Misc comments and checks (#671)

* Add a clarifying comment to obs_table.py

* Add some comments

* Update physical_model.py

* Add some validity checks

* Update graph_state.py

Author: jeremykubica

src/lightcurvelynx/effects/extinction.py

@@ -177,4 +177,7 @@ def apply(
         if wavelengths is None:
             raise ValueError("wavelengths must be provided")
 
-        return flux_density * self.extinction_model.extinguish(wavelengths * u.angstrom, Ebv=ebv)
+        # The extinction factor computed by dust_extinction is a multiplicative
+        # factor to reduce the flux (<= 1 for all wavelengths).
+        ext_factor = self.extinction_model.extinguish(wavelengths * u.angstrom, Ebv=ebv)
+        return flux_density * ext_factor

src/lightcurvelynx/graph_state.py

@@ -869,7 +869,7 @@ def to_networkx(self):
         """
         try:
             import networkx as nx
-        except ImportError as err:
+        except ImportError as err:  # pragma: no cover
             raise ImportError(
                 "NetworkX is required to convert the dependency graph to a NetworkX graph. "
                 "Please install it with 'pip install networkx'."
@@ -919,7 +919,7 @@ def draw(self, param_name=None):
         try:
             import matplotlib.pyplot as plt
             import networkx as nx
-        except ImportError as err:
+        except ImportError as err:  # pragma: no cover
             raise ImportError(
                 "NetworkX and Matplotlib are required to draw the graph. "
                 "Please install them with 'pip install networkx matplotlib'."

src/lightcurvelynx/models/physical_model.py

@@ -94,7 +94,8 @@ def __init__(
                 allow_gradient=False,
             )
         elif redshift is not None and kwargs.get("cosmology") is not None:
-            self._redshift_func = RedshiftDistFunc(redshift=self.redshift, **kwargs)
+            cosmology = kwargs.pop("cosmology")
+            self._redshift_func = RedshiftDistFunc(redshift=self.redshift, cosmology=cosmology)
             self.add_parameter(
                 "distance",
                 self._redshift_func,

src/lightcurvelynx/models/redback_models.py

@@ -107,6 +107,8 @@ def __init__(
                 ) from err
 
             self.source_name = source
+            if source not in redback.model_library.all_models_dict:  # pragma: no cover
+                raise ValueError(f"Redback model '{source}' not found in redback model library.")
             self.source = redback.model_library.all_models_dict[source]
         else:
             self.source_name = source.__name__

src/lightcurvelynx/obstable/obs_table.py

@@ -705,6 +705,9 @@ def range_search(self, query_ra, query_dec, *, radius=None, t_min=None, t_max=No
         # Confirm the query RA and Dec have the same length.
         if len(query_ra) != len(query_dec):
             raise ValueError("Query RA and Dec must have the same length.")
+
+        # Check that there are no None values in the query. We use == to do
+        # an element-wise comparison.
         if np.any(query_ra == None) or np.any(query_dec == None):  # noqa: E711
             raise ValueError("Query RA and dec cannot contain None.")
 

tests/lightcurvelynx/astro_utils/test_sed_basis_models.py

@@ -47,6 +47,14 @@ def test_sed_basis_model() -> None:
     )
     assert np.allclose(flux_density, expected)
 
+    # The computation fails if any filter is unknown.
+    with pytest.raises(ValueError):
+        _ = sed_basis.compute_sed_from_bandfluxes(["r", "g", "x", "r"], bandfluxes=[2.0, 1.0, 1.5, 2.5])
+
+    # The computation fails if bandfluxes length doesn't match filters length.
+    with pytest.raises(ValueError):
+        _ = sed_basis.compute_sed_from_bandfluxes(["r", "g", "g", "r"], bandfluxes=[2.0, 1.0, 1.5])
+
     # SED creation fails if the lengths do not match.
     with pytest.raises(ValueError):
         _ = SEDBasisModel(np.array([300, 400, 500, 600, 700]), filter_data)

tests/lightcurvelynx/effects/test_extinction.py

@@ -114,6 +114,8 @@ def test_constant_dust_extinction():
     states = model.sample_parameters(num_samples=3)
     fluxes = model.evaluate_sed(times, wavelengths, states)
 
+    # We check that all fluxes are reduced, and that higher ebv leads to
+    # lower fluxes.
     assert fluxes.shape == (3, 5, 3)
     assert np.all(fluxes < 100.0)
     assert np.all(fluxes[0, :, :] > fluxes[1, :, :])