Update tests

doped/chemical_potentials.py

@@ -1349,21 +1349,13 @@ def from_vaspruns(self, path="competing_phases", folder="vasp_std", csv_path=Non
  el = next(iter(vr.atomic_symbols)) # elemental, so first symbol is only (unique) element
  if el not in self.elemental_energies:
  self.elemental_energies[el] = energy_per_atom
- if el not in self.elements: # new (extrinsic) element
+ if el not in self.elements + self.extrinsic_elements: # new (extrinsic) element
  self.extrinsic_elements.append(el)
 
  elif energy_per_atom < self.elemental_energies[el]:
  # only include lowest energy elemental polymorph
  self.elemental_energies[el] = energy_per_atom
 
- # sort extrinsic elements and energies dict by atomic number (deterministically), and add to
- # self.elements:
- self.extrinsic_elements = sorted(self.extrinsic_elements, key=lambda x: Element(x).Z)
- self.elemental_energies = dict(
- sorted(self.elemental_energies.items(), key=lambda x: Element(x[0]).Z)
- )
- self.elements += self.extrinsic_elements
-
  d = {
  "Formula": comp.reduced_formula,
  "k-points": kpoints,
@@ -1373,6 +1365,14 @@ def from_vaspruns(self, path="competing_phases", folder="vasp_std", csv_path=Non
  }
  data.append(d)
 
+ # sort extrinsic elements and energies dict by atomic number (deterministically), and add to
+ # self.elements:
+ self.extrinsic_elements = sorted(self.extrinsic_elements, key=lambda x: Element(x).Z)
+ self.elemental_energies = dict(
+ sorted(self.elemental_energies.items(), key=lambda x: Element(x[0]).Z)
+ )
+ self.elements += self.extrinsic_elements
+
  formation_energy_df = _calculate_formation_energies(data, self.elemental_energies)
  self.data = formation_energy_df.to_dict(orient="records")
  self.formation_energy_df = pd.DataFrame(self._get_and_sort_formation_energy_data()) # sort data
@@ -1492,14 +1492,16 @@ def from_csv(self, csv_path):
  for i in self.data:
  c = Composition(i["Formula"])
  if len(c.elements) == 1:
- el = c.chemical_system
+ el = str(next(iter(c.elements))) # elemental, so first symbol is only (unique) element
  if "DFT Energy (eV/atom)" in list(formation_energy_df.columns):
  el_energy_per_atom = i["DFT Energy (eV/atom)"]
  else:
  el_energy_per_atom = i["DFT Energy (eV/fu)"] / c.num_atoms
 
  if el not in self.elemental_energies or el_energy_per_atom < self.elemental_energies[el]:
  self.elemental_energies[el] = el_energy_per_atom
+ if el not in self.elements + self.extrinsic_elements: # new (extrinsic) element
+ self.extrinsic_elements.append(el)
 
  if "Formation Energy (eV/fu)" not in list(formation_energy_df.columns):
  formation_energy_df = _calculate_formation_energies(self.data, self.elemental_energies)
@@ -1508,6 +1510,14 @@ def from_csv(self, csv_path):
  self.formation_energy_df = pd.DataFrame(self._get_and_sort_formation_energy_data()) # sort data
  self.formation_energy_df.set_index("Formula")
 
+ # sort extrinsic elements and energies dict by atomic number (deterministically), and add to
+ # self.elements:
+ self.extrinsic_elements = sorted(self.extrinsic_elements, key=lambda x: Element(x).Z)
+ self.elemental_energies = dict(
+ sorted(self.elemental_energies.items(), key=lambda x: Element(x[0]).Z)
+ )
+ self.elements += self.extrinsic_elements
+
  def calculate_chempots(
  self,
  extrinsic_species: Optional[str] = None,
@@ -1759,6 +1769,11 @@ def _calculate_extrinsic_chempot_lims(
  def chempots(self) -> dict:
  """
  Returns the calculated chemical potential limits.
+
+ If this is used with ``ExtrinsicCompetingPhases``
+ before calling ``calculate_chempots`` with a specified
+ ``extrinsic_species``, then the intrinsic chemical
+ potential limits will be returned.
  """
  if not hasattr(self, "_chempots"):
  self.calculate_chempots()

tests/test_chemical_potentials.py

@@ -382,13 +382,11 @@ def tearDown(self) -> None:
  def test_cpa_csv(self):
  stable_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  stable_cpa.from_csv(self.csv_path)
- self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(
- self.stable_system, self.extrinsic_species
- )
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  self.ext_cpa.from_csv(self.csv_path_ext)
 
- assert len(stable_cpa.elemental) == 2
- assert len(self.ext_cpa.elemental) == 3
+ assert len(stable_cpa.elements) == 2
+ assert len(self.ext_cpa.elements) == 3
  assert any(entry["Formula"] == "O2" for entry in stable_cpa.data)
  assert np.isclose(
  next(
@@ -408,11 +406,9 @@ def test_cpa_chempots(self):
  # check if it's no longer Element
  assert isinstance(next(iter(stable_cpa.intrinsic_chempots["elemental_refs"].keys())), str)
 
- self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(
- self.stable_system, self.extrinsic_species
- )
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  self.ext_cpa.from_csv(self.csv_path_ext)
- chempot_df = self.ext_cpa.calculate_chempots()
+ chempot_df = self.ext_cpa.calculate_chempots(extrinsic_species="La")
  assert next(iter(chempot_df["La-Limiting Phase"])) == "La2Zr2O7"
  assert np.isclose(next(iter(chempot_df["La"])), -9.46298748)
 
@@ -457,10 +453,16 @@ def test_ext_cpa_chempots(self):
  stable_cpa.from_csv(self.csv_path)
  _compare_chempot_dicts(stable_cpa.chempots, self.parsed_chempots)
 
- self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(
-  self.stable_system, self.extrinsic_species
- )
+ # for ext_cpa, because we haven't yet specified the extrinsic species (with calculate_chempots),
+ # just returns the intrinsic chempots:
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  self.ext_cpa.from_csv(self.csv_path_ext)
+ for host_el, chempot in self.ext_cpa.chempots["elemental_refs"].items():
+ assert chempot == self.parsed_ext_chempots["elemental_refs"][host_el]
+
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
+ self.ext_cpa.from_csv(self.csv_path_ext)
+ self.ext_cpa.calculate_chempots(extrinsic_species="La")
  assert self.ext_cpa.chempots["elemental_refs"] == self.parsed_ext_chempots["elemental_refs"]
 
  def test_sort_by(self):
@@ -478,7 +480,7 @@ def test_vaspruns(self):
  cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  path = self.path / "ZrO2"
  cpa.from_vaspruns(path=path, folder="relax", csv_path=self.csv_path)
- assert len(cpa.elemental) == 2
+ assert len(cpa.elements) == 2
  assert cpa.data[0]["Formula"] == "O2"
 
  cpa_no = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
@@ -488,10 +490,11 @@ def test_vaspruns(self):
  with pytest.raises(ValueError):
  cpa_no.from_vaspruns(path=0)
 
- ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system, self.extrinsic_species)
+ ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  path2 = self.path / "La_ZrO2"
  ext_cpa.from_vaspruns(path=path2, folder="relax", csv_path=self.csv_path_ext)
- assert len(ext_cpa.elemental) == 3
+ assert len(ext_cpa.elements) == 3
+ assert len(ext_cpa.extrinsic_elements) == 1
  # sorted by num_species, then alphabetically, then by num_atoms_in_fu, then by
  # formation_energy
  assert [entry["Formula"] for entry in ext_cpa.data] == [
@@ -559,13 +562,13 @@ def test_vaspruns(self):
  all_paths.append(ppgz)
  lst_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  lst_cpa.from_vaspruns(path=all_paths)
- assert len(lst_cpa.elemental) == 2
+ assert len(lst_cpa.elements) == 2
  assert len(lst_cpa.vasprun_paths) == 8
 
  all_fols = [p / "relax" for p in path.iterdir() if not p.name.startswith(".")]
  lst_fols_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  lst_fols_cpa.from_vaspruns(path=all_fols)
- assert len(lst_fols_cpa.elemental) == 2
+ assert len(lst_fols_cpa.elements) == 2
 
  def test_vaspruns_hidden_files(self):
  cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
@@ -693,14 +696,10 @@ def test_to_csv(self):
  # check chem limits the same:
  _compare_chempot_dicts(stable_cpa.chempots, reloaded_cpa.chempots)
 
- self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(
- self.stable_system, self.extrinsic_species
- )
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  self.ext_cpa.from_csv(self.csv_path_ext)
  self.ext_cpa.to_csv("competing_phases.csv")
- reloaded_ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(
- self.stable_system, self.extrinsic_species
- )
+ reloaded_ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  reloaded_ext_cpa.from_csv("competing_phases.csv")
  reloaded_ext_cpa._get_and_sort_formation_energy_data()
 
@@ -723,17 +722,21 @@ def test_to_csv(self):
  # check chem limits the same:
  _compare_chempot_dicts(reloaded_cpa.chempots, stable_cpa.chempots)
 
- self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(
-  self.stable_system, self.extrinsic_species
- )
+ # for ext_cpa, because we haven't yet specified the extrinsic species (with calculate_chempots),
+ # just returns the intrinsic chempots:
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  self.ext_cpa.from_csv(self.csv_path_ext)
+ for host_el, chempot in self.ext_cpa.chempots["elemental_refs"].items():
+ assert chempot == self.parsed_ext_chempots["elemental_refs"][host_el]
+
+ self.ext_cpa = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
+ self.ext_cpa.from_csv(self.csv_path_ext)
+ self.ext_cpa.calculate_chempots(extrinsic_species="La")
  assert self.ext_cpa.chempots["elemental_refs"] == self.parsed_ext_chempots["elemental_refs"]
 
  # test correct sorting:
  self.ext_cpa.to_csv("competing_phases.csv", prune_polymorphs=True, sort_by_energy=True)
- reloaded_ext_cpa_energy_sorted = chemical_potentials.CompetingPhasesAnalyzer(
- self.stable_system, self.extrinsic_species
- )
+ reloaded_ext_cpa_energy_sorted = chemical_potentials.CompetingPhasesAnalyzer(self.stable_system)
  reloaded_ext_cpa_energy_sorted.from_csv("competing_phases.csv")
  assert len(reloaded_ext_cpa.data) == 8 # polymorphs pruned