# Source code for pymatgen.io.gaussian

    # coding: utf-8
    # Copyright (c) Pymatgen Development Team.
    # Distributed under the terms of the MIT License.

    """
    This module implements input and output processing from Gaussian.
    """

    import re

    import numpy as np
    import warnings

    from pymatgen.core.operations import SymmOp
    from pymatgen import Element, Molecule, Composition
    from monty.io import zopen
    from pymatgen.core.units import Ha_to_eV
    from pymatgen.util.coord import get_angle
    import scipy.constants as cst

    from pymatgen.electronic_structure.core import Spin

    __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'

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

    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(r"^([sS][cC][rR][fF])\s*=\s*(.+)")
        multi_params_patt = re.compile(r"^([A-z]+[0-9]*)[\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 tok.upper() in ["#", "#N", "#P", "#T"]:
                    # does not store # in route to avoid error in input
                    if tok == "#":
                        dieze_tag = "#N"
                    else:
                        dieze_tag = tok
                    continue
                else:
                    m = re.match(multi_params_patt, tok.strip("#"))
                    if m:
                        pars = {}
                        for par in m.group(2).split(","):
                            p = par.split("=")
                            pars[p[0]] = None if len(p) == 1 else p[1]
                        route_params[m.group(1)] = pars
                    else:
                        d = tok.strip("#").split("=")
                        route_params[d[0]] = None if len(d) == 1 else d[1]

        return functional, basis_set, route_params, dieze_tag

    class GaussianInput:
        """
        An object representing a Gaussian input file.
        """

        # Commonly used regex patterns
        _zmat_patt = re.compile(r"^(\w+)*([\s,]+(\w+)[\s,]+(\w+))*[\-\.\s,\w]*$")
        _xyz_patt = re.compile(r"^(\w+)[\s,]+([\d\.eE\-]+)[\s,]+([\d\.eE\-]+)[\s,]+"
                               r"([\d\.eE\-]+)[\-\.\s,\w.]*$")

        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):
            """
            Args:
                mol: Input molecule. It can either be a Molecule object,
                    a string giving the geometry in a format supported by Guassian,
                    or ``None``. If the molecule is ``None``, you will need to use
                    read it in from a checkpoint. Consider adding ``CHK`` to the
                    ``link0_parameters``.
                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.
                    If ``mol`` is not a Molecule object, then you must specify a charge.
                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. If ``mol`` is not a Molecule object, then you
                     must specify the multiplicity
                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".
            """
            self._mol = mol

            # Determine multiplicity and charge settings
            if isinstance(mol, Molecule):
                self.charge = charge if charge is not None else mol.charge
                nelectrons = mol.charge + mol.nelectrons - self.charge
                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

                # Get a title from the molecule name
                self.title = title if title else self._mol.composition.formula
            else:
                if charge is None or spin_multiplicity is None:
                    raise ValueError('`charge` and `spin_multiplicity` must be specified')
                self.charge = charge
                self.spin_multiplicity = spin_multiplicity

                # Set a title
                self.title = title if title else 'Restart'

            # Store the remaining settings
            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.dieze_tag = dieze_tag if dieze_tag[0] == "#" else "#" + dieze_tag
            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(r"^([A-Za-z]+\S*)[\s=,]+([\d\-\.]+)$")
            for l in coord_lines:
                m = var_pattern.match(l.strip())
                if m:
                    paras[m.group(1).strip("=")] = 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(r"[,\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(r"[,\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(r"\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(r"^(%.+)\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).strip("=")] = m.group(2)

            route_patt = re.compile(r"^#[sSpPnN]*.*")
            route = ""
            route_index = None
            for i, l in enumerate(lines):
                if route_patt.match(l):
                    route += " " + l
                    route_index = i
                # This condition allows for route cards spanning multiple lines
                elif (l == "" or l.isspace()) and route_index:
                    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(r"[,\s]+", lines[route_index + ind])
            charge = int(float(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
            """
            def to_s(x):
                return "%0.6f" % x

            outs = []
            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 = []
                # sorted is only done to make unittests work reliably
                for par, val in sorted(para.items()):
                    if val is None or val == "":
                        para_str.append(par)
                    elif isinstance(val, dict):
                        val_str = para_dict_to_string(val, joiner=",")
                        para_str.append("{}=({})".format(par, val_str))
                    else:
                        para_str.append("{}={}".format(par, val))
                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("%d %d" % (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())
            elif self._mol is not None:
                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: MSONable dict
            """
            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):
            """
            :param d: dict
            :return: GaussianInput
            """
            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:
        """
        Parser for Gaussian output files.

        .. note::

            Still in early beta.

        Attributes:

        .. attribute:: structures

            All structures from the calculation in the standard orientation. If the
            symmetry is not considered, the standard orientation is not printed out
            and the input orientation is used instead. Check the `standard_orientation`
            attribute.

        .. attribute:: structures_input_orientation

            All structures from the calculation in the input orientation or the
            Z-matrix orientation (if an opt=z-matrix was requested).

        .. attribute:: opt_structures

            All optimized structures from the calculation in the input orientation
            or the Z-matrix orientation.

        .. attribute:: energies

            All energies from the calculation.

        .. attribute:: eigenvalues

            List of eigenvalues for the last geometry

        .. attribute:: MO_coefficients

            Matrix of MO coefficients for the last geometry

        .. attribute:: cart_forces

            All cartesian forces from the calculation.

        .. attribute:: frequencies

            A list for each freq calculation and for each mode of a dict with
            {
                "frequency": freq in cm-1,
                "symmetry": symmetry tag
                "r_mass": Reduce mass,
                "f_constant": force constant,
                "IR_intensity": IR Intensity,
                "mode": normal mode
             }

            The normal mode is a 1D vector of dx, dy dz of each atom.

        .. attribute:: hessian

            Matrix of second derivatives of the energy with respect to cartesian
            coordinates in the **input orientation** frame. Need #P in the
            route section in order to be in the output.

        .. attribute:: properly_terminated

            True if run has properly terminated

        .. attribute:: is_pcm

            True if run is a PCM run.

        .. attribute:: is_spin

            True if it is an unrestricted 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_multiplicity

            Spin multiplicity for structure

        .. attribute:: num_basis_func

            Number of basis functions in the run.

        .. attribute:: electrons

            number of alpha and beta electrons as (N alpha, N beta)

        .. 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

        .. attribute:: eigenvectors

            Matrix of shape (num_basis_func, num_basis_func). Each column is an
            eigenvectors and contains AO coefficients of an MO.

            eigenvectors[Spin] = mat(num_basis_func, num_basis_func)

        .. attribute:: molecular_orbital

            MO development coefficients on AO in a more convenient array dict
            for each atom and basis set label.

            mo[Spin][OM j][atom i] = {AO_k: coeff, AO_k: coeff ... }

        .. attribute:: atom_basis_labels

            Labels of AO for each atoms. These labels are those used in the output
            of molecular orbital coefficients (POP=Full) and in the
            molecular_orbital array dict.

            atom_basis_labels[iatom] = [AO_k, AO_k, ...]

        .. attribute:: resumes

            List of gaussian data resume given at the end of the output file before
            the quotation. The resumes are given as string.

        .. attribute:: title

            Title of the gaussian run.

        .. attribute:: standard_orientation

            If True, the geometries stored in the structures are in the standard
            orientation. Else, the geometries are in the input orientation.

        .. attribute:: bond_orders

            Dict of bond order values read in the output file such as:
            {(0, 1): 0.8709, (1, 6): 1.234, ...}

            The keys are the atom indexes and the values are the Wiberg bond indexes
            that are printed using `pop=NBOREAD` and `$nbo bndidx $end`.

        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):
            """
            Args:
                filename: Filename of Gaussian output file.
            """
            self.filename = filename
            self._parse(filename)

        @property
        def final_energy(self):
            """
            :return: Final energy in Gaussian output.
            """
            return self.energies[-1]

        @property
        def final_structure(self):
            """
            :return: Final structure in Gaussian output.
            """
            return self.structures[-1]

        def _parse(self, filename):
            start_patt = re.compile(r" \(Enter \S+l101\.exe\)")
            route_patt = re.compile(r" #[pPnNtT]*.*")
            link0_patt = re.compile(r"^\s(%.+)\s*=\s*(.+)")
            charge_mul_patt = re.compile(r"Charge\s+=\s*([-\d]+)\s+"
                                         r"Multiplicity\s+=\s*(\d+)")
            num_basis_func_patt = re.compile(r"([0-9]+)\s+basis functions")
            num_elec_patt = re.compile(r"(\d+)\s+alpha electrons\s+(\d+)\s+beta electrons")
            pcm_patt = re.compile(r"Polarizable Continuum Model")
            stat_type_patt = re.compile(r"imaginary frequencies")
            scf_patt = re.compile(r"E\(.*\)\s*=\s*([-\.\d]+)\s+")
            mp2_patt = re.compile(r"EUMP2\s*=\s*(.*)")
            oniom_patt = re.compile(r"ONIOM:\s+extrapolated energy\s*=\s*(.*)")
            termination_patt = re.compile(r"(Normal|Error) termination")
            error_patt = re.compile(
                r"(! Non-Optimized Parameters !|Convergence failure)")
            mulliken_patt = re.compile(
                r"^\s*(Mulliken charges|Mulliken atomic charges)")
            mulliken_charge_patt = re.compile(
                r'^\s+(\d+)\s+([A-Z][a-z]?)\s*(\S*)')
            end_mulliken_patt = re.compile(
                r'(Sum of Mulliken )(.*)(charges)\s*=\s*(\D)')
            std_orientation_patt = re.compile(r"Standard orientation")
            input_orientation_patt = re.compile(r"Input orientation|Z-Matrix orientation")
            orbital_patt = re.compile(r"(Alpha|Beta)\s*\S+\s*eigenvalues --(.*)")
            thermo_patt = re.compile(r"(Zero-point|Thermal) correction(.*)="
                                     r"\s+([\d\.-]+)")
            forces_on_patt = re.compile(
                r"Center\s+Atomic\s+Forces\s+\(Hartrees/Bohr\)")
            forces_off_patt = re.compile(r"Cartesian\s+Forces:\s+Max.*RMS.*")
            forces_patt = re.compile(
                r"\s+(\d+)\s+(\d+)\s+([0-9\.-]+)\s+([0-9\.-]+)\s+([0-9\.-]+)")

            freq_on_patt = re.compile(
                r"Harmonic\sfrequencies\s+\(cm\*\*-1\),\sIR\sintensities.*Raman.*")

            normal_mode_patt = re.compile(
                r"\s+(\d+)\s+(\d+)\s+([0-9\.-]{4,5})\s+([0-9\.-]{4,5}).*")

            mo_coeff_patt = re.compile(r"Molecular Orbital Coefficients:")
            mo_coeff_name_patt = re.compile(r"\d+\s((\d+|\s+)\s+([a-zA-Z]{1,2}|\s+))\s+(\d+\S+)")

            hessian_patt = re.compile(r"Force constants in Cartesian coordinates:")
            resume_patt = re.compile(r"^\s1\\1\\GINC-\S*")
            resume_end_patt = re.compile(r"^\s.*\\\\@")

            bond_order_patt = re.compile(r"Wiberg bond index matrix in the NAO basis:")

            self.properly_terminated = False
            self.is_pcm = False
            self.stationary_type = "Minimum"
            self.corrections = {}
            self.energies = []
            self.pcm = None
            self.errors = []
            self.Mulliken_charges = {}
            self.link0 = {}
            self.cart_forces = []
            self.frequencies = []
            self.eigenvalues = []
            self.is_spin = False
            self.hessian = None
            self.resumes = []
            self.title = None
            self.bond_orders = {}

            read_coord = 0
            read_mulliken = False
            read_eigen = False
            eigen_txt = []
            parse_stage = 0
            num_basis_found = False
            terminated = False
            parse_forces = False
            forces = []
            parse_freq = False
            frequencies = []
            read_mo = False
            parse_hessian = False
            routeline = ""
            standard_orientation = False
            parse_bond_order = False
            input_structures = list()
            std_structures = list()
            geom_orientation = None
            opt_structures = list()

            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) or routeline != "":
                            if set(line.strip()) == {"-"}:
                                params = read_route_line(routeline)
                                self.functional = params[0]
                                self.basis_set = params[1]
                                self.route_parameters = params[2]
                                route_lower = {k.lower(): v
                                               for k, v in
                                               self.route_parameters.items()}
                                self.dieze_tag = params[3]
                                parse_stage = 1
                            else:
                                routeline += line.strip()
                    elif parse_stage == 1:
                        if set(line.strip()) == {"-"} and self.title is None:
                            self.title = ""
                        elif self.title == "":
                            self.title = line.strip()
                        elif charge_mul_patt.search(line):
                            m = charge_mul_patt.search(line)
                            self.charge = int(m.group(1))
                            self.spin_multiplicity = int(m.group(2))
                            parse_stage = 2
                    elif parse_stage == 2:

                        if self.is_pcm:
                            self._check_pcm(line)

                        if "freq" in route_lower 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:
                            [f.readline() for i in range(3)]
                            line = f.readline()
                            sp = []
                            coords = []
                            while set(line.strip()) != {"-"}:
                                toks = line.split()
                                sp.append(Element.from_Z(int(toks[1])))
                                coords.append([float(x) for x in toks[3:6]])
                                line = f.readline()

                            read_coord = False
                            if geom_orientation == "input":
                                input_structures.append(Molecule(sp, coords))
                            elif geom_orientation == "standard":
                                std_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

                        # read molecular orbital eigenvalues
                        if read_eigen:
                            m = orbital_patt.search(line)
                            if m:
                                eigen_txt.append(line)
                            else:
                                read_eigen = False
                                self.eigenvalues = {Spin.up: []}
                                for eigenline in eigen_txt:
                                    if "Alpha" in eigenline:
                                        self.eigenvalues[Spin.up] += [float(e) for e in float_patt.findall(eigenline)]
                                    elif "Beta" in eigenline:
                                        if Spin.down not in self.eigenvalues:
                                            self.eigenvalues[Spin.down] = []
                                        self.eigenvalues[Spin.down] += [float(e) for e in float_patt.findall(eigenline)]
                                eigen_txt = []

                        # read molecular orbital coefficients
                        if (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 read_mo:
                            # build a matrix with all coefficients
                            all_spin = [Spin.up]
                            if self.is_spin:
                                all_spin.append(Spin.down)

                            mat_mo = {}
                            for spin in all_spin:
                                mat_mo[spin] = np.zeros((self.num_basis_func,
                                                         self.num_basis_func))
                                nMO = 0
                                end_mo = False
                                while nMO < self.num_basis_func and not end_mo:
                                    f.readline()
                                    f.readline()
                                    self.atom_basis_labels = []
                                    for i in range(self.num_basis_func):
                                        line = f.readline()

                                        # identify atom and OA labels
                                        m = mo_coeff_name_patt.search(line)
                                        if m.group(1).strip() != "":
                                            iat = int(m.group(2)) - 1
                                            # atname = m.group(3)
                                            self.atom_basis_labels.append([m.group(4)])
                                        else:
                                            self.atom_basis_labels[iat].append(m.group(4))

                                        # MO coefficients
                                        coeffs = [float(c) for c in
                                                  float_patt.findall(line)]
                                        for j in range(len(coeffs)):
                                            mat_mo[spin][i, nMO + j] = coeffs[j]

                                    nMO += len(coeffs)
                                    line = f.readline()
                                    # manage pop=regular case (not all MO)
                                    if nMO < self.num_basis_func and \
                                        ("Density Matrix:" in line or
                                         mo_coeff_patt.search(line)):
                                        end_mo = True
                                        warnings.warn("POP=regular case, matrix "
                                                      "coefficients not complete")
                                f.readline()

                            self.eigenvectors = mat_mo
                            read_mo = False

                            # build a more convenient array dict with MO
                            # coefficient of each atom in each MO.
                            # mo[Spin][OM j][atom i] =
                            # {AO_k: coeff, AO_k: coeff ... }
                            mo = {}
                            for spin in all_spin:
                                mo[spin] = [[{} for iat in
                                             range(len(self.atom_basis_labels))]
                                            for j in range(self.num_basis_func)]
                                for j in range(self.num_basis_func):
                                    i = 0
                                    for iat in range(len(self.atom_basis_labels)):
                                        for label in self.atom_basis_labels[iat]:
                                            mo[spin][j][iat][label] = self.eigenvectors[spin][i, j]
                                            i += 1

                            self.molecular_orbital = mo

                        elif parse_freq:
                            while line.strip() != "":  #  blank line
                                ifreqs = [int(val) - 1 for val in line.split()]
                                for ifreq in ifreqs:
                                    frequencies.append({"frequency": None,
                                                        "r_mass": None,
                                                        "f_constant": None,
                                                        "IR_intensity": None,
                                                        "symmetry": None,
                                                        "mode": []})
                                # read freq, intensity, masses, symmetry ...
                                while "Atom  AN" not in line:
                                    if "Frequencies --" in line:
                                        freqs = map(float,
                                                    float_patt.findall(line))
                                        for ifreq, freq in zip(ifreqs, freqs):
                                            frequencies[ifreq]["frequency"] = freq
                                    elif "Red. masses --" in line:
                                        r_masses = map(float,
                                                       float_patt.findall(line))
                                        for ifreq, r_mass in zip(ifreqs, r_masses):
                                            frequencies[ifreq]["r_mass"] = r_mass
                                    elif "Frc consts  --" in line:
                                        f_consts = map(float,
                                                       float_patt.findall(line))
                                        for ifreq, f_const in zip(ifreqs, f_consts):
                                            frequencies[ifreq]["f_constant"] = f_const
                                    elif "IR Inten    --" in line:
                                        IR_intens = map(float,
                                                        float_patt.findall(line))
                                        for ifreq, intens in zip(ifreqs, IR_intens):
                                            frequencies[ifreq]["IR_intensity"] = intens
                                    else:
                                        syms = line.split()[:3]
                                        for ifreq, sym in zip(ifreqs, syms):
                                            frequencies[ifreq]["symmetry"] = sym
                                    line = f.readline()

                                #  read normal modes
                                line = f.readline()
                                while normal_mode_patt.search(line):
                                    values = list(map(float,
                                                      float_patt.findall(line)))
                                    for i, ifreq in zip(range(0, len(values), 3),
                                                        ifreqs):
                                        frequencies[ifreq]["mode"].extend(values[i:i+3])
                                    line = f.readline()

                            parse_freq = False
                            self.frequencies.append(frequencies)
                            frequencies = []

                        elif parse_hessian:
                            #  read Hessian matrix under "Force constants in Cartesian coordinates"
                            #  Hessian matrix is in the input  orientation framework
                            # WARNING : need #P in the route line
                            parse_hessian = False
                            ndf = 3 * len(input_structures[0])
                            self.hessian = np.zeros((ndf, ndf))
                            j_indices = range(5)
                            jndf = 0
                            while jndf < ndf:
                                for i in range(jndf, ndf):
                                    line = f.readline()
                                    vals = re.findall(r"\s*([+-]?\d+\.\d+[eEdD]?[+-]\d+)", line)
                                    vals = [float(val.replace("D", "E"))
                                            for val in vals]
                                    for jval, val in enumerate(vals):
                                        j = j_indices[jval]
                                        self.hessian[i, j] = val
                                        self.hessian[j, i] = val
                                jndf += len(vals)
                                line = f.readline()
                                j_indices = [j + 5 for j in j_indices]

                        elif parse_bond_order:
                            # parse Wiberg bond order
                            line = f.readline()
                            line = f.readline()
                            nat = len(input_structures[0])
                            matrix = list()
                            for iat in range(nat):
                                line = f.readline()
                                matrix.append([float(v) for v in line.split()[2:]])

                            self.bond_orders = dict()
                            for iat in range(nat):
                                for jat in range(iat + 1, nat):
                                    self.bond_orders[(iat, jat)] = matrix[iat][jat]
                            parse_bond_order = False

                        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 num_elec_patt.search(line):
                            m = num_elec_patt.search(line)
                            self.electrons = (int(m.group(1)), int(m.group(2)))
                        elif (not self.is_pcm) and pcm_patt.search(line):
                            self.is_pcm = True
                            self.pcm = {}
                        elif "freq" in route_lower and "opt" in route_lower 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):
                            standard_orientation = True
                            geom_orientation = "standard"
                            read_coord = True
                        elif input_orientation_patt.search(line):
                            geom_orientation = "input"
                            read_coord = True
                        elif "Optimization completed." in line:
                            line = f.readline()
                            if " -- Stationary point found." not in line:
                                warnings.warn("\n" + self.filename +
                                              ": Optimization complete but this is not a stationary point")
                            opt_structures.append(input_structures[-1])
                        elif not read_eigen and orbital_patt.search(line):
                            eigen_txt.append(line)
                            read_eigen = True
                        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
                            [f.readline() for i in range(3)]
                        elif mo_coeff_patt.search(line):
                            if "Alpha" in line:
                                self.is_spin = True
                            read_mo = True
                        elif hessian_patt.search(line):
                            parse_hessian = True
                        elif resume_patt.search(line):
                            resume = []
                            while not resume_end_patt.search(line):
                                resume.append(line)
                                line = f.readline()
                                #  security if \\@ not in one line !
                                if line == "\n":
                                    break
                            resume.append(line)
                            resume = "".join([r.strip() for r in resume])
                            self.resumes.append(resume)
                        elif bond_order_patt.search(line):
                            parse_bond_order = 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)
                                        dic = {int(m.group(1)):
                                               [m.group(2), float(m.group(3))]}
                                        mulliken_charges.update(dic)
                                read_mulliken = False
                                self.Mulliken_charges = mulliken_charges

            # store the structures. If symmetry is considered, the standard orientation
            # is used. Else the input orientation is used.
            if standard_orientation:
                self.structures = std_structures
                self.structures_input_orientation = input_structures
            else:
                self.structures = input_structures
                self.structures_input_orientation = input_structures
            # store optimized structure in input orientation
            self.opt_structures = opt_structures

            if not terminated:
                warnings.warn("\n" + self.filename +
                              ": Termination error or bad Gaussian output file !")

        def _check_pcm(self, line):
            energy_patt = re.compile(r"(Dispersion|Cavitation|Repulsion) energy"
                                     r"\s+\S+\s+=\s+(\S*)")
            total_patt = re.compile(r"with all non electrostatic terms\s+\S+\s+"
                                    r"=\s+(\S*)")
            parameter_patt = re.compile(r"(Eps|Numeral density|RSolv|Eps"
                                        r"\(inf[inity]*\))\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_multiplicity

            vin = {"route": self.route_parameters, "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(r"^\sSummary of the potential surface scan:")
            optscan_patt = re.compile(r"^\sSummary of Optimized Potential Surface Scan")
            coord_patt = re.compile(r"^\s*(\w+)((\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 coord_patt.match(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 not re.search(r"^\s+((\s*\d+)+)", 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(r"^\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 import pretty_plot

            plt = pretty_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) * Ha_to_eV 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), ... ]
            """

            transitions = list()

            # read in file
            with zopen(self.filename, "r") as f:
                line = f.readline()
                td = False
                while line != "":
                    if re.search(r"^\sExcitation energies and oscillator strengths:", line):
                        td = True

                    if td:
                        if re.search(r"^\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 xas. Transition are plotted
            as vertical lines and as a sum of normal functions with sigma with. The
            broadening is applied in energy and the xas 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, "xas": values}
                        where values are lists of abscissa (energies, lamba) and
                        the sum of gaussian functions (xas).
                A matplotlib plot.
            """
            from pymatgen.util.plotting import pretty_plot
            from scipy.stats import norm
            plt = pretty_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] * norm(eneval, trans[0], sigma)
            spectre /= spectre.max()
            plt.plot(lambdaval, spectre, "r-", label="spectre")

            data = {"energies": eneval, "lambda": lambdaval, "xas": 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, 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):
            """
            Create a new input object 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 charge is None:
                charge = self.charge

            if spin_multiplicity is None:
                spin_multiplicity = self.spin_multiplicity

            if not title:
                title = self.title

            if not functional:
                functional = self.functional

            if not basis_set:
                basis_set = self.basis_set

            if not route_parameters:
                route_parameters = self.route_parameters

            if not link0_parameters:
                link0_parameters = self.link0

            if not dieze_tag:
                dieze_tag = self.dieze_tag

            return 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)