





from __future__ import annotations

from statistics import mean





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   list[int]:




    """simple docstring"""




    _A    =       2
    _A    =       list(_SCREAMING_SNAKE_CASE							)
    _A    =       [0] * len(_SCREAMING_SNAKE_CASE							)
    _A    =       0
    while True:
        _A    =       True
        for i, burst_time in enumerate(_SCREAMING_SNAKE_CASE							):
            if rem_burst_times[i] > 0:
                _A    =       False
                if rem_burst_times[i] > quantum:
                    t += quantum
                    rem_burst_times[i] -= quantum
                else:
                    t += rem_burst_times[i]
                    _A    =       t - burst_time
                    _A    =       0
        if done is True:
            return waiting_times





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   list[int]:




    """simple docstring"""




    return [burst + waiting for burst, waiting in zip(_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)]


if __name__ == "__main__":
       __A       : Optional[int]						    = [3, 5, 7]
       __A       : List[str]						    = calculate_waiting_times(burst_times)
       __A       : Union[str, Any]						    = calculate_turn_around_times(burst_times, waiting_times)
       print("Process ID \tBurst Time \tWaiting Time \tTurnaround Time")
       for i, burst_time in enumerate(burst_times):
              print(
                  f"  {i + 1}\t\t  {burst_time}\t\t  {waiting_times[i]}\t\t  "
                  f"{turn_around_times[i]}"
              )
       print(f"\nAverage waiting time = {mean(waiting_times):.5f}")
       print(f"Average turn around time = {mean(turn_around_times):.5f}")












import numpy as np





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   List[Any]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       abs(predict - actual							)
    _A    =       difference.mean()

    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Optional[int]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       predict - actual
    _A    =       np.square(_SCREAMING_SNAKE_CASE							)

    _A    =       square_diff.mean()
    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Tuple:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       predict - actual
    _A    =       np.square(_SCREAMING_SNAKE_CASE							)
    _A    =       square_diff.mean()
    _A    =       np.sqrt(_SCREAMING_SNAKE_CASE							)
    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   List[Any]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       np.log(predict + 1							)
    _A    =       np.log(actual + 1							)

    _A    =       log_predict - log_actual
    _A    =       np.square(_SCREAMING_SNAKE_CASE							)
    _A    =       square_diff.mean()

    _A    =       np.sqrt(_SCREAMING_SNAKE_CASE							)

    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Optional[int]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       predict - actual
    _A    =       np.sum(_SCREAMING_SNAKE_CASE							) / len(_SCREAMING_SNAKE_CASE							)
    _A    =       np.sum(_SCREAMING_SNAKE_CASE							) / len(_SCREAMING_SNAKE_CASE							)
    # print(numerator, denumerator)
    _A    =       float(_SCREAMING_SNAKE_CASE							) / denumerator * 100

    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Dict:




    """simple docstring"""




    return np.mean(np.array(_SCREAMING_SNAKE_CASE							) == np.array(_SCREAMING_SNAKE_CASE							)							)





