text: import numpy as np
  import numpy.random as npr
  from system_definitions import example_system_twostate
  from experiments import multi_experiment_increasing_rollout_count, load_plot_multi_experiment
  
  # Scalar experiment
  seed = 1
  npr.seed(seed)
  
  # System definition
  n,m,A,B,SigmaA,SigmaB = example_system_twostate()
  
  # Number of rollouts
  nr = int(1e6)
  
  # Rollout length
  ell = int((m**2*n**4)/2 + (m**2*n**2)/2 + m**2 + 1)
  
  # Model estimation points
  ns = 40
  s_hist = np.unique(np.round(np.logspace(0,np.log10(nr),ns+1,base=10)).astype(int)[1:])
  ns_cur = s_hist.size
  while s_hist.size < ns:
      ns_cur += 1
      s_hist = np.unique(np.round(np.logspace(0,np.log10(nr),ns_cur+1,base=10)).astype(int)[1:])
  
  # Number of experiments
  ne = 4
  
  # Input mean and covariance settings
  u_mean_std = 1
  u_covr_std = 0.1
  
  timestr = multi_experiment_increasing_rollout_count(n,m,A,B,SigmaA,SigmaB,ne,ns,s_hist,nr,ell,u_mean_std,u_covr_std,print_updates=True)
  load_plot_multi_experiment(timestr)