docs: def fit_radius_from_potentials(z, SampleFreq, Damping, HistBins=100, show_fig=False):
      """
      Fits the dynamical potential to the Steady 
      State Potential by varying the Radius.
      
      z : ndarray
          Position data
      SampleFreq : float
          frequency at which the position data was 
          sampled
      Damping : float
          value of damping (in radians/second)
      HistBins : int
          number of values at which to evaluate 
          the steady state potential / perform
          the fitting to the dynamical potential
  
      Returns
      -------
      Radius : float
          Radius of the nanoparticle
      RadiusError : float
          One Standard Deviation Error in the Radius from the Fit
          (doesn't take into account possible error in damping)
      fig : matplotlib.figure.Figure object
          figure showing fitted dynamical potential and stationary potential
      ax : matplotlib.axes.Axes object
          axes for above figure
  
      """
      dt = 1/SampleFreq
      boltzmann=Boltzmann
      temp=300 # why halved??
      density=1800
      SteadyStatePotnl = list(steady_state_potential(z, HistBins=HistBins))
      yoffset=min(SteadyStatePotnl[1])
      SteadyStatePotnl[1] -= yoffset
  
      SpringPotnlFunc = dynamical_potential(z, dt)
      SpringPotnl = SpringPotnlFunc(z)
      kBT_Gamma = temp*boltzmann*1/Damping
      
      DynamicPotentialFunc = make_dynamical_potential_func(kBT_Gamma, density, SpringPotnlFunc)
      FitSoln = _curve_fit(DynamicPotentialFunc, SteadyStatePotnl[0], SteadyStatePotnl[1], p0 = 50)
      print(FitSoln)
      popt, pcov = FitSoln
      perr = _np.sqrt(_np.diag(pcov))
      Radius, RadiusError = popt[0], perr[0]
  
      mass=((4/3)*pi*((Radius*10**-9)**3))*density
      yfit=(kBT_Gamma/mass)
      Y = yfit*SpringPotnl
      
      fig, ax = _plt.subplots()
      ax.plot(SteadyStatePotnl[0], SteadyStatePotnl[1], 'bo', label="Steady State Potential")
      _plt.plot(z,Y, 'r-', label="Dynamical Potential")
      ax.legend(loc='best')
      ax.set_ylabel('U ($k_{B} T $ Joules)')
      ax.set_xlabel('Distance (mV)')
      _plt.tight_layout()
      if show_fig == True:
          _plt.show()
      return Radius*1e-9, RadiusError*1e-9, fig, ax