How to use the lightkurve.utils.plot_image function in lightkurve

def plot_diagnostics(self, data, figsize=(12, 4), *params, **kwargs):
        """Plots an image of the model for a given point in the parameter space."""
        fig, ax = plt.subplots(nrows=1, ncols=3, figsize=figsize)
        fit = self.fit(data)
        extent = (self.prfmodel.column, self.prfmodel.column + self.prfmodel.shape[1],
                  self.prfmodel.row, self.prfmodel.row + self.prfmodel.shape[0])
        plot_image(data, ax=ax[0],
                   title='Observed Data, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        plot_image(fit.predicted_image, ax=ax[1],
                   title='Predicted Image, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        plot_image(fit.residual_image, ax=ax[2],
                   title='Residual Image, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        return fit

def plot_diagnostics(self, data, figsize=(12, 4), *params, **kwargs):
        """Plots an image of the model for a given point in the parameter space."""
        fig, ax = plt.subplots(nrows=1, ncols=3, figsize=figsize)
        fit = self.fit(data)
        extent = (self.prfmodel.column, self.prfmodel.column + self.prfmodel.shape[1],
                  self.prfmodel.row, self.prfmodel.row + self.prfmodel.shape[0])
        plot_image(data, ax=ax[0],
                   title='Observed Data, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        plot_image(fit.predicted_image, ax=ax[1],
                   title='Predicted Image, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        plot_image(fit.residual_image, ax=ax[2],
                   title='Residual Image, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        return fit

def plot_diagnostics(self, data, figsize=(12, 4), *params, **kwargs):
        """Plots an image of the model for a given point in the parameter space."""
        fig, ax = plt.subplots(nrows=1, ncols=3, figsize=figsize)
        fit = self.fit(data)
        extent = (self.prfmodel.column, self.prfmodel.column + self.prfmodel.shape[1],
                  self.prfmodel.row, self.prfmodel.row + self.prfmodel.shape[0])
        plot_image(data, ax=ax[0],
                   title='Observed Data, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        plot_image(fit.predicted_image, ax=ax[1],
                   title='Predicted Image, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        plot_image(fit.residual_image, ax=ax[2],
                   title='Residual Image, Channel: {}'.format(self.prfmodel.channel),
                   extent=extent, **kwargs)
        return fit

def plot(self, *params, **kwargs):
        pflux = self.evaluate(*params)
        plot_image(pflux, title='Kepler PRF Model, Channel: {}'.format(self.channel),
                   extent=(self.column, self.column + self.shape[1],
                           self.row, self.row + self.shape[0]), **kwargs)

Parameters
        ----------
        ax : `~matplotlib.axes.Axes`
            A matplotlib axes object to plot into. If no axes is provided,
            a new one will be created.
        **kwargs : dict
            Extra parameters to be passed to `.plot_image`.

        Returns
        -------
        `~matplotlib.axes.Axes`
            The matplotlib axes object.
        """
        with plt.style.context(MPLSTYLE):
            ax = plot_image(self.values, ax=ax, xlabel='Component', ylabel='X',
                            clabel='Component Value', title=self.name, **kwargs)
            ax.set_aspect(self.shape[1]/(1.6*self.shape[0]))
            if self.shape[1] <= 40:
                ax.set_xticks(np.arange(self.shape[1]))
                ax.set_xticklabels([r'${}$'.format(i) for i in self.columns],
                                   rotation=90, fontsize=8)
        return ax

"must be in the range {}-{}.".format(
                                     cadenceno, self.cadenceno[0], self.cadenceno[-1]))
        try:
            if bkg and np.any(np.isfinite(self.flux_bkg[frame])):
                pflux = self.flux[frame] + self.flux_bkg[frame]
            else:
                pflux = self.flux[frame]
        except IndexError:
            raise ValueError("frame {} is out of bounds, must be in the range "
                             "0-{}.".format(frame, self.shape[0]))
        with plt.style.context(style):
            if title is None:
                title = 'Target ID: {}, Cadence: {}'.format(self.targetid, self.cadenceno[frame])
            img_extent = (self.column, self.column + self.shape[2],
                          self.row, self.row + self.shape[1])
            ax = plot_image(pflux, ax=ax, title=title, extent=img_extent,
                            show_colorbar=show_colorbar, **kwargs)
            ax.grid(False)
        if aperture_mask is not None:
            aperture_mask = self._parse_aperture_mask(aperture_mask)
            for i in range(self.shape[1]):
                for j in range(self.shape[2]):
                    if aperture_mask[i, j]:
                        ax.add_patch(patches.Rectangle((j+self.column, i+self.row),
                                                       1, 1, color=mask_color, fill=True,
                                                       alpha=.6))
        return ax

def plot(self, *params, **kwargs):
        """Plots an image of the model for a given point in the parameter space."""
        img = self.predict(*params)
        plot_image(img,
                   title='TPF Model',
                   extent=(self.prfmodel.column, self.prfmodel.column + self.prfmodel.shape[1],
                           self.prfmodel.row, self.prfmodel.row + self.prfmodel.shape[0]),
                   **kwargs)