def write_run(run, run_folder, write_vasprun=False):
os.makedirs(run_folder, exist_ok=True)
incar = Incar.from_dict(run['incar'])
poscar = Poscar.from_dict(run['poscar'])
kpoints = Kpoints.from_dict(run['kpoints'])
energy = run['energy']
files = [
('INCAR', incar),
('KPOINTS', kpoints),
('POSCAR', poscar),
]
for filename, pymg_object in files:
pymg_object.write_file(os.path.join(run_folder, filename))
with open(os.path.join(run_folder, 'energy.txt'), 'w') as f:
f.write(str(energy))
if write_vasprun:
if not os.path.exists(os.path.join(run_folder, 'vasprun.xml')):
print(' Writing Vasprun')
get_file(fs, run['vasprun'], new_file=os.path.join(run_folder, 'vasprun.xml'))
def add_to_string(string, base, ovac, bounds, weight=2, max_val=2):
labels = ('material', 'barrier', 'ovac', 'density', 'fermi', 'o_p_band')
labels = ('material', 'barrier', 'density', 'fermi', 'o_p_band')
material = base['material'][1]
if 'descriptors' in base and all(
[x in base['descriptors']
for x in labels[3:]]): # if all labels are made
descriptors = base['descriptors']
else:
s = Structure.from_dict(base['poscar']['structure'])
v_file = get_file(fs, base['vasprun'])
v = Vasprun(v_file)
os.remove(v_file)
# set descriptors
descriptors = {
'density': s.volume / len(s),
'bandgap': v.tdos.get_gap(),
'fermi': v.efermi,
'o_p_band': get_band_center(v, 'p', 'O'),
'p_band': get_band_center(v, 'p', 'O')
}
base['descriptors'] = descriptors
db.database.update_one({'_id': base['_id']},
{'$set': {
'descriptors': descriptors
}})
properties = [descriptors[label] for label in labels[2:]]
predicted = (
0.73118E+00 + 0.96547E-04 * ovac**6 +
0.75320E-02 * np.exp(ovac) * ovac / descriptors['o_p_band']
# -0.28972E+01 +
# 0.45890E+02 * np.exp(descriptors['o_p_band']) * descriptors['density'] * descriptors['density']
)
format_string = '{} ' + '{:.4f} ' * len(labels[1:]) + '\n'
if string == '':
label_string = '{} ' * len(labels) + '\n'
string = label_string.format(*labels)
difference = abs(bounds[0] - bounds[1])
if difference > max_val:
return string, predicted
else:
weight = max(2, weight * (max_val - difference) / max_val)
for bound in np.linspace(bounds[0], bounds[1], weight):
string += format_string.format(material, bound, *properties)
# string += format_string.format(material, bound, ovac, *properties)
return string, predicted
def fxn(self, unit, base, start, final):
f = get_file(fs, unit['ICOHPLIST_lobster'])
icohp = Icohplist(filename=f).icohpcollection
os.remove(f)
elements = unit['elements'].copy()
elements.pop(elements.index('O'))
elements.append('O') # Put O at end for easier referencing
material = get_lower_material(unit)
unit_s = Poscar.from_dict(unit['poscar']).structure
summed_icohp = {}
for i, site in enumerate(unit_s):
icohp_dict = icohp.get_icohp_dict_of_site(i)
for icohp_key in icohp_dict:
icohp_value = icohp_dict[icohp_key].summed_icohp
# print('{}: {:3.2f}'.format(pt['site_index'], pt['weight']))
if site.species_string in summed_icohp:
summed_icohp[site.species_string] = (
summed_icohp[site.species_string][0] + icohp_value,
summed_icohp[site.species_string][1] + 1)
else:
summed_icohp[site.species_string] = (icohp_value, 1)
if material.find(elements[0].lower()) == 0 and material.find(
elements[1].lower()) == 0:
raise Exception('Both Could be Element A')
elif material.find(elements[0].lower()) == 0:
bonds = {
'A_Bonds':
summed_icohp[elements[0]][0] / summed_icohp[elements[0]][1],
'B_Bonds':
summed_icohp[elements[1]][0] / summed_icohp[elements[1]][1]
}
elif material.find(elements[1].lower()) == 0:
bonds = {
'A_Bonds':
summed_icohp[elements[1]][0] / summed_icohp[elements[1]][1],
'B_Bonds':
summed_icohp[elements[0]][0] / summed_icohp[elements[0]][1]
}
else:
raise Exception('Couldn\'t find A')
bonds['O_bonds'] = summed_icohp['O'][0] / summed_icohp['O'][1]
return bonds
]
metals = ['bimno3']
for material in materials:
print(material)
# vaspruns[material] = {}
for type in ['base', 'start']:
try:
vaspruns[material][type]
except:
try:
vaspruns[material]
except:
vaspruns[material] = {}
if type == 'lb':
v_file = get_file(fs, mat_dict[material][type]['vasprun'])
v_file = get_file(fs, mat_dict[material][type]['vasprun'])
vaspruns[material][type] = Vasprun(v_file)
os.remove(v_file)
#%% Plot
import Make_Dos
from scipy.interpolate import spline
figsize=(3,5.5)
ylim = [0,3]
xlim = [-10,10]
#vasprun shift name
plots = [
def get_vasprun(run):
v = get_file(fs, run['vasprun'], 'vasprun')
vasprun = Vasprun(v)
os.remove(v)
return vasprun
final_exists = True
final = f
if not final_exists:
continue
print(material)
pairs = [
('start', start),
('final', final),
]
material_folder = os.path.join(folder, material)
for name, d in pairs:
run_folder = os.path.join(material_folder, name)
os.makedirs(run_folder, exist_ok=True)
incar = Incar.from_dict(d['incar'])
poscar = Poscar.from_dict(d['poscar'])
kpoints = Kpoints.from_dict(d['kpoints'])
for f in ['OUTCAR', 'vasprun']:
outcar_file = get_file(fs, d[f.lower()])
if f == 'vasprun':
f = 'vasprun.xml'
shutil.move(outcar_file, os.path.join(run_folder, f))
files = [
('INCAR', incar),
('KPOINTS', kpoints),
('POSCAR', poscar),
]
for filename, pymg_object in files:
pymg_object.write_file(os.path.join(run_folder, filename))
yerr = np.array(err)/2
x = x[np.where(xerr < maxrange)]
y = y[np.where(xerr < maxrange)]
yerr = yerr[np.where(xerr < maxrange)]
ll = np.array(label_list)[np.where(xerr < maxrange)]
xerr = xerr[np.where(xerr < maxrange)]
color = []
for material in ll:
print(material)
f=get_file(fs, mat_dict[material]['base']['vasprun'])
vasprun = Vasprun(f)
color.append(vasprun.get_band_structure().get_band_gap()['energy'])
os.remove(f)
# color.append(mat_dict[material]['base']['descriptors']['bandgap'])
# #%%
#
maxbarrier = 5.5
plt.plot([0, maxbarrier], [0, maxbarrier], '--', color='gray')
plt.errorbar(x, y, xerr=xerr, yerr=yerr, fmt='none', color='k')
scat = plt.scatter(x, y, c=color, cmap='gnuplot2', marker='o')
# scat = plt.scatter(x, y, marker='o)
plt.colorbar(scat, label='Band Gap (eV)')
# plt.colorbar(scat, label='V$_O$ Energy (eV)')
plt.xlabel('V$_O$ Diffusion Barrier (eV)')
('INCAR', incar),
('KPOINTS', kpoints),
('00/POSCAR', start),
('01/POSCAR', relax),
('02/POSCAR', final),
]
fs_files = [
(mat['start']['outcar'], os.path.join(run_folder, '00', 'OUTCAR')),
(mat['start']['vasprun'],os.path.join(run_folder, '00', 'vasprun.xml')),
(mat['finals'][i-1]['outcar'],os.path.join(run_folder, '02', 'OUTCAR')),
(mat['finals'][i-1]['vasprun'],os.path.join(run_folder, '02', 'vasprun.xml')),
]
for oid, location in fs_files:
if not os.path.exists(location):
get_file(fs, oid, new_file=location)
for filename, pymg_object in files:
pymg_object.write_file(os.path.join(run_folder, filename))
# with open(os.path.join(run_folder, 'energy.txt'), 'w') as f:
# f.write(str(ub['energies'][ub_i]))
with open(os.path.join(run_folder, 'potcar.txt'), 'w') as f:
f.write('\n'.join(potcar))
neb = nebmake('', start.structure,
final.structure, 4, tolerance=tolerance, write=False, quickfail=True)
del incar['SPRING']
incar['IMAGES'] = 3
incar['LCLIMB'] = True
#!/usr/bin/env python
from AddDB import load_db
from Database_Tools import get_file
from Classes_Pymatgen import Poscar,Kpoints
import sys
import os
(db, fs, client) = load_db()
match_criteria = {
'defect' : 'mn-vac',
'defect_charge' : 2
}
matches = list(db.database.find(match_criteria))
print(len(matches))
if len(sys.argv) > 1 and sys.argv[1] == 'write':
for match in matches[0:1]:
name = '{}.{}'.format(''.join([x for x in match['material'] if 'mnte' not in x]), match['antiferromagnetic_label'][0])
os.makedirs(name, exist_ok=True)
get_file(fs, match['outcar'], fix_as='outcar', new_file=os.path.join(name, 'OUTCAR'))
Poscar.from_dict(match['poscar']).write_file(os.path.join(name, 'POSCAR'))
Kpoints.from_dict(match['kpoints']).write_file(os.path.join(name, 'KPOINTS'))
print(name)
gmean([lb_bars[i], ub_bars[i]]) if ub_bars[i] else 9999
for i in range(len(thermo))
]
lowest_ts_estimate = min(ts_estimates)
i = ts_estimates.index(lowest_ts_estimate) - 1
i = 1
if i == -1:
continue
base = mat['base']
start = mat['start']
final = mat['finals'][i]
o_nelect = 6
outcar_file = get_file(fs, base['outcar'])
outcar = Outcar(outcar_file)
os.remove(outcar_file)
pairs = [
('base', base),
('start', start),
('final.{}'.format(i), final),
]
material_folder = os.path.join(folder, material)
for name, d in pairs:
run_folder = os.path.join(material_folder, name)
os.makedirs(run_folder, exist_ok=True)
incar = Incar.from_dict(d['incar'])
poscar = Poscar.from_dict(d['poscar'])