pymatgen.io.nwchem module

This module implements input and output processing from Nwchem.

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

NwOutput will read new kinds of data:

1. normal hessian matrix. [“hessian”]

2. projected hessian matrix. [“projected_hessian”]

3. normal frequencies. [“normal_frequencies”]

For backward compatibility, the key for accessing the projected frequencies is still ‘frequencies’.

2015/10/12 - Xin Chen

NwOutput will read new kinds of data:

1. forces. [“forces”]

class NwInput(mol, tasks, directives=None, geometry_options=('units', 'angstroms'), symmetry_options=None, memory_options=None)

Bases: MSONable

An object representing a Nwchem input file, which is essentially a list of tasks on a particular molecule.

Parameters:

• mol – Input molecule. If molecule is a single string, it is used as a direct input to the geometry section of the Gaussian input file.

• tasks – List of NwTasks.

• directives – List of root level directives as tuple. E.g., [(“start”, “water”), (“print”, “high”)]

• geometry_options – Additional list of options to be supplied to the geometry. E.g., [“units”, “angstroms”, “noautoz”]. Defaults to (“units”, “angstroms”).

• symmetry_options – Addition list of option to be supplied to the symmetry. E.g. [“c1”] to turn off the symmetry

• memory_options – Memory controlling options. str. E.g “total 1000 mb stack 400 mb”

as_dict()

Returns: MSONable dict

classmethod from_dict(d)

Parameters:

d (dict) – Dict representation

Returns:

NwInput

classmethod from_file(filename)

Read an NwInput from a file. Currently tested to work with files generated from this class itself.

Parameters:

filename – Filename to parse.

Returns:

NwInput object

classmethod from_string(string_input)

Read an NwInput from a string. Currently tested to work with files generated from this class itself.

Parameters:

string_input – string_input to parse.

Returns:

NwInput object

property molecule

Returns molecule associated with this GaussianInput.

write_file(filename)

Parameters:

filename (str) – Filename

exception NwInputError

Bases: Exception

Error class for NwInput.

class NwOutput(filename)

Bases: object

A Nwchem output file parser. Very basic for now - supports only dft and only parses energies and geometries. Please note that Nwchem typically outputs energies in either au or kJ/mol. All energies are converted to eV in the parser.

Parameters:

filename – Filename to read.

get_excitation_spectrum(width=0.1, npoints=2000)

Generate an excitation spectra from the singlet roots of TDDFT calculations.

Parameters:

• width (float) – Width for Gaussian smearing.

• npoints (int) – Number of energy points. More points => smoother curve.

Returns:

(ExcitationSpectrum) which can be plotted using

pymatgen.vis.plotters.SpectrumPlotter.

parse_tddft()

Parses TDDFT roots. Adapted from nw_spectrum.py script.

Returns:

{

“singlet”: [

{

“energy”: float, “osc_strength: float

}

], “triplet”: [

{

“energy”: float

}

]

}

class NwTask(charge, spin_multiplicity, basis_set, basis_set_option='cartesian', title=None, theory='dft', operation='optimize', theory_directives=None, alternate_directives=None)

Bases: MSONable

Base task for Nwchem.

Very flexible arguments to support many types of potential setups. Users should use more friendly static methods unless they need the flexibility.

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.

• spin_multiplicity – Spin multiplicity of molecule. Defaults to None, which means that the spin multiplicity is set to 1 if the molecule has no unpaired electrons and to 2 if there are unpaired electrons.

• basis_set – The basis set used for the task as a dict. E.g., {“C”: “6-311++G**”, “H”: “6-31++G**”}.

• basis_set_option – cartesian (default) | spherical,

• title – Title for the task. Defaults to None, which means a title based on the theory and operation of the task is autogenerated.

• theory – The theory used for the task. Defaults to “dft”.

• operation – The operation for the task. Defaults to “optimize”.

• theory_directives – A dict of theory directives. For example, if you are running dft calculations, you may specify the exchange correlation functional using {“xc”: “b3lyp”}.

• alternate_directives – A dict of alternate directives. For example, to perform cosmo calculations and dielectric constant of 78, you’d supply {‘cosmo’: {“dielectric”: 78}}.

as_dict()

Returns: MSONable dict.

classmethod dft_task(mol, xc='b3lyp', **kwargs)

A class method for quickly creating DFT tasks with optional cosmo parameter .

Parameters:

• mol – Input molecule

• xc – Exchange correlation to use.

• kwargs – Any of the other kwargs supported by NwTask. Note the theory is always “dft” for a dft task.

classmethod esp_task(mol, **kwargs)

A class method for quickly creating ESP tasks with RESP charge fitting.

Parameters:

• mol – Input molecule

• kwargs – Any of the other kwargs supported by NwTask. Note the theory is always “dft” for a dft task.

classmethod from_dict(d)

Parameters:

d (dict) – Dict representation

Returns:

NwTask

classmethod from_molecule(mol, theory, charge=None, spin_multiplicity=None, basis_set='6-31g', basis_set_option='cartesian', title=None, operation='optimize', theory_directives=None, alternate_directives=None)

Very flexible arguments to support many types of potential setups. Users should use more friendly static methods unless they need the flexibility.

Parameters:

• mol – Input molecule

• charge – Charge of the molecule. If None, charge on molecule is used. Defaults to None. This allows the input file to be set a charge independently from the molecule itself.

• spin_multiplicity – Spin multiplicity of molecule. Defaults to None, which means that the spin multiplicity is set to 1 if the molecule has no unpaired electrons and to 2 if there are unpaired electrons.

• basis_set – The basis set to be used as string or a dict. E.g., {“C”: “6-311++G**”, “H”: “6-31++G**”} or “6-31G”. If string, same basis set is used for all elements.

• basis_set_option – cartesian (default) | spherical,

• title – Title for the task. Defaults to None, which means a title based on the theory and operation of the task is autogenerated.

• theory – The theory used for the task. Defaults to “dft”.

• operation – The operation for the task. Defaults to “optimize”.

• theory_directives – A dict of theory directives. For example, if you are running dft calculations, you may specify the exchange correlation functional using {“xc”: “b3lyp”}.

• alternate_directives – A dict of alternate directives. For example, to perform cosmo calculations with DFT, you’d supply {‘cosmo’: “cosmo”}.

operations = {'': 'dummy', 'dynamics': 'Perform classical molecular dynamics.', 'energy': 'Evaluate the single point energy.', 'freq': 'Same as frequencies.', 'frequencies': 'Compute second derivatives and print out an analysis of molecular vibrations.', 'gradient': 'Evaluate the derivative of the energy with respect to nuclear coordinates.', 'hessian': 'Compute second derivatives.', 'optimize': 'Minimize the energy by varying the molecular structure.', 'property': 'Calculate the properties for the wave function.', 'saddle': 'Conduct a search for a transition state (or saddle point).', 'thermodynamics': 'Perform multi-configuration thermodynamic integration using classical MD.', 'vscf': 'Compute anharmonic contributions to the vibrational modes.'}

theories = {'band': 'Pseudopotential plane-wave DFT for solids using NWPW', 'ccsd': 'Coupled-cluster single and double excitations', 'ccsd(t)': 'Coupled-cluster linearized triples approximation', 'ccsd+t(ccsd)': 'Fourth order triples contribution', 'dft': 'DFT', 'direct_mp2': 'MP2 using a full-direct algorithm', 'esp': 'ESP', 'g3gn': 'some description', 'mcscf': 'Multiconfiguration SCF', 'md': 'Classical molecular dynamics simulation', 'mp2': 'MP2 using a semi-direct algorithm', 'pspw': 'Pseudopotential plane-wave DFT for molecules and insulating solids using NWPW', 'rimp2': 'MP2 using the RI approximation', 'scf': 'Hartree-Fock', 'selci': 'Selected CI with perturbation correction', 'sodft': 'Spin-Orbit DFT', 'tce': 'Tensor Contraction Engine', 'tddft': 'Time Dependent DFT'}