





from __future__ import annotations

import pandas as pd






def 				_UpperCAmelCase			(    A				,							A				,							A     ):




   '''simple docstring'''

   UpperCAmelCase__						=[0] * no_of_processes
   UpperCAmelCase__						=[0] * no_of_processes
   # Copy the burst time into remaining_time[]
   for i in range(A     ):
      UpperCAmelCase__						=burst_time[i]

   UpperCAmelCase__						=0
   UpperCAmelCase__						=0
   UpperCAmelCase__						=999999999
   UpperCAmelCase__						=0
   UpperCAmelCase__						=False

   # Process until all processes are completed
   while complete != no_of_processes:
      for j in range(A     ):
         if arrival_time[j] <= increment_time and remaining_time[j] > 0:
            if remaining_time[j] < minm:
               UpperCAmelCase__						=remaining_time[j]
               UpperCAmelCase__						=j
               UpperCAmelCase__						=True

      if not check:
         increment_time += 1
         continue
      remaining_time[short] -= 1

      UpperCAmelCase__						=remaining_time[short]
      if minm == 0:
         UpperCAmelCase__						=999999999

      if remaining_time[short] == 0:
         complete += 1
         UpperCAmelCase__						=False

         # Find finish time of current process
         UpperCAmelCase__						=increment_time + 1

         # Calculate waiting time
         UpperCAmelCase__						=finish_time - arrival_time[short]
         UpperCAmelCase__						=finar - burst_time[short]

         if waiting_time[short] < 0:
            UpperCAmelCase__						=0

        # Increment time
      increment_time += 1
   return waiting_time






def 				_UpperCAmelCase			(    A				,							A				,							A     ):




   '''simple docstring'''

   UpperCAmelCase__						=[0] * no_of_processes
   for i in range(A     ):
      UpperCAmelCase__						=burst_time[i] + waiting_time[i]
   return turn_around_time






def 				_UpperCAmelCase			(    A				,							A				,							A     ):




   '''simple docstring'''

   UpperCAmelCase__						=0
   UpperCAmelCase__						=0
   for i in range(A     ):
      UpperCAmelCase__						=total_waiting_time + waiting_time[i]
      UpperCAmelCase__						=total_turn_around_time + turn_around_time[i]
   print(F"""Average waiting time = {total_waiting_time / no_of_processes:.5f}"""     )
   print("Average turn around time ="				,							total_turn_around_time / no_of_processes     )


if __name__ == "__main__":
    print('Enter how many process you want to analyze')
    UpperCamelCase_												=	int(input())
    UpperCamelCase_												=	[0] * no_of_processes
    UpperCamelCase_												=	[0] * no_of_processes
    UpperCamelCase_												=	list(range(1, no_of_processes + 1))

    for i in range(no_of_processes):
        print('Enter the arrival time and burst time for process:--' + str(i + 1))
        UpperCamelCase_							,						UpperCamelCase_												=	map(int, input().split())

    UpperCamelCase_												=	calculate_waitingtime(arrival_time, burst_time, no_of_processes)

    UpperCamelCase_												=	burst_time
    UpperCamelCase_												=	no_of_processes
    UpperCamelCase_												=	waiting_time
    UpperCamelCase_												=	calculate_turnaroundtime(bt, n, wt)

    calculate_average_times(waiting_time, turn_around_time, no_of_processes)

    UpperCamelCase_												=	pd.DataFrame(
        list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
        columns=[
            'Process',
            'BurstTime',
            'ArrivalTime',
            'WaitingTime',
            'TurnAroundTime',
        ],
    )

    # Printing the dataFrame
    pd.set_option('display.max_rows', fcfs.shape[0] + 1)
    print(fcfs)










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase_												=	{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_												=	['OwlViTFeatureExtractor']
    UpperCamelCase_												=	['OwlViTImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_												=	[
        'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'OwlViTModel',
        'OwlViTPreTrainedModel',
        'OwlViTTextModel',
        'OwlViTVisionModel',
        'OwlViTForObjectDetection',
    ]

if TYPE_CHECKING:
    from .configuration_owlvit import (
        OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        OwlViTConfig,
        OwlViTOnnxConfig,
        OwlViTTextConfig,
        OwlViTVisionConfig,
    )
    from .processing_owlvit import OwlViTProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_owlvit import OwlViTFeatureExtractor
        from .image_processing_owlvit import OwlViTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_owlvit import (
            OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            OwlViTForObjectDetection,
            OwlViTModel,
            OwlViTPreTrainedModel,
            OwlViTTextModel,
            OwlViTVisionModel,
        )

else:
    import sys

    UpperCamelCase_												=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



