
                    explored.add(__lowerCamelCase					)
                    result.append(__lowerCamelCase					)
                    queue.put(__lowerCamelCase					)
     return result





def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> list[str]:

     '''simple docstring'''
     UpperCAmelCase__			:     Optional[Any]										= {start}
     UpperCAmelCase__			:     Optional[Any]										= [start]
     UpperCAmelCase__			:     List[str]										= deque([start]					)
     while queue:
          UpperCAmelCase__			:     Union[str, Any]										= queue.popleft()
          for child in graph[v]:
               if child not in visited:
                    visited.add(__lowerCamelCase					)
                    result.append(__lowerCamelCase					)
                    queue.append(__lowerCamelCase					)
     return result





def    _lowerCamelCase	(	__lowerCamelCase					)   -> None:

     '''simple docstring'''
     UpperCAmelCase__			:     Any										= F"from __main__ import G, {name}"
     UpperCAmelCase__			:     List[str]										= 1_0000
     UpperCAmelCase__			:     str										= timeit(F"{name}(G, 'A')"   ,       setup=__lowerCamelCase   ,       number=__lowerCamelCase					)
     print(F"{name:<35} finished {number} runs in {res:.5f} seconds"					)


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      benchmark_function("""breadth_first_search""")
      benchmark_function("""breadth_first_search_with_deque""")
      # breadth_first_search                finished 10000 runs in 0.20999 seconds
      # breadth_first_search_with_deque     finished 10000 runs in 0.01421 seconds














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()






