rename xas variables, improve plotting

src/toolbox_scs/detectors/viking.py

@@ -195,12 +195,12 @@ class Viking:
         std_err_ref = std_ref / np.sqrt(data_ref.sizes['trainId'])
         
         ds = xr.Dataset()
-        ds['sample'] = spectrum
-        ds['sample_std'] = std
-        ds['sample_std_err'] = std_err
-        ds['ref'] = spectrum_ref
-        ds['ref_std'] = std
-        ds['ref_std_err'] = std_err
+        ds['It'] = spectrum
+        ds['It_std'] = std
+        ds['It_std_err'] = std_err
+        ds['I0'] = spectrum_ref
+        ds['I0_std'] = std
+        ds['I0_std_err'] = std_err
         ds['absorption'] = spectrum_ref / spectrum
         ds['absorption_std'] = np.abs(ds['absorption']) * np.sqrt(
             std_ref**2 / spectrum_ref**2 + std**2 / spectrum**2)
@@ -215,25 +215,28 @@ class Viking:
         return ds
 
 def plot_viking_xas(xas, plot_errors=True, xas_ylim=(-1, 3)):
-    fig, ax = plt.subplots(3, 1, figsize=(8,8), sharex=True)
-    ax[0].plot(xas.newt_x, xas['ref'])
+    fig, ax = plt.subplots(3, 1, figsize=(7,7), sharex=True)
+    ax[0].plot(xas.newt_x, xas['I0'])
     ax[0].grid()
+    ax[0].set_title('I0 spectra')
 
-    ax[1].plot(xas.newt_x, xas['sample'])
+    ax[1].plot(xas.newt_x, xas['It'])
     ax[1].grid()
+    ax[1].set_title('It spectra')
 
     ax[2].plot(xas.newt_x, xas['absorptionCoef'])
     ax[2].set_ylim(*xas_ylim)
     ax[2].grid()
-    
+    ax[2].set_title('XAS')
+
     if plot_errors:
         ax[0].fill_between(xas.newt_x,
-                           xas['ref'] - 1.96*xas['ref_std_err'], 
-                           xas['ref'] + 1.96*xas['ref_std_err'],
+                           xas['I0'] - 1.96*xas['I0_std_err'], 
+                           xas['I0'] + 1.96*xas['I0_std_err'],
                            alpha=0.2)
         ax[1].fill_between(xas.newt_x,
-                           xas['sample'] - 1.96*xas['sample_std_err'], 
-                           xas['sample'] + 1.96*xas['sample_std_err'],
+                           xas['It'] - 1.96*xas['It_std_err'], 
+                           xas['It'] + 1.96*xas['It_std_err'],
                            alpha=0.2)
         ax[2].fill_between(xas.newt_x,
                            xas['absorptionCoef'] - 1.96*xas['absorptionCoef_stderr'],