






from statistics import mean

import numpy as np
def      a_ (      _A      ,   _A      ,   _A      ,   _A  )			->			list:







				"""simple docstring"""
				snake_case__									=     0
				# Number of processes finished
				snake_case__									=     0
				# Displays the finished process.
				# If it is 0, the performance is completed if it is 1, before the performance.
				snake_case__									=     [0] * no_of_process
				# List to include calculation results
				snake_case__									=     [0] * no_of_process

				# Sort by arrival time.
				snake_case__									=     [burst_time[i] for i in np.argsort(_SCREAMING_SNAKE_CASE  )]
				snake_case__									=     [process_name[i] for i in np.argsort(_SCREAMING_SNAKE_CASE  )]
				arrival_time.sort()

				while no_of_process > finished_process_count:
								snake_case__									=     0
								while finished_process[i] == 1:
												i += 1
								if current_time < arrival_time[i]:
												snake_case__									=     arrival_time[i]

								snake_case__									=     0
								# Index showing the location of the process being performed
								snake_case__									=     0
								# Saves the current response ratio.
								snake_case__									=     0
								for i in range(0      ,   _SCREAMING_SNAKE_CASE  ):
												if finished_process[i] == 0 and arrival_time[i] <= current_time:
																snake_case__									=     (burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																    i
																]
												if response_ratio < temp:
																snake_case__									=     temp
																snake_case__									=     i

																# Calculate the turn around time
								snake_case__									=     current_time + burst_time[loc] - arrival_time[loc]
								current_time += burst_time[loc]
								# Indicates that the process has been performed.
								snake_case__									=     1
								# Increase finished_process_count by 1
								finished_process_count += 1

				return turn_around_time
def      a_ (      _A      ,   _A      ,   _A      ,   _A  )			->			list:







				"""simple docstring"""
				snake_case__									=     [0] * no_of_process
				for i in range(0      ,   _SCREAMING_SNAKE_CASE  ):
								snake_case__									=     turn_around_time[i] - burst_time[i]
				return waiting_time


if __name__ == "__main__":
							__UpperCamelCase					:		Tuple	  =						5
							__UpperCamelCase					:		str	  =						["""A""", """B""", """C""", """D""", """E"""]
							__UpperCamelCase					:		int	  =						[1, 2, 3, 4, 5]
							__UpperCamelCase					:		Optional[int]	  =						[1, 2, 3, 4, 5]

							__UpperCamelCase					:		List[str]	  =						calculate_turn_around_time(
							    process_name, arrival_time, burst_time, no_of_process
							)
							__UpperCamelCase					:		List[str]	  =						calculate_waiting_time(
							    process_name, turn_around_time, burst_time, no_of_process
							)

							print("""Process name \tArrival time \tBurst time \tTurn around time \tWaiting time""")
							for i in range(0, no_of_process):
														print(
														    f'''{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'''
														    f'''{turn_around_time[i]}\t\t\t{waiting_time[i]}'''
														)

							print(f'''average waiting time : {mean(waiting_time):.5f}''')
							print(f'''average turn around time : {mean(turn_around_time):.5f}''')












def      a_ (      _A      ,   _A  )			->			float:







				"""simple docstring"""
				if digit_amount > 0:
								return round(number - int(_A  )      ,   _A  )
				return number - int(_A  )


if __name__ == "__main__":
							print(decimal_isolate(1.5_3, 0))
							print(decimal_isolate(3_5.3_4_5, 1))
							print(decimal_isolate(3_5.3_4_5, 2))
							print(decimal_isolate(3_5.3_4_5, 3))
							print(decimal_isolate(-1_4.7_8_9, 3))
							print(decimal_isolate(0, 2))
							print(decimal_isolate(-1_4.1_2_3, 1))
							print(decimal_isolate(-1_4.1_2_3, 2))
							print(decimal_isolate(-1_4.1_2_3, 3))




