Optionally convert bytes into strings in plot_empirical

species/analysis/empirical.py

@@ -135,7 +135,12 @@ def spectral_type(self,
         for i, item in enumerate(h5_file[f'spectra/{self.spec_library}']):
             # Read spectrum spectral type from library
             dset = h5_file[f'spectra/{self.spec_library}/{item}']
-            item_sptype = dset.attrs['sptype'].decode('utf-8')
+
+            if isinstance(dset.attrs['sptype'], str):
+                item_sptype = dset.attrs['sptype']
+            else:
+                # Use decode for backward compatibility
+                item_sptype = dset.attrs['sptype'].decode('utf-8')
 
             if item_sptype == 'None':
                 continue
@@ -163,6 +168,7 @@ def spectral_type(self,
                                          'use a broader range as argument of \'wavel_range\'.')
 
                     spectrum = spectrum[indices, ]
+
                 empty_message = len(print_message)*' '
                 print(f'\r{empty_message}', end='')
 
@@ -257,9 +263,15 @@ def spectral_type(self,
 
         print('Best-fitting spectra:')
 
-        for i in range(10):
-            print(f'   - G = {gk_select[i]:.2e} -> {name_select[i]}, {spt_select[i]}, '
-                  f'A_V = {av_select[i]:.2f}, RV = {rv_select[i]:.0f} km/s')
+        if len(gk_select) < 10:
+            for i in range(len(gk_select)):
+                print(f'   {i+1:2d}. G = {gk_select[i]:.2e} -> {name_select[i]}, {spt_select[i]}, '
+                      f'A_V = {av_select[i]:.2f}, RV = {rv_select[i]:.0f} km/s')
+
+        else:
+            for i in range(10):
+                print(f'   {i+1:2d}. G = {gk_select[i]:.2e} -> {name_select[i]}, {spt_select[i]}, '
+                      f'A_V = {av_select[i]:.2f}, RV = {rv_select[i]:.0f} km/s')
 
         species_db = database.Database()
 

species/plot/plot_empirical.py

@@ -125,6 +125,9 @@ def plot_statistic(tag: str,
 
     for i, item in enumerate(sptypes):
         for j in range(10):
+            if not isinstance(item, str):
+                item = item.decode('utf-8')
+
             if item == f'M{j}':
                 sptype_num[i] = float(j)
 
@@ -257,7 +260,12 @@ def plot_empirical_spectra(tag: str,
     obj_res = read_obj.get_spectrum()[spec_name][3]
 
     for i in range(n_spectra):
-        spectrum = np.asarray(h5_file[f'spectra/{spec_library}/{names[i]}'])
+        if isinstance(names[i], str):
+            name_item = names[i]
+        else:
+            name_item = names[i].decode('utf-8')
+
+        spectrum = np.asarray(h5_file[f'spectra/{spec_library}/{name_item}'])
 
         ism_ext = dust_util.ism_extinction(av_ext[i], 3.1, spectrum[:, 0])
         ext_scaling = 10.**(-0.4*ism_ext)