Apply black

kuibit/cactus_grid_functions.py

@@ -807,9 +807,9 @@ def current_data_to_UniformGridData(
 
                     # Write iterations_to_time
                     if current_iteration not in self._iterations_to_times:
-                        self._iterations_to_times[
-                            current_iteration
-                        ] = current_time
+                        self._iterations_to_times[current_iteration] = (
+                            current_time
+                        )
 
                     # Reset everything
                     current_iteration = line_data[0]
@@ -1169,9 +1169,9 @@ def _read_component_as_uniform_grid_data(
                 )
                 data = np.transpose(dataset[()])
 
-                self.alldata[path][iteration][ref_level][
-                    component
-                ] = grid_data.UniformGridData(grid, data)
+                self.alldata[path][iteration][ref_level][component] = (
+                    grid_data.UniformGridData(grid, data)
+                )
 
         return self.alldata[path][iteration][ref_level][component]
 

kuibit/cactus_waves.py

@@ -928,14 +928,10 @@ def d_lm(el, em):
             )
 
             if direction == 0:
-                return (
-                    self.dist**2 / (8 * np.pi) * (Pp_int1 * Pp_int2).real()
-                )
+                return self.dist**2 / (8 * np.pi) * (Pp_int1 * Pp_int2).real()
 
             if direction == 1:
-                return (
-                    self.dist**2 / (8 * np.pi) * (Pp_int1 * Pp_int2).imag()
-                )
+                return self.dist**2 / (8 * np.pi) * (Pp_int1 * Pp_int2).imag()
 
         # This is direction == 2
 
@@ -1288,9 +1284,7 @@ def get_power_lm(self, mult_l, mult_m):
                   time.
         :rtype: :py:class:`~TimeSeries`
         """
-        return (
-            self.dist**2 / (4 * np.pi) * np.abs(self[(mult_l, mult_m)]) ** 2
-        )
+        return self.dist**2 / (4 * np.pi) * np.abs(self[(mult_l, mult_m)]) ** 2
 
     def get_energy_lm(self, mult_l, mult_m):
         """Return the cumulative energy lost in the mode (l, m).

kuibit/visualize_matplotlib.py

@@ -433,6 +433,7 @@ def save(
     """
     if os.path.splitext(outputpath)[-1] == ".tikz":
         import tikzplotlib
+
         # If clean_figure is True, we extract from kwargs those argument
         # that tikzplotlib.clean_figure would take. For this, we need to
         # know what argument that function takes.

tests/test_cactus_waves.py

@@ -285,9 +285,7 @@ def test_get_force_linear_momentum_em(self):
 
         phi2lm_2 = c_lm * np.conj(phi2lm)
 
-        force_lm = (
-            self.phi2.dist**2 / (4 * np.pi) * (phi2lm * phi2lm_2).real()
-        )
+        force_lm = self.phi2.dist**2 / (4 * np.pi) * (phi2lm * phi2lm_2).real()
 
         self.assertEqual(force_lm, self.phi2.get_force_z_lm(2, 2))
 
@@ -650,9 +648,7 @@ def test_get_force_linear_momentum(self):
         )
 
         Pp_lm = (
-            psi4_234.dist**2
-            / (8 * np.pi)
-            * (psi4lm_xy_int1 * psi4lm_xy_int2)
+            psi4_234.dist**2 / (8 * np.pi) * (psi4lm_xy_int1 * psi4lm_xy_int2)
         )
 
         self.assertEqual(Pp_lm.real(), psi4_234.get_force_x_lm(3, 1, 0.1))

tests/test_gw_utils.py

@@ -169,8 +169,7 @@ def test_effective_amplitude_spectral_density(self):
         freqs = strain_plus_fft.f
         vals = (
             strain_plus_fft.f
-            * (0.5 * (strain_plus_fft.amp**2 + strain_cross_fft.amp**2))
-            ** 0.5
+            * (0.5 * (strain_plus_fft.amp**2 + strain_cross_fft.amp**2)) ** 0.5
         )
 
         expected_heff = FrequencySeries(freqs, vals)

tests/test_sensitivity_curves.py

@@ -40,9 +40,7 @@ def test_ETB(self):
 
         self.assertEqual(
             etb,
-            fs.FrequencySeries(
-                freqs, [4.8012536e-21**2, 6.5667816e-25**2]
-            ),
+            fs.FrequencySeries(freqs, [4.8012536e-21**2, 6.5667816e-25**2]),
         )
 
     def test_ETD(self):
@@ -52,9 +50,7 @@ def test_ETD(self):
 
         self.assertEqual(
             etd,
-            fs.FrequencySeries(
-                freqs, [3.4959517e-17**2, 5.7819941e-25**2]
-            ),
+            fs.FrequencySeries(freqs, [3.4959517e-17**2, 5.7819941e-25**2]),
         )
 
     def test_CE1(self):

tests/test_tensor.py

@@ -394,9 +394,7 @@ def test_dot(self):
         self.assertEqual(dot, expected)
 
     def test_norm(self):
-        self.assertEqual(
-            self.vec.norm(), (sum(t**2 for t in self.ts)).sqrt()
-        )
+        self.assertEqual(self.vec.norm(), (sum(t**2 for t in self.ts)).sqrt())
 
 
 class TestMatrix(unittest.TestCase):