How to use the impedance.plotting.plot_bode function in impedance

return ax
        elif kind == 'bode':
            if ax is None:
                fig, ax = plt.subplots(nrows=2, figsize=(5, 5))

            if Z_data is not None:
                ax = plot_bode(ax, f_data, Z_data, ls='', marker='s', **kwargs)

            if self._is_fit():
                if f_data is not None:
                    f_pred = f_data
                else:
                    f_pred = np.logspace(5, -3)

                Z_fit = self.predict(f_pred)
                ax = plot_bode(ax, f_pred, Z_fit, ls='-', marker='', **kwargs)
            return ax
        elif kind == 'altair':
            plot_dict = {}

            if Z_data is not None and f_data is not None:
                plot_dict['data'] = {'f': f_data, 'Z': Z_data}

            if self._is_fit():
                if f_data is not None:
                    f_pred = f_data
                else:
                    f_pred = np.logspace(5, -3)

                Z_fit = self.predict(f_pred)
                if self.name is not None:
                    name = self.name

if self._is_fit():
                if f_data is not None:
                    f_pred = f_data
                else:
                    f_pred = np.logspace(5, -3)

                Z_fit = self.predict(f_pred)
                ax = plot_nyquist(ax, Z_fit, ls='-', marker='', **kwargs)
            return ax
        elif kind == 'bode':
            if ax is None:
                fig, ax = plt.subplots(nrows=2, figsize=(5, 5))

            if Z_data is not None:
                ax = plot_bode(ax, f_data, Z_data, ls='', marker='s', **kwargs)

            if self._is_fit():
                if f_data is not None:
                    f_pred = f_data
                else:
                    f_pred = np.logspace(5, -3)

                Z_fit = self.predict(f_pred)
                ax = plot_bode(ax, f_pred, Z_fit, ls='-', marker='', **kwargs)
            return ax
        elif kind == 'altair':
            plot_dict = {}

            if Z_data is not None and f_data is not None:
                plot_dict['data'] = {'f': f_data, 'Z': Z_data}