diff --git a/pes_to_spec/test/offline_analysis.py b/pes_to_spec/test/offline_analysis.py
index 90ce3ce5eacc6733fa7343d9db891fc2513975ff..cdf54cba11fb59b2cbe71d9da32dfce86a3d467a 100755
--- a/pes_to_spec/test/offline_analysis.py
+++ b/pes_to_spec/test/offline_analysis.py
@@ -400,7 +400,7 @@ def main():
 
     df = pd.DataFrame(dict(auto_corr_hr=model.auto_corr_hr,
                            auto_corr_virt=model.auto_corr_virt,
-                           energy=model.wiener_energy
+                           energy=model.wiener_energy,
                            fwhm_hr=model.fwhm_hr*np.ones_like(model.auto_corr_hr),
                            fwhm_virt=model.fwhm_virt*np.ones_like(model.auto_corr_virt),
                           )
diff --git a/pes_to_spec/test/prepare_plots.py b/pes_to_spec/test/prepare_plots.py
index f103df5a1405045f8311682c203e48b4859bc63e..a0b4222316050bce3b3b9b48f0ca9fab9baaee58 100755
--- a/pes_to_spec/test/prepare_plots.py
+++ b/pes_to_spec/test/prepare_plots.py
@@ -56,15 +56,16 @@ def plot_autocov(df: pd.DataFrame, filename: str):
     ax = fig.add_subplot(gs[0, 0])
     fwhm_hr = df.fwhm_hr[0]
     fwhm_virt = df.fwhm_virt[0]
-    ax.plot(df.energy, df.auto_corr_hr, c='b', lw=3, label="FEL + Grating spec. (FWHM={fwhm_hr:.2} eV)")
-    ax.plot(df.energy, df.auto_corr_virt, c='r', lw=3, label="FEL + Virtual spec. (FWHM={fwhm_cirt:.2} eV)")
+    ax.plot(df.energy, df.auto_corr_hr, c='b', lw=3, label=f"FEL + Grating spec. (FWHM={fwhm_hr:.2} eV)")
+    ax.plot(df.energy, df.auto_corr_virt, c='r', lw=3, label=f"FEL + Virtual spec. (FWHM={fwhm_virt:.2} eV)")
     ax.legend(frameon=False, borderaxespad=0, loc='upper left')
     ax.spines['top'].set_visible(False)
     ax.spines['right'].set_visible(False)
     ax.set(
            xlabel="Photon energy [eV]",
            ylabel="Auto-covariance [a.u.]",
-           ylim=(0, 1.0))
+           xlim=(-3.0, 3.0),
+           ylim=(None, 1.3))
     plt.tight_layout()
     fig.savefig(filename)
     plt.close(fig)