Formatting updates

doped/thermodynamics.py

@@ -2526,11 +2526,11 @@ def get_transition_levels(
         self,
         all: bool = False,
         format_charges: bool = True,
-    ) -> pd.DataFrame:
+    ) -> Union[pd.DataFrame, None]:
         """
-        Return a DataFrame of the charge transition levels for the defects in
-        the DefectThermodynamics object (stored in the transition_level_map
-        attribute).
+        Return a ``DataFrame`` of the charge transition levels for the defects
+        in the ``DefectThermodynamics`` object (stored in the
+        ``transition_level_map`` attribute).
 
         Note that the transition level (and Fermi level) positions are given
         relative to ``self.vbm``, which is the VBM eigenvalue of the bulk
@@ -2547,7 +2547,7 @@ def get_transition_levels(
         If instead all single-electron transition levels are desired, set
         ``all = True``.
 
-        Returns a DataFrame with columns:
+        Returns a ``DataFrame`` with columns:
 
         - "Defect": Defect name
         - "Charges": Defect charge states which make up the transition level
@@ -2627,6 +2627,9 @@ def _TL_naming_func(TL_charges, i_meta=False, j_meta=False):
                             }
                         )
 
+        if not transition_level_map_list:
+            warnings.warn("No transition levels found for chosen parameters!")
+            return None
         tl_df = pd.DataFrame(transition_level_map_list)
         # sort df by Defect appearance order in defect_entries, Defect, then by TL position:
         tl_df["Defect Appearance Order"] = tl_df["Defect"].map(self._name_wout_charge_appearance_order)
@@ -2669,6 +2672,8 @@ def print_transition_levels(self, all: bool = False):
 
         else:
             all_TLs_df = self.get_transition_levels(all=True)
+            if all_TLs_df is None:
+                return
             for defect_name, tl_df in all_TLs_df.groupby("Defect", sort=False):
                 bold_print(f"Defect: {defect_name}")
                 for _, row in tl_df.iterrows():

tests/test_generation.py

@@ -3373,9 +3373,8 @@ def test_unrecognised_gen_kwargs(self):
         with pytest.raises(TypeError) as exc:
             DefectsGenerator(self.prim_cdte, interstitial_gen_kwargs={"unrecognised_kwarg": 1})
 
-        assert (
-            "TopographyAnalyzer.__init__() got an unexpected keyword argument 'unrecognised_kwarg'"
-            in str(exc.value)
+        assert (  # TopographyAnalyzer.__init__() but only __init__() shown in python 3.9
+            "__init__() got an unexpected keyword argument 'unrecognised_kwarg'" in str(exc.value)
         )
 
         with pytest.raises(TypeError) as exc:

tests/test_thermodynamics.py

@@ -1382,7 +1382,7 @@ def _check_formation_energy_methods(form_en_df_row, thermo_obj, fermi_level):
             assert list(row)[7] == list(te_rich_df.iloc[i])[7]
             assert list(row)[8] != list(te_rich_df.iloc[i])[8]
             assert list(row)[9] == list(te_rich_df.iloc[i])[9]
-            _check_formation_energy_methods(row, manual_thermo, 3)
+            _check_formation_energy_methods(list(row), manual_thermo, 3)
 
         assert list(manual_form_en_df.iloc[2])[:-1] == [
             "v_Cd",
@@ -1923,8 +1923,8 @@ def test_Sb2O5_formation_energies(self):
             df_row = formation_energy_table_df.iloc[i]
             reloaded_df_row = formation_energy_table_df_wout_charge_formatting.iloc[i]
             for j, val in enumerate(df_row):
-                print(val, reloaded_df_row[j])
-            assert val == reloaded_df_row[j]
+                print(val, reloaded_df_row.iloc[j])
+            assert val == reloaded_df_row.iloc[j]
 
         os.remove("test.csv")