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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_umbrella_sampling_data(ntherm=11, us_fc=20.0, us_length=500, md_length=1000, nmd=20):
 """ 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. """

    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