Calculate the mean velocity for a step (mm/ms which is equivalent to
        m/s). Fit a line to the capacitance data and get the slope.

def mean_velocity(self, tol=0.05, Lx=None):
        '''
        Calculate the mean velocity for a step (mm/ms which is equivalent to
        m/s). Fit a line to the capacitance data and get the slope.
        '''
        dx = None
        dt = None
        p = None
        ind = None
        t_end = None

        if self.area == 0:
            return dict(dx=dx, dt=dt, p=p, ind=ind, t_end=t_end)

        x = self.x_position(Lx=Lx)

        # find the first and last valid indices
        ind_start = mlab.find(x.mask==False)[0]
        ind_last = mlab.find(x.mask==False)[-1]

        # if the original x value is within tol % of the final x value, include
        # all samples
        if x[ind_start] > (1 - tol) * x[ind_last] or x[ind_last] < 0:
            ind_stop = ind_last
        else: # otherwise, stop when x reaches (1 - tol) % of it's final value
            ind_stop = mlab.find(x > (1 - tol) * x[ind_last])[0]

        ind = [ind_start, ind_stop]

        # if we have at least 2 valid samples
        if len(ind) >=2:
            dx = np.diff(x[ind])[0]
            dt = np.diff(self.time[ind])[0] # ms

            # suppress polyfit warnings
            with warnings.catch_warnings():
                warnings.simplefilter("ignore")
                # fit a line to the data
                p = np.polyfit(self.time[ind[0]:ind[1]], x[ind[0]:ind[1]], 1)

            # find time when the the line intercepts x[ind_last]
            ind_stop = mlab.find(self.time > \
                                 (x[ind_last] - p[1]) / p[0])
            if len(ind_stop):
                t_end = self.time[ind_stop[0]]
            else:
                t_end = self.time[-1]
        return dict(dx=dx, dt=dt, p=p, ind=ind, t_end=t_end)