Address a few warnings from tests

openmc/mgxs/mgxs.py

@@ -925,7 +925,7 @@ class MGXS:
         # Tabulate the atomic number densities for all nuclides
         elif nuclides == 'all':
             nuclides = self.get_nuclides()
-            densities = np.zeros(self.num_nuclides, dtype=np.float)
+            densities = np.zeros(self.num_nuclides, dtype=float)
             for i, nuclide in enumerate(nuclides):
                 densities[i] += self.get_nuclide_density(nuclide)
 
@@ -3019,7 +3019,7 @@ class DiffusionCoefficient(TransportXS):
                 new_filt = openmc.EnergyFilter(old_filt.values)
                 p1_tally.filters[-2] = new_filt
 
-                p1_tally = p1_tally.get_slice(filters=[openmc.LegendreFilter], 
+                p1_tally = p1_tally.get_slice(filters=[openmc.LegendreFilter],
                     filter_bins=[('P1',)],squeeze=True)
                 p1_tally._scores = ['scatter-1']
                 total_xs = self.tallies['total'] / self.tallies['flux (tracklength)']

tests/regression_tests/diff_tally/test.py

@@ -103,9 +103,8 @@ class DiffTallyTestHarness(PyAPITestHarness):
         sp = openmc.StatePoint(statepoint)
 
         # Extract the tally data as a Pandas DataFrame.
-        df = pd.DataFrame()
-        for t in sp.tallies.values():
-            df = df.append(t.get_pandas_dataframe(), ignore_index=True)
+        tally_dfs = [t.get_pandas_dataframe() for t in sp.tallies.values()]
+        df = pd.concat(tally_dfs, ignore_index=True)
 
         # Extract the relevant data as a CSV string.
         cols = ('d_material', 'd_nuclide', 'd_variable', 'score', 'mean',

tests/regression_tests/surface_tally/test.py

@@ -164,9 +164,8 @@ class SurfaceTallyTestHarness(PyAPITestHarness):
         sp = openmc.StatePoint(self._sp_name)
 
         # Extract the tally data as a Pandas DataFrame.
-        df = pd.DataFrame()
-        for t in sp.tallies.values():
-            df = df.append(t.get_pandas_dataframe(), ignore_index=True)
+        tally_dfs = [t.get_pandas_dataframe() for t in sp.tallies.values()]
+        df = pd.concat(tally_dfs, ignore_index=True)
 
         # Extract the relevant data as a CSV string.
         cols = ('mean', 'std. dev.')

tests/unit_tests/test_mesh_to_vtk.py

@@ -77,8 +77,8 @@ def test_write_data_to_vtk_size_mismatch(mesh):
     # by regex. These are needed to make the test string match the error message
     # string when using the match argument as that uses regular expression
     expected_error_msg = (
-        f"The size of the dataset 'label' \({len(data)}\) should be equal to "
-        f"the number of mesh cells \({mesh.num_mesh_cells}\)"
+        f"The size of the dataset 'label' ({len(data)}) should be equal to "
+        f"the number of mesh cells ({mesh.num_mesh_cells})"
     )
     with pytest.raises(ValueError, match=expected_error_msg):
         mesh.write_data_to_vtk(filename="out.vtk", datasets={"label": data})