Plot the scaled ChIP-seq data.

        :param x: X-axis to use (e.g, for TSS +/- 1kb with 100 bins, this would
            be `np.linspace(-1000, 1000, 100)`)
        :param row_order: Array-like object containing row order -- typically
            the result of an `np.argsort` call.
        :param strip: Include axes along the left side with points that can be
            clicked to spawn a minibrowser for that feature.

def plot(self, x, row_order=None, imshow_kwargs=None, strip=True):
        """
        Plot the scaled ChIP-seq data.

        :param x: X-axis to use (e.g, for TSS +/- 1kb with 100 bins, this would
            be `np.linspace(-1000, 1000, 100)`)
        :param row_order: Array-like object containing row order -- typically
            the result of an `np.argsort` call.
        :param strip: Include axes along the left side with points that can be
            clicked to spawn a minibrowser for that feature.
        """
        nrows = self.diffed_array.shape[0]
        if row_order is None:
            row_order = np.arange(nrows)
        extent = (min(x), max(x), 0, nrows)
        axes_info = metaseq.plotutils.matrix_and_line_shell(strip=strip)
        fig, matrix_ax, line_ax, strip_ax, cbar_ax = axes_info
        _imshow_kwargs = dict(
            aspect='auto', extent=extent, interpolation='nearest')
        if imshow_kwargs:
            _imshow_kwargs.update(imshow_kwargs)

        if 'cmap' not in _imshow_kwargs:
            _imshow_kwargs['cmap'] = metaseq.colormap_adjust.smart_colormap(
                self.diffed_array.min(),
                self.diffed_array.max()
            )
        mappable = matrix_ax.imshow(
            self.diffed_array[row_order],
            **_imshow_kwargs)
        plt.colorbar(mappable, cbar_ax)
        line_ax.plot(x, self.diffed_array.mean(axis=0))
        if strip_ax:
            line, = strip_ax.plot(np.zeros((nrows,)), np.arange(nrows) + 0.5,
                                  **self._strip_kwargs)
            line.features = self.features
            line.ind = row_order

        matrix_ax.axis('tight')
        if strip_ax:
            strip_ax.xaxis.set_visible(False)
            matrix_ax.yaxis.set_visible(False)

        matrix_ax.xaxis.set_visible(False)

        if self.db:
            self.minibrowser = GeneChipseqMiniBrowser(
                [self.ip, self.control],
                db=self.db,
                plotting_kwargs=self.browser_plotting_kwargs,
                local_coverage_kwargs=self.browser_local_coverage_kwargs)
        else:
            self.minibrowser = SignalChipseqMiniBrowser(
                [self.ip, self.control],
                plotting_kwargs=self.browser_plotting_kwargs,
                local_coverage_kwargs=self.browser_local_coverage_kwargs)

        fig.canvas.mpl_connect('pick_event', self.callback)

        self.fig = fig
        self.axes = {
            'matrix_ax': matrix_ax,
            'strip_ax': strip_ax,
            'line_ax': line_ax,
            'cbar_ax': cbar_ax
        }