Added further resolution analysis.

pes_to_spec/test/offline_analysis.py

@@ -401,6 +401,8 @@ def main():
     df = pd.DataFrame(dict(auto_corr_hr=model.auto_corr_hr,
                            auto_corr_virt=model.auto_corr_virt,
                            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),
                           )
                      )
     df.to_csv(os.path.join(args.directory, "resolution.csv"))

pes_to_spec/test/prepare_plots.py

@@ -54,8 +54,10 @@ def plot_autocov(df: pd.DataFrame, filename: str):
     fig = plt.figure(figsize=(12, 8))
     gs = GridSpec(1, 1)
     ax = fig.add_subplot(gs[0, 0])
-    ax.plot(df.energy, df.auto_corr_hr, c='b', lw=3, label="Grating spectrometer")
-    ax.plot(df.energy, df.auto_corr_virt, c='r', lw=3, label="Virtual spectrometer")
+    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="Grating spectrometer (FWHM={fwhm_hr:.2} eV)")
+    ax.plot(df.energy, df.auto_corr_virt, c='r', lw=3, label="Virtual spectrometer (FWHM={fwhm_cirt:.2} eV)")
     ax.legend(frameon=False, borderaxespad=0, loc='upper left')
     ax.spines['top'].set_visible(False)
     ax.spines['right'].set_visible(False)
@@ -546,5 +548,5 @@ if __name__ == '__main__':
     pca_variance_plot(pd.read_csv(f'{indir}/pca_spec.csv'), f'pca_spec.pdf', max_comp_frac=0.99)
     pca_variance_plot(pd.read_csv(f'{indir}/pca_pes.csv'), f'pca_pes.pdf', max_comp_frac=0.95)
 
-    plot_autocov(pd.read_csv(f'{indir}/autocov.csv'), f'autocov.pdf')
+    plot_autocov(pd.read_csv(f'{indir}/resolution.csv'), f'autocov.pdf')