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# coding: utf-8 

# Copyright (c) Pymatgen Development Team. 

# Distributed under the terms of the MIT License. 

 

from __future__ import division, unicode_literals 

 

""" 

This module implements input and output processing from Nwchem. 

 

2015/09/21 - Xin Chen (chenxin13@mails.tsinghua.edu.cn): 

 

NwOutput will read new kinds of data: 

1. normal hessian matrix. ["hessian"] 

2. projected hessian matrix. ["projected_hessian"] 

3. normal frequencies. ["normal_frequencies"] 

 

For backward compatibility, the key for accessing the projected frequencies 

is still 'frequencies'. 

 

2015/10/12 - Xin Chen 

NwOutput will read new kinds of data: 

1. forces. ["forces"] 

 

""" 

 

__author__ = "Shyue Ping Ong" 

__copyright__ = "Copyright 2012, The Materials Project" 

__version__ = "0.1" 

__maintainer__ = "Shyue Ping Ong" 

__email__ = "shyuep@gmail.com" 

__date__ = "6/5/13" 

 

 

import re 

from string import Template 

 

from six import string_types 

from six.moves import zip 

 

from monty.io import zopen 

 

from pymatgen.core import Molecule,Structure 

from monty.json import MSONable 

from pymatgen.core.units import Energy 

from pymatgen.core.units import FloatWithUnit 

 

 

class NwTask(MSONable): 

""" 

Base task for Nwchem. 

""" 

 

theories = {"g3gn": "some description", 

"scf": "Hartree-Fock", 

"dft": "DFT", 

"esp": "ESP", 

"sodft": "Spin-Orbit DFT", 

"mp2": "MP2 using a semi-direct algorithm", 

"direct_mp2": "MP2 using a full-direct algorithm", 

"rimp2": "MP2 using the RI approximation", 

"ccsd": "Coupled-cluster single and double excitations", 

"ccsd(t)": "Coupled-cluster linearized triples approximation", 

"ccsd+t(ccsd)": "Fourth order triples contribution", 

"mcscf": "Multiconfiguration SCF", 

"selci": "Selected CI with perturbation correction", 

"md": "Classical molecular dynamics simulation", 

"pspw": "Pseudopotential plane-wave DFT for molecules and " 

"insulating solids using NWPW", 

"band": "Pseudopotential plane-wave DFT for solids using NWPW", 

"tce": "Tensor Contraction Engine"} 

 

operations = {"energy": "Evaluate the single point energy.", 

"gradient": "Evaluate the derivative of the energy with " 

"respect to nuclear coordinates.", 

"optimize": "Minimize the energy by varying the molecular " 

"structure.", 

"saddle": "Conduct a search for a transition state (or " 

"saddle point).", 

"hessian": "Compute second derivatives.", 

"frequencies": "Compute second derivatives and print out an " 

"analysis of molecular vibrations.", 

"freq": "Same as frequencies.", 

"vscf": "Compute anharmonic contributions to the " 

"vibrational modes.", 

"property": "Calculate the properties for the wave " 

"function.", 

"dynamics": "Perform classical molecular dynamics.", 

"thermodynamics": "Perform multi-configuration " 

"thermodynamic integration using " 

"classical MD.", 

"": "dummy"} 

 

def __init__(self, charge, spin_multiplicity, basis_set, basis_set_option="cartesian", 

title=None, theory="dft", operation="optimize", 

theory_directives=None, alternate_directives=None): 

""" 

Very flexible arguments to support many types of potential setups. 

Users should use more friendly static methods unless they need the 

flexibility. 

 

Args: 

charge: Charge of the molecule. If None, charge on molecule is 

used. Defaults to None. This allows the input file to be set a 

charge independently from the molecule itself. 

spin_multiplicity: Spin multiplicity of molecule. Defaults to None, 

which means that the spin multiplicity is set to 1 if the 

molecule has no unpaired electrons and to 2 if there are 

unpaired electrons. 

basis_set: The basis set used for the task as a dict. E.g., 

{"C": "6-311++G**", "H": "6-31++G**"}. 

basis_set_option: cartesian (default) | spherical, 

title: Title for the task. Defaults to None, which means a title 

based on the theory and operation of the task is 

autogenerated. 

theory: The theory used for the task. Defaults to "dft". 

operation: The operation for the task. Defaults to "optimize". 

theory_directives: A dict of theory directives. For example, 

if you are running dft calculations, you may specify the 

exchange correlation functional using {"xc": "b3lyp"}. 

alternate_directives: A dict of alternate directives. For 

example, to perform cosmo calculations and dielectric 

constant of 78, you'd supply {'cosmo': {"dielectric": 78}}. 

""" 

#Basic checks. 

if theory.lower() not in NwTask.theories.keys(): 

raise NwInputError("Invalid theory {}".format(theory)) 

 

if operation.lower() not in NwTask.operations.keys(): 

raise NwInputError("Invalid operation {}".format(operation)) 

self.charge = charge 

self.spin_multiplicity = spin_multiplicity 

self.title = title if title is not None else "{} {}".format(theory, 

operation) 

self.theory = theory 

self.basis_set = basis_set 

self.basis_set_option = basis_set_option 

 

self.operation = operation 

self.theory_directives = theory_directives \ 

if theory_directives is not None else {} 

self.alternate_directives = alternate_directives \ 

if alternate_directives is not None else {} 

 

def __str__(self): 

bset_spec = [] 

for el, bset in sorted(self.basis_set.items(), key=lambda x: x[0]): 

bset_spec.append(" {} library \"{}\"".format(el, bset)) 

theory_spec = [] 

if self.theory_directives: 

theory_spec.append("{}".format(self.theory)) 

for k in sorted(self.theory_directives.keys()): 

theory_spec.append(" {} {}".format(k, self.theory_directives[ 

k])) 

theory_spec.append("end") 

for k in sorted(self.alternate_directives.keys()): 

theory_spec.append(k) 

for k2 in sorted(self.alternate_directives[k].keys()): 

theory_spec.append(" {} {}".format( 

k2, self.alternate_directives[k][k2])) 

theory_spec.append("end") 

t = Template("""title "$title" 

charge $charge 

basis $basis_set_option 

$bset_spec 

end 

$theory_spec 

task $theory $operation""") 

 

return t.substitute( 

title=self.title, charge=self.charge, basis_set_option=self.basis_set_option, 

bset_spec="\n".join(bset_spec), 

theory_spec="\n".join(theory_spec), 

theory=self.theory, operation=self.operation) 

 

def as_dict(self): 

return {"@module": self.__class__.__module__, 

"@class": self.__class__.__name__, 

"charge": self.charge, 

"spin_multiplicity": self.spin_multiplicity, 

"title": self.title, "theory": self.theory, 

"operation": self.operation, "basis_set": self.basis_set, 

"basis_set_option": self.basis_set_option, 

"theory_directives": self.theory_directives, 

"alternate_directives": self.alternate_directives} 

 

@classmethod 

def from_dict(cls, d): 

return NwTask(charge=d["charge"], 

spin_multiplicity=d["spin_multiplicity"], 

title=d["title"], theory=d["theory"], 

operation=d["operation"], basis_set=d["basis_set"], 

basis_set_option=d['basis_set_option'], 

theory_directives=d["theory_directives"], 

alternate_directives=d["alternate_directives"]) 

 

@classmethod 

def from_molecule(cls, mol, theory, charge=None, spin_multiplicity=None, 

basis_set="6-31g", basis_set_option="cartesian", title=None, 

operation="optimize", theory_directives=None, 

alternate_directives=None): 

""" 

Very flexible arguments to support many types of potential setups. 

Users should use more friendly static methods unless they need the 

flexibility. 

 

Args: 

mol: Input molecule 

charge: Charge of the molecule. If None, charge on molecule is 

used. Defaults to None. This allows the input file to be set a 

charge independently from the molecule itself. 

spin_multiplicity: Spin multiplicity of molecule. Defaults to None, 

which means that the spin multiplicity is set to 1 if the 

molecule has no unpaired electrons and to 2 if there are 

unpaired electrons. 

basis_set: The basis set to be used as string or a dict. E.g., 

{"C": "6-311++G**", "H": "6-31++G**"} or "6-31G". If string, 

same basis set is used for all elements. 

basis_set_option: cartesian (default) | spherical, 

title: Title for the task. Defaults to None, which means a title 

based on the theory and operation of the task is 

autogenerated. 

theory: The theory used for the task. Defaults to "dft". 

operation: The operation for the task. Defaults to "optimize". 

theory_directives: A dict of theory directives. For example, 

if you are running dft calculations, you may specify the 

exchange correlation functional using {"xc": "b3lyp"}. 

alternate_directives: A dict of alternate directives. For 

example, to perform cosmo calculations with DFT, you'd supply 

{'cosmo': "cosmo"}. 

""" 

title = title if title is not None else "{} {} {}".format( 

re.sub("\s", "", mol.formula), theory, operation) 

 

charge = charge if charge is not None else mol.charge 

nelectrons = - charge + mol.charge + mol.nelectrons 

if spin_multiplicity is not None: 

spin_multiplicity = spin_multiplicity 

if (nelectrons + spin_multiplicity) % 2 != 1: 

raise ValueError( 

"Charge of {} and spin multiplicity of {} is" 

" not possible for this molecule".format( 

charge, spin_multiplicity)) 

elif charge == mol.charge: 

spin_multiplicity = mol.spin_multiplicity 

else: 

spin_multiplicity = 1 if nelectrons % 2 == 0 else 2 

 

elements = set(mol.composition.get_el_amt_dict().keys()) 

if isinstance(basis_set, string_types): 

basis_set = {el: basis_set for el in elements} 

 

basis_set_option = basis_set_option 

 

return NwTask(charge, spin_multiplicity, basis_set, basis_set_option=basis_set_option, 

title=title, theory=theory, operation=operation, 

theory_directives=theory_directives, 

alternate_directives=alternate_directives) 

 

@classmethod 

def dft_task(cls, mol, xc="b3lyp", **kwargs): 

""" 

A class method for quickly creating DFT tasks with optional 

cosmo parameter . 

 

Args: 

mol: Input molecule 

xc: Exchange correlation to use. 

dielectric: Using water dielectric 

\*\*kwargs: Any of the other kwargs supported by NwTask. Note the 

theory is always "dft" for a dft task. 

""" 

t = NwTask.from_molecule(mol, theory="dft", **kwargs) 

t.theory_directives.update({"xc": xc, 

"mult": t.spin_multiplicity}) 

return t 

 

@classmethod 

def esp_task(cls, mol, **kwargs): 

""" 

A class method for quickly creating ESP tasks with RESP 

charge fitting. 

 

Args: 

mol: Input molecule 

\*\*kwargs: Any of the other kwargs supported by NwTask. Note the 

theory is always "dft" for a dft task. 

""" 

return NwTask.from_molecule(mol, theory="esp", **kwargs) 

 

 

class NwInput(MSONable): 

""" 

An object representing a Nwchem input file, which is essentially a list 

of tasks on a particular molecule. 

 

Args: 

mol: Input molecule. If molecule is a single string, it is used as a 

direct input to the geometry section of the Gaussian input 

file. 

tasks: List of NwTasks. 

directives: List of root level directives as tuple. E.g., 

[("start", "water"), ("print", "high")] 

geometry_options: Additional list of options to be supplied to the 

geometry. E.g., ["units", "angstroms", "noautoz"]. Defaults to 

("units", "angstroms"). 

symmetry_options: Addition list of option to be supplied to the 

symmetry. E.g. ["c1"] to turn off the symmetry 

memory_options: Memory controlling options. str. 

E.g "total 1000 mb stack 400 mb" 

""" 

 

def __init__(self, mol, tasks, directives=None, 

geometry_options=("units", "angstroms"), 

symmetry_options=None, 

memory_options=None): 

""" 

 

""" 

self._mol = mol 

self.directives = directives if directives is not None else [] 

self.tasks = tasks 

self.geometry_options = geometry_options 

self.symmetry_options = symmetry_options 

self.memory_options = memory_options 

 

@property 

def molecule(self): 

""" 

Returns molecule associated with this GaussianInput. 

""" 

return self._mol 

 

def __str__(self): 

o = [] 

if self.memory_options: 

o.append('memory ' + self.memory_options) 

for d in self.directives: 

o.append("{} {}".format(d[0], d[1])) 

o.append("geometry " 

+ " ".join(self.geometry_options)) 

if self.symmetry_options: 

o.append(" symmetry " + " ".join(self.symmetry_options)) 

for site in self._mol: 

o.append(" {} {} {} {}".format(site.specie.symbol, site.x, site.y, 

site.z)) 

o.append("end\n") 

for t in self.tasks: 

o.append(str(t)) 

o.append("") 

return "\n".join(o) 

 

def write_file(self, filename): 

with zopen(filename, "w") as f: 

f.write(self.__str__()) 

 

def as_dict(self): 

return { 

"mol": self._mol.as_dict(), 

"tasks": [t.as_dict() for t in self.tasks], 

"directives": [list(t) for t in self.directives], 

"geometry_options": list(self.geometry_options), 

"symmetry_options": self.symmetry_options, 

"memory_options": self.memory_options 

} 

 

@classmethod 

def from_dict(cls, d): 

return NwInput(Molecule.from_dict(d["mol"]), 

tasks=[NwTask.from_dict(dt) for dt in d["tasks"]], 

directives=[tuple(li) for li in d["directives"]], 

geometry_options=d["geometry_options"], 

symmetry_options=d["symmetry_options"], 

memory_options=d["memory_options"]) 

 

@classmethod 

def from_string(cls, string_input): 

""" 

Read an NwInput from a string. Currently tested to work with 

files generated from this class itself. 

 

Args: 

string_input: string_input to parse. 

 

Returns: 

NwInput object 

""" 

directives = [] 

tasks = [] 

charge = None 

spin_multiplicity = None 

title = None 

basis_set = None 

basis_set_option = None 

theory_directives = {} 

geom_options = None 

symmetry_options = None 

memory_options = None 

lines = string_input.strip().split("\n") 

while len(lines) > 0: 

l = lines.pop(0).strip() 

if l == "": 

continue 

 

toks = l.split() 

if toks[0].lower() == "geometry": 

geom_options = toks[1:] 

l = lines.pop(0).strip() 

toks = l.split() 

if toks[0].lower() == "symmetry": 

symmetry_options = toks[1:] 

l = lines.pop(0).strip() 

#Parse geometry 

species = [] 

coords = [] 

while l.lower() != "end": 

toks = l.split() 

species.append(toks[0]) 

coords.append([float(i) for i in toks[1:]]) 

l = lines.pop(0).strip() 

mol = Molecule(species, coords) 

elif toks[0].lower() == "charge": 

charge = int(toks[1]) 

elif toks[0].lower() == "title": 

title = l[5:].strip().strip("\"") 

elif toks[0].lower() == "basis": 

#Parse basis sets 

l = lines.pop(0).strip() 

basis_set = {} 

while l.lower() != "end": 

toks = l.split() 

basis_set[toks[0]] = toks[-1].strip("\"") 

l = lines.pop(0).strip() 

elif toks[0].lower() in NwTask.theories: 

#read the basis_set_option 

if len(toks) > 1: 

basis_set_option = toks[1] 

#Parse theory directives. 

theory = toks[0].lower() 

l = lines.pop(0).strip() 

theory_directives[theory] = {} 

while l.lower() != "end": 

toks = l.split() 

theory_directives[theory][toks[0]] = toks[-1] 

if toks[0] == "mult": 

spin_multiplicity = float(toks[1]) 

l = lines.pop(0).strip() 

elif toks[0].lower() == "task": 

tasks.append( 

NwTask(charge=charge, 

spin_multiplicity=spin_multiplicity, 

title=title, theory=toks[1], 

operation=toks[2], basis_set=basis_set, 

basis_set_option=basis_set_option, 

theory_directives=theory_directives.get(toks[1]))) 

elif toks[0].lower() == "memory": 

memory_options = ' '.join(toks[1:]) 

else: 

directives.append(l.strip().split()) 

 

return NwInput(mol, tasks=tasks, directives=directives, 

geometry_options=geom_options, 

symmetry_options=symmetry_options, 

memory_options=memory_options) 

 

@classmethod 

def from_file(cls, filename): 

""" 

Read an NwInput from a file. Currently tested to work with 

files generated from this class itself. 

 

Args: 

filename: Filename to parse. 

 

Returns: 

NwInput object 

""" 

with zopen(filename) as f: 

return cls.from_string(f.read()) 

 

 

class NwInputError(Exception): 

""" 

Error class for NwInput. 

""" 

pass 

 

 

class NwOutput(object): 

""" 

A Nwchem output file parser. Very basic for now - supports only dft and 

only parses energies and geometries. Please note that Nwchem typically 

outputs energies in either au or kJ/mol. All energies are converted to 

eV in the parser. 

 

Args: 

filename: Filename to read. 

""" 

 

def __init__(self, filename): 

self.filename = filename 

 

with zopen(filename) as f: 

data = f.read() 

 

chunks = re.split("NWChem Input Module", data) 

if re.search("CITATION", chunks[-1]): 

chunks.pop() 

preamble = chunks.pop(0) 

self.job_info = self._parse_preamble(preamble) 

self.data = [self._parse_job(c) for c in chunks] 

 

def _parse_preamble(self, preamble): 

info = {} 

for l in preamble.split("\n"): 

toks = l.split("=") 

if len(toks) > 1: 

info[toks[0].strip()] = toks[-1].strip() 

return info 

 

def _parse_job(self, output): 

energy_patt = re.compile("Total \w+ energy\s+=\s+([\.\-\d]+)") 

energy_gas_patt = re.compile("gas phase energy\s+=\s+([\.\-\d]+)") 

energy_sol_patt = re.compile("sol phase energy\s+=\s+([\.\-\d]+)") 

coord_patt = re.compile("\d+\s+(\w+)\s+[\.\-\d]+\s+([\.\-\d]+)\s+" 

"([\.\-\d]+)\s+([\.\-\d]+)") 

lat_vector_patt = re.compile("a[123]=<\s+([\.\-\d]+)\s+" 

"([\.\-\d]+)\s+([\.\-\d]+)\s+>") 

corrections_patt = re.compile("([\w\-]+ correction to \w+)\s+=" 

"\s+([\.\-\d]+)") 

preamble_patt = re.compile("(No. of atoms|No. of electrons" 

"|SCF calculation type|Charge|Spin " 

"multiplicity)\s*:\s*(\S+)") 

force_patt = re.compile("\s+(\d+)\s+(\w+)" + 6 * "\s+([0-9\.\-]+)") 

 

time_patt = re.compile("\s+ Task \s+ times \s+ cpu: \s+ ([\.\d]+)s .+ ", re.VERBOSE) 

 

error_defs = { 

"calculations not reaching convergence": "Bad convergence", 

"Calculation failed to converge": "Bad convergence", 

"geom_binvr: #indep variables incorrect": "autoz error", 

"dft optimize failed": "Geometry optimization failed"} 

 

fort2py = lambda x : x.replace("D", "e") 

isfloatstring = lambda s : s.find(".") == -1 

 

parse_hess = False 

parse_proj_hess = False 

hessian = None 

projected_hessian = None 

parse_force = False 

all_forces = [] 

forces = [] 

 

data = {} 

energies = [] 

frequencies = None 

normal_frequencies = None 

corrections = {} 

molecules = [] 

structures = [] 

species = [] 

coords = [] 

lattice = [] 

errors = [] 

basis_set = {} 

bset_header = [] 

parse_geom = False 

parse_freq = False 

parse_bset = False 

parse_projected_freq = False 

job_type = "" 

parse_time = False 

time = 0 

for l in output.split("\n"): 

for e, v in error_defs.items(): 

if l.find(e) != -1: 

errors.append(v) 

if parse_time: 

m = time_patt.search(l) 

if m: 

time = m.group(1) 

parse_time = False 

if parse_geom: 

if l.strip() == "Atomic Mass": 

if lattice: 

structures.append(Structure(lattice, species, coords, 

coords_are_cartesian=True)) 

else: 

molecules.append(Molecule(species, coords)) 

species = [] 

coords = [] 

lattice = [] 

parse_geom = False 

else: 

m = coord_patt.search(l) 

if m: 

species.append(m.group(1).capitalize()) 

coords.append([float(m.group(2)), float(m.group(3)), 

float(m.group(4))]) 

m = lat_vector_patt.search(l) 

if m: 

lattice.append([float(m.group(1)), float(m.group(2)), 

float(m.group(3))]) 

 

if parse_force: 

m = force_patt.search(l) 

if m: 

forces.extend(map(float, m.groups()[5:])) 

elif len(forces) > 0: 

all_forces.append(forces) 

forces = [] 

parse_force = False 

 

elif parse_freq: 

if len(l.strip()) == 0: 

if len(normal_frequencies[-1][1]) == 0: 

continue 

else: 

parse_freq = False 

else: 

vibs = [float(vib) for vib in l.strip().split()[1:]] 

num_vibs = len(vibs) 

for mode, dis in zip(normal_frequencies[-num_vibs:], vibs): 

mode[1].append(dis) 

 

elif parse_projected_freq: 

if len(l.strip()) == 0: 

if len(frequencies[-1][1]) == 0: 

continue 

else: 

parse_projected_freq = False 

else: 

vibs = [float(vib) for vib in l.strip().split()[1:]] 

num_vibs = len(vibs) 

for mode, dis in zip( 

frequencies[-num_vibs:], vibs): 

mode[1].append(dis) 

 

elif parse_bset: 

if l.strip() == "": 

parse_bset = False 

else: 

toks = l.split() 

if toks[0] != "Tag" and not re.match("\-+", toks[0]): 

basis_set[toks[0]] = dict(zip(bset_header[1:], 

toks[1:])) 

elif toks[0] == "Tag": 

bset_header = toks 

bset_header.pop(4) 

bset_header = [h.lower() for h in bset_header] 

 

elif parse_hess: 

if l.strip() == "": 

continue 

if len(hessian) > 0 and l.find("----------") != -1: 

parse_hess = False 

continue 

toks = l.strip().split() 

if len(toks) > 1: 

try: 

row = int(toks[0]) 

except Exception as e: 

continue 

if isfloatstring(toks[1]): 

continue 

vals = [float(fort2py(x)) for x in toks[1:]] 

if len(hessian) < row: 

hessian.append(vals) 

else: 

hessian[row - 1].extend(vals) 

 

elif parse_proj_hess: 

if l.strip() == "": 

continue 

nat3 = len(hessian) 

toks = l.strip().split() 

if len(toks) > 1: 

try: 

row = int(toks[0]) 

except Exception as e: 

continue 

if isfloatstring(toks[1]): 

continue 

vals = [float(fort2py(x)) for x in toks[1:]] 

if len(projected_hessian) < row: 

projected_hessian.append(vals) 

else: 

projected_hessian[row - 1].extend(vals) 

if len(projected_hessian[-1]) == nat3: 

parse_proj_hess = False 

 

else: 

m = energy_patt.search(l) 

if m: 

energies.append(Energy(m.group(1), "Ha").to("eV")) 

parse_time = True 

continue 

 

m = energy_gas_patt.search(l) 

if m: 

cosmo_scf_energy = energies[-1] 

energies[-1] = dict() 

energies[-1].update({"cosmo scf": cosmo_scf_energy}) 

energies[-1].update({"gas phase": 

Energy(m.group(1), "Ha").to("eV")}) 

 

 

m = energy_sol_patt.search(l) 

if m: 

energies[-1].update( 

{"sol phase": Energy(m.group(1), "Ha").to("eV")}) 

 

m = preamble_patt.search(l) 

if m: 

try: 

val = int(m.group(2)) 

except ValueError: 

val = m.group(2) 

k = m.group(1).replace("No. of ", "n").replace(" ", "_") 

data[k.lower()] = val 

elif l.find("Geometry \"geometry\"") != -1: 

parse_geom = True 

elif l.find("Summary of \"ao basis\"") != -1: 

parse_bset = True 

elif l.find("P.Frequency") != -1: 

parse_projected_freq = True 

if frequencies is None: 

frequencies = [] 

toks = l.strip().split()[1:] 

frequencies.extend([(float(freq), []) for freq in toks]) 

 

elif l.find("Frequency") != -1: 

toks = l.strip().split() 

if len(toks) > 1 and toks[0] == "Frequency": 

parse_freq = True 

if normal_frequencies is None: 

normal_frequencies = [] 

normal_frequencies.extend([(float(freq), []) for freq 

in l.strip().split()[1:]]) 

 

elif l.find("MASS-WEIGHTED NUCLEAR HESSIAN") != -1: 

parse_hess = True 

if not hessian: 

hessian = [] 

elif l.find("MASS-WEIGHTED PROJECTED HESSIAN") != -1: 

parse_proj_hess = True 

if not projected_hessian: 

projected_hessian = [] 

 

elif l.find("atom coordinates gradient") != -1: 

parse_force = True 

 

elif job_type == "" and l.strip().startswith("NWChem"): 

job_type = l.strip() 

if job_type == "NWChem DFT Module" and \ 

"COSMO solvation results" in output: 

job_type += " COSMO" 

else: 

m = corrections_patt.search(l) 

if m: 

corrections[m.group(1)] = FloatWithUnit( 

m.group(2), "kJ mol^-1").to("eV atom^-1") 

 

if frequencies: 

for freq, mode in frequencies: 

mode[:] = zip(*[iter(mode)]*3) 

if normal_frequencies: 

for freq, mode in normal_frequencies: 

mode[:] = zip(*[iter(mode)]*3) 

if hessian: 

n = len(hessian) 

for i in range(n): 

for j in range(i + 1, n): 

hessian[i].append(hessian[j][i]) 

if projected_hessian: 

n = len(projected_hessian) 

for i in range(n): 

for j in range(i + 1, n): 

projected_hessian[i].append(projected_hessian[j][i]) 

 

data.update({"job_type": job_type, "energies": energies, 

"corrections": corrections, 

"molecules": molecules, 

"structures": structures, 

"basis_set": basis_set, 

"errors": errors, 

"has_error": len(errors) > 0, 

"frequencies": frequencies, 

"normal_frequencies": normal_frequencies, 

"hessian": hessian, 

"projected_hessian": projected_hessian, 

"forces": all_forces, 

"task_time": time}) 

 

return data