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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 Gaussian. 

""" 

 

__author__ = 'Shyue Ping Ong, Germain Salvato-Vallverdu, Xin Chen' 

__copyright__ = 'Copyright 2013, The Materials Virtual Lab' 

__version__ = '0.1' 

__maintainer__ = 'Shyue Ping Ong' 

__email__ = 'ongsp@ucsd.edu' 

__date__ = '8/1/15' 

 

 

import re 

 

import numpy as np 

import warnings 

 

from pymatgen.core.operations import SymmOp 

from pymatgen.core import Element, Molecule, Composition 

from monty.io import zopen 

from pymatgen.util.coord_utils import get_angle 

import pymatgen.core.physical_constants as cst 

 

 

def read_route_line(route): 

""" 

read route line in gaussian input/output and return functional basis_set 

and a dictionary of other route parameters 

 

Args: 

route (str) : the route line 

 

return 

functional (str) : the method (HF, PBE ...) 

basis_set (str) : the basis set 

route (dict) : dictionary of parameters  

""" 

scrf_patt = re.compile("^([sS][cC][rR][fF])\s*=\s*(.+)") 

 

functional = None 

basis_set = None 

route_params = {} 

dieze_tag = None 

if route: 

if "/" in route: 

tok = route.split("/") 

functional = tok[0].split()[-1] 

basis_set = tok[1].split()[0] 

for tok in [functional, basis_set, "/"]: 

route = route.replace(tok, "") 

 

for tok in route.split(): 

if scrf_patt.match(tok): 

m = scrf_patt.match(tok) 

route_params[m.group(1)] = m.group(2) 

elif "#" in tok: 

# does not store # in route to avoid error in input  

dieze_tag = tok 

continue 

else: 

d = tok.split("=") 

v = None if len(d) == 1 else d[1] 

route_params[d[0]] = v 

 

return functional, basis_set, route_params, dieze_tag 

 

class GaussianInput(object): 

""" 

An object representing a Gaussian input file. 

 

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. 

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. 

title: Title for run. Defaults to formula of molecule if None. 

functional: Functional for run. 

basis_set: Basis set for run. 

route_parameters: Additional route parameters as a dict. For example, 

{'SP':"", "SCF":"Tight"} 

input_parameters: Additional input parameters for run as a dict. Used 

for example, in PCM calculations. E.g., {"EPS":12} 

link0_parameters: Link0 parameters as a dict. E.g., {"%mem": "1000MW"} 

dieze_tag: # preceding the route line. E.g. "#p" 

gen_basis: allows a user-specified basis set to be used in a Gaussian 

calculation. If this is not None, the attribute ``basis_set`` will 

be set to "Gen". 

""" 

 

#Commonly used regex patterns 

zmat_patt = re.compile("^(\w+)*([\s,]+(\w+)[\s,]+(\w+))*[\-\.\s,\w]*$") 

xyz_patt = re.compile("^(\w+)[\s,]+([\d\.eE\-]+)[\s,]+([\d\.eE\-]+)[\s,]+" 

"([\d\.eE\-]+)[\-\.\s,\w.]*$") 

 

def __init__(self, mol, charge=None, spin_multiplicity=None, title=None, 

functional="HF", basis_set="6-31G(d)", route_parameters=None, 

input_parameters=None, link0_parameters=None, dieze_tag="#P", 

gen_basis=None): 

self._mol = mol 

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

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

if spin_multiplicity is not None: 

self.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( 

self.charge, spin_multiplicity)) 

else: 

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

self.functional = functional 

self.basis_set = basis_set 

self.link0_parameters = link0_parameters if link0_parameters else {} 

self.route_parameters = route_parameters if route_parameters else {} 

self.input_parameters = input_parameters if input_parameters else {} 

self.title = title if title else self._mol.composition.formula 

self.dieze_tag = dieze_tag if dieze_tag[0] == "#" else "#P" 

self.gen_basis = gen_basis 

if gen_basis is not None: 

self.basis_set = "Gen" 

 

@property 

def molecule(self): 

""" 

Returns molecule associated with this GaussianInput. 

""" 

return self._mol 

 

@staticmethod 

def parse_coords(coord_lines): 

""" 

Helper method to parse coordinates. 

""" 

paras = {} 

var_pattern = re.compile("^([A-Za-z]+\S*)[\s=,]+([\d\-\.]+)$") 

for l in coord_lines: 

m = var_pattern.match(l.strip()) 

if m: 

paras[m.group(1)] = float(m.group(2)) 

 

species = [] 

coords = [] 

# Stores whether a Zmatrix format is detected. Once a zmatrix format 

# is detected, it is assumed for the remaining of the parsing. 

zmode = False 

for l in coord_lines: 

l = l.strip() 

if not l: 

break 

if (not zmode) and GaussianInput.xyz_patt.match(l): 

m = GaussianInput.xyz_patt.match(l) 

species.append(m.group(1)) 

toks = re.split("[,\s]+", l.strip()) 

if len(toks) > 4: 

coords.append([float(i) for i in toks[2:5]]) 

else: 

coords.append([float(i) for i in toks[1:4]]) 

elif GaussianInput.zmat_patt.match(l): 

zmode = True 

toks = re.split("[,\s]+", l.strip()) 

species.append(toks[0]) 

toks.pop(0) 

if len(toks) == 0: 

coords.append(np.array([0, 0, 0])) 

else: 

nn = [] 

parameters = [] 

while len(toks) > 1: 

ind = toks.pop(0) 

data = toks.pop(0) 

try: 

nn.append(int(ind)) 

except ValueError: 

nn.append(species.index(ind) + 1) 

try: 

val = float(data) 

parameters.append(val) 

except ValueError: 

if data.startswith("-"): 

parameters.append(-paras[data[1:]]) 

else: 

parameters.append(paras[data]) 

if len(nn) == 1: 

coords.append(np.array([0, 0, parameters[0]])) 

elif len(nn) == 2: 

coords1 = coords[nn[0] - 1] 

coords2 = coords[nn[1] - 1] 

bl = parameters[0] 

angle = parameters[1] 

axis = [0, 1, 0] 

op = SymmOp.from_origin_axis_angle(coords1, axis, 

angle, False) 

coord = op.operate(coords2) 

vec = coord - coords1 

coord = vec * bl / np.linalg.norm(vec) + coords1 

coords.append(coord) 

elif len(nn) == 3: 

coords1 = coords[nn[0] - 1] 

coords2 = coords[nn[1] - 1] 

coords3 = coords[nn[2] - 1] 

bl = parameters[0] 

angle = parameters[1] 

dih = parameters[2] 

v1 = coords3 - coords2 

v2 = coords1 - coords2 

axis = np.cross(v1, v2) 

op = SymmOp.from_origin_axis_angle( 

coords1, axis, angle, False) 

coord = op.operate(coords2) 

v1 = coord - coords1 

v2 = coords1 - coords2 

v3 = np.cross(v1, v2) 

adj = get_angle(v3, axis) 

axis = coords1 - coords2 

op = SymmOp.from_origin_axis_angle( 

coords1, axis, dih - adj, False) 

coord = op.operate(coord) 

vec = coord - coords1 

coord = vec * bl / np.linalg.norm(vec) + coords1 

coords.append(coord) 

 

def parse_species(sp_str): 

""" 

The species specification can take many forms. E.g., 

simple integers representing atomic numbers ("8"), 

actual species string ("C") or a labelled species ("C1"). 

Sometimes, the species string is also not properly capitalized, 

e.g, ("c1"). This method should take care of these known formats. 

""" 

try: 

return int(sp_str) 

except ValueError: 

sp = re.sub("\d", "", sp_str) 

return sp.capitalize() 

 

species = [parse_species(sp) for sp in species] 

 

return Molecule(species, coords) 

 

@staticmethod 

def from_string(contents): 

""" 

Creates GaussianInput from a string. 

 

Args: 

contents: String representing an Gaussian input file. 

 

Returns: 

GaussianInput object 

""" 

lines = [l.strip() for l in contents.split("\n")] 

 

link0_patt = re.compile("^(%.+)\s*=\s*(.+)") 

link0_dict = {} 

for i, l in enumerate(lines): 

if link0_patt.match(l): 

m = link0_patt.match(l) 

link0_dict[m.group(1)] = m.group(2) 

 

route_patt = re.compile("^#[sSpPnN]*.*") 

route = None 

for i, l in enumerate(lines): 

if route_patt.match(l): 

route = l 

route_index = i 

break 

functional, basis_set, route_paras, dieze_tag = read_route_line(route) 

 

ind = 2 

title = [] 

while lines[route_index + ind].strip(): 

title.append(lines[route_index + ind].strip()) 

ind += 1 

title = ' '.join(title) 

ind += 1 

toks = re.split("[\s,]", lines[route_index + ind]) 

charge = int(toks[0]) 

spin_mult = int(toks[1]) 

coord_lines = [] 

spaces = 0 

input_paras = {} 

ind += 1 

for i in range(route_index + ind, len(lines)): 

if lines[i].strip() == "": 

spaces += 1 

if spaces >= 2: 

d = lines[i].split("=") 

if len(d) == 2: 

input_paras[d[0]] = d[1] 

else: 

coord_lines.append(lines[i].strip()) 

mol = GaussianInput.parse_coords(coord_lines) 

mol.set_charge_and_spin(charge, spin_mult) 

 

return GaussianInput(mol, charge=charge, spin_multiplicity=spin_mult, 

title=title, functional=functional, 

basis_set=basis_set, route_parameters=route_paras, 

input_parameters=input_paras,link0_parameters=link0_dict, 

dieze_tag=dieze_tag) 

 

@staticmethod 

def from_file(filename): 

""" 

Creates GaussianInput from a file. 

 

Args: 

filename: Gaussian input filename 

 

Returns: 

GaussianInput object 

""" 

with zopen(filename, "r") as f: 

return GaussianInput.from_string(f.read()) 

 

def _find_nn_pos_before_site(self, siteindex): 

""" 

Returns index of nearest neighbor atoms. 

""" 

alldist = [(self._mol.get_distance(siteindex, i), i) 

for i in range(siteindex)] 

alldist = sorted(alldist, key=lambda x: x[0]) 

return [d[1] for d in alldist] 

 

def get_zmatrix(self): 

""" 

Returns a z-matrix representation of the molecule. 

""" 

output = [] 

outputvar = [] 

for i, site in enumerate(self._mol): 

if i == 0: 

output.append("{}".format(site.specie)) 

elif i == 1: 

nn = self._find_nn_pos_before_site(i) 

bondlength = self._mol.get_distance(i, nn[0]) 

output.append("{} {} B{}".format(self._mol[i].specie, 

nn[0] + 1, i)) 

outputvar.append("B{}={:.6f}".format(i, bondlength)) 

elif i == 2: 

nn = self._find_nn_pos_before_site(i) 

bondlength = self._mol.get_distance(i, nn[0]) 

angle = self._mol.get_angle(i, nn[0], nn[1]) 

output.append("{} {} B{} {} A{}".format(self._mol[i].specie, 

nn[0] + 1, i, 

nn[1] + 1, i)) 

outputvar.append("B{}={:.6f}".format(i, bondlength)) 

outputvar.append("A{}={:.6f}".format(i, angle)) 

else: 

nn = self._find_nn_pos_before_site(i) 

bondlength = self._mol.get_distance(i, nn[0]) 

angle = self._mol.get_angle(i, nn[0], nn[1]) 

dih = self._mol.get_dihedral(i, nn[0], nn[1], nn[2]) 

output.append("{} {} B{} {} A{} {} D{}" 

.format(self._mol[i].specie, nn[0] + 1, i, 

nn[1] + 1, i, nn[2] + 1, i)) 

outputvar.append("B{}={:.6f}".format(i, bondlength)) 

outputvar.append("A{}={:.6f}".format(i, angle)) 

outputvar.append("D{}={:.6f}".format(i, dih)) 

return "\n".join(output) + "\n\n" + "\n".join(outputvar) 

 

def get_cart_coords(self): 

""" 

Return the cartesian coordinates of the molecule 

""" 

outs = [] 

to_s = lambda x: "%0.6f" % x 

for i, site in enumerate(self._mol): 

outs.append(" ".join([site.species_string, " ".join([to_s(j) for j in site.coords])])) 

return "\n".join(outs) 

 

def __str__(self): 

return self.to_string() 

 

 

def to_string(self, cart_coords=False): 

""" 

Return GaussianInput string 

 

Option: whe cart_coords sets to True return the cartesian coordinates 

instead of the z-matrix 

 

""" 

def para_dict_to_string(para, joiner=" "): 

para_str = ["{}={}".format(k, v) if v else k 

for k, v in sorted(para.items())] 

return joiner.join(para_str) 

 

output = [] 

if self.link0_parameters: 

output.append(para_dict_to_string(self.link0_parameters, "\n")) 

output.append("{diez} {func}/{bset} {route}" 

.format(diez=self.dieze_tag, func=self.functional, 

bset=self.basis_set, 

route=para_dict_to_string(self.route_parameters)) 

) 

output.append("") 

output.append(self.title) 

output.append("") 

output.append("{} {}".format(self.charge, self.spin_multiplicity)) 

if isinstance(self._mol, Molecule): 

if cart_coords is True: 

output.append(self.get_cart_coords()) 

else: 

output.append(self.get_zmatrix()) 

else: 

output.append(str(self._mol)) 

output.append("") 

if self.gen_basis is not None: 

output.append("{:s}\n".format(self.gen_basis)) 

output.append(para_dict_to_string(self.input_parameters, "\n")) 

output.append("\n") 

return "\n".join(output) 

 

def write_file(self, filename,cart_coords=False): 

""" 

Write the input string into a file 

 

Option: see __str__ method 

""" 

with zopen(filename, "w") as f: 

f.write(self.to_string(cart_coords)) 

 

def as_dict(self): 

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

"@class": self.__class__.__name__, 

"molecule": self.molecule.as_dict(), 

"functional": self.functional, 

"basis_set": self.basis_set, 

"route_parameters": self.route_parameters, 

"title": self.title, 

"charge": self.charge, 

"spin_multiplicity": self.spin_multiplicity, 

"input_parameters": self.input_parameters, 

"link0_parameters": self.link0_parameters, 

"dieze_tag": self.dieze_tag} 

 

@classmethod 

def from_dict(cls, d): 

return GaussianInput(mol=Molecule.from_dict(d["molecule"]), 

functional=d["functional"], 

basis_set=d["basis_set"], 

route_parameters=d["route_parameters"], 

title=d["title"], 

charge=d["charge"], 

spin_multiplicity=d["spin_multiplicity"], 

input_parameters=d["input_parameters"], 

link0_parameters=d["link0_parameters"]) 

 

 

 

class GaussianOutput(object): 

""" 

Parser for Gaussian output files. 

 

Args: 

filename: Filename of Gaussian output file. 

 

.. note:: 

 

Still in early beta. 

 

Attributes: 

 

.. attribute:: structures 

 

All structures from the calculation. 

 

.. attribute:: energies 

 

All energies from the calculation. 

 

.. attribute:: cart_forces 

 

All cartesian forces from the calculation. 

 

.. attribute:: frequencies 

 

The frequencies and normal modes. 

 

.. attribute:: properly_terminated 

 

True if run has properly terminated 

 

.. attribute:: is_pcm 

 

True if run is a PCM run. 

 

.. attribute:: stationary_type 

 

If it is a relaxation run, indicates whether it is a minimum (Minimum) 

or a saddle point ("Saddle"). 

 

.. attribute:: corrections 

 

Thermochemical corrections if this run is a Freq run as a dict. Keys 

are "Zero-point", "Thermal", "Enthalpy" and "Gibbs Free Energy" 

 

.. attribute:: functional 

 

Functional used in the run. 

 

.. attribute:: basis_set 

 

Basis set used in the run 

 

.. attribute:: route 

 

Additional route parameters as a dict. For example, 

{'SP':"", "SCF":"Tight"} 

 

.. attribute:: dieze_tag 

 

# preceding the route line, e.g. "#P" 

 

.. attribute:: link0 

 

Link0 parameters as a dict. E.g., {"%mem": "1000MW"} 

 

.. attribute:: charge 

 

Charge for structure 

 

.. attribute:: spin_mult 

 

Spin multiplicity for structure 

 

.. attribute:: num_basis_func 

 

Number of basis functions in the run. 

 

.. attribute:: pcm 

 

PCM parameters and output if available. 

 

.. attribute:: errors 

 

error if not properly terminated (list to be completed in error_defs) 

 

.. attribute:: Mulliken_charges 

 

Mulliken atomic charges 

 

Methods: 

 

.. method:: to_input() 

 

Return a GaussianInput object using the last geometry and the same 

calculation parameters. 

 

.. method:: read_scan() 

 

Read a potential energy surface from a gaussian scan calculation. 

 

.. method:: get_scan_plot() 

 

Get a matplotlib plot of the potential energy surface 

 

.. method:: save_scan_plot() 

 

Save a matplotlib plot of the potential energy surface to a file 

 

""" 

 

def __init__(self, filename): 

self.filename = filename 

self._parse(filename) 

 

@property 

def final_energy(self): 

return self.energies[-1] 

 

@property 

def final_structure(self): 

return self.structures[-1] 

 

def _parse(self, filename): 

start_patt = re.compile(" \(Enter \S+l101\.exe\)") 

route_patt = re.compile(" #[pPnNtT]*.*") 

link0_patt = re.compile("^\s(%.+)\s*=\s*(.+)") 

charge_mul_patt = re.compile("Charge\s+=\s*([-\\d]+)\s+" 

"Multiplicity\s+=\s*(\d+)") 

num_basis_func_patt = re.compile("([0-9]+)\s+basis functions") 

pcm_patt = re.compile("Polarizable Continuum Model") 

stat_type_patt = re.compile("imaginary frequencies") 

scf_patt = re.compile("E\(.*\)\s*=\s*([-\.\d]+)\s+") 

mp2_patt = re.compile("EUMP2\s*=\s*(.*)") 

oniom_patt = re.compile("ONIOM:\s+extrapolated energy\s*=\s*(.*)") 

termination_patt = re.compile("(Normal|Error) termination") 

error_patt = re.compile( 

"(! Non-Optimized Parameters !|Convergence failure)") 

mulliken_patt = re.compile( 

"^\s*(Mulliken charges|Mulliken atomic charges)") 

mulliken_charge_patt = re.compile( 

'^\s+(\d+)\s+([A-Z][a-z]?)\s*(\S*)') 

end_mulliken_patt = re.compile( 

'(Sum of Mulliken )(.*)(charges)\s*=\s*(\D)') 

std_orientation_patt = re.compile("Standard orientation") 

end_patt = re.compile("--+") 

orbital_patt = re.compile("Alpha\s*\S+\s*eigenvalues --(.*)") 

thermo_patt = re.compile("(Zero-point|Thermal) correction(.*)=" 

"\s+([\d\.-]+)") 

forces_on_patt = re.compile( 

"Center\s+Atomic\s+Forces\s+\(Hartrees/Bohr\)") 

forces_off_patt = re.compile("Cartesian\s+Forces:\s+Max.*RMS.*") 

forces_patt = re.compile( 

"\s+(\d+)\s+(\d+)\s+([0-9\.-]+)\s+([0-9\.-]+)\s+([0-9\.-]+)") 

 

freq_on_patt = re.compile( 

"Harmonic\sfrequencies\s+\(cm\*\*-1\),\sIR\sintensities.*Raman.*") 

freq_patt = re.compile("Frequencies\s--\s+(.*)") 

normal_mode_patt = re.compile( 

"\s+(\d+)\s+(\d+)\s+([0-9\.-]{4,5})\s+([0-9\.-]{4,5}).*") 

 

self.properly_terminated = False 

self.is_pcm = False 

self.stationary_type = "Minimum" 

self.structures = [] 

self.corrections = {} 

self.energies = [] 

self.pcm = None 

self.errors = [] 

self.Mulliken_charges = {} 

self.link0 = {} 

self.cart_forces = [] 

self.frequencies = [] 

 

coord_txt = [] 

read_coord = 0 

read_mulliken = False 

orbitals_txt = [] 

parse_stage = 0 

num_basis_found = False 

terminated = False 

parse_forces = False 

forces = [] 

parse_freq = False 

frequencies = [] 

 

with zopen(filename) as f: 

for line in f: 

if parse_stage == 0: 

if start_patt.search(line): 

parse_stage = 1 

elif link0_patt.match(line): 

m = link0_patt.match(line) 

self.link0[m.group(1)] = m.group(2) 

elif route_patt.search(line): 

params = read_route_line(line) 

self.functional = params[0] 

self.basis_set = params[1] 

self.route = params[2] 

self.dieze_tag = params[3] 

parse_stage = 1 

elif parse_stage == 1: 

if charge_mul_patt.search(line): 

m = charge_mul_patt.search(line) 

self.charge = int(m.group(1)) 

self.spin_mult = int(m.group(2)) 

parse_stage = 2 

elif parse_stage == 2: 

 

if self.is_pcm: 

self._check_pcm(line) 

 

if "FREQ" in self.route and thermo_patt.search(line): 

m = thermo_patt.search(line) 

if m.group(1) == "Zero-point": 

self.corrections["Zero-point"] = float(m.group(3)) 

else: 

key = m.group(2).strip(" to ") 

self.corrections[key] = float(m.group(3)) 

 

if read_coord: 

if not end_patt.search(line): 

coord_txt.append(line) 

else: 

read_coord = (read_coord + 1) % 4 

if not read_coord: 

sp = [] 

coords = [] 

for l in coord_txt[2:]: 

toks = l.split() 

sp.append(Element.from_Z(int(toks[1]))) 

coords.append([float(i) for i in toks[3:6]]) 

self.structures.append(Molecule(sp, coords)) 

 

if parse_forces: 

m = forces_patt.search(line) 

if m: 

forces.extend([float(_v) for _v in m.groups()[2:5]]) 

elif forces_off_patt.search(line): 

self.cart_forces.append(forces) 

forces = [] 

parse_forces = False 

 

elif parse_freq: 

m = freq_patt.search(line) 

if m: 

values = [float(_v) for _v in m.groups()[0].split()] 

for value in values: 

frequencies.append([value, []]) 

elif normal_mode_patt.search(line): 

values = [float(_v) for _v in line.split()[2:]] 

n = int(len(values) / 3) 

for i in range(0, len(values), 3): 

j = -n + int(i / 3) 

frequencies[j][1].extend(values[i:i+3]) 

elif line.find("-------------------") != -1: 

parse_freq = False 

self.frequencies.append(frequencies) 

frequencies = [] 

 

elif termination_patt.search(line): 

m = termination_patt.search(line) 

if m.group(1) == "Normal": 

self.properly_terminated = True 

terminated = True 

elif error_patt.search(line): 

error_defs = { 

"! Non-Optimized Parameters !": "Optimization " 

"error", 

"Convergence failure": "SCF convergence error" 

} 

m = error_patt.search(line) 

self.errors.append(error_defs[m.group(1)]) 

elif (not num_basis_found) and \ 

num_basis_func_patt.search(line): 

m = num_basis_func_patt.search(line) 

self.num_basis_func = int(m.group(1)) 

num_basis_found = True 

elif (not self.is_pcm) and pcm_patt.search(line): 

self.is_pcm = True 

self.pcm = {} 

elif "FREQ" in self.route and "OPT" in self.route and \ 

stat_type_patt.search(line): 

self.stationary_type = "Saddle" 

elif mp2_patt.search(line): 

m = mp2_patt.search(line) 

self.energies.append(float(m.group(1).replace("D", 

"E"))) 

elif oniom_patt.search(line): 

m = oniom_patt.matcher(line) 

self.energies.append(float(m.group(1))) 

elif scf_patt.search(line): 

m = scf_patt.search(line) 

self.energies.append(float(m.group(1))) 

elif std_orientation_patt.search(line): 

coord_txt = [] 

read_coord = 1 

elif orbital_patt.search(line): 

orbitals_txt.append(line) 

elif mulliken_patt.search(line): 

mulliken_txt = [] 

read_mulliken = True 

elif not parse_forces and forces_on_patt.search(line): 

parse_forces = True 

elif freq_on_patt.search(line): 

parse_freq = True 

 

if read_mulliken: 

if not end_mulliken_patt.search(line): 

mulliken_txt.append(line) 

else: 

m = end_mulliken_patt.search(line) 

mulliken_charges = {} 

for line in mulliken_txt: 

if mulliken_charge_patt.search(line): 

m = mulliken_charge_patt.search(line) 

dict = {int(m.group(1)): [m.group(2), float(m.group(3))]} 

mulliken_charges.update(dict) 

read_mulliken = False 

self.Mulliken_charges = mulliken_charges 

 

if not terminated: 

#raise IOError("Bad Gaussian output file.") 

warnings.warn("\n" + self.filename + \ 

": Termination error or bad Gaussian output file !") 

 

def _check_pcm(self, line): 

energy_patt = re.compile("(Dispersion|Cavitation|Repulsion) energy" 

"\s+\S+\s+=\s+(\S*)") 

total_patt = re.compile("with all non electrostatic terms\s+\S+\s+" 

"=\s+(\S*)") 

parameter_patt = re.compile("(Eps|Numeral density|RSolv|Eps" 

"\(inf[inity]*\))\s+=\s*(\S*)") 

 

if energy_patt.search(line): 

m = energy_patt.search(line) 

self.pcm['{} energy'.format(m.group(1))] = float(m.group(2)) 

elif total_patt.search(line): 

m = total_patt.search(line) 

self.pcm['Total energy'] = float(m.group(1)) 

elif parameter_patt.search(line): 

m = parameter_patt.search(line) 

self.pcm[m.group(1)] = float(m.group(2)) 

 

def as_dict(self): 

""" 

Json-serializable dict representation. 

""" 

structure = self.final_structure 

d = {"has_gaussian_completed": self.properly_terminated, 

"nsites": len(structure)} 

comp = structure.composition 

d["unit_cell_formula"] = comp.as_dict() 

d["reduced_cell_formula"] = Composition(comp.reduced_formula).as_dict() 

d["pretty_formula"] = comp.reduced_formula 

d["is_pcm"] = self.is_pcm 

d["errors"] = self.errors 

d["Mulliken_charges"] = self.Mulliken_charges 

 

unique_symbols = sorted(list(d["unit_cell_formula"].keys())) 

d["elements"] = unique_symbols 

d["nelements"] = len(unique_symbols) 

d["charge"] = self.charge 

d["spin_multiplicity"] = self.spin_mult 

 

vin = {"route": self.route, "functional": self.functional, 

"basis_set": self.basis_set, 

"nbasisfunctions": self.num_basis_func, 

"pcm_parameters": self.pcm} 

 

d["input"] = vin 

 

nsites = len(self.final_structure) 

 

vout = { 

"energies": self.energies, 

"final_energy": self.final_energy, 

"final_energy_per_atom": self.final_energy / nsites, 

"molecule": structure.as_dict(), 

"stationary_type": self.stationary_type, 

"corrections": self.corrections 

} 

 

d['output'] = vout 

d["@module"] = self.__class__.__module__ 

d["@class"] = self.__class__.__name__ 

 

return d 

 

def read_scan(self): 

"""  

Read a potential energy surface from a gaussian scan calculation. 

 

Returns: 

 

A dict: {"energies": [ values ],  

"coords": {"d1": [ values ], "A2", [ values ], ... }} 

 

"energies" are the energies of all points of the potential energy 

surface. "coords" are the internal coordinates used to compute the  

potential energy surface and the internal coordinates optimized,  

labelled by their name as defined in the calculation. 

""" 

 

def floatList(l): 

""" return a list of float from a list of string """ 

return [float(v) for v in l] 

 

scan_patt = re.compile("^\sSummary of the potential surface scan:") 

optscan_patt = re.compile("^\sSummary of Optimized Potential Surface Scan") 

float_patt = re.compile("\s*([+-]?\d+\.\d+)") 

 

# data dict return 

data = {"energies": list(), "coords": dict()} 

 

# read in file 

with zopen(self.filename, "r") as f: 

line = f.readline() 

 

while line != "": 

if optscan_patt.match(line): 

f.readline() 

line = f.readline() 

endScan = False 

while not endScan: 

data["energies"] += floatList(float_patt.findall(line)) 

line = f.readline() 

while not re.search("(^\s+(\d+)|^\s-+)", line): 

icname = line.split()[0].strip() 

if icname in data["coords"]: 

data["coords"][icname] += floatList(float_patt.findall(line)) 

else: 

data["coords"][icname] = floatList(float_patt.findall(line)) 

line = f.readline() 

if re.search("^\s-+", line): 

endScan = True 

else: 

line = f.readline() 

 

elif scan_patt.match(line): 

line = f.readline() 

data["coords"] = {icname: list() for icname in line.split()[1:-1]} 

f.readline() 

line = f.readline() 

while not re.search("^\s-+", line): 

values = floatList(line.split()) 

data["energies"].append(values[-1]) 

for i, icname in enumerate(data["coords"]): 

data["coords"][icname].append(values[i+1]) 

line = f.readline() 

else: 

line = f.readline() 

 

return data 

 

def get_scan_plot(self, coords=None): 

""" 

Get a matplotlib plot of the potential energy surface. 

 

Args: 

coords: internal coordinate name to use as abcissa. 

""" 

from pymatgen.util.plotting_utils import get_publication_quality_plot 

 

plt = get_publication_quality_plot(12, 8) 

 

d = self.read_scan() 

 

if coords and coords in d["coords"]: 

x = d["coords"][coords] 

plt.xlabel(coords) 

else: 

x = range(len(d["energies"])) 

plt.xlabel("points") 

 

plt.ylabel("Energy / eV") 

 

e_min = min(d["energies"]) 

y = [(e - e_min) * cst.HARTREE_TO_ELECTRON_VOLT for e in d["energies"]] 

 

plt.plot(x, y, "ro--") 

return plt 

 

def save_scan_plot(self, filename="scan.pdf", img_format="pdf", coords=None): 

""" 

Save matplotlib plot of the potential energy surface to a file. 

 

Args: 

filename: Filename to write to. 

img_format: Image format to use. Defaults to EPS. 

coords: internal coordinate name to use as abcissa. 

""" 

plt = self.get_scan_plot(coords) 

plt.savefig(filename, format=img_format) 

 

def read_excitation_energies(self): 

""" 

Read a excitation energies after a TD-DFT calculation. 

 

Returns: 

 

A list: A list of tuple for each transition such as  

[(energie (eV), lambda (nm), oscillatory strength), ... ] 

""" 

float_patt = re.compile("\s*([+-]?\d+\.\d+)") 

 

transitions = list() 

 

# read in file 

with zopen(self.filename, "r") as f: 

line = f.readline() 

td = False 

while line != "": 

if re.search("^\sExcitation energies and oscillator strengths:", line): 

td = True 

 

if td: 

if re.search("^\sExcited State\s*\d", line): 

val = [float(v) for v in float_patt.findall(line)] 

transitions.append(tuple(val[0:3])) 

line = f.readline() 

return transitions 

 

def get_spectre_plot(self, sigma=0.05, step=0.01): 

""" 

Get a matplotlib plot of the UV-visible spectra. Transition are plotted 

as vertical lines and as a sum of normal functions with sigma with. The 

broadening is applied in energy and the spectra is plotted as a function 

of the wavelength. 

 

Args: 

sigma: Full width at half maximum in eV for normal functions. 

step: bin interval in eV 

 

Returns: 

A dict: {"energies": values, "lambda": values, "spectra": values} 

where values are lists of abscissa (energies, lamba) and 

the sum of gaussian functions (spectra). 

A matplotlib plot. 

""" 

from pymatgen.util.plotting_utils import get_publication_quality_plot 

from matplotlib.mlab import normpdf 

plt = get_publication_quality_plot(12, 8) 

 

transitions = self.read_excitation_energies() 

 

minval = min([val[0] for val in transitions]) - 5.0 * sigma 

maxval = max([val[0] for val in transitions]) + 5.0 * sigma 

npts = int((maxval - minval) / step) + 1 

 

eneval = np.linspace(minval, maxval, npts) # in eV 

lambdaval = [cst.h * cst.c / (val * cst.e) * 1.e9 for val in eneval] # in nm 

 

# sum of gaussian functions  

spectre = np.zeros(npts) 

for trans in transitions: 

spectre += trans[2] * normpdf(eneval, trans[0], sigma) 

spectre /= spectre.max() 

plt.plot(lambdaval, spectre, "r-", label="spectre") 

 

data = {"energies": eneval, "lambda": lambdaval, "spectra": spectre} 

 

# plot transitions as vlines 

plt.vlines([val[1] for val in transitions], \ 

0., \ 

[val[2] for val in transitions], \ 

color="blue", \ 

label="transitions", 

linewidth=2) 

 

plt.xlabel("$\lambda$ (nm)") 

plt.ylabel("Arbitrary unit") 

plt.legend() 

 

return data, plt 

 

def save_spectre_plot(self, filename="spectre.pdf", img_format="pdf", 

sigma=0.05, step=0.01): 

""" 

Save matplotlib plot of the spectre to a file. 

 

Args: 

filename: Filename to write to. 

img_format: Image format to use. Defaults to EPS. 

sigma: Full width at half maximum in eV for normal functions. 

step: bin interval in eV  

""" 

d, plt = self.get_spectre_plot(sigma, step) 

plt.savefig(filename, format=img_format) 

 

def to_input(self, filename, mol=None, charge=None, 

spin_multiplicity=None, title=None, functional=None, 

basis_set=None, route_parameters=None, input_parameters=None, 

link0_parameters=None, dieze_tag=None, cart_coords=False): 

""" 

Write a new input file using by default the last geometry read in the output 

file and with the same calculation parameters. Arguments are the same as 

GaussianInput class. 

 

Returns 

gaunip (GaussianInput) : the gaussian input object 

""" 

if not mol: 

mol = self.final_structure 

 

if not charge: 

charge = self.charge 

 

if not spin_multiplicity: 

spin_multiplicity = self.spin_mult 

 

if not title: 

title = "restart " 

 

if not functional: 

functional = self.functional 

 

if not basis_set: 

basis_set = self.basis_set 

 

if not route_parameters: 

route_parameters = self.route 

 

if not link0_parameters: 

link0_parameters = self.link0 

 

if not dieze_tag: 

dieze_tag = self.dieze_tag 

 

gauinp = GaussianInput(mol=mol, 

charge=charge, 

spin_multiplicity=spin_multiplicity, 

title=title, 

functional=functional, 

basis_set=basis_set, 

route_parameters=route_parameters, 

input_parameters=input_parameters, 

link0_parameters=link0_parameters, 

dieze_tag=dieze_tag) 

 

gauinp.write_file(filename, cart_coords=cart_coords) 

 

return gauinp