






'''simple docstring'''







from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase    ,      UpperCamelCase				):
							lowerCamelCase__ :     Any	  =	k_size // 2
							lowerCamelCase__ :     Optional[int]	  =	mgrid[0 - center : k_size - center, 0 - center : k_size - center]
							lowerCamelCase__ :     Optional[int]	  =	1 / (2 * pi * sigma) * exp(-(square(UpperCamelCase				) + square(UpperCamelCase				)) / (2 * square(UpperCamelCase				))				)
							return g





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase    ,      UpperCamelCase    ,      UpperCamelCase				):
							lowerCamelCase__ :     List[str]	  =	image.shape[0], image.shape[1]
							# dst image height and width
							lowerCamelCase__ :     Dict	  =	height - k_size + 1
							lowerCamelCase__ :     Dict	  =	width - k_size + 1

							# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
							lowerCamelCase__ :     int	  =	zeros((dst_height * dst_width, k_size * k_size)				)
							lowerCamelCase__ :     Optional[Any]	  =	0
							for i, j in product(range(UpperCamelCase				)    ,      range(UpperCamelCase				)				):
														lowerCamelCase__ :     int	  =	ravel(image[i : i + k_size, j : j + k_size]				)
														lowerCamelCase__ :     List[Any]	  =	window
														row += 1

							#  turn the kernel into shape(k*k, 1)
							lowerCamelCase__ :     Tuple	  =	gen_gaussian_kernel(UpperCamelCase    ,      UpperCamelCase				)
							lowerCamelCase__ :     List[Any]	  =	ravel(UpperCamelCase				)

							# reshape and get the dst image
							lowerCamelCase__ :     Dict	  =	dot(UpperCamelCase    ,      UpperCamelCase				).reshape(UpperCamelCase    ,      UpperCamelCase				).astype(UpperCamelCase				)

							return dst


if __name__ == "__main__":
			# read original image
			_A     :      Any   					=imread(r'''../image_data/lena.jpg''')
			# turn image in gray scale value
			_A     :      Tuple   					=cvtColor(img, COLOR_BGR2GRAY)

			# get values with two different mask size
			_A     :      str   					=gaussian_filter(gray, 3, sigma=1)
			_A     :      Optional[Any]   					=gaussian_filter(gray, 5, sigma=0.8)

			# show result images
			imshow('''gaussian filter with 3x3 mask''', gaussianaxa)
			imshow('''gaussian filter with 5x5 mask''', gaussianaxa)
			waitKey()









'''simple docstring'''







from collections import deque

class _lowercase     :




							def __init__(							self:    int      ,							UpperCamelCase__:    str      ,							UpperCamelCase__:    int      ,							UpperCamelCase__:    int					):
														lowerCamelCase__ :     int	  =	process_name  # process name
														lowerCamelCase__ :     int	  =	arrival_time  # arrival time of the process
														# completion time of finished process or last interrupted time
														lowerCamelCase__ :     List[str]	  =	arrival_time
														lowerCamelCase__ :     Tuple	  =	burst_time  # remaining burst time
														lowerCamelCase__ :     str	  =	0  # total time of the process wait in ready queue
														lowerCamelCase__ :     Optional[Any]	  =	0  # time from arrival time to completion time



class _lowercase     :




							def __init__(							self:    Any      ,							UpperCamelCase__:    int      ,							UpperCamelCase__:    list[int]      ,							UpperCamelCase__:    deque[Process]      ,							UpperCamelCase__:    int      ,							):
														# total number of mlfq's queues
														lowerCamelCase__ :     Tuple	  =	number_of_queues
														# time slice of queues that round robin algorithm applied
														lowerCamelCase__ :     List[Any]	  =	time_slices
														# unfinished process is in this ready_queue
														lowerCamelCase__ :     int	  =	queue
														# current time
														lowerCamelCase__ :     Optional[int]	  =	current_time
														# finished process is in this sequence queue
														lowerCamelCase__ :     deque[Process]	  =	deque()




							def 		lowerCamelCase_    (							self:    Union[str, Any]					):
														lowerCamelCase__ :     Union[str, Any]	  =	[]
														for i in range(len(self.finish_queue					)					):
																					sequence.append(self.finish_queue[i].process_name					)
														return sequence




							def 		lowerCamelCase_    (							self:    Union[str, Any]      ,							UpperCamelCase__:    list[Process]					):
														lowerCamelCase__ :     int	  =	[]
														for i in range(len(UpperCamelCase__					)					):
																					waiting_times.append(queue[i].waiting_time					)
														return waiting_times




							def 		lowerCamelCase_    (							self:    Any      ,							UpperCamelCase__:    list[Process]					):
														lowerCamelCase__ :     Optional[int]	  =	[]
														for i in range(len(UpperCamelCase__					)					):
																					turnaround_times.append(queue[i].turnaround_time					)
														return turnaround_times




							def 		lowerCamelCase_    (							self:    Union[str, Any]      ,							UpperCamelCase__:    list[Process]					):
														lowerCamelCase__ :     List[Any]	  =	[]
														for i in range(len(UpperCamelCase__					)					):
																					completion_times.append(queue[i].stop_time					)
														return completion_times




							def 		lowerCamelCase_    (							self:    int      ,							UpperCamelCase__:    deque[Process]					):
														return [q.burst_time for q in queue]




							def 		lowerCamelCase_    (							self:    List[str]      ,							UpperCamelCase__:    Process					):
														process.waiting_time += self.current_time - process.stop_time
														return process.waiting_time




							def 		lowerCamelCase_    (							self:    Optional[Any]      ,							UpperCamelCase__:    deque[Process]					):
														lowerCamelCase__ :     deque[Process]	  =	deque()  # sequence deque of finished process
														while len(UpperCamelCase__					) != 0:
																					lowerCamelCase__ :     List[Any]	  =	ready_queue.popleft()  # current process

																					# if process's arrival time is later than current time, update current time
																					if self.current_time < cp.arrival_time:
																												self.current_time += cp.arrival_time

																					# update waiting time of current process
																					self.update_waiting_time(UpperCamelCase__					)
																					# update current time
																					self.current_time += cp.burst_time
																					# finish the process and set the process's burst-time 0
																					lowerCamelCase__ :     Dict	  =	0
																					# set the process's turnaround time because it is finished
																					lowerCamelCase__ :     List[str]	  =	self.current_time - cp.arrival_time
																					# set the completion time
																					lowerCamelCase__ :     int	  =	self.current_time
																					# add the process to queue that has finished queue
																					finished.append(UpperCamelCase__					)

														self.finish_queue.extend(UpperCamelCase__					)  # add finished process to finish queue
														# FCFS will finish all remaining processes
														return finished




							def 		lowerCamelCase_    (							self:    Union[str, Any]      ,							UpperCamelCase__:    deque[Process]      ,							UpperCamelCase__:    int					):
														lowerCamelCase__ :     deque[Process]	  =	deque()  # sequence deque of terminated process
														# just for 1 cycle and unfinished processes will go back to queue
														for _ in range(len(UpperCamelCase__					)					):
																					lowerCamelCase__ :     Optional[int]	  =	ready_queue.popleft()  # current process

																					# if process's arrival time is later than current time, update current time
																					if self.current_time < cp.arrival_time:
																												self.current_time += cp.arrival_time

																					# update waiting time of unfinished processes
																					self.update_waiting_time(UpperCamelCase__					)
																					# if the burst time of process is bigger than time-slice
																					if cp.burst_time > time_slice:
																												# use CPU for only time-slice
																												self.current_time += time_slice
																												# update remaining burst time
																												cp.burst_time -= time_slice
																												# update end point time
																												lowerCamelCase__ :     Dict	  =	self.current_time
																												# locate the process behind the queue because it is not finished
																												ready_queue.append(UpperCamelCase__					)
																					else:
																												# use CPU for remaining burst time
																												self.current_time += cp.burst_time
																												# set burst time 0 because the process is finished
																												lowerCamelCase__ :     Any	  =	0
																												# set the finish time
																												lowerCamelCase__ :     List[Any]	  =	self.current_time
																												# update the process' turnaround time because it is finished
																												lowerCamelCase__ :     Any	  =	self.current_time - cp.arrival_time
																												# add the process to queue that has finished queue
																												finished.append(UpperCamelCase__					)

														self.finish_queue.extend(UpperCamelCase__					)  # add finished process to finish queue
														# return finished processes queue and remaining processes queue
														return finished, ready_queue




							def 		lowerCamelCase_    (							self:    Tuple					):

														#  all queues except last one have round_robin algorithm
														for i in range(self.number_of_queues - 1					):
																					lowerCamelCase__  ,		lowerCamelCase__ :     str	  =	self.round_robin(
																					    self.ready_queue      ,							self.time_slices[i]					)
														#  the last queue has first_come_first_served algorithm
														self.first_come_first_served(self.ready_queue					)

														return self.finish_queue


if __name__ == "__main__":
			import doctest

			_A     :      Optional[Any]   					=Process('''P1''', 0, 53)
			_A     :      List[Any]   					=Process('''P2''', 0, 17)
			_A     :      Any   					=Process('''P3''', 0, 68)
			_A     :      Tuple   					=Process('''P4''', 0, 24)
			_A     :      int   					=3
			_A     :      Tuple   					=[17, 25]
			_A     :      List[Any]   					=deque([Pa, Pa, Pa, Pa])

			if len(time_slices) != number_of_queues - 1:
						raise SystemExit(0)

			doctest.testmod(extraglobs={'''queue''': deque([Pa, Pa, Pa, Pa])})

			_A     :      Dict   					=Process('''P1''', 0, 53)
			_A     :      Union[str, Any]   					=Process('''P2''', 0, 17)
			_A     :      int   					=Process('''P3''', 0, 68)
			_A     :      Dict   					=Process('''P4''', 0, 24)
			_A     :      List[str]   					=3
			_A     :      List[Any]   					=[17, 25]
			_A     :      Any   					=deque([Pa, Pa, Pa, Pa])
			_A     :      List[str]   					=MLFQ(number_of_queues, time_slices, queue, 0)
			_A     :      Union[str, Any]   					=mlfq.multi_level_feedback_queue()

			# print total waiting times of processes(P1, P2, P3, P4)
			print(
			    F'waiting time:\
        \t\t\t{MLFQ.calculate_waiting_time(mlfq, [Pa, Pa, Pa, Pa])}'
			)
			# print completion times of processes(P1, P2, P3, P4)
			print(
			    F'completion time:\
        \t\t{MLFQ.calculate_completion_time(mlfq, [Pa, Pa, Pa, Pa])}'
			)
			# print total turnaround times of processes(P1, P2, P3, P4)
			print(
			    F'turnaround time:\
        \t\t{MLFQ.calculate_turnaround_time(mlfq, [Pa, Pa, Pa, Pa])}'
			)
			# print sequence of finished processes
			print(
			    F'sequence of finished processes:\
        {mlfq.calculate_sequence_of_finish_queue()}'
			)

