




from statistics import mean

import numpy as np

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	Union[str, Any]     ,							lowercase     :	Optional[Any]     ,							lowercase     :	Tuple     ,							lowercase     :	Union[str, Any]					):


      '''simple docstring'''



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

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

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

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

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

      return turn_around_time

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	str     ,							lowercase     :	Dict     ,							lowercase     :	str     ,							lowercase     :	List[Any]					):


      '''simple docstring'''



      lowerCamelCase_							=   [0] * no_of_process
      for i in range(0     ,							_UpperCAmelCase					):
            lowerCamelCase_							=   turn_around_time[i] - burst_time[i]
      return waiting_time


if __name__ == "__main__":
   lowerCamelCase    :		List[str]			   =       5
   lowerCamelCase    :		Tuple			   =       ["A", "B", "C", "D", "E"]
   lowerCamelCase    :		Union[str, Any]			   =       [1, 2, 3, 4, 5]
   lowerCamelCase    :		str			   =       [1, 2, 3, 4, 5]

   lowerCamelCase    :		int			   =       calculate_turn_around_time(
       process_name, arrival_time, burst_time, no_of_process
   )
   lowerCamelCase    :		Tuple			   =       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}""")









from ..utils import DummyObject, requires_backends







class   A(						metaclass=UpperCamelCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						['''transformers''', '''torch''', '''note_seq''']

 def __init__(    self :  Any						,							*A_ :  Any						,							**A_ :  Tuple  )       ->     List[Any]:

       """simple docstring"""






       requires_backends(self						,							['transformers', 'torch', 'note_seq']  )

 @classmethod
 def     a__			(    cls :  Tuple						,							*A_ :  Dict						,							**A_ :  Optional[Any]  )       ->     Union[str, Any]:

       """simple docstring"""






       requires_backends(cls						,							['transformers', 'torch', 'note_seq']  )





 @classmethod
 def     a__			(    cls :  int						,							*A_ :  Dict						,							**A_ :  List[str]  )       ->     Tuple:

       """simple docstring"""






       requires_backends(cls						,							['transformers', 'torch', 'note_seq']  )



