Remove need for hard-coded ELEMENT_DICT.

emle/emle.py

@@ -49,9 +49,11 @@
 BOHR_TO_ANGSTROM = ase.units.Bohr
 EV_TO_HARTREE = 1.0 / ase.units.Hartree
 KCAL_MOL_TO_HARTREE = 1.0 / ase.units.Hartree * ase.units.kcal / ase.units.mol
+
+# Settings for the default model. For system specific models, these will be
+# overwritten by values in the model file.
 SPECIES = (1, 6, 7, 8, 16)
 SIGMA = 1e-3
-
 SPHERICAL_EXPANSION_HYPERS_COMMON = {
     "gaussian_sigma_constant": 0.5,
     "gaussian_sigma_type": "Constant",
@@ -61,8 +63,6 @@
     "global_species": SPECIES,
 }
 
-ELEMENT_DICT = {1: "H", 6: "C", 7: "N", 8: "O", 16: "S"}
-
 
 class GPRCalculator:
     """Predicts an atomic property for a molecule with Gaussian Process Regression (GPR)."""
@@ -844,6 +844,11 @@ def __init__(
                 except:
                     self._hypers[key] = self._params[key]
 
+        # Work out the supported elements.
+        self._supported_elements = []
+        for id in self._hypers["global_species"]:
+            self._supported_elements.append(ase.atoms.Atom(id).symbol)
+
         self._get_soap = SOAPCalculatorSpinv(self._hypers)
         self._q_core = torch.tensor(
             self._params["q_core"], dtype=torch.float32, device=self._device
@@ -1001,11 +1006,11 @@ def run(self, path=None):
         for id in atomic_numbers:
             try:
                 species_id.append(self._hypers["global_species"].index(id))
-                elements.append(ELEMENT_DICT[id])
+                elements.append(ase.atom.Atom(id).symbol)
             except:
                 raise ValueError(
                     f"Unsupported element index '{id}'. "
-                    f"We currently support {', '.join(ELEMENT_DICT.values())}."
+                    f"The current model supports {', '.join(self._supported_elements)}"
                 )
         self._species_id = np.array(species_id)