


'''simple docstring'''
from statistics import mean

import numpy as np


def 			a      (			__a ,					__a ,					__a ,					__a   )  ->	list:



					'''simple docstring'''






					UpperCamelCase__   :Optional[Any]												= 0
					# Number of processes finished
					UpperCamelCase__   :Any												= 0
					# Displays the finished process.
					# If it is 0, the performance is completed if it is 1, before the performance.
					UpperCamelCase__   :Union[str, Any]												= [0] * no_of_process
					# List to include calculation results
					UpperCamelCase__   :Union[str, Any]												= [0] * no_of_process

					# Sort by arrival time.
					UpperCamelCase__   :str												= [burst_time[i] for i in np.argsort(__a   )]
					UpperCamelCase__   :Optional[int]												= [process_name[i] for i in np.argsort(__a   )]
					arrival_time.sort()

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

										UpperCamelCase__   :Tuple												= 0
										# Index showing the location of the process being performed
										UpperCamelCase__   :Dict												= 0
										# Saves the current response ratio.
										UpperCamelCase__   :Optional[Any]												= 0
										for i in range(0 ,					__a   ):
															if finished_process[i] == 0 and arrival_time[i] <= current_time:
																				UpperCamelCase__   :List[str]												= (burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																				    i
																				]
															if response_ratio < temp:
																				UpperCamelCase__   :Union[str, Any]												= temp
																				UpperCamelCase__   :Optional[Any]												= i

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

					return turn_around_time


def 			a      (			__a ,					__a ,					__a ,					__a   )  ->	list:



					'''simple docstring'''






					UpperCamelCase__   :Dict												= [0] * no_of_process
					for i in range(0 ,					__a   ):
										UpperCamelCase__   :Optional[int]												= turn_around_time[i] - burst_time[i]
					return waiting_time


if __name__ == "__main__":
		__snake_case							      =     5
		__snake_case							      =     ['''A''', '''B''', '''C''', '''D''', '''E''']
		__snake_case							      =     [1, 2, 3, 4, 5]
		__snake_case							      =     [1, 2, 3, 4, 5]

		__snake_case							      =     calculate_turn_around_time(
		    process_name, arrival_time, burst_time, no_of_process
		)
		__snake_case							      =     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}""")



'''simple docstring'''
from datetime import datetime

import matplotlib.pyplot as plt
import torch


def 			a      (			__a   )  ->	int:



					'''simple docstring'''






					for param in module.parameters():
										UpperCamelCase__   :Dict												= False


def 			a      (			)  ->	Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__   :List[Any]												= '''cuda''' if torch.cuda.is_available() else '''cpu'''
					if torch.backends.mps.is_available() and torch.backends.mps.is_built():
										UpperCamelCase__   :Optional[int]												= '''mps'''
					if device == "mps":
										print(
										    '''WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'''
										    ''' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'''
										    ''' with generations.'''   )
					return device


def 			a      (			__a   )  ->	Any:



					'''simple docstring'''






					UpperCamelCase__   :Dict												= plt.imshow(__a   )
					fig.axes.get_xaxis().set_visible(__a   )
					fig.axes.get_yaxis().set_visible(__a   )
					plt.show()







def 			a      (			)  ->	str:



					'''simple docstring'''






					UpperCamelCase__   :int												= datetime.now()
					UpperCamelCase__   :str												= current_time.strftime('''%H:%M:%S'''   )
					return timestamp