def plot_residuals(self, plot=None):
if plot is None:<EOL><INDENT>import matplotlib.pyplot as plot<EOL><DEDENT>x = numpy.arange(<NUM_LIT:1>, len(self.residuals) + <NUM_LIT:1>)<EOL>y = _gvar.mean(self.residuals)<EOL>yerr = _gvar.sdev(self.residuals)<EOL>plot.errorbar(x=x, y=y, yerr=yerr, fmt='<STR_LIT:o>', color='<STR_LIT:b>')<EOL>plot.ylabel('<STR_LIT>')<EOL>xr = [x[<NUM_LIT:0>], x[-<NUM_LIT:1>]]<EOL>plot.plot([x[<NUM_LIT:0>], x[-<NUM_LIT:1>]], [<NUM_LIT:0>, <NUM_LIT:0>], '<STR_LIT>')<EOL>plot.fill_between(<EOL>x=xr, y1=[-<NUM_LIT:1>,-<NUM_LIT:1>], y2=[<NUM_LIT:1>,<NUM_LIT:1>], color='<STR_LIT:r>', alpha=<NUM_LIT><EOL>)<EOL>return plot<EOL>
Plot normalized fit residuals.

        The sum of the squares of the residuals equals ``self.chi2``.
        Individual residuals should be distributed about one, in
        a Gaussian distribution.

        Args:
            plot: :mod:`matplotlib` plotter. If ``None``, uses
                ``matplotlib.pyplot`.

        Returns:
            Plotter ``plot``.