def main():
df = pd.read_csv('calc_data.csv')
converged = df['converged'] == True
few_steps = df['ionic_steps'] < 10
to_scrape = list(df[converged & few_steps].iloc[:, 0])
converged_calculations = []
for converged_calculation in tqdm(to_scrape):
vr = Vasprun(f'{converged_calculation}/vasprun.xml',
parse_potcar_file=False)
entry = vr.get_computed_entry()
entry.entry_id = converged_calculation
entry_dict = entry.as_dict()
if vr.parameters['LORBIT'] == 11:
outcar = Outcar(f'{converged_calculation}/OUTCAR')
entry_dict.update({'MAGMOMS': outcar.magnetization})
converged_calculations.append(entry_dict)
with open('calculation_data.json', 'w') as calc_data:
json.dump(converged_calculations, calc_data)
entry for entry in all_entries if entry.composition.reduced_formula ==
Composition(formula).reduced_formula
]
relevant_entries = sorted(relevant_entries,
key=lambda e: e.energy_per_atom)
return relevant_entries[0]
def get_comp_entries(formula, all_entries):
relevant_entries = [
entry for entry in all_entries if entry.composition.reduced_formula ==
Composition(formula).reduced_formula
]
return relevant_entries
def find_entry_index(formula, all_entries):
entry_index = [
all_entries.index(entry) for entry in all_entries
if entry.composition.reduced_formula == Composition(
formula).reduced_formula
]
return entry_index
vasprun = Vasprun("vasprun.xml")
entry = vasprun.get_computed_entry(inc_structure=True)
compatibility = MaterialsProjectCompatibility()
entry = compatibility.process_entry(entry)
#entries = compatibility.process_entries([entry] + mp_entries)
