@@ -196,7 +196,7 @@ def root_locus(sys, kvect=None, xlim=None, ylim=None, plotstr=None,
                 # This replaces the previous _sgrid_func()
                 ax, fig = sgrid(fig=fig, position=position)
         else:
-            # Use lighter style for axis lines when there are no grid lines
+            # Use lighter style for axes when there are no grid lines
             ax, fig = nogrid(ax=ax, axlinestyle=':', axlinewidth=.75)
             if isdtime(sys, strict=True):
                 # Plot unit circle
@@ -655,86 +655,4 @@ def _removeLine(label, ax):
             del line
 
 
-# TODO: Are these functions still needed?  They are currently redundant since
-#       `_sgrid_func` was replaced with `grid.sgrid`.  See Issue #634.
-#
-# def _default_zetas(xlim, ylim):
-#     """Return default list of damping coefficients
-
-#     This function computes a list of damping coefficients based on the limits
-#     of the graph.  A set of 4 damping coefficients are computed for the x-axis
-#     and a set of three damping coefficients are computed for the y-axis
-#     (corresponding to the normal 4:3 plot aspect ratio in `matplotlib`?).
-
-#     Parameters
-#     ----------
-#     xlim : array_like
-#         List of x-axis limits [min, max]
-#     ylim : array_like
-#         List of y-axis limits [min, max]
-
-#     Returns
-#     -------
-#     zeta : list
-#         List of default damping coefficients for the plot
-
-#     """
-#     # Damping coefficient lines that intersect the x-axis
-#     sep1 = -xlim[0] / 4
-#     ang1 = [np.arctan((sep1*i)/ylim[1]) for i in np.arange(1, 4, 1)]
-
-#     # Damping coefficient lines that intersection the y-axis
-#     sep2 = ylim[1] / 3
-#     ang2 = [np.arctan(-xlim[0]/(ylim[1]-sep2*i)) for i in np.arange(1, 3, 1)]
-
-#     # Put the lines together and add one at -pi/2 (negative real axis)
-#     angles = np.concatenate((ang1, ang2))
-#     angles = np.insert(angles, len(angles), np.pi/2)
-
-#     # Return the damping coefficients corresponding to these angles
-#     zeta = np.sin(angles)
-#     return zeta.tolist()
-
-
-# def _default_wn(xloc, yloc, max_lines=7):
-#     """Return default natural frequencies for root locus plot
-
-#     This function computes a list of natural frequencies based on the grid
-#     parameters of the graph.
-
-#     Parameters
-#     ----------
-#     xloc : array_like
-#         List of x-axis tick values
-#     ylim : array_like
-#         List of y-axis limits [min, max]
-#     max_lines : int, optional
-#         Maximum number of frequencies to generate (default = 7)
-
-#     Returns
-#     -------
-#     wn : list
-#         List of default natural frequencies for the plot
-
-#     """
-#     sep = xloc[1]-xloc[0]       # separation between x-ticks
-
-#     # Decide whether to use the x or y axis for determining wn
-#     if yloc[-1] / sep > max_lines*10:
-#         # y-axis scale >> x-axis scale
-#         wn = yloc                   # one frequency per y-axis tick mark
-#     else:
-#         wn = xloc                   # one frequency per x-axis tick mark
-
-#         # Insert additional frequencies to span the y-axis
-#         while np.abs(wn[0]) < yloc[-1]:
-#             wn = np.insert(wn, 0, wn[0]-sep)
-
-#     # If there are too many values, cut them in half
-#     while len(wn) > max_lines:
-#         wn = wn[0:-1:2]
-
-#     return wn
-
-
 rlocus = root_locus