def process_vasprun(self, dir_name, taskname, filename):
"""
Process a vasprun.xml file.
"""
vasprun_file = os.path.join(dir_name, filename)
r = Vasprun(vasprun_file)
d = r.as_dict()
d["dir_name"] = os.path.abspath(dir_name)
d["completed_at"] = \
str(datetime.datetime.fromtimestamp(os.path.getmtime(
vasprun_file)))
d["cif"] = str(CifWriter(r.final_structure))
d["density"] = r.final_structure.density
if self.parse_dos and (self.parse_dos != 'final' \
or taskname == self.runs[-1]):
try:
d["dos"] = r.complete_dos.as_dict()
except Exception:
logger.warn("No valid dos data exist in {}.\n Skipping dos"
.format(dir_name))
if taskname == "relax1" or taskname == "relax2":
d["task"] = {"type": "aflow", "name": taskname}
else:
d["task"] = {"type": taskname, "name": taskname}
return d
def plot_dos(args):
v = Vasprun(args.filename[0])
dos = v.complete_dos
all_dos = OrderedDict()
all_dos["Total"] = dos
structure = v.final_structure
if args.site:
for i in xrange(len(structure)):
site = structure[i]
all_dos["Site " + str(i) + " " + site.specie.symbol] = \
dos.get_site_dos(site)
if args.element:
syms = [tok.strip() for tok in args.element[0].split(",")]
all_dos = {}
for el, dos in dos.get_element_dos().items():
if el.symbol in syms:
all_dos[el] = dos
if args.orbital:
all_dos = dos.get_spd_dos()
plotter = DosPlotter()
plotter.add_dos_dict(all_dos)
if args.file:
plotter.get_plot().savefig(args.file[0])
else:
plotter.show()
def process_vasprun(cls, dir_name, taskname, filename, parse_dos):
"""
Process a vasprun.xml file.
"""
vasprun_file = os.path.join(dir_name, filename)
r = Vasprun(vasprun_file)
d = r.to_dict
d["dir_name"] = os.path.abspath(dir_name)
d["completed_at"] = \
str(datetime.datetime.fromtimestamp(os.path.getmtime(
vasprun_file)))
d["cif"] = str(CifWriter(r.final_structure))
d["density"] = r.final_structure.density
if parse_dos:
try:
d["dos"] = r.complete_dos.to_dict
except Exception:
logger.warn(
"No valid dos data exist in {}.\n Skipping dos".format(
dir_name))
if taskname == "relax1" or taskname == "relax2":
d["task"] = {"type": "aflow", "name": taskname}
else:
d["task"] = {"type": "standard", "name": "standard"}
return d
def read_structure(filename):
"""
Reads a structure based on file extension. For example, anything ending in
a "cif" is assumed to be a Crystallographic Information Format file.
Supported formats include CIF, POSCAR/CONTCAR, CHGCAR, LOCPOT,
vasprun.xml, CSSR and pymatgen's JSON serialized structures.
Args:
filename:
A filename to read from.
Returns:
A Structure object.
"""
fname = os.path.basename(filename)
if fnmatch(fname.lower(), "*.cif*"):
parser = CifParser(filename)
return parser.get_structures(True)[0]
elif fnmatch(fname, "POSCAR*") or fnmatch(fname, "CONTCAR*"):
return Poscar.from_file(filename, False).structure
elif fnmatch(fname, "CHGCAR*") or fnmatch(fname, "LOCPOT*"):
return Chgcar.from_file(filename).structure
elif fnmatch(fname, "vasprun*.xml*"):
return Vasprun(filename).final_structure
elif fnmatch(fname.lower(), "*.cssr*"):
cssr = Cssr.from_file(filename)
return cssr.structure
elif fnmatch(fname, "*.json*") or fnmatch(fname, "*.mson*"):
with zopen(filename) as f:
s = json.load(f, cls=PMGJSONDecoder)
if type(s) != Structure:
raise IOError("File does not contain a valid serialized "
"structure")
return s
raise ValueError("Unrecognized file extension!")
def read_structure(filename, primitive=True, sort=False):
"""
Reads a structure based on file extension. For example, anything ending in
a "cif" is assumed to be a Crystallographic Information Format file.
Supported formats include CIF, POSCAR/CONTCAR, CHGCAR, LOCPOT,
vasprun.xml, CSSR and pymatgen's JSON serialized structures.
Args:
filename (str): A filename to read from.
primitive (bool): Whether to convert to a primitive cell for cifs.
Defaults to True.
sort (bool): Whether to sort sites. Default to False.
Returns:
A Structure object.
"""
fname = os.path.basename(filename)
if fnmatch(fname.lower(), "*.cif*"):
parser = CifParser(filename)
s = parser.get_structures(primitive=primitive)[0]
elif fnmatch(fname, "POSCAR*") or fnmatch(fname, "CONTCAR*"):
s = Poscar.from_file(filename, False).structure
elif fnmatch(fname, "CHGCAR*") or fnmatch(fname, "LOCPOT*"):
s = Chgcar.from_file(filename).structure
elif fnmatch(fname, "vasprun*.xml*"):
s = Vasprun(filename).final_structure
elif fnmatch(fname.lower(), "*.cssr*"):
cssr = Cssr.from_file(filename)
s = cssr.structure
elif fnmatch(fname, "*.json*") or fnmatch(fname, "*.mson*"):
with zopen(filename) as f:
s = json.load(f, cls=MontyDecoder)
if type(s) != Structure:
raise IOError("File does not contain a valid serialized "
"structure")
else:
raise ValueError("Unrecognized file extension!")
if sort:
s = s.get_sorted_structure()
return s
def read_structure(filename, primitive=True, sort=False):
"""
Reads a structure based on file extension. For example, anything ending in
a "cif" is assumed to be a Crystallographic Information Format file.
Supported formats include CIF, POSCAR/CONTCAR, CHGCAR, LOCPOT,
vasprun.xml, CSSR and pymatgen's JSON serialized structures.
Args:
filename (str): A filename to read from.
primitive (bool): Whether to convert to a primitive cell for cifs.
Defaults to False.
sort (bool): Whether to sort sites. Default to False.
Returns:
A Structure object.
"""
fname = os.path.basename(filename)
if fnmatch(fname.lower(), "*.cif*"):
parser = CifParser(filename)
s = parser.get_structures(primitive=primitive)[0]
elif fnmatch(fname, "POSCAR*") or fnmatch(fname, "CONTCAR*"):
s = Poscar.from_file(filename, False).structure
elif fnmatch(fname, "CHGCAR*") or fnmatch(fname, "LOCPOT*"):
s = Chgcar.from_file(filename).structure
elif fnmatch(fname, "vasprun*.xml*"):
s = Vasprun(filename).final_structure
elif fnmatch(fname.lower(), "*.cssr*"):
cssr = Cssr.from_file(filename)
s = cssr.structure
elif fnmatch(fname, "*.json*") or fnmatch(fname, "*.mson*"):
with zopen(filename) as f:
s = json.load(f, cls=PMGJSONDecoder)
if type(s) != Structure:
raise IOError("File does not contain a valid serialized "
"structure")
else:
raise ValueError("Unrecognized file extension!")
if sort:
s = s.get_sorted_structure()
return s
def parse_xml():
v = Vasprun("../test_files/vasprun.xml")
def vasprun_test():
from pymatgen.io.vaspio import Vasprun
v = Vasprun("../test_files/vasprun.xml")
print v.final_energy
def extract_json_data():
"""
Routine tries to read VASP data into pymatgen objects, and
then extracts only the relevant data. This is then written to json,
allowing the voluminous OUTCAR and vasprun.xml files to be discarded.
"""
try:
o = Outcar('OUTCAR')
found_outcar = True
except:
print('OUTCAR file missing or not readable')
found_outcar = False
try:
vr = Vasprun('vasprun.xml')
found_vasprun = True
except:
print('vasprun.xml file missing or not readable')
found_vasprun = False
dictionary_data = {}
if found_outcar:
dictionary_data['OUTCAR'] = o.as_dict()
if found_vasprun:
try:
# try to extract a Computed Entry object, using
# pymatgen technology
drone = VaspToComputedEntryDrone()
queen = BorgQueen(drone, './', 1)
entry = queen.get_data()[0]
dictionary_data['ComputedEntry'] = entry.as_dict()
except:
print('ComputedEntry COULD NOT BE EXTRACTED BY PYMATGEN...')
"""
# Do not extract DOS in run_data.json; this is too memory intensive!
try:
dictionary_data['DOS'] = vr.complete_dos.as_dict()
pymatgen_dos_success = True
except:
print('DOS COULD NOT BE EXTRACTED BY PYMATGEN...')
pymatgen_dos_success = False
"""
relaxation_data = []
for step in vr.ionic_steps:
data_dict = {}
for key in ['forces', 'structure', 'stress']:
if key in step:
data_dict[key] = step[key]
data_dict['electronic'] = step['electronic_steps'][-1]
relaxation_data.append(data_dict)
dictionary_data['relaxation'] = relaxation_data
if found_outcar or found_vasprun:
pmg_dump(dictionary_data, 'run_data.json')
return