def add_data_entry(self, path):
"""
parse the data found in path and add it to data
"""
try:
xml = Vasprun(os.path.join(path, "vasprun.xml"))
out = Outcar(os.path.join(path, "OUTCAR"))
if xml.converged or True:
entry = {
'system': path.split('/')[1].split('_par')[0],
"NPAR": xml.parameters.get('NPAR'),
'nband': xml.parameters.get('NBANDS'),
'ncpus': int(out.run_stats['cores']),
"final_energy": xml.final_energy,
"vasp_version": xml.vasp_version,
"generator": xml.generator,
"generator_hash": hash(frozenset(xml.generator)),
"run_stats": out.run_stats
}
entry_hash = hash((entry['ncpus'], entry['NPAR'],
entry['generator_hash'], entry['system']))
#print(entry)
self.data.update({str(entry_hash): entry})
print(entry['ncpus'], entry['NPAR'], entry['generator_hash'],
entry['system'])
except (ParseError, ValueError, IOError):
try:
out = Outcar(os.path.join(path, "OUTCAR"))
inc = Incar(os.path.join(path, "INCAR"))
entry = {
"NPAR": inc.as_dict()['NPAR'],
"nband": inc.as_dict()['nband'],
'ncpus': int(out.run_stats['cores']),
"final_energy": -1,
"vasp_version": 'v',
"generator": {},
"generator_hash": hash(' '),
"run_stats": out.run_stats
}
entry_hash = hash((entry['ncpus'], entry['NPAR'],
entry['generator_hash'], entry['system']))
log(entry)
self.data.update({str(entry_hash): entry})
print(entry['ncpus'], entry['NPAR'], entry['generator_hash'],
entry['system'])
except (ParseError, ValueError, IOError):
print('parsing error')
pass
def run_task(self, fw_spec):
try:
vasp_run = Vasprun("vasprun.xml", parse_dos=False,
parse_eigen=False)
outcar = Outcar(os.path.join(os.getcwd(), "OUTCAR"))
except Exception as e:
raise RuntimeError("Can't get valid results from relaxed run: " +
str(e))
user_incar_settings = MPNonSCFVaspInputSet.get_incar_settings(
vasp_run, outcar)
user_incar_settings.update({"NPAR": 2})
structure = MPNonSCFVaspInputSet.get_structure(vasp_run, outcar,
initial_structure=True)
if self.line:
mpnscfvip = MPNonSCFVaspInputSet(user_incar_settings, mode="Line")
for k, v in mpnscfvip.get_all_vasp_input(
structure, generate_potcar=True).items():
v.write_file(os.path.join(os.getcwd(), k))
kpath = HighSymmKpath(structure)
else:
mpnscfvip = MPNonSCFVaspInputSet(user_incar_settings,
mode="Uniform")
for k, v in mpnscfvip.get_all_vasp_input(
structure, generate_potcar=True).items():
v.write_file(os.path.join(os.getcwd(), k))
if self.line:
return FWAction(stored_data={"kpath": kpath.kpath,
"kpath_name": kpath.name})
else:
return FWAction()
def from_previous_vasp_run(previous_vasp_dir, output_dir='.',
user_incar_settings=None,
make_dir_if_not_present=True):
"""
Generate a set of Vasp input files for static calculations from a
directory of previous Vasp run.
Args:
previous_vasp_dir:
The directory contains the outputs(vasprun.xml and OUTCAR) of
previous vasp run.
output_dir:
The directory to write the VASP input files for the static
calculations. Default to write in the current directory.
make_dir_if_not_present:
Set to True if you want the directory (and the whole path) to
be created if it is not present.
"""
try:
vasp_run = Vasprun(os.path.join(previous_vasp_dir, "vasprun.xml"),
parse_dos=False, parse_eigen=None)
outcar = Outcar(os.path.join(previous_vasp_dir, "OUTCAR"))
except:
traceback.format_exc()
raise RuntimeError("Can't get valid results from previous run")
structure = MPStaticVaspInputSet.get_structure(
vasp_run, outcar)
mpsvip = MPStaticVaspInputSet(
user_incar_settings=user_incar_settings)
mpsvip.write_input(structure, output_dir, make_dir_if_not_present)
def get_fermi_energy(self, directory):
"""Returns the Fermi energy from a directory"""
abspath = '%s/%s/' % (self.directory, directory)
if ('vasprun.xml' in os.listdir(abspath)):
return Vasprun('%s/vasprun.xml' % abspath).efermi
elif ('OUTCAR' in os.listdir(abspath)):
return Outcar('%s/OUTCAR' % abspath).efermi
def test_single_atom(self):
filepath = os.path.join(test_dir, "OUTCAR.Al")
outcar = Outcar(filepath)
expected_mag = ({u'p': 0.0, u's': 0.0, u'd': 0.0, u'tot': 0.0},)
expected_chg = ({u'p': 0.343, u's': 0.425, u'd': 0.0, u'tot': 0.768},)
self.assertAlmostEqual(outcar.magnetization, expected_mag)
self.assertAlmostEqual(outcar.charge, expected_chg)
self.assertFalse(outcar.is_stopped)
self.assertEqual(outcar.run_stats, {'System time (sec)': 0.592,
'Total CPU time used (sec)': 50.194,
'Elapsed time (sec)': 52.337,
'Maximum memory used (kb)': 62900.0,
'Average memory used (kb)': 0.0,
'User time (sec)': 49.602,
'cores': '32'})
self.assertAlmostEqual(outcar.efermi, 8.0942)
self.assertAlmostEqual(outcar.nelect, 3)
self.assertAlmostEqual(outcar.total_mag, 8.2e-06)
self.assertIsNotNone(outcar.as_dict())
def test_init(self):
for f in ['OUTCAR', 'OUTCAR.gz']:
filepath = os.path.join(test_dir, f)
outcar = Outcar(filepath)
expected_mag = ({'d': 0.0, 'p': 0.003, 's': 0.002, 'tot': 0.005},
{'d': 0.798, 'p': 0.008, 's': 0.007, 'tot': 0.813},
{'d': 0.798, 'p': 0.008, 's': 0.007, 'tot': 0.813},
{'d': 0.0, 'p':-0.117, 's': 0.005, 'tot':-0.112},
{'d': 0.0, 'p':-0.165, 's': 0.004, 'tot':-0.162},
{'d': 0.0, 'p':-0.117, 's': 0.005, 'tot':-0.112},
{'d': 0.0, 'p':-0.165, 's': 0.004, 'tot':-0.162})
expected_chg = ({'p': 0.154, 's': 0.078, 'd': 0.0, 'tot': 0.232},
{'p': 0.707, 's': 0.463, 'd': 8.316, 'tot': 9.486},
{'p': 0.707, 's': 0.463, 'd': 8.316, 'tot': 9.486},
{'p': 3.388, 's': 1.576, 'd': 0.0, 'tot': 4.964},
{'p': 3.365, 's': 1.582, 'd': 0.0, 'tot': 4.947},
{'p': 3.388, 's': 1.576, 'd': 0.0, 'tot': 4.964},
{'p': 3.365, 's': 1.582, 'd': 0.0, 'tot': 4.947})
self.assertAlmostEqual(outcar.magnetization, expected_mag, 5,
"Wrong magnetization read from Outcar")
self.assertAlmostEqual(outcar.charge, expected_chg, 5,
"Wrong charge read from Outcar")
self.assertFalse(outcar.is_stopped)
self.assertEqual(outcar.run_stats, {'System time (sec)': 0.938,
'Total CPU time used (sec)': 545.142,
'Elapsed time (sec)': 546.709,
'Maximum memory used (kb)': 0.0,
'Average memory used (kb)': 0.0,
'User time (sec)': 544.204,
'cores': '8'})
self.assertAlmostEqual(outcar.efermi, 2.0112)
self.assertAlmostEqual(outcar.nelect, 44.9999991)
self.assertAlmostEqual(outcar.total_mag, 0.9999998)
self.assertIsNotNone(outcar.as_dict())
filepath = os.path.join(test_dir, 'OUTCAR.stopped')
outcar = Outcar(filepath)
self.assertTrue(outcar.is_stopped)
def run_task(self, fw_spec):
user_incar_settings = {"NPAR": 2}
MPStaticVaspInputSet.from_previous_vasp_run(os.getcwd(),
user_incar_settings=user_incar_settings)
structure = MPStaticVaspInputSet.get_structure(Vasprun("vasprun.xml"), Outcar("OUTCAR"),
initial_structure=False,
additional_info=True)
return FWAction(stored_data={'refined_structure': structure[1][0].to_dict,
'conventional_standard_structure': structure[1][1].to_dict,
'symmetry_dataset': structure[1][2],
'symmetry_operations': [x.to_dict for x in structure[1][3]]})
def test_init(self):
filepath = os.path.join(test_dir, 'OUTCAR')
outcar = Outcar(filepath)
expected_mag = ({'d': 0.0, 'p': 0.003, 's': 0.002, 'tot': 0.005},
{'d': 0.798, 'p': 0.008, 's': 0.007, 'tot': 0.813},
{'d': 0.798, 'p': 0.008, 's': 0.007, 'tot': 0.813},
{'d': 0.0, 'p':-0.117, 's': 0.005, 'tot':-0.112},
{'d': 0.0, 'p':-0.165, 's': 0.004, 'tot':-0.162},
{'d': 0.0, 'p':-0.117, 's': 0.005, 'tot':-0.112},
{'d': 0.0, 'p':-0.165, 's': 0.004, 'tot':-0.162})
expected_chg = ({'p': 0.154, 's': 0.078, 'd': 0.0, 'tot': 0.232},
{'p': 0.707, 's': 0.463, 'd': 8.316, 'tot': 9.486},
{'p': 0.707, 's': 0.463, 'd': 8.316, 'tot': 9.486},
{'p': 3.388, 's': 1.576, 'd': 0.0, 'tot': 4.964},
{'p': 3.365, 's': 1.582, 'd': 0.0, 'tot': 4.947},
{'p': 3.388, 's': 1.576, 'd': 0.0, 'tot': 4.964},
{'p': 3.365, 's': 1.582, 'd': 0.0, 'tot': 4.947})
self.assertAlmostEqual(outcar.magnetization, expected_mag, 5,
"Wrong magnetization read from Outcar")
self.assertAlmostEqual(outcar.charge, expected_chg, 5,
"Wrong charge read from Outcar")
self.assertFalse(outcar.is_stopped)
self.assertEqual(outcar.run_stats, {'System time (sec)': 0.938,
'Total CPU time used (sec)': 545.142,
'Elapsed time (sec)': 546.709,
'Maximum memory used (kb)': 0.0,
'Average memory used (kb)': 0.0,
'User time (sec)': 544.204})
self.assertAlmostEqual(outcar.efermi, 2.0112)
self.assertAlmostEqual(outcar.nelect, 44.9999991)
self.assertAlmostEqual(outcar.total_mag, 0.9999998)
self.assertIsNotNone(outcar.to_dict)
filepath = os.path.join(test_dir, 'OUTCAR.stopped')
outcar = Outcar(filepath)
self.assertTrue(outcar.is_stopped)
def test_single_atom(self):
filepath = os.path.join(test_dir, "OUTCAR.Al")
outcar = Outcar(filepath)
expected_mag = ({u'p': 0.0, u's': 0.0, u'd': 0.0, u'tot': 0.0}, )
expected_chg = ({u'p': 0.343, u's': 0.425, u'd': 0.0, u'tot': 0.768}, )
self.assertAlmostEqual(outcar.magnetization, expected_mag)
self.assertAlmostEqual(outcar.charge, expected_chg)
self.assertFalse(outcar.is_stopped)
self.assertEqual(
outcar.run_stats, {
'System time (sec)': 0.592,
'Total CPU time used (sec)': 50.194,
'Elapsed time (sec)': 52.337,
'Maximum memory used (kb)': 62900.0,
'Average memory used (kb)': 0.0,
'User time (sec)': 49.602,
'cores': '32'
})
self.assertAlmostEqual(outcar.efermi, 8.0942)
self.assertAlmostEqual(outcar.nelect, 3)
self.assertAlmostEqual(outcar.total_mag, 8.2e-06)
self.assertIsNotNone(outcar.as_dict())
def from_previous_vasp_run(previous_vasp_dir,
output_dir='.',
mode="Uniform",
user_incar_settings=None,
copy_chgcar=True,
make_dir_if_not_present=True):
"""
Generate a set of Vasp input files for NonSCF calculations from a
directory of previous static Vasp run.
Args:
previous_vasp_dir:
The directory contains the outputs(vasprun.xml and OUTCAR) of
previous vasp run.
output_dir:
The directory to write the VASP input files for the NonSCF
calculations. Default to write in the current directory.
copy_chgcar:
Default to copy CHGCAR from SC run
make_dir_if_not_present:
Set to True if you want the directory (and the whole path) to
be created if it is not present.
"""
try:
vasp_run = Vasprun(os.path.join(previous_vasp_dir, "vasprun.xml"),
parse_dos=False,
parse_eigen=None)
outcar = Outcar(os.path.join(previous_vasp_dir, "OUTCAR"))
except:
traceback.format_exc()
raise RuntimeError("Can't get valid results from previous run")
#Get a Magmom-decorated structure
structure = MPNonSCFVaspInputSet.get_structure(vasp_run, outcar)
user_incar_settings = MPNonSCFVaspInputSet.get_incar_settings(
vasp_run, outcar)
mpnscfvip = MPNonSCFVaspInputSet(user_incar_settings, mode)
mpnscfvip.write_input(structure, output_dir, make_dir_if_not_present)
if copy_chgcar:
try:
shutil.copyfile(os.path.join(previous_vasp_dir, "CHGCAR"),
os.path.join(output_dir, "CHGCAR"))
except Exception as e:
traceback.format_exc()
raise RuntimeError("Can't copy CHGCAR from SC run" + '\n' +
str(e))
def test_core_state_eigen(self):
filepath = os.path.join(test_dir, "OUTCAR.CL")
cl = Outcar(filepath).read_core_state_eigen()
self.assertAlmostEqual(cl[6]["2s"][-1], -174.4779)
def test_init(self):
for f in ['OUTCAR', 'OUTCAR.gz']:
filepath = os.path.join(test_dir, f)
outcar = Outcar(filepath)
expected_mag = ({'d': 0.0, 'p': 0.003, 's': 0.002, 'tot': 0.005},
{'d': 0.798, 'p': 0.008, 's': 0.007, 'tot': 0.813},
{'d': 0.798, 'p': 0.008, 's': 0.007, 'tot': 0.813},
{'d': 0.0, 'p':-0.117, 's': 0.005, 'tot':-0.112},
{'d': 0.0, 'p':-0.165, 's': 0.004, 'tot':-0.162},
{'d': 0.0, 'p':-0.117, 's': 0.005, 'tot':-0.112},
{'d': 0.0, 'p':-0.165, 's': 0.004, 'tot':-0.162})
expected_chg = ({'p': 0.154, 's': 0.078, 'd': 0.0, 'tot': 0.232},
{'p': 0.707, 's': 0.463, 'd': 8.316, 'tot': 9.486},
{'p': 0.707, 's': 0.463, 'd': 8.316, 'tot': 9.486},
{'p': 3.388, 's': 1.576, 'd': 0.0, 'tot': 4.964},
{'p': 3.365, 's': 1.582, 'd': 0.0, 'tot': 4.947},
{'p': 3.388, 's': 1.576, 'd': 0.0, 'tot': 4.964},
{'p': 3.365, 's': 1.582, 'd': 0.0, 'tot': 4.947})
self.assertAlmostEqual(outcar.magnetization, expected_mag, 5,
"Wrong magnetization read from Outcar")
self.assertAlmostEqual(outcar.charge, expected_chg, 5,
"Wrong charge read from Outcar")
self.assertFalse(outcar.is_stopped)
self.assertEqual(outcar.run_stats, {'System time (sec)': 0.938,
'Total CPU time used (sec)': 545.142,
'Elapsed time (sec)': 546.709,
'Maximum memory used (kb)': 0.0,
'Average memory used (kb)': 0.0,
'User time (sec)': 544.204,
'cores': '8'})
self.assertAlmostEqual(outcar.efermi, 2.0112)
self.assertAlmostEqual(outcar.nelect, 44.9999991)
self.assertAlmostEqual(outcar.total_mag, 0.9999998)
self.assertIsNotNone(outcar.as_dict())
filepath = os.path.join(test_dir, 'OUTCAR.stopped')
outcar = Outcar(filepath)
self.assertTrue(outcar.is_stopped)
for f in ['OUTCAR.lepsilon', 'OUTCAR.lepsilon.gz']:
filepath = os.path.join(test_dir, f)
outcar = Outcar(filepath)
outcar.read_lepsilon()
outcar.read_lepsilon_ionic()
self.assertAlmostEqual(outcar.dielectric_tensor[0][0], 3.716432)
self.assertAlmostEqual(outcar.dielectric_tensor[0][1], -0.20464)
self.assertAlmostEqual(outcar.dielectric_tensor[1][2], -0.20464)
self.assertAlmostEqual(outcar.dielectric_ionic_tensor[0][0], 0.001419)
self.assertAlmostEqual(outcar.dielectric_ionic_tensor[0][2], 0.001419)
self.assertAlmostEqual(outcar.dielectric_ionic_tensor[2][2], 0.001419)
self.assertAlmostEqual(outcar.piezo_tensor[0][0], 0.52799)
self.assertAlmostEqual(outcar.piezo_tensor[1][3], 0.35998)
self.assertAlmostEqual(outcar.piezo_tensor[2][5], 0.35997)
self.assertAlmostEqual(outcar.piezo_ionic_tensor[0][0], 0.05868)
self.assertAlmostEqual(outcar.piezo_ionic_tensor[1][3], 0.06241)
self.assertAlmostEqual(outcar.piezo_ionic_tensor[2][5], 0.06242)
self.assertAlmostEqual(outcar.born[0][1][2], -0.385)
self.assertAlmostEqual(outcar.born[1][2][0], 0.36465)
import pymatgen
from pymatgen.io.vaspio.vasp_output import Outcar
import os
import pickle
import numpy as np
outcar = Outcar('OUTCAR')
magarray = []
magx = outcar.magnetizationx
magy = outcar.magnetizationy
magz = outcar.magnetizationz
magxlist = [x["tot"] for x in magx]
magylist = [y["tot"] for y in magy]
magzlist = [z["tot"] for z in magz]
strlist = []
for i in range(0, len(magxlist)):
# change this if loop to select only the magnetic species of interest
# this example was used for a 48 atom unit cell where atoms 41-48 were magnetic
if i >= 0:
strlist.append(
str(magxlist[i]) + " " + str(magylist[i]) + " " + str(magzlist[i]))
magstr = " ".join(strlist)
print magstr
def test_init(self):
for f in ['OUTCAR', 'OUTCAR.gz']:
filepath = os.path.join(test_dir, f)
outcar = Outcar(filepath)
expected_mag = ({
'd': 0.0,
'p': 0.003,
's': 0.002,
'tot': 0.005
}, {
'd': 0.798,
'p': 0.008,
's': 0.007,
'tot': 0.813
}, {
'd': 0.798,
'p': 0.008,
's': 0.007,
'tot': 0.813
}, {
'd': 0.0,
'p': -0.117,
's': 0.005,
'tot': -0.112
}, {
'd': 0.0,
'p': -0.165,
's': 0.004,
'tot': -0.162
}, {
'd': 0.0,
'p': -0.117,
's': 0.005,
'tot': -0.112
}, {
'd': 0.0,
'p': -0.165,
's': 0.004,
'tot': -0.162
})
expected_chg = ({
'p': 0.154,
's': 0.078,
'd': 0.0,
'tot': 0.232
}, {
'p': 0.707,
's': 0.463,
'd': 8.316,
'tot': 9.486
}, {
'p': 0.707,
's': 0.463,
'd': 8.316,
'tot': 9.486
}, {
'p': 3.388,
's': 1.576,
'd': 0.0,
'tot': 4.964
}, {
'p': 3.365,
's': 1.582,
'd': 0.0,
'tot': 4.947
}, {
'p': 3.388,
's': 1.576,
'd': 0.0,
'tot': 4.964
}, {
'p': 3.365,
's': 1.582,
'd': 0.0,
'tot': 4.947
})
self.assertAlmostEqual(outcar.magnetization, expected_mag, 5,
"Wrong magnetization read from Outcar")
self.assertAlmostEqual(outcar.charge, expected_chg, 5,
"Wrong charge read from Outcar")
self.assertFalse(outcar.is_stopped)
self.assertEqual(
outcar.run_stats, {
'System time (sec)': 0.938,
'Total CPU time used (sec)': 545.142,
'Elapsed time (sec)': 546.709,
'Maximum memory used (kb)': 0.0,
'Average memory used (kb)': 0.0,
'User time (sec)': 544.204,
'cores': '8'
})
self.assertAlmostEqual(outcar.efermi, 2.0112)
self.assertAlmostEqual(outcar.nelect, 44.9999991)
self.assertAlmostEqual(outcar.total_mag, 0.9999998)
self.assertIsNotNone(outcar.as_dict())
filepath = os.path.join(test_dir, 'OUTCAR.stopped')
outcar = Outcar(filepath)
self.assertTrue(outcar.is_stopped)
for f in ['OUTCAR.lepsilon', 'OUTCAR.lepsilon.gz']:
filepath = os.path.join(test_dir, f)
outcar = Outcar(filepath)
outcar.read_lepsilon()
outcar.read_lepsilon_ionic()
self.assertAlmostEqual(outcar.dielectric_tensor[0][0], 3.716432)
self.assertAlmostEqual(outcar.dielectric_tensor[0][1], -0.20464)
self.assertAlmostEqual(outcar.dielectric_tensor[1][2], -0.20464)
self.assertAlmostEqual(outcar.dielectric_ionic_tensor[0][0],
0.001419)
self.assertAlmostEqual(outcar.dielectric_ionic_tensor[0][2],
0.001419)
self.assertAlmostEqual(outcar.dielectric_ionic_tensor[2][2],
0.001419)
self.assertAlmostEqual(outcar.piezo_tensor[0][0], 0.52799)
self.assertAlmostEqual(outcar.piezo_tensor[1][3], 0.35998)
self.assertAlmostEqual(outcar.piezo_tensor[2][5], 0.35997)
self.assertAlmostEqual(outcar.piezo_ionic_tensor[0][0], 0.05868)
self.assertAlmostEqual(outcar.piezo_ionic_tensor[1][3], 0.06241)
self.assertAlmostEqual(outcar.piezo_ionic_tensor[2][5], 0.06242)
self.assertAlmostEqual(outcar.born[0][1][2], -0.385)
self.assertAlmostEqual(outcar.born[1][2][0], 0.36465)
def from_previous_vasp_run(previous_vasp_dir,
output_dir='.',
user_incar_settings=None,
make_dir_if_not_present=True):
"""
Generate a set of Vasp input files for static calculations from a
directory of previous Vasp run.
Args:
previous_vasp_dir:
The directory contains the outputs(vasprun.xml and OUTCAR) of
previous vasp run.
output_dir:
The directory to write the VASP input files for the static
calculations. Default to write in the current directory.
make_dir_if_not_present:
Set to True if you want the directory (and the whole path) to
be created if it is not present.
"""
try:
vasp_run = Vasprun(os.path.join(previous_vasp_dir, "vasprun.xml"),
parse_dos=False,
parse_eigen=None)
outcar = Outcar(os.path.join(previous_vasp_dir, "OUTCAR"))
previous_incar = vasp_run.incar
previous_kpoints = vasp_run.kpoints
previous_final_structure = vasp_run.final_structure
except:
traceback.format_exc()
raise RuntimeError("Can't get valid results from previous run")
structure = MPStaticVaspInputSet.get_structure(vasp_run, outcar)
mpsvip = MPStaticVaspInputSet()
mpsvip.write_input(structure, output_dir, make_dir_if_not_present)
#new_incar = Incar.from_file(os.path.join(output_dir, "INCAR"))
new_incar = mpsvip.get_incar(structure)
# Use previous run INCAR and override necessary parameters
previous_incar.update({
"IBRION": -1,
"ISMEAR": -5,
"LAECHG": True,
"LCHARG": True,
"LORBIT": 11,
"LVHAR": True,
"LWAVE": False,
"NSW": 0,
"ICHARG": 0
})
for incar_key in ["MAGMOM", "NUPDOWN"]:
if new_incar.get(incar_key, None):
previous_incar.update({incar_key: new_incar[incar_key]})
else:
previous_incar.pop(incar_key, None)
# use new LDAUU when possible b/c the Poscar might have changed
# representation
if previous_incar.get('LDAU'):
u = previous_incar.get('LDAUU', [])
j = previous_incar.get('LDAUJ', [])
if sum([u[x] - j[x] for x, y in enumerate(u)]) > 0:
for tag in ('LDAUU', 'LDAUL', 'LDAUJ'):
previous_incar.update({tag: new_incar[tag]})
# Compare ediff between previous and staticinputset values,
# choose the tighter ediff
previous_incar.update(
{"EDIFF": min(previous_incar.get("EDIFF", 1), new_incar["EDIFF"])})
# add user settings
if user_incar_settings:
previous_incar.update(user_incar_settings)
previous_incar.write_file(os.path.join(output_dir, "INCAR"))
# Prefer to use k-point scheme from previous run
previous_kpoints_density = np.prod(previous_kpoints.kpts[0]) / \
previous_final_structure.lattice.reciprocal_lattice.volume
new_kpoints_density = max(previous_kpoints_density, 90)
new_kpoints = mpsvip.get_kpoints(structure,
kpoints_density=new_kpoints_density)
if previous_kpoints.style[0] != new_kpoints.style[0]:
if previous_kpoints.style[0] == "M" and \
SymmetryFinder(structure, 0.01).get_lattice_type() != \
"hexagonal":
k_div = (kp + 1 if kp % 2 == 1 else kp
for kp in new_kpoints.kpts[0])
Kpoints.monkhorst_automatic(k_div). \
write_file(os.path.join(output_dir, "KPOINTS"))
else:
Kpoints.gamma_automatic(new_kpoints.kpts[0]). \
write_file(os.path.join(output_dir, "KPOINTS"))
else:
new_kpoints.write_file(os.path.join(output_dir, "KPOINTS"))
def assimilate(self, path, launches_coll=None):
"""
Parses vasp runs. Then insert the result into the db. and return the
task_id or doc of the insertion.
Returns:
If in simulate_mode, the entire doc is returned for debugging
purposes. Else, only the task_id of the inserted doc is returned.
"""
d = self.get_task_doc(path)
if self.additional_fields:
d.update(self.additional_fields) # always add additional fields, even for failed jobs
try:
d["dir_name_full"] = d["dir_name"].split(":")[1]
d["dir_name"] = get_block_part(d["dir_name_full"])
d["stored_data"] = {}
except:
print 'COULD NOT GET DIR NAME'
pprint.pprint(d)
print traceback.format_exc()
raise ValueError('IMPROPER PARSING OF {}'.format(path))
if not self.simulate:
# Perform actual insertion into db. Because db connections cannot
# be pickled, every insertion needs to create a new connection
# to the db.
conn = MongoClient(self.host, self.port)
db = conn[self.database]
if self.user:
db.authenticate(self.user, self.password)
coll = db[self.collection]
# Insert dos data into gridfs and then remove it from the dict.
# DOS data tends to be above the 4Mb limit for mongo docs. A ref
# to the dos file is in the dos_fs_id.
result = coll.find_one({"dir_name": d["dir_name"]})
if result is None or self.update_duplicates:
if self.parse_dos and "calculations" in d:
for calc in d["calculations"]:
if "dos" in calc:
dos = json.dumps(calc["dos"], cls=MontyEncoder)
fs = gridfs.GridFS(db, "dos_fs")
dosid = fs.put(dos)
calc["dos_fs_id"] = dosid
del calc["dos"]
d["last_updated"] = datetime.datetime.today()
if result is None:
if ("task_id" not in d) or (not d["task_id"]):
d["task_id"] = "mp-{}".format(
db.counter.find_and_modify(
query={"_id": "taskid"},
update={"$inc": {"c": 1}})["c"])
logger.info("Inserting {} with taskid = {}"
.format(d["dir_name"], d["task_id"]))
elif self.update_duplicates:
d["task_id"] = result["task_id"]
logger.info("Updating {} with taskid = {}"
.format(d["dir_name"], d["task_id"]))
#Fireworks processing
self.process_fw(path, d)
try:
#Add oxide_type
struct=Structure.from_dict(d["output"]["crystal"])
d["oxide_type"]=oxide_type(struct)
except:
logger.error("can't get oxide_type for {}".format(d["task_id"]))
d["oxide_type"] = None
#Override incorrect outcar subdocs for two step relaxations
if "optimize structure" in d['task_type'] and \
os.path.exists(os.path.join(path, "relax2")):
try:
run_stats = {}
for i in [1,2]:
o_path = os.path.join(path,"relax"+str(i),"OUTCAR")
o_path = o_path if os.path.exists(o_path) else o_path+".gz"
outcar = Outcar(o_path)
d["calculations"][i-1]["output"]["outcar"] = outcar.as_dict()
run_stats["relax"+str(i)] = outcar.run_stats
except:
logger.error("Bad OUTCAR for {}.".format(path))
try:
overall_run_stats = {}
for key in ["Total CPU time used (sec)", "User time (sec)",
"System time (sec)", "Elapsed time (sec)"]:
overall_run_stats[key] = sum([v[key]
for v in run_stats.values()])
run_stats["overall"] = overall_run_stats
except:
logger.error("Bad run stats for {}.".format(path))
d["run_stats"] = run_stats
# add is_compatible
mpc = MaterialsProjectCompatibility("Advanced")
try:
func = d["pseudo_potential"]["functional"]
labels = d["pseudo_potential"]["labels"]
symbols = ["{} {}".format(func, label) for label in labels]
parameters = {"run_type": d["run_type"],
"is_hubbard": d["is_hubbard"],
"hubbards": d["hubbards"],
"potcar_symbols": symbols}
entry = ComputedEntry(Composition(d["unit_cell_formula"]),
0.0, 0.0, parameters=parameters,
entry_id=d["task_id"])
d['is_compatible'] = bool(mpc.process_entry(entry))
except:
traceback.print_exc()
print 'ERROR in getting compatibility'
d['is_compatible'] = None
#task_type dependent processing
if 'static' in d['task_type']:
launch_doc = launches_coll.find_one({"fw_id": d['fw_id'], "launch_dir": {"$regex": d["dir_name"]}}, {"action.stored_data": 1})
for i in ["conventional_standard_structure", "symmetry_operations",
"symmetry_dataset", "refined_structure"]:
try:
d['stored_data'][i] = launch_doc['action']['stored_data'][i]
except:
pass
#parse band structure if necessary
if ('band structure' in d['task_type'] or "Uniform" in d['task_type'])\
and d['state'] == 'successful':
launch_doc = launches_coll.find_one({"fw_id": d['fw_id'], "launch_dir": {"$regex": d["dir_name"]}},
{"action.stored_data": 1})
vasp_run = Vasprun(zpath(os.path.join(path, "vasprun.xml")), parse_projected_eigen=False)
if 'band structure' in d['task_type']:
def string_to_numlist(stringlist):
g=re.search('([0-9\-\.eE]+)\s+([0-9\-\.eE]+)\s+([0-9\-\.eE]+)', stringlist)
return [float(g.group(i)) for i in range(1,4)]
for i in ["kpath_name", "kpath"]:
d['stored_data'][i] = launch_doc['action']['stored_data'][i]
kpoints_doc = d['stored_data']['kpath']['kpoints']
for i in kpoints_doc:
kpoints_doc[i]=string_to_numlist(kpoints_doc[i])
bs=vasp_run.get_band_structure(efermi=d['calculations'][0]['output']['outcar']['efermi'],
line_mode=True)
else:
bs=vasp_run.get_band_structure(efermi=d['calculations'][0]['output']['outcar']['efermi'],
line_mode=False)
bs_json = json.dumps(bs.as_dict(), cls=MontyEncoder)
fs = gridfs.GridFS(db, "band_structure_fs")
bs_id = fs.put(bs_json)
d['calculations'][0]["band_structure_fs_id"] = bs_id
# also override band gap in task doc
gap = bs.get_band_gap()
vbm = bs.get_vbm()
cbm = bs.get_cbm()
update_doc = {'bandgap': gap['energy'], 'vbm': vbm['energy'], 'cbm': cbm['energy'], 'is_gap_direct': gap['direct']}
d['analysis'].update(update_doc)
d['calculations'][0]['output'].update(update_doc)
coll.update({"dir_name": d["dir_name"]}, d, upsert=True)
return d["task_id"], d
else:
logger.info("Skipping duplicate {}".format(d["dir_name"]))
return result["task_id"], result
else:
d["task_id"] = 0
logger.info("Simulated insert into database for {} with task_id {}"
.format(d["dir_name"], d["task_id"]))
return 0, d
def from_previous_vasp_run(previous_vasp_dir, output_dir='.',
user_incar_settings=None,
copy_chgcar=True, make_dir_if_not_present=True,
kpoints_density=1000):
"""
Generate a set of Vasp input files for NonSCF calculations from a
directory of previous static Vasp run.
Args:
previous_vasp_dir (str): The directory contains the outputs(
vasprun.xml and OUTCAR) of previous vasp run.
output_dir (str): The directory to write the VASP input files
for the NonSCF calculations. Default to write in the current
directory.
user_incar_settings (dict): A dict specify customized settings
for INCAR.
copy_chgcar (bool): Default to copy CHGCAR from SC run
make_dir_if_not_present (bool): Set to True if you want the
directory (and the whole path) to be created if it is not
present.
kpoints_density (int): kpoints density for the reciprocal cell
of structure. Might need to increase the default value when
calculating metallic materials.
kpoints_line_density (int): kpoints density to use in line-mode.
Might need to increase the default value when calculating
metallic materials.
"""
user_incar_settings = user_incar_settings or {}
try:
vasp_run = Vasprun(os.path.join(previous_vasp_dir, "vasprun.xml"),
parse_dos=False, parse_eigen=None)
outcar = Outcar(os.path.join(previous_vasp_dir, "OUTCAR"))
previous_incar = vasp_run.incar
except:
traceback.print_exc()
raise RuntimeError("Can't get valid results from previous run. prev dir: {}".format(previous_vasp_dir))
#Get a Magmom-decorated structure
structure = TetrahedronDosSet.get_structure(vasp_run, outcar,
initial_structure=True)
nscf_incar_settings = TetrahedronDosSet.get_incar_settings(vasp_run,
outcar)
mpnscfvip = TetrahedronDosSet(nscf_incar_settings, kpoints_density=kpoints_density)
mpnscfvip.write_input(structure, output_dir, make_dir_if_not_present)
if copy_chgcar:
try:
shutil.copyfile(os.path.join(previous_vasp_dir, "CHGCAR"),
os.path.join(output_dir, "CHGCAR"))
except Exception as e:
traceback.print_exc()
raise RuntimeError("Can't copy CHGCAR from SC run" + '\n'
+ str(e))
#Overwrite necessary INCAR parameters from previous runs
# this is already done in the __init__; is it necessary here?
previous_incar.update(nscf_incar_settings)
previous_incar.update(user_incar_settings)
# MAKE EXTRA DUPER SURE THESE PARAMETERS ARE NOT OVERWRITTEN
previous_incar.update({"IBRION": -1, "ISMEAR": -5,
"LCHARG": False, "LORBIT": 11, "LWAVE": False,
"NSW": 0, "ISYM": 0, "ICHARG": 11})
previous_incar.pop("MAGMOM", None)
previous_incar.pop('SIGMA',None)
previous_incar.write_file(os.path.join(output_dir, "INCAR"))
# Perform checking on INCAR parameters
if any([previous_incar.get("NSW", 0) != 0,
previous_incar["IBRION"] != -1,
previous_incar["ICHARG"] != 11,
any([sum(previous_incar["LDAUU"]) <= 0,
previous_incar["LMAXMIX"] < 4])
if previous_incar.get("LDAU") else False]):
raise ValueError("Incompatible INCAR parameters!")
def assimilate(self, path, launches_coll=None):
"""
Parses vasp runs. Then insert the result into the db. and return the
task_id or doc of the insertion.
Returns:
If in simulate_mode, the entire doc is returned for debugging
purposes. Else, only the task_id of the inserted doc is returned.
"""
d = self.get_task_doc(path, self.parse_dos,
self.additional_fields)
try:
d["dir_name_full"] = d["dir_name"].split(":")[1]
d["dir_name"] = get_block_part(d["dir_name_full"])
d["stored_data"] = {}
except:
print 'COULD NOT GET DIR NAME'
pprint.pprint(d)
print traceback.format_exc()
raise ValueError('IMPROPER PARSING OF {}'.format(path))
if not self.simulate:
# Perform actual insertion into db. Because db connections cannot
# be pickled, every insertion needs to create a new connection
# to the db.
conn = MongoClient(self.host, self.port)
db = conn[self.database]
if self.user:
db.authenticate(self.user, self.password)
coll = db[self.collection]
# Insert dos data into gridfs and then remove it from the dict.
# DOS data tends to be above the 4Mb limit for mongo docs. A ref
# to the dos file is in the dos_fs_id.
result = coll.find_one({"dir_name": d["dir_name"]})
if result is None or self.update_duplicates:
if self.parse_dos and "calculations" in d:
for calc in d["calculations"]:
if "dos" in calc:
dos = json.dumps(calc["dos"])
fs = gridfs.GridFS(db, "dos_fs")
dosid = fs.put(dos)
calc["dos_fs_id"] = dosid
del calc["dos"]
d["last_updated"] = datetime.datetime.today()
if result is None:
if ("task_id" not in d) or (not d["task_id"]):
d["task_id"] = "mp-{}".format(
db.counter.find_and_modify(
query={"_id": "taskid"},
update={"$inc": {"c": 1}})["c"])
logger.info("Inserting {} with taskid = {}"
.format(d["dir_name"], d["task_id"]))
elif self.update_duplicates:
d["task_id"] = result["task_id"]
logger.info("Updating {} with taskid = {}"
.format(d["dir_name"], d["task_id"]))
#Fireworks processing
self.process_fw(path, d)
#Override incorrect outcar subdocs for two step relaxations
if "optimize structure" in d['task_type'] and \
os.path.exists(os.path.join(path, "relax2")):
try:
run_stats = {}
for i in [1,2]:
outcar = Outcar(os.path.join(path,"relax"+str(i),"OUTCAR"))
d["calculations"][i-1]["output"]["outcar"] = outcar.to_dict
run_stats["relax"+str(i)] = outcar.run_stats
except:
logger.error("Bad OUTCAR for {}.".format(path))
try:
overall_run_stats = {}
for key in ["Total CPU time used (sec)", "User time (sec)",
"System time (sec)", "Elapsed time (sec)"]:
overall_run_stats[key] = sum([v[key]
for v in run_stats.values()])
run_stats["overall"] = overall_run_stats
except:
logger.error("Bad run stats for {}.".format(path))
d["run_stats"] = run_stats
#task_type dependent processing
if 'static' in d['task_type']:
launch_doc = launches_coll.find_one({"fw_id": d['fw_id'], "launch_dir": {"$regex": d["dir_name"]}}, {"action.stored_data": 1})
for i in ["conventional_standard_structure", "symmetry_operations",
"symmetry_dataset", "refined_structure"]:
try:
d['stored_data'][i] = launch_doc['action']['stored_data'][i]
except:
pass
#parse band structure if necessary
if ('band structure' in d['task_type'] or "Uniform" in d['task_type'])\
and d['state'] == 'successful':
launch_doc = launches_coll.find_one({"fw_id": d['fw_id'], "launch_dir": {"$regex": d["dir_name"]}},
{"action.stored_data": 1})
vasp_run = Vasprun(os.path.join(path, "vasprun.xml"), parse_projected_eigen=False)
if 'band structure' in d['task_type']:
def string_to_numlist(stringlist):
g=re.search('([0-9\-\.eE]+)\s+([0-9\-\.eE]+)\s+([0-9\-\.eE]+)', stringlist)
return [float(g.group(i)) for i in range(1,4)]
for i in ["kpath_name", "kpath"]:
d['stored_data'][i] = launch_doc['action']['stored_data'][i]
kpoints_doc = d['stored_data']['kpath']['kpoints']
for i in kpoints_doc:
kpoints_doc[i]=string_to_numlist(kpoints_doc[i])
bs=vasp_run.get_band_structure(efermi=d['calculations'][0]['output']['outcar']['efermi'],
line_mode=True)
else:
bs=vasp_run.get_band_structure(efermi=d['calculations'][0]['output']['outcar']['efermi'],
line_mode=False)
bs_json = json.dumps(bs.to_dict)
fs = gridfs.GridFS(db, "band_structure_fs")
bs_id = fs.put(bs_json)
d['calculations'][0]["band_structure_fs_id"] = bs_id
coll.update({"dir_name": d["dir_name"]}, d, upsert=True)
return d["task_id"], d
else:
logger.info("Skipping duplicate {}".format(d["dir_name"]))
return result["task_id"], result
else:
d["task_id"] = 0
logger.info("Simulated insert into database for {} with task_id {}"
.format(d["dir_name"], d["task_id"]))
return 0, d
