Reformat using Ruff and Black

tardis/spectrum/base.py

@@ -104,7 +104,7 @@ def spectrum_integrated(self):
                     np.array([np.nan]) * u.erg / u.s,
                 )
         return self._spectrum_integrated
-    
+
     @property
     def integrator(self):
         if self._integrator is None:

tardis/tests/test_tardis_full_formal_integral.py

@@ -6,11 +6,10 @@
 from astropy.tests.helper import assert_quantity_allclose
 
 from tardis.io.configuration.config_reader import Configuration
-from tardis.simulation.base import Simulation
 from tardis.io.util import HDFWriterMixin
+from tardis.simulation.base import Simulation
 from tardis.tests.fixtures.regression_data import RegressionData
 
-
 config_line_modes = ["downbranch", "macroatom"]
 interpolate_shells = [-1, 30]
 
@@ -30,65 +29,70 @@ def base_config(request, example_configuration_dir: Path):
 
     return config
 
+
 @pytest.fixture(scope="module", params=interpolate_shells)
 def config(base_config, request):
     base_config["spectrum"]["integrated"]["interpolate_shells"] = request.param
     return base_config
 
+
 class SimulationContainer(HDFWriterMixin):
-  hdf_properties = ["spectrum_solver", "transport"]
-
-  def __init__(self, simulation):
-      self.spectrum_solver = simulation.spectrum_solver
-      self.transport = simulation.transport
+    hdf_properties = ["spectrum_solver", "transport"]
+
+    def __init__(self, simulation):
+        self.spectrum_solver = simulation.spectrum_solver
+        self.transport = simulation.transport
+
 
 class TestTransportSimpleFormalIntegral:
-  """
-  Very simple run with the formal integral spectral synthesis method
-  """
-
-  _name = "test_transport_simple_integral"
-
-  @pytest.fixture(scope="class")
-  def simulation(self, config, atomic_data_fname ):
-      config.atom_data = atomic_data_fname
-
-      self.name = self._name + f"_{config.plasma.line_interaction_type:s}"
-      if config.spectrum.integrated.interpolate_shells > 0:
-          self.name += "_interp"
-
-      simulation = Simulation.from_config(config)
-      simulation.run_convergence()
-      simulation.run_final()
-      simulation.spectrum_solver.hdf_properties = [
-        "spectrum_real_packets",
-        "spectrum_integrated",
-      ]
-      simulation.transport.hdf_properties = ["transport_state"]
-
-      return simulation
-
-  def test_simulation(self, simulation, request):
-      regression_data = RegressionData(request)
-      container = SimulationContainer(simulation)
-      regression_data.sync_hdf_store(container)
-
-  def test_j_blue_estimators(self, simulation, request):
-      regression_data = RegressionData(request)
-      j_blue_estimator = simulation.transport.transport_state.radfield_mc_estimators.j_blue_estimator
-      expected = regression_data.sync_ndarray(j_blue_estimator)
-      npt.assert_allclose(j_blue_estimator, expected)
-
-  def test_spectrum(self, simulation, request):
-      regression_data = RegressionData(request)
-      luminosity = simulation.spectrum_solver.spectrum_real_packets.luminosity
-      expected = regression_data.sync_ndarray(luminosity.cgs.value)
-      expected = u.Quantity(expected, "erg /s")
-      assert_quantity_allclose(luminosity, expected)
-
-  def test_spectrum_integrated(self, simulation, request):
-      regression_data = RegressionData(request)
-      luminosity = simulation.spectrum_solver.spectrum_integrated.luminosity
-      expected = regression_data.sync_ndarray(luminosity.cgs.value)
-      expected = u.Quantity(expected, "erg /s")
-      assert_quantity_allclose(luminosity, expected)
+    """
+    Very simple run with the formal integral spectral synthesis method
+    """
+
+    _name = "test_transport_simple_integral"
+
+    @pytest.fixture(scope="class")
+    def simulation(self, config, atomic_data_fname):
+        config.atom_data = atomic_data_fname
+
+        self.name = self._name + f"_{config.plasma.line_interaction_type:s}"
+        if config.spectrum.integrated.interpolate_shells > 0:
+            self.name += "_interp"
+
+        simulation = Simulation.from_config(config)
+        simulation.run_convergence()
+        simulation.run_final()
+        simulation.spectrum_solver.hdf_properties = [
+            "spectrum_real_packets",
+            "spectrum_integrated",
+        ]
+        simulation.transport.hdf_properties = ["transport_state"]
+
+        return simulation
+
+    def test_simulation(self, simulation, request):
+        regression_data = RegressionData(request)
+        container = SimulationContainer(simulation)
+        regression_data.sync_hdf_store(container)
+
+    def test_j_blue_estimators(self, simulation, request):
+        regression_data = RegressionData(request)
+        j_blue_estimator = (
+            simulation.transport.transport_state.radfield_mc_estimators.j_blue_estimator
+        )
+        expected = regression_data.sync_ndarray(j_blue_estimator)
+        npt.assert_allclose(j_blue_estimator, expected)
+
+    def test_spectrum(self, simulation, request):
+        regression_data = RegressionData(request)
+        luminosity = simulation.spectrum_solver.spectrum_real_packets.luminosity
+        expected = regression_data.sync_ndarray(luminosity.cgs.value)
+        expected = u.Quantity(expected, "erg /s")
+        assert_quantity_allclose(luminosity, expected)
+
+    def test_spectrum_integrated(self, simulation, request):
+        regression_data = RegressionData(request)
+        luminosity = simulation.spectrum_solver.spectrum_integrated.luminosity
+        expected = regression_data.sync_ndarray(luminosity.cgs.value)
+        expected = u.Quantity(expected, "erg /s")
+        assert_quantity_allclose(luminosity, expected)