Python API#

Python API of the tblite project

Note

The documentation of the ASE integration can be found in Usage in ASE.

Library interface#

Definition of the basic interface to library for most further integration in other Python frameworks. The classes defined here allow a more Pythonic usage of the library in actual workflows than the low-level access provided in the CFFI generated wrappers.

Structure#

class tblite.interface.Structure(numbers: numpy.ndarray, positions: numpy.ndarray, charge: Optional[float] = None, uhf: Optional[int] = None, lattice: Optional[numpy.ndarray] = None, periodic: Optional[numpy.ndarray] = None)[source]#

Represents a wrapped structure object in tblite. The molecular structure data object has a fixed number of atoms and immutable atomic identifiers.

Example

>>> from tblite.interface import Structure
>>> import numpy as np
>>> mol = Structure(
...     positions=np.array([
...         [+0.00000000000000, +0.00000000000000, -0.73578586109551],
...         [+1.44183152868459, +0.00000000000000, +0.36789293054775],
...         [-1.44183152868459, +0.00000000000000, +0.36789293054775],
...     ]),
...     numbers = np.array([8, 1, 1]),
... )
...
>>> len(mol)
3
Raises:

ValueError – on invalid input, like incorrect shape / type of the passed arrays

update(positions: Optional[numpy.ndarray] = None, lattice: Optional[numpy.ndarray] = None, charge: Optional[float] = None, uhf: Optional[int] = None) → None[source]#

Update coordinates and lattice parameters, both provided in atomic units (Bohr). The lattice update is optional also for periodic structures.

Generally, only the cartesian coordinates and the lattice parameters can be updated, every other modification, regarding total charge, total spin, boundary condition, atomic types or number of atoms requires the complete reconstruction of the object.

Raises:

ValueError – on invalid input, like incorrect shape / type of the passed arrays

Calculator#

class tblite.interface.Calculator(method: str, numbers: numpy.ndarray, positions: numpy.ndarray, charge: Optional[float] = None, uhf: Optional[int] = None, lattice: Optional[numpy.ndarray] = None, periodic: Optional[numpy.ndarray] = None)[source]#

Represents a wrapped calculator object in tblite and the associated structure data. The calculator is instantiated for the respective structure and is immutable once created. The cartesian coordinates and the lattice parameters of the structure can be updated, while changing the boundary conditions, atomic types or number of atoms require the complete reconstruction of the calculator instance.

Available methods to parametrization of the calculator are:

GFN2-xTB:

Self-consistent extended tight binding Hamiltonian with anisotropic second order electrostatic contributions, third order on-site contributions and self-consistent D4 dispersion.

Geometry, frequency and non-covalent interactions parametrisation for elements up to Z=86.

Cite as:

GFN1-xTB:

Self-consistent extended tight binding Hamiltonian with isotropic second order electrostatic contributions and third order on-site contributions.

Geometry, frequency and non-covalent interactions parametrisation for elements up to Z=86.

Cite as:

IPEA1-xTB:

Special parametrisation for the GFN1-xTB Hamiltonian to improve the description of vertical ionisation potentials and electron affinities. Uses additional diffuse s-functions on light main group elements. Parametrised up to Z=86.

Cite as:

  • V. Asgeirsson, C. Bauer and S. Grimme, Chem. Sci. (2017), 8, 4879. DOI: 10.1039/c7sc00601b

Example

>>> from tblite.interface import Calculator
>>> import numpy as np
>>> numbers = np.array([1, 1, 6, 5, 1, 15, 8, 17, 13, 15, 5, 1, 9, 15, 1, 15])
>>> positions = np.array([  # Coordinates in Bohr
...     [+2.79274810283778, +3.82998228828316, -2.79287054959216],
...     [-1.43447454186833, +0.43418729987882, +5.53854345129809],
...     [-3.26268343665218, -2.50644032426151, -1.56631149351046],
...     [+2.14548759959147, -0.88798018953965, -2.24592534506187],
...     [-4.30233097423181, -3.93631518670031, -0.48930754109119],
...     [+0.06107643564880, -3.82467931731366, -2.22333344469482],
...     [+0.41168550401858, +0.58105573172764, +5.56854609916143],
...     [+4.41363836635653, +3.92515871809283, +2.57961724984000],
...     [+1.33707758998700, +1.40194471661647, +1.97530004949523],
...     [+3.08342709834868, +1.72520024666801, -4.42666116106828],
...     [-3.02346932078505, +0.04438199934191, -0.27636197425010],
...     [+1.11508390868455, -0.97617412809198, +6.25462847718180],
...     [+0.61938955433011, +2.17903547389232, -6.21279842416963],
...     [-2.67491681346835, +3.00175899761859, +1.05038813614845],
...     [-4.13181080289514, -2.34226739863660, -3.44356159392859],
...     [+2.85007173009739, -2.64884892757600, +0.71010806424206],
... ])
>>> calc = Calculator("GFN2-xTB", numbers, positions)
>>> res = calc.singlepoint()
>>> res.get("energy")  # Results in atomic units
-31.716159156026254
Raises:

ValueError – on invalid input, like incorrect shape / type of the passed arrays

add(interaction, *args) → None[source]#

Add an interaction to the calculator instance. Supported interactions are

name

description

Arguments

electric-field

Uniform electric field

Field vector (3,)

spin-polarization

Spin polarization

Scaling factor
get(attribute: str) → Any[source]#

Set an attribute from the calculator instance. Supported attributes are

name

description

angular-momenta

Angular momenta of shells

orbital-map

Mapping from orbitals to shells

shell-map

Mapping from shells to atoms
Raises:

ValueError – on invalid attributes

set(attribute: str, value) → None[source]#

Set an attribute in the calculator instance. Supported attributes are

name

description

default

accuracy

Numerical thresholds for SCC

1.0

guess

Initial guess for wavefunction

0 (SAD)

max-iter

Maximum number of SCC iterations

250

mixer-damping

Parameter for the SCC mixer

0.4

save-integrals

Keep integral matrices in results

0 (False)

temperature

Electronic temperature for filling

9.500e-4

verbosity

Set verbosity of printout

1

Note

The electronic temperature is given in Hartree, rather than Kelvin. The conversion factor from Kelvin to Hartree is the Boltzmann constant in Hartree/Kelvin (3.166808578545117e-6).

Raises:

ValueError – on invalid input, like incorrect shape / type of the passed arrays

singlepoint(res: Optional[Result] = None, copy: bool = False) → Result[source]#

Perform actual single point calculation in the library backend. The output of the library will be forwarded to the standard output.

The routine returns an object containing the results, which can be used to restart the calculation. Unless specified the restart object will be updated inplace rather than copied.

Raises:

RuntimeError – in case the calculation fails

Result#

class tblite.interface.Result(other=None)[source]#

Container for calculation results, can be passed to a single point calculation as restart data. Allows to retrieve individual results or export all results as dict.

Example

>>> from tblite.interface import Calculator
>>> import numpy as np
>>> calc = Calculator(
...     method="GFN2-xTB",
...     numbers=np.array([14, 1, 1, 1, 1]),
...     positions=np.array([
...         [ 0.000000000000, 0.000000000000, 0.000000000000],
...         [ 1.617683897558, 1.617683897558,-1.617683897558],
...         [-1.617683897558,-1.617683897558,-1.617683897558],
...         [ 1.617683897558,-1.617683897558, 1.617683897558],
...         [-1.617683897558, 1.617683897558, 1.617683897558],
...     ]),
... )
>>> res = calc.singlepoint()
------------------------------------------------------------
  cycle        total energy    energy error   density error
------------------------------------------------------------
      1     -3.710873811182  -3.7424104E+00   1.5535536E-01
      2     -3.763115011046  -5.2241200E-02   4.8803250E-02
      3     -3.763205560205  -9.0549159E-05   2.0456319E-02
      4     -3.763213200846  -7.6406409E-06   2.7461272E-03
      5     -3.763250843634  -3.7642788E-05   2.4071582E-03
      6     -3.763236758520   1.4085114E-05   2.3635321E-04
      7     -3.763237287151  -5.2863152E-07   3.5812281E-04
      8     -3.763233829618   3.4575334E-06   8.5040576E-06
      9     -3.763233750684   7.8934355E-08   1.1095285E-07
------------------------------------------------------------
>>> res.get("energy")
-3.7632337506836944
>>> res = calc.singlepoint(res)
------------------------------------------------------------
  cycle        total energy    energy error   density error
------------------------------------------------------------
      1     -3.763233752583  -3.7947704E+00   1.3823013E-07
      2     -3.763233751557   1.0256169E-09   1.4215249E-08
------------------------------------------------------------
Raises:

  • ValueError – on invalid input, like incorrect shape / type of the passed arrays

  • RuntimeError – if a requested quantity is not available in the container

dict() → dict[source]#

Return all quantities inside the result container as dict. In case no results are present an empty dict is returned.

get(attribute: str)[source]#

Get a quantity stored instade the result container. The following quantities are available

property

dimension

unit

energy

scalar

Hartree

energies

nat

Hartree

gradient

nat, 3

Hartree/Bohr

virial

3, 3

Hartree

charges

n

e

dipole

3

e·Bohr

quadrupole

6

e·Bohr²

orbital-energies

norb

Hartree

orbital-occupations

norb

e

orbital-coefficients

norb

unitless

overlap-matrix

norb, norb

unitless

hamiltonian-matrix

norb, norb

Hartree

density-matrix

norb, norb

e

Notes

The Hamiltonian matrix is the core Hamiltonian rather than the converged full Hamiltonian after selfconsistency. To reconstruct it transform the orbital energies from the MO to the AO basis using the orbital coefficients.

Raises:

  • ValueError – on invalid input, like incorrect shape / type of the passed arrays

  • RuntimeError – if a requested quantity is not available in the container

set(attribute: str, value)[source]#

Get a quantity stored instade the result container. Currently, no quantities can be set in the result container.

Raises:

  • ValueError – on invalid input, like incorrect shape / type of the passed arrays

  • RuntimeError – if a requested quantity cannot be set in the container