'''simple docstring'''






from __future__ import annotations

from statistics import mean





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			list[int]   ,		__snake_case							:			list[int]   ,		__snake_case							:			int				):
     _A    		=  [0] * no_of_processes
     _A    		=  [0] * no_of_processes

     # Initialize remaining_time to waiting_time.

     for i in range(__snake_case				):
          _A    		=  burst_time[i]
     _A    		=  []

     _A    		=  0
     _A    		=  0

     # When processes are not completed,
     # A process whose arrival time has passed \
     # and has remaining execution time is put into the ready_process.
     # The shortest process in the ready_process, target_process is executed.

     while completed != no_of_processes:
          _A    		=  []
          _A    		=  -1

          for i in range(__snake_case				):
               if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
                    ready_process.append(__snake_case				)

          if len(__snake_case				) > 0:
               _A    		=  ready_process[0]
               for i in ready_process:
                    if remaining_time[i] < remaining_time[target_process]:
                         _A    		=  i
               total_time += burst_time[target_process]
               completed += 1
               _A    		=  0
               _A    		=  (
                   total_time - arrival_time[target_process] - burst_time[target_process]
               )
          else:
               total_time += 1

     return waiting_time





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			list[int]   ,		__snake_case							:			int   ,		__snake_case							:			list[int]				):
     _A    		=  [0] * no_of_processes
     for i in range(__snake_case				):
          _A    		=  burst_time[i] + waiting_time[i]
     return turn_around_time


if __name__ == "__main__":
   print('''[TEST CASE 01]''')

   _UpperCAmelCase    :     Optional[int]         =       4
   _UpperCAmelCase    :     Optional[int]         =       [2, 5, 3, 7]
   _UpperCAmelCase    :     Tuple         =       [0, 0, 0, 0]
   _UpperCAmelCase    :     int         =       calculate_waitingtime(arrival_time, burst_time, no_of_processes)
   _UpperCAmelCase    :     Union[str, Any]         =       calculate_turnaroundtime(
       burst_time, no_of_processes, waiting_time
   )

   # Printing the Result
   print('''PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time''')
   for i, process_id in enumerate(list(range(1, 5))):
      print(
          F'''{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t'''
          F'''{waiting_time[i]}\t\t\t\t{turn_around_time[i]}'''
      )
   print(F'''\nAverage waiting time = {mean(waiting_time):.5f}''')
   print(F'''Average turnaround time = {mean(turn_around_time):.5f}''')




"""simple docstring"""




import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		if (ksize % 2) == 0:
				lowerCAmelCase__   = ksize + 1
		lowerCAmelCase__   = np.zeros((ksize, ksize)      ,	dtype=np.floataa  )

		# each value
		for y in range(lowerCamelCase__  ):
				for x in range(lowerCamelCase__  ):
						# distance from center
						lowerCAmelCase__   = x - ksize // 2
						lowerCAmelCase__   = y - ksize // 2

						# degree to radiant
						lowerCAmelCase__   = theta / 180 * np.pi
						lowerCAmelCase__   = np.cos(_theta  )
						lowerCAmelCase__   = np.sin(_theta  )

						# get kernel x
						lowerCAmelCase__   = cos_theta * px + sin_theta * py

						# get kernel y
						lowerCAmelCase__   = -sin_theta * px + cos_theta * py

						# fill kernel
						lowerCAmelCase__   = np.exp(
						    -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)  ) * np.cos(2 * np.pi * _x / lambd + psi  )

		return gabor


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			# read original image
			__lowerCAmelCase     :				Tuple    				=    imread("../image_data/lena.jpg")
			# turn image in gray scale value
			__lowerCAmelCase     :				List[str]    				=    cvtColor(img, COLOR_BGR2GRAY)

			# Apply multiple Kernel to detect edges
			__lowerCAmelCase     :				Union[str, Any]    				=    np.zeros(gray.shape[:2])
			for theta in [0, 30, 60, 90, 1_20, 1_50]:
						__lowerCAmelCase     :				Union[str, Any]    				=    gabor_filter_kernel(10, 8, theta, 10, 0, 0)
						out += filteraD(gray, CV_8UC3, kernel_aa)
			__lowerCAmelCase     :				Optional[int]    				=    out / out.max() * 2_55
			__lowerCAmelCase     :				Tuple    				=    out.astype(np.uinta)

			imshow("Original", gray)
			imshow("Gabor filter with 20x20 mask and 6 directions", out)

			waitKey(0)




