run_sim: Predictions of Foreground Jobs.
In carlonlv/DataCenterSim: Simulations for Data Centers

Sequentially training and testing by predicting the availability of CPU resource at next windows.

run_sim(
  epoch_setting,
  additional_setting = list(),
  x,
  xreg,
  start_point = 1,
  wait_time = 0,
  cores = parallel::detectCores(),
  write_type,
  plot_type,
  result_loc = getwd()
)

`epoch_setting`	A dataframe representing a specific parameter setting.
`additional_setting`	A list containing additional vector-like parameter settings.
`x`	A matrix of size n by m representing the target dataset for scheduling and evaluations.
`xreg`	A matrix or a list of matrices of length n by m representing the dataset that target dataset depends on for scheduling and evaluations, or `NULL`.
`start_point`	A numeric number that represents the starting point of the simulation. Default value is `1`.
`wait_time`	A numeric number that represents the time between training and testing. Default value is `0`.
`cores`	A numeric numb representing the number of threads for parallel programming for multiple traces, not supported for windows users.
`write_type`	A character that represents how to write the result of simulation, can be one of "charwise", "tracewise", "paramwise" or "none".
`plot_type`	A character that represents how to plot the result of simulation can be one of "charwise", "tracewise", "paramwise" or "none".
`result_loc`	A character that specify the path to which the result of simulations will be saved to. Default is your work directory.