Some minor improvements

species/data/database.py

@@ -91,13 +91,17 @@ def _descend(
             """
 
             if isinstance(h5_object, (h5py._hl.files.File, h5py._hl.group.Group)):
-                for key in h5_object.keys():
-                    print(seperator + "- " + key + ": " + str(h5_object[key]))
-                    _descend(h5_object[key], seperator=seperator + "\t")
+                for group_key in h5_object.keys():
+                    print(seperator + "- " + group_key + ": " + str(h5_object[group_key]))
+
+                    _descend(h5_object[group_key], seperator=seperator + "\t")
+
+                    for attr_key in h5_object[group_key].attrs.keys():
+                        print(seperator + "\t" + "- " + attr_key + " = " + str(h5_object[group_key].attrs[attr_key]))
 
             elif isinstance(h5_object, h5py._hl.dataset.Dataset):
-                for key in h5_object.attrs.keys():
-                    print(seperator + "- " + key + ": " + str(h5_object.attrs[key]))
+                for attr_key in h5_object.attrs.keys():
+                    print(seperator + "- " + attr_key + ": " + str(h5_object.attrs[attr_key]))
 
         with h5py.File(self.database, "r") as hdf_file:
             _descend(hdf_file)

species/data/model_data/custom_model.py

@@ -273,6 +273,11 @@ def add_custom_model_grid(
         np.asarray(flux),
     )
 
-    write_data(model_name, parameters, database, data_sorted)
+    if wavel_sampling is None:
+        wavel_sampling = np.mean(
+            0.5 * (wavelength[1:] + wavelength[:-1]) / np.diff(wavelength)
+        )
+
+    write_data(model_name, parameters, wavel_sampling, database, data_sorted)
 
     add_missing(model_name, parameters, database)

species/data/model_data/model_spectra.py

@@ -251,7 +251,6 @@ def add_model_grid(
     if wavel_range is not None and wavel_sampling is not None:
         wavelength = create_wavelengths(wavel_range, wavel_sampling)
         print(f"Wavelength range (um) = {wavel_range[0]} - {wavel_range[1]}")
-        print(f"Sampling (lambda/d_lambda) = {wavel_sampling}")
 
     else:
         wavelength = None
@@ -260,7 +259,9 @@ def add_model_grid(
             f"{model_info['wavelength range'][0]} - "
             f"{model_info['wavelength range'][1]}"
         )
-        print(f"Sampling (lambda/d_lambda) = {model_info['lambda/d_lambda']}")
+        wavel_sampling = model_info["lambda/d_lambda"]
+
+    print(f"Sampling (lambda/d_lambda) = {wavel_sampling}")
 
     if teff_range is None:
         print(
@@ -386,6 +387,8 @@ def add_model_grid(
         np.asarray(flux),
     )
 
-    write_data(model_tag, model_info["parameters"], database, data_sorted)
+    write_data(
+        model_tag, model_info["parameters"], wavel_sampling, database, data_sorted
+    )
 
     add_missing(model_tag, model_info["parameters"], database)

species/util/data_util.py

@@ -308,6 +308,7 @@ def sort_data(
 def write_data(
     model: str,
     parameters: List[str],
+    wavel_sampling: float,
     database: h5py._hl.files.File,
     data_sorted: List[np.ndarray],
 ) -> None:
@@ -321,8 +322,10 @@ def write_data(
         Atmosphere model.
     parameters : list(str)
         Model parameters.
+    wavel_sampling : float
+        Wavelength sampling :math:`\\lambda/\\Delta\\lambda`.
     database: h5py._hl.files.File
-        Database.
+        HDF5 database.
     data_sorted : list(np.ndarray)
         Sorted model data with the parameter values, wavelength
         points (um), and flux densities (W m-2 um-1).
@@ -341,6 +344,7 @@ def write_data(
     dset = database.create_group(f"models/{model}")
 
     dset.attrs["n_param"] = n_param
+    dset.attrs["lambda/d_lambda"] = wavel_sampling
 
     for i, item in enumerate(parameters):
         dset.attrs[f"parameter{i}"] = item