


from statistics import mean

import numpy as np

def 		__lowerCAmelCase   (							_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase		)    ->				list:






      '''simple docstring'''

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

      # Sort by arrival time.
      lowerCamelCase__:						List[Any]							   = [burst_time[i] for i in np.argsort(__A		)]
      lowerCamelCase__:						Optional[Any]							   = [process_name[i] for i in np.argsort(__A		)]
      arrival_time.sort()

      while no_of_process > finished_process_count:
            lowerCamelCase__:						Union[str, Any]							   = 0
            while finished_process[i] == 1:
                  i += 1
            if current_time < arrival_time[i]:
                  lowerCamelCase__:						Optional[Any]							   = arrival_time[i]

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

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

      return turn_around_time

def 		__lowerCAmelCase   (							_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase		)    ->				list:






      '''simple docstring'''

      lowerCamelCase__:						Optional[Any]							   = [0] * no_of_process
      for i in range(0       ,			__A		):
            lowerCamelCase__:						Union[str, Any]							   = turn_around_time[i] - burst_time[i]
      return waiting_time


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

      _lowercase				     = calculate_turn_around_time(
          process_name, arrival_time, burst_time, no_of_process
      )
      _lowercase				     = 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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase__      			=						{
    '''configuration_poolformer''': [
        '''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''PoolFormerConfig''',
        '''PoolFormerOnnxConfig''',
    ]
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__      			=						['''PoolFormerFeatureExtractor''']
			UpperCAmelCase__      			=						['''PoolFormerImageProcessor''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__      			=						[
			    '''POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''PoolFormerForImageClassification''',
			    '''PoolFormerModel''',
			    '''PoolFormerPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_poolformer import (
			    POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    PoolFormerConfig,
			    PoolFormerOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_poolformer import PoolFormerFeatureExtractor
						from .image_processing_poolformer import PoolFormerImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_poolformer import (
						    POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    PoolFormerForImageClassification,
						    PoolFormerModel,
						    PoolFormerPreTrainedModel,
						)


else:
			import sys

			UpperCAmelCase__      			=						_LazyModule(__name__, globals()['''__file__'''], _import_structure)





