deep-scheduler/relaunch_plot.py at master · schr476/deep-scheduler · GitHub

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from modeling import *
from relaunch_data import *

ro0_l = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
w_l, ro0_scherid_X_l_m = get_w_l__ro0_Scherwrelaunchid_X_l_m()

def plot_ET_wrt_w():
  def plot_(ro0):
    log(INFO, "ro0= {}".format(ro0) )

    scherid_X_l_m = ro_scherid_X_l_m[ro0]
    sim_ET_l, sim_StdT_l = [], []
    ET_wMGc_l, approx_ET_wMGc_l = [], []
    for w in w_l:
      ET_wMGc, EW_wMGc, Prqing_wMGc = relaunch_ET_EW_Prqing_wMGc(ro0, N, Cap, k, r, b, beta, a, alpha, w)
        if ET_wMGc is None: # sys is unstable
          break
        elif ET_wMGc > 200:
          ET_wMGc = None
        ET_wMGc_l.append(ET_wMGc)

      X_l_m = scherid_X_l_m['Scher_wrelaunch_w={}'.format(w) ]
      sim_ET_l.append(np.mean(X_l_m['ET_l'] ) )
      sim_StdT_l.append(np.std(X_l_m['ET_l'] ) )

      approx_ET_wMGc, approx_EW_wMGc, approx_Prqing_wMGc = relaunch_approx_ET_EW_Prqing_wMGc(ro0, N, Cap, k, r, b, beta, a, alpha, w)
      if approx_ET_wMGc > 200:
        approx_ET_wMGc = None
      approx_ET_wMGc_l.append(approx_ET_wMGc)
    plot.errorbar(w_l, sim_ET_l, yerr=sim_StdT_l, label='Simulation', c=NICE_RED, marker='d', ls=':', mew=0.5, ms=8)
    plot.plot(w_l, ET_wMGc_l, label='M/G/c', c=NICE_BLUE, marker='o', ls=':')
    plot.plot(w_l, approx_ET_wMGc_l, label='Asymptotic', c=NICE_GREEN, marker='p', ls=':', mew=0.5, ms=8)

    plot.xscale('log')
    prettify(plot.gca() )
    fontsize = 21
    plot.legend(loc='best', framealpha=0.5, fontsize=14, numpoints=1)
    plot.xlabel(r'$w$', fontsize=fontsize)
    plot.ylabel(r'$E[T]$', fontsize=fontsize)

    plot.title(r'$\rho_0= {}$'.format(ro0), fontsize=fontsize)
    fig = plot.gcf()
    fig.set_size_inches(4, 4)
    plot.savefig('plot_ET_wrt_w_ro{}.png'.format(ro0), bbox_inches='tight')
    fig.clear()

  # for ro0 in ro0_l:
  #   plot_(ro0)
  plot_(ro0=0.1)

  log(INFO, "done.")
  # log(INFO, "done;", ro0_l=ro0_l, dopt_l=dopt_l)

if __name__ == "__main__":
  N, Cap = 20, 10
  k = BZipf(1, 10) # BZipf(1, 5)
  R = Uniform(1, 1)
  b, beta = 10, 3 # 4
  # L = Pareto(b, beta)
  a, alpha = 1, 3
  # Sl = Pareto(a, alpha)

  plot_ET_wrt_w()