pymatgen.io.lobster package

Subpackages

Submodules

pymatgen.io.lobster.inputs module

Module for reading LOBSTER input files. For more information on LOBSTER see www.cohp.de.

If you use this module, please cite: J. George, G. Petretto, A. Naik, M. Esters, A. J. Jackson, R. Nelson, R. Dronskowski, G.-M. Rignanese, G. Hautier, “Automated Bonding Analysis with Crystal Orbital Hamilton Populations”, ChemPlusChem 2022, e202200123, DOI: 10.1002/cplu.202200123.

class Lobsterin(settingsdict: dict)[source]

Bases: UserDict, MSONable

Handle and generate lobsterin files. Furthermore, it can also modify INCAR files for LOBSTER, generate KPOINTS files for fatband calculations in LOBSTER, and generate the standard primitive cells in a POSCAR file that are needed for the fatband calculations. There are also several standard lobsterin files that can be easily generated.

Reminder: lobsterin keywords are not case sensitive.

Parameters:

settingsdict – dict to initialize Lobsterin.

AVAILABLE_KEYWORDS: ClassVar[dict[str, str]] = {'autorotate': 'autoRotate', 'bandwisespilling': 'bandwiseSpilling', 'basisfunctions': 'basisfunctions', 'basisrotation': 'basisRotation', 'basisset': 'basisSet', 'bwdf': 'BWDF', 'bwdfcohp': 'BWDFCOHP', 'cobibetween': 'cobiBetween', 'cohpbetween': 'cohpbetween', 'cohpendenergy': 'COHPendEnergy', 'cohpgenerator': 'cohpGenerator', 'cohpstartenergy': 'COHPstartEnergy', 'cohpsteps': 'COHPSteps', 'createfatband': 'createFatband', 'customstoforatom': 'customSTOforAtom', 'densityofenergy': 'DensityOfEnergy', 'donotignoreexcessivebands': 'doNotIgnoreExcessiveBands', 'donotorthogonalizebasis': 'doNotOrthogonalizeBasis', 'donotuseabsolutespilling': 'doNotUseAbsoluteSpilling', 'ewaldsum': 'EwaldSum', 'forceenergyrange': 'forceEnergyRange', 'forcev1hmatrix': 'forceV1HMatrix', 'gaussiansmearingwidth': 'gaussianSmearingWidth', 'gridbufferforprinting': 'gridBufferForPrinting', 'griddensityforprinting': 'gridDensityForPrinting', 'kpointwisespilling': 'kpointwiseSpilling', 'kspacecohp': 'kSpaceCOHP', 'loadprojectionfromfile': 'loadProjectionFromFile', 'lsodos': 'LSODOS', 'molecule': 'molecule', 'nofftforvisualization': 'noFFTforVisualization', 'nomemorymappedfiles': 'noMemoryMappedFiles', 'onlyreadvasprun.xml': 'onlyReadVasprun.xml', 'printlcaorealspacewavefunction': 'printLCAORealSpaceWavefunction', 'printlmosonatoms': 'printLmosOnAtoms', 'printlmosonatomswriteatomicdensities': 'printLmosOnAtomswriteAtomicDensities', 'printmofeatomwise': 'printMofeAtomWise', 'printmofemoleculewise': 'printMofeMoleculeWise', 'printpawrealspacewavefunction': 'printPAWRealSpaceWavefunction', 'printtotalspilling': 'printTotalSpilling', 'realspacehamiltonian': 'realspaceHamiltonian', 'realspaceoverlap': 'realspaceOverlap', 'rmsp': 'RMSp', 'saveprojectiontofile': 'saveProjectionToFile', 'skipcar': 'skipCar', 'skipcobi': 'skipcobi', 'skipcohp': 'skipcohp', 'skipcoop': 'skipcoop', 'skipdos': 'skipdos', 'skipgrosspopulation': 'skipGrossPopulation', 'skipmadelungenergy': 'skipMadelungEnergy', 'skipmofe': 'skipMOFE', 'skipmolecularorbitals': 'skipMolecularOrbitals', 'skippaworthonormalitytest': 'skipPAWOrthonormalityTest', 'skippopulationanalysis': 'skipPopulationAnalysis', 'skipprojection': 'skipProjection', 'skipreorthonormalization': 'skipReOrthonormalization', 'usedecimalplaces': 'useDecimalPlaces', 'useoriginaltetrahedronmethod': 'useOriginalTetrahedronMethod', 'userecommendedbasisfunctions': 'userecommendedbasisfunctions', 'writeatomicorbitals': 'writeAtomicOrbitals', 'writebasisfunctions': 'writeBasisFunctions', 'writematricestofile': 'writeMatricesToFile'}[source]

BOOLEAN_KEYWORDS: ClassVar[dict[str, str]] = {'autorotate': 'autoRotate', 'bandwisespilling': 'bandwiseSpilling', 'bwdf': 'BWDF', 'bwdfcohp': 'BWDFCOHP', 'densityofenergy': 'DensityOfEnergy', 'donotignoreexcessivebands': 'doNotIgnoreExcessiveBands', 'donotorthogonalizebasis': 'doNotOrthogonalizeBasis', 'donotuseabsolutespilling': 'doNotUseAbsoluteSpilling', 'forceenergyrange': 'forceEnergyRange', 'forcev1hmatrix': 'forceV1HMatrix', 'kpointwisespilling': 'kpointwiseSpilling', 'loadprojectionfromfile': 'loadProjectionFromFile', 'lsodos': 'LSODOS', 'nofftforvisualization': 'noFFTforVisualization', 'nomemorymappedfiles': 'noMemoryMappedFiles', 'onlyreadvasprun.xml': 'onlyReadVasprun.xml', 'printlmosonatoms': 'printLmosOnAtoms', 'printmofeatomwise': 'printMofeAtomWise', 'printmofemoleculewise': 'printMofeMoleculeWise', 'printtotalspilling': 'printTotalSpilling', 'rmsp': 'RMSp', 'saveprojectiontofile': 'saveProjectionToFile', 'skipcar': 'skipCar', 'skipcobi': 'skipcobi', 'skipcohp': 'skipcohp', 'skipcoop': 'skipcoop', 'skipdos': 'skipdos', 'skipgrosspopulation': 'skipGrossPopulation', 'skipmadelungenergy': 'skipMadelungEnergy', 'skipmofe': 'skipMOFE', 'skipmolecularorbitals': 'skipMolecularOrbitals', 'skippaworthonormalitytest': 'skipPAWOrthonormalityTest', 'skippopulationanalysis': 'skipPopulationAnalysis', 'skipprojection': 'skipProjection', 'skipreorthonormalization': 'skipReOrthonormalization', 'useoriginaltetrahedronmethod': 'useOriginalTetrahedronMethod', 'userecommendedbasisfunctions': 'userecommendedbasisfunctions', 'writeatomicorbitals': 'writeAtomicOrbitals', 'writebasisfunctions': 'writeBasisFunctions', 'writematricestofile': 'writeMatricesToFile'}[source]

FLOAT_KEYWORDS: ClassVar[dict[str, str]] = {'basisrotation': 'basisRotation', 'cohpendenergy': 'COHPendEnergy', 'cohpstartenergy': 'COHPstartEnergy', 'cohpsteps': 'COHPSteps', 'gaussiansmearingwidth': 'gaussianSmearingWidth', 'gridbufferforprinting': 'gridBufferForPrinting', 'griddensityforprinting': 'gridDensityForPrinting', 'usedecimalplaces': 'useDecimalPlaces'}[source]

LIST_KEYWORDS: ClassVar[dict[str, str]] = {'basisfunctions': 'basisfunctions', 'cobibetween': 'cobiBetween', 'cohpbetween': 'cohpbetween', 'createfatband': 'createFatband', 'customstoforatom': 'customSTOforAtom', 'molecule': 'molecule', 'printlmosonatomswriteatomicdensities': 'printLmosOnAtomswriteAtomicDensities'}[source]

STRING_KEYWORDS: ClassVar[dict[str, str]] = {'basisset': 'basisSet', 'cohpgenerator': 'cohpGenerator', 'ewaldsum': 'EwaldSum', 'kspacecohp': 'kSpaceCOHP', 'printlcaorealspacewavefunction': 'printLCAORealSpaceWavefunction', 'printpawrealspacewavefunction': 'printPAWRealSpaceWavefunction', 'realspacehamiltonian': 'realspaceHamiltonian', 'realspaceoverlap': 'realspaceOverlap'}[source]

as_dict() → dict[source]

MSONable dict.

diff(other: Self) → dict[str, dict[str, Any]][source]

Compare two Lobsterin and find which parameters are the same. Similar to the diff method of Incar.

Parameters:

other (Lobsterin) – Lobsterin object to compare to.

Returns:

{“Same”: same_params, “Different”: diff_params}

Return type:

dict

classmethod from_dict(dct: dict) → Self[source]

Parameters:

dct (dict) – Dict representation.

Returns:

Lobsterin

classmethod from_file(lobsterin: PathLike) → Self[source]

Create Lobsterin from lobsterin file.

Parameters:

lobsterin (PathLike) – path to lobsterin.

Returns:

Lobsterin object

static get_all_possible_basis_functions(structure: Structure | IStructure, potcar_symbols: list[str], address_basis_file_min: PathLike | None = None, address_basis_file_max: PathLike | None = None) → list[dict][source]

Parameters:

• structure – Structure object

• potcar_symbols – list of the potcar symbols

• address_basis_file_min – path to file with the minimum required basis by the POTCAR

• address_basis_file_max – path to file with the largest possible basis of the POTCAR.

Returns:

Can be used to create new Lobsterin objects in

standard_calculations_from_vasp_files as dict_for_basis

Return type:

list[dict]

static get_basis(structure: Structure | IStructure, potcar_symbols: list[str], address_basis_file: PathLike | None = None) → list[str][source]

Get the basis functions from given potcar_symbols, e.g., [“Fe_pv”, “Si”].

Parameters:

• structure (Structure) – Structure object

• potcar_symbols – list of potcar symbols

• address_basis_file (PathLike) – path to the basis file

Returns:

basis

classmethod standard_calculations_from_vasp_files(POSCAR_input: PathLike = 'POSCAR', INCAR_input: PathLike = 'INCAR', POTCAR_input: PathLike | None = None, Vasprun_output: PathLike = 'vasprun.xml', dict_for_basis: dict | None = None, option: str = 'standard') → Self[source]

Generate lobsterin with standard settings.

Parameters:

• POSCAR_input (PathLike) – path to POSCAR

• INCAR_input (PathLike) – path to INCAR

• POTCAR_input (PathLike) – path to POTCAR

• Vasprun_output (PathLike) – path to vasprun.xml

• dict_for_basis (dict) – can be provided: it should look the following: dict_for_basis={“Fe”:’3p 3d 4s 4f’, “C”: ‘2s 2p’} and will overwrite all settings from POTCAR_input

• option (str) – ‘standard’ will start a normal LOBSTER run where COHPs, COOPs, DOS, CHARGE etc. will be calculated ‘standard_with_energy_range_from_vasprun’ will start a normal LOBSTER run for entire energy range of VASP static run. vasprun.xml file needs to be in current directory. ‘standard_from_projection’ will start a normal LOBSTER run from a projection ‘standard_with_fatband’ will do a fatband calculation, run over all orbitals ‘onlyprojection’ will only do a projection ‘onlydos’ will only calculate a projected dos ‘onlycohp’ will only calculate cohp ‘onlycoop’ will only calculate coop ‘onlycohpcoop’ will only calculate cohp and coop

Returns:

Lobsterin with standard settings

write_INCAR(incar_input: PathLike = 'INCAR', incar_output: PathLike = 'INCAR.lobster', poscar_input: PathLike = 'POSCAR', isym: Literal[-1, 0] = 0, further_settings: dict | None = None) → None[source]

Write INCAR file. Will only make the run static, insert NBANDS, set ISYM=0, LWAVE=True and you have to check for the rest.

Parameters:

• incar_input (PathLike) – path to input INCAR

• incar_output (PathLike) – path to output INCAR

• poscar_input (PathLike) – path to input POSCAR

• isym (-1 | 0) – ISYM value.

• further_settings (dict) – A dict can be used to include further settings, e.g. {“ISMEAR”:-5}

static write_KPOINTS(POSCAR_input: PathLike = 'POSCAR', KPOINTS_output: PathLike = 'KPOINTS.lobster', reciprocal_density: int = 100, isym: Literal[-1, 0] = 0, from_grid: bool = False, input_grid: tuple[int, int, int] = (5, 5, 5), line_mode: bool = True, kpoints_line_density: int = 20, symprec: float = 0.01) → None[source]

Write a gamma-centered KPOINTS file for LOBSTER.

Parameters:

• POSCAR_input (PathLike) – path to POSCAR

• KPOINTS_output (PathLike) – path to output KPOINTS

• reciprocal_density (int) – Grid density

• isym (-1 | 0) – ISYM value.

• from_grid (bool) – If True KPOINTS will be generated with the help of a grid given in input_grid. Otherwise, they will be generated from the reciprocal_density

• input_grid (tuple) – grid to generate the KPOINTS file

• line_mode (bool) – If True, band structure will be generated

• kpoints_line_density (int) – density of the lines in the band structure

• symprec (float) – precision to determine symmetry

static write_POSCAR_with_standard_primitive(POSCAR_input: PathLike = 'POSCAR', POSCAR_output: PathLike = 'POSCAR.lobster', symprec: float = 0.01) → None[source]

Write a POSCAR with the standard primitive cell. This is needed to arrive at the correct kpath.

Parameters:

• POSCAR_input (PathLike) – Input POSCAR file

• POSCAR_output (PathLike) – Output POSCAR file

• symprec (float) – precision to find symmetry

write_lobsterin(path: PathLike = 'lobsterin', overwritedict: dict | None = None) → None[source]

Write a lobsterin file, and recover keys to Camel case.

Parameters:

• path (str) – filename of the output lobsterin file

• overwritedict (dict) – dict that can be used to update lobsterin, e.g. {“skipdos”: True}

get_all_possible_basis_combinations(min_basis: list, max_basis: list) → list[list[str]][source]

Get all possible basis combinations.

Parameters:

• min_basis – list of basis entries: e.g., [“Si 3p 3s”]

• max_basis – list of basis entries: e.g., [“Si 3p 3s”].

Returns:

all possible combinations of basis functions, e.g. [[“Si 3p 3s”]]

Return type:

list[list[str]]

pymatgen.io.lobster.lobsterenv module

Deprecated class for analyzing NearNeighbors using ICOHPs/ICOOPs/ICOBIs.

class LobsterNeighbors(*args, **kwargs)[source]

Bases: object

Deprecated LobsterNeighbors class for analyzing NearNeighbor interactions using ICOHPs/ICOOPs/ICOBIs.

pymatgen.io.lobster.outputs module

Module for reading Lobster output files. For more information on LOBSTER see www.cohp.de.

If you use this module, please cite: J. George, G. Petretto, A. Naik, M. Esters, A. J. Jackson, R. Nelson, R. Dronskowski, G.-M. Rignanese, G. Hautier, “Automated Bonding Analysis with Crystal Orbital Hamilton Populations”, ChemPlusChem 2022, e202200123, DOI: 10.1002/cplu.202200123.

class Bandoverlaps(filename: PathLike = 'bandOverlaps.lobster', band_overlaps_dict: dict[Spin, dict] | None = None, max_deviation: list[float] | None = None)[source]

Bases: MSONable

Read bandOverlaps.lobster files, which are not created during every LOBSTER run.

band_overlaps_dict[source]

A dictionary containing the band overlap data of the form: {spin: {“kpoint as string”: {“maxDeviation”: float that describes the max deviation, “matrix”: 2D array of the size number of bands times number of bands including the overlap matrices with}}}.

Type:

dict[Spin, Dict[str, Dict[str, Union[float, NDArray]]]]

max_deviation[source]

The maximal deviation for each problematic kpoint.

Type:

list[float]

Parameters:

• filename (PathLike) – The “bandOverlaps.lobster” file.

• band_overlaps_dict –

  The band overlap data of the form: {

  spin: {

  “k_points” : list of k-point array, “max_deviations”: list of max deviations associated with each k-point, “matrices”: list of the overlap matrices associated with each k-point,

  }

  }.

• max_deviation (list[float]) – The maximal deviations for each problematic k-point.

property bandoverlapsdict: dict[source]

has_good_quality_check_occupied_bands(number_occ_bands_spin_up: int, number_occ_bands_spin_down: int | None = None, spin_polarized: bool = False, limit_deviation: float = 0.1) → bool[source]

Check if the deviation from the ideal bandoverlap of all occupied bands is smaller or equal to limit_deviation.

Parameters:

• number_occ_bands_spin_up (int) – Number of occupied bands of spin up.

• number_occ_bands_spin_down (int) – Number of occupied bands of spin down.

• spin_polarized (bool) – Whether this is a spin polarized calculation.

• limit_deviation (float) – Upper limit of the maxDeviation.

Returns:

True if the quality of the projection is good.

Return type:

bool

has_good_quality_maxDeviation(limit_maxDeviation: float = 0.1) → bool[source]

Check if the maxDeviation from the ideal bandoverlap is smaller or equal to a limit.

Parameters:

limit_maxDeviation (float) – Upper Limit of the maxDeviation.

Returns:

Whether the ideal bandoverlap is smaller or equal to the limit.

Return type:

bool

class Bwdf(filename: PathLike = 'BWDF.lobster', centers: NDArray | None = None, bwdf: dict[Spin, NDArray] | None = None, bin_width: float | None = None)[source]

Bases: MSONable

Read BWDF.lobster/BWDFCOHP.lobster file generated by LOBSTER.

centers[source]

Bond length centers for the distribution.

Type:

NDArray

bwdf[source]

Bond weighted distribution function.

Type:

dict[Spin, NDArray]

bin_width[source]

Bin width used for computing the distribution by LOBSTER.

Type:

float

Parameters:

• filename (PathLike) – The “BWDF.lobster” file. Can also read BWDFCOHP.lobster.

• centers (NDArray) – Bond length centers for the distribution.

• bwdf (dict[Spin, NDArray]) – Bond weighted distribution function.

• bin_width (float) – Bin width used for computing the distribution by LOBSTER.

class Charge(filename: PathLike = 'CHARGE.lobster', is_lcfo: bool = False, num_atoms: int | None = None, atomlist: list[str] | None = None, types: list[str] | None = None, mulliken: list[float] | None = None, loewdin: list[float] | None = None)[source]

Bases: MSONable

Read CHARGE.lobster/ CHARGE.LCFO.lobster files generated by LOBSTER.

atomlist[source]

List of atoms in CHARGE.lobster.

Type:

list[str]

is_lcfo[source]

Whether the CHARGE file is from LCFO analysis. Default is False.

Type:

bool

types[source]

List of types of atoms in CHARGE.lobster.

Type:

list[str]

mulliken[source]

List of Mulliken charges of atoms in CHARGE.lobster.

Type:

list[float]

loewdin[source]

List of Loewdin charges of atoms in CHARGE.Loewdin.

Type:

list[float]

num_atoms[source]

Number of atoms in CHARGE.lobster.

Type:

int

Parameters:

• filename (PathLike) – The CHARGE file, typically “CHARGE.lobster”.

• is_lcfo (bool) – Whether the CHARGE file is from LCFO analysis. Default is False.

• num_atoms (int) – Number of atoms in the structure.

• atomlist (list[str]) – Atoms in the structure.

• types (list[str]) – Unique species in the structure.

• mulliken (list[float]) – Mulliken charges.

• loewdin (list[float]) – Loewdin charges.

property Loewdin: list[float][source]

property Mulliken: list[float][source]

get_structure_with_charges(structure_filename: PathLike) → Structure[source]

Get a Structure with Mulliken and Loewdin charges as site properties

Parameters:

structure_filename (PathLike) – The POSCAR file.

Returns:

Structure Object with Mulliken and Loewdin charges as site properties.

class Cohpcar(are_coops: bool = False, are_cobis: bool = False, are_multi_center_cobis: bool = False, is_lcfo: bool = False, filename: PathLike | None = None)[source]

Bases: object

Read COXXCAR.lobster/COXXCAR.LCFO.lobster files generated by LOBSTER.

cohp_data[source]

The COHP data of the form: {bond: {“COHP”: {Spin.up: cohps, Spin.down:cohps},

“ICOHP”: {Spin.up: icohps, Spin.down: icohps}, “length”: bond length, “sites”: sites corresponding to the bond}

Also contains an entry for the average, which does not have a “length” key.

Type:

dict[str, Dict[str, Any]]

efermi[source]

The Fermi level in eV.

Type:

float

energies[source]

Sequence of energies in eV. Note that LOBSTER shifts the energies so that the Fermi level is at zero.

Type:

Sequence[float]

is_spin_polarized[source]

True if the calculation is spin polarized.

Type:

bool

orb_res_cohp[source]

The orbital-resolved COHPs of the form: orb_res_cohp[label] = {bond_data[“orb_label”]: {

“COHP”: {Spin.up: cohps, Spin.down:cohps}, “ICOHP”: {Spin.up: icohps, Spin.down: icohps}, “orbitals”: orbitals, “length”: bond lengths, “sites”: sites corresponding to the bond},

}

Type:

dict[str, Dict[str, Dict[str, Any]]]

Parameters:

• are_coops (bool) – Whether the file includes COOPs (True) or COHPs (False). Default is False.

• are_cobis (bool) – Whether the file is COBIs (True) or COHPs (False). Default is False.

• are_multi_center_cobis (bool) – Whether the file include multi-center COBIs (True) or two-center COBIs (False). Default is False.

• is_lcfo (bool) – Whether the COXXCAR file is from LCFO analysis.

• filename (PathLike) – The COHPCAR file. If it is None, the default file name will be chosen, depending on the value of are_coops.

class Doscar(doscar: PathLike = 'DOSCAR.lobster', is_lcfo: bool = False, structure_file: PathLike | None = 'POSCAR', structure: IStructure | Structure | None = None)[source]

Bases: object

Store LOBSTER’s projected DOS and local projected DOS. The beforehand quantum-chemical calculation was performed with VASP.

completedos[source]

LobsterCompleteDos Object.

Type:

LobsterCompleteDos

pdos[source]

List of Dict including NumPy arrays with pdos. Access as pdos[atomindex][‘orbitalstring’][‘Spin.up/Spin.down’].

Type:

list

tdos[source]

Dos Object of the total density of states.

Type:

Dos

energies[source]

Numpy array of the energies at which the DOS was calculated (in eV, relative to Efermi).

Type:

NDArray

tdensities[source]

tdensities[Spin.up]: NumPy array of the total density of states for the Spin.up contribution at each of the energies. tdensities[Spin.down]: NumPy array of the total density of states for the Spin.down contribution at each of the energies. If is_spin_polarized=False, tdensities[Spin.up]: NumPy array of the total density of states.

Type:

dict

itdensities[source]

itdensities[Spin.up]: NumPy array of the total density of states for the Spin.up contribution at each of the energies. itdensities[Spin.down]: NumPy array of the total density of states for the Spin.down contribution at each of the energies. If is_spin_polarized=False, itdensities[Spin.up]: NumPy array of the total density of states.

Type:

dict

is_spin_polarized[source]

Whether the system is spin polarized.

Type:

bool

Parameters:

• doscar (PathLike) – The DOSCAR file, typically “DOSCAR.lobster”.

• is_lcfo (bool) – Whether the DOSCAR file is from LCFO analysis.

• structure_file (PathLike) – For VASP, this is typically “POSCAR”.

• structure (Structure) – Instead of a structure file (preferred), the Structure can be given directly.

property completedos: LobsterCompleteDos[source]

LobsterCompleteDos.

property energies: NDArray[source]

Energies.

property is_spin_polarized: bool[source]

Whether run is spin polarized.

property itdensities: dict[Spin, NDArray][source]

Integrated total DOS as a np.array.

property pdos: list[dict][source]

Projected DOS (PDOS).

property tdensities: dict[Spin, NDArray][source]

Total DOS as a np.array.

property tdos: Dos[source]

Total DOS (TDOS).

class Fatband(filenames: PathLike | list[PathLike] = '.', kpoints_file: PathLike = 'KPOINTS', vasprun_file: PathLike | None = 'vasprun.xml', structure: Structure | IStructure | None = None, efermi: float | None = None)[source]

Bases: object

Read FATBAND_x_y.lobster files.

efermi[source]

Fermi level read from vasprun.xml.

Type:

float

eigenvals[source]

Eigenvalues as a dictionary of NumPy arrays of shape (nbands, nkpoints). The first index of the array refers to the band and the second to the index of the kpoint. The kpoints are ordered according to the order of the kpoints_array attribute. If the band structure is not spin polarized, we only store one data set under Spin.up.

Type:

dict[Spin, NDArray]

is_spin_polarized[source]

Whether this was a spin-polarized calculation.

Type:

bool

kpoints_array[source]

List of kpoints as NumPy arrays, in frac_coords of the given lattice by default.

Type:

list[NDArray]

label_dict[source]

Dictionary that links a kpoint (in frac coords or Cartesian coordinates depending on the coords attribute) to a label.

Type:

dict[str, Union[str, NDArray]]

lattice[source]

Lattice object of reciprocal lattice as read from vasprun.xml.

Type:

Lattice

nbands[source]

Number of bands used in the calculation.

Type:

int

p_eigenvals[source]

Dictionary of orbital projections as {spin: array of dict}. The indices of the array are [band_index, kpoint_index]. The dict is then built the following way: {“string of element”: “string of orbital as read in from FATBAND file”}. If the band structure is not spin polarized, we only store one data set under Spin.up.

Type:

dict[Spin, NDArray]

structure[source]

Structure object.

Type:

Structure

Parameters:

• filenames (PathLike | list[PathLike]) – File names or path to a folder from which all “FATBAND_*” files will be read.

• kpoints_file (PathLike) – KPOINTS file for bandstructure calculation, typically “KPOINTS”.

• vasprun_file (PathLike) – Corresponding vasprun.xml file. Instead, the Fermi level from the DFT run can be provided. Then, this should be set to None.

• structure (Structure) – Structure object.

• efermi (float) – Fermi level in eV.

get_bandstructure() → LobsterBandStructureSymmLine[source]

Get a LobsterBandStructureSymmLine object which can be plotted with a normal BSPlotter.

class Grosspop(filename: PathLike = 'GROSSPOP.lobster', is_lcfo: bool = False, list_dict_grosspop: list[dict] | None = None)[source]

Bases: MSONable

Read GROSSPOP.lobster/ GROSSPOP.LCFO.lobster files.

list_dict_grosspop[source]

List of dictionaries including all information about the grosspopulations. Each dictionary contains the following keys: - ‘element’: The element symbol of the atom. - ‘Mulliken GP’: A dictionary of Mulliken gross populations, where the keys are the orbital labels and the

values are the corresponding gross populations as strings.

• ‘Loewdin GP’: A dictionary of Loewdin gross populations, where the keys are the orbital labels and the

  values are the corresponding gross populations as strings.

The 0th entry of the list refers to the first atom in GROSSPOP.lobster and so on.

Type:

list[dict[str, str| dict[str, str]]]

Parameters:

• filename (PathLike) – The “GROSSPOP.lobster” file.

• is_lcfo (bool) – Whether the GROSSPOP file is in LCFO format.

• list_dict_grosspop (list[dict]) – All information about the gross populations.

get_structure_with_total_grosspop(structure_filename: PathLike) → Structure[source]

Get a Structure with Mulliken and Loewdin total grosspopulations as site properties.

Parameters:

structure_filename (PathLike) – The POSCAR file.

Returns:

Structure Object with Mulliken and Loewdin total grosspopulations as site properties.

class Icohplist(is_lcfo: bool = False, are_coops: bool = False, are_cobis: bool = False, filename: PathLike | None = None, is_spin_polarized: bool = False, orbitalwise: bool = False, icohpcollection: IcohpCollection | None = None)[source]

Bases: MSONable

Read ICOXXLIST/ICOXXLIST.LCFO.lobster files generated by LOBSTER.

are_coops[source]

Whether the file includes COOPs (True) or COHPs (False).

Type:

bool

is_lcfo[source]

Whether the ICOXXLIST file is from LCFO analysis.

Type:

bool

is_spin_polarized[source]

Whether the calculation is spin polarized.

Type:

bool

Icohplist[source]

The listfile data of the form: {

bond: {

“length”: Bond length, “number_of_bonds”: Number of bonds, “icohp”: {Spin.up: ICOHP(Ef)_up, Spin.down: …}, }

}

Type:

dict[str, Dict[str, Union[float, int, Dict[Spin, float]]]]

IcohpCollection[source]

IcohpCollection Object.

Type:

IcohpCollection

Parameters:

• is_lcfo (bool) – Whether the ICOHPLIST file is from LCFO analysis.

• are_coops (bool) – Whether the file includes COOPs (True) or COHPs (False). Default is False.

• are_cobis (bool) – Whether the file is COBIs (True) or COHPs (False). Default is False.

• filename (PathLike) – The ICOHPLIST file. If it is None, the default file name will be chosen, depending on the value of are_coops

• is_spin_polarized (bool) – Whether the calculation is spin polarized.

• orbitalwise (bool) – Whether the calculation is orbitalwise.

• icohpcollection (IcohpCollection) – IcohpCollection Object.

property icohpcollection: IcohpCollection | None[source]

The IcohpCollection object.

property icohplist: dict[Any, dict[str, Any]][source]

The ICOHP list compatible with older version of this class.

class LobsterMatrices(e_fermi: float | None = None, filename: PathLike = 'hamiltonMatrices.lobster')[source]

Bases: object

Read Matrices file generated by LOBSTER (e.g. hamiltonMatrices.lobster).

If filename == "hamiltonMatrices.lobster"

onsite_energies (list[NDArray]): Real parts of onsite energies from the

matrices each k-point.

average_onsite_energies (dict): Average onsite elements energies for

all k-points with keys as basis used in the LOBSTER computation (uses only real part of matrix).

hamilton_matrices (dict[Spin, NDArray]): The complex Hamilton matrix at each

k-point with k-point and spin as keys.

If filename == "coefficientMatrices.lobster"

onsite_coefficients (list[NDArray]): Real parts of onsite coefficients

from the matrices each k-point.

average_onsite_coefficient (dict): Average onsite elements coefficients

for all k-points with keys as basis used in the LOBSTER computation (uses only real part of matrix).

coefficient_matrices (dict[Spin, NDArray]): The coefficients matrix

at each k-point with k-point and spin as keys.

If filename == "transferMatrices.lobster"

onsite_transfer (list[NDArray]): Real parts of onsite transfer

coefficients from the matrices at each k-point.

average_onsite_transfer (dict): Average onsite elements transfer

coefficients for all k-points with keys as basis used in the LOBSTER computation (uses only real part of matrix).

transfer_matrices (dict[Spin, NDArray]): The coefficients matrix at

each k-point with k-point and spin as keys.

If filename == "overlapMatrices.lobster"

onsite_overlaps (list[NDArray]): Real parts of onsite overlaps

from the matrices each k-point.

average_onsite_overlaps (dict): Average onsite elements overlaps

for all k-points with keys as basis used in the LOBSTER computation (uses only real part of matrix).

overlap_matrices (dict[NDArray]): The overlap matrix at

each k-point with k-point as keys.

Parameters:

• e_fermi (float) – Fermi level in eV for the structure only. Relevant if input file contains Hamilton matrices data.

• filename (PathLike) – The hamiltonMatrices file, typically “hamiltonMatrices.lobster”.

class Lobsterout(filename: PathLike | None, **kwargs)[source]

Bases: MSONable

Read the lobsterout and evaluate the spilling, save the basis, save warnings, save info.

basis_functions[source]

Basis functions that were used in lobster run as strings.

Type:

list[str]

basis_type[source]

Basis types that were used in lobster run as strings.

Type:

list[str]

charge_spilling[source]

Charge spilling (first entry: result for spin 1, second entry: result for spin 2 or not present).

Type:

list[float]

dft_program[source]

The DFT program used for the calculation of the wave function.

Type:

str

elements[source]

Elements that were present in LOBSTER calculation.

Type:

list[str]

has_charge[source]

Whether CHARGE.lobster is present.

Type:

bool

has_cohpcar[source]

Whether COHPCAR.lobster and ICOHPLIST.lobster are present.

Type:

bool

has_madelung[source]

Whether SitePotentials.lobster and MadelungEnergies.lobster are present.

Type:

bool

has_coopcar[source]

Whether COOPCAR.lobster and ICOOPLIST.lobster are present.

Type:

bool

has_cobicar[source]

Whether COBICAR.lobster and ICOBILIST.lobster are present.

Type:

bool

has_doscar[source]

Whether DOSCAR.lobster is present.

Type:

bool

has_doscar_lso[source]

Whether DOSCAR.LSO.lobster is present.

Type:

bool

has_projection[source]

Whether projectionData.lobster is present.

Type:

bool

has_bandoverlaps[source]

Whether bandOverlaps.lobster is present.

Type:

bool

has_density_of_energies[source]

Whether DensityOfEnergy.lobster is present.

Type:

bool

has_fatbands[source]

Whether fatband calculation was performed.

Type:

bool

has_grosspopulation[source]

Whether GROSSPOP.lobster is present.

Type:

bool

has_polarization[source]

Whether POLARIZATION.lobster is present.

Type:

bool

info_lines[source]

Additional information on the run.

Type:

str

info_orthonormalization[source]

Information on orthonormalization.

Type:

str

is_restart_from_projection[source]

Whether that calculation was restarted from an existing projection file.

Type:

bool

lobster_version[source]

The LOBSTER version.

Type:

str

number_of_spins[source]

The number of spins.

Type:

int

number_of_threads[source]

How many threads were used.

Type:

int

timing[source]

Dict with infos on timing.

Type:

dict[str, float]

total_spilling[source]

The total spilling for spin channel 1 (and spin channel 2).

Type:

list[float]

warning_lines[source]

String with all warnings.

Type:

str

Parameters:

• filename (PathLike) – The lobsterout file.

• **kwargs – dict to initialize Lobsterout instance

as_dict() → dict[str, Any][source]

MSONable dict.

get_doc() → dict[str, Any][source]

Get a dict with all information stored in lobsterout.