code: def get_umbrella_sampling_data(ntherm=11, us_fc=20.0, us_length=500, md_length=1000, nmd=20):
      
      dws = _DWS()
      us_data = dws.us_sample(
          ntherm=ntherm, us_fc=us_fc, us_length=us_length, md_length=md_length, nmd=nmd)
      us_data.update(centers=dws.centers)
      return us_data
docs: Continuous MCMC process in an asymmetric double well potential using umbrella sampling.
  
      Parameters
      ----------
      ntherm: int, optional, default=11
          Number of umbrella states.
      us_fc: double, optional, default=20.0
          Force constant in kT/length^2 for each umbrella.
      us_length: int, optional, default=500
          Length in steps of each umbrella trajectory.
      md_length: int, optional, default=1000
          Length in steps of each unbiased trajectory.
      nmd: int, optional, default=20
          Number of unbiased trajectories.
  
      Returns
      -------
      dict - keys shown below in brackets
          Trajectory data from umbrella sampling (us_trajs) and unbiased (md_trajs) MCMC runs and
          their discretised counterparts (us_dtrajs + md_dtrajs + centers). The umbrella sampling
          parameters (us_centers + us_force_constants) are in the same order as the umbrella sampling
          trajectories. Energies are given in kT, lengths in arbitrary units.