
"""simple docstring"""





from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros







def 			__a  (	__lowerCamelCase,	__lowerCamelCase						):
   UpperCAmelCase_  ,     UpperCAmelCase_      :      Any      =					image.shape
   UpperCAmelCase_      :      str      =					cols - block_size[1] + 1
   UpperCAmelCase_      :      Dict      =					rows - block_size[0] + 1
   UpperCAmelCase_      :      Optional[int]      =					zeros((dst_height * dst_width, block_size[1] * block_size[0])						)
   UpperCAmelCase_      :      str      =					0
   for i in range(0,	__lowerCamelCase						):
      for j in range(0,	__lowerCamelCase						):
         UpperCAmelCase_      :      List[str]      =					ravel(image[i : i + block_size[0], j : j + block_size[1]]						)
         UpperCAmelCase_      :      Optional[Any]      =					window
         row += 1

   return image_array







def 			__a  (	__lowerCamelCase,	__lowerCamelCase						):
   UpperCAmelCase_  ,     UpperCAmelCase_      :      Optional[Any]      =					image.shape[0], image.shape[1]
   UpperCAmelCase_      :      Optional[Any]      =					filter_kernel.shape[0]
   UpperCAmelCase_      :      int      =					k_size // 2
   # Pads image with the edge values of array.
   UpperCAmelCase_      :      List[str]      =					pad(__lowerCamelCase,	__lowerCamelCase,	mode="edge"						)

   # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
   UpperCAmelCase_      :      int      =					imacol(__lowerCamelCase,	(k_size, k_size)						)

   #  turn the kernel into shape(k*k, 1)
   UpperCAmelCase_      :      int      =					ravel(__lowerCamelCase						)
   # reshape and get the dst image
   UpperCAmelCase_      :      int      =					dot(__lowerCamelCase,	__lowerCamelCase						).reshape(__lowerCamelCase,	__lowerCamelCase						)
   return dst


if __name__ == "__main__":
    # read original image
    _a	 =							imread(R'../image_data/lena.jpg')
    # turn image in gray scale value
    _a	 =							cvtColor(img, COLOR_BGR2GRAY)
    # Laplace operator
    _a	 =							array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
    _a	 =							img_convolve(gray, Laplace_kernel).astype(uinta)
    imshow('Laplacian', out)
    waitKey(0)




"""simple docstring"""





from __future__ import annotations

from statistics import mean







def 			__a  (	__lowerCamelCase						):
   UpperCAmelCase_      :      Dict      =					2
   UpperCAmelCase_      :      Any      =					list(__lowerCamelCase						)
   UpperCAmelCase_      :      List[Any]      =					[0] * len(__lowerCamelCase						)
   UpperCAmelCase_      :      str      =					0
   while True:
      UpperCAmelCase_      :      int      =					True
      for i, burst_time in enumerate(__lowerCamelCase						):
         if rem_burst_times[i] > 0:
            UpperCAmelCase_      :      List[Any]      =					False
            if rem_burst_times[i] > quantum:
               t += quantum
               rem_burst_times[i] -= quantum
            else:
               t += rem_burst_times[i]
               UpperCAmelCase_      :      Optional[int]      =					t - burst_time
               UpperCAmelCase_      :      Union[str, Any]      =					0
      if done is True:
         return waiting_times







def 			__a  (	__lowerCamelCase,	__lowerCamelCase						):
   return [burst + waiting for burst, waiting in zip(__lowerCamelCase,	__lowerCamelCase						)]


if __name__ == "__main__":
    _a	 =							[3, 5, 7]
    _a	 =							calculate_waiting_times(burst_times)
    _a	 =							calculate_turn_around_times(burst_times, waiting_times)
    print('Process ID \tBurst Time \tWaiting Time \tTurnaround Time')
    for i, burst_time in enumerate(burst_times):
        print(
            f"""  {i + 1}\t\t  {burst_time}\t\t  {waiting_times[i]}\t\t  """
            f"""{turn_around_times[i]}"""
        )
    print(f"""\nAverage waiting time = {mean(waiting_times):.5f}""")
    print(f"""Average turn around time = {mean(turn_around_times):.5f}""")


