





"""simple docstring"""




import colorsys

from PIL import Image  # type: ignore






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       float       ,			_lowercase		:       float       ,			_lowercase		:       int   )					->float:






	'''simple docstring'''






	a :						Optional[int]      =							x
	a :						Dict      =							y
	for step in range(_lowercase   ):  # noqa: B007
		a :						int      =							a * a - b * b + x
		a :						Optional[int]      =							2 * a * b + y
		a :						Optional[Any]      =							a_new

		# divergence happens for all complex number with an absolute value
		# greater than 4
		if a * a + b * b > 4:
			break
	return step / (max_step - 1)






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       float   )					->tuple:






	'''simple docstring'''






	if distance == 1:
		return (0, 0, 0)
	else:
		return (255, 255, 255)






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       float   )					->tuple:






	'''simple docstring'''






	if distance == 1:
		return (0, 0, 0)
	else:
		return tuple(round(i * 255   ) for i in colorsys.hsv_to_rgb(_lowercase       ,			1       ,			1   )   )






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       int = 800       ,			_lowercase		:       int = 600       ,			_lowercase		:       float = -0.6       ,			_lowercase		:       float = 0       ,			_lowercase		:       float = 3.2       ,			_lowercase		:       int = 50       ,			_lowercase		:       bool = True       ,			)					->Image.Image:






	'''simple docstring'''






	a :						List[str]      =							Image.new("RGB"       ,			(image_width, image_height)   )
	a :						Optional[int]      =							img.load()

	# loop through the image-coordinates
	for image_x in range(_lowercase   ):
		for image_y in range(_lowercase   ):
			# determine the figure-coordinates based on the image-coordinates
			a :						List[str]      =							figure_width / image_width * image_height
			a :						str      =							figure_center_x + (image_x / image_width - 0.5) * figure_width
			a :						Optional[Any]      =							figure_center_y + (image_y / image_height - 0.5) * figure_height

			a :						Dict      =							get_distance(_lowercase       ,			_lowercase       ,			_lowercase   )

			# color the corresponding pixel based on the selected coloring-function
			if use_distance_color_coding:
				a :						Union[str, Any]      =							get_color_coded_rgb(_lowercase   )
			else:
				a :						Optional[int]      =							get_black_and_white_rgb(_lowercase   )

	return img


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		# colored version, full figure
		a		:					Optional[Any]	      =     get_image()

		# uncomment for colored version, different section, zoomed in
		# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
		# figure_width = 0.8)

		# uncomment for black and white version, full figure
		# img = get_image(use_distance_color_coding = False)

		# uncomment to save the image
		# img.save("mandelbrot.png")

		img.show()









"""simple docstring"""




from __future__ import annotations

from statistics import mean






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list[int]       ,			_lowercase		:       list[int]       ,			_lowercase		:       int   )					->list[int]:






	'''simple docstring'''






	a :						Union[str, Any]      =							[0] * no_of_processes
	a :						int      =							[0] * no_of_processes

	# Initialize remaining_time to waiting_time.

	for i in range(_lowercase   ):
		a :						List[Any]      =							burst_time[i]
	a :						list[int]      =							[]

	a :						List[Any]      =							0
	a :						Any      =							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 :						str      =							[]
		a :						Tuple      =							-1

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

		if len(_lowercase   ) > 0:
			a :						List[Any]      =							ready_process[0]
			for i in ready_process:
				if remaining_time[i] < remaining_time[target_process]:
					a :						Optional[Any]      =							i
			total_time += burst_time[target_process]
			completed += 1
			a :						str      =							0
			a :						Union[str, Any]      =							(
			    total_time - arrival_time[target_process] - burst_time[target_process]
			)
		else:
			total_time += 1

	return waiting_time






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list[int]       ,			_lowercase		:       int       ,			_lowercase		:       list[int]   )					->list[int]:






	'''simple docstring'''






	a :						List[str]      =							[0] * no_of_processes
	for i in range(_lowercase   ):
		a :						Optional[int]      =							burst_time[i] + waiting_time[i]
	return turn_around_time


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

		a		:					Dict	      =     4
		a		:					Tuple	      =     [2, 5, 3, 7]
		a		:					List[Any]	      =     [0, 0, 0, 0]
		a		:					int	      =     calculate_waitingtime(arrival_time, burst_time, no_of_processes)
		a		:					List[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}''')


